Estimating the scale of hospital admissions for people experiencing homelessness in England: a population-based multiple systems estimation study using national Hospital Episodes Statistics

Abstract

Background: people experiencing homelessness have substantial health needs and poor access to primary healthcare, resulting in high rates of hospital care. Housing status is not routinely recorded in English electronic health records, undermining service planning. We developed methods to estimate the scale of hospital admissions for people experiencing homelessness in England.

Methods: we analysed admissions for people experiencing homelessness using Hospital Episode Statistics for 2013/2014, 2015/2016 and 2017/2018. We applied multiple systems estimation Poisson regression methods to estimate total admissions and an inflation factor to correct for under-reporting. We calculated unadjusted admission rates per 1000 population per year and admission rate ratios compared with the housed population.

Results: we observed 34 790 admissions in 2017/2018, with total homeless admissions estimated at 176 342 (95% CI 164 031 to 188 654) (inflation factor=5.07 (95% CI 4.71 to 5.42)). The unadjusted admission rate for the 2017/2018 homeless population was 879.0 admissions per 1000 population per year (95% CI 817.7 to 940.4), 2.5 (95% CI 2.3 to 2.7) times higher than the housed population. Restricted to rough sleepers and hostel residents, the unadjusted rate was 3516.7 per 1000 (95% CI 3271.2 to 3762.2), with a rate ratio of 10.0 (95% CI 9.3 to 10.7) compared with the housed population.

Conclusions: we estimated five times as many hospital admissions for people experiencing homelessness than we observed directly. We advise caution when applying these inflation factors to other datasets because of methodological limitations in this study and sensitivities to local coding practices. In the absence of routine housing status recording, multiple systems estimation could facilitate improved service planning.

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ORCID for Dankmar Böhning: orcid.org/0000-0003-0638-7106

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