Measuring and optimising the efficiency of community hospital inpatient care for older people: the MoCHA mixed-methods study - John Young; Claire Hulme; Andrew Smith; John Buckell; Mary Godfrey; Claire Holditch; Jessica Grantham; Helen Tucker; Pam Enderby; John Gladman; Elizabeth Teale; Jean-Christophe Thiebaud (National Institute for Health Research, 2020)
Background: Community hospitals are small hospitals providing local inpatient and outpatient services. National surveys report that inpatient rehabilitation for older people is a core function but there are large differences in key performance measures. We have investigated these variations in community hospital ward performance. Objectives: (1) To measure the relative performance of community hospital wards (studies 1 and 2); (2) to identify characteristics of community hospital wards that optimise performance (studies 1 and 3); (3) to develop a web-based interactive toolkit that supports operational changes to optimise ward performance (study 4); (4) to investigate the impact of community hospital wards on secondary care use (study 5); and (5) to investigate associations between short-term community (intermediate care) services and secondary care utilisation (study 5). Methods: Study 1 - we used national data to conduct econometric estimations using stochastic frontier analysis in which a cost function was modelled using significant predictors of community hospital ward costs. Study 2 - a national postal survey was developed to collect data from a larger sample of community hospitals. Study 3 - three ethnographic case studies were performed to provide insight into less tangible aspects of community hospital ward care. Study 4 - a web-based interactive toolkit was developed by integrating the econometrics (study 1) and case study (study 3) findings. Study 5 - regression analyses were conducted using data from the Atlas of Variation Map 61 (rate of emergency admissions to hospital for people aged ≥ 75 years with a length of stay of < 24 hours) and the National Audit of Intermediate Care. Results: Community hospital ward efficiency is comparable with the NHS acute hospital sector (mean cost efficiency 0.83, range 0.72-0.92). The rank order of community hospital ward efficiencies was distinguished to facilitate learning across the sector. On average, if all community hospital wards were operating in line with the highest cost efficiency, savings of 17% (or £47M per year) could be achieved (price year 2013/14) for our sample of 101 wards. Significant economies of scale were found: a 1% rise in output was associated with an average 0.85% increase in costs. We were unable to obtain a larger community hospital sample because of the low response rate to our national survey. The case studies identified how rehabilitation was delivered through collaborative, interdisciplinary working; interprofessional communication; and meaningful patient and family engagement. We also developed insight into patients' recovery trajectories and care transitions. The web-based interactive toolkit was established [http://mocha.nhsbenchmarking.nhs.uk/ (accessed 9 September 2019)]. The crisis response team type of intermediate care, but not community hospitals, had a statistically significant negative association with emergency admissions. Limitations: The econometric analyses were based on cross-sectional data and were also limited by missing data. The low response rate to our national survey means that we cannot extrapolate reliably from our community hospital sample. Conclusions: The results suggest that significant community hospital ward savings may be realised by improving modifiable performance factors that might be augmented further by economies of scale. Future work: How less efficient hospitals might reduce costs and sustain quality requires further research. Funding: This project was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research; Vol. 8, No. 1. See the NIHR Journals Library website for further project information.