SYSTEM, METHOD AND COMPUTER PROGRAM PRODUCT FOR PROVIDING HEALTH CARE SERVICES PERFORMANCE ANALYTICS

• US 20090099862A1
• Filed: 10/16/2007
• Published: 04/16/2009
• Est. Priority Date: 10/16/2007
• Status: Abandoned Application

• Current Assignee: Heuristic Analytics LLC
• Original Assignee: Heuristic Analytics LLC
• Inventors: Fireman, Andrew F., Glickman, Michael L., Gadhi, Sridhar, Kanumuri, Peddi R.
• Application Number:
  US11/873,247
• Publication Number:
  US 20090099862A1
• Time in Patent Office: Days
• US Class Current: 705/2
• CPC Class Codes: G06Q 10/06375 Prediction of business process outcome or impact based on a proposed change
• CPC Class Codes: G06Q 10/0639 Performance analysis of employees; Performance analysis of enterprise or organisation operations
• CPC Class Codes: G16H 20/00 ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
• CPC Class Codes: G16H 30/20 for handling medical images, e.g. DICOM, HL7 or PACS
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

A system, method and computer program product for improving the delivery of healthcare services may include, e.g., but not limited to, in an exemplary embodiment, a) capturing data associated with at least one health care services event, wherein said data comprises at least one aspect of said at least one health care services event; b) categorizing, into at least one category, said at least one aspect of said at least one health care services event; c) analyzing said data associated with said categorized health care services event comprising: i) determining a correlation between said at least one aspect of said data to said at least one category, and ii) determining any cause and effect relationship between said at least one aspect and said at least one category; and d) recommending at least one course of action based on said at least one aspect having said correlation and said cause and effect relationship to said at least one category, is disclosed.

Claims

1. A method for improving the delivery of healthcare services comprising:

a) capturing data associated with at least one health care services event, wherein said data comprises at least one aspect of said at least one health care services event;

b) categorizing, into at least one category, said at least one aspect of said at least one health care services event;

c) analyzing said data associated with said categorized health care services event comprising;

i) determining a correlation between said at least one aspect of said data to said at least one category, and

ii) determining any cause and effect relationship between said at least one aspect and said at least one category; and

d) recommending at least one course of action based on said at least one aspect having said correlation and said cause and effect relationship to said at least one category.

2. The method according to claim 1, wherein said (a) comprises at least one of:

i) capturing data associated with at least one health care services event, wherein said at least one health care services event comprises at least one of;

at least one event;

a plurality of events;

at least one pre-operative event;

at least one post-operative event;

at least one operative event;

at least one pre-procedure event;

at least one post-procedure event;

at least one procedure;

at least one emergency room procedure;

at least one triage event;

at least one nursing station event;

at least one patient/nurse interaction event; and

/or

at least one healthcare provider/patient interaction event;

ii) capturing said at least one aspect of said data, wherein said at least one aspect comprises;

at least one temporal duration;

at least one quantity of time;

at least one quantity of health care resources used;

at least one type of health care resource used;

at least one health care provider preference;

at least one health care facility preference;

at least one preference;

at least one norm;

at least one procedure;

at least one of a minimum, a mean, and/or a maximum quantity of at least one resource;

at least one location;

at least one proximity between a plurality of resources;

at least one change of location by a resource;

at least one rate of change of said location;

at least one movement from a first location to a second location of a resource;

at least one regulatory requirement;

at least one order; and

/or

at least one protocol;

iii) capturing said data, wherein said data relates to at least one of a plurality of entities comprising at least one of;

a health care resource,

a patient,

a health care provider,

a staff member;

a location;

a data processing system;

a healthcare system;

a person;

a system;

a supply; and

/or

at least one piece of equipment;

iv) capturing said data, wherein said capturing comprises at least one of;

tracking said data;

collecting said data;

aggregating said data;

storing said data;

transmitting said data;

capturing said data over time;

capturing said data by location; and

/or

capturing said data by location and time; and

/or

v) capturing said data wherein said data comprises at least one of;

at least one medical record;

at least one physical record;

at least one electronic record;

a patient medical record;

at least one electronic medical record;

at least one personal health record (PHR);

at least one location data;

at least one temporal data;

at least one radio frequency identification (RFID) device;

at least one health level seven (HL-7) protocol message;

at least one data from any hospital system;

at least one standards-based healthcare data;

at least one American Society for Testing and Materials (ASTM) based data;

at least one Digital Imaging and Communications in Medicine (DICOM) based data;

at least one entity preference;

at least one healthcare facility protocol;

at least one protocol;

at least one order;

at least one procedure;

at least one bar code;

at least one regulatory data;

at least one other input from an existing hospital information system;

at least one aspect of data;

at least one demographic of an entity;

at least one experience data;

at least one expertise data; and

/or

data from another system.

3. The method according to claim 1, wherein said (b) comprises at least one of:

i) comparing said at least one aspect of said health care services event to at least one preference, and

assigning said at least one aspect of said at least one health care services event to said at least one category based on said comparing;

ii) comparing a first at least one aspect of said health care services event to a second at least one aspect of a second said health care services event, and

assigning said first at least one aspect of said health care services event to said at least one category based on said comparing;

iii) comparing at least one aspect of a first said health care services event to at least one aspect of a second said health care services event, and

assigning said at least one aspect of said first health care services event to said at least one category based on said comparing; and

/or

iv) categorizing along at least one of;

a continuum of said at least one categories, wherein said continuum comprises at least one of;

a multi-variate category;

a range of categories;

a continuum from optimal to unacceptable; and

/or

a discrete set of said categories comprises at least one of;

a binary category; and

/or

at least three discrete categories.

4. The method according to claim 3, wherein said comparing comprises at least one of:

(i) comparing to said at least one preference, wherein said preference comprises at least one of;

comparing whether a duration of said health care services event was completed in an allotted time preference;

comparing health care resources used during said health care services event to an allotted amount of resources preference;

comparing an occurrence of said health care services event to a defined point in time preference;

comparing a proximity aspect to a defined proximity preference; and

/or

comparing a location of said health care services event to a defined location preference; and

/or

(ii) comparing to said at least one preference, wherein said preference is established by at least one of;

a health care facility;

a physician preference;

a nurse preference;

a health care provider preference;

an iterative preference; and

/or

a recommended preference.

5. The method according to claim 1, wherein said (c) comprises at least one of:

i) performing at least one of;

stochastic analysis;

Bayesian analysis;

deterministic analysis; and

/or

non-deterministic analysis;

ii) iteratively improving said at least one aspect;

iii) learning an improved health care preference;

iv) performing heuristic analysis on said data;

v) iteratively improving a preference related to said at least one healthcare services event; and

/or

vi) optimizing utilization of health care service resources associated with said at least one health care services event.

6. The method according to claim 1, wherein said (d) comprises at least one of:

i) recommending at least one change to said capturing comprising at least one of;

adding a new at least one datapoint to capture, and/or

deleting an instance of said at least one datapoint;

ii) recommending at least one change to said capturing comprising at least one of;

adding a new at least one aspect,

deleting an existing of said at least one aspect, and/or

modifying said at least one aspect;

iii) recommending at least one change to said categories comprising at least one of;

adding a new at least one category,

deleting an existing of said at least one category, and/or

modifying said at least one category;

iv) recommending said at least one course of action to effect a change in said at least one health care services event; and

/or

v) minimizing at least one of an underlying activity, and/or subevent leading to at least one of a negative data point and/or a negative aspect, wherein said negative datapoint and/or said negative aspect is associated with any negative category;

vi) maximizing at least one of an underlying activity and/or subevent leading to a at least one of a positive data point and/or a positive aspect, wherein said positive datapoint and/or said positive aspect is associated with any positive category;

vii) recommending in at least one of real time, and/or retroactively; and

/or

viii) recommending said course of action directed at improving utilization of health care facility resources.

7. The method according to claim 1, further comprising

e) notifying at least one entity wherein said notifying comprises at least one of:

i) notifying of said at least one course of action;

ii) alerting said at least one entity;

iii) providing output to at least one entity;

iv) providing interactive prompting to said at least one entity;

v) allowing interactive deferral by said at least one entity;

vi) providing prompting to said at least one entity;

vii) providing output data in an easily accessible and interactive format;

viii) notifying in at least one of real time, and/or retroactively; and

/or

ix) notifying of said course of action directed at improving utilization of health care facility resources.

8. The method according to claim 7, wherein said (e) comprises at least one of:

x) providing a dashboard user interface application;

xi) providing an executive information system (EIS);

xii) providing a graphical user interface (GUI);

xiiii) providing an interface customized to user needs and/or preferences;

xiv) providing a dashboard and/or interactive, easy to use user interface elements;

xv) providing an easy to change and/or customize interface; and

/or

xvi) a dashboard customizable for the needs of an entity.

9. The method according to claim 1, further comprising

e) ranking, based on at least one metric, at least one of:

a plurality of entities,

at least one healthcare service facility,

at least one department of said at least one healthcare service facility,

said at least one healthcare service event; and

/or

said at least one health care service event across a plurality of healthcare service facilities,

wherein said ranking comprises at least one of a comparative ranking and/or a benchmark.

10. The method of claim 1, wherein said data comprises location based data comprising at least one of:

a location of each of said plurality of entities;

a temporal relationship associated with said each of said plurality of entities being located at said location;

a temporal extent of said each of said plurality of entities being located at said location;

a proximity between at least two of said plurality of entities;

a temporal extent of said proximity;

a temporal relationship associated with said proximity;

a location of said at least one health care service delivery event;

a temporal extent of said at least one health care service delivery event; and

/or

a temporal relationship associated with said health care service delivery event.

11. The method according to claim 10, wherein said location based data comprises at least one of:

location based data in at least two dimensions;

location based data in at least three dimensions;

location based data in at least two dimensions plus time;

a geosynchronous positioning satellite (GPS) data;

a real time location system (RTLS) data;

a radio frequency identification (RFID) data;

a wireless and/or wired network based data;

a WI-FI based location data;

a WI-MAX based location data;

an ultra-wideband location data; and

/or

an auto identification system (AIS).

12. The method according to claim 1, wherein said health care services event is delivered by a health care resource comprising at least one of:

a healthcare provider;

a healthcare worker;

a physician;

a nurse;

a care giver;

a surgeon;

an orderly;

transportation;

a therapist;

an occupational therapist (OT);

a physical therapist (PT);

a pulmonary therapist (PT);

a pulmonologist;

an oncological surgeon;

a cardiac surgeon;

an executive;

an administrator;

an ancillary service provider;

a physician'"'"'s assistant;

an emergency medical technician (EMT);

a first responder;

a police officer; and

/or

a clinician.

13. The method according to claim 1, wherein said health care services event is delivered by a health care resource comprising at least one of:

a medical device;

a medical supply;

a piece of equipment;

a specimen;

a lab specimen;

a medication;

an instrument;

a bed;

a gurney;

an imaging device comprising at least one of an X-Ray device, a CT scan device, an MRI image device, a scanned image device, an electronic image device, and/or another image device;

a waveform comprising at least one of an EKG, an ECG, another waveform;

a medical device comprising at least one of a pulmonary function monitor, a heart monitor, a wireless RF monitor, and/or a wired monitor;

a physical record;

an electronic medical record;

a personal health record;

a patient medical record; and

/or

an RFID tag;

wherein said health care services event is delivered by a health care facility comprising at least one of;

a hospital;

a health care system;

an integrated delivery network;

a plurality of hospitals;

a nursing home;

a critical care service;

an assisted living facility;

a hospice service;

a physical therapy clinic;

a therapy clinic;

a clinic;

a medical supplier;

a pharmacy;

a doctor'"'"'s office;

a dental office;

a home;

a remotely monitored location;

a remote consultation location;

a home health care service; and

/or

a health care clinic; and

wherein said health care services event is delivered by a health care facility comprising a plurality of departments comprising at least one of;

an operating room;

a nursing station;

an emergency department;

a critical care unit;

a cardiac care unit;

an intensive care unit;

a nursery;

a pediatric department;

a maternity department;

a surgery department;

a surgery center;

an oncology department;

a geriatrics department;

a physical therapy department;

an occupational therapy department;

an orthopedic department;

a radiology department;

a ward (inpatient);

a clinic (outpatient);

a medical office;

a physician'"'"'s office;

a medical specialty department;

a health care facility room;

a care delivery room;

a recovery room;

a waiting room;

a pre-operative room;

a post-operative room;

another department; and

/or

a patient room.

14. The method of claim 1, further comprising:

e) identifying at least one health care service preference relating to said at least one aspect of said at least one health care services event.

15. A computer program product embodied on a computer readable medium comprising program logic which when executed on a processor performs a method for improving the delivery of healthcare services, said method comprising:

a) capturing data associated with at least one health care services event, wherein said data comprises at least one aspect of said at least one health care services event;

b) categorizing, into at least one category, said at least one aspect of said at least one health care services event;

c) analyzing said data associated with said categorized health care services event comprising;

i) determining a correlation between said at least one aspect of said data to said at least one category, and

ii) determining any cause and effect relationship between said at least one aspect and said at least one category; and

d) recommending at least one course of action based on said at least one aspect having said correlation and said cause and effect relationship to said at least one category.

16. A system for improving the delivery of healthcare services comprising:

means for capturing data associated with at least one health care services event, wherein said data comprises at least one aspect of said at least one health care services event;

means for categorizing, into at least one category, said at least one aspect of said at least one health care services event;

means for analyzing said data associated with said categorized health care services event comprising;

means for determining a correlation between said at least one aspect of said data to said at least one category, and

means for determining any cause and effect relationship between said at least one aspect and said at least one category; and

means for recommending at least one course of action based on said at least one aspect having said correlation and said cause and effect relationship to said at least one category.

17. The system according to claim 16, further comprising:

an analytics system adapted for assisting an entity to optimize resource utilization via a performance analytics engine (PAE) infrastructure and services system, said analytics system comprising at least one of;

at least one transaction source data feed (TSDF) non-location based ordering system,

at least one transaction source extractor means for extracting transaction data from said transaction source data feed,

at least one transaction source normalizer means for preparing data for analysis, and for normalizing transaction data from said transaction source extractor, and

at least one transaction source aggregation engine means for homogeneous collecting, screening, and sorting through large volumes of normalized transaction data from said transaction source normalizer,

wherein said at least one transaction source aggregation engine means uses proprietary algorithms based on at least one of Bayesian analysis and/or heuristic methods; and

/or

at least one location source data feed (LSDF) location based system comprising data relating to location of at least one of a patient location, a device location, and/or a clinician location,

at least one location source extractor means for extracting location data from said location source data feed,

at least one location source normalizer means for normalizing location data from said location source extractor, and

at least one location source aggregation engine means for collecting heterogeneously, screening, and sorting through large volumes of normalized location data from said location source extractor,

wherein said at least one location source aggregation engine uses proprietary algorithms based on Bayesian analysis and/or heuristic methods; and

at least one interface means for interactive entry and/or acceptance by at least one of an administrative user, a healthcare provider, a support staff person, and/or a health care facility system, wherein said interactive entry and/or acceptance is of at least one of at least one expected event, at least one rule, at least one time measure, at least one outcome, and/or at least one preference or set of preferences.

18. The system according to claim 17, wherein said transaction source data comprises at least one data from at least one transaction system regarding at least one of:

an admission/discharge/transfer;

an order,

a result,

a computerized physician order entry (CPOE),

a scheduled event,

an appointment,

a patient movement, and/or

a device movement.

19. The system according to claim 17, wherein said at least one LSDF comprises location source data comprising a location data set relating to a location of at least one of:

at least one patient;

at least one person;

at least one employee;

at least one non-employee;

at least one contractor;

at least one affiliate;

at least one business partner;

at least one resident;

at least one healthcare worker;

at least one healthcare provider;

at least one living being;

at least one supply;

at least one piece of equipment; and

/or

at least one device.

20. The system of claim 17, wherein said performance analytics engine comprises at least one of:

at least one means for moving and/or extracting data;

at least one means for normalizing data;

at least one means for aggregating data;

at least one means for matching data and expected events;

at least one means for matching expected events and actual events;

at least one means for preparing at least one of an alarm, a notification, a recommendation, and/or a message to at least one of individuals and/or systems;

at least one means for delivering a message to at least one of a person, interface and/or a system;

at least one means for updating an algorithm;

at least one means for learning;

at least one means for providing a heuristic method;

at least one means for correlating;

at least one means for determining a relative importance of a deviations;

at least one application service provider (ASP) service;

at least one software as a service (SaaS) based service;

at least one on demand service offering;

at least one utility computing offering;

at least one service oriented architecture (SOA) based offering;

at least one knowledge base (KB);

at least one rules database;

at least one inference engine

at least one Bayesian inference engine; and

/or

at least one means for providing an expert system.

21. The system according to claim 17, wherein said at least one performance analytics engine comprises at least one of:

means for matching clinical orders and/or procedures,

wherein said clinical orders and/or procedures comprise at least one of;

a lab test, an x-ray, an image, a magnetic resonance image (MRIs),

a computer tomography (CT) scan, an ultrasound, patient data, a scheduled event, an unscheduled event, a movement, a transfer, and/or an expected event;

means for matching an expected event with an actual event;

means for comparing an expected event with actual event;

means for matching expected and actual event deviations;

means for preparing an alarm, a message, an alert, a prompt, an indication, a recommendation, and/or a notification,

wherein said means for preparing comprises means for using a delivery mechanism to notify individuals of deviations with or without appropriate remedial actions;

means for preparing an alarm and/or a message using a delivery mechanism to notify health care facility systems; and

means for updating an algorithm, for using a heuristic method, for learning, for iteratively learning, for correlating, and/or for determining a relative importance of a deviation.