Literature DB >> 22315466

Cancelled surgeries and payment by results in the English National Health Service.

Bryan McIntosh1, Graham Cookson, Simon Jones.   

Abstract

OBJECTIVES: To model the frequency of 'last minute' cancellations of planned elective procedures in the English NHS with respect to the patient and provider factors that led to these cancellations.
METHODS: A dataset of 5,288,604 elective patients spell in the English NHS from January 1st, 2007 to December 31st, 2007 was extracted from the Hospital Episode Statistics. A binary dependent variable indicating whether or not a patient had a Health Resource Group coded as S22--'Planned elective procedure not carried out'--was modeled using a probit regression estimated via maximum likelihood including patient, case and hospital level covariates.
RESULTS: Longer waiting times and being admitted on a Monday were associated with a greater rate of cancelled procedures. Male patients, patients from lower socio-economic groups and older patients had higher rates of cancelled procedures. There was significant variation in cancellation rates between hospitals; Foundation Trusts and private facilities had the lowest cancellation rates.
CONCLUSIONS: Further research is needed on why Foundation Trusts exhibit lower cancellation rates. Hospitals with relatively high cancellation rates should be encouraged to tackle this problem. Further evidence is needed on whether hospitals are more likely to cancel operations where the procedure tariff is lower than the S22 tariff as this creates a perverse incentive to cancel. Understanding the underlying causes of why male, older and patients from lower socio-economic groups are more likely to have their operations cancelled is important to inform the appropriate policy response. This research suggests that interventions designed to reduce cancellation rates should be targeted to high-cancellation groups.

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Year:  2012        PMID: 22315466     DOI: 10.1258/jhsrp.2011.011053

Source DB:  PubMed          Journal:  J Health Serv Res Policy        ISSN: 1355-8196


  4 in total

1.  Combining regression trees and panel regression for exploring and testing the impact of complementary management practices on short-notice elective operation cancellation rates.

Authors:  Reza Salehnejad; Manhal Ali; Nathan Proudlove
Journal:  Health Syst (Basingstoke)       Date:  2019-04-19

2.  Implementation of a 23-h surgery model in a tertiary care hospital: a safe and feasible model with high patient satisfaction.

Authors:  U-M Ruohoaho; P Toroi; J Hirvonen; S Aaltomaa; H Kokki; M Kokki
Journal:  BJS Open       Date:  2020-02-28

3.  Assessing the Rates and Reasons of Elective Surgical Cancellations on the Day of Surgery: A Multicentre Study from Urban Indian Hospitals.

Authors:  Bhakti Sarang; Geetu Bhandoria; Priti Patil; Anita Gadgil; Lovenish Bains; Monty Khajanchi; Deepa Kizhakke Veetil; Rohini Dutta; Priyansh Shah; Prashant Bhandarkar; Lileswar Kaman; Dhruva Ghosh; Kavita Mandrelle; Ashwani Kumar; Akshay Bahadur; Sunil Krishna; Kamal Kishore Gautam; Ya Dev; Manisha Aggarwal; Neil Thivalapill; Nobhojit Roy
Journal:  World J Surg       Date:  2021-11-16       Impact factor: 3.352

4.  The impact of cancellations in waiting times analysis: evidence from scheduled surgeries in the Portuguese NHS.

Authors:  Joana Cima; Álvaro Almeida
Journal:  Eur J Health Econ       Date:  2021-07-25
  4 in total

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