Hiding in Plain Sight: Insights about Health-Care Trends Gained through Open Health Data

ABSTRACT

The open data movement constitutes an approach to achieving accountability for government organizations. Government agencies at the Federal and State levels have released open health data consisting of de-identified patient outcomes, costs and ratings. We 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 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. 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 helps in understanding 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.

KEYWORDS:

• Analytics
• big data
• open healthcare data
• outliers
• trend analysis