An Informatics-based Chronic Disease Practice: Case Study of a 35-year Computer-based Longitudinal Record System

Abstract

The authors present the case study of a 35-year informatics-based single subspecialty practice for the management of patients with chronic thyroid disease. This extensive experience provides a paradigm for the organization of longitudinal medical information by integrating individual patient care with clinical research and education. The kernel of the process is a set of worksheets easily completed by the physician during the patient encounter. It is a structured medical record that has been computerized since 1972, enabling analysis of different groups of patients to answer questions about chronic conditions and the effects of therapeutic interventions. The recording process and resulting studies serve as an important vehicle for medical education about the nuances of clinical practice. The authors suggest ways in which computerized medical records can become an integral part of medical practice, rather than a luxury or novelty.

Future Directions in Evaluation Research: People, Organizational, and Social Issues

“…Researchers have addressed work flow and routines [14,[43][44][45][46][47][48][49][50][51][52]; clinicians' level of expertise [48]; values and professional norms [53][54][55]; institutional setting, history, and structure [37,50,56]; communication patterns [37-39, 52, 55]; organizational culture, status relationships, control relationships, division of labor, work roles, and professional responsibility [25,49,56,57]; cognitive processes [58]; congruence with existing organizational business models and strategic partners [59]; compatibility with clinical-patient encounter and consultation patterns [50,52,60]; and the extent to which models embodied in a system are shared by its users [3,14,55,61,62]. Authors have also addressed (in various combinations) fit between information technology and how individuals define their work, user characteristics and preferences (e.g., information needs], the clinical operating model under which a system is used, and the organization into which it is introduced [37,43,55,[63][64][65][66][67][68]. Others have...…”

“…Telehealth and telemedicine then are examples of how new technologies, like some older applications, raise new issues related to different meanings information and communication technologies have for different users and how people make sense of them [50,55,61,66,75,85,103,143,200,217]. Studies of imaging technologies, like ultrasonography [151], CT scanning [143][144][145][146], or clinical imaging systems [218,219] point to the need for newer studies to understand contemporary systems [131].…”

Toward rapid learning in cancer treatment selection: An analytical engine for practice-based clinical data

“…Rapid learning systems represent a modern paradigm for precision clinical practice, in which knowledge mined from electronic medical records is seamlessly integrated into the clinical workflow of physicians [10–13]. A functional RLS therefore requires several components, including clinical databases supplied with EHR data, information pipelines that facilitate rapid transformation and filtration of clinical data to identify cohorts of interest, analytic platforms, and clinical decision support (CDS) utilities that provide physicians with relevant clinical insights at point of care (Figure 1).…”

Implementing Single Source: The STARBRITE Proof-of-Concept Study

“…Technological advances in the last 20 years have the potential to strengthen links between patient healthcare and clinical research. Many authors have endorsed secondary uses of healthcare data, including for research purposes; [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18] however, this potential remains largely untapped. Data that could benefit patients, physicians, investigators, regulators, and the biopharmaceutical industry remain sequestered in disparate databases, stored as narrative text, or confined to paper records.…”

“…Large-scale direct use of healthcare data for research, although advocated by many, [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18] has thus far eluded researchers. 9 Successful implementations described in the literature 6,26 cite workflow incompatibility, additional research data requirements, and regulatory differences as challenges.…”