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...

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Published inANESTHESIOLOGY AND PERIOPERATIVE SCIENCE Vol. 2; no. 4; pp. 1 - 13
Main Authors Zhang, Chen, Dunstan, Claire, Pandit, Jaideep J.
Format Journal Article
LanguageEnglish
Published Singapore Springer Nature Singapore 16.10.2024
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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.
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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
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10.1080/00031305.1993.10475997
10.1111/j.1365-2044.2008.05854.x
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10.1016/j.jclinane.2019.06.013
10.1111/j.1365-2044.2012.07160.x
10.1007/BF00996639
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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
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JJ Pandit (73_CR34) 2012; 67
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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
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O Faiz (73_CR6) 2008; 8
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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
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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...
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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
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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
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