Avoiding double counting: the effect of bundling hospital events in administrative datasets for the interpretation of rural-urban differences in Aotearoa New Zealand

Background All publicly funded hospital discharges in Aotearoa New Zealand (NZ) are recorded in the National Minimum Dataset (NMDS). Movement of patients between hospitals (and occasionally within the same hospital) results in separate records (discharge events) within the NMDS and if these consecutive health records are not accounted for hospitalisation (encounters) rates might be overestimated. The aim of this study was to determine the impact of four different methods to bundle multiple discharge events in the NMDS into encounters on the relative comparison of rural and urban Ambulatory Sensitive Hospitalisation (ASH) rates. Methods NMDS discharge events with an admission date between July 1 2015 and December 31 2019 were bundled into encounters using either using a) no method, b) an “admission flag”, c) a “discharge flag” or d) a date-based method. ASH incidence rates and rate ratios (IRR), the mean total length of stay and the percentage of inter-hospital transfers were estimated for each bundling method. These outcomes were compared across 4 categories of the Geographic Classification for Health (GCH). Results Compared with no bundling, using the date-based method resulted in an 8.3% reduction (150 less hospitalisations per 100 000 person years) in the estimated incidence rate for ASH in the most rural (R2-3) regions. There was no difference in the interpretation of the rural-urban IRR for any bundling methodology. Length of stay was longer for all bundling methods used. For patients that live in the most rural regions, using a date-based method identified up to twice as many inter-hospital transfers (5.7% vs. 12.4%) compared to using admission flags. Conclusion Consecutive events within hospital discharge datasets should be bundled into encounters to estimate incidence. This reduces the over-estimation of incidence rates and the undercounting of inter-hospital transfers and total length of stay.