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The national picture of the comparative costs and diagnoses of hospitalised homeless patients are examined using the 'no fixed abode' flag in English hospital statistics. Comparable studies sample patients in single cities, eg New York and Toronto. The most common diagnosis is substance misuse; the share of homeless NHS patients with this diagnosis is rising, and now equals that found in North American cities. About half of the cost of homeless patients relates to diagnoses of mental illness, although these comprise a much smaller share of homeless patients than in North America. Hospital costs for homeless patients - both total and per admission -have fallen significantly in recent years, primarily because of fewer admissions and shorter lengths of stay for mentally ill patients. Aims to reduce NHS costs at the level of individual institutions have often shaped policy. Broader policy to prevent and reduce homelessness offers substantial long-term reductions in the cost of chronic care. [ABSTRACT FROM AUTHOR]

Background Hospital standardized mortality rates (HSMRs) are considered to identify unsafe hospital care, but are criticized for disregarding unmeasured variations of both coding practice and outside of hospital palliative provision. Methods The validity of HSMR methods is explored by examining whether the additional deaths implied by a Primary Care Trust (PCT) HSMR, as supplied by Dr Foster, are (i) detectable in English PCT mortality data and (ii) correlated with the percentage of PCT deaths out of hospital. Results Higher PCT HSMRs were positively associated with higher area mortality, although this effect was significantly smaller than the HSMR model implies. There was a significant negative association between PCT HSMR and the percentage of deaths outside of hospital. Conclusions This evidence suggests that the PCT HSMR is associated with all-cause area mortality, but it overstates the in-hospital mortality attributed to unsafe care. It also suggests that this overstatement is partially explained by the PCT HSMR reflecting the adverse case mix associated with a high share of deaths in hospital, i.e. the HSMR does not only reflect quality failings. Policy analyses that compare HSMRs to measure quality change may be biased by unbalanced samples of hospital patients. [ABSTRACT FROM AUTHOR]

Severe Mental Illness (SMI) encompasses a range of chronic conditions including schizophrenia, bipolar disorder and psychoses. Patients with SMI often require inpatient psychiatric care. Despite equity being a key objective in the English National Health Service (NHS) and in many other health care systems worldwide, little is known about the socio-economic equity of hospital care utilisation for patients with SMI and how it has changed over time. This analysis seeks to address that gap in the evidence base. We exploit a five-year (2006–2010) panel dataset of admission rates at small area level ( n = 162,410). The choice of control variables was informed by a systematic literature search. To assess changes in socio-economic equity of utilisation, OLS-based standardisation was first used to conduct analysis of discrete deprivation groups. Geographical inequity was then illustrated by plotting standardised and crude admission rates at local purchaser level. Lastly, formal statistical tests for changes in socio-economic equity of utilisation were applied to a continuous measure of deprivation using pooled negative binomial regression analysis, adjusting for a range of risk factors. Our results suggest that one additional percentage point of area income deprivation is associated with a 1.5% ( p < 0.001) increase in admissions for SMI after controlling for population size, age, sex, prevalence of SMI in the local population, as well as other need and supply factors. This finding is robust to sensitivity analyses, suggesting that a pro-poor inequality in utilisation exists for SMI-related inpatient services. One possible explanation is that the supply or quality of primary, community or social care for people with mental health problems is suboptimal in deprived areas. Although there is some evidence that inequity has reduced over time, the changes are small and not always robust to sensitivity analyses. [ABSTRACT FROM AUTHOR]