For a peek into the future of population health management, a visit to Stanford Coordinated Care, a new clinic in northern California that is part of Stanford Health System, is in order. Staffed with three part-time physicians, one nurse and a handful of medical assistants, the clinic targets a select group of patients that health care cost accountants might just as soon send elsewhere. "We are recruiting the top 10 percent of the riskiest patients," says the clinic's co-director, Ann Lindsay, M.D. "Our patients usually have several conditions."
The clinic is paid on a specially negotiated capitated basis with Stanford's own health plan and negotiations with other commercial payers to treat their at-risk patients are under way, Lindsay says. To manage these patients - who typically have such chronic conditions as diabetes, asthma and hypertension - the clinic relies on a mini-arsenal of I.T. including an electronic health record, a clinical data warehouse and an analytics engine. "We offer an intensive model of caring for complex chronic conditions," says Lindsay, describing a model which sometimes includes house visits by physicians and other staff.
Its payer contract calls for shared savings if the clinic can beat anticipated outlays for the patient groups, not an easy task given the typically higher rate of hospitalizations, ED visits and 30-day readmissions for this group. But Lindsay is convinced that the model will work - and notes that already its ED utilization rate has dropped within the clinic's first year of operation. "The difference between us and fee-for-service is that we manage a panel of patients and pay attention whether or not they show up. In the traditional model, you only pay attention when they show up."
Lindsay's summation of the clinic's operating principles captures the essence of population health management. As the industry shifts to outcomes-based payment models, providers still must deliver care patient by patient, but they must also monitor those patients most likely to throw budgets off course. That requires a population-based approach, in which providers track patients by either clinical risk, financial risk, or some combination of the two. Upholding the idea requires insuring that preventive screenings are complete, that patients with certain conditions follow care guidelines and treatment plans, and that care is coordinated among different settings. The I.T. requirements are steep, but manageable, experts say. An EHR, a patient registry, analytics capacity and rudimentary data exchange are prerequisites. But managing patient populations effectively also requires new staff roles. The challenges are many, from spanning I.T. interfaces to just good old-fashioned resistance to change by some physicians and, equally important, by patients themselves.
The fundamental building block of population health management is an EHR. Digitizing clinical data sets the stage for subsequent number crunching of patient and physician performance around preventive measures and treatment plans, but EHR systems usually contain alert mechanisms to let providers know if the patient before them lacks a recommended screening or care intervention.
Gary Baldwin’s feature story in the August issue of Health Data Management examines how providers are using a mix of electronic health records, data analytics and data exchange technologies to manage patients by risk categories.
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