Search

The purpose of this research was to gain an understanding of how to measure the impact of information management (IM), to demonstrate its added value. The study is undertaken within UK local government and seeks to introduce an outcomes based way of thinking, mainly through the application of Outcomes Mapping (OM), taken from the overseas development arena. The organisation participating in this research believes that IM is of value but is unable to make explicit its contribution towards organisational outcomes. [Continues.]

Supplemental material, HSR911392 Supplemental Material for Healthcare utilization among migrants to the UK: cross-sectional analysis of two national surveys by Catherine L Saunders, Adam Steventon, Barbara Janta, Mai Stafford, Carol Sinnott, Lucinda Allen and Sarah R Deeny in Journal of Health Services Research & Policy

There is a profusion of evidence on the population and supply side factors explaining demand for emergency care, but surprisingly very little evidence about how seasonal patterns of demand vary across regions. Such information is crucial to help hospitals manage fluctuations in demand and ease capacity constraints. The objective of this study is to analyse the patterns of weekly attendances to Accident and Emergency departments in England, controlling for a wide range of determinants. The study uses both panel and common trend methods on data for 135 English hospitals and their catchment areas merged from a variety of sources over 156 weeks from 2012 to 2015. Modelling of unobservable factors with common trend models shows systematic patterns in the data related to season and the location of providers. Coastal areas experience more attendances in summer than urban areas, and this trend is reversed in winter, possibly due to temporary population movements. Internal reorganizations between major A&E departments and minor injury units within hospitals lead to structural breaks in attendances. In the panel models, only the share of the working population, weather and socioeconomic deprivation are statistically significant predictors of attendances in the panel models. The forecasting ability of both panel and common trends methods is similar. Fine-tuning funding allocations across trusts and seasons according to temporary population movements could be a promising avenue to help alleviate existing capacity constraints emergency departments.

Objective Simple forms of blood pressure (BP) telemonitoring require patients to text readings to central servers creating an opportunity for both entry error and manipulation. We wished to determine if there was an apparent preference for particular end digits and entries which were just below target BPs which might suggest evidence of data manipulation. Design Prospective cohort studySetting 37 socio-economically diverse primary care practices from South East NHS Lothian, Scotland.Participants Patients were recruited with hypertension to a telemonitoring service in which patients submitted home BP readings by manually transcribing the measurements into text messages for transmission (‘patient-texted system’). These readings were compared to those from primary care patients with uncontrolled hypertension using a system in which readings were automatically transmitted, eliminating the possibility of manipulation of values (‘automatic-transmission system’).Methods A Generalised Estimating Equations method was used to compare BP readings between the patient-texted and automatic-transmission systems, while taking into account clustering of readings within patients.Results A total of 44,150 BP readings were analysed on 1,068 patients using the patient-texted system compared to 20,705 readings on 199 patients using the automatic-transmission system. Compared to the automatic-transmission data, the patient-texted data showed a significantly higher proportion of occurrences of both systolic and diastolic BP having a zero end digit (OR 2.1, 95% CI 1.7 to 2.6) although incidence was less than 2% of readings. Similarly, there was a preference for systolic 134 and diastolic 84 (the threshold for alerts was 135/85) (134 systolic BP OR 1.52, 95% CI 1.28 to 1.82; 84 diastolic BP OR 1.54, 95% CI 1.28 to 1.86). Conclusion End-digit preference for zero numbers and specific value preference for readings just below the alert threshold exists among patients self-reporting their BP using telemonitoring. However, the proportion of readings affected is small and unlikely to be clinically important.

Table S2. Unadjusted logistic regression models estimating health care utilisation. This table sets out the results of the unadjusted logistic regression models and the association between living alone and health care utilisation. Odds ratios and p values are reported. (DOCX 22 kb)

Table S4. Sensitivity testing - Logistic regression modelling health care utilisation. This table sets out the results of the sensitivity testing for general practice utilisation and outpatient attendances. Odds ratios and p values are reported. (DOCX 23 kb)

Table S1. Utilisation by utilisation, count (percentage %). This table sets out a count of patients by utilisation and demonstrates the relationship between utilisation of different health care services (DOCX 22 kb)