Hiding in plain sight: insights about health-care trends gained through open health data

TL;DR

This paper presents an open-source analytics tool, BOAT, that leverages open health data to uncover healthcare trends, costs, and patterns, empowering citizens and stakeholders with unbiased insights amidst economic and political challenges.

Contribution

The paper introduces BOAT, a novel open-source tool for analyzing open health data, enabling detailed exploration of healthcare trends and costs with real-world case studies.

Findings

40% increase in adolescent mental health issues (2009-2014)

88% of hip replacement surgeries cost less than $30,000

BOAT facilitates unbiased analysis of healthcare expenditures

Abstract

The open data movement constitutes an approach to achieving accountability for government organizations, and is aligned with one of the sustainable development goals outlined by the United Nations. In the area of health care, government agencies at the Federal and State levels have released open health data consisting of de-identified patient outcomes, costs and ratings. We have applied big data analytics to understand patterns and trends in open health data. We envision the use of this data by concerned citizens to understand both national and local trends in health expenditures. We have built an open-source tool, BOAT (Big Data Open Source Analytics Tool, https://github.com/fdudatamining) to facilitate analytical exploration of open health data sets. We used BOAT to analyze data from the New York Statewide Planning and Research Cooperative System and determined that there has been a significant increase (40 percent) in the incidences of mental health issues amongst adolescents from 2009-2014. Using BOAT we analyzed costs for hip replacement surgery for 168,676 patients is in New York State, and showed that 88% of these patients had surgery costs of less than \$30,000. This figure provides a basis to understand the decision by The California Public Employees' Retirement System to cap hip replacement reimbursements at $30,000, resulting in significant savings. Our tool could enable researchers, hospitals, insurers and citizens to obtain an unbiased view on health-care expenditures, costs and emerging trends. Our tool is especially valuable in the current economic environment, where a significant amount of reporting is controlled by special interests groups and lobbies.