English Clinical Commissioning Groups Research Articles

P08 Preventing and managing urinary tract infections: using thematic analysis to explore interventions and strategies implemented by NHS commissioning organizations in English primary care, 2017–22

Abstract Objectives To identify and explore strategies, interventions and activities used by English Clinical Commissioning Groups (CCGs) to improve prevention and management of urinary tract infections (UTIs) from 2017–22. Methods Online questionnaires were sent to primary care chief nurses and medicines optimization leads via regional infection prevention control (IPC) and antimicrobial stewardship (AMS) leads August–September 2022. Qualitative data were mapped to the Theoretical Domains Framework. Results Response rate was 14.1% (56/397 participants approached), with representation from 29.2% (31/106) English CCGs. Respondents provided 201 examples of UTI interventions. Themes identified included: (i) populations and settings; (ii) aspects of UTI targeted; (iii) types and functions of interventions and activities; (iv) resources, tools and policies; and (v) implementation strategies. Education and training were the most used type of intervention, while changing the environment to facilitate ideal behaviours was the least used intervention type. Most interventions targeted general practice staff and patients accessing primary care, followed by care home staff and residents and their families. The most used success measures included reduction in antibiotic prescribing (54.5%, 97/178 intervention examples); positive feedback from stakeholders (42.1%, 75/178); and increased adherence to national diagnostic guidelines (32.6%, 58/178). However, 48.8% (20/41) stated their team’s UTI activities had not been evaluated, indicating that success was determined using informal data or perceived outcomes. Barriers to implementation of UTI interventions included: lack of resources and time; low staff engagement, inaccurate data due to lack of clinical coding; inconsistent systems and processes; and lack of dedicated roles. Facilitators to implementation included: availability of tools; financial incentives; multidisciplinary collaboration; sharing of information; staff motivation; embedding resources into systems; digitalization; and dedicated roles. Conclusions Multidisciplinary teams and cross-sector collaboration are key facilitators for implementation of UTI interventions. Although some teams are already using robust success measures, there is a need to improve how interventions are evaluated to inform resource allocation and planning. Education and training interventions should address or leverage the barriers and facilitators identified, including clinical coding skills, embedding resources and tools into existing systems and auditing adherence to diagnostic and antibiotic prescribing guidance. There may be missed opportunities for intervention types that are less widely used e.g. changing environmental factors.

A Model to Compare International Hospital Bed Numbers, including a Case Study on the Role of Indigenous People on Acute 'Occupied' Bed Demand in Australian States.

Comparing international or regional hospital bed numbers is not an easy matter, and a pragmatic method has been proposed that plots the number of beds per 1000 deaths versus the log of deaths per 1000 population. This method relies on the fact that 55% of a person’s lifetime hospital bed utilization occurs in the last year of life—irrespective of the age at death. This is called the nearness to death effect. The slope and intercept of the logarithmic relationship between the two are highly correlated. This study demonstrates how lines of equivalent bed provision can be constructed based on the value of the intercept. Sweden looks to be the most bed-efficient country due to long-term investment in integrated care. The potential limitations of the method are illustrated using data from English Clinical Commissioning Groups. The main limitation is that maternity, paediatric, and mental health care do not conform to the nearness to death effect, and hence, the method mainly applies to adult acute care, especially medical and critical care bed numbers. It is also suggested that sensible comparison can only be made by comparing levels of occupied beds rather than available beds. Occupied beds measure the expressed bed demand (although often constrained by access to care issues), while available beds measure supply. The issue of bed supply is made complex by the role of hospital size on the average occupancy margin. Smaller hospitals are forced to operate at a lower average occupancy; hence, countries with many smaller hospitals such as Germany and the USA appear to have very high numbers of available beds. The so-called 85% occupancy rule is an “urban myth” and has no fundamental basis whatsoever. The very high number of “hospital” beds in Japan is simply an artefact arising from “nursing home” beds being counted as a “hospital” bed in this country. Finally, the new method is applied to the expressed demand for occupied acute beds in Australian states. Using data specific to acute care, i.e., excluding mental health and maternity, a long-standing deficit of beds was identified in Tasmania, while an unusually high level of occupied beds in the Northern Territory (NT) was revealed. The high level of demand for beds in the NT appears due to an exceptionally large population of indigenous people in this state, who are recognized to have elevated health care needs relative to non-indigenous Australians. In this respect, indigenous Australians use 3.5 times more occupied bed days per 1000 deaths (1509 versus 429 beds per 1000 deaths) and 6 times more occupied bed days per 1000 population (90 versus 15 beds per 1000 population) than their non-indigenous counterparts. The figure of 1509 beds per 1000 deaths (or 4.13 occupied beds per 1000 deaths) for indigenous Australians is indicative of a high level of “acute” nursing care in the last months of life, probably because nursing home care is not readily available due to remoteness. A lack of acute beds in the NT then results in an extremely high average bed occupancy rate with contingent efficiency and delayed access implications.

Outsourcing of health-care services to the private sector by English Clinical Commissioning Groups and mortality rates, 2013–20: an observational analysis

BackgroundOutsourcing services to for-profit organisations within a publicly funded health-care service, which runs alongside private provision in a two-tier system, aims to increase competition between health-care providers, driving up their performance. However, there are concerns that this approach might lead to cost-cutting by for-profit providers and poorer outcomes for patients. We aimed to assess whether increased outsourcing to the private sector is associated with changes to treatable mortality rates, and, therefore, with quality of health care. MethodsWe constructed a database compiling every procurement contract over 7 years (2013–2020; n=647 541, total value £204·1 bn) across England's 173 Clinical Commissioning Groups (regional health boards). We identified institutions registered with Companies House that supplied regional commissioners in England's NHS and aggregated this information with local mortality data for each year. By analysing the different changes to commissioners' spend on private sector providers, we estimated the association between outsourcing and the following years' age-standardised treatable mortality rates (deaths that can be mainly avoided through timely and effective health-care interventions, including secondary prevention and treatment). We accounted for year and individual fixed effects and controlled for multiple covariates, including average household income, Local Authority spending, and population demographics. FindingsAverage levels of outsourcing increased over this period, from 4·9% of the £14·8 billion total spend from April to December, 2013 to 6·8% of the £5·0 billion recorded in the first three months of 2020, but the extent of change varied substantially between regional commissioners. An annual increase of one percentage point of outsourcing to the private sector corresponded with an annual increase in treatable mortality in the following year of 0·34% (95% CI 0·12–0·55; p=0·0080), or 0·23 deaths per 100 000 population (from a mean population of 275 840 per commissioning group). InterpretationThe incorporation of private sector providers into England's NHS appears to correspond with a decline in the quality of health-care services. Strengths of this research lie in the novel dataset, which enables longitudinal evaluation of outsourcing. Unfortunately, precise mechanisms driving our finding are hard to isolate because the services delivered by providers and their case mix are not recorded in the contract and mortality data. FundingWellcome Trust.

Were the hospital bed reductions proposed by English Clinical Commissioning Groups (CCGs) in the sustainability and transformation plans (STPs) achievable? Insights from a new model to compare international bed numbers.

A new model for hospital bed numbers which adjusts for end-of-life care and age structure is used to demonstrate that England has 20% fewer occupied beds than the other countries in the United Kingdom. It also shows that occupied beds in English Clinical Commissioning Groups (CCGs) lie parallel to a line of equivalence with New Zealand and Singapore. This is despite New Zealand and Singapore having invested many years into developing integrated care, while England has not. In addition, England has around half the number of nursing home beds per death available in these two countries. Large bed reductions proposed in the sustainability and transformation plans were likely to have been manipulated to meet financial cost-saving targets rather than a result of genuine modelling of demand. The ways in which bed demand models can be manipulated to give whatever answer is required are discussed. Trends in occupied acute medical beds in England over the past 20 years show no real reduction, despite a large reduction in available beds. This has resulted in daytime occupancy for adult beds being close to 100% and with resulting queues to admission. The ways to improve the small-area application of the model including the use of deprivation or social groups are discussed.

The place for dementia-friendly communities in England and its relationship with epidemiological need.

ObjectivesThe dementia‐friendly community (DFC) initiative was set up to enable people living with dementia to remain active, engaged, and valued members of society. Dementia prevalence varies nationally and is strongly associated with the age and sex distribution of the population and level of social deprivation. As part of a wider project to evaluate DFCs, we examined whether there is a relationship between provision of DFCs and epidemiological need.MethodsDementia‐friendly communities were identified through the formal recognition process of DFC status by the Alzheimer's Society and mapped against areas defined by English Clinical Commissioning Groups. We tested whether provision of a DFC was associated with: (1) dementia prevalence, (2) number of known cases, and (3) known plus estimated number of unknown cases.ResultsOf the 209 English Clinical Commissioning Group areas, 115 had at least one DFC. The presence of a DFC was significantly associated with number of known dementia cases (mean difference = 577; 95% CI, 249 to 905; P = 0.001) and unknown dementia cases (mean difference = 881; 95% CI, 349 to 1413; P = 0.001) but not prevalence (mean difference = 0.03; 95% CI, −0.09 to 0.16; P = 0.61). This remains true when controlling for potential confounding variables.ConclusionsOur findings suggest that DFC provision is consistent with epidemiological‐based need. Dementia‐friendly communities are located in areas where they can have the greatest impact. A retrospective understanding of how DFCs have developed in England can inform how equivalent international initiatives might be designed and implemented.

Detecting change in comparison to peers in NHS prescribing data: a novel application of cumulative sum methodology

BackgroundThe widely used OpenPrescribing.net service provides standard measures which compare prescribing of Clinical Commissioning Groups (CCGs) and English General Practices against that of their peers. Detecting changes in prescribing behaviour compared with peers can help identify missed opportunities for medicines optimisation. Automating the process of detecting these changes is necessary due to the volume of data, but challenging due to variation in prescribing volume for different measures and locations. We set out to develop and implement a method of detecting change on all individual prescribing measures, in order to notify CCGs and practices of such changes in a timely manner.MethodsWe used the statistical process control method CUSUM to detect prescribing behaviour changes in relation to population trends for the individual standard measures on OpenPrescribing. Increases and decreases in percentile were detected separately, using a multiple of standard deviation as the threshold for detecting change. The algorithm was modified to continue re-triggering when trajectory persists. It was deployed, user-tested, and summary statistics generated on the number of alerts by CCG and practice.ResultsThe algorithm detected changes in prescribing for 32 prespecified measures, across a wide range of CCG and practice sizes. Across the 209 English CCGs, a mean of 2.5 increase and 2.4 decrease alerts were triggered per CCG, per month. For the 7578 practices, a mean of 1.3 increase and 1.4 decrease alerts were triggered per practice, per month.ConclusionsThe CUSUM method appears to effectively discriminate between random noise and sustained change in prescribing behaviour. This method aims to allow practices and CCGs to be informed of important changes quickly, with a view to improve their prescribing behaviour. The number of alerts triggered for CCGs and practices appears to be appropriate. Prescribing behaviour after users are alerted to changes will be monitored in order to assess the impact of these alerts.

Emollient prescribing formularies in England and Wales: a cross-sectional study

ObjectiveTo identify and compare emollient formularies across all clinical commissioning groups (CCGs) and local health boards (LHBs) in England and Wales.DesignFormularies were retrieved via CCG/LHB websites or Google search (October...

Growth in NHS admissions and length of stay: A policy-based evidence fiasco

Growth in NHS admissions and length of stay: A policy-based evidence fiasco

The Effects of Environmental Factors on the Efficiency of Clinical Commissioning Groups in England: A Data Envelopment Analysis

Clinical Commissioning Groups (CCGs) were created in 2013 to make the NHS more responsive, efficient and accountable. A large number of different indicators can be used to measure the quality and outcomes of services provided by CCGs, however there is currently no single measure of overall efficiency available. The performance of CCGs may also be confounded by environmental factors such as deprivation, population size and burden of disease. Data Envelopment Analysis (DEA) is a linear programming technique that can be used to measure the relative efficiency of a given set of organisations. To use DEA to measure the efficiency of English CCGs and assess the impact of environmental factors. This study estimates the technical efficiency of 208 CCGs in England using DEA. The inputs and outputs used include budget allocation, number of general practitioners, mortality rates, patient satisfaction and Quality and Outcomes Framework achievement scores. Regression analysis is used to assess the effects of environmental factors on efficiency, such as population size, prevalence of disease, and socio-economic status. Twenty-three percent (47/208) of CCGs were efficient compared to the others. Three environmental factors were statistically significant predictors of efficiency: CCGs with smaller population sizes were more efficient than those with larger ones, while high unemployment rates and a high prevalence of chronic obstructive pulmonary disease led to a decrease in efficiency scores. Comparative deprivation was not a significant predictor of efficiency. The finding that the relationship between deprivation and efficiency is not statistically significant suggests that NHS England’s adjustment for environmental factors within the CCG-level budget allocation is broadly successful. This study shows the potential of DEA for assessing technical efficiency at CCG-level in the English NHS.

P3.07-011 Geographical Variation in the Use of Radiotherapy and Surgical Resection for Treatment of Non-Small Cell Lung Cancer in England: Topic: Other – Geographical Differences

Despite global improvements in survival non-small cell lung cancer (NSCLC) remains lethal, with 20% five year survival in a limited number of developed nations. Fit, early stage NSCLC patients can be offered curative treatment, using surgery or radical radiotherapy. Geographical variation in surgery usage in England has previously been demonstrated. We aimed to further investigate this variation, incorporating all curative treatments and considering associated survival. Information on 143,886 patients diagnosed with a first NSCLC between April 2009 and December 2013 in England was extracted from the national cancer registration dataset linked to radiotherapy treatment and Hospital Episode Statistics data. In England Clinical Commissioning Groups (CCG) are the statutory bodies responsible for the planning and commissioning of health care services for their local area. We calculated the proportion of patients receiving curative treatment in each CCG, and created quintiles from the resulting distribution. Logistic regression was used to assess the effect of age, sex, stage, comorbidity, performance status and socio-economic deprivation on curative treatment usage. Multivariable Cox regression models were used to analyze survival in relation to curative treatment quintile. Overall, 29,580 (20.6%) NSCLC patients received curative treatment: 20,177 (14.0%) NSCLC patients underwent resection and 9,403 (6.5%) received radical radiotherapy. The proportion of patients receiving curative treatments ranged from 11.8% to 31.7% across English CCGs and decreased with advancing age (p < 0.001), increasing stage (p < 0.001) and worsening performance status (p < 0.001). The proportion of patients receiving curative treatment was greater for females compared with males (p < 0.001). The absolute risk of dying within 5 years ranged from 90% in the lowest treatment quintile to 85% in the highest. Increasing curative treatment rates were associated with lower mortality (p < 0.001), with an adjusted HR of 0.93 (95% CI 0.92 to 0.95) in the highest treatment quintile compared with the lowest. Despite adjustment for case-mix variables we demonstrated that significant variation in the use of curative treatment for NSCLC persists across CCGs with increasing curative treatment rates associated with lower mortality. There is a need to further explore the factors driving this variation in order to guide changes in care which may deliver improved outcomes.

PHS137 - English CCG Formularies: Resources And Priorities

Commissioners working in English clinical commissioning groups (CCGs) were surveyed to understand the processes for evaluating local formulary submissions for new drugs, the stakeholders involved and the expertise of stakeholders involved. Commissioners subscribing to The Commissioning Review and who had a valid NHS email address were invited to take an online survey open between 12 June and 12 July 2016. The survey included ten questions and all participants were entered in a prize draw for a £100 Amazon voucher as a thank you for their participation. Preliminary findings show most local formulary decision-making group regularly collaborate with similar groups in other CCGs. Patient or patient-representative groups are represented on, or consulted by, most local formulary groups. Interestingly, such groups were reportedly consulted more frequently than clinical groups and networks during decisions relating to local formulary submissions. Cost effectiveness and budget impact estimates are important factors when deciding whether or not to include new drugs on the formulary. Health economic estimates derived using CCG specific data were considered more frequently than estimates derived from national data. Many, but not all, CCGs conduct their own cost-effectiveness and budget impact assessments. However, only half of respondents indicated that a member of their CCG’s local formulary decision making group had formal training in how to conduct literature reviews or appraise systematic reviews or clinical data. The processes for deciding on inclusion of a new drug on a local formulary vary between CCGs. Regional data are considered more important than national data. However, only half of respondents reported that a member of their local formulary group has received formal training in how to evaluate data forming part of submissions.

Declining length of stay and future bed numbers

British Journal of Healthcare ManagementVol. 21, No. 9 Money MattersDeclining length of stay and future bed numbersRod JonesRod JonesSearch for more papers by this authorRod JonesPublished Online:24 Sep 2015https://doi.org/10.12968/bjhc.2015.21.9.440AboutSectionsView articleView Full TextPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareShare onFacebookTwitterLinked InEmail View article References Advisory Board Company International (2009) Next-generation capacity management: Collaborating for clinically appropriate and efficient inpatient throughput. Available at: https://www.advisory.com/International/Research/Clinical-Operations-Board/Studies/2010/Next-Generation-Capacity-Management (accessed 27 August 2015) Google ScholarJones R (2009) Emergency admissions and hospital beds. BJHCM 15(6): 289–96 Google ScholarJones R (2009) Length of stay efficiency. BJHCM 15(11): 563–4 Google ScholarJones R (2010) Benchmarking length of stay. BJHCM 16(5): 248–50 Google ScholarJones R (2011) Does hospital bed demand depend more on death than demography? BJHCM 17(5): 190–7 Google ScholarJones R (2011) Hospital bed occupancy demystified. BJHCM 17(6): 242–48 Google ScholarJones R (2011) A&E performance and inpatient bed occupancy. BJHCM 17(6): 256–7 Google ScholarJones R (2011) Bed occupancy – the impact on hospital planning. BJHCM 17(7): 307–13 Google ScholarJones R (2011) Factors influencing demand for hospital beds in English Primary Care Organisations. BJHCM 17(8): 360–7 Google ScholarJones R (2011) A paradigm shift for bed occupancy. BJHCM 17(8): 376–7 Google ScholarJones R (2011) Volatility in bed occupancy for emergency admissions. BJHCM 17(9): 424–30 Google ScholarJones R (2013) Optimum bed occupancy in psychiatric hospitals. Psychiatry On-Line Available at: http://www.priory.com/psychiatry/psychiatric_beds.htm (accessed 27 August 2015) Google ScholarJones R (2013) The NHS England review of urgent and emergency care. BJHCM 19(8): 406–7 Google ScholarJones R (2014) Medical bed occupancy and cancelled operations. BJHCM 20(12): 594–5 Google ScholarJones R (2015) Is length of stay a reliable efficiency measure? BJHCM 21(7): 344–5 Google Scholar FiguresReferencesRelatedDetailsCited byWere the hospital bed reductions proposed by English Clinical Commissioning Groups (CCGs) in the sustainability and transformation plans (STPs) achievable? Insights from a new model to compare international bed numbers11 December 2020 | The International Journal of Health Planning and Management, Vol. 36, No. 2 2 September 2015Volume 21Issue 9ISSN (print): 1358-0574ISSN (online): 1759-7382 Metrics History Published online 24 September 2015 Published in print 2 September 2015 Information© MA Healthcare LimitedPDF download