A tutorial on ‘capped utilisation’ as a metric and key performance target in NHS England’s Model Hospital operating theatres database: caution for international healthcare systems
The National Health Service (NHS) in England has set hospitals a target of achieving > 85% in a metric called ‘capped theatre utilisation’ (CTU), as central to its post-pandemic surgical waiting list recovery planning. This could serve as a model internationally, as other countries seek to improv...
Saved in:
Published in | ANESTHESIOLOGY AND PERIOPERATIVE SCIENCE Vol. 2; no. 4; pp. 1 - 13 |
---|---|
Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Singapore
Springer Nature Singapore
16.10.2024
Springer |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Abstract | The National Health Service (NHS) in England has set hospitals a target of achieving > 85% in a metric called ‘capped theatre utilisation’ (CTU), as central to its post-pandemic surgical waiting list recovery planning. This could serve as a model internationally, as other countries seek to improve operating theatre efficiency. Our review presents an analysis of what CTU means in the context of other measures of theatre ‘utilisation’, serving as a tutorial for clinical leaders, managers and all staff involved in theatres better to understand the metrics sometimes being used to assess their performance. We present results of a theoretical sensitivity analysis to assess how CTU values vary for hypothetical operating lists of three different structures (number of cases, their duration, and intercase gap times), as the stated start and finish times are shifted backwards and forwards in time. We then present results of our interrogation of the NHS Model Health Operating Theatres database to assess hospitals' CTU performance over three years. We discovered that in theory, CTU was especially sensitive to both stated list start times and list structure. The relationship to start time was asymmetric: early starts in one list did not compensate for loss of CTU value with late start in another list, when values were averaged across lists. This sensitivity analysis also predicted wide weekly CTU fluctuations, with values < 85% more likely than > 85%, especially for tertiary referral centres predominantly undertaking long, complex procedures. Our interrogation of the database confirmed these predictions. Moreover, we discovered many instances of implausible CTU values and underlying patterns indicating fundamental flaws in the CTU algorithm, rather than data entry errors. We conclude that CTU, and the NHS target of 85%, is not a suitable metric for operating theatre performance. It has proved unachievable in any sustainable way, and its underlying algorithm produces aberrant values. We discuss the serious consequences of basing other national policies or funding models on a fundamentally flawed metric. These results have lessons for international healthcare systems. |
---|---|
AbstractList | Abstract The National Health Service (NHS) in England has set hospitals a target of achieving > 85% in a metric called ‘capped theatre utilisation’ (CTU), as central to its post-pandemic surgical waiting list recovery planning. This could serve as a model internationally, as other countries seek to improve operating theatre efficiency. Our review presents an analysis of what CTU means in the context of other measures of theatre ‘utilisation’, serving as a tutorial for clinical leaders, managers and all staff involved in theatres better to understand the metrics sometimes being used to assess their performance. We present results of a theoretical sensitivity analysis to assess how CTU values vary for hypothetical operating lists of three different structures (number of cases, their duration, and intercase gap times), as the stated start and finish times are shifted backwards and forwards in time. We then present results of our interrogation of the NHS Model Health Operating Theatres database to assess hospitals' CTU performance over three years. We discovered that in theory, CTU was especially sensitive to both stated list start times and list structure. The relationship to start time was asymmetric: early starts in one list did not compensate for loss of CTU value with late start in another list, when values were averaged across lists. This sensitivity analysis also predicted wide weekly CTU fluctuations, with values < 85% more likely than > 85%, especially for tertiary referral centres predominantly undertaking long, complex procedures. Our interrogation of the database confirmed these predictions. Moreover, we discovered many instances of implausible CTU values and underlying patterns indicating fundamental flaws in the CTU algorithm, rather than data entry errors. We conclude that CTU, and the NHS target of 85%, is not a suitable metric for operating theatre performance. It has proved unachievable in any sustainable way, and its underlying algorithm produces aberrant values. We discuss the serious consequences of basing other national policies or funding models on a fundamentally flawed metric. These results have lessons for international healthcare systems. The National Health Service (NHS) in England has set hospitals a target of achieving > 85% in a metric called ‘capped theatre utilisation’ (CTU), as central to its post-pandemic surgical waiting list recovery planning. This could serve as a model internationally, as other countries seek to improve operating theatre efficiency. Our review presents an analysis of what CTU means in the context of other measures of theatre ‘utilisation’, serving as a tutorial for clinical leaders, managers and all staff involved in theatres better to understand the metrics sometimes being used to assess their performance. We present results of a theoretical sensitivity analysis to assess how CTU values vary for hypothetical operating lists of three different structures (number of cases, their duration, and intercase gap times), as the stated start and finish times are shifted backwards and forwards in time. We then present results of our interrogation of the NHS Model Health Operating Theatres database to assess hospitals' CTU performance over three years. We discovered that in theory, CTU was especially sensitive to both stated list start times and list structure. The relationship to start time was asymmetric: early starts in one list did not compensate for loss of CTU value with late start in another list, when values were averaged across lists. This sensitivity analysis also predicted wide weekly CTU fluctuations, with values < 85% more likely than > 85%, especially for tertiary referral centres predominantly undertaking long, complex procedures. Our interrogation of the database confirmed these predictions. Moreover, we discovered many instances of implausible CTU values and underlying patterns indicating fundamental flaws in the CTU algorithm, rather than data entry errors. We conclude that CTU, and the NHS target of 85%, is not a suitable metric for operating theatre performance. It has proved unachievable in any sustainable way, and its underlying algorithm produces aberrant values. We discuss the serious consequences of basing other national policies or funding models on a fundamentally flawed metric. These results have lessons for international healthcare systems. |
ArticleNumber | 35 |
Author | Zhang, Chen Dunstan, Claire Pandit, Jaideep J. |
Author_xml | – sequence: 1 givenname: Chen surname: Zhang fullname: Zhang, Chen organization: Nuffield Department of Anaesthetics, Oxford University Hospitals NHS Foundation Trust – sequence: 2 givenname: Claire surname: Dunstan fullname: Dunstan, Claire organization: Cardiff & Vale University Health Board, Anaesthetics and Peri-Operative Care NHS – sequence: 3 givenname: Jaideep J. surname: Pandit fullname: Pandit, Jaideep J. email: jaideep.pandit@sjc.ox.ac.uk organization: Department of Clinical Neurosciences, University of Oxford, St John’s College |
BookMark | eNp9kU1uFDEQhVsoSISQC7CqCzS0f6Z_2EVRYCKFsCB7q9qu7vTQY7dsz2J2OQYchevkJNTMIMQqC8s_et8r6723xZkPnorivag-iKpqPiat5UqXleTFd1WqV8W5bJQoW9V2Z_-d3xSXKW1YJDupGqnPi99XkHc5xAlnCB6en35aXBZysMvTPCXMU_DPT78AEyBsKcfJAnoHP2gPC8UhxC16S5AxjpRh8nC__g43fpxZxWCCr8HRDOuQlikfhjDFrn6E_EiYIyVwmLHHRJ_A4u4wENiWrTJFf_wAY6yd86PFSJD2KdM2vSteDzgnuvy7XxQPn28ertfl3bcvt9dXd6UVHWfRt2pw6CpbNShkpxvd2qFr-7YdlJRt3Qy1siurBSpcUV-RoE7XygnGa07porg92bqAG7PEaYtxbwJO5vgQ4mgw5snOZHheY1ft0CtZa0Wi1YOrFQ0cthNOEHvJk5eNIaVIwz8_UZlDleZUpeEqzbFKoxhSJyix2I8UzSbsOJg5vUT9AYNTqVo |
Cites_doi | 10.1213/01.ane.0000244535.54710.28 10.3166/jds.19.225-252 10.1213/ANE.0000000000002144 10.1213/ane.0b013e31819fe7a4 10.1016/j.bja.2021.10.033 10.1152/jappl.1996.81.5.2274 10.1007/s10729-014-9269-z 10.1016/j.bja.2023.03.032 10.1007/s10878-018-0322-6 10.1136/qshc.2005.013755 10.1213/ane.0b013e31819f9fd2 10.1016/j.bja.2024.03.006 10.1016/S0925-5273(03)00087-2 10.1111/anae.14645 10.1111/anae.14958 10.1017/9781108164061 10.1097/ALN.0000000000004722 10.1186/1472-6963-8-28 10.7196/SAMJ.2019.v109i10.13815 10.1080/00031305.1993.10475997 10.1111/j.1365-2044.2008.05854.x 10.1097/EJA.0b013e3283446b9c 10.1016/j.jclinane.2019.06.013 10.1111/j.1365-2044.2012.07160.x 10.1007/BF00996639 |
ContentType | Journal Article |
Copyright | The Author(s) 2024 |
Copyright_xml | – notice: The Author(s) 2024 |
DBID | C6C AAYXX CITATION DOA |
DOI | 10.1007/s44254-024-00073-3 |
DatabaseName | Springer Nature OA Free Journals CrossRef DOAJ Directory of Open Access Journals |
DatabaseTitle | CrossRef |
DatabaseTitleList | CrossRef |
Database_xml | – sequence: 1 dbid: C6C name: Springer Nature OA Free Journals url: http://www.springeropen.com/ sourceTypes: Publisher – sequence: 2 dbid: DOA name: Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Medicine |
EISSN | 2731-8389 |
EndPage | 13 |
ExternalDocumentID | oai_doaj_org_article_1977c58fb32643e184fd63ef292d1d1e 10_1007_s44254_024_00073_3 |
GroupedDBID | 0R~ AAKKN AAYZJ ABEEZ ACACY ACULB AFGXO ALMA_UNASSIGNED_HOLDINGS C24 C6C EBS GROUPED_DOAJ M~E RSV SOJ AAYXX CITATION |
ID | FETCH-LOGICAL-c1973-b83fdad0c07a1294748cf98b88f322867f63c5c41a3a5eb0e1e9463d1c196923 |
IEDL.DBID | C6C |
ISSN | 2731-8389 |
IngestDate | Wed Aug 27 01:26:07 EDT 2025 Tue Jul 01 04:24:35 EDT 2025 Fri Feb 21 02:37:27 EST 2025 |
IsDoiOpenAccess | true |
IsOpenAccess | true |
IsPeerReviewed | true |
IsScholarly | true |
Issue | 4 |
Keywords | Operating theatres NHS management Quality improvement Theatre efficiency Health economics Case scheduling |
Language | English |
LinkModel | DirectLink |
MergedId | FETCHMERGED-LOGICAL-c1973-b83fdad0c07a1294748cf98b88f322867f63c5c41a3a5eb0e1e9463d1c196923 |
OpenAccessLink | https://doi.org/10.1007/s44254-024-00073-3 |
PageCount | 13 |
ParticipantIDs | doaj_primary_oai_doaj_org_article_1977c58fb32643e184fd63ef292d1d1e crossref_primary_10_1007_s44254_024_00073_3 springer_journals_10_1007_s44254_024_00073_3 |
ProviderPackageCode | CITATION AAYXX |
PublicationCentury | 2000 |
PublicationDate | 20241016 |
PublicationDateYYYYMMDD | 2024-10-16 |
PublicationDate_xml | – month: 10 year: 2024 text: 20241016 day: 16 |
PublicationDecade | 2020 |
PublicationPlace | Singapore |
PublicationPlace_xml | – name: Singapore |
PublicationTitle | ANESTHESIOLOGY AND PERIOPERATIVE SCIENCE |
PublicationTitleAbbrev | APS |
PublicationYear | 2024 |
Publisher | Springer Nature Singapore Springer |
Publisher_xml | – name: Springer Nature Singapore – name: Springer |
References | Liang PJ, Pandit JJ, Robbins PA. Statistical properties of breath-to-breath variations in ventilation at constant PETCO2 and PETO2 in humans. J Appl Physiol. 1996;81(5):2274–86. Auditor General for Wales, Wales Audit Office [Internet]. Operating Theatres: A Summary of Local Audit Findings. 2016. [cited 2024 Apr 6]. Available from: https://www.audit.wales/sites/default/files/operating-theatres-2016-eng_7.pdf. HosseiniNTaaffeKMAllocating operating room block time using historical caseload variabilityHealth Care Manag Sci20151841943010.1007/s10729-014-9269-z24590259 ZhangCPanditJJGetting operating theatre metrics right to underpin quality improvement: understanding limitations of NHS Model Hospital calculationsBr J Anaesth202313113013410.1016/j.bja.2023.03.0323716962910308435 McIntoshCDexterFEpsteinRHThe impact of service-specific staffing, case scheduling, turnovers, and first-case starts on anesthesia group and operating room productivity: a tutorial using data from an Australian hospitalAnesth Analg20061031499151610.1213/01.ane.0000244535.54710.2817122231 NHS England [Internet]. Model Hospital efficiency plan development support pack 2019/20. [cited 2024 Apr 7]. Available from: https://model.nhs.uk/downloads/20190219_CIPSUPPORT_FINAL%20FULL.pdf. ParmarDWoodmanMPanditJJA graphical assessment of emergency surgical list efficiency to determine operating theatre capacity needsBr J Anaesth202212857458310.1016/j.bja.2021.10.03334865827 PanditJJAbbottTPanditMKapilaAAbrahamRIs 'starting on time' useful (or useless) as a surrogate measure for 'surgical theatre efficiency'?Anaesthesia20126782383210.1111/j.1365-2044.2012.07160.x22506738 NamisiBAKaruguCHGaciVMA Survey of the factors affecting theatre turnaround time in Kenyatta National Hospital main theatresInt J Anesth Anesthesiol202310155 ZhuSFanWYangSOperating room planning and surgical case scheduling: a review of literatureJ Comb Optim20193775780510.1007/s10878-018-0322-6 AsmalIIKeerathKCronjéLAn audit of operating theatre utilisation and day-of-surgery cancellations at a regional hospital in the Durban metropoleSouth Afr Med J201910976577010.7196/SAMJ.2019.v109i10.13815 NHS England [Internet]. Theatres improvement project (Cheshire and Merseyside) [cited 2024 Apr 7]. Available from: https://www.england.nhs.uk/north-west/recovery-bulletin/recovery-bulletin-issue-04-february-2023/theatres-improvement-project/. Harris M, Tayler B. Don’t let metrics undermine your business. Harvard Bus Rev. 2019. [cited 2024 Apr 7];97:[about 9 p.]. Available from: https://store.hbr.org/product/don-t-let-metrics-undermine-your-business/R1905C?srsltid=AfmBOoqgdhXbwu8MDfd1yHfY_nXlNo0Zno-iWBsFctBIwsDOjLAD8eGsSubscriptionrequired. mintzberg.org [Internet]. How productivity killed American enterprise. Essay. 2007. [cited 2016 Aug 21]. Available from: https://mintzberg.org/sites/default/files/article/download/productivity2008.pdf. Dexter F, Epstein RH, Penning DH. Late first-case of the day starts do not cause greater minutes of over-utilized time at an endoscopy suite with 8-hour workdays and late running rooms. A historical cohort study. J Clin Anesth. 2020;59:18–25. MahajanAIslamSDSchwartzMJCannessonMA hospital is not just a factory, but a complex adaptive system - implications for perioperative careAnesth Analg201712533334110.1213/ANE.000000000000214428614127 GordonTPaulSLylesAFountainJSurgical unit time utilization review: resource utilization and management implicationsJ Med Systems19881216917910.1007/BF00996639 MuduliAKauraVSouthwest Airlines success: a case study analysisBIVMR Manage Edge20114115118 FosterTOR manager data for benchmarking your OR’s performanceOp Room Manager20122815 ReutershanJRupprechtCRupprechtTOperating room scheduling: knowing and accepting your limitsBr J Anaesth20241321334133510.1016/j.bja.2024.03.00638582721 SpiegelhalterDJHandling over-dispersion of performance indicatorsQual Saf Health Care20051434735110.1136/qshc.2005.013755161955681744077 GuinetAChaabaneSOperating theatre planningInt J Prod Econ200385698110.1016/S0925-5273(03)00087-2 PanditJJStubbsDPanditMMeasuring the quantitative performance of surgical operating lists: theoretical modelling of 'productive potential' and 'efficiency'Anaesthesia20096447348610.1111/j.1365-2044.2008.05854.x19431218 Percival DB. Three curious properties of the sample variance and autocovariance for stationary processes with unknown mean. Am Stat. 1993;47(4):274–6. Abdel-HafezAWinningMGillMTheatre performance dashboard: development and challengesStud Health Technol Inform2021284808234920478 PanditJJDexterFLack of sensitivity of staffing for 8-hour sessions to standard deviation in daily actual hours of operating room time used for surgeons with long queuesAnesth Analg20091081910191510.1213/ane.0b013e31819fe7a419448221 Pandit JJ. Rational planning of operating lists: a prospective comparison of 'booking to the mean' vs. 'probabilistic case scheduling' in urology. Anaesthesia. 2020;75(5):642–7. NHS England and GIRFT [Internet]. Theatre Productivity [cited 2024 Apr 7 ]. Available from: https://gettingitrightfirsttime.co.uk/hvlc/theatre-productivity/. NHS England [Internet]. Addressing the significant financial challenges created by industrial action in 2023/24, and immediate actions to take. 2023. [cited 2024 Apr 7]. Available from: https://www.england.nhs.uk/long-read/addressing-the-significant-financial-challenges-created-by-industrial-action-in-2023-24/. FaizOTekkisPMcGuireAPapagrigoriadisSRennieJLeatherAIs theatre utilization a valid performance indicator for NHS operating theatres?BMC Health Serv Res200882810.1186/1472-6963-8-28182374112275239 AbouleishAEWhittenCWHudsonMEMeasuring and comparing clinical productivity of individual anesthesiologistsAnesthesiol202313968469610.1097/ALN.0000000000004722 NHS improvement [Internet]. NHS Improvement report "Operating theatres: opportunities to reduce waiting lists". 2019. [cited 2024 Apr 7]. Available from: https://www.insource.co.uk/nhs-improvement-report-operating-theatres-opportunities-to-reduce-waiting-lists/. WachtelREDexterFReducing tardiness from scheduled start times by making adjustments to the operating room scheduleAnesth Analg20091081902190910.1213/ane.0b013e31819f9fd219448220 Pandit JJ. Practical operating theatre management: measuring and improving performance and patient experience. 1st ed. Cambridge: Cambridge University Press; 2019. PanditJJTavareAUsing mean duration and variation of procedure times to plan a list of surgical operations to fit into the scheduled list timeEur J Anaesthesiol20112849350110.1097/EJA.0b013e3283446b9c21623186 SoukiMRebaiAHeuristics for the operating theatre planning and schedulingJ Decision Sys20101922525210.3166/jds.19.225-252 PanditJJTheNHSImprovement report on operating theatres: really 'getting it right first time'?Anaesthesia20197483984410.1111/anae.1464530919446 73_CR18 T Gordon (73_CR5) 1988; 12 JJ Pandit (73_CR34) 2012; 67 C Zhang (73_CR4) 2023; 131 C McIntosh (73_CR7) 2006; 103 73_CR32 73_CR11 73_CR12 BA Namisi (73_CR29) 2023; 10 73_CR36 73_CR37 73_CR16 73_CR38 73_CR3 JJ Pandit (73_CR8) 2009; 64 73_CR2 A Muduli (73_CR20) 2011; 4 DJ Spiegelhalter (73_CR10) 2005; 14 T Foster (73_CR24) 2012; 28 JJ Pandit (73_CR15) 2011; 28 RE Wachtel (73_CR33) 2009; 108 C McIntosh (73_CR31) 2006; 103 M Souki (73_CR14) 2010; 19 A Mahajan (73_CR27) 2017; 125 AE Abouleish (73_CR9) 2023; 139 D Parmar (73_CR13) 2022; 128 J Reutershan (73_CR28) 2024; 132 II Asmal (73_CR30) 2019; 109 73_CR21 73_CR1 JJ Pandit (73_CR17) 2009; 108 O Faiz (73_CR6) 2008; 8 73_CR26 JJ Pandit (73_CR22) 2019; 74 A Abdel-Hafez (73_CR35) 2021; 284 S Zhu (73_CR19) 2019; 37 A Guinet (73_CR23) 2003; 85 N Hosseini (73_CR25) 2015; 18 |
References_xml | – reference: NHS England [Internet]. Addressing the significant financial challenges created by industrial action in 2023/24, and immediate actions to take. 2023. [cited 2024 Apr 7]. Available from: https://www.england.nhs.uk/long-read/addressing-the-significant-financial-challenges-created-by-industrial-action-in-2023-24/. – reference: Harris M, Tayler B. Don’t let metrics undermine your business. Harvard Bus Rev. 2019. [cited 2024 Apr 7];97:[about 9 p.]. Available from: https://store.hbr.org/product/don-t-let-metrics-undermine-your-business/R1905C?srsltid=AfmBOoqgdhXbwu8MDfd1yHfY_nXlNo0Zno-iWBsFctBIwsDOjLAD8eGsSubscriptionrequired. – reference: Abdel-HafezAWinningMGillMTheatre performance dashboard: development and challengesStud Health Technol Inform2021284808234920478 – reference: McIntoshCDexterFEpsteinRHThe impact of service-specific staffing, case scheduling, turnovers, and first-case starts on anesthesia group and operating room productivity: a tutorial using data from an Australian hospitalAnesth Analg20061031499151610.1213/01.ane.0000244535.54710.2817122231 – reference: SpiegelhalterDJHandling over-dispersion of performance indicatorsQual Saf Health Care20051434735110.1136/qshc.2005.013755161955681744077 – reference: GuinetAChaabaneSOperating theatre planningInt J Prod Econ200385698110.1016/S0925-5273(03)00087-2 – reference: Liang PJ, Pandit JJ, Robbins PA. Statistical properties of breath-to-breath variations in ventilation at constant PETCO2 and PETO2 in humans. J Appl Physiol. 1996;81(5):2274–86. – reference: NHS improvement [Internet]. NHS Improvement report "Operating theatres: opportunities to reduce waiting lists". 2019. [cited 2024 Apr 7]. Available from: https://www.insource.co.uk/nhs-improvement-report-operating-theatres-opportunities-to-reduce-waiting-lists/. – reference: ParmarDWoodmanMPanditJJA graphical assessment of emergency surgical list efficiency to determine operating theatre capacity needsBr J Anaesth202212857458310.1016/j.bja.2021.10.03334865827 – reference: MuduliAKauraVSouthwest Airlines success: a case study analysisBIVMR Manage Edge20114115118 – reference: NHS England and GIRFT [Internet]. Theatre Productivity [cited 2024 Apr 7 ]. Available from: https://gettingitrightfirsttime.co.uk/hvlc/theatre-productivity/. – reference: PanditJJTheNHSImprovement report on operating theatres: really 'getting it right first time'?Anaesthesia20197483984410.1111/anae.1464530919446 – reference: ZhangCPanditJJGetting operating theatre metrics right to underpin quality improvement: understanding limitations of NHS Model Hospital calculationsBr J Anaesth202313113013410.1016/j.bja.2023.03.0323716962910308435 – reference: SoukiMRebaiAHeuristics for the operating theatre planning and schedulingJ Decision Sys20101922525210.3166/jds.19.225-252 – reference: Dexter F, Epstein RH, Penning DH. Late first-case of the day starts do not cause greater minutes of over-utilized time at an endoscopy suite with 8-hour workdays and late running rooms. A historical cohort study. J Clin Anesth. 2020;59:18–25. – reference: Pandit JJ. Rational planning of operating lists: a prospective comparison of 'booking to the mean' vs. 'probabilistic case scheduling' in urology. Anaesthesia. 2020;75(5):642–7. – reference: Pandit JJ. Practical operating theatre management: measuring and improving performance and patient experience. 1st ed. Cambridge: Cambridge University Press; 2019. – reference: AsmalIIKeerathKCronjéLAn audit of operating theatre utilisation and day-of-surgery cancellations at a regional hospital in the Durban metropoleSouth Afr Med J201910976577010.7196/SAMJ.2019.v109i10.13815 – reference: PanditJJAbbottTPanditMKapilaAAbrahamRIs 'starting on time' useful (or useless) as a surrogate measure for 'surgical theatre efficiency'?Anaesthesia20126782383210.1111/j.1365-2044.2012.07160.x22506738 – reference: PanditJJStubbsDPanditMMeasuring the quantitative performance of surgical operating lists: theoretical modelling of 'productive potential' and 'efficiency'Anaesthesia20096447348610.1111/j.1365-2044.2008.05854.x19431218 – reference: NamisiBAKaruguCHGaciVMA Survey of the factors affecting theatre turnaround time in Kenyatta National Hospital main theatresInt J Anesth Anesthesiol202310155 – reference: NHS England [Internet]. Model Hospital efficiency plan development support pack 2019/20. [cited 2024 Apr 7]. Available from: https://model.nhs.uk/downloads/20190219_CIPSUPPORT_FINAL%20FULL.pdf. – reference: HosseiniNTaaffeKMAllocating operating room block time using historical caseload variabilityHealth Care Manag Sci20151841943010.1007/s10729-014-9269-z24590259 – reference: WachtelREDexterFReducing tardiness from scheduled start times by making adjustments to the operating room scheduleAnesth Analg20091081902190910.1213/ane.0b013e31819f9fd219448220 – reference: Percival DB. Three curious properties of the sample variance and autocovariance for stationary processes with unknown mean. Am Stat. 1993;47(4):274–6. – reference: mintzberg.org [Internet]. How productivity killed American enterprise. Essay. 2007. [cited 2016 Aug 21]. Available from: https://mintzberg.org/sites/default/files/article/download/productivity2008.pdf. – reference: PanditJJDexterFLack of sensitivity of staffing for 8-hour sessions to standard deviation in daily actual hours of operating room time used for surgeons with long queuesAnesth Analg20091081910191510.1213/ane.0b013e31819fe7a419448221 – reference: ReutershanJRupprechtCRupprechtTOperating room scheduling: knowing and accepting your limitsBr J Anaesth20241321334133510.1016/j.bja.2024.03.00638582721 – reference: NHS England [Internet]. Theatres improvement project (Cheshire and Merseyside) [cited 2024 Apr 7]. Available from: https://www.england.nhs.uk/north-west/recovery-bulletin/recovery-bulletin-issue-04-february-2023/theatres-improvement-project/. – reference: GordonTPaulSLylesAFountainJSurgical unit time utilization review: resource utilization and management implicationsJ Med Systems19881216917910.1007/BF00996639 – reference: FaizOTekkisPMcGuireAPapagrigoriadisSRennieJLeatherAIs theatre utilization a valid performance indicator for NHS operating theatres?BMC Health Serv Res200882810.1186/1472-6963-8-28182374112275239 – reference: MahajanAIslamSDSchwartzMJCannessonMA hospital is not just a factory, but a complex adaptive system - implications for perioperative careAnesth Analg201712533334110.1213/ANE.000000000000214428614127 – reference: Auditor General for Wales, Wales Audit Office [Internet]. Operating Theatres: A Summary of Local Audit Findings. 2016. [cited 2024 Apr 6]. Available from: https://www.audit.wales/sites/default/files/operating-theatres-2016-eng_7.pdf. – reference: ZhuSFanWYangSOperating room planning and surgical case scheduling: a review of literatureJ Comb Optim20193775780510.1007/s10878-018-0322-6 – reference: PanditJJTavareAUsing mean duration and variation of procedure times to plan a list of surgical operations to fit into the scheduled list timeEur J Anaesthesiol20112849350110.1097/EJA.0b013e3283446b9c21623186 – reference: FosterTOR manager data for benchmarking your OR’s performanceOp Room Manager20122815 – reference: AbouleishAEWhittenCWHudsonMEMeasuring and comparing clinical productivity of individual anesthesiologistsAnesthesiol202313968469610.1097/ALN.0000000000004722 – ident: 73_CR21 – volume: 103 start-page: 1499 year: 2006 ident: 73_CR7 publication-title: Anesth Analg doi: 10.1213/01.ane.0000244535.54710.28 – volume: 19 start-page: 225 year: 2010 ident: 73_CR14 publication-title: J Decision Sys doi: 10.3166/jds.19.225-252 – ident: 73_CR2 – volume: 125 start-page: 333 year: 2017 ident: 73_CR27 publication-title: Anesth Analg doi: 10.1213/ANE.0000000000002144 – ident: 73_CR38 – volume: 108 start-page: 1910 year: 2009 ident: 73_CR17 publication-title: Anesth Analg doi: 10.1213/ane.0b013e31819fe7a4 – volume: 128 start-page: 574 year: 2022 ident: 73_CR13 publication-title: Br J Anaesth doi: 10.1016/j.bja.2021.10.033 – ident: 73_CR12 doi: 10.1152/jappl.1996.81.5.2274 – volume: 18 start-page: 419 year: 2015 ident: 73_CR25 publication-title: Health Care Manag Sci doi: 10.1007/s10729-014-9269-z – volume: 131 start-page: 130 year: 2023 ident: 73_CR4 publication-title: Br J Anaesth doi: 10.1016/j.bja.2023.03.032 – volume: 37 start-page: 757 year: 2019 ident: 73_CR19 publication-title: J Comb Optim doi: 10.1007/s10878-018-0322-6 – ident: 73_CR26 – volume: 14 start-page: 347 year: 2005 ident: 73_CR10 publication-title: Qual Saf Health Care doi: 10.1136/qshc.2005.013755 – volume: 108 start-page: 1902 year: 2009 ident: 73_CR33 publication-title: Anesth Analg doi: 10.1213/ane.0b013e31819f9fd2 – volume: 132 start-page: 1334 year: 2024 ident: 73_CR28 publication-title: Br J Anaesth doi: 10.1016/j.bja.2024.03.006 – volume: 85 start-page: 69 year: 2003 ident: 73_CR23 publication-title: Int J Prod Econ doi: 10.1016/S0925-5273(03)00087-2 – volume: 74 start-page: 839 year: 2019 ident: 73_CR22 publication-title: Anaesthesia doi: 10.1111/anae.14645 – ident: 73_CR16 doi: 10.1111/anae.14958 – volume: 10 start-page: 155 year: 2023 ident: 73_CR29 publication-title: Int J Anesth Anesthesiol – ident: 73_CR3 – ident: 73_CR18 doi: 10.1017/9781108164061 – volume: 139 start-page: 684 year: 2023 ident: 73_CR9 publication-title: Anesthesiol doi: 10.1097/ALN.0000000000004722 – ident: 73_CR1 – volume: 8 start-page: 28 year: 2008 ident: 73_CR6 publication-title: BMC Health Serv Res doi: 10.1186/1472-6963-8-28 – ident: 73_CR37 – volume: 103 start-page: 1499 year: 2006 ident: 73_CR31 publication-title: Anesth Analg doi: 10.1213/01.ane.0000244535.54710.28 – volume: 109 start-page: 765 year: 2019 ident: 73_CR30 publication-title: South Afr Med J doi: 10.7196/SAMJ.2019.v109i10.13815 – ident: 73_CR11 doi: 10.1080/00031305.1993.10475997 – ident: 73_CR36 – volume: 64 start-page: 473 year: 2009 ident: 73_CR8 publication-title: Anaesthesia doi: 10.1111/j.1365-2044.2008.05854.x – volume: 28 start-page: 493 year: 2011 ident: 73_CR15 publication-title: Eur J Anaesthesiol doi: 10.1097/EJA.0b013e3283446b9c – ident: 73_CR32 doi: 10.1016/j.jclinane.2019.06.013 – volume: 67 start-page: 823 year: 2012 ident: 73_CR34 publication-title: Anaesthesia doi: 10.1111/j.1365-2044.2012.07160.x – volume: 4 start-page: 115 year: 2011 ident: 73_CR20 publication-title: BIVMR Manage Edge – volume: 28 start-page: 1 year: 2012 ident: 73_CR24 publication-title: Op Room Manager – volume: 12 start-page: 169 year: 1988 ident: 73_CR5 publication-title: J Med Systems doi: 10.1007/BF00996639 – volume: 284 start-page: 80 year: 2021 ident: 73_CR35 publication-title: Stud Health Technol Inform |
SSID | ssj0002923724 |
Score | 2.27147 |
SecondaryResourceType | review_article |
Snippet | The National Health Service (NHS) in England has set hospitals a target of achieving > 85% in a metric called ‘capped theatre utilisation’ (CTU), as central to... Abstract The National Health Service (NHS) in England has set hospitals a target of achieving > 85% in a metric called ‘capped theatre utilisation’ (CTU), as... |
SourceID | doaj crossref springer |
SourceType | Open Website Index Database Publisher |
StartPage | 1 |
SubjectTerms | Anesthesiology Case scheduling Critical Care Medicine Health economics Intensive Medicine Medicine & Public Health Neurosciences NHS management Operating theatres Pharmacology/Toxicology Quality improvement Review Article Surgery Theatre efficiency |
SummonAdditionalLinks | – databaseName: DOAJ Directory of Open Access Journals dbid: DOA link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV3NbtQwELZQT1wQFSC2FDQHbmB1k3Ecp7eCulpx6KVbaW-RYztipZKNmvS-jwGPwuv0STrjZLdbIdFLr_mz5fnsGcfffCPEZ59USWWsklgVWqrgC2nQe4lB144iDE7vZLbFhZ5fqR_LbLlX6os5YYM88DBwJwkFKC4zdUVxhsJAG5Laawx1WqQ-8Ung1Zd83t5mitdguot5qsYsmZgrpwidSpJLkvF4SuIjTxQF-_85DY1OZvZavBqjQzgbenUoXoTmjfh7Bj0rDRBSYN3A3ea3s20bPBBmrkc2zt3mD9gOLPziClkObOOBpie0D3kBMJC-YdXAxfwSxuod9GIHXBDtGrYlRGDdstIydRB6XqppQw5MJGWHdwrORqgCfRZW-78T4eeOSgaDPnT3Vixm54vvczlWXJCOxhllZbD21k_dNLcUCKhcGVcXpjKmpolvdF5rdJlTiUWbhWoaklAojT5xrLKT4jtx0Kyb8F5AEXKHTvmALija1VmHOblBy_xsm2d6Ir5sB79sB12NcqegHE1VkqnKaKoSJ-Ib22f3JGtixwuElHJESvkUUibi69a65ThRu_-0efQcbX4QL1OGHFNg9LE46G9uw0eKYvrqUwTsPRec800 priority: 102 providerName: Directory of Open Access Journals |
Title | A tutorial on ‘capped utilisation’ as a metric and key performance target in NHS England’s Model Hospital operating theatres database: caution for international healthcare systems |
URI | https://link.springer.com/article/10.1007/s44254-024-00073-3 https://doaj.org/article/1977c58fb32643e184fd63ef292d1d1e |
Volume | 2 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3NbtQwELaglRAXVFoQC2U1B25gdR07ttNbWbVaIbUXitRb5NiOqFSyUbO9Vn0MeBRep0_SGa93aQEhcckhsvM3nzMznplvGHsXRCMa6xSXTaW5iqHiVobAZdStRwuDyjsp2-JEz76oT2flWabJoVqY3-L3e4NCUCmOmoSnqBKXj9lmKaShNg1TPV3vpxRoqZhC5bqYv099oHsSRf8f8c-kVo622LNsD8LBUoDP2aPYbbMnxznivcN-HsCCaAYQJjDv4Pbmu3d9HwMgYC5yKs7tzQ9wAzj4Ru2xPLguAK5N6H8VBcAy4xvOOziZfYbcugMnDkDd0C5g1T8E5j3RLOOzwoL-0-iNA2WRkrbbB-8STgEvC-f39xLh6zqPDJbk0MMLdnp0eDqd8dxugXtR4edprGyDCxM_MQ6tAGWU9W1lG2tbXPVWm1ZLX3olnHRlbCZRxEppGYQnip1CvmQb3byLrxhU0XjpVYjSR4UunfPSoA50lJztTKlH7P1KDnW_JNWo1_TJSWo1Sq1OUqvliH0kUa1HEiF2OoE4qfP6qvENjC9t26A5qmREv7UNWsYWYRFEEHHEPqwEXedVOvzjnq__b_gb9rQgnFGmi95lG4vLq_gWjZVFM0aUFmqcsDpODj8ej68P7wCdQ-nf |
linkProvider | Springer Nature |
linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Lb9QwELaqIgGXiqdYymMOcAJLm9hxHCQOpVBtabsXFqk3y7EdqFSy0WYR4tafAWd-BX-nv4QZr7OAQEgcek2cl77xPDLfzDD2yGd1VmsruagrxWXwFdfCey6Cahx6GFTeSWyLqZq8la-Pi-MN9m2ohYls9yElGTX1uthNonhJjjaFx_wSH0ZWH4TPnzBQ65_vv0RUH-f53qvZ7oSnWQLcZRUurrVovPVjNy4tmjhZSu2aStdaNyjSWpWNEq5wMrPCFqEehyxUUgmfOeofQ90NUM9fkhiiE29wN5VUkLrP8WyZy1SQ8_c3_c3oxdkAfyReoz3bu8a2kiMKOyvJuc42QnuDXT5Kqfab7PsOLKm_AconzFs4P_vibNcFDyipp4kDdH72FWwPFj7QXC4HtvWASgG6n9UIsKKaw0kL08kbSDND8MIeaAzbKQyDS2DeUX9nfFdYkoFYhB6Ivkpm9hk4GzcI4G3h5NefmPB-TWCDVVfq_habXQQ2t9lmO2_DHQZVKJ1w0gfhgsRY0jpRovG1xAq3ZaFG7MmAg-lW3TzMum9zRM0gaiaiZsSIvSCo1iupE3c8MF-8M2ljG_yC0hW6qdEPliJgwNx4JUKDYuEzn4URezoAbZJ66P_xzLv_t_whuzKZHR2aw_3pwTa7mpPMEd1G3WOby8XHcB89pmX9IEosMHPBO-QHuZEmJA |
linkToPdf | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3NbtQwELaqIlVcEL9iocAc4ARR17HjOEgcypbVlsIKiSL1Zjn-gUolG21SIW59DHgKzrxOn4Sx8wMIhMSh18RJHH1jz4xn5htCHlpa0lJqnrCyEAl3tkgkszZhTniDFkYo7wzZFkuxeMdfHmVHG-TbUAsTs92HkGRX0xBYmqp2p7Z-Zyx84yhqPEH9ksRYUzK0rz5wnz-h09Y8299DhB-l6fzF4WyR9H0FEkMLHFxK5q22UzPNNao7nnNpfCFLKT2KtxS5F8xkhlPNdObKqaOu4IJZagKXTGA6wD3_EjpGNHh7MzEbD3VSvJunvC_O-ftMf1OAsU_AH0HYqNvmV8mV3iiF3U6KrpENV10nW6_7sPsN8n0X2sB1gLIKqwrOz74YXdfOAkrtSZ8PdH72FXQDGj6GHl0GdGUBNwiof1YmQJd2DscVLBdvoe8fgg82EFqyncDQxARWdeB6xrlCG5TF2jUQUlmDyn0KRsfFAvhaOP71QBM-jMls0DFUNzfJ4UVgc4tsVqvK3SZQuNwww61jxnH0K7VhOSpiHTLEdZ6JCXk84KDqjtlDjRzOETWFqKmImmIT8jxANY4MrNzxwmr9XvWLXOEf5CaTvkSbmDOHzrO3gjmPYmGppW5CngxAq36raP7xzTv_N_wB2XqzN1ev9pcHd8nlNIhcyLwR22SzXZ-6e2g8teX9KLBA1AUvkB_U7CqH |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=A+tutorial+on+%E2%80%98capped+utilisation%E2%80%99+as+a+metric+and+key+performance+target+in+NHS+England%E2%80%99s+Model+Hospital+operating+theatres+database%3A+caution+for+international+healthcare+systems&rft.jtitle=ANESTHESIOLOGY+AND+PERIOPERATIVE+SCIENCE&rft.au=Zhang%2C+Chen&rft.au=Dunstan%2C+Claire&rft.au=Pandit%2C+Jaideep+J.&rft.date=2024-10-16&rft.pub=Springer+Nature+Singapore&rft.eissn=2731-8389&rft.volume=2&rft.issue=4&rft_id=info:doi/10.1007%2Fs44254-024-00073-3&rft.externalDocID=10_1007_s44254_024_00073_3 |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2731-8389&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2731-8389&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2731-8389&client=summon |