Rosenfeld, Brian A. (Baltimore, MD, US)
Breslow, Michael (Lutherville, MD, US)

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08/12/2008

09/26/2005

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VISICU, Inc. (Baltimore, MD, US)

340/521

340/517, 340/524, 340/525, 340/3.1, 340/506, 340/573.1, 340/825.36, 340/825.49

G08B23/00

340/521, 340/517, 340/524, 340/525, 340/3.1, 340/506, 340/825.36, 340/825.49

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WO/1998/029790	July, 1998			MEDICAL INFORMATION SYSTEM
WO/1999/013766	March, 1999			CRITICAL CARE MANAGEMENT SYSTEM INCORPORATING REMOTE IMAGING AND TELEMETRY
WO/2000/079466	December, 2000			TELEMEDICAL EXPERT SERVICE PROVISION FOR INTENSIVE CARE UNITS

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Reed M. Gardner, Ph.D., David V. Ostler, and O. Hank Duffy, M.D., Computers in the Emergency Room, Internal Medicine for the Specialist, vol. 8, No. 3, Mar. 1987.
Dean F. Sittig, Nathan L. Pace, Reed M. Gardner, Eduardo Beck, and Alan H. Morris, Implementation of a Computerized Patient Advice System Using the HELP Clinical Information System, Computers and Biomedical Research 22, 474-487, 1989, Academic Press Inc.
P. D. Clayton, R. Scott Evans, T. Pryor, R. M. Gardner, P. J. Haug, O. B. Wigertz, and H. R. Warner, Bringing HELP to the Clinical Laboratory—Use of an Expert System to Provide Automatic Interpretation of Laboratory Data, Ann Clin Biochem 1987; 24: Supplement.
D. F. Sittig, Ph.D., R. M. Gardner, Ph.D., N. L. Pace, M.D., M. Bombino, M.D., and A. H. Morris, M.D., Compas: A Computerized Patient Advice System to Direct Ventilatory Care, Medical Informatics 88: Computers in Clinical Medicine, Sep. 13-15, 1988, British Medical Informatics Society, London.
Karen E. Bradshaw, Ph.D., Dean F. Sittig, Ph.D., Reed M. Gardner, Ph.D., T. Alllan Pryor, Ph.D., and Marge Budd, M.S., Improving Efficiency and Quality in a Computerized ICU, 1988 SCAMC, Inc.
Dean F. Sittig, Ph.D., C. Gregory Elliott, M.D., C. Jane Wallace, R.N., B.S.N., Polly Bailey, R.N., Reed M. Gardner, Ph.D., Computerized Screening for Identification of Adult Respiration Distress Syndrome (ARDS) Patients, 1988 SCAMC, Inc.
R. Scott Evans, Ph.D., Reed M. Gardner, Ph.D., John P. Burke, M.D., Stanley L. Pestotnik, R.P.H., Robert A. Larsen, M.D., David C. Classen, M.D., and Paul D. Clayton, Ph.D., A Computerized Approach to Monitor Prophylactic Antibiotics, 1987, SCAMC, Inc.
H. Keller and CH. Trendelenburg, Data Presentation Interpretation, Clinical Biochemistry Principles, Methods, Applications, Walter-deGruyter & Co., 1989.
Emmanuel Furst, Ph.D., Cardiovascular Technology, The Journal of Cardiovascular Nursing, Nov. 1989, 68-78.
Dean F. Sittig, Reed M. Gardner, Nathan L. Pace, Alan H. Morris, and Eduardo Beck, Computerized Management of Patient Care in a Complex, Controlled Clinical Trial in the Intensive Care Unit, Computer Methods and Programs in Biomedicine 30, 1989, 77-84.
Karen E. Bradshaw, Ph.D., Dean F. Sittig, Ph.D., Reed M. Gardner, Ph.D., T. Allan Pryor, Ph.D., and Marge Budd, R.N., M.S., Computer-Based Data Entry for Nurses in the ICU, Clinical Computing, Nov. 1988.
Thomas D. East, Ph.D., Alan H. Morris, M.D., Terry Clemmer, M.D., James F. Orme, M.D., C. Jane Wallace, B.S.N., Susan Henderson, B.A., Dean F. Sittig, Ph.D., Reed M. Gardner, Ph.D., Development of Computerized Critical Care Protocols—A Strategy That Really Works!, 1990 LDS Hospital, Salt Lake City, UT.
R. Scott Evans, Ph.D., John P. Burke, M.D., Stanley L. Pestonik, R.Ph., David C. Classen, M.D., Ronald L. Menlove, Ph.D., and Reed M. Gardner, Ph.D., Prediction of Hospital Inflections and Selection of Antibiotics Using an Automated Hospital Database, 1990, SCAMC, Inc. 663-667.
Susan E. Henderson, B.A., Robert O. Crapo, M.D., Thomas D. East, Ph.D., Alan H. Morris, M.D., C. Jane Wallace, R.N., Reed M. Gardner, Ph.D., Computerized Clinical Protocols in an Intensive Care Unit: How Well are They Followed?, 1990, SCAMC, Inc., LDS Hospital, Salt Lake City, UT.
Reed M. Gardner, PHD, Russell K. Hulse, RPH, MBA, Keith G. Larsen, RPH, Assessing The Effectiveness Of A Computerized Pharmacy System, 1990, SCAMC, Inc., 668-672.
Reed M. Gardner, “Patient-Monitoring Systems”, Medical Informatics: Computer Applications in Health Care, E.H. Shortliffe and L.E. Perrealt (eds.), G. Wiederhold and L.M. Fagan (assoc. eds.) (Reading, MA: Addison-Wesley, 1990.
Reed M. Gardner, Olaf K. Golubjatnikov, R. Myron Laub, Julie T. Jacobson, and R. Scott Evans, Computer-Critiqued Blood Ordering Using the HELP System, Computers and Biomedical Research 23, 514-528, 1990, Academic Press, Inc.
Karen E. Tate, Ph.D., Reed M. Gard'ner, Ph.D., and Lindell K. Weaver, M.D., A Computerized Laboratory Alerting System, Clinical Computing, 1990, vol. 7, No. 5, 296-301.
Dean F. Sittig, Reed M. Gardner, Alan H. Morris, and C. Jane Wallace, Clinical Evaluation of Computer-Based Respiratory Care Algorithms, International Journal of Clinical Monitoring and Computing 7, 1990, 177-185, Kluwer Academic Publishers, Netherlands.
R. Scott Evans, Stanley L. Pestotnilc, John P. Burke, Reed M. Gardner, Robert A. Larsen, and David C. Classen, Reducing Tile Duration Of Prophylactic Antibiotic Use Through Computer Monitoring Of Surgical Patients, DICP, The Annals of Pharmacotherapy, Apr. 1990, vol. 24, 351-354, Harvey Whitney Books Company, Cincinnati, OH.
Reed M. Gardner, and M. Michael Shabot, Computerized ICU Data Management: Pitfalls and Promises, International Journal of Clinical Monitoring and Computing 7: 99-105, 1990, Kluwer Academic Publishers, Netherlands.
Stanley L. Pestotnik, R.Ph., R. Scott Evans, Ph.D., John P. Burke, M.D., Reed M. Gardner, Ph.D., David C. Classen, M.D., Therapeutic Antibiotic Monitoring: Surveillance Using a Computerized Expert System, The American Journal of Medicine, Jan. 1990, vol. 88, 43-48.
Gil Kuperman, MD, Brent James, MD, Mstat, Julie Jacobsen, MT (ASCP), Reed M. Gardner, PhD, Continuous Quality Improvement Applied To Medical Care: Experiences At LDS Hospital, Medical Decision Making, Oct.-Dec. 1991, 60-65, vol. 11, No. 4.
Susan Henderson, Robert O. Crapo, C. Jane Wallace, Thomas D. East, Alan H. Morris, & Reed M. Gardner, Performance Of Computerized Protocols For The Management Of Arterial Oxygenation In An Intensive Care Unit, International Journal of Clinical Monitoring and Computing 8, 1992, 271-180, Kluwer Academic Publishers, Netherlands.
Eric F. LePage, MD, Reed M. Gardner, PhD, R. Myron Laub, MD, Julie T. Jacobson, MT(ASCP), Assessing The Effectiveness Of A Computerized Blood Order Consultation System, LDS Hospital, 1992, 33-37, AMIA, Inc.
E. LePage, R. Traineau, PH. Marchetti, M. Benbunan, R. M. Gardner, Development Of A Computerized Knowledge Based System Integrated To A Medical Workstation: Application To Blood Transfusion, MEDINFO, 1992, 585-590, Elsevier Science Publishers B.V.
Reed M. Gardner, Ph.D. and R. Scott Evans, Ph.D., Computer-Assisted Quality Assurance, Group Practice Journal, May/Jun. 1992, 41(3), 8-11.
Thomas D. East, Ph.D., W. Hsueh-Fen Young, M.S., and Reed M. Gardner, Ph.D., Digital Electronic Communication between ICU Ventilators and Computers and Printers, Respiratory Care, Sep. 1992, vol. 37 No. 9, 1113-1123.
Reed M. Gardner, Computers in Critical Care, Wellcome Trends in Hospital Pharmacy, Jul. 1992.
T. Allan Pryor, Reed M. Gardner and W. Clinton Day, Computer System for Research and Clinical Application to Medicine, AFIPS—Conference Proceedings, vol. 33, 1968, 809-816.
Homer R. Warner, M.D., Reed M. Gardner and Alan F. Toronto, M.D., Computer-Based Monitoring of Cardiovascular Functions in Postoperative Patients, Supplement II to Circulation, Apr. 1968, vols. 37 & 38, 68-74.
Russell M. Nelson, Homer R. Warner, Reed E. Gardner and J. D. Mortensen, Computer Based Monitoring of Patients Following Cardiac Surgery, Computers in Cardiology, Jul.-Aug. 1969, vol. 5, No. 4, 926-930.
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Reed M. Gardner, George H. Cannon, Alan H. Morris, Kenneth R. Olsen, W. Gary Price, Computerized Blood Gas Interpretation and Reporting System, Computer Magazine, Jan. 1975, 39-45.
Russell K. Hulse, Stephen J. Clark, J. Craig Jackson, Homer R. Warner and Reed M. Gardner, Computerized Medication Monitoring System, American Journal of Hospital Pharmacy 33, Oct. 1976, 1061-1064.
Reed M. Gardner, Ph.D., Computers in the ICU, Medical Electronics, Jun. 1984, 129-135.
Robert D. Andrews, M.S., M.T., Reed M. Gardner, Ph.D., Sandy M. Metcalf, R.R.T., and Deon Simmons, R.R.T., Computer Charting: An Evaluation of a Respiratory Care Computer System, Respiratory Care, Aug. 1985, vol. 30, No. 8, 695-707.
Reed M. Gardner, Ph.D., Computerized Data Management and Decision Making in Critical Care, Symposium on Critical Care, Aug. 1985, vol. 65, No. 4, 1041-1051.
Reed M. Gardner, David P. Scoville, Blair J. West, Beth Bateman, Robert M. Cundick, Jr., Terry P. Clemmer, Integrated Computer Systems for Monitoring of the Critically Ill, 1977, 301-307.
T. Allan Pryor, Reed M. Gardner, Paul D. Clayton, Homer R. Warner, A Distributed Processing System for Patient Management, Computers in Cardiology, Sep. 1978, 325-328.
Reed M. Gardner, Ph.D., Terry P. Clemmer, M.D., Keith G. Larsen, R.Ph., and Dickey S. Johnson, R.N., Computerized Alert System Use in Clinical Medicine, IEEE Session 6, 1979, 136-140.
Scott R. Cannon, and Reed M. Gardner, Experience with a Computerized Interactive Protocol System Using HELP, Computers and Biomedical Research 13, 1980, 399-409, Academic Press, Inc.
T. Allan Pryor, Paul D. Clayton, Reed M. Gardner, Randy Waki, and Homer R. Warner, HELP—A Hospital-Wide System for Computer-Based Support of Decision-Making, Jan. 1981.
T. A. Pryor, R. M. Gardner, P. D. Clayton and H. R. Warner, The HELP System, Proceedings of the Sixth Annual Symposium on Computer Applications in Medical Care, Oct.-Nov. 1982, 19-27, IEEE.
Reed M. Gardner, Information Management—Hemodynamic Monitoring, Seminars in Anesthesia, Dec. 1983, vol. 2, No. 4, 287-299.
T. A. Pryor, R. M. Gardner, P. D. Clayton, H. R. Warner, The HELP System, Journal of Medical Systems, 1983, vol. 7, No. 2, 87-102.
Reed M. Gardner, Blair J. West, T. Allan Pryor, Distributed Data Base and Network for ICU Monitoring, IEEE Computers in Cardiology, Sep. 18-24, 1984, 305-307.
Reed M. Gardner, T. Allan Pryor, Paul D. Clayton, and R. Scott Evans, Integrated Computer Network for Acute Patient Care, Symposium on Computer Applications in Medical Care, Nov. 4-7, 1984.
Reed M. Gardner, Tomorrow's Electronic Hospital is Here Today, IEEE Spectrum, Jun. 1984, 101-103.
Karen E. Bradshaw, Reed M. Gardner, Terry P. Clemmer, Jams F. Orme, Frank Thomas, and Blair J. West, Physician Decision Making—Evaluation of Data Used in a Computerized ICU, International Journal of Clinical Monitoring and Computing 1, 1984, 81-91.
Terry P. Clemmer, M.D., and Reed M. Gardner, Ph.D., Data Gathering, Analysis, and Display in Critical Care Medicine, Respiratory Care, Jul. 1985, vol. 30, No. 7, 586-601.
Reed M. Gardner, Ph.D., and William L. Hawley, Standardizing Communications and Networks in the ICU, Patient Monitoring and Data Management, 1985, 59-63.
R. Scott Evans, Reed M. Gardner, Allan R. Bush, John P. Burke, Jay A. Jacobson, Robert A. Larsen, Fred M. Meier, and Homer R. Warner, Development of a Computerized Infectious Disease Monitor (CIDM), Computers and Biomedical Research 18, 1985, 103-113.
R. Scott Evans, PhD, Robert A. Larsen, MD, John P. Burke, MD, Reed M. Gardner, PhD, Frederick A. Meier, MD, Jay A. Jacobson, MD, Marlyn T. Conti, BSN, Julie T. Jacobson, MT, Russell K. Hulse, RPH, Computer Surveillance of Hospital-Acquired Infections and Antibiotic Use, Journal of the American Medical Association, Aug. 22-29, 1986, vol. 256, No. 8, 1007-1011.
Reed M. Gardner, Computerized Management of Intensive Care Patients, Images, Signals, and Devices, 1986, vol. 3, No. 1.
R. Whiting, L. Hayes, The Practice of Telemedicine—The TARDIS Perspective, Informatics in Healthcare—Australia, Jul./Aug. 1997, vol. 6, No. 3, 103-106.
Ho Sung Lee, Seung Hun Park, and Eung Je Woo, Remote Patient Monitoring Service Through World-Wide Web, Proceedings—19th International Conference—IEEE/EMBS, Oct. 30-Nov. 2, 1997, 928-931.
Betty L. Grundy, M.D., Pauline Crawford, R.N., Paul K. Jones, Ph.D., May Lou Kiley, Ph.D., Arnold Reisman, Ph.D., Yoh-Han Pao, Ph.D., Edward L. Wilkerson, M.D., J. S. Gravenstein, M.D., Telemedicine in Critical Care: An Experiment in Health Care Delivery, Oct. 1977, 6:10.
Betty Lou Grundy, M.D., Paul K. Jones, Ph.D., and Ann Lovitt, M.D., Telemedicine in Critical Care: Problems in Design, Implementation, and Assessment, Critical Care Medicine, Jul. 1982, vol. 10, No. 7, 471-475.
Geraldine Fitzpatrick, TARDIS Evaluation: Report on Final Usage Evaluation of the TARDIS Telehealth System, Jul. 24, 1998, Issue No. 1.0.
Stephen M. Ayres, M.D., F.C.C.M., Ake Grenvik, M.D., Ph.D., F.C.C.M., Peter R. Holbrook, M.D., F.C.C.M., William C. Shoemaker, M.D., F.C.C.M., Textbook of Critical Care, 3rd Edition, 1995, Harcourt Brace & Company.
Karen B. Tate, Ph.D., Reed M. Gardner, Ph.D., Kurt Scherting, Nurses, Pagers, and Patient-Specific Criteria; Three Keys to Improved Critical Value Reporting, 1995, 164-168, AMIA, Inc.
Karen E. Tate, Ph.D., Reed M. Gardner, Ph.D., Computers, Quality, and the Clinical Laboratory: A Look at Critical Value Reporting, 17th Annual Symposium on Computer Applications in Medical Care, Oct. 30-Nov. 3, 1993, 193-197.
Peter J. Haug, Reed M. Gardner, Karen E. Tate, R. Scott Evans, Thomas D. East, Gilad Kuperman, T. Allan Pryor, Stanley M. Huff, and Homer R. Warner, Decision Support in Medicine: Examples from the HELP System, Computers and Biomedical Research 27, 1994, 396-418.
Thomas D. East, Ph.D., C. Jane Wallace, R.N., M.S., Alan H. Morris, M.D., Reed M. Gardner, Ph.D., and Dwayne R. Westenskow, Ph.D., Computers in Critical Care, New Technologies in Critical Care, Jun. 1995, vol. 7, No. 2, 203-216.
Reed M. Gardner, Ph.D., Bette B. Maack, R.R.A., R. Scott Evans, Ph.D., and Stanley M. Huff, M.D., Computerized Medical Care: The HELP System at LDS Hospital, Journal of AHIMA, Jun. 1992, 63(6):68-78.
Reed M. Gardner, Ph.D., Integrated Computerized Records Provide Improved Quality of Care with Little Loss of Privacy, Journal of the AMIA, Jul./Aug. 1994, vol. 1, No. 4, 320-322.
S Reddy, M Niewiadomska-Bugaj, Y V Reddy, H C Galfalvy, V Jagannathan, R Raman, K. Srinivas, R. Shank, T. Davis, S. Friedman, MD, B. Merkin, MD, M. Kilkenny,MD, Experience with ARTEMIS—An Internet-Based Telemedicine System, AMIA, 1997, 759-763.
Patrick R. Norris, M.S., Benoit M Dawant, Ph.D., Antoine Geissbuhler, M.D., Web-Based Data Integration and Annotation in the Intensive Care Unit, 1997.
H. C. Galfalvy, M.S., S. M. Reddy, Ph.D., M. Niewiadomska-Bugaj, Ph.D., S. Friedman, M.D., Evaluation of Community Care Network (CNN) System in a Rural Health Care Setting, 1995, AMIA Inc., 698-702.
K. Major, M. Shabot, S. Cunneen, Wireless Critical Alerts and Patient Outcomes in the Surgical Intensive Care Unit; The American Surgeon, 2000; p. 1057-1060.
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Pope, Daryl C.

Roberts, Mardula & Wertheim, LLC

This application is a continuation in part of application Ser. No. 10/654,668 filed Sep. 04, 2003 and a continuation in part of application Ser. No. 10/946,548 filed Sep. 21, 2004, both of which are continuations in part of application Ser. No. 09/443,072 filed Nov. 18, 1999, now U.S. Pat. No. 6,804,656 issued Oct. 12, 2004, which claims the benefit of U.S. Provisional Application Ser. No. 60/141,520, filed Jun. 23, 1999. The Ser. No. 09/443,072 application is hereby incorporated by reference in its entirety for all purposes.

What is claimed is:

1. A portable monitoring system for geographically dispersed health care locations comprising: a telecommunication network; portable monitoring stations comprising monitoring equipment, wherein the monitoring equipment comprises instructions for monitoring data elements from patients assigned to geographically dispersed health care locations and for sending the monitored data elements to a remote command center via the telecommunications network, wherein the remote command center comprises instructions for: receiving the monitored data elements from a patient assigned to a health care location; accessing patient data elements indicative of a medical condition associated with the patient; establishing a patient-specific rule associated with the patient; and applying the patient-specific rule continuously and simultaneously using a rules engine, wherein the rules engine comprises instructions for: selecting data elements from the monitored data elements and the patient data elements associated with the patient; applying the patient-specific rule to the selected data elements; determining in an automated fashion at the remote command center whether the patient-specific rule for the patient has been contravened; and in the event the patient-specific rule for the patient has been contravened, issuing an alert from the remote command center.

2. The system of claim 1, wherein the monitoring equipment comprises physiological sensors and wherein monitored data elements comprise physiological data elements.

3. The system of claim 1, wherein the portable monitoring system further comprises: a visual monitoring system; an audio system; and a network interface to connect the portable monitoring system to the network.

4. The system of claim 3, wherein the monitored data elements comprise patient video image data elements and patient audio data elements.

5. The system of claim 1, wherein the portable monitoring station is wearable by the patient.

6. The system of claim 5, wherein the patient is a fetus carried by an expectant mother and wherein the portable monitoring station comprises a tachodynamometer.

7. The system of claim 1, wherein the portable monitoring station comprises a patient support device, and wherein the monitoring equipment is integrated into the patient support device.

8. The system of claim 7, wherein the patient support device is selected from the group consisting of a bed, a chair, a recliner, a wheelchair, a stretcher and a gurney.

9. The system of claim 1, wherein the telecommunications network comprises a wireless sub-network and wherein the monitored data elements are sent to the remote command center via the wireless subnetwork.

10. The system of claim 1, wherein the portable monitoring station comprises a cart.

11. The system of claim 1, wherein the health care location is a hospital.

12. The system of claim 1, wherein the health care location is a nursing home.

13. The system of claim 1, wherein the health care location is a mobile health care facility.

14. The system of claim 13, wherein the mobile health care facility is selected from the group consisting of a ship, a helicopter, and an ambulance.

15. The system of claim 1, wherein the health care location is a space-based health care facility.

16. The system of claim 1, wherein the health care location is a field health care facility.

17. The system of claim 1, wherein the health care location is a residence.

18. The system of claim 1, wherein the health care location is an emergency room.

19. The system of claim 1, wherein the health care location is an intensive care unit.

20. The system of claim 1, wherein the health care location is an operating room.

21. The system of claim 1, wherein the health care location is a step down unit.

22. The method for monitoring patients assigned to geographically dispersed health care locations of claim 2, wherein the portable monitoring station comprises a cart.

23. The system of claim 1, wherein the remote command center further comprises: an external network interface, wherein the external network interface comprises instructions for connecting to an external network; and instructions for providing a health care provider access to the remote command center via the external network.

24. The system of claim 23, wherein the external network is selected from the group consisting of a wired network, a wireless network, a cable network, a fiber optic network, and the Internet.

25. The system of claim 23, wherein the health care provider is selected from the group consisting of a physician, a nurse, a clinician, a diagnostician, and a intensivist.

26. The system of claim 23, wherein the remote command center further comprises instructions for sending the health care provider the alert if the patient-specific rule for the hospitalized patient has been contravened.

27. A method for monitoring patients assigned to geographically dispersed health care locations comprising: associating a portable monitoring station with a patient assigned to a health care location; receiving at a remote command center monitored data elements from the patient and other patients associated with other portable monitoring stations and assigned to other geographically dispersed health care locations via a telecommunications network; accessing patient data elements indicative of a medical condition associated with the patient and the other patients; establishing patient-specific rules associated with the patient and each of the other patients; selecting data elements from the monitored data elements associated with the patient and the patient data elements associated with the patient; applying the patient-specific rule associated with the patient to the selected data elements continuously and simultaneously with the application of the other patient-specific rules to the patient data elements associated with the other patients; making a determination in an automated fashion at the remote command center whether the patient-specific rule for the patient has been contravened; and in the event the patient-specific rule for the patient has been contravened, issuing an alert from the remote command center.

28. The method for monitoring patients assigned to geographically dispersed health care locations of claim 27, wherein monitoring equipment comprises physiological sensors and wherein monitored data elements comprise physiological data elements.

29. The method for monitoring patients assigned to geographically dispersed health care locations of claim 28, wherein the portable monitoring system further comprises: a visual monitoring system; an audio system; and a network interface to connect the portable monitoring system to the network.

30. The method for monitoring patients assigned to geographically dispersed health care locations of claim 29, wherein the portable monitoring station is wearable by the patient.

31. The method for monitoring patients assigned to geographically dispersed health care locations of claim 30, wherein the patient is a fetus carried by an expectant mother and wherein the portable monitoring station comprises a tachodynamometer.

32. The method for monitoring patients assigned to geographically dispersed health care locations of claim 31, wherein the monitored data elements are acquired using monitoring equipment integrated into a patient support device.

33. The method for monitoring patients assigned to geographically dispersed health care locations of claim 32, wherein the patient support device is selected from the group consisting of a bed, a chair, a recliner, a wheelchair, a stretcher and a gurney.

34. The method for monitoring patients assigned to geographically dispersed health care locations of claim 27, wherein the telecommunications network comprises a wireless sub-network and wherein receiving at a remote command center monitored data elements from geographically dispersed patients via a telecommunications network comprises receiving at the remote command center monitored data elements from the geographically dispersed patients via the wireless subnetwork.

35. The method for monitoring patients assigned to geographically dispersed health care locations of claim 27, wherein the health care location is a hospital.

36. The method for monitoring patients assigned to geographically dispersed health care locations of claim 27, wherein the health care location is a nursing home.

37. The method for monitoring patients assigned to geographically dispersed health care locations of claim 27, wherein the health care location is a mobile health care facility.

38. The method for monitoring patients assigned to geographically dispersed health care locations of claim 37, wherein the mobile health care facility is selected from the group consisting of a ship, a helicopter, and an ambulance.

39. The method for monitoring patients assigned to geographically dispersed health care locations of claim 27, wherein the health care location is a space-based health care facility.

40. The method for monitoring patients assigned to geographically dispersed health care locations for of claim 27, wherein the health care location is a field health care facility.

41. The method for monitoring patients assigned to geographically dispersed health care locations of claim 27, wherein the health care location is a residence.

42. The method for monitoring patients assigned to geographically dispersed health care locations of claim 27, wherein the wherein health care location is an emergency room.

43. The method for monitoring patients assigned to geographically dispersed health care locations of claim 27, wherein the health care location is an intensive care unit.

44. The method for monitoring patients assigned to geographically dispersed health care locations of claim 27, wherein the health care location is an operating room.

45. The method for monitoring patients assigned to geographically dispersed health care locations of claim 27, wherein the health care location is a step down unit.

46. The method for monitoring patients assigned to geographically dispersed health care locations of claim 27, wherein the telecommunications network is selected from the group consisting of a wired network, a wireless network, a cable network, a fiber optic network, and the Internet.

47. The method for monitoring patients assigned to geographically dispersed health care locations of claim 27 further comprising: interfacing with an external network; and providing a health care provider access to the remote command center via the external network.

48. The method for monitoring patients assigned to geographically dispersed health care locations of claim 47, wherein the external network is selected from the group consisting of a wired network, a wireless network, a cable network, a fiber optic network, and the Internet.

49. The method for monitoring patients assigned to geographically dispersed health care locations as claim 47, wherein the health care provider is selected from the group consisting of a physician, a nurse, a clinician, a diagnostician, and a intensivist.

50. The method for monitoring patients assigned to geographically dispersed health care locations of claim 47 further comprising sending the health care provider the alert if the patient-specific rule for the hospitalized patient has been contravened.

51. The system of claim 1, wherein the telecommunications network is selected from the group consisting of a wired network, a wireless network, a cable network, a fiber optic network, and the Internet.

FIELD OF THE INVENTION

This invention relates generally to the care of patients in health care locations, as for example and without limitation, Intensive Care Units (ICUs). More particularly this invention is a system and method for care of the critically ill that combines a real-time, multi-node telemedicine network and an integrated, patient care management system to enable specially-trained Intensivists to provide 24-hour/7-day-per-week patient monitoring and management to multiple, geographically dispersed ICUs from both on-site and remote locations.

BACKGROUND OF THE INVENTION

While the severity of illness of ICU patients over the past 15 years has increased dramatically, the level of and type of physician coverage in most ICUs has remained constant. Most ICU patients receive brief minutes of attention during morning rounds from physicians with limited critical care experience. During the remainder of the day and night, nurses are the primary caregivers, with specialists called only after patient conditions have started to deteriorate. The result of this mismatch between severity of illness and physician coverage is an unacceptably high ICU mortality rate (10% nationwide), and a high prevalence of avoidable errors that result in clinical complications. In 1998, an Institute of Medicine Roundtable determined that avoidable patient complications were the single largest problem in medical care delivery. In another prominent 1998 study of 1000 patients, 46% experienced an avoidable adverse event in care, with 40% of these errors resulting in serious disability or death.

The physicians who can remedy this situation are in critically short supply. Numerous studies have shown that Intensivists (physicians who have trained and board certified in Critical Care Medicine) can markedly improve patient outcomes. However, only one-third of all ICU patients ever has an Intensivist involved in their care, and the number of Intensivists would need to increase tenfold (nationally) to provide 24-hour coverage to all ICU patients. With the rapid aging of the population, this shortfall of expertise is going to increase dramatically.

Even where Intensivists are present (and especially where they are not), patients suffer from unnecessary variation in practice. There is little incentive for physicians to develop and conform to evidence-based best practices (it takes significant work and a change in behavior to develop and implement them). This variation contributes to sub-optimal outcomes, in both the quality and cost of care delivered to ICU patients.

What is needed is a redesigning of the critical care regimen offered to patients in an ICU. Rather than the consultative model where a periodic visit takes place and the doctor then goes away, a more active 24-hour intensivist managed care is required. Further, technology that leverages the intensivists' expertise and standardizes the care afforded to patients in an ICU is required. Further, continuous feedback to improve the practice of intensivists in an ICU is necessary to provide the intervention required to minimize adverse events. This invention seeks to provide new methods for managing and delivering care to the critically ill.

Attempts to automate various aspects of patient care have been the subject of various inventions. For example, U.S. Pat. No. 5,868,669 to Iliff was issued for “Medical Diagnostic and Treatment Advice System.” The disclosed invention is for a system and method for providing knowledge based medical diagnostic and treatment advice to the general public over a telephone network.

U.S. Pat. No. 5,823,948 to Ross, Jr. et al was issued for “Medical Records Documentation, Tracking and Order Entry System”. The disclosed invention is for a system and method that computerizes medical records, documentation, tracking and order entries. A teleconferencing system is employed to allow patient and medical personnel to communicate with each other. A video system can be employed to videotape a patient's consent.

U.S. Pat. No. 4,878,175 to Norden-Paul et al. was issued for “Method for Generating Patient-Specific Flowsheets By Adding/Deleting Parameters.” The disclosed invention is for an automated clinical records system for automated entry of bedside equipment results, such as an EKG monitor, respirator, etc. The system allows for information to be entered at the bedside using a terminal having input means and a video display.

U.S. Pat. No. 5,544,649 to David et al. was issued for “Ambulatory Patient Health Monitoring Techniques Utilizing Interactive Visual Communications.” The disclosed invention is for an interactive visual system, which allows monitoring of patients at remote sites, such as the patient's home. Electronic equipment and sensors are used at the remote site to obtain data from the patient, which is sent to the monitoring site. The monitoring site can display and save the video, audio and patient's data.

U.S. Pat. No. 5,867,821 to Ballantyne et al. was issued for “Method and Apparatus for Electronically Accessing and Distributing Personal Health Care Information and Services in Hospitals and Homes.” The disclosed invention is for an automated system and method for distribution and administration of medical services, entertainment services, and electronic health records for health care facilities.

U.S. Pat. No. 5,832,450 to Myers et al. issued for “Electronic Medical Record Using Text Database.” The disclosed invention is for an electronic medical record system, which stores data about patient encounters arising from a content generator in freeform text.

U.S. Pat. No. 5,812,983 to Kumagai was issued for “Computer Medical File and Chart System.” The disclosed invention is for a system and method which integrates and displays medical data in which a computer program links a flow sheet of a medical record to medical charts.

U.S. Pat. No. 4,489,387 to Lamb et al. was issued for “Method and Apparatus for Coordinating Medical Procedures.” The disclosed invention is for a method and apparatus that coordinates two or more medical teams to evaluate and treat a patient at the same time without repeating the same steps.

U.S. Pat. No. 4,731,725 to Suto et al. issued for “Data Processing System which Suggests a Pattern of Medical Tests to Reduce the Number of Tests Necessary to Confirm or Deny a Diagnosis.” The disclosed invention is for a data processing system that uses decision trees for diagnosing a patient's symptoms to confirm or deny the patient's ailment.

U.S. Pat. No. 5,255,187 to Sorensen issued for “Computer Aided Medical Diagnostic Method and Apparatus.” The disclosed invention is for an interactive diagnostic system which relies on color codes which signify the presence or absence of the possibility of a disease based on the symptoms a physician provides the system.

U.S. Pat. No. 5,553,609 to Chen et al. issued for “Intelligent Remote Visual Monitoring System for Home Health Care Service.” The disclosed invention is for a computer-based remote visual monitoring system, which provides in-home patient health care from a remote location via ordinary telephone lines.

U.S. Pat. No. 5,842,978 to Levy was issued for “Supplemental Audio Visual Emergency Reviewing Apparatus and Method.” The disclosed invention is for a system which videotapes a patient and superimposes the patient's vital statistics onto the videotape.

While these inventions provide useful records management and diagnostic tools, none of them provides a comprehensive method for monitoring and providing real time critical care at disparate ICUs. In short, they are NOT designed for critical care. Further, none of these inventions provide for the care of a full time intensivist backed by appropriate database and decision support assistance in the intensive care environment. What would be useful is a system and method for providing care for the critically ill that maximizes the presence of an intensivist trained in the care of the critically ill. Further such a system would standardize the care in ICUs at a high level and reduce the mortality rate of patients being cared for in ICUs.

SUMMARY OF THE INVENTION

The present invention provides a core business of Continuous Expert Care Network (CXCN) solution for hospital intensive care units (ICUs). This e-solution uses network, database, and decision support technologies to provide 24-hour connectivity between Intensivists and ICUs. The improved access to clinical information and continuous expert oversight leads to reduced clinical complications, fewer medical errors, reduced mortality, reduced length of stay, and reduced overall cost per case.

The technology of the present invention as explained below can be implemented all at once or in stages. Thus the technology, as more fully explained below is available in separate components to allow for the fact that hospitals may not be able to implement all of the technology at once. Thus modular pieces (e.g. videoconferencing, vital sign monitoring with smart alarms, hand-held physician productivity tools, etc.) can be implemented, all of which can add value in a stand-alone capacity. First amongst these offerings will be an Intensivist Decision Support System, a stand-alone software application that codifies evidence-based, best practice medicine for 150 common ICU clinical scenarios. These support algorithms are explained more fully below.

The “Command Center” model, again as more fully set forth below, will ultimately give way to a more distributed remote management model where Intensivists and other physicians can access ICU patients and clinicians (voice, video, data) from their office or home. In this scenario, the present invention will be available in hospital applications that centralize ICU information, and offer physicians web-based applications that provide them with real-time connectivity to this information and to the ICUs. This access and connectivity will enable physicians to monitor and care for their patients remotely. These products will be natural extensions and adaptations of the present invention and the existing applications disclosed herein that those skilled in the art will appreciate and which do not depart from the scope of the invention as disclosed herein.

The present invention addresses these issues and shortcomings of the existing situation in intensive care, and its shortfalls via two major thrusts. First, an integrated video/voice/data network application enables continuous real-time management of ICU patients from a remote setting. Second, a client-server database application—integrated to the remote care network—provides the data analysis, data presentation, productivity tools and expert knowledge base that enable a single Intensivist to manage the care of up to 40 patients simultaneously. The combination of these two thrusts—care management from a remote location and new, technology-enhanced efficiency of Intensivist efforts—allows health care systems to economically raise the standard of care in their ICUs to one of 24×7 continuous Intensivist oversight.

It is therefore an object of the present invention to reduce avoidable complications in an ICU.

It is a further object of the present invention to reduce unexplained variations in resource utilization in an ICU.

It is a further objective of the present invention to mitigate the serious shortage of intensivists.

It is yet another objective of the present invention to reduce the occurrence of adverse events in an ICU.

It is a further objective of the present invention to standardize the care at a high level among ICUs.

It is yet another objective of the present invention to reduce the cost of ICU care.

It is yet another objective of the present invention to dramatically decrease the mortality in an ICU.

It is yet another objective of the present invention to bring information from the ICU to the intensivist, rather than bring the intensivist to the ICU.

It is a further objective of the present invention to combine tele-medical systems comprising two-way audio/video communication with a continuous real time feed of clinical information to enable the intensivist to oversee care within the ICU.

It is a further objective of the present invention to allow intensivists to monitor ICUs from a site remote from each individual ICU.

It is a further objective of the present invention to bring organized detailed clinical information to the intensivist, thereby providing standardized care in the ICU.

It is yet another objective of the present invention to utilize knowledge-based software to use rules, logic, and expertise to provide preliminary analysis and warnings for the intensivists.

The present invention comprises a command center/remote location, which is electronically linked to ICUs remote from the command center/remote location. The command center/remote location is manned by intensivists 24 hours a day, seven days per week. Each ICU comprises a nurse's station, to which data flows from individual beds in the ICU. Each patient in the ICU is monitored by a video camera, as well as by clinical monitors typical for the intensive care unit. These monitors provide constant real time patient information to the nurse's station, which in turn provides that information over a dedicated T- 1 (high bandwidth) line to the ICU command center/remote location. As noted earlier, the command center/remote location is remote from the ICU, thereby allowing the command center/remote location to simultaneously monitor a number of patients in different ICUs remote from the command center/remote location.

At each command center/remote location, video monitors exist so that the intensivist can visually monitor patients within the ICU. Further, the intensivist can steer and zoom the video camera near each patient so that specific views of the patient may be obtained, both up close and generally. Audio links allow intensivists to talk to patients and staff at an ICU bed location and allow those individuals to converse with the intensivist.

Clinical data is constantly monitored and presented to the command center/remote location in real time so that the intensivist can not only monitor the video of the patient but also see the vital signs as transmitted from the bedside. The signals from the clinical data and video data are submitted to a relational database, which comprises 1) standardized guidelines for the care of the critically ill, 2) various algorithms to support the intensive care regimen, 3) order writing software so that knowledge-based recommendations and prescriptions for medication can be made based upon the clinical data, and 4) knowledge-based vital-sign/hemodynamic algorithms that key the intensivist to engage in early intervention to minimize adverse events.

The advantage of the present invention is that intensivists see all patients at a plurality of ICU's at all times. Further, there is a continuous proactive intensivist care of all patients within the ICU, thereby minimizing adverse events. Intervention is triggered by evidence-based data-driven feedback to the intensivist so that standardized care can be provided across a plurality of ICUs.

The economic benefits of the present invention are manifold. For the first time, 24-hour a day, seven day a week intensivist care for patients in an ICU can be obtained. Further, more timely interventions in the care of the patients can be created by the knowledge-based guidelines of the present invention, thereby minimizing complications and adverse events. This in turn will lead to a reduced mortality within the ICU, and hence, a reduced liability cost due to the dramatic reduction in avoidable errors in health care.

By providing timely interventions, the length of stay within the ICU can be greatly reduced, thereby allowing more critically ill patients to be cared for in the ICU.

In addition, by reviewing and standardizing the care afforded to patients in an ICU, a more standardized practice across a variety of ICUs can be achieved. This will lead to more cost-effective care within the ICU, and reduced ancillary cost for the care of the critically ill.

The overall architecture of the present invention comprises a “pod.” The pod comprises a tele-medicine command center/remote location connected to a plurality multiple ICUs at various locations. The connection between the command center/remote location and the ICUs is via a dedicated wide-area network linking the ICUs to the command center/remote location and a team of intensivists who integrate their services to provide 24-hour, seven day a week care to all of the pod ICUs.

The pod is connected via a wide-area network using dedicated T- 1 lines, for example, with redundant backup. This network provides reliable, high speed secure transmission of clinical data and video/audio signals between each patient room and the command center/remote location. The use of a T- 1 line is not meant as a limitation. It is expected that more and higher bandwidth networks will become available. Such high bandwidth networks would come within the scope of the invention as well.

Each patient room is equipped with a pan/tilt/zoom video camera with audio and speaker to enable full videoconferencing capability. In addition, computer workstations are dedicated for exclusive physician use in each ICU, preferably at the nurse's station. Intensivists use the workstations to view patient information, consult decision support information, record their notes, and generate patient orders.

The patient management software used by intensivists is provided across the pod. Updates and changes made to the record are available at both the ICU and the command center/remote location for any given patient.

Each command center/remote location contains at least three workstations: one for the intensivist, one for the critical care registered nurse, and one for a clerk/administrative person.

The intensivist workstation comprises separate monitors for displaying ICU video images of patients and/or ICU personnel, output from bedside monitoring equipment, patient clinical data comprising history, notes, lab reports, etc., and decision support information. The staff at the command center/remote location are able to activate and control the cameras in each patient's room so that appropriate visual views of the patient can be generated.

Intensivists are able to switch between rooms and patients and can monitor at least two rooms simultaneously via the video screens. Patient data such as X-ray and ECG images are scanned and transmitted to the command center/remote location upon request of the intensivist.

Remote patient management is utilized in the present invention's critical care program to supplement traditional onsite care. The rationale underlying the remote patient management of the present invention is that critically ill patients are inherently unstable and require continuous expert care that is not now offered in existing ICU monitoring regimens. Further, remote monitoring allows a single intensivist to care for patients in multiple ICU locations, thereby creating an efficiency that makes continuous care feasible.

Remote intensivist care of the present invention is proactive. Intensivists will order needed therapies and check results of tests and monitor modalities in a more timely fashion than is currently offered. Patients can be observed visually when needed using the ceiling-mounted cameras in each room.

Command center/remote location personnel communicate with ICU staff through videoconferencing and through “hot phones,” which are dedicated telephones directly linked between the command center/remote location and the ICU. These communications links are used to discuss patient care issues and to communicate when a new order has been generated.

Intensivists document important events occurring during their shift in progress notes generated on the command center/remote location computer terminal.

Intensivists detect impending problems by intermittently screening patient data, including both real time and continuously stored vital sign data. Patient severity of illness determines the frequency with which each patient's data is reviewed by the intensivists.

Embodiments of the present invention provide a system for providing continuous, expert network health care services from a remote location. The system comprises a plurality of health care locations, at least one remote command center for managing health care at said plurality of health care locations, and at least one network. The plurality of health care locations is electronically connected to at least one remote command center by the network. The at least one remote command center provides intensivist monitoring of the plurality of health care locations 24 hours per days seven days per week. By way of illustration and not as a limitation, a health care location may be a hospital, an emergency room, an intensive care unit, an operating room, a step down unit, a nursing home, a space-based health care facility, a field health care facility, a residence, a labor delivery unit, and a mobile health care facility. By way of illustration and not as a limitation, a mobile health care facility may be a ship, a helicopter, and an ambulance. In an embodiment, a health care location comprises monitoring stations adapted for monitoring patient data elements from a patient and for transmitting the monitored patient data elements to the remote command center. In an alternate embodiment, the portable monitoring station comprises a cart. In still another embodiment, the transportable monitoring station is wearable by the patient. By way of illustration and not as a limitation, the patient is a fetus carried by an expectant mother and wherein the transportable monitoring station comprises a tachodynamometer. In yet another embodiment, the monitoring station comprises a patient support device and the monitoring equipment is integrated into the patient support device. By way of illustration and not as a limitation, the patient support device is selected from the group consisting of a bed, a chair, a recliner, a wheelchair, a stretcher and a gurney.

The remote command center further comprises a patient care management system for monitoring and treating individual patients at any of said plurality of healthcare locations. The patient care management system further comprises a data server/data warehouse for storing and analyzing data from the at least one remote command center.

Each of the plurality of health care locations further comprises patient monitoring equipment electronically connected to the at least one remote command center over the network. In another embodiment of the present invention each health care location further comprises a nurses' station electronically connected to said monitoring equipment and to the at least one remote command center over the network. In still another embodiment of the present invention, the healthcare locations comprise intensive care units (ICU's).

Optionally, the patient care management system further comprises a relational database for storing a plurality of decision support algorithms and for prompting intensivists to provide care to patients based upon any of the decision support algorithms. The algorithms are selected from the group consisting of algorithms for treating Acalculous Cholecystitis, Acute Pancreatitis Algorithms, Acute Renal Failure-Diagnosis, Acute Renal Failure-Management & Treatment, Adrenal Insufficiency. Agitation and Anxiety, Depression & Withdrawal, Aminoglycoside Dosing and Therapeutic Monitoring, an Amphotericin-B Treatment Guidelines, Analgesia, Antibiotic Classification & Costs, Antibiograms Algorithm, Antibiotic associated Colitis Algorithm, ARDS: Hemodynamic Management, ARDS: Steroid Use, ARDS: Ventilator Strategies, Asthma, Bleeding Patient, Bloodstream Infections, Blunt Cardiac Injury, Bradyarrhythmias, Brain Death, Bronchodilator Use in Ventilator Patients, Bronchoscopy & Thoracentesis Guidelines, Candiduria, Cardiogenic Shock, CardioPulmonary Resuscitation Guideline, Catheter Related Septicemia, a Catheter Replacement Strategies, Cervical Cord Injury, Congestive Heart Failure, COPD Exacerbation & Treatment, CXR (Indications), Dealing with Difficult patients and families, Diabetic Ketoacidosis, Dialysis, Diuretic Use, Drug Changes with Renal Dysfunction, Emergency Cardiac Pacing, Endocarditis Diagnosis and Treatment, Endocarditis Prophylaxis, End of Life Decisions, Endotracheal Tubes & Tracheotomy, Ethical Guidelines, Febrile Neutropenia, FUO, Fluid Resuscitation, Guillain-Barre Syndrome, Heparin, Heparin-Induced Thrombocytopenia, Hepatic Encephalopathy, Hepatic Failure, HIV+Patient Infections, Hypercalcemia Diagnosis and Treatment, Hyperglycemia Insulin Treatment, Hyperkalemia: Etiology & Treatment, Hypematremia: Etiology & Treatment, Hypertensive Crisis, Hypokalemia: Etiology & Treatment, Hyponatremia: Etiology & Treatment, Hypothermia, Identification of Cervical Cord Injury, Implantable Cardio-defibrillator, Intra-Aortic Balloon Device, Intracerebral Hemorrhage, Latex Allergy, Magnesium Administration, Management of Hypotension, Inotropes, Management of Patients with Ascites, Empiric Meningitis, Meningitis, a Myasthenia Gravis, Myocardial Infarction, Myocardial Infarction with left bundle branch block, Necrotizing Soft Tissue Infections, Neuromuscular Blockers, Neuromuscular Complications of Critical Illness, Non-Infectious Causes of Fever, Non-Traumatic Coma, Noninvasive Modes of Ventilation, Nutritional Management, Obstetrical Complication, Oliguria, Open Fractures, Ophthalmic Infections, Organ Procurement Guidelines, PA Catheter Guideline and Troubleshooting, Pancreatitis, Penetrating Abdominal Injury, Penetrating Chest Injury, Penicillin Allergy, Permanent Pacemaker and Indications, Pneumonia Community Acquired, Pneumonia Hospital Acquired, Post-Op Bleeding, Post-Op Hypertension, Post-Op Management of Abdominal Post-Op Management of Carotid, Post-Op Management of Open Heart, Post-Op Management of Thoracotomy, Post-Op Myocardial Ischemia (Non-Cardiac Arrhythmias after Cardiac Surgery), Post-Op Power Weaning, Pressure Ulcers, Pulmonary Embolism Diagnosis, Pulmonary Embolism Treatment, Respiratory Isolation, Sedation, Seizure, Status Epilepticus, Stroke, Sub-Arachnoid Hemorrhage, Supra-Ventricular Tachyarrhythmia, Supra-Ventricular Tachycardia, Wide Complex QRS Tachycardia, Therapeutic Drug Monitoring, Thrombocytopenia, Thrombolytic Therapy, Transfusion Guidelines, Traumatic Brain Injury, Assessment of Sedation, Sedation, Septic Shock, Bolus Sliding, Scale Midazolam, Short Term Sedation Process, Sinusitis, SIRS, Spinal Cord Injury, Steroid Replacement Strategy, Thyroid Disease, Transplant Infection Prophylaxis, Transplant Related Infections, Treatment of Airway Obstruction, Unknown Poisoning, Unstable Angina, Upper GI Bleeding Stress Prophylaxis, Vancomycin, Upper GI Bleeding Non-Variceal, Upper GI Bleeding Variceal, Use of Hematopoietic Growth Factors, Ventilator Weaning, Ventilator Weaning Protocol, Venous Thrombosis Diagnosis and Treatment, Venous Thromboembolism Prophylaxis, Ventricular Arrhythmia, Warfarin, Warfarin Dosing, and Wound Healing Strategies.

In yet another embodiment of the present invention, the patient care management system further comprises order writing software for providing knowledge-based recommendations and prescriptions for medication based upon the clinical data. In another embodiment of the present invention, the patient care management system further comprises knowledge-based vital sign/hemodynamic algorithms that prompt said intensivist to engage in early intervention.

Embodiments of the present invention provide methods for continuous expert critical care. Patients are monitored in a plurality of ICU's. Information from the patient monitoring is communicated to at least one command center over a first network. The information from the patient monitoring is received and analyzed at the command center over the first network; and guidance is provided from the command center to the plurality of ICU's to take actions regarding patient care. In another embodiment of the present invention, providing guidance from the command center further comprises an intensivist reviewing decision support algorithms that provide guidance for treating a plurality of critical care conditions. The algorithms are taken from the group consisting of algorithms for treating Acalculous Cholecystitis, Acute Pancreatitis Algorithm, Acute Renal Failure-Diagnosis, Acute Renal Failure-Management & Treatment, Adrenal Insufficiency, Agitation and Anxiety, Depression & Withdrawal, Aminoglycoside Dosing and Therapeutic Monitoring, an Amphotericin-B Treatment Guidelines, Analgesia, Antibiotic Classification & Costs, Antibiograms Algorithm, Antibiotic associated Colitis Algorithm, ARDS: Hemodynamic Management, ARDS: Steroid Use, ARDS: Ventilator Strategies, Asthma, Bleeding Patient, Bloodstream Infections, Blunt Cardiac Injury, Bradyarrhythmias, Brain Death, Bronchodilator Use in Ventilator Patients, Bronchoscopy & Thoracentesis Guidelines, Candiduria, Cardiogenic Shock, CardioPulmonary Resuscitation Guideline, Catheter Related Septicemia, a Catheter Replacement Strategies, Cervical Cord Injury, Congestive Heart Failure, COPD Exacerbation & Treatment, CXR (Indications), Dealing with Difficult patients and families, Diabetic Ketoacidosis, Dialysis, Diuretic Use, Drug Changes with Renal Dysfunction, Emergency Cardiac Pacing, Endocarditis Diagnosis and Treatment, Endocarditis Prophylaxis, End of Life Decisions, Endotracheal Tubes & Tracheotomy, Ethical Guidelines, Febrile Neutropenia, FUO, Fluid Resuscitation, Guillain-Barre Syndrome, Heparin, Heparin-Induced Thrombocytopenia, Hepatic Encephalopathy, Hepatic Failure, HIV+Patient Infections, Hypercalcemia Diagnosis and Treatment, Hyperglycemia Insulin Treatment, Hyperkalemia: Etiology & Treatment, Hypernatremia: Etiology & Treatment, Hypertensive Crisis, Hypokalemia: Etiology & Treatment, Hyponatremia: Etiology & Treatment, Hypothermia, Identification of Cervical Cord Injury, Implantable Cardio-defibrillator, Intra-Aortic Balloon Device, Intracerebral Hemorrhage, Latex Allergy, Magnesium Administration, Management of Hypotension, Inotropes, Management of Patients with Ascites, Empiric Meningitis, Meningitis, a Myasthenia Gravis, Myocardial Infarction, Myocardial Infarction with left bundle branch block, Necrotizing Soft Tissue Infections, Neuromuscular Blockers, Neuromuscular Complications of Critical Illness, Non-Infectious Causes of Fever, Non-Traumatic Coma, Noninvasive Modes of Ventilation, Nutritional Management, Obstetrical Complications, Oliguria, Open Fractures, Ophthalmic Infections, Organ Procurement Guidelines, PA Catheter Guideline and Troubleshooting, Pancreatitis, Penetrating Abdominal Injury, Penetrating Chest Injury, Penicillin Allergy, Permanent Pacemaker and Indications, Pneumonia Community Acquired, Pneumonia Hospital Acquired, Post-Op Bleeding, Post-Op Hypertension, Post-Op Management of Abdominal, Post-Op Management of Carotid, Post-Op Management of Open Heart, Post-Op Management of Thoracotomy, Post-Op Myocardial Ischemia, (Non-Cardiac Arrhythmias after Cardiac Surgery), Post-Op Power Weaning, Pressure Ulcers, Pulmonary Embolism Diagnosis, Pulmonary Embolism Treatment, Respiratory Isolation, Sedation, Seizure, Status Epilepticus, Stroke, Sub-Arachnoid Hemorrhage, Supra-Ventricular Tachyarrhythmia, Supra-Ventricular Tachycardia, Wide Complex QRS Tachycardia, Therapeutic Drug Monitoring, Thrombocytopenia, Thrombolytic Therapy, Transfusion Guidelines, Traumatic Brain Injury, Assessment of Sedation, Sedation, Septic Shock, Bolus Sliding Scale Midazolam, Short Term Sedation Process, Sinusitis, SIRS, Spinal Cord Injury, Steroid Replacement Strategy, Thyroid Disease, Transplant Infection Prophylaxis, Transplant Related Infections, Treatment of Airway Obstruction, Unknown Poisoning, Unstable Angina, Upper GI Bleeding Stress Prophylaxis, Vancomycin, Upper GI Bleeding Non-Variceal, Upper GI Bleeding Variceal, Use of Hematopoietic Growth Factors, Ventilator Weaning, Ventilator Weaning Protocol, Venous Thrombosis Diagnosis and Treatment, Venous Thromboembolism Prophylaxis, Ventricular Arrhythmia, Warfarin, Warfarin Dosing, and Wound Healing Strategies.

In another embodiment, a method further comprises a data server/ data warehouse storing and analyzing patient data from the at least one command center and providing analysis in results over a second network to the at least one command center.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1A illustrates the logical data structure for billing, insurance and demographic information.

FIG. 1B illustrates the logical data structure for billing, insurance and demographic information (cont).

FIG. 2A illustrates the command center logical data structure.

FIG. 2B illustrates the command center logical data structure (cont).

FIG. 3 illustrates the logical data structure for creating a medical history.

FIG. 4A illustrates the logical data structure for creating notes relating to patient treatment and diagnosis.

FIG. 4B illustrates the logical data structure for creating notes relating to patient treatment and diagnosis (cont).

FIG. 4C illustrates the logical data structure for creating notes relating to patient treatment and diagnosis (cont).

FIG. 5 illustrates the logical data structure for entry of medical orders.

FIG. 6A illustrates the logical data structure for patient care, laboratory testing and diagnostic imaging.

FIG. 6B illustrates the logical data structure for patient care, laboratory testing and diagnostic imaging (cont).

FIG. 7A illustrates the logical data structure for categories of information that are permitted to be presented to intensivists and other care givers by the system.

FIG. 8A illustrates the logical data structure for documenting patient vital signs.

FIG. 8B illustrates the logical data structure for documenting patient vital signs (cont).

FIG. 9 illustrates the distributed architecture of the present invention.

FIG. 10 illustrates the system architecture of the present invention.

FIG. 11 illustrates the decision support algorithm for diagnosis and treatment of pancreatitis.

FIG. 12 illustrates the vital signs data flow.

FIG. 13A illustrates capture and display of diagnostic imaging.

FIG. 13B illustrates establishing videoconferencing in the present invention.

FIG. 14 illustrates the physician resources order writing data interface of the present invention.

FIG. 15 illustrates the physician resources database data interface of the present invention.

FIG. 16 illustrates the automated coding and billing system integrated with the workflow and dataflow of the present invention.

FIG. 17 illustrates the order writing data flow of the present invention.

FIG. 18 illustrates the event log flow of the present invention.

FIG. 19 illustrates the smart alarms implementation of the present invention.

FIG. 20 illustrates the procedure note creation and line log for the present invention.

FIGS. 21A-B illustrate the acalculous cholecystitis decision support algorithm.

FIG. 22 illustrates the adrenal insufficiency decision support algorithm.

FIG. 23 illustrates the blunt cardiac injury decision support algorithm.

FIGS. 24A-B illustrate the candiduria decision support algorithm.

FIGS. 25A-B illustrate the cervical spine injury decision support algorithm.

FIGS. 26A-B illustrate the oliguria decision support algorithm.

FIGS. 26C-D illustrate the oliguria decision support algorithm (cont).

FIG. 26E illustrates the oliguria decision support algorithm (cont).

FIGS. 27A-B illustrate the open fractures decision support algorithm.

FIGS. 28A-B illustrate the pancreatitis decision support algorithm.

FIGS. 29A-B illustrate the penicillin allergy decision support algorithm.

FIGS. 30A-B illustrate the post-op hypertension decision support algorithm.

FIG. 31A illustrates the pulmonary embolism decision support algorithm.

FIG. 31B illustrates the pulmonary embolism decision support algorithm (cont).

FIG. 32 illustrates the seizure decision support algorithm.

FIGS. 33A-B illustrate the SVT determination decision support algorithm.

FIG. 33C illustrates the SVT unstable decision support algorithm.

FIGS. 34A-B illustrate the wide complex QRS Tachycardia decision support algorithm.

FIG. 34C illustrates the wide complex QRS Tachycardia decision support algorithm (cont).

FIG. 35A illustrates the assessment of sedation decision support algorithm.

FIG. 35B illustrates the assessment of sedation decision suppo