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@article{Clarke:2020:10.1136/bmjopen-2020-042392,
author = {Clarke, J and Murray, A and Markar, S and Barahona, M and Kinross, J},
doi = {10.1136/bmjopen-2020-042392},
journal = {BMJ Open},
pages = {1--9},
title = {A new geographic model of care to manage the post-COVID-19 elective surgery aftershock in England: a retrospective observational study},
url = {http://dx.doi.org/10.1136/bmjopen-2020-042392},
volume = {10},
year = {2020}
}
TY - JOUR
AB - 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. DesignRetrospective observational study using Hospital Episode Statistics.SettingPublic and private hospitals providing surgical care to National Health Service (NHS) patients in England. ParticipantsAll adult patients resident in England undergoing NHS-funded planned surgical procedures between 1st April 2017 and 31st March 2018. Main outcome measuresThe 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.ResultsA 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.ConclusionsPooled waiting lists for low risk elective procedures and patients across integrated, expanded natural surgical community networks have the pot
AU - Clarke,J
AU - Murray,A
AU - Markar,S
AU - Barahona,M
AU - Kinross,J
DO - 10.1136/bmjopen-2020-042392
EP - 9
PY - 2020///
SN - 2044-6055
SP - 1
TI - A new geographic model of care to manage the post-COVID-19 elective surgery aftershock in England: a retrospective observational study
T2 - BMJ Open
UR - http://dx.doi.org/10.1136/bmjopen-2020-042392
UR - https://bmjopen.bmj.com/content/10/10/e042392.info
UR - http://hdl.handle.net/10044/1/83183
VL - 10
ER -