Why physicians will need analytics to thrive within an ACO

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Physicians looking to get more involved with accountable care contracts will need to become comfortable with data analytics, particularly as they take on increasingly complex caseloads.

That appears inevitable, as more providers shift to value-based care contracts, says Cindy Friend, vice president of clinical population health solutions and transformations at Caradigm, an analytics and population health management vendor.

Heading into 2018, the risks are rising for providers, as insurers are offering more quality-related reimbursement contracts.

“Analytics can assess goals for patients and help standardize processes,” Friend says. “Analytics give insight into risk stratification to separate patient populations, risk scoring to identify patients likely to develop chronic conditions, quality improvement, financial improvement and care improvement.”

Provider organizations, and particularly the primary care physicians in them, need to regularly use applications that help them manage care for patients before their conditions become worse and they need more expensive, intensive care.

“How many doctors know how many of their diabetic patients have an A1C greater than 7 percent? Analytics also give insights into workflows for nurses, and getting patients in the office for a visit on a regular basis,” Friend says.

For ACOs to succeed, they will have to help doctors understand the complexity that will come with accountable care.

Also See: Institute to collect data and evidence to identify ACO best practices

Friend believes there is another major mindset among physicians that must change—they must see care continuing past the time they’re directly treating patients. For example, under bundled payment programs, a patient who undergoes a procedure might have a three-day hospital stay before discharge. But depending on the bundled payment model, a 90-day post-discharge period of monitoring the patient may be required.

“Some other conditions can actually be a higher cost than emergency medical events, and that often is not recognized,” Friend notes. “These patients have high readmission rates and transitions of care, and so do patients with HIV or AIDs, especially in urbanized regions. Typically, healthcare providers gear toward heart failure and diabetes for condition management, but providers must get a total view of their population. In a previous role at a large payer, our approach to population health analytics uncovered that osteoarthritis was our most costly condition over heart failure and diabetes."

Friend says providers must improve analytics capabilities in three areas:

• Risk stratification, to enable users to assign patients to care management for ongoing intervention.

• Clinical quality measures, to enable users to drill down to assess care quality at the practice, provider and patient level.

• Financial and utilization, which can provide real-time insights into utilization patterns across populations, care settings, networks and payers.

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