Feasibility and usefulness of Gini coefficients of primary care visits as a measure of service inequality: preliminary findings from a cross-sectional study using region-wide electronic medical records in Anhui, China.

objectiveThe aim of this study was to investigate inequalities in primary healthcare visits by using the Gini coefficients of primary healthcare visits (GPVs) as derived from large-scale and region-wide electronic records and to explore estimation and utility of GPV.

designThe study used a cross-sectional study design. It first extracted a random sample of 7.09 million primary care records from 1 October 2019 to 31 December 2021. Then it developed logarithmic models of GPVs using different months of records and performed descriptive and generalised linear mixed-effects regression analyses of the GPVs for all-cause diseases. The study also produced topographic maps of the GPVs for nine selected diseases.

settingAll primary healthcare facilities within the 105 townships or communities randomly selected from Anhui province, China.

participantsAll practising doctors working with and all patients presenting to the above sampled facilities during the 27-month study period.

resultsThe overall rate of primary healthcare visits during the 27-month period was estimated at 147.78%, with intra-regional variation coefficients by all-cause and system-specific disease ranging from 49.02% to 68.96%, and women were more likely than men to seek primary healthcare. The observed GPVs for all-cause and system-specific diseases all fitted very well with logarithmic equations and the goodness of fit increased rapidly when the months of EMRs were extended for the first few months, being over 78.92%, 91.17% and 94.78% for the first 3 months, 6 months and 12 months, respectively. These logarithmic models predicted at least high disparity (GPV>0.4) for all the system-specific diseases when the time period reached 6 months to 8 years. The observed GPVs for system-specific diseases, as estimated using the 27-month electronic medical records, ranged from 0.341 for skin-immune disease to 0.514 for cardiovascular disease. While the observed GPVs for all causes witnessed: great inter-region variations, with the highest GPV being 4.38 times the lowest; a general decreasing trend over the 9-quarter period, being reduced by 18.48% on average; and atypical J-shaped trajectories along age groups for both sexes. The multivariate modelling revealed statistically significant associations between the all-cause-GPV and 10 out of 14 commonly available community-level variables studied.

conclusionsGPVs can be accurately estimated using a limited number of months of EMRs and, guided by the relevant framework, analysis of GPVs can unveil useful clues in addressing unequal primary healthcare utilisation.