The US healthcare system serves as an example case in this chapter for leveraging analytics for financial insights. The presented financial metrics and performance measures will be a vital part in the holistic framework of data-driven analytics and business intelligence in the context of population health management, an approach that aims to reduce the cost of healthcare while simultaneously holding the possibility of meaningfully improving quality and experience of care for defined patient populations. The here described methodology of population health analytics is in turn adaptable to other countries’ healthcare systems and data governance. Healthcare organizations will be gaining significant returns on investments on population health analytics solutions when they want to succeed in an increasingly value-driven reimbursement system where regulations and payment incentives are created to move away from the current fee-for-service models towards outcomes-based accountable care. As a result, healthcare organizations are incentivized and penalized financially around health outcomes which means that it is paramount to see improvements in care quality and to lower spending for all stakeholders across the care continuum. Hence, healthcare organizations have a lot to gain in understanding their own financial performance in terms of costs, utilization, and compensations, their patient populations in terms of health outcomes, and their palette of intervention, outreach, and engagement opportunities. It is evident that the integration of population health management solutions with the data warehouse of health providers will increase demand for a new job type, the healthcare data scientist. This chapter will provide an introduction to the reader to learn more about the domain-specific skillset of a healthcare financial data scientist. The general skillset of a data scientist is a prerequisite, and very interesting more advanced topics can be found throughout this book. This chapter (1) starts with an overview of financing healthcare delivery, (2) uses well-documented administrative healthcare claims as sample data source, (3) introduces medical coding classification systems and related sources, (4) provides methods how to create selected financial and clinical key performance indicators (KPIs) and drill downs, and (5) provides a concept to visualize the results to the C-suite executives of provider organizations on a performance dashboard that can inform on decision-making and the development of best practices.
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- Leveraging Financial Analytics for Healthcare Organizations in Value-Based Care Environments
Dieter Van de Craen
Daniele De Massari
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