The Triangle Model for evaluating the effect of health information technology on healthcare quality and safety
- 1Department of Pediatrics, Weill Cornell Medical College, New York, New York, USA
- 2Department of Public Health, Weill Cornell Medical College, New York, New York, USA
- 3Health Information Technology Evaluation Collaborative (HITEC), New York, New York, USA
- 4Department of Medicine, Weill Cornell Medical College, New York, New York, USA
- 5New York-Presbyterian Hospital, New York, New York, USA
- Correspondence to Dr Jessica S Ancker, Weill Cornell Medical College, 402 E 67th St, LA-251, New York, NY 10065, USA; jsa7002{at}med.cornell.edu
- Received 20 May 2011
- Accepted 26 July 2011
- Published Online First 20 August 2011
Abstract
With the proliferation of relatively mature health information technology (IT) systems with large numbers of users, it becomes increasingly important to evaluate the effect of these systems on the quality and safety of healthcare. Previous research on the effectiveness of health IT has had mixed results, which may be in part attributable to the evaluation frameworks used. The authors propose a model for evaluation, the Triangle Model, developed for designing studies of quality and safety outcomes of health IT. This model identifies structure-level predictors, including characteristics of: (1) the technology itself; (2) the provider using the technology; (3) the organizational setting; and (4) the patient population. In addition, the model outlines process predictors, including (1) usage of the technology, (2) organizational support for and customization of the technology, and (3) organizational policies and procedures about quality and safety. The Triangle Model specifies the variables to be measured, but is flexible enough to accommodate both qualitative and quantitative approaches to capturing them. The authors illustrate this model, which integrates perspectives from both health services research and biomedical informatics, with examples from evaluations of electronic prescribing, but it is also applicable to a variety of types of health IT systems.
- Evaluation studies
- research design
- quality of healthcare
- medical errors
- medical informatics applications
- cognitive study (including experiments emphasizing verbal protocol analysis and usability)
- classical experimental and quasi-experimental study methods (lab and field)
- uncertain reasoning and decision theory
- delivering health information and knowledge to the public
- human-computer interaction and human-centered computing
- quality of care
- measuring/improving patient safety and reducing medical errors
Footnotes
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Funding The investigators are supported by the New York State Department of Health (NYS contract number C023699).
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Competing interests None.
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Provenance and peer review Not commissioned; externally peer reviewed.









