Difference between revisions of "Problem-Oriented Medical Information System (PROMIS)"

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(Inherent Issues with Computer-Based POMR methodolgy?)
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An example of this tension occurs in the computer-based POMR where data must be stored in discrete and unambiguous terms. This results in a loss of information: the rich “analog” data of life is represented in the computer with discrete “digital” data; and complex inter-related body functions are organized into discrete “silos” of information. PKC again partly addresses this issue by recognizing the necessity of free text, but even this cannot replace the richness of information stored in an image, such as in a CT-scan or an MRI or a high-quality color photograph of a wound.   
 
An example of this tension occurs in the computer-based POMR where data must be stored in discrete and unambiguous terms. This results in a loss of information: the rich “analog” data of life is represented in the computer with discrete “digital” data; and complex inter-related body functions are organized into discrete “silos” of information. PKC again partly addresses this issue by recognizing the necessity of free text, but even this cannot replace the richness of information stored in an image, such as in a CT-scan or an MRI or a high-quality color photograph of a wound.   
  
In addition, the structuring of data in the computer in a hierarchical fashion, as described by PKC, further abstracts and artificially isolates medical data. The elements in one hierarchical list may interact with those on another list, but the list structure itself imposed by the computer model may obscure such interdependent relationships. As a result the computer-based POMR is optimized for Boolean searches and hierarchical analysis, but such constructs are poor models of living systems.[[User:MikeField|MikeField]] 21:53, 16 January 2010 (CST)
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In addition, the structuring of data in the computer in a hierarchical fashion, as described by PKC, further abstracts and artificially isolates medical data. The elements in one hierarchical list may interact with those on another list, but the list structure itself imposed by the computer model may obscure such interdependent relationships. As a result the computer-based POMR is optimized for Boolean searches and hierarchical analysis, but such constructs are arguably poor models of living systems.[[User:MikeField|MikeField]] 21:53, 16 January 2010 (CST)
  
 
==References==
 
==References==

Revision as of 04:03, 17 January 2010

From 1969 to 1982, Dr. Lawrence L. Weed worked at the University of Vermont to computerize the problem-oriented medical record (POMR). He recognized that the mind of the physician could not effectively process the large amount of information received, and this could interfere with the care of the patient. He began to organize the data temporarily to make them more available to the physician. This pairing of data led to the development of a commercial product, Problem - Knowledge Couplers (PKC - [1]).

PROMIS was one of the first electronic medical records (EMR) to implement support from other parts of the medical community (e.g., pharmacy and nursing). A patient’s profile could be accessed at any terminal with little delay in the transfer of the information, making healthcare more efficient. [Schultz 1988]

The system consisted of several dozen computer terminals which fed into the central memory unit. A terminal was wheeled to a patient's bedside where the patient with the help of a nurse would enter his or her medical history via touch-sensitive screen. The physican would then review the entries and formulated the problems.

The introduction of the problem-oriented medical record (POMR) by Lawrence Weed (1969) influenced medical thinking about both manual and automated medical records. By suggesting that the primary organization of the medical record should be by the medical problem and all diagnostic and therapeutic plans should be linked to a specific problem, Weed was one of the people who recognize the importance of an internal structure of a medical record either stored on paper or in a computer. PROMIS was developed at the University of Vermont in 1976, by Jan Schultz and Dr. Larry Weed. Apparently, the developers of Carnegie Mellon University's ZOG system were so impressed with PROMIS that it reinspired them to return to their own work.PROMIS was a hypertext system specially designed for maintaining health care records.

An interactive, touch screen system, PROMIS allowed users to access a medical record within a large body of medical knowledge. At its peak, the PROMIS system had over 60,000 frames of knowledge. PROMIS was also known for its fast responsiveness, especially for its time.


Inherent Issues with Computer-Based POMR methodology?

PKC’s insightful 1998 white paper on Problem Oriented Medical Records (POMR) illuminates the strengths and weaknesses of the methodology.[PKC paper] Classically, POMR information is organized under four sections: Screening Data, Problem List, Initial Plans, and Progress Notes. Problems are further broken into health maintenance (e.g., lifestyle factors related to smoking, diet, and exercise), active medical problems and inactive medical problems. The challenge is to view the problem lists holistically rather than discretely. Plans for one problem may preclude action on another: priorities must be set and interactions considered. PKC partly addresses this by recommending a list of “assets” (e.g., positive mental, emotional, and physical attributes) be used to help make a balanced judgment of the patient’s potential response to the presumed illness or its suggested treatment. But the POMR model remains oriented around discrete information that is not well integrated in a holistic fashion.

An example of this tension occurs in the computer-based POMR where data must be stored in discrete and unambiguous terms. This results in a loss of information: the rich “analog” data of life is represented in the computer with discrete “digital” data; and complex inter-related body functions are organized into discrete “silos” of information. PKC again partly addresses this issue by recognizing the necessity of free text, but even this cannot replace the richness of information stored in an image, such as in a CT-scan or an MRI or a high-quality color photograph of a wound.

In addition, the structuring of data in the computer in a hierarchical fashion, as described by PKC, further abstracts and artificially isolates medical data. The elements in one hierarchical list may interact with those on another list, but the list structure itself imposed by the computer model may obscure such interdependent relationships. As a result the computer-based POMR is optimized for Boolean searches and hierarchical analysis, but such constructs are arguably poor models of living systems.MikeField 21:53, 16 January 2010 (CST)

References

Gordon C. A Medical Revolution That Could...: The Work of the PROMIS Laboratory and Lawrence L. Weed, M.D. US Department of Health, Education Welfare National Institute of Education. 1978 http://eric.ed.gov/ERICDocs/data/ericdocs2sql/content_storage_01/0000019b/80/3f/1a/15.pdf

Schultz J. A History of the PROMIS Technology: An effective Human Interface. A History of Personal Workstations. 1988. New York. PP. 44-46. Available from: http://www.campwoodsw.com/mentorwizard/


A History of the PROMIS Technology: An Effective Human Interface (PDF file) Retrieved from "http://en.wikipedia.org/wiki/Problem-Oriented_Medical_Information_System"