Studying population health has evolved over time and we now find ourselves in an era of big data and sophisticated analytics options. At PCIC, we leverage advanced techniques at our disposal with a focus on the metrics most important to improving patient care and modifiable factors.
Population health identifies trends in the overall health of a community and the impact of interventions on large groups. At PCIC, we work with population data to uncover trends in Super-users and other complex patients and recommend new approaches for improving outcomes.
Our efforts fall into two broad buckets – quantitative efforts and mixed methods approaches.
As part of the quantitative effort, we seek to map risk factors that are predictive of super-utilization and other complex health and behavioral problems, to contextualize populations of interest within their neighborhood and built environments, and to describe patients over time. We focus on modifiable factors at the patient, neighborhood and service delivery levels to build hypotheses to appropriately design and direct interventions.
As part of our mixed methods portfolio, we seek to understand quantitative data with directed and innovative qualitative inquiries.