Population Health Management Analytics: What’s it all about?
Population health management analytics revolves around the collection and analysis of population health data sets from disparate sources across the healthcare ecosystem. The application of advanced healthcare analytics to the collected data sets of individual patients and larger populations can help healthcare organizations yield insights that drive healthcare outcomes and reduce the cost of care.
Though population health management has been around for a while, only recently has it gained serious attention from mainstream healthcare organizations. Fueled by the ongoing crisis, the healthcare landscape is transforming rapidly than one could have ever imagined. This transformation is characterized by a shift to newer healthcare delivery models, competition for treatment location, modality and convenience, and an unsustainable cost burden.
To tackle the challenges put forth by the COVID-19 crisis, healthcare institutions are now adopting new business models, enhancing patient care, and shifting their focus from episodic care to continuous healthcare improvements. Quantzig views this transformation as a journey to continuous healthcare improvement- one in which healthcare institutions implement processes enabled by the aggregation of data, advanced population health management analytics, and impactful workflows to assess, manage and empower the health of individuals and populations they serve.
Population health management analytics is now an indispensable part of every healthcare delivery model. Wonder why?
Operational Capabilities for Enhanced Population Health Management
Population Monitoring and Stratification
To control the spread of diseases and manage population health effectively, healthcare service providers must track and monitor the health of patients at a cohort-level as well as individual patient-level. Stratification of the patient population also plays a pivotal role in identifying patients that are at a higher risk when compared to the other patient population.
From a healthcare management perspective, cohorts must be identified based on the risk potential of individual patients. Also, categorizing patients based on this condition has always been the traditional approach adopted by several healthcare organizations. In contrast, population health management stratification focuses on categorizing patient based on demographics, health status, behavioral risk, and financial risk to classify patients into two groups- those who require continuous support from a healthcare service provider and the others that are healthy enough and require minimal support in the form of preventive care and education.
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Healthcare service providers must focus on catering to the needs of the patients, especially at times like these when the whole world has come to a standstill due to a pandemic outbreak. To tackle and control the crisis, healthcare institutions must not only focus on delivering appropriate, evidence-based care during patient visits, but they must also ensure that the care gaps are addressed on an ongoing basis. Apart from collaborating with patients, healthcare service providers must also find ways to help patients understand their care plans and the importance of complying with healthcare guidelines.
The main objective of every population health management strategy revolves around primary, value-based care. This is because it’s the primary healthcare service provider that helps maintain the continuity required to ensure patients receive appropriate preventive care on a timely basis. As such, team-based interventions form the crux of population health management strategies, and teams led by physicians, healthcare practitioners, and other healthcare professionals can manage more patients and address their needs on an ongoing basis than what can be offered by the traditional healthcare models.
The value provided by advanced population health data analytics plays a crucial role in driving better outcomes. Request a free demo to discover the true potential of data in transforming the healthcare industry.
Patient Outcome Analysis
Healthcare service providers now use innovative BI applications to gauge the fatality rate, disease progression patterns, and cater to the dynamic needs of patients. This implies data analytics and data dashboarding are bound to form an integral part of a population health management strategy. Also, tracking and monitoring of patient health data can help healthcare companies to leverage patient data to drive improvements in business processes. Apart from individual patient analysis, organizations must also ensure they measure costs and patient experience on a population-wide basis. This can help them gain holistic insights for quality reporting to payers and other external entities.
Based on our analysis, population health management analytics requires healthcare providers to develop new skills and set up new infrastructures for establishing a value-based healthcare model. Since automation turns out to be a crucial aspect of population health management, healthcare providers must adopt advanced analytics methodologies to track patient outcomes and gauge service efficiency on an ongoing basis, while enhancing financial and organizational stability.