Building an Open Health Data Analytics Platform: a Case Study Examining Relationships and Trends in Seniority and...

Area of Science:

• Healthcare Analytics
• Medical Professional Studies
• Public Health Data

Background:

• Governments are increasingly releasing public data to enhance transparency.
• Extracting actionable knowledge from open data presents significant challenges.
• The relationship between healthcare practitioner seniority and performance is a complex and debated topic.

Purpose of the Study:

• To investigate the correlation between healthcare practitioner seniority and performance using an open, reproducible framework.
• To analyze large-scale healthcare datasets to identify trends and relationships.

Main Methods:

• Utilized data from the Center for Medicare and Medicaid Services (CMS) and the New York Statewide Planning and Research Cooperative System (SPARCS).
• Employed Spearman rank correlation to assess the relationship between graduation year (proxy for seniority) and performance metrics.
• Applied K-means clustering for outlier detection and trend analysis, including nurse practitioner numbers.

Main Results:

• Weak but statistically significant correlations (Spearman's rho < 0.164, p < 0.05) were found between graduation year and hospital value-based performance in 29 of 74 specialties.
• Similar weak correlations (Spearman's rho = -0.096, p < 0.0005) were observed between graduation year and cardiac surgery outcomes in New York.
• K-means clustering identified a rapid increase in nurse practitioners since 2010 and consistent practitioner placement across hospitals.

Conclusions:

• Healthcare professional training appears robust, preparing individuals for stable and enduring careers in most specialties.
• The findings indicate that while seniority has a minor statistical link to performance, the overall system supports consistent professional longevity.
• Open data analysis reveals important trends in healthcare workforce dynamics and practitioner performance.