Browsing Health Studies by Author "Yu, V."
Hospital admissions after vertical integration of general practices with an acute hospital: a retrospective synthetic matched controlled database studyYu, V.; Wyatt, S.; Woodall, M.; Sultan, M.; Klaire, V.; Bailey, K.; Mohammed, Mohammed A. (2020)Background New healthcare models are being explored to enhance care coordination, efficiency, and outcomes. Evidence is scarce regarding the impact of vertical integration of primary and secondary care on emergency department (ED) attendances, unplanned hospital admissions, and readmissions. Aim To examine the impact of vertical integration of an NHS provider hospital and 10 general practices on unplanned hospital care Design and setting A retrospective database study using synthetic controls of an NHS hospital in Wolverhampton integrated with 10 general practices, providing primary medical services for 67 402 registered patients. Method For each vertical integration GP practice, a synthetic counterpart was constructed. The difference in rate of ED attendances, unplanned hospital admissions, and unplanned hospital readmissions was compared, and pooled across vertical integration practices versus synthetic control practices pre-intervention versus post-intervention. Results Across the 10 practices, pooled rates of ED attendances did not change significantly after vertical integration. However, there were statistically significant reductions in the rates of unplanned hospital admissions (−0.11, 95% CI = −0.18 to −0.045, P = 0.0012) and unplanned hospital readmissions (−0.021, 95% CI = −0.037 to −0.0049, P = 0.012), per 100 patients per month. These effect sizes represent 888 avoided unplanned hospital admissions and 168 readmissions for a population of 67 402 patients per annum. Utilising NHS reference costs, the estimated savings from the reductions in unplanned care are ∼£1.7 million. Conclusion Vertical integration was associated with a reduction in the rate of unplanned hospital admissions and readmissions in this study. Further work is required to understand the mechanisms involved in this complex intervention, to assess the generalisability of these findings, and to determine the impact on patient satisfaction, health outcomes, and GP workload.