14
IRUS TotalDownloads
Altmetric
A new geographic model of care to manage the post-COVID-19 elective surgery aftershock in England: a retrospective observational study
File | Description | Size | Format | |
---|---|---|---|---|
e042392.full.pdf | Published version | 1.53 MB | Adobe PDF | View/Open |
Title: | A new geographic model of care to manage the post-COVID-19 elective surgery aftershock in England: a retrospective observational study |
Authors: | Clarke, J Murray, A Markar, S Barahona, M Kinross, J |
Item Type: | Journal Article |
Abstract: | Objectives The suspension of elective surgery during the COVID pandemic is unprecedented and has resulted in record volumes of patients waiting for operations. Novel approaches that maximise capacity and efficiency of surgical care are urgently required. This study applies Markov Multiscale Community Detection (MMCD), an unsupervised graph-based clustering framework, to identify new surgical care models based on pooled waiting lists delivered across an expanded network of surgical providers. Design Retrospective observational study using Hospital Episode Statistics. Setting Public and private hospitals providing surgical care to National Health Service (NHS) patients in England. Participants All adult patients resident in England undergoing NHS-funded planned surgical procedures between 1st April 2017 and 31st March 2018. Main outcome measures The identification of the most common planned surgical procedures in England (High Volume Procedures – HVP) and proportion of low, medium and high-risk patients undergoing each HVP. The mapping of hospitals providing surgical care onto optimised groupings based on patient usage data. Results A total of 7,811,891 planned operations were identified in 4,284,925 adults during the one-year period of our study. The 28 most common surgical procedures accounted for a combined 3,907,474 operations (50.0% of the total). 2,412,613 (61.7%) of these most common procedures involved ‘low risk’ patients. Patients travelled an average of 11.3 km for these procedures. Based on the data, MMCD partitioned England into 45, 16 and 7 mutually exclusive and collectively exhaustive natural surgical communities of increasing coarseness. The coarser partitions into 16 and 7 surgical communities were shown to be associated with balanced supply and demand for surgical care within communities. Conclusions Pooled waiting lists for low risk elective procedures and patients across integrated, expanded natural surgical community networks have the potential to increase efficiency by innovatively flexing existing supply to better match demand. |
Issue Date: | 31-Oct-2020 |
Date of Acceptance: | 30-Sep-2020 |
URI: | http://hdl.handle.net/10044/1/83183 |
DOI: | 10.1136/bmjopen-2020-042392 |
ISSN: | 2044-6055 |
Publisher: | BMJ Journals |
Start Page: | 1 |
End Page: | 9 |
Journal / Book Title: | BMJ Open |
Volume: | 10 |
Issue: | 10 |
Copyright Statement: | © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/. |
Sponsor/Funder: | Engineering & Physical Science Research Council (EPSRC) Wellcome Trust Imperial College Healthcare NHS Trust- BRC Funding Imperial College Healthcare NHS Trust- BRC Funding |
Funder's Grant Number: | EP/N014529/1 UNS81609 - 215938/Z/19/Z RDB04 79560 RD207 |
Keywords: | Science & Technology Life Sciences & Biomedicine Medicine, General & Internal General & Internal Medicine surgery health policy organisation of health services public health WAITING-LISTS CHOICE MARKET TIMES health policy organisation of health services public health surgery Adult Betacoronavirus COVID-19 Community Networks Coronavirus Infections Efficiency, Organizational Elective Surgical Procedures England Health Services Accessibility Humans Intersectoral Collaboration Markov Chains Models, Organizational Pandemics Pneumonia, Viral Retrospective Studies Risk Assessment SARS-CoV-2 State Medicine Waiting Lists PanSurg Collaborative Humans Pneumonia, Viral Coronavirus Infections Markov Chains Risk Assessment Retrospective Studies Models, Organizational Community Networks Adult State Medicine Waiting Lists Efficiency, Organizational Health Services Accessibility England Pandemics Elective Surgical Procedures Intersectoral Collaboration Betacoronavirus COVID-19 SARS-CoV-2 1103 Clinical Sciences 1117 Public Health and Health Services 1199 Other Medical and Health Sciences |
Publication Status: | Published |
Online Publication Date: | 2020-10-31 |
Appears in Collections: | Department of Surgery and Cancer Applied Mathematics and Mathematical Physics Faculty of Medicine Institute of Global Health Innovation Imperial College London COVID-19 Faculty of Natural Sciences Mathematics |
This item is licensed under a Creative Commons License