Healthcare Data Analytics – Unlocking the Potential of Big Data in Population Health Management

Implications from fragmentation of the healthcare industry are most obvious in this chronic disease age.  Affordable Care Organizations have no choice but traverse a rough terrain of unconnected, disparate data to unravel unidentified facts and relationships if they want to achieve true value-based care.

Big Data Offers Boundaryless Availability of Data Synthesis to Healthcare

Population health has always been a priority to healthcare practitioners and providers since healthcare was perceived as a discipline. However, the concept of managing population health through the systematic definition of care outcome among groups is a rather recent move propelled by the Affordable Care Act.

The mechanics of the healthcare industry are much more dynamic than any other industry existent today. Looking at the healthcare industry as a value chain, the primary entity, being the patient has to traverse a whole maze that comprises a hospital or a clinical setting, an insurance provider, a primary care provider including the specialists, the pharmacy, and the urgent care center.

As patient data is fed into the healthcare ecosystem using disparate algorithms and formats at each healthcare setting through Electronic Health Records (EHRs), data analysts have reason to complain about the incomplete nature of the patient profile.

Moreover, inability to form connections between care providers while ensuring the availability of patient data outside of the hospital for comprehensive care management, is another important perspective that needs to be given due diligence. Clinical and claims data despite being available in disparate formats and fragmented storage, must be available for making meaningful and analytical decisions. The role of Big Data in Population Health Management starts at this juncture, where mighty, measurable goals are set to guarantee accuracy and efficiency in data synthesis of disparate data that will far outdo benchmarks in care outcomes, while leading the way to bottom line benefits.

Big Data Analytics opens up doors of opportunity for healthcare providers to aggregate, filter and make sense of data silos that were otherwise redundant in care settings. However, it will take more than just a set of algorithms to achieve usable patient data and population-wide outcomes.

For healthcare providers who wish to sustain their success in the current healthcare scenario, focus on patient data amalgamation should be of paramount importance. True success in the present scenario in terms of Accountable Care will only be available to providers who can tap the potential of Big Data to merge complete patient profiles with secondary data sources. Attempts to harness Big Data in the Population Health realm will reveal data relationships for raising the quality of population health and in the bargain achieve never before values for typical business variables including cost, efficiency, outcomes, sustainability and patient-centeredness.

The Present Use of Big Data in Healthcare is Disparate and Exploratory

Inefficient utilization of resources, lack of transparency and absence of laxation in legislative guidelines restrict the provision of quality care. However, care providers and forward-thinking organizations operating in the Population Health Management space are making use of Population Health Data to achieve measurable goals in the form of financial benefits and quality of care:

  • Existing health management tools help healthcare organizations perform better by showing them where they stand against similar players on the regional and national levels. By investing in Comparative Data Analytics, organizations will be motivated to establish more ambitious goals in terms of performance through real-time insights about similar organizations.
  • Many healthcare leaders are also investing in machine learning, cognitive computing and natural language processing to derive insights from Big Data pertaining to Population Health. Analysts in the field trust that the need for deriving meaningful use from Big Data is so intense that it can single-handedly revolutionize complete processes, teams and technical capability.
  • Big Data is also utilized for Data Mining and Predictive Modeling, with the goal of achieving “Patient Centered Datasets” as the foundation for effective Population Health Management. Recommendations from this analytical approach is likely to guide the providers towards providing the most viable intervention, leading to better outcomes on the path to value-based care.

Healthcare analysts focusing on different innovative provider and payer settings are in the process of aggressively traversing terabytes of data pertaining to patients and the paths they traverse in the interconnected process of healthcare delivery (Big Data Volume). Healthcare data has particularly witnessed an upsurge after the deep penetration of Health IT (Big Data Velocity).

Silos of data with patient information in sometimes incommunicable formats (Big Data Variety) are undergoing the next stage of evolution. However, the high credibility attached to healthcare data (Big Data Veracity) will singularly ensure that the resultant painstaking analysis (Predictive Analytics, Comparative Analytics, Data Visualization, Reporting and much more) will safely deliver healthcare towards the sought after medley of quality, outcomes and value-based care. 

In Future, Value Based Care Will Drastically Impact Provider Performance and Patient Outcomes

The Gartner report 2015 uncovers that the most important investment that an organization will make in future is in terms of information assets. Success will come only after a complete overhaul of the analytics infrastructure along with a Data Warehouse Approach.

In order to realize benefits in terms of reduced costs and increased efficiency, healthcare players are moving to the cloud, banking largely on Software as a Service (SaaS) applications for transparent data sharing and aggregation. As this process matures across payers, providers, networks and the public, high-quality insights will be available from huge databases of state wise patient and claims information.

The future holds great promise in this regard, where Big Data Analytics will help identify workforce performance issues, leading to the establishment of the best care provider teams and the best payment system.

Moving forward, healthcare organizations are bound to embrace Big Data analytics for the processing power, which in turn will enable intelligent decision making and revolutionary optimization of processes through predictive and insightful information discovery.