Abstract
Context: Many governments have publicly released healthcare data, which can be mined for insights about disease conditions, and their impact on society. Methods: We present a big-data analytics approach to investigate data in the New York Statewide Planning and Research Cooperative System (SPARCS) consisting of 20 million patient records. Findings: Whereas the age group 30–48 years exhibited an 18% decline in mental health (MH) disorders from 2009 to 2016, the age group 0–17 years showed a 5.4% increase. MH issues amongst the age group 0–17 years comprise a significant expenditure in New York State. Within this age group, we find a higher prevalence of MH disorders in females and minority populations. Westchester County has seen a 32% increase in incidences and a 41% increase in costs. Conclusions: Our approach is scalable to data from multiple government agencies and provides an independent perspective on health care issues, which can prove valuable to policy and decision-makers.
Original language | English (US) |
---|---|
Pages (from-to) | 41-51 |
Number of pages | 11 |
Journal | Community Mental Health Journal |
Volume | 58 |
Issue number | 1 |
DOIs | |
State | Published - Jan 2022 |
Keywords
- Big data analytics
- Mental health
ASJC Scopus subject areas
- Health(social science)
- Public Health, Environmental and Occupational Health
- Psychiatry and Mental health