How Population Health Analytics Can Enhance Patient Care & Cost Utilization
September 12, 2023
Consider all the healthcare data at your disposal. It lies in patient EHRs and EMRs. It lies in claims records. It lies in hospitals, laboratories, private practices, and other patient touchpoints.
All that data can give a holistic picture not only of individuals within your healthcare ecosystem, but also the population as a whole. This is especially important for payers and providers who want to reduce costs and improve patient care and outcomes.
Unfortunately, too many healthcare organizations lack interoperability-driven technological solutions to integrate this data and achieve deep, accurate population analytics. Most use legacy tools, which increase fragmentation and cannot support improved care coordination.
Central to effective population health analytics, then, are the technology and platforms underlying patient interactions. Read on to see why modern, interoperable systems are key to population analytics, and how we helped a provider upgrade their system to improve patient care and cost utilization
How to overcome technological, data, and interoperability challenges to population health analytics
A leading provider of healthcare technologies sought to build an end-to-end solution for value-based care that would give patients real-time visibility into quality and cost performance. This digital platform to connect various discrete healthcare data into a singular and holistic patient record. This client—a value-based, precision medicine company leading the industry in real-world data, analytics, and AI capabilities for specialty care organizations—partnered with us to build a holistic population health analytics platform connecting to clinical and billing systems, as well as CMS claims and other sources, and bring those data into a holistic view for the patient. We helped the client develop a cloud-based data exchange hub with automated ETL processes to onboard new hospitals and providers faster without sacrificing security and compliance standards (e.g. HIPAA). The solution consisted of two parts:- ETLs for clinical and financial data from disparate sources
- A new provider-facing web application with predefined and canned reports and self-service data analytics with KPI-based, real-time notifications
Benefits of using population analytics to assess performance
Population health analytics aggregates individual healthcare data to bring into focus population-level health concerns, identifying ways to allocate resources to overcome those problems. As such, those studying population health management need ongoing access to data, which they can then analyze to derive meaningful insights. These data must be standardized and accurate, regardless of original source:- Billing data
- Clinical data
- Patient-generated health data (PGHD)
- Prescription and medication adherence data
- Patient sociodemographic information (including socioeconomic data)
- Social determinants of health (SDOH)
Improved resource allocation & lower costs
When providers have detailed, population-level data on interventions, outcomes, and care gaps, they can engage in more efficient and effective outreach. This enables better forecasting of expected healthcare utilization, enabling payers and providers to deploy resources to where they may have the greatest impact. This can improve overall performance and reduce costs.Predicting patient risk
By stratifying population health data by risk profiles, payers and providers can better guide their engagements with at-risk patients. This includes drilling into specific details to identify patients within the population who need care most, especially those at risk of chronic conditions, substance abuse, or future hospitalizations. While adopting predictive analytics may not yield immediate results, failure to adopt it could result in payers losing the race to competitors.Reducing access barriers based on SDOH
Social determinants of health (SDOH) such as lack of transportation, poverty, domestic violence, and food insecurity can all lead to poor health outcomes. Population health analytics can take these factors into account, enabling payers and providers to recognize and overcome barriers to care.Performance benchmarking
Population health analytics can also demonstrate how outcomes among segmented member populations measure against national and regional benchmarks. This data can be crucial in measuring disease prevalence and risk profiles. Health systems use this data to not only better negotiate value-based programs, but also improve the patient experience.Final thoughts on population analytics technology
Often the obstacle standing between you and your population health analysis goals is the technology at your disposal. By understanding the challenges of legacy systems and adopting alternatives, you can contribute not only to your own bottom line, but make tangible improvements to the wellbeing of your population. To do so, you need a trusted technology partner who can guide you through the process, identify areas of breakdown, and propose solutions that minimize time to value. 3Pillar Global has helped a number of healthcare clients through this journey, and we can do the same for you. Learn more about how 3Pillar Global can support your healthcare technology transformation here.About the Author
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