ABSTRACT
Objectives ....................................................................................................... 285 Abstract ........................................................................................................... 286 Introduction ................................................................................................... 286 Cost and Quality Transparency through Publicly Available Data .......... 287 Making Informed Decisions Using Individual-Level Clinical Data ....... 290
Supporting Treatment Decisions in Cancer Care .................................291 Supporting the Selection of Intervention Programs with Risk Prediction Models .................................................................................... 296
Predictive Analytics for Detection of Fraud, Waste, and Abuse Using Claims Data ............................................................................. 298 Conclusion ..................................................................................................... 303 References ....................................................................................................... 304
• Describe how prediction models, and cost and benefit characteristics of different intervention programs, can be combined to optimize decisions about program design and patient enrollment
• Demonstrate opportunities to use predictive analytics to improve the detection of fraud, waste, and abuse in health care billing claims
The increasing availability of data in the health care industry is creating striking opportunities to apply sophisticated analytical techniques to address persistent problems in health care related to cost, quality, and patient safety. Data from across the health care sector, including from clinical systems, administrative records, and open government initiatives, are being used to support decision-making by a wide range of stakeholders. This chapter provides illustrations of four opportunities to support better decision-making, including evaluating health care cost, making informed treatment decisions, improving the design and selection of intervention programs, and combatting fraud, waste, and abuse in health care billing practices.
