Automating Population Health Data Initiatives
Population Health Success Begins with the Data
Population health is grounded in the idea that healthcare providers should work together to keep patients healthy and avoid hospitalizations. Hospitals, health systems and provider organizations are putting data to work to improve patient care and lower expenses with a variety of data-driven initiatives. One of the primary considerations in developing population health programs is organizing and sorting through complex stores of information sources and the volume of data involved. Automation is a clinical, technical and financial ally in developing robust population health initiatives that result in positive outcomes with lower costs.
Population Health initiatives begin with gathering and measuring demographic, clinical, and financial information gleaned from a variety of sources including academic insights, actuarial costs and risk stratification, government statistics, public health records, hospital and health system information, consumer health data, provider medical records, payer cost models, pharmacy and lab data.
There are many variables to consider. While some elements have shared attributes, each has its own context, value and impact. One miscalculation unbalances the accuracy of care, cost and anticipated outcomes.
Population Health Challenges Resolved by Automation
Cost: Automation completes even the most complicated data exercises in a fraction of the time it takes for accomplished teams of data professionals to complete.
Consistency: Automation technology adheres to the step-by-step processes laid out for it and does not skip or forget edits or entries. Results are systematically generated in an exacting manner.
Complexity: Algorithms involving numerous individual measurements are rigorously run, reducing the need for large, diverse sets of data to be processed in stages. Complex processes are completed in predictable streamlined fashion, and initiatives can be developed based on accurate, data-driven decisions.
Flexibility: Accounting for the numerous stakeholders involved in these projects is important; the same set of data may need to be analyzed from several different perspectives. Automation enables economic, high speed interoperability within and between data sources and organizations.
Time: Built on historic, real-time and forecasted data; outcomes and trends are perpetually refined based on results, new data and changes in treatment standards, costs or other variables. Automation operates at a digital processing pace 24/7/365, shrinking timeframes while enabling adjustments for immediate insight without delays.
Accuracy: Automation fortifies population health with precise data. Exceptions receive focused attention and are re-run for quick, comprehensive results.
The Top Five Automation Applications for Population Health Initiatives
- Data Extraction
- Risk Management
- Reporting
- Integration
- Communications
Successful population health programs are inherently data dependent.Automation is a clinical, financial and technical ally for patient, medical, administrative, provider organization and payer stakeholders, providing a pivotal resource to transform data from a costly, intimidating burden to a valuable, engaging asset. Patients, providers, payers and other stakeholders benefit from impactful and economic ways to advance higher levels of patient care at a lower cost.