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Clinical Trial
. 2005 Feb;11(2):93-102.

Using a claims data-based sentinel system to improve compliance with clinical guidelines: results of a randomized prospective study

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  • PMID: 15726857
Free article
Clinical Trial

Using a claims data-based sentinel system to improve compliance with clinical guidelines: results of a randomized prospective study

Jonathan C Javitt et al. Am J Manag Care. 2005 Feb.
Free article

Abstract

Objective: To demonstrate the potential effect of deploying a sentinel system that scans administrative claims information and clinical data to detect and mitigate errors in care and deviations from best medical practices.

Methods: Members (n = 39 462; age range, 12-64 years) of a midwestern managed care plan were randomly assigned to an intervention or a control group. The sentinel system was programmed with more than 1000 decision rules that were capable of generating clinical recommendations. Clinical recommendations triggered for subjects in the intervention group were relayed to treating physicians, and those for the control group were deferred to study end.

Results: Nine hundred eight clinical recommendations were issued to the intervention group. Among those in both groups who triggered recommendations, there were 19% fewer hospital admissions in the intervention group compared with the control group (P < .001). Charges among those whose recommendations were communicated were dollar 77.91 per member per month (pmpm) lower and paid claims were dollar 68.08 pmpm lower than among controls compared with the baseline values (P = .003 for both). Paid claims for the entire intervention group (with or without recommendations) were dollar 8.07 pmpm lower than those for the entire control group. In contrast, the intervention cost dollar 1.00 pmpm, suggesting an 8-fold return on investment.

Conclusion: Ongoing use of a sentinel system to prompt clinically actionable, patient-specific alerts generated from administratively derived clinical data was associated with a reduction in hospitalization, medical costs, and morbidity.

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