[Identifying Factors Associated with Visits to Doctors using a Multilevel Zero-inflated Poisson Model]

Area of Science:

• Health Services Research
• Biostatistics
• Rural Health

Background:

• Understanding healthcare utilization is crucial for resource allocation.
• Rural populations often face unique barriers to accessing medical care.
• Previous studies have not fully addressed the complexities of zero-inflated count data in healthcare utilization.

Purpose of the Study:

• To identify key determinants of patient visits to doctors among rural populations.
• To apply a specialized statistical model for analyzing healthcare utilization data with excess zeros.
• To inform targeted health interventions for rural communities.

Main Methods:

• Utilized data from the Fifth National Health Service Survey (2013) in Sichuan Province.
• Employed a multilevel random intercept zero-inflated Poisson model to analyze factors influencing doctor visits.
• Distinguished between factors affecting the likelihood of visiting and the number of visits.

Main Results:

• Likelihood of doctor visits was associated with gender, age, and chronic disease presence.
• Number of doctor visits was influenced by travel time to facilities, ethnicity, marital status, and education.
• Higher education, being unmarried, and proximity to medical facilities correlated with more frequent visits.

Conclusions:

• Educational attainment, marital status, and geographic proximity significantly impact rural healthcare-seeking behavior.
• The multilevel zero-inflated Poisson model is effective for analyzing healthcare utilization data with excess zero counts.
• Findings can guide policy to improve healthcare access and utilization in rural areas.