Understanding Quantity and Intensity of Hospital Rehabilitation Using Electronic Health Record Data

Background Many hospitalised patients require rehabilitation during recovery from acute illness. We use routine data from electronic health records (EHR) to report the quantity and intensity of rehabilitation and compared this in patients with and without COVID-19.Methods We performed a retrospective cohort study of consecutive adults in whom COVID-19 testing was undertaken between March 2020 and August 2021 across three acute hospitals in Scotland. We defined rehabilitation contacts (physiotherapy, occupational therapy, dietetics and speech and language therapy) from timestamped EHR data and determined contact time from a linked workforce planning dataset. We included survivors to hospital discharge who received at least two rehabilitation contacts. The primary outcome was total rehabilitation time. Secondary outcomes included the number of contacts, time to first contact, and rehabilitation minutes per day. A multivariate regression analysis for predictors of rehabilitation time included age, sex, comorbidities, and socioeconomic status.Findings We included 11,591 consecutive unique patient admissions (76 [63,85] years, 56% female), of which 651 (6%) were with COVID-19, and 10,940 (94%) were admissions with negative testing. There were 128,646 rehabilitation contacts. Patients with COVID-19 received more than double the rehabilitation time compared to those without (365 [165,772] vs 170 [95,350] mins, p<0.001), and this was delivered over more specialist contacts (12 [6,25] vs 6 [3,11], p<0.001). Time to first rehabilitation contact was later in patients with COVID-19 (3 [1,5] vs 2 [1,4] days from admission). Overall, patients with COVID-19 received fewer minutes of rehabilitation per day of admission (14.1 [9.8,18.7] vs 15.6 [10.6,21.3], p<0.001). In our regression analyses, older age and COVID-19 were the most important predictors of increased rehabilitation time.Interpretation Patients with COVID received more rehabilitation contact time than those without COVID, but this was delivered less intensively. Rehabilitation data derived from the EHR represents a novel measure of delivered hospital care.### Competing Interest StatementThe authors have declared no competing interest.### Funding StatementKG is supported by a PhD Fellowship award from the Sir Jules Thorn Charitable Trust (21/01PhD) as part of the University of Edinburgh Precision Medicine PhD programme. DD is supported by an award from the Medical Research Council (MR/N013166/1). NLM is supported by a Chair Award, Programme Grant, Research Excellence Award (CH/F/21/90010, RG/20/10/34966, RE/18/5/34216) from the British Heart Foundation. This work was supported by DataLoch (dataloch.org), which is core-funded by the Data-Driven Innovation programme within the Edinburgh and South East Scotland City Region Deal (ddi.ac.uk), and the Chief Scientist Office, Scottish Government (cso.scot.nhs.uk).### Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:This work was reviewed by the DataLoch ethics review panel (LPAC) and approved under Lothian REC approval to this service (Edinburgh, United Kingdom, ref: 17/NS/0072). All data was collected from Electronic Health Records and national registries previously anonymised by the DataLoch service and analysed in a Secure Data Environment. Consent from patients was not required for this study.I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.YesThis study makes use of several routine electronic health care data sources that are linked, de-identified, and held in a Secure Data Environment (DataLoch), which is accessible by approved individuals who have undertaken the necessary governance training. Summary data can be made available upon request to the corresponding author. All data processing and modelling were conducted in RStudio version 4.2.0 using publicly available libraries through CRAN. The data extraction and cleaning procedures were performed using tidyverse, the visualisations were performed using ggplot2, the mixed-effects model was fit using lme4 and the weights for the IPTW adjustments were generated using the ipw and survey packages. The data analysis code is held in a Secure Data Environment but may be made available for review in a non-disclosive format on discussion with the corresponding author.