A state affiliate-sponsored web-based outcomes management program effectively collects outpatient cardiac rehabilitation data that are comparable to published controlled studies.
Supports feasibility of web-based cardiac rehab data collection; leaves open efficacy versus standard programs in randomized trials.
PURPOSE: The measurement of outpatient cardiac rehabilitation (OCR) outcomes is now considered common practice. Unfortunately, because of the costs involved in purchasing outcomes tracking software, many programs are not able to participate in pooled outcomes analysis and benchmarking. The purpose of this report is to describe the current OCR outcomes data in the state of Wisconsin using a web-based model for outcomes data collection, data pooling, and benchmarking. METHODS: Participating OCR programs collected individual patient outcomes according to protocols developed by the Wisconsin Society for Cardiovascular and Pulmonary Rehabilitation's Outcomes Committee. Programs analyzed their data quarterly and submitted the values to a database via an Internet web site. Aggregate outcomes data from 34 programs were collected over a 27-month period. RESULTS: Aggregate data representing 5235 OCR patients are presented. The mean age for the men was 64 +/- 5 years (N = 3612; 69% of the sample). The mean age for the women was 67 +/- 6 years (N = 1623; 31% of the sample). The completion rate for the group was 89% (95%CI, 86-91). The average number of OCR sessions per patient was 22 +/- 6 over 9 +/- 3 weeks. The clinical and behavioral outcomes for this sample ranged from a median value of 88% for the percentage of patients meeting the blood pressure goal (95%CI, 87-91) to less than 5% for the percentage of patients receiving formal psychosocial counseling (95%CI, 0). The major cardiovascular event rate was 0.17 per 10,000 patient-hours. CONCLUSION: This report describes the baseline OCR outcomes obtained via a state affiliate-sponsored outcomes management program. These data show that this model of OCR outcomes measurement, collection, and interprogram analysis produces data that are comparable with those of published, controlled studies. Determining baseline characteristics of OCR outcomes data will be important in the development of benchmarks and best practice guidelines.
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Mark Vitcenda (2003) studied this question.
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