Building a value-based primary care network for population health.

The move to value-based care has many primary care physicians worried about the future of their practices. Six strategies developed by a clinic in Northeastern Oklahoma can help: Determine your "why." Let leadership drive. Educate staff, and communicate the transformation plan. Find alignments. Get patients engaged. Scale the program with technology.

9 steps to effective population health management.

A focus on population health management is a necessary ingredient for success under value-based payment models. As part of that effort, nine ways to embrace technology can help healthcare organizations improve population health, enhance the patient experience, and reduce costs: Use predictive analytics for risk stratification. Combine predictive modeling with algorithms for financial risk management. Use population registries to identify care gaps. Use automated messaging for patient outreach. Engage patients with automated alerts and educational campaigns. Automate care management tasks. Build programs and organize clinicians into care teams. Apply new technologies effectively. Use analytics to measure performance of organizations and providers.

Population health approach for diabetic patients with poor A1C control.

BACKGROUND: Diabetes is frequently monitored as part of quality programs and initiatives. The glycated hemoglobin (A1C) test and corresponding values are often used as quality metrics, and patients with values of 9.0% or above (9+) tend to utilize intensive resources. However, this strategy may be missing more profound opportunities to improve quality. OBJECTIVES: To analyze A1C outcomes in 2 ways: (1) year over year for patients identified as diabetic and (2) from test to test. METHODS: This study was conducted using data on more than 23,000 patients identified as having diabetes and included A1C laboratory results extracted from electronic medical records. RESULTS: The percentage of patients with poorly controlled diabetes (9+) is increasing annually, but there is sizable turnover within the population- meaning that new uncontrolled patients replace those whose outcomes improve. More than half (57.5%) of patients have their first 9+ score on their first test. And for those with a prior 9+ result, only 16.8% have 3 consecutive 9+ scores after their initial 9+ test. For all patients, the longer the interval between tests, the greater the probability that the next test result will be 9+. CONCLUSION: Instead of focusing resources only on the highly dynamic and relatively small subpopulation of patients with 9+ scores, a better option may be ensuring that all patients get regular testing according to appropriate protocols. This total population-based approach would engage all diabetic patients inside and outside practice walls to optimize provider ability to impact health outcomes.