Understanding health service utilisation patterns for care home residents during the COVID-19 pandemic using routinely collected healthcare data.

BACKGROUND: Healthcare in care homes during the COVID-19 pandemic required a balance, providing treatment while minimising exposure risk. Policy for how residents should receive care changed rapidly throughout the pandemic. A lack of accessible data on care home residents over this time meant policy decisions were difficult to make and verify. This study investigates common patterns of healthcare utilisation for care home residents in relation to COVID-19 testing events, and associations between utilisation patterns and resident characteristics. METHODS: Datasets from County Durham and Darlington NHS Foundation Trust including secondary care, community care and a care home telehealth app are linked by NHS number used to define daily healthcare utilisation sequences for care home residents. We derive four 10-day sets of sequences related to Pillar 1 COVID-19 testing; before [1] and after [2] a resident's first positive test and before [3] and after [4] a resident's first test. These sequences are clustered, grouping residents with similar healthcare patterns in each set. Association of individual characteristics (e.g. health conditions such as diabetes and dementia) with healthcare patterns are investigated. RESULTS: We demonstrate how routinely collected health data can be used to produce longitudinal descriptions of patient care. Clustered sequences [1,2,3,4] are produced for 3,471 care home residents tested between 01/03/2020-01/09/2021. Clusters characterised by higher levels of utilisation were significantly associated with higher prevalence of diabetes. Dementia is associated with higher levels of care after a testing event and appears to be correlated with a hospital discharge after a first test. Residents discharged from inpatient care within 10 days of their first test had the same mortality rate as those who stayed in hospital. CONCLUSION: We provide longitudinal, resident-level data on care home resident healthcare during the COVID-19 pandemic. We find that vulnerable residents were associated with higher levels of healthcare usage despite the additional risks. Implications of findings are limited by the challenges of routinely collected data. However, this study demonstrates the potential for further research into healthcare pathways using linked, routinely collected datasets.

Retrospective audit of unplanned admissions to pediatric high dependency and intensive care after surgery.

BACKGROUND: Unplanned admissions to intensive care after surgery are a recommended clinical indicator of patient safety in the perioperative period and are validated to reflect both surgical and anesthesia-related complications. OBJECTIVES: To determine the rate and reasons for unplanned admissions to high dependency (HDU) and pediatric intensive care (PICU) following noncardiac surgery. METHODS: Data, including diagnosis, operation, and history of presenting complaint, were retrieved from electronic HDU and PICU data and hospital records for a 5-year period. All cases were individually reviewed by two pediatric anesthetists to identify unplanned admissions along with their urgency, source, and cause. RESULTS: During the study period, 53,876 procedures were performed resulting in 319 unplanned admissions to HDU/PICU, a rate of 0.6%. Of these, 108 (34%) were related to complications of anesthesia. The rate of unplanned admission to HDU/PICU secondary to a complication of anesthesia was therefore 0.2%. Emergency procedures and procedures involving a shared airway were particular risk factors for admission. CONCLUSION: The rate of unplanned admission to HDU/PICU is low and is comparable to previously published data. The high number of admissions following procedures involving a shared airway may represent patient-related factors and the case mix at this hospital. However, such a finding has prompted a combined ENT and anesthetic review of the care pathway for children with problems following airway instrumentation.