U.S. patent application number 09/798691 was filed with the patent office on 2002-07-04 for health care data manipulation and analysis system.
This patent application is currently assigned to HomeOpt LLC. Invention is credited to Benigno, Benedict B., Burrell, Matthew O., Feuer, Gerald A., Sadler, William E., Withers, Leland A..
Application Number | 20020087361 09/798691 |
Document ID | / |
Family ID | 27371427 |
Filed Date | 2002-07-04 |
United States Patent
Application |
20020087361 |
Kind Code |
A1 |
Benigno, Benedict B. ; et
al. |
July 4, 2002 |
Health care data manipulation and analysis system
Abstract
Systems useful for analyzing data related to clinical pathways
and performing actions based upon the analyses. A self-analyzing
system for suggesting default clinical pathways for various
procedures. A self-analyzing system for suggesting deviation from a
current clinical pathway and entry into an alternative clinical
pathway based upon historical information about the results of
actions. Statistical analysis systems based on clinical pathways. A
rating system for care providers or proposed pathways based on
historical information. Systems for gathering clinical pathway
information. Systems for tracking clinical pathway outcomes based
on data collected post-treatment. A system for prequalification for
appropriate discharge and post-discharge handling of and
communication with a new class of patient, those requiring stable
acute care. A questionnaire computer language and subsystem are
used in various stages of the systems of the invention.
Corresponding methods are also disclosed.
Inventors: |
Benigno, Benedict B.;
(Atlanta, GA) ; Feuer, Gerald A.; (Atlanta,
GA) ; Burrell, Matthew O.; (Atlanta, GA) ;
Sadler, William E.; (Stone Mountain, GA) ; Withers,
Leland A.; (Atlanta, GA) |
Correspondence
Address: |
Gregory J. Kirsch, Esq.
NEEDLE & ROSENBERG, P.C.
The Candler Building, Suite 1200,
127 Peachtree Street, N.E.
Atlanta
GA
30303-1811
US
|
Assignee: |
HomeOpt LLC
|
Family ID: |
27371427 |
Appl. No.: |
09/798691 |
Filed: |
March 2, 2001 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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09798691 |
Mar 2, 2001 |
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09139423 |
Aug 25, 1998 |
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6230142 |
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60068825 |
Dec 24, 1997 |
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60091552 |
Jul 2, 1998 |
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Current U.S.
Class: |
705/3 |
Current CPC
Class: |
G16H 50/70 20180101;
Y10S 707/99945 20130101; G16H 80/00 20180101; G16H 40/67 20180101;
G16H 70/20 20180101; G16H 10/60 20180101; Y10S 707/99948 20130101;
G16H 10/20 20180101 |
Class at
Publication: |
705/3 |
International
Class: |
G06F 017/60 |
Claims
What is claimed is:
1. A system for analyzing health care data, comprising: (a) a
database comprising a plurality of records, each record including:
(1) event data corresponding to a health-related event for a
person, (2) type data corresponding to the health-related event
type, (3) chronological data corresponding to a relative point in
time that the health-related event occurred; (b) processing means
for performing the steps of: (1) analyzing the database in order to
identify correlations between the plurality of event data within
the plurality of records, based upon the type data and
chronological data in each record; (2) modifying a selected series
of records within the database in order to maximize the likelihood
of occurrence of a desired health-related event having
chronological data corresponding to a point in time later than the
chronological data associated with the selected series of
records.
2. The system of claim 1, wherein the event data corresponds to a
decision point among the plurality of records.
3. The system of claim 1, wherein the selected series of records
corresponds to a clinical pathway.
4. The system of claim 3, wherein the clinical pathway corresponds
to a medical procedure performed on the person.
5. The system of claim 1, wherein the analyzing step is performed
using a genetic algorithm.
6. The system of claim 1, wherein the analyzing step is performed
using actuarial analysis techniques.
7. A system for analyzing health care data, comprising: (a) an
output device for providing output to a user; (b) a database
comprising a plurality of records, each record including: (1) event
data corresponding to a health-related event for a person, (2) type
data corresponding to the health-related event type, (3)
chronological data corresponding to a relative point in time that
the health-related event occurred; (c) processing means for
performing the steps of: (1) analyzing the database in order to
identify correlations between the plurality of event data within
the plurality of records, based upon the type data and
chronological data in each record; (2) identifying a selected
series of records within the database that may be modified in order
to maximize the likelihood of occurrence of a desired
health-related event having chronological data corresponding to a
point in time later than the chronological data associated with the
selected series of records; and (3) outputting to the user an
identifier associated with the selected series of records.
8. The system of claim 7, wherein the processing means further
performs the steps of: (4) prompting the user whether the selected
series of records should be modified; and (5) modifying the
selected series of records.
9. A process for analyzing health care data, comprising the steps
of: (a) storing a plurality of records, each record including: (1)
event data corresponding to a health-related event for a person,
(2) type data corresponding to the health-related event type, (3)
chronological data corresponding to a relative point in time that
the health-related event occurred; (b) analyzing the plurality of
records to identify correlations between the plurality of event
data within the plurality of records, based upon the type data and
chronological data in each record; (c) modifying a selected series
of records in order to maximize the likelihood of occurrence of a
desired health-related event having chronological data
corresponding to a point in time later than the chronological data
associated with the selected series of records.
10. The process of claim 9, wherein the analyzing step is performed
using actuarial analysis techniques.
11. A system for manipulation and analysis of data related to
clinical pathways, comprising: (a) a clinical pathway database for
storing: (i) an initial procedure decision data element,
corresponding to a decision point within the clinical pathway; and
(ii) at least one subsequent decision data element, corresponding
to an available subsequent decision point within the clinical
pathway; (b) a historical clinical pathway database for storing
previously selected subsequent decision data elements, selected
corresponding to the initial procedure decision data element; and
(c) processing means, including a storage device, for performing
the steps of: (i) selecting one of the at least one subsequent
decision data elements; (ii) comparing the selected subsequent
decision data element with the previously selected subsequent
decision data elements stored in the historical clinical pathway
database; and (iii) based upon predetermined correlation criteria,
modifying the at least one subsequent decision data element within
the clinical pathway database.
12. The system of claim 11, further comprising means for storing
the selected subsequent decision data element in the storage
device.
13. The system of claim 11, wherein the clinical pathway database
subsequent decision data elements further comprise default
subsequent decision data elements and wherein the processing means
modifies the default subsequent decision data elements.
14. The system of claim 11, wherein the clinical pathway database
further comprises a medical procedure data element corresponding to
the initial and subsequent decision data elements for a particular
medical procedure.
15. The system of claim 14, wherein the medical procedure
corresponds to the stable acute care of a patient.
16. The system of claim 11, wherein the processing means further
comprises means for, prior to modifying the at least one subsequent
decision data element within the clinical pathway database,
querying the user for authorization to make the modification.
17. The system of claim 11, wherein at least one of the at least
one subsequent decision data elements corresponds to an appropriate
discharge of a patient and wherein the processing means further
comprises means for comparing the selected subsequent decision data
element with predetermined appropriate discharge criteria and,
based upon the comparison, generating a signal corresponding to the
appropriateness of discharging the patient.
18. The system of claim 14, wherein the historical clinical pathway
database further comprises a medical procedure data element
corresponding to the initial and subsequent decision data elements
for a particular medical procedure and wherein the processing means
further comprises: (iv) means for storing the medical procedure
data element, and the modified at least one subsequent decision
data element within the historical clinical pathway database; (v)
means for correlating the modified at least one subsequent decision
data elements in the historical clinical pathway database with the
medical procedure data element; (vi) means for querying the
historical clinical pathway database and generating a signal
corresponding to the at least subsequent decision data element
corresponding to a particular medical procedure; and (vii) means
for outputting the signal to a signal processing means.
19. The system of claim 11, wherein the clinical pathway database
further comprises a patient identification data element
corresponding to the initial and sub sequent decision data elements
for a particular patient.
20. The system of claim 19, wherein the clinical pathway database
further comprises at least one patient visit data element
corresponding to the patient identification data element.
21. The system of claim 20, wherein the clinical pathway database
further comprises a time stamp data element corresponding to each
of the a least one patient visit data elements, and wherein the
processing means further comprises: (ix) means for comparing the
time stamp data element to predetermined criteria; and (x) means
for generating a signal corresponding to the result of the
comparison and outputting the signal to a signal processing
means.
22. The system of claim 11, further comprising a database for
storing follow-up information and wherein the comparing means of
the processing means is further responsive to the stored follow-up
information in the follow-up information database.
23. A client/server system for manipulation and analysis of data
related to clinical pathways, comprising: (a) a communication
network; (b) a client workstation in communication with the
communication network, wherein the client workstation comprises:
(i) means for generating at least one signal corresponding to a
clinical pathway decision and transmitting the at least one
decision signal over the communication network; and (ii) means for
receiving at least one signal corresponding to a clinical pathway
modification from the communication network; and (iii) means for
outputting the at least one modification signal to a signal
processing means; (c) a server on the communication network,
wherein the server comprises: (i) a clinical pathway database for
storing: (1) an initial procedure decision data element,
corresponding to a decision point within the clinical pathway; and
(2) at least one subsequent decision data element, corresponding to
at least one available subsequent decision point within the
clinical pathway; and (ii) a historical clinical pathway database
for storing previously selected subsequent decision data elements,
selected corresponding to the initial procedure decision data
element; and (d) processing means, in communication with the
communication network, the client workstation, and the server, for
performing the steps of: (1) receiving the at least one decision
signal from the communication network; (2) based on the received
decision signal, selecting one of the at least one subsequent
decision data elements; (3) comparing the selected subsequent
decision data element with the previously selected subsequent
decision data elements stored in the historical clinical pathway
database; (4) based upon predetermined correlation criteria,
modifying the at least one subsequent decision data elements within
the clinical pathway database; (5) generating at least one signal
corresponding to a clinical pathway modification of the subsequent
decision data elements in the clinical pathway database; and (6)
transmitting the at least one clinical pathway modification signal
over the communication network to the receiving means of the client
workstation.
24. A system for manipulation and analysis of data related to
clinical pathways, comprising: (a) a clinical pathway database for
storing: (i) an initial procedure decision data element,
corresponding to a decision point within the clinical pathway; and
(ii) at least one subsequent decision data element corresponding to
at least one available subsequent decision point within the
clinical pathway; (b) a historical clinical pathway database for
storing previously selected subsequent decision data elements,
selected corresponding to the initial procedure decision data
element; and (c) processing means, including a storage device, for
performing the steps of: (i) selecting one of the at least one
subsequent decision data elements; (ii) comparing the selected
subsequent decision data element with the previously selected
subsequent decision data elements stored in the historical clinical
pathway database; and (iii) based upon predetermined correlation
criteria, modifying the at least one subsequent decision data
elements within the clinical pathway database.
25. A system for assessing utilization of medical resources based
upon manipulation and analysis of statistical data related to
clinical pathways, comprising: (a) a clinical pathway database for
storing: (i) an initial procedure decision data element,
corresponding to a decision point within the clinical pathway; and
(ii) at least one subsequent decision data element corresponding to
at least one available subsequent decision points within the
clinical pathway; (b) a historical clinical pathway database for
storing: (i) previously selected subsequent decision data elements,
selected corresponding to the initial procedure decision data
element; and (ii) for each of the previously selected subsequent
decision data elements, a utilization value corresponding to the
decision data element; (c) processing means, including a storage
device, for performing the steps of: (i) selecting one of the at
least one subsequent decision data elements; (ii) comparing the
selected subsequent decision data element with the previously
selected subsequent decision data elements stored in the historical
clinical pathway database; and (iii) based upon predetermined
correlation criteria, modifying the at least one subsequent
decision data elements within the clinical pathway database; and
(d) statistical processing means, in communication with the
clinical pathway database and the historical clinical pathway
database, for performing the steps of: (i) accessing the historical
clinical pathway database; (ii) computing pathway utilization value
based on the accessed utilization values in the database; (iii)
generating at least one signal corresponding to the pathway
utilization value; and (iv) outputting the at least one utilization
value signal to a signal processing means.
26. A system for rating medical care based upon manipulation and
analysis of data related to clinical pathways, comprising: (a) a
clinical pathway database for storing: (i) an initial procedure
decision data element, corresponding to a decision point within the
clinical pathway; and (ii) at least one subsequent decision data
elements, corresponding to available subsequent decision points
within the clinical pathway; (b) a historical clinical pathway
database for storing: (i) previously selected subsequent decision
data elements, selected corresponding to the initial procedure
decision data element; and (ii) for each of the previously selected
subsequent decision data elements, a rating value; (c) processing
means, including a storage device, for performing the steps of: (i)
selecting one of the at least one subsequent decision data
elements; (ii) comparing the selected subsequent decision data
element with the previously selected subsequent decision data
elements stored in the historical clinical pathway database; and
(iii) based upon predetermined correlation criteria, modifying the
at least one subsequent decision data elements within the clinical
pathway database; and (d) statistical processing means, in
communication with the clinical pathway database and the historical
clinical pathway database, for performing the steps of: (i)
accessing the historical clinical pathway database; (ii) computing
a pathway rating value based on the accessed rating values in the
historical database; (iii) generating at least one signal
corresponding to the pathway rating value; and (iv) outputting the
at least one rating signal to a signal processing means.
27. The system of claim 26, wherein the historical database further
stores the identity of the medical care provider determining the
selection subsequent decision element and wherein the computing
means is further responsive to the identity.
28. The system of claim 26, wherein the historical database further
stores a rating for each of the historical clinical pathways in the
database, and wherein the computing means is further responsive to
the historical pathway ratings.
29. A method for manipulation and analysis of data related to
clinical pathways, the method comprising the steps of: (a)
providing a clinical pathway database for storing: (i) an initial
procedure decision data element, corresponding to a decision point
within the clinical pathway; and (ii) at least one subsequent
decision data element, corresponding to an available subsequent
decision point within the clinical pathway; (b) providing a
historical clinical pathway database for storing previously
selected subsequent decision data elements, selected corresponding
to the initial procedure decision data element; (c) selecting one
of the at least one subsequent decision data elements; (d)
comparing the selected subsequent decision data element with the
previously selected subsequent decision data elements stored in the
historical clinical pathway database; and (e) based upon
predetermined correlation criteria, modifying the at least one
subsequent decision data element within the clinical pathway
database.
30. The method of claim 29, further comprising storing the selected
subsequent decision data element in a storage device.
31. The method of claim 29, wherein the clinical pathway database
subsequent decision data elements further comprise default
subsequent decision data elements and wherein the method further
comprises modifying the default subsequent decision data
elements.
32. The method of claim 29, wherein the clinical pathway database
further comprises a medical procedure data element corresponding to
the initial and subsequent decision data elements for a particular
medical procedure.
33. The method of claim 32, wherein the medical procedure
corresponds to the stable acute care of a patient.
34. The method of claim 29, further comprising, prior to modifying
the at least one subsequent decision data element within the
clinical pathway database, querying the user for authorization to
make the modification.
35. The method of claim 29, wherein at least one of the at least
one subsequent decision data elements corresponds to an appropriate
discharge of a patient and wherein the method further comprises
comparing the selected subsequent decision data element with
predetermined appropriate discharge criteria and, based upon the
comparison, generating a signal corresponding to the
appropriateness of discharging the patient.
36. The method of claim 32, wherein the historical clinical pathway
database further comprises a medical procedure data element
corresponding to the initial and subsequent decision data elements
for a particular medical procedure and wherein the method further
comprises: (f) storing the medical procedure data element, and the
modified at least one subsequent decision data element within the
historical clinical pathway database; (g) correlating the modified
at least one subsequent decision data elements in the historical
clinical pathway database with the medical procedure data element;
(h) querying the historical clinical pathway database and
generating a signal corresponding to the at least subsequent
decision data element corresponding to a particular medical
procedure; and (i) outputting the signal to a signal processing
means.
37. The method of claim 29, wherein the clinical pathway database
further comprises a patient identification data element
corresponding to the initial and subsequent decision data elements
for a particular patient.
38. The method of claim 37, wherein the clinical pathway database
further comprises at least one patient visit data element
corresponding to the patient identification data element.
39. The method of claim 38, wherein the clinical pathway database
further comprises a time stamp data element corresponding to each
of the a least one patient visit data elements, and wherein the
method further comprises: (f) comparing the time stamp data element
to predetermined criteria; and (g) generating a signal
corresponding to the result of the comparison and outputting the
signal to a signal processing means.
40. The method of claim 29, further comprising a database for
storing follow-up information, wherein the comparing step is
further responsive to the stored follow-up information in the
follow-up information database.
41. A client/server method for manipulation and analysis of data
related to clinical pathways, the method comprising the steps of:
(a) providing a communication network; (b) providing a client
workstation in communication with the communication network,
wherein the client workstation comprises: (i) means for generating
at least one signal corresponding to a clinical pathway decision
and transmitting the at least one decision signal over the
communication network; and (ii) means for receiving at least one
signal corresponding to a clinical pathway modification from the
communication network; and (iii) means for outputting the at least
one modification signal to a signal processing means; (c) providing
a server on the communication network, wherein the server
comprises: (i) a clinical pathway database for storing: (1) an
initial procedure decision data element, corresponding to a
decision point within the clinical pathway; and (2) at least one
subsequent decision data element, corresponding to at least one
available subsequent decision point within the clinical pathway;
and (ii) a historical clinical pathway database for storing
previously selected subsequent decision data elements, selected
corresponding to the initial procedure decision data element; and
(d) receiving the at least one decision signal from the
communication network; (e) based on the received decision signal,
selecting one of the at least one subsequent decision data
elements; (f) comparing the selected subsequent decision data
element with the previously selected subsequent decision data
elements stored in the historical clinical pathway database; (g)
based upon predetermined correlation criteria, modifying the at
least one subsequent decision data elements within the clinical
pathway database; (h) generating at least one signal corresponding
to a clinical pathway modification of the subsequent decision data
elements in the clinical pathway database; and (i) transmitting the
at least one clinical pathway modification signal over the
communication network to the receiving means of the client
workstation.
42. A method for manipulation and analysis of data related to
clinical pathways, the method comprising the steps of: (a)
providing a clinical pathway database for storing: (i) an initial
procedure decision data element, corresponding to a decision point
within the clinical pathway; and (ii) at least one subsequent
decision data element corresponding to at least one available
subsequent decision point within the clinical pathway; (b)
providing a historical clinical pathway database for storing
previously selected subsequent decision data elements, selected
corresponding to the initial procedure decision data element; and
(c) selecting one of the at least one subsequent decision data
elements; (d) comparing the selected subsequent decision data
element with the previously selected subsequent decision data
elements stored in the historical clinical pathway database; and
(e) based upon predetermined correlation criteria, modifying the at
least one subsequent decision data elements within the clinical
pathway database.
43. A method for assessing utilization of medical resources based
upon manipulation and analysis of statistical data related to
clinical pathways, the method comprising the steps of: (a)
providing a clinical pathway database for storing: (i) an initial
procedure decision data element, corresponding to a decision point
within the clinical pathway; and (ii) at least one subsequent
decision data element corresponding to at least one available
subsequent decision points within the clinical pathway; (b)
providing a historical clinical pathway database for storing: (i)
previously selected subsequent decision data elements, selected
corresponding to the initial procedure decision data element; and
(ii) for each of the previously selected subsequent decision data
elements, a utilization value corresponding to the decision data
element; (c) selecting one of the at least one subsequent decision
data elements; (d) comparing the selected subsequent decision data
element with the previously selected subsequent decision data
elements stored in the historical clinical pathway database; (e)
based upon predetermined correlation criteria, modifying the at
least one subsequent decision data elements within the clinical
pathway database; (f) accessing the historical clinical pathway
database; (g) computing pathway utilization value based on the
accessed utilization values in the database; (h) generating at
least one signal corresponding to the pathway utilization value;
and (i) outputting the at least one utilization value signal to a
signal processing means.
44. A method for rating medical care based upon manipulation and
analysis of data related to clinical pathways, the method
comprising the steps of: (a) providing a clinical pathway database
for storing: (i) an initial procedure decision data element,
corresponding to a decision point within the clinical pathway; and
(ii) at least one subsequent decision data elements, corresponding
to available subsequent decision points within the clinical
pathway; (b) providing a historical clinical pathway database for
storing: (i) previously selected subsequent decision data elements,
selected corresponding to the initial procedure decision data
element; and (ii) for each of the previously selected subsequent
decision data elements, a rating value; (c) selecting one of the at
least one subsequent decision data elements; (d) comparing the
selected subsequent decision data element with the previously
selected subsequent decision data elements stored in the historical
clinical pathway database; (e) based upon predetermined correlation
criteria, modifying the at least one subsequent decision data
elements within the clinical pathway database; (f) accessing the
historical clinical pathway database; (g) computing a pathway
rating value based on the accessed rating values in the historical
database; (h) generating at least one signal corresponding to the
pathway rating value; and (i) outputting the at least one rating
signal to a signal processing means.
45. The method of claim 44, wherein the historical database further
stores the identity of the medical care provider determining the
selection subsequent decision element and wherein the comparing
step is further responsive to the identity.
46. The method of claim 44, wherein the historical database further
stores a rating for each of the historical clinical pathways in the
database, and wherein the comparing step is further responsive to
the historical pathway ratings.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This utility patent application claims the benefit of
priority of U.S. Provisional Patent Application, Serial No.
60/068,825, filed Dec. 24, 1997, and U.S. Provisional Patent
Application, Serial No. 60/091,552, filed Jul. 2, 1998.
BACKGROUND OF THE INVENTION
[0002] I. Field of the Invention
[0003] The present invention provides data manipulation and
analysis systems and methods associated therewith. In particular,
the present invention is directed to systems useful for analyzing
medical data related to clinical pathways and performing actions
based upon the analyses.
[0004] II. Background of the Invention
[0005] Escalation of medical costs has led to attempts in the past
to streamline systems for providing medical care. Attempts to
control such costs have heretofore been thwarted by inexact methods
of gathering statistical information relevant to the medical care
of interest. Certainly, rudimentary systems for tracking patient
information have been developed. Moreover, patient treatment
information has also been tracked and stored for further analysis.
However, to date, there have not been systems for continuously
tracking patient information and patient treatment information,
such as clinical pathways for the patient, incorporating these into
a useful form, and reacting in an automated fashion according to
the recorded information. Therefore, consistent with the goal of
providing cost-effective medical care, there remains a need for
integrated systems capable of tracking and analyzing medical
treatment information.
[0006] As an example, home health care is expected to account for
an ever-increasing amount of medical care to be provided over the
coming years. Therefore, cost reduction systems applicable to the
home care setting are similarly highly desirable and yet are,
heretofore, virtually unknown.
[0007] Similarly, there exists a need for effective data tracking
and manipulation vital to providing "stable acute" care, as that
term is defined and used herein. Historically, patients who had
surgery would have to come to the hospital anywhere from one to
three days early. After surgery, they would then spend significant
time in the hospital and, in years past, these patients would
actually be kept in the hospital and on bed rest for a lengthy
stay. The operative patient's stay can be broken down to three
phases: pre-operative, operative and post-operative. Each of these
phases has changed drastically over the years.
[0008] During the pre-operative time period, patients historically
came to the hospital anywhere from one to three days prior to
surgery. Early arrival at the hospital usually was required for
patients undergoing abdominal procedures because of the necessary
to perform a bowel prep believed to be necessarily done in the
hospital. This has changed because patients now can receive an
equivalent bowel prep in their own home before coming to the
hospital. However, although the bowel prep may be equally effective
in cleaning out the intestine, the home prepared patients often
become dehydrated. Yet pressures from managed care to save money
have forced the medical community to ignore the fact that these
patients are often dehydrated.
[0009] Additionally, even those patients not needing a bowel prep
used to come in one day prior to surgery. A history and physical
would be done the night before surgery and then the pre-op,
including anesthesia visit and various x-rays and blood tests,
would be done prior to the operation. This, too, has changed in
that the history and physical is now done in the doctor's office
and the pre-op, including the anesthesia visit, laboratories and
x-rays, are now done a number of days prior to the operation.
Again, the pressures of managed care have reduced the prior one to
three day in-hospital pre-operative period to the current practice
of admission to the hospital early in the morning of surgery.
[0010] Economic pressures have recently forced movement toward
minimizing any pre-operative stay. For similar reasons, it would be
desirable to minimize postoperative in-hospital stays. One example
of the result of this desire is the so-called "drive through
mastectomy," which permits discharge from the hospital within 24-36
hours after abdominal hysterectomy or laparoscopic procedures.
Unfortunately, in major abdominal procedures, there are great
limitations to sending patients home early. These limitations are
present for any major procedure requiring an abdominal incision
(such as in gynecological oncology, radical hysterectomy, lymph
node sampling or debulking, urology, radical prostatectomy,
nephrectomy through abdominal approach, general surgical procedures
including colectomy, small bowel resection with abdominal approach,
or gastrectomy). Once there has been significant manipulation of
the intestines after an abdominal incision, there are tremendous
limitations to sending the patients home prior to demonstration of
gastrointestinal ("GI") function, an event which can easily take
four to seven days to occur.
[0011] In the operative period, there are many changes that have
occurred in the past few years. For instance, the suture materials
used today cause much fewer adverse reactions and are much more
secure. Staple devices have increased the speed of the operative
procedures as well as providing more security resulting in less
problems post-operatively. For example, colectomies are now done
with staple anastomoses thereby minimizing the likelihood of a leak
of stool through the anastomosis is minimal. This, of course,
effects the post-operative time period because fewer complications
are expected and observed compared to the past. Finally, operative
procedures have been significantly refined and improved, which also
aids in shorter operating room ("OR") time and less post-op
complications.
[0012] The post-operative period has seen many changes and
improvements over the years, including quicker ambulation of the
patient, decreased bed rest, knowledge that faster discharge
probably decreases likelihood of venous thrombosis and hospital
acquired infections, and understanding that many post-operative
situations do not necessitate long hospital stays. For example,
patients who had mastectomies used to stay in the hospital for four
to five days until the drain stopped yielding fluid. Presently,
patients with mastectomies can go home within the first 24 hours of
surgery and are taught how to take care of the drains at home.
However, there are patients who have had mastectomies who have no
care giver at home, yet are expected to take care of the drains,
pain, any questions and any emotional discomfort without any
assistance. Other improvements include decreased use of nasogastric
tube after gastrointestinal procedures including small bowel
resection or large bowel resection, use of patient controlled
analgesia as opposed to injections which allows the patient to
manage his or her pain more easily at home, development of
intravenous computerized monitors which prevent against possible IV
errors, use of sequential hose which are stockings which blow up on
the legs in a sequential manner and significantly decrease the
likelihood of thrombosis, use of H2 blockers (Histamine-2 blockers)
such as PEPCID.RTM., TAGAMET.RTM., and ZANTAC.RTM. in the
post-operative setting to significantly decrease the chance of
gastric bleeding or other upper GI complications, use of home care
for either the chronically ill post-operative patients or the
generally chronically ill patient, and the use of improved IV
antibiotics to decrease post-operative infections.
[0013] Over the past ten to fifteen years, home care has also
become a viable option. However, although home care has been quite
successful in the past with patients, home care has only been known
for handling patients classified as chronically ill or, very
recently, for handling patients who would usually come to the
emergency room. For a chronically ill patient, the patient remains
in the hospital for a long period of time. While it may take 24-48
hours to send the patient home, the stay at home may vary from as
much as two weeks to a few months.
[0014] Hospital length of stay and other clinical pathways are
ultimately the purview of the physician. However, certain
guidelines exist, such as those published under the title Milliman
& Robertson Healthcare Management Guidelines by Milliman &
Robertson, Inc., Actuaries & Consultants. These guidelines are
gathered manually by physicians and nurses based on their
collective judgment of suitable care. The gathering process is
tedious and subjective. The resulting "standards" are developed not
through the collection and analysis of actual data (such as would
be done in preparing, for example, life insurance mortality
tables), but instead are developed by committees of clinicians and
others who are hired by actuarial companies and asked their
subjective opinions. Therefore, these exists a need for an
automated system to determine optimal treatment steps so as to
improve important factors such as length of post-operative stay and
recovery.
[0015] For example, the post-operative hospital stay standard for a
woman after an abdominal hysterectomy is set today by such a
committee. It is referred to as the "optimal" hospital stay for
this procedure. If described as a 5-day post-op hospital stay,
there are events during the stay that are looked for and flagged,
such as a bowel movement. However, there is no data or supporting
analysis that concludes that such a woman must remain in the
hospital for yet another day if she has not had a bowel movement.
It is simply unknown whether a bowel movement truly is a
statistically significant variable or event. Rather, in prior art
systems, the committee of clinicians, or others, simply make a best
guess that this is a significant factor.
[0016] Because of economic pressures, it is highly desirable to
provide an optimized post-operative discharge program.
Additionally, it is highly desirable to provide a system capable of
decreasing infection and decreasing the incidence of, for example,
venous thrombosis by permitting early discharge.
[0017] The post-operative period has changed dramatically over the
years from a very lengthy stay only in the hospital to using
procedures that allow patients to go home sooner, such as
laparoscopically assisted procedures, as well as refining various
procedures so as not to require lengthy stays. Again, many of these
procedures are procedures that do not require an abdominal incision
and yield no problem with postoperative bowel function. In essence,
the post-operative stay has already deviated somewhat from the
hospital setting to the home.
[0018] Using the example of the "drive through mastectomy", the
patient has had a complex procedure which may often take up to
three or more hours and has suffered a large incision. These
patients are nonetheless released from the hospital because the
incision is a high one which does not impair their breathing. In
addition, because the patient does not have an abdominal incision,
there is a low likelihood of any bowel dysfunction. However, a
number of problems can still occur. First, the fairly large
incision may impart a significant amount of pain for the patient,
yet the patient is released with only oral medication while the
patient may, in fact, require patient controlled analgesics (e.g.,
intravenous type medications such as MORPHINE.RTM. or
DEMERAL.RTM.). The patient has also had a very lengthy procedure
and depending on the type of anesthesia used, may have some
residual anesthesia effects, which could include nausea. The
patient may require an IV antiemetic (anti-nausea agents) or
intravenous fluids to aid in diminishing the nausea. Many of these
patients not only have a long incision with a dressing which could
leak or become infected, but they also have one or more drains in
place. The patients are instructed in how to use these drains but
this can be cumbersome or not entirely understood by the
patient.
[0019] Moreover, once released, the physician loses track of the
patient except for phone calls initiated by the patient to the
physician, which may be difficult for many reasons. First, many
physician phone calls during the day do not actually reach the
physician but rather go to his or her staff. During the evening,
the physician may not receive knowledge of the phone call
whatsoever and the patient may be forced to go to the emergency
room. Therefore, it would be highly desirable to have a system
permitting the capability to provide home care and direct
information communication to the physician and his or her staff in
real time, so as to reduce the recovery period and the risk of
complications.
[0020] Other patients who are rapidly discharged are post abdominal
hysterectomy patients. Often these patients have low transverse
incisions which again do not yield significant problems for
breathing. However, bowel dysfunction problems may still exist.
Patients sometimes have difficulty taking down liquids or food for
as many as three or four days. Unfortunately, these patients are
sent home after post-op day one to one and a half and, at that
time, with current systems, do not have any way of receiving IV
fluids in the event they have nausea or difficulty taking in
fluids. Additionally, if they have any significant discomfort, they
are only on oral medications which may not be potent enough.
Therefore, there exists a need for systems and methods for
permitting expeditious and appropriate post-operative discharge,
while maintaining the capability of providing an appropriate level
of care to the patient while the patient continues to recover.
[0021] A third example of early discharge includes patients who
have had gastrointestinal procedures. Patients with colectomies,
after demonstrating the ability to take in fluids without
developing abdominal distention, may be discharged from the
hospital. These patients remain at risk for developing bowel
dysfunction, abdominal distention, and possible major complications
such as leakage from a bowel anastomosis. In present day systems,
they are nevertheless sent home without any significant continued
communication with the doctor or any prearranged skilled nursing
care. A tremendous risk exists the patient could become ill and
severely dehydrated and require a lengthy stay in the hospital upon
re-admission. In some areas of the country, such discharges do not
occur because physicians oppose it. There exists a need for a
system able to permit such discharged patients to remain safely in
the home without the attendant risks described above.
[0022] As stated previously, actuarial companies serving the health
care industry today do not make recommendations to their customers
(e.g., insurance companies, etc.) based upon their analysis of
large collections of data as they would in other industries (e.g.,
life insurance), but instead use subjective, and potentially
inaccurate, committees. One reason why this is true might be that
actuarial companies simply have not created, nor have access to,
the large amounts of data and processes needed to perform such
analysis. While others have collected health care data previously,
no databases exist whereby the data is organized in such a way so
as to enable meaningful analysis of the data, and no processes
exist to analyze such data.
[0023] The above background describes some pre-existing mechanisms
by which patients are released to the home for part of their
post-operative period. Each of these mechanisms suffers from
drawbacks and is, in some way, not satisfactory in comparison to
the use of the present invention as a way to provide appropriate
postoperative care to patients, including stable acute patients.
The foregoing evidences the significant difficulties and
shortcomings of known systems.
SUMMARY OF THE INVENTION
[0024] The invention herein solves the drawbacks discussed above.
The present invention is directed to data storage and manipulation
system whereby clinical pathway data is collected for patients and
stored in appropriate databases. The system is, preferably, a
client/server based system where clients, such as actuarials,
doctors, hospitals, nurses, insurance companies, and other
healthcare providers can access a central repository of relevant
clinical treatment information. A particularly effective aspect of
the invention is that the system includes functionality for
continuously reviewing the clinical pathway and treatment data for
trends and, where appropriate, prompting appropriate parties of the
need to change the default treatment protocols and clinical pathway
or to change the particular treatment orders for a patient. While
certain trends may be searched for explicitly, an important aspect
of the invention is that it continuously reviews the
ever-increasing data repository using automatically generated
propositions in search of correlations between data elements, even
unexpected correlations.
[0025] Moreover, the system provides a mechanism for rating
proposed clinical pathways. For instance, a caregiver may engage
the system to review a proposed pathway against the historical
database and the system will provide a ranking, based on the
historical data, of the usefulness/effectiveness of the proposed
approach in past cases. Moreover, in another aspect of the
invention, the rating system is associated with particular care
givers, such as doctors or nurses, and their historical performance
can be analyzed against the general data set so as to arrive at an
objective rating of the caregiver against either given or system
generated criteria.
[0026] In addition, the system further comprises the functionality
of providing follow-up data tracking and analysis. Previous data
collection systems are hindered in that, unless there is a
complication, data concerning a patient's follow-up status is
rarely tracked, and even when tracked, is not tracked in sufficient
detail to provide meaningful information. The follow-up data
tracking portion of the present invention, however, provides a
mechanism for contacting patients and generating additional,
clinical pathway related data elements, wherein those elements are
incorporated into the analysis for automated analysis of the
effectiveness of particular clinical pathways.
[0027] For gathering the clinical pathway data, the present
invention involves the use of a computerized or electronic system.
In the stable acute care scenario, the computerized system is used
to address the issue of sending patients home at an appropriate
time in the post-operative period. The computer enables appropriate
communication between the home, the nurse/caregiver seeing the
patient, and the physician or the physician's assistant in the
office. This type of care has been heretofore unknown. The system
allows providing services to an entirely new class of care, stable
acute care.
[0028] In one embodiment, the system is used to identify patients
who are candidates for early (or late) post-operative discharge
(and possibly stable acute care). The nurse or caregiver then sees
the patient almost immediately at home and tracks the patient at
home one or more times per day using the system and the information
is used to create and update the clinical pathway database records
for the patient. Real-time communication systems of the invention
allow supervision by the physician, while not requiring the
supervision to occur in a hospital setting. Assessment of the
patient's condition is performed using an questionnaire or form
generated based upon the current patient's customized and
changeable clinical pathway. In the stable acute care (e.g.,
"home") setting or facility, the nurse provider can assess the
patient and send information regarding the patient by using the
questionnaire. The questionnaire itself will create a SOAP
(Subjective, Objective, Analysis, Plan) note. The SOAP note is
known to those of ordinary skill in the art as the means whereby a
physician describes the patient's status and care plan.
[0029] Additionally, the system allows the physician or physician's
staff to gather historical information regarding the medications,
IV fluids, and other therapies provided to a patient and to
determine whether or not they were given as ordered. The system
also provides the capability to change the orders as needed.
[0030] One significant benefit of the invention is that the data
gathered about various clinical pathways and their successfulness
can be catalogued. The data can be repackaged and manipulated as
needed and is believed to be of significant value in and of itself.
The gathering of this data as it pertains to the heretofore
nonexistent stable acute care patient class is an important
advantage of the invention.
[0031] The important features of the system of the invention
include the use of a computerized or electronic interface between
the skilled nurse/caregiver, the patient, and the physician. In
addition, the invention relies upon specialized software subsystems
that allow the use of the interface, allow immediate translation
from questionnaire into on-screen formats which can be read by a
physician or staff, and allow prequalifying of patients during the
pre-operative period for appropriate (i.e., earlier or later than
the average) release and stable acute care.
[0032] In prior systems, patients were only sent home when their
status had reached the chronic care level. In that case, the loss
of a day or two arranging home care was not considered to be a
major problem because the chronic care stay at home would last
anywhere from two weeks to even four weeks. However, using the
present invention, the stay at home is short and once the patient
is designated to go home for stable acute care, it is important to
proceed with their discharge expeditiously. This rapid process
requires the use of systems of the invention which provide for
prequalification of patients into the stable acute care
program.
[0033] Another aspect of the invention is the use of a computerized
system for identifying appropriate patients for receiving stable
acute care. The system identifies patients who would usually stay
in the hospital for a significant period of time because of post-op
ileus (delay in bowel function). In addition, the system provides
pre-operative training at the doctors office as well as informing
the nurse of a patient's imminent discharge so the nurse can meet
the patient soon after the discharge into the patient's home.
[0034] The communications subsystems of the invention are important
to its capability of providing stable acute care and tracking
clinical pathways. Point of service communication at home using
either a suitable electronic or computerized device is provided by
the invention. The computer can be put into communication with a
data storage server computer via any suitable means, including a
modem or network adapter.
[0035] During stable acute care using the systems of the invention,
daily patient visits occur. From two to four visits per day may be
required and are contemplated. Daily communication includes SOAP
notes, notification of whether the patient received appropriate IV
medications and intravenous fluids, as well as the ability to
communicate with nurses, and nurse communications with physicians
for order changes. The initial orders created when the patient is
sent home represent an initial or default clinical pathway
anticipating potential problems and providing appropriate care
orders at that time.
[0036] In addition, using the methods and systems of the present
invention, the postoperative patient's stay at home may be as
little as from two to five days. In order not to lose a day or two
days of potential early discharge, the patient is preferably
identified and classified as an early discharge candidate prior to
hospital admission.
[0037] The present invention provides systems and methods with
numerous advantages. One such advantage provided by the system is
the emotional advantage of sending the patient home in his or her
own environment at the appropriate time, as soon as practicable
under the new system. Such patients will often be more comfortable,
in a psycho-social sense, and many of the difficulties that occur
in the hospital regarding nursing care not being accessible are
removed. A patient having a 24-hour a day caregiver directed
specifically to him or her eliminates most difficulties with regard
to immediate appropriate care, i.e., care that does not involve
skilled nursing care such as turning on IV pumps, changing an IV
bag, or working with IV medicines. In addition, skilled nursing
care visits vary anywhere between two and four times a day (or
whatever frequency and level of care is necessary) and amount to
less burden than what is required from nurses in the hospital
setting.
[0038] Another aspect of the invention involves a new questionnaire
format, which may be used as one way of collecting the data to be
analyzed according to the present invention. This questionnaire
format allows stable acute care caregivers the ability to closely
track and instantly inform a patient's physician of that patient's
condition. The format, as it applies to a particular patient, also
provides the clinical pathway for the patient, as described infra.
With the present invention, stable acute care providers receive
updated orders about the patient on a visit by visit basis and
physicians are able to track the progress of their patients
instantly. The questionnaire system in conjunction with the other
components of the systems of the invention allows the close
communication required between home care givers and physicians in
this kind of situation and solves various problems of the prior
art. Statements of the language used to create each questionnaire
are saved in the clinical pathway database as opposed to a simple
flat file. Entire questionnaires are versioned, and may be easily
modified, or recalled from earlier versions. Questions once entered
may be reused in many questionnaires.
[0039] In one embodiment, the invention provides a system for
manipulation and analysis of data related to clinical pathways,
comprising a clinical pathway database for storing an initial
procedure decision data element, corresponding to a decision point
within the clinical pathway and at least one, preferably a
plurality of, subsequent decision data elements, corresponding to
available subsequent decision points within the clinical pathway, a
historical clinical pathway database for storing previously
selected subsequent decision data elements, selected corresponding
to the initial procedure decision data element, processing means,
including a storage device, for performing the steps of selecting
one of the at least one subsequent decision data elements,
comparing the selected subsequent decision data element with the
previously selected subsequent decision data elements stored in the
historical clinical pathway database, and based upon predetermined
correlation criteria, modifying the subsequent decision data
elements within the clinical pathway database.
[0040] In addition, the present invention provides a client/server
system for manipulation and analysis of data related to clinical
pathways, comprising a communication network, a client workstation
in communication with the communication network, wherein the client
workstation comprises means for generating at least one signal
corresponding to a clinical pathway decision and transmitting the
at least one decision signal over the communication network, and
means for receiving at least one signal corresponding to a clinical
pathway modification from the communication network, and means for
outputting the at least one modification signal to a signal
processing means, a server on the communication network, wherein
the server comprises a clinical pathway database for storing an
initial procedure decision data element, corresponding to a
decision point within the clinical pathway, and at least one
subsequent decision data element corresponding to at least one
available subsequent decision point within the clinical pathway,
and a historical clinical pathway database for storing previously
selected subsequent decision data elements, selected corresponding
to the initial procedure decision data element, and processing
means, in communication with the communication network, the client
workstation, and the server, for performing the steps of receiving
the at least one decision signal from the communication network,
based on the received decision signal, selecting one of the at
least one subsequent decision data elements, comparing the selected
subsequent decision data element with the previously selected
subsequent decision data elements stored in the historical clinical
pathway database, and based upon predetermined correlation
criteria, modifying the at least one subsequent decision data
elements within the clinical pathway database, then generating at
least one signal corresponding to a clinical pathway modification
of the subsequent decision data elements in the clinical pathway
database, and transmitting the at least one clinical pathway
modification signal over the communication network to the receiving
means of the client workstation.
[0041] The present invention also provides a system for
manipulation and analysis of data related to clinical pathways,
comprising a clinical pathway database for storing an initial
procedure decision data element, corresponding to a decision point
within the clinical pathway, and at least one subsequent decision
data element corresponding to at least one available subsequent
decision points within the clinical pathway, a historical clinical
pathway database for storing previously selected subsequent
decision data elements, selected corresponding to the initial
procedure decision data element, and processing means, including a
storage device, for performing the steps of selecting one of the at
least one subsequent decision data elements, comparing the selected
subsequent decision data element with the previously selected
subsequent decision data elements stored in the historical clinical
pathway database, and based upon predetermined correlation
criteria, modifying the at least one subsequent decision data
element within the clinical pathway database.
[0042] In a further embodiment, the present invention provides a
system for assessing utilization of medical resources based upon
manipulation and analysis of statistical data related to clinical
pathways, comprising a clinical pathway database for storing an
initial procedure decision data element, corresponding to a
decision point within the clinical pathway, and at least one
subsequent decision data element corresponding to available
subsequent decision points within the clinical pathway, a
historical clinical pathway database for storing previously
selected subsequent decision data elements, selected corresponding
to the initial procedure decision data element, and, for each of
the previously selected subsequent decision data elements, a
utilization value corresponding to the decision data element
processing means, including a storage device, for performing the
steps of selecting one of the at least one subsequent decision data
elements, comparing the selected subsequent decision data element
with the previously selected subsequent decision data elements
stored in the historical clinical pathway database, and based upon
predetermined correlation criteria, modifying the at least one
subsequent decision data elements within the clinical pathway
database, and statistical processing means, in communication with
the clinical pathway database and the historical clinical pathway
database, for performing the steps of accessing the historical
clinical pathway database, computing pathway utilization value
based on the accessed utilization values in the database,
generating at least one signal corresponding to the pathway
utilization value, and outputting the at least one utilization
value signal to a signal processing means.
[0043] In another embodiment, the invention provides a system for
rating medical care based upon manipulation and analysis of data
related to clinical pathways, comprising a clinical pathway
database for storing an initial procedure decision data element,
corresponding to a decision point within the clinical pathway, and
at least one subsequent decision data element corresponding to
available subsequent decision points within the clinical pathway, a
historical clinical pathway database for storing previously
selected subsequent decision data elements, selected corresponding
to the initial procedure decision data element, and, for each of
the previously selected subsequent decision data elements, a rating
value, processing means, including a storage device, for performing
the steps of selecting one of the subsequent decision data
elements, comparing the selected subsequent decision data element
with the previously selected subsequent decision data elements
stored in the historical clinical pathway database, based upon
predetermined correlation criteria, modifying the subsequent
decision data elements within the clinical pathway database, and
statistical processing means, in communication with the clinical
pathway database and the historical clinical pathway database, for
performing the steps of accessing the historical clinical pathway
database, computing a pathway rating value based on the accessed
rating values in the historical database, generating at least one
signal corresponding to the pathway rating value, and outputting
the at least one rating signal to a signal processing means.
[0044] Additional advantages of the invention will be set forth in
part in the description which follows, and in part will be obvious
from the description, or may be learned by practice of the
invention. The advantages of the invention will be realized and
attained by means of the elements and combinations particularly
pointed out in the appended claims. It is to be understood that
both the foregoing general description and the following detailed
description are exemplary and explanatory only and are not
restrictive of the invention, as claimed.
BRIEF DESCRIPTION OF THE DRAWINGS
[0045] FIGS. 1A and 1B show flowcharts of the questionnaire system
in operation from the care giver's point of view.
[0046] FIGS. 2A, 2B, and 2C show flowcharts of the questionnaire
system in operation from the physician's point of view.
[0047] FIGS. 3A and 3B show flowcharts detailing the steps taken to
add a patient to the system.
[0048] FIG. 4 shows a block diagram of a client/server embodiment
of the system of the invention.
[0049] FIG. 5 shows a flowchart of a genetic algorithm analysis
process, which may be used in one embodiment of the present
invention.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
[0050] The present invention may be understood more readily by
reference to the following detailed description of preferred
embodiments of the invention.
[0051] Before the present methods and apparatuses are disclosed and
described, it is to be understood that the terminology used herein
is for the purpose of describing particular embodiments only and is
not intended to be limiting. It must be noted that, as used in the
specification and the appended claims, the singular forms "a," "an"
and "the" include plural referents unless the context clearly
dictates otherwise.
[0052] Throughout this application, where publications are
referenced, the disclosures of these publications in their
entireties are hereby incorporated by reference into this
application in order to more fully describe the state of the art to
which this invention pertains.
[0053] The present invention provides a wide range of systems and
processes for automating and improving upon the collection of
clinical data, and the actuarial and statistical analysis of that
data. In one embodiment, these systems and techniques can be
applied to the health care industry, but may also have other
applications as well.
[0054] In one embodiment, the present invention provides a
"feedback loop" where automated actuarial analysis of an
ever-growing collection of data provides ever-improving suggestions
to a physician or other decision-making authority. These
suggestions may take the form of recommendations of changes to
continuously improve clinical pathways (as will be defined in
further detail below). These suggestions can occur because the
automated system of the present invention may search for
statistically significant variables and correlations within the
collected body of data, and the present invention may thereafter
make suggestions or actually alter the existing clinical pathways
based upon its analysis of the data.
[0055] As used herein "stable acute care" refers to the level of
care that would, in the past, have required administration of the
care in a hospital setting. Thus, stable acute care refers to care
which would have been acute care in the hospital setting and which,
when not in the hospital setting, is above the level of care of
chronic home care.
[0056] As used herein, the term "clinical pathway" refers to a
decision tree corresponding to the care of a patient. The decision
tree that is the clinical pathway can have one or more nodes and
each of these nodes can have one or more links to additional nodes
in the tree. Each node can correspond to a care decision and can
include additional information about the care actually given. The
traversal of the tree, through each decision node, to the next node
in the tree represents the clinical pathway. The end effect of the
clinical pathway is to document the step-by-step treatment of the
patient.
[0057] I. Data Manipulation and Analysis System:
[0058] The present invention provides a system for (and
corresponding methods for) manipulation and analysis of data
related to clinical pathways. The system includes a clinical
pathway database. In one embodiment of the present invention,
clinical pathway database models a decision tree comprising various
decision nodes. These nodes are stored as either text or tokenized
representations of the Questionnaire Language ("QL") statements
(see infra). The records can have the following structure:
[0059] Protocol ID
[0060] Group ID
[0061] Question ID
[0062] Version
[0063] Ordinality
[0064] Question Text
[0065] The protocol ID is the protocol being defined. Group ID
identifies the grouping of the question with like questions, i.e.,
all related questions belong to the same group, and are displayed
in a single group box on the screen. Question ID is the identifier
of the question itself. Version is the version of the question
being asked. Ordinality is the order of the question within its
group. Finally, the question text is the QL statement itself.
[0066] As each patient is added to the system, a copy of the base
questionnaire for their procedure is produced and offered to the
physician or system operator for change. The base questionnaire is
simply a set of the clinical pathway node structures as described
above. As individual questions are changed, they are versioned,
e.g., by incrementing a version number. Versioning of the question
can also include further information, such as date and time of the
change, identity of the party making the change, original question
text, etc., such that the system can provide a suitable audit trail
to review all changes in any particular questionnaire.
[0067] In accordance with the present invention, the database
stores an initial procedure decision data element (using the
structure set forth above) corresponding to a decision point within
the clinical pathway and at least one, preferably a plurality of,
subsequent decision data elements, corresponding to available
subsequent decision points within the clinical pathway. The system
also includes a historical clinical pathway database for storing
previously selected subsequent decision data elements, selected
corresponding to the initial procedure decision data element. In
addition, the system includes a processing means, optionally
including a storage device, for various steps. While the present
invention has been described in terms of particular data structures
and data flow, the computational steps could be carried out by any
Von Neuman machine, i.e., the processing means can be any
programmable digital computer, whether imbedded into a device or
not or whether part of a network or not.
[0068] Also, in accordance with the present invention, the present
invention provides methods for determining the quality of a
clinical pathway. For instance, in one such method a default
pathway is determined by, e.g., experts in the field or by the
administrator of the present system. This default clinical pathway
is flagged in the database as a default pathway. Using the systems
described elsewhere herein, data is collected on the decisions
taken and care given along the actual clinical pathway. The system
further records any deviations from the default pathway by users of
the system. This data is then used for the feedback systems of the
present invention.
[0069] In one embodiment, the feedback system tests correlations
against sets of criteria and question results. The criteria can be
generated by the system administrator or user or can be generated
after analyzing data in; the system. For example, the system can be
pre-configured to track costs, hospital stays, and long term
complications. In this configuration, for each decision point made
within the clinical pathway and for each patient, the database
records a particular result. In addition, the system also records
the path taken through the decision tree (clinical pathway) and
this path is then correlated against the result variables of
interest to determine if there is any correlation. For example, the
decision as to whether or not to prescreen (by asking a background
question using the QL) for diabetes may alter the final cost and/or
hospital duration for a particular patient. Therefore, depending
upon the magnitude of these influences, a correlation can be
determined to exist or not.
[0070] As noted above, a predefined preliminary set of these
correlation searches may be entered manually and the system is
configured to search this problem space automatically. The
correlation matrix potentially includes all combinations of all
questions in the questionnaire versus all recorded outcomes.
Selecting and matching significant independent variables which
result from this problem space is computationally NP-complete.
However, one of ordinary skill in the art would recognize a number
of suitable correlation algorithms useful for finding plausible
solutions to this NP-complete problem space. As one example, and
not intending to be bound to any particular implementation, the
selection and matching of variables can be carried out using
genetic programming or genetic algorithm ("GA") methods. Such
algorithms can generate hypotheses upon which to test correlations.
As used for the present invention, a GA will search the set of
questionnaire decision points and correlate decisions against the
various output variables. The system is constantly evaluating
itself. As the system finds new correlating factors, they are put
in place to aid in determining changes to be made to the current or
default clinical pathway. In addition, as correlations are
determined between clinical pathway decisions and significant
outcomes (i.e., outcomes of interest), changes can be made to the
default pathway to optimize systematically the clinical pathway
toward the desired results. These changes can be automatically made
or can be presented to the physician, system administrator, or
other user for approval.
[0071] In addition to GAs, there are other suitable methods for
attacking the present NP-complete problem. For instance,
correlations can be viewed as patterns and the patterns then
subjected to pattern matching routines. Such pattern matching is a
known domain of neural networks. However, even if neural networks
are used, it is preferred that the nodes and loadings still be
determined by a GA. GAs can also be used in this manner to actually
create analysis programs by determining an input grid for a finite
state machine. Other methods for finding near optimal solutions for
NP-complete problems could also be used to determine the optimal
correlation matrix, such as simulated annealing. No matter the
approach, one of skill in the art would recognize that the present
correlation problem is combinatorily explosive is likely impossible
to be attacked at all with closed form or brute-force methods.
[0072] The above-described problem is a multivariate analysis where
the independent variables are the answers to questions asked during
the treatment of the patient. Dependent variables are the desired
outcomes. The data space is well defined, with definite sets of
potential independent variables and definite sets of potential
dependent variables. Difficulty exists however because the data set
is so large, and which variables are significant is not known.
[0073] Traditionally this problem has gone unsolved by machine
methods. The typical solution is to have domain experts determine
what they believe are the significant independent variables and
measure correlation to effect on desired dependent variables using
standard multivariate analysis techniques. While this can lead to
advances (indeed, all advances to date are done this way) there is
no way to find the hidden dependencies which exist in the data
sets.
[0074] Again, the selection of the possible sets of independent
variables for each dependent variable is an NP complete problem,
and is considered to be computationally intractable. However, while
there are no definite solutions to NP complete problems, it is
possible to find multiple local maxima and minima, and to
progressively move towards more optimal solutions.
[0075] As described in further detail elsewhere, the specific
application of the techniques comprising the present invention is,
in one embodiment, for a treatment decision tree for a particular
ailment. The decision tree is determined by a clinician. This tree
is recorded in a computer database as a series of questions, which
are asked to patients and their caregivers. Data is collected in
much greater detail about each step of the treatment process than
has ever been done before. Time based information is also
collected. This gives not only the treatment, but also the exact
sequence of events for the treatment.
[0076] The questionnaire and its answers are all stored. As the
store becomes large, they may be analyzed for variance in treatment
leading to more desired results (long term efficacy, reduced cost,
etc.). The method for analysis chosen is a Genetic Algorithm
(GA).
[0077] The mathematics of the Genetic Algorithm are based upon the
study of complex non-linear systems. This field has come to be
known as "Complexity Theory". Complexity theory discusses the
phenomenon of "emergent systems"--systems that are defined by very
simple rules, but which exhibit extremely complex behavior because
of the non-linear nature of the problem. Complexity theory itself
arose out of the study of non-linear dynamical systems in a field,
which has been called "chaos theory". There are several excellent
references to these fields, including: "Chaos and Fractals, New
Frontiers of Science" by Peitgen; "Applied Chaos Theory, A Paradigm
for Complexity" by Cambel; "Complexity, Metaphors, Models, and
Reality" by Cowan, among others.
[0078] Genetic programming has significant advantages over previous
attacks on NP complete problems, yielding order(s) of magnitude
faster convergence to local minima, with the added bonus that the
system does not tend to settle on local minima but to continue to
search the phase space of the problem for different solutions.
Results of typical GA performance can be found in "Genetic
Programming" and "Genetic Programming II" by Koza. known. This
means that the fitness function has to be dynamic, as opposed to
static as in standard GA approaches. The very dynamic nature of the
fitness function suggests a two tiered GA approach to the solution.
Not only are populations tested against specific criteria, they are
tested against different criteria. The optimization not only looks
at input data, but input data along with different fitness
functions. The purpose is to search for existing but unsuspected
correlations.
[0079] In a standard GA, the fitness function is fixed. Therefore,
the system can only optimize towards those fixed criteria. In this
system, not only can the subset of input (independent variables) be
searched, but the subset of criteria (dependent variables) can also
be searched. This leads to a problem of representation: How is a
genotype represented? One approach used in the present invention is
as follows, as also described elsewhere:
[0080] Clinical pathways are stored as a series of questions. Each
question can be thought of as a decision point within a decision
tree, and each question is uniquely identified. Data is collected
from the patient at each point within the decision tree that
represents the care given that patient. Also, medical history is
collected in the same way, as answers to pre-defined questions.
Lastly, result information is collected in the same manner. This
yields a huge phase space for the algorithm to search. The data
must be represented in a manner such that simple manipulation of a
string will yield results.
[0081] The representation chosen is one that consists of a string
that represents the answers to questions. For example, if questions
1, 2 and 3 had possible answers of Y/N, A/B/C, D/E/F the genome
would consist of 3 packets of information, the actual string (for
instance YAD) and constraining information (Y/N, A/B/C, D/E/F). The
string can then be mutated by random selection from available
answers. This prevents mutation from producing meaningless
answers.
[0082] This approach has an analog in genetics, where genes are
constructed of simple proteins. Mutation can only select between
the proteins to produce a new gene. The concepts are identical.
[0083] Note that dependent variables are represented in the same
manner. The point of the search then is to find subsets of the
problem data space that reflect a causal relationship to other
subsets within the data space. Also note that this is a substantial
departure from how traditional GAs are performed--the fitness
function is also represented in this manner. Questions that would
be asked for fitness, i.e. Variable A>value Y, can also be
represented in the same manner. In this case, the question would be
a 3 part string, where the first part is the list of possible
variables, the second is a list of possible logical operators, the
third is another list of possible variables. This allows the
fitness function to be manipulated by the GA as well.
[0084] A summary of the differences between standard GA s and the
present approach is provided below:
[0085] 1) Dependent and independent variables are represented
together in a single data space.
[0086] 2) Fitness functions are represented within the same data
space.
[0087] 3) The object is to locate causal effects within the entire
data space, as opposed to a narrowly defined fitness function.
[0088] 4) There is no terminal condition that signals the end of
the GA. The process continues indefinitely.
[0089] For this specific problem, the following methodology may be
followed, described with respect to FIG. 5. For purposes of the
process described below, the reference numerals in [brackets]
correspond to like-numbered reference numerals shown in the
figure:
[0090] Create initial population - the population will initially be
determined by "best guess" from human clinicians, along with the
sets of independent, dependent, and fitness variables.
[0091] Initial population is evaluated.
[0092] Repeat the following steps:
[0093] Assign reproductive probabilities based upon individuals
fitness
[0094] Form new genotypes with recombination and mutation
[0095] Evaluate the new population.
[0096] If high level of correlation is found report it.
[0097] Go to step 5003
[0098] There are several exceptions to the routine that must be
allowed. For instance, there may be factors that are always
optimized. Cost would be a good example. If lower costs are
desired, then those genes that define the fitness function that
evaluate cost can be marked as being permanent. They will always be
in the fitness function. This would be entered as "delta cost less
than 0".
[0099] The second exception to the fitness rules are weighing.
Fitness statements are simply taken as a point score on the basis
of the number of true statements. For instance, if there are 10
fitness statements, if all 10 are true, then the genotype scores a
10. It is possible to weigh a statement. If there were a fitness
statement that you wanted to defiantly select against, assign it a
weight of negative infinity. An example of this would be increased
mortality. The fitness statement, "delta mortality greater than 0"
would be weighed as negative infinity, then if that case were true
(mortality is higher) it wouldn't matter what the other fitness
function values were, the genotype would be selected against.
[0100] As noted above, the data elements can represent a default
clinical pathway and, thus, the system updates the default pathway
to be presented to users in the future. Alternatively, the pathway
can be the one currently being followed, where some input generates
a correlation that causes a deviation or modification (or
suggestion to take one) to the pathway.
[0101] In a further embodiment, the system includes means for
storing the selected subsequent decision data element in the
storage device. Suitable storage devices include diskettes, random
access memory, or any other device capable of storing digital
information.
[0102] In an enhanced version of the system, the clinical pathways
in the database are each associated with a particular medical
procedure. This can be done by offering a new database, or
extending the clinical pathway database further to include a
medical procedure data element corresponding to the initial and
subsequent decision data elements for a particular medical
procedure. As is evident, the system is readily suited and optimal
for tracking care which can be classified as stable acute care as
that term is used herein.
[0103] In another embodiment, the processing means further
comprises means for, prior to modifying the subsequent decision
data elements within the clinical pathway database, querying the
user for authorization to make the modification. For instance, if
the user is at a computer terminal, a prompt can be given to the
user describing the correlation that was found and requesting
authorization to, e.g., change the default clinical pathway
presented to other users. Assuming the user is trusted or has valid
access, the change can be made globally on behalf of all users of
the system.
[0104] In a further embodiment, at least one of the subsequent
decision data elements corresponds to an appropriate discharge of a
patient. In this system, the processing means also includes means
for comparing the selected subsequent decision data element with
predetermined appropriate discharge criteria and, based upon the
comparison, generating a signal corresponding to the
appropriateness of discharging the patient. Such comparing means
can be implemented, for example, using computer software in
conjunction with the above described system. The signal can
correspond to various states, including permissibility/advisability
of discharge or lack thereof.
[0105] In another embodiment, the historical clinical pathway
database further comprises a medical procedure data element
corresponding to the initial and subsequent decision data elements
for a particular medical procedure and wherein the processing means
further comprises means for storing the medical procedure data
element. In this system, the modified subsequent decision data
elements are also stored within the historical clinical pathway
database. The system includes means for correlating the modified
subsequent decision data elements in the historical clinical
pathway database with the medical procedure data element, means for
querying the historical clinical pathway database and generating a
signal corresponding to the subsequent decision data elements
corresponding to a particular medical procedure, and means for
outputting the signal to a signal processing means. Suitable signal
processing means include, a communication network, a computer, a
storage medium, a display, a printer, or the like.
[0106] In another embodiment, the clinical pathway database further
comprises a patient identification data element corresponding to
the initial and subsequent decision data elements for a particular
patient. In this fashion, the clinical pathways can be associated
with particular patients. The identification element can identify
the patient directly, or can be an anonymous or random identifier
if patient confidence is critical or desired.
[0107] In another embodiment, the clinical pathway database further
comprises at least one patient visit data element corresponding or
related to the patient identification data element. For settings
such as stable acute care or home care, the clinical pathway events
are generally in terms of "visits." Therefore, in this embodiment,
the system allows correlations based upon patient visits and this
data element becomes a part of the overall feedback system. In yet
another embodiment, the clinical pathway database further comprises
a time stamp data element corresponding to each of the at least one
patient visit data elements, and the processing means further
includes means for comparing the time stamp data element to
predetermined criteria, and means for generating a signal
corresponding to the result of the comparison and outputting the
signal to a signal processing means. Thus, the system allows
correlations based upon the visit duration (one example of a
predetermined criteria generally of interest) or chronology.
[0108] In a further embodiment, the system includes a database for
storing follow-up information and wherein the comparing means of
the processing means is further responsive to the stored follow-up
information in the follow-up information database. Where available,
follow-up visit information is incorporated into the databases of
the system and the system can use the follow-up information to
determine correlations. For instance, if the patient's condition
deteriorates months after the procedure, a correlation might be
found in some treatment activity in the original clinical pathway.
In essence, the pathway is continued forward an indefinite amount
of time tracking the patient.
[0109] In addition, in one embodiment, the present invention
provides a client/server system for manipulation and analysis of
data related to clinical pathways. Referring now to FIG. 4, one
possible client/server configuration 400 useful for practicing the
present invention is shown. The system accommodates an arbitrary
number of physician or nurse clients 401. A major portion of the
communication system of the invention is used to handle connections
by physicians and nurses to the system. In one embodiment, data is
converted internally to a more efficient format than the external
standard BL7 protocol. All communications are coordinated by the
server 402 of the system. When a physician or nurse requests
information from a source 404 outside of the system, the
information may be retrieved from an outside information server
403. Of course, both servers 402, 403 could be implemented on a
single machine, if desired. The outside information server 403
contains a translation mechanism for handling translation to and
from internal representations based on HL7. By interfacing with
HL7, the system of the invention is capable of accessing patient
information from existing HL7 external clients 404, as well as
serving such information to HL7 systems requesting it.
[0110] Thus, the client/server system includes a communication
network. In addition, the system includes at least one client
workstation in communication with the communication network, where
the client includes means (such as a modem or network adapter) for
generating at least one signal corresponding to a clinical pathway
decision and transmitting the at least one decision signal over the
communication network. In addition, the client includes means
(which can also be a modem or network adapter) for receiving at
least one signal corresponding to a clinical pathway modification
from the communication network. The client further includes means
for outputting the at least one modification signal to a signal
processing means (such as a monitor, printer, digital storage
device, network connection, or further computing system). The
system also includes a server on the communication network and the
server includes (locally or remotely via appropriate connectivity)
the clinical pathway database for storing an initial procedure
decision data element corresponding to a decision point within the
clinical pathway and at least one subsequent decision data element
corresponding to available subsequent decision points within the
clinical pathway. In addition, also associated with the server is a
historical clinical pathway database (the two databases could, of
course, exist on a single machine and, in fact, could have
overlapping storage) for storing previously selected subsequent
decision data elements, selected corresponding to the initial
procedure decision data element. Finally, the system includes
processing means, in communication with the communication network,
the client workstation, and the server, for performing various
steps. The processing means is responsible for receiving the
decision signal from the communication network and, based on the
received decision signal, selecting one of the subsequent decision
data elements. Then the processing means is responsible for
comparing the selected subsequent decision data element with the
previously selected subsequent decision data elements stored in the
historical clinical pathway database, and, based upon predetermined
correlation criteria, modifying the subsequent decision data
elements within the clinical pathway database. Finally, the
processing means is responsible for generating at least one signal
corresponding to a clinical pathway modification of the subsequent
decision data elements in the clinical pathway database and
transmitting the at least one clinical pathway modification signal
over the communication network to the receiving means of the client
workstation.
[0111] The present invention also provides a system for
manipulation and analysis of data related to clinical pathways,
comprising a clinical pathway database for storing an initial
procedure decision data element corresponding to a decision point
within the clinical pathway, and at least one subsequent decision
data element corresponding to available subsequent decision points
within the clinical pathway, a historical clinical pathway database
for storing previously selected subsequent decision data elements,
selected corresponding to the initial procedure decision data
element, and processing means, including a storage device, for
performing the steps of selecting one of the subsequent decision
data elements, comparing the selected subsequent decision data
element with the previously selected subsequent decision data
elements stored in the historical clinical pathway database, and
based upon predetermined correlation criteria, modifying the
subsequent decision data elements within the clinical pathway
database.
[0112] In a further embodiment, the present invention provides a
system for assessing utilization of medical resources based upon
manipulation and analysis of statistical data related to clinical
pathways, comprising a clinical pathway database for storing an
initial procedure decision data element corresponding to a decision
point within the clinical pathway, and at least one subsequent
decision data element corresponding to available subsequent
decision points within the clinical pathway. The system also
includes a historical clinical pathway database for storing
previously selected subsequent decision data elements selected
corresponding to the initial procedure decision data element, and,
for each of the previously selected subsequent decision data
elements, a utilization value corresponding to the decision data
element. The system also includes processing means, optionally
including a storage device, for selecting one of the subsequent
decision data elements and comparing the selected subsequent
decision data element with the previously selected subsequent
decision data elements stored in the historical clinical pathway
database. Based upon predetermined correlation criteria, the system
then modifies the subsequent decision data elements within the
clinical pathway database. In addition, the system includes a
statistical processing means, in communication with the clinical
pathway database and the historical clinical pathway database, for
accessing the historical clinical pathway database, computing a
pathway utilization value based on the accessed utilization values
in the database, generating at least one signal corresponding to
the pathway utilization value, and outputting the at least one
utilization value signal to a signal processing means.
[0113] In an alternate embodiment, the system for determining
optimal pathways is responsive to criteria determined to assess
efficacy of the pathway. For instance, if the system is configured
to optimize for three variables, e.g., minimization of cost, time
of stay, and post-op complications, then clinical pathways are
simply ranked according to their overall efficacy under the stated
criteria. Any clinical pathway that departs from a clinical pathway
already resident in the database of the system can be annotated as
being untested relative to the criteria. As patient information is
accumulated about the new criteria, it is evaluated along with all
the other criteria already resident in the system. Because the
system coordinates communications between a physician and attending
nurse, in each case the information needed to track a clinical
pathway's progress must necessarily pass through the system at
which time the system can record and then or later analyze the
path. The system is then able to determine all known pathways used
to treat a particular problem and this data set can form one
statistical database into which queries are made to determine
efficacy.
[0114] The selection of criteria on which to base rankings may be
entered along with the weightings of the criteria. For instance,
using the three criteria above, these criteria can be manually
ranked in the following order: least complications, shorter stay,
lower cost. Any pathway which results in a higher incidence of
complications will be ranked below any which have lower rates, even
if they have lower cost because cost is not the primary criteria.
In addition, the system itself can suggest ranking order, rather
than relying on manual entry in all cases.
[0115] In addition, using the present system, as described above,
it is possible to assign weights to the rankings as opposed to
making them simple absolute rankings relative to each other. In
this embodiment, it would be readily be possible for a weighted
combination of least cost in conjunction with shorter stay to
outweigh differences in complications.
[0116] In another embodiment, the invention provides a system for
rating medical care based upon manipulation and analysis of data
related to clinical pathways, including a clinical pathway database
for storing an initial procedure decision data element,
corresponding to a decision point within the clinical pathway, and
at least one subsequent decision data elements corresponding to
available subsequent decision points within the clinical pathway.
The system also includes a historical clinical pathway database for
storing previously selected subsequent decision data elements,
selected corresponding to the initial procedure decision data
element, and, for each of the previously selected subsequent
decision data elements, a rating value. In addition, the system
includes processing means, including optionally a storage device,
for selecting one of the subsequent decision data elements,
comparing the selected subsequent decision data element with the
previously selected subsequent decision data elements stored in the
historical clinical pathway database, and, based upon predetermined
correlation criteria, modifying the subsequent decision data
elements within the clinical pathway database. The system further
includes statistical processing means, in communication with the
clinical pathway database and the historical clinical pathway
database, for accessing the historical clinical pathway database,
computing a pathway rating value based on the accessed rating
values in the historical database, generating at least one signal
corresponding to the pathway rating value, and outputting the at
least one rating signal to a signal processing means.
[0117] With the present invention, the clinical pathway database of
the system can, in one embodiment, be initialized with current
proposed optimal clinical pathways. As a physician makes changes in
the default pathway, a departure index is be created that is a
measure of how far from the original pathway the physician is. In
one embodiment, this index is calculated as a simple geometric
distance from the current pathway. In such an embodiment, clinical
pathways and their associated decision tree nodes are represented
as points in n-space, thus making a distance function easy to
compute. N-tuple representations of a particular clinical pathway
decision tree also provide an exact identifier for that tree. No
evaluation of the efficacy of the pathway can be made unless the
particular departure is one that is already known to the system.
Likewise, if a pathway is too different from existing pathways,
then the system is configured to circumvent evaluations at all,
even distance calculations, because the pathway is, in fact, in a
different arbitrary space. In this case, new data for that clinical
pathway decision tree is determined incrementally as new
statistical data for the decision tree is collected over time.
[0118] For trees that are similar enough to be existing pathways
known to the system, relative efficiency can, in one embodiment, be
accomplished by a simple ranking according to the efficacy criteria
established for the system. For instance, this can be represented
using a chart where column headings represent grading criteria, in
order of importance, and relative efficiency in each category is
reported relative to the optimal profile.
[0119] Similarly, in a further embodiment of the present invention,
caregivers can be rated or ranked using, for instance, the final
results of their contribution to tracking a patient through a
particular clinical pathway. If a caregiver deviates from the
optimal (default) pathway, yet still concludes with sufficiently
successful outcome results, then the caregiver would be accorded a
more positive rating. Again, ratings are based on the criteria as
described above. In this embodiment, a simple ranking of patient
data relative to the criteria is generated.
[0120] In a further embodiment, the historical database further
stores the identity of the medical care provider determining the
selection subsequent decision element and wherein the computing
means is further responsive to the identity. In an alternate
embodiment, the historical database further stores a rating for
each of the historical clinical pathways in the database, and
wherein the computing means is further responsive to the historical
pathway ratings.
[0121] II. Data Inputting System Including Stable Acute Care
System:
[0122] The improved input systems of the invention make possible a
new type of care, stable acute care. The above data gathering and
manipulation systems rely heavily upon access to a database of
clinical pathways. Pursuant to the present invention, systems for
inputting this information in a format suitable for the purposes
described herein are also provided.
[0123] Using the present input systems, post-operative surgical
procedures having any of following properties may be suitable
candidates for stable acute care and prequalification for
appropriate (early or late) post-operative hospital discharge. Such
patients include those who have been discharged very quickly and
are in need of possible IV fluid, IV medication, or nursing care;
patients having surgeries where there has been an abdominal
incision with significant manipulation of the intestines which
would have required a post-operative ileus in the past; and
patients where it is desirable to discharge the patient sooner than
is standard care (e.g., as recited in Milliman & Robertson) in
this country.
[0124] Stable acute care is appropriate for a variety of
procedures. Stable acute care is made possible using the
prequalification and communication systems of the present
invention. For instance, using gynecological oncology as an
example, radical hysterectomies, procedures with lymph node
dissections, debulking procedures, procedures with gastrointestinal
anastomoses, and even vaginal procedures may be suitable for stable
acute care.
[0125] Regardless of the particular procedure being performed, in
each case the initial history and physical are evaluated and
entered into the system. Any conditions which would restrict a
patient from receiving stable acute care are specifically
determined for the patient. For instance, such conditions can
include, but are not limited to, whether the patient has a 24 hour
care giver, whether the patient's environment is inappropriate (for
example, the patient has no electricity or no refrigerator), or
whether the patient has particular medical problems or physical
problems (absolute restrictive criteria would include patient with
recent heart attack or a recent CVA). Once a patient is
prequalified by the system as an appropriate candidate based on the
procedure and the above noted restrictive criteria, the patient is
then informed about the program. Assuming consent, the patient may
then be seen by a nurse preferably capable of performing stable
acute care who will educate them and give them other appropriate
information.
[0126] After obtaining prequalification information and determining
that the patient is suitable for receiving stable acute care, the
system develops an appropriate set of orders for the specific
surgery or procedure the patient is undergoing. The initial orders
correspond to a default clinical pathway and, depending on the
procedure, there may be as few as only five or six different
default orders per procedure such that the difference between
post-operative and/or stable acute care for a radical hysterectomy
and a mastectomy may be very minimal.
[0127] For use in the system, a questionnaire (again representing
the default clinical pathway) is also developed specifically for
each procedure. The questionnaire is later processed by the
computer software to develop a SOAP note for the patient. When the
patient is visited by the nurse, the SOAP note is generated by the
computer for that visit and/or procedure. In a similar fashion,
events such as IV hydration and IV meds and the use of H2 blockers
such as TAGAMET.RTM. are also addressed for each procedure. Often,
the decision elements or points which yield daily progress notes
are similar from one procedure to another. Additionally, an order
sheet may be created and may be modified by the physician or the
nurse on a daily basis and the orders on the order sheet are
determined from the initial order sheet that was created. In this
fashion, the initial order sheet is essentially a clinical pathway
printout, or at least a decision data element and subsequent data
element printout.
[0128] In essence, the system creates a universal protocol template
and, often, only minor changes are needed for each procedure for a
specific plan. The data elements tracked in the model include, but
are not required to include and are not limited to, appropriate
procedures, restrictive criteria for patients, insurance
information, pre-operative education, the clinical pathway, daily
order sheets for subsequent orders, the questionnaire developed to
determine specific notes, and daily progress sheets created to
track the fluids, IV's, or medications given.
[0129] The patient information is collected in the doctors office
during the first visit. Once the patient is known to be, for
instance, an insurance candidate, the patient then receives
appropriate information on a pre-operative visit. The patient is
educated and given any appropriate information at that time. In the
post-operative period in the hospital, once the patient appears to
be in satisfactory condition to be released, the nursing care team
is contacted and an arrangement is made for visits at the patient's
house or other stable acute care facility.
[0130] Criteria for discharge may be simple or complex. For
instance, the patient for some procedures need only demonstrate
adequate pain control and no significant medical or physical
problems. As long as the patient is not demonstrating any nausea,
vomiting or GI dysfunction, remains afebrile, and does not
demonstrate any medical complications, the patient can be released
to at least a stable acute care facility. Prior to the patient
being released, the default clinical pathway is generated for the
patient by the system and is used to instruct the nurse care giver
as to how many times a day to see the patient and what kind care to
administer to the patient. The nurse practitioner also supplies the
appropriate information to the physician and communicates to the
physician when a patient is ready to be released from the
program.
[0131] Questionnaire Language grammar
[0132] The present invention includes data structures used to track
clinical pathways. Because the pathways form a decision tree, the
decisions at nodes can be analogized to questions. To assist in
automating the present system, a special questionnaire language was
developed for the system. The grammar and syntax of that system are
described in the following paragraphs.
[0133] Items are entered into the database in the following
form:
[0134] (text,{}) [(text,,{ } ) . . . ]
[0135] Notation:
[0136] Italics are literal strings.
[0137] Items enclosed in square brackets are optional.
[0138] Items enclosed in parenthesis are a selection (choose one of
the list).
[0139] Ellipses indicate that you can repeat the previous grouped
item.
[0140] Items enclosed in curly braces are format strings for field
entry.
[0141] Valid Operator List
[0142] Following is the List of Valid Operators:
[0143] Numeric
[0144] {INT, s [, [n], [m]][:d]}
[0145] {FLOAT, x.y [, [n], [m]][:d]}
[0146] Text
[0147] {CHAR, (s. "(x, 9 char)") [:d]}
[0148] {RADIO, (h, v) 9, "text") . . . [:d]}
[0149] {CHECK, (h, v) (, "test") . . . [:d]}
[0150] Date/Time
[0151] {TODAY}
[0152] {NOW}
[0153] {DATE, n[:d]}
[0154] {TIME, n[:d]}
[0155] Boolean
[0156] {BOOL,)n, { } )n, { } ) [:d{ }
[0157] {ERROR}
[0158] Valid Operator Description
[0159] Numeric
[0160] {INT, s [, [n], [m]][:d]}
[0161] Arguments:
[0162] s--size of input field
[0163] n--lower limit, n=>m
[0164] m--upper limit, m>=n
[0165] d--default value
[0166] Returns:
[0167] input integer value
[0168] Question Example:
[0169] "Enter Pulse:" {INT,4,0,} {IF{ERROR}, "Must be greater than
0" {REDO}, {NOOP} };
[0170] {FLOAT, X.Y [, [n], [m] ] [:d] }
[0171] Arguments:
[0172] x.y--format x--# of digits left of decimal, y--# of digits
right of decimal
[0173] n--lower limit, n<=m
[0174] m--upper limit, m>=n
[0175] d--default value
[0176] Returns:
[0177] input floating point value
[0178] Question Example:
[0179] "Enter CBC count:" {FLOAT,1.2,0.0,5.0} {IF {ERROR), "Must be
between 0 and 5" {REDO}, {NOOP} };
[0180] Text
[0181] {CHAR, (s, "(x, 9, char)") [:d] }
[0182] Arguments:
[0183] s--size of input field
[0184] mask, x matches any character, 9 matches numbers, any other
character is a literal.
[0185] d--default value
[0186] Returns:
[0187] string value of the input
[0188] Question Example:
[0189] "Enter SSN :"{CHAR,"999-99-9999"};
[0190] "Enter Name;"{CHAR,40};
[0191] {RADIO, (h, v) (, "text") . . . [:d] }
[0192] Arguments:
[0193] h,v--horizontal or vertical presentation
[0194] "text"--items to be selected
[0195] d--default item number
[0196] Returns:
[0197] integer--corresponds to selected item, beginning with 0
[0198] Question Example:
[0199] "Select One :"{RADIO, h, "item 1", "item 2", "item
3":2};
[0200] This would display as:
[0201] Select One : item 1 ( ), item 2 ( ), item 3 (x)
[0202] This would return a 2, if item 1 were selected, item 3 would
automatically de-select and the operation would return 0.
[0203] {CHECK, (h, v) (, "test") . . . [:d]}
[0204] Arguments:
[0205] h,v--horizontal or vertical presentation
[0206] "text"--items to be selected
[0207] d--default item number
[0208] Returns:
[0209] array of integers--corresponds to all selected items
[0210] Question Example:
[0211] Which of the following do you have "{CHECK, v, "diabetes",
"hypertension", "hangnail"};
[0212] This Would Display as:
[0213] Which of the following do you have: [ ] Diabetes
[0214] [ ] Hypertension
[0215] [ ] Hangnail
[0216] Date/Time
[0217] {TODAY}
[0218] Returns:
[0219] integer--Julian number of today's date
[0220] {NOW}
[0221] Returns:
[0222] integer--integer time since midnight
[0223] {DATE, n[:d] }
[0224] Arguments:
[0225] n--number of format
[0226] 1--mm/dd/yy
[0227] 2--dd-mmm-yy
[0228] d--default
[0229] Returns:
[0230] integer--Julian number of the date
[0231] Question Example:
[0232] "Procedure Schedule time: "{TIME,2};
[0233] Boolean
[0234] {BOOL, n["d] }
[0235] Arguments:
[0236] n--format
[0237] 1--yes/no
[0238] 2--true/false
[0239] d--default value, ) or 1
[0240] Returns:
[0241] 0 for false/negative
[0242] 1 for true/positive
[0243] Question Example:
[0244] "All vital signs normal? "{IF({BOOL, 1:1} ), {DEFAULT,
{GROUP} }, {NOOP} }
[0245] {ERROR}
[0246] Returns:
[0247] 0 for no errors
[0248] 1 for errors exist
[0249] Question Example:
[0250] see INT example
[0251] Control
[0252] {IF(exp), [{1} ], [{2}] }
[0253] Arguments:
[0254] (exp)--boolean expression, accepts <> <= >= =
==
[0255] Returns:
[0256] {NOOP}
[0257] Question Example:
[0258] If exp is true, 1 is performed. If exp is false, 2 is
performed. {DEFAULT, (screen id, tab id, group id, question id,
field id) [,(screen id, tab id, group id, question id, field id] .
. . }
[0259] Arguments
[0260] 5 tuple that specifies questions to trip default value
on.
[0261] Returns:
[0262] {NOOP}
[0263] {ANSWER}
[0264] Returns:
[0265] Text of entire question after answer accepted
[0266] {NOOP}
[0267] Null Operation.
[0268] {ERRMSG, TEXT}
[0269] Arguments:
[0270] test--Text to display in error status box.
[0271] Question Example:
[0272] See INT example
[0273] {SCREEN}
[0274] Returns:
[0275] Current screen id
[0276] {TAB}
[0277] Returns:
[0278] Current tab id
[0279] {GROUP]}
[0280] Returns:
[0281] Current group id
[0282] {QUESTION}
[0283] Returns:
[0284] Current question id
[0285] {FIELD}
[0286] Returns:
[0287] Current field id
[0288] With reference to FIGS. 1A-1B, a sample daily routine for a
caregiver using the system of the present invention is depicted.
For purposes of FIG. 1A, it will be assumed that the caregiver is a
nurse or other medical professional who provides the care to a
patient in the home, or other location remote from a primary care
center (e.g., hospital, doctor's office, etc.). Of course, other
suitable applications of the present invention may also be made,
and the patient need not necessarily be in the home, but may also
be in other locations (even in the hospital). Also, for purposes of
the present discussion, it will be assumed that a client computer
401 (see FIG. 4) may be used by either a nurse or by a physician.
The mode of operation may be dictated by who logs into the
particular computer 401. Of course, in another embodiment, two
separate types of client computers 401 could also be created, one
for a physician and one for a nurse, etc.
[0289] In step 101, a nurse logs into a client computer 401. In
step 102, the nurse, using the client computer 401 (FIG. 4)
communicates with the server 402, in order to obtain updated
pathway instructions, etc., regarding what steps to perform during
visit(s) for one or more patient(s). The communication can take
place via modem and standard phone lines, via wireless transmission
(e.g., cellular, etc.), via the Internet, or via any other
communication link.
[0290] In steps 103-104, the nurse prepares for the visit to the
patient (or a first patient, if more than one) by obtaining the
necessary supplies, etc., and travels to the patient's location. In
step 105, the nurse, through client computer 401, may again
communicate with server 402, in order to obtain the most current
instructions and data.
[0291] In step 106 and 108, the client computer 401, via the
questionnaire language previously described, or through any other
data collection mechanism, may obtain data from the nurse or other
source corresponding to the clinical pathway to be followed, as
dictated by the physician. As a result, SOAP notes may be
generated, alerts can be generated, etc., for ultimate
retransmission to the server 402.
[0292] Alternatively, or in addition, in step 107 the nurse may
carry out orders created by the physician and transmitted in steps
102 and/or 105 from the server 402 to the client computer 401. The
results of such orders may generate a flow of care to be followed
by the nurse, and/or may generate alerts, etc. In step 109, the
nurse records in the client computer 401 compliance or
non-compliance with the orders. If noncompliance, the reasons are
also stored. gain, all such stored data may later be transmitted
back to the server 402.
[0293] In step 110, the client computer 401 communicates with the
server 402, in order to update both the computer 401 and server 402
as in steps 102 and 105. In step 111, if there are additional
patients assigned to the nurse, as would be indicated on a list
maintained on the computer 401 (as communicated from the server
402), then steps 104-110 may be repeated for each of the remaining
patients. After all patients have been processed by the nurse, the
final step 112 is reached.
[0294] Steps 102, 105 and 110, wherein the client computer 401
communicates with the server 402, are each described in further
detail in steps 121-129, depicted in FIG. 11B. In step 121, the
processes commences. In step 122, the modem on the client computer
401 dials into the server 402. Again, this assumes that the
computer 401 and server 402 are to be connected via modem and
standard telephone lines. Again, it will be understood that this
connection may be accomplished in a variety of ways, including over
telephone lines, via a wireless connection (cellular or otherwise),
via the Internet, etc. For purposes of the present discussion, a
modem and telephone line connection will be assumed.
[0295] In step 124, if the modem connection was not successful,
then in step 123 the user may be allowed to try the connection
again, returning to step 122. If another attempt is not to be made,
then step 128 is encountered, as described further below.
[0296] Assuming the connection between the client computer 401 and
server 402 is successful in step 124, then in step 125 the patient
list, patient orders and patient questionnaire is updated.
Specifically, the client computer 401 sends information to the
server 402 regarding the actions that the nurse has taken (as input
into the client computer 401 by the nurse), and the server 402
sends to the client computer 401 the updated patient list, patient
orders, patient questionnaires, flow of care, etc. Other data as
appropriate may also be transmitted back and forth between the
client computer 401 and the server 402.
[0297] In step 127, if the data has been correctly exchanged
between the client computer 401 and server 402, then final step 129
is encountered. Otherwise, step 126 is encountered, where a
decision is made whether to retry the transmission. If a retry is
to be attempted, then step 125 is performed again. Otherwise, step
128 is encountered. In step 128, an alert is set at the client
computer 401, indicating that the transmission between the client
computer 401 and server was unsuccessful, allowing the nurse to
manually provide the data to the physician, or other personnel at
the central location (e.g., via voice telephone, etc.).
[0298] Just as FIGS. 1A and 1B depict a remote caregiver's routine,
FIGS. 2A-2C depict a sample routine performed by a physician. With
reference to FIG. 2A, in step 201, the physician logs into a client
computer 401. In step 202, the physician may examine all patients
for whom an alert has been generated (such as in certain of the
steps of FIGS. 1A and 1B, described previously). The physician may
thereafter selectively examine previously scheduled patients (step
203) and/or add new patients to be examined (step 204). At some
point thereafter, the physician may log off of the client computer
401 in step 205.
[0299] FIG. 2B depicts the patient examination step 203 of FIG. 2A
in further detail. In step 206, the examination process begins.
Using the client computer 401, the physician may selectively review
SOAP notes generated for the patient (step 207) and/or review the
flow of care (FOC) generated for the patient (step 208). In step
209, the physician may review orders and questionnairse based on
the SOAP notes and flow of care. Finally, in step 210, the
physician is done with the present patient.
[0300] Step 209 of FIG. 2B is described in further detail with
respect to FIG. 2C. In step 211, the review of order or
questionnaire process begins. In step 212, the physician determines
whether changes are required in the patient's flow of care, or in
the questionnaire(s) to be used by the nurse. If changes are
required, then the physician may modify the orders or the
questionnaire as necessary in step 213. In step 214, such
modifications are transmitted to the nurse's computer 401 using the
process previously described with respect to FIG. 1B. In step 215,
if the transmission is successful, then step 216 is finally
encountered. If not, then in step 217 a decision is made whether to
retry the transmission. If so, step 214 is encountered again.
Otherwise, an alert is set in step 218, and step 216 is finally
encountered.
[0301] FIGS. 3A and 3B depict in further detail the new patient
addition step 204 of FIG. 2A. In step 301, the process begins, and
the patient is diagnosed with a particular ailment by a physician,
etc. In step 302, a decision is made whether the patient is a
candidate for a particular type of surgery, for example. If not,
then step 303 is encountered, indicating that the process of FIG.
3A and 3B is not necessarily applicable.
[0302] In step 304, a new patient record is created, using for
example the client computer 401 and the server 402. This record may
be stored on the server 402, or at any other external location. In
step 305, a criteria questionnaire is administered on the client
computer 401, in order to determine whether the patient satisfies
the criteria to be eligible for, for example, home health care.
Examples of such criteria and conditions have been previously
described elsewhere.
[0303] In step 306, a decision is made whether the patient has any
restrictive criteria, which would prevent the patient from being
eligible for home health care. If so, then step 307 is encountered,
and the process stops. Otherwise, in step 306 an initial visit is
arranged. In step 309, an initial visit questionnaire is
administered, and in step 310 a determination is made whether the
initial visit is OK. Of not, then step 311 is encountered.
[0304] Otherwise, in step 312, a preop questionnaire is
administered, and step 313 is encountered. In step 314, a
determination is made whether the preop questionnaire is OK. If
not, step 315 is encountered. Otherwise, in step 316 the patient is
admitted to the hospital, and in step 317 the procedure is
performed. In steps 318-319, a discharge questionnaire and orders
are reviewed until OK, and in steps 320-321 the discharge
questionnaire is administered until acceptable answers are
obtained. In step 322, the home care provider is notified regarding
the new patient, and in step 323 the patient becomes part of the
daily routine of the physician and home care provider, previously
described.
[0305] The present invention provides for a very flexible data
structure to be used for collecting data, as well as a relatively
detailed amount of information to be collected about patients and
their progress through a clinical pathway. This data format is
required for purposes of optimizing the pathways and procedures, as
previously described. Because of the flexible data structure
allowed by the present invention, the present invention has the
ability to produce custom reports. These reports can easily be
tailored to present information in any format desired. Examples of
this might be productions of the standard "Home Health
Certification and Plan of Care" form HCFA-485 and the HCFA-487
form, which is an addendum to the plan of treatment or a medical
update.
[0306] Both of these forms can be constructed from a subset of the
data required by the present invention. Home health agencies,
Medicare and many private insurance plans use the HCFA-485 form for
reimbursement of services. Changes to orders and the patient's
condition are reported on the HCFA-487 form. Both of these forms
are used to track a patient's progress through some treatment plan.
Within the present invention, this treatment plan corresponds to a
clinical pathway. Progress may be noted in the present invention by
recording visits to the patient, and the patient's actual
condition. Changes made to orders are recorded as changes to the
pathway. As a result of recording the information needed by the
system of the present invention, it would be easy to produce
reports, in whatever format needed, to demonstrate compliance with
various regulatory or insurance requirements.
[0307] It will be apparent to those skilled in the art that various
modifications and variations can be made in the present invention
without departing from the scope or spirit of the invention. Other
embodiments of the invention will be apparent to those skilled in
the art from consideration of the specification and practice of the
invention disclosed herein. It is intended that the specification
and examples be considered as exemplary only, with the true scope
and spirit of the invention being indicated by the following
claims.
* * * * *