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Establishing outcomes & evaluation metrics

Organization: Geisinger Health System

Country: USA

Forum: Accountable care

In 2005, the Geisinger Health System in Pennsylvania, which cares for more than 25,000 patients with diabetes, began transforming its approach to diabetes care.

Geisinger’s solution was to redesign care around national guidelines on key clinical metrics for diabetes management. Having compiled a list of best-practice guidelines, distilled from a variety of national sources, Geisinger found that nine of the underlying components – such as haemoglobin levels, immunizations, smoking status, and so on – could already be tracked through its EHR system. The nine criteria formed an “all-or-none bundle,” on which the new care regimen was to be based. An “all-or-none bundle” is a performance target that is met only when patients satisfy all of the individual criteria. It reflects “ideal” care, and fosters teamwork, as multiple individuals rely on one another to register a success. The nine criteria were “hard-wired” into clinical care, via various EHR-enabled tools that flag up requirements for completing the full bundle. Patients could monitor their own progress with the help of an online portal, and thereby manage their own care more actively.

Geisinger developed a process to monitor the performance levels of individual physicians and teams and compared the data against national benchmarks. This process helps identify gaps in care and motivates each team to improve its results. Up to 20 percent of a clinician’s income depends on improving all-or-none scores for the patients in his or her care.

The new approach has proved very effective. Scores on the diabetes bundle began rising impressively, and within three years this rise translated into dramatically improved end-state outcomes for patients, including reduced risk of retinopathy, stroke, and myocardial infarction. Two factors were critical to success: the national frameworks for best-practice diabetes care, which helped in defining evidence-based targets; and Geisinger’s own data systems and tools, which helped to evaluate patient-level data and integrate it speedily into care delivery. Geisinger is working to personalize the targets for individual patients; for example, by specifying target HbA1c readings to reflect each patient’s priorities and realistic goals.

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