The Promise and Perils of Big Data in Healthcare: Evaluating Opportunities to Improve Quality and Access while Reducing Costs

Abstract

Big data analytics holds significant promise for transforming healthcare quality, access, and costs. Advanced analysis of vast data streams and datasets enables enhanced clinical decision-making, earlier public health interventions, accelerated research, and improved patient outcomes. However, there are also important challenges involving privacy, discrimination, efficacy, costs, and unintended consequences that must be addressed responsibly even while innovation advances. This paper examines the opportunities for leveraging big data across healthcare including population health initiatives, clinical support tools, medical discoveries, and personalized medicine. It also explores limitations and risks such as re-identification vulnerabilities, biased algorithms, infrastructure expenses, and nonlinear system effects. An integrated oversight framework is recommended that combines governance mechanisms across stakeholders to enable context-appropriate progress. Providers, patients, innovators, payers, and regulators each have roles in stewarding data use towards safe and ethical applications focused on health gains. Hybrid oversight strategies can foster breakthroughs by guiding evidence-based decision-making while monitoring impacts among priority groups. Ultimately realizing the promise of big data in healthcare requires policy innovation at pace with technical innovation. Collaborative development of flexible policies can accelerate life-saving discoveries through data while building public trust in data-driven interventions aimed at democratizing quality care.