Using Data to Grow your Direct Primary Care (DPC) Practice
Many DPC practices are quickly realizing the value of using data analytics in their practices. Analytics can be used for improving operational efficiencies, enhancing population health practices, tracking cost savings, and creating compelling stories to share with current and prospective patients and employers. This in turn contributes to continued growth, improved quality of care, and greater acceptance of DPC.
KPI Ninja is sharing a framework which is designed to measure and advance DPC capabilities. There are four major stages in this:
- Data Integrations
- Tracking Insights
- Making Data Actionable
- Predictive Analytics
Stage 1: Data Integrations
Data integration is the foundation of analytics. DPC providers know what high quality, low-cost healthcare looks like. They deliver it every day. Without integration, data is scattered among disparate sources, making it difficult to decipher information or draw applicable conclusions.
The core integrations to consider for your DPC practice include:
- Electronic medical records (EMRs)
- DPC membership billing platforms
- Virtual communication tools
- Claims data (if supporting self-insured employers)
Sources of advanced integrations to consider include:
- Health Information Exchanges (HIEs)
- Patient satisfaction surveys
- Wearable devices
- Patient engagement platforms
- Appointment scheduling applications
These tools can help you paint a more comprehensive picture about your practice and providers as well as the patients you serve, which in turn better positions you as a resource for employers.
Stage 2: Tracking Insights
Utilizing dashboards and scorecards in creative ways helps DPC organizations draw conclusions about operational, clinical, and financial performance. Creating data-driven stories helps clinics make better internal decisions, yet also drive conversations with employers. By incorporating solutions that seamlessly share data with each other, tracking data is fluid. Allowing easy insight for performance improvement, clinics can more effectively compete in the healthcare market.
Stage 3: Making Data Actionable
For DPC providers to become data-driven organizations, it’s important to make data actionable. For example, data could reveal that a diabetic patient has been without a physical visit for the last six months or show a gap in the patient’s prescription drug compliance. Leveraging this information empowers you to make more informed decisions about care, which in turn makes your practice and the DPC model more appealing to employer groups who are constantly looking for ways to tackle chronic diseases in the workforce.
Stage 4: Using Predictive Analytics
Beyond descriptive analytics, DPC organizations can investigate advanced analytics that provide deep insights into concurrent and predictive population health trends. Most models analyze a population by a subset of diagnosis codes. Consider looking into models that evaluate the population at a patient-level through the clustering of morbidity, as they can be better indicators of cost and healthcare resources. Using markers and models can also help you support the diverse needs of employers through population health monitoring, clinical screenings for care management activities, profiling of groups and providers to compare performance and a variety of financial applications to name a few.
About KPI Ninja
KPI Ninja is a data analytics company that helps healthcare organizations accelerate their quality, safety, and financial goals with a unique combination of software and service. We are differentiated by our signature mix of technology, performance management consulting and healthcare expertise. We don’t merely offer software solutions but work shoulder to shoulder with clients to help them draw on the power of analytics and continuous improvement methodologies to become more efficient. In harmony with our data-centered ethos, we truly believe that our success is strongly co-related with yours.