As part of a multi-year collaboration between Advocates for Community Health (ACH) and UnitedHealthcare, Mariposa Community Health Center (MCHC) is one of five community health centers receiving $500,000 each to address complex problems affecting the overall wellness of the underserved communities where they provide care. We recently had a chance to talk to MCHC Lead Data Analyst Greg Starr to learn more about his health center and winning proposal to improve patient outcomes.

Why is Mariposa Health Center’s work in the community you serve so important?

Since its founding in 1980, Mariposa Community Health Center has become the largest and most comprehensive provider of medical, dental, disease prevention and health promotion services in SE Arizona. Locations in Nogales, Rio Rico, Tubac, and Patagonia offer a “one stop wellness” model of integrated care that recognizes and responds to the whole person from physical to social to psychological needs. Services include adult/internal medicine, pediatrics, obstetrics and gynecology, general surgery, dentistry, behavioral health and two full-service pharmacies. More than 300 dedicated staff members support Mariposa and our mission of service in the community.

Nogales, a city of almost 20,000 people, sits on the US-Mexican border. About 95% of the city identifies as Hispanic or Latino. With almost one third of the population living below the poverty line, access to affordable quality healthcare is crucial for our community. MCHC plays a vital role by providing a patient-centered health care home that ensures access to culturally appropriate primary care, responding to community and patient needs, and encouraging individual responsibility for one’s health.

Please briefly describe your winning proposal. How will the use of this new type of technology help bridge the health care gap in your community?

Medical Records and Practice Management Systems store extensive patient data. They are built to record and document patient points of contact. From making the appointment, through the visit, labs, pharmacy, and insurance/billing. However, these data and any subsequent reporting are always retrospective. To improve patient care, a predictive modeling approach will enable us to maximize data utility and benefit. We will also be able to make proactive and predictive decisions based on data science.

As part of our winning proposal, Mariposa will implement machine learning and artificial intelligence (AI) system from Austin based ClosedLoop AI to improve patient care. The application of machine learning and AI allows for decision-making not based on best guess or rule-of-thumb, but on the application of data that can point to future probable outcomes. All data in the organization, from clinical/claims/practice management data, as well as publicly available data sources such as Social Determinants of Health, Geographic Information System Mapping (GIS), and other public demographic sources can be utilized to maximize the effectiveness and efficiency of the organization. Leveraging data in this manner will allow providers to make more informed clinical decisions, empower executive management to make data-based decisions on value-based contracts, achieve clinical quality goals, address health equity and bias, and improve patient outcomes.

If you had a magic wand, what would a successful first year look like? What are some of the metrics that will be taken into consideration?

A first-year success will be to get data feeds into the ClosedLoop system and some initial data models training on our data. Project success will be measured by comparing current metrics with post-implementation metrics. For example, did hospital re-admissions and emergency department utilization go down? Were there significant increases in the number of gap closures in value-based contracts? Did the number of patients who are in control of their diabetes or hypertension increase significantly? We hope to identify and implement measures to address patients requiring proactive care and engagement. Lastly, a successful first year would include improvement of clinical performance on measures within the annual UDS reporting, HQM Measures, and PCMH.

You can learn more about MCHS and its impactful work at

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