COVID-19, deaths at home and end-of-life cancer care.

During the COVID-19 pandemic there was a period of high excess deaths from cancer at home as opposed to in hospitals or in care homes. In this paper we aim to explore whether healthcare utilisation trajectories of cancer patients in the final months of life during the COVID-19 pandemic reveal any potential unmet healthcare need. We use English hospital records linked to data on all deaths in and out of hospital which identifies the cause and location of death. Our analysis shows that during the periods of peak COVID-19 caseload, patients dying of cancer experienced up to 42% less hospital treatment in their final month of life compared to historical controls. We find reductions in end-of-life hospital care for cancer patients dying in hospitals, care homes/hospices and at home, however the effect is amplified by the shift to more patients dying at home. Through the first year of the pandemic in England, we estimate the number of inpatient bed-days for end-of-life cancer patients in their final month reduced by approximately 282,282, or 25%. For outpatient appointments in the final month of life we find a reduction in face-to-face appointments and an increase in remote appointments which persists through the pandemic year and is not confined only to the periods of peak COVID-19 caseload. Our results suggest reductions in care provision during the COVID-19 pandemic may have led to unmet need, and future emergency reorganisations of health care systems must ensure consistent care provision for vulnerable groups such as cancer patients.

The impact of the COVID-19 pandemic on cardiovascular disease prevention and corresponding geographical inequalities in England: interrupted time series analysis.

BACKGROUND: There has been disruption to the detection and management of those with hypertension and atrial fibrillation (AF) during the COVID-19 pandemic. This is likely to vary geographically and could have implications for future mortality and morbidity. We aimed to estimate the change in diagnosed prevalence, treatment and prescription indicators for AF and hypertension and assess corresponding geographical inequalities. METHODS: Using the Quality and Outcomes Framework (2016/17 to 2021/22) and the English Prescribing Datasets (2018 to 2022), we described age standardised prevalence, treatment and prescription item rates for hypertension and AF by geography and over time. Using an interrupted time-series (ITS) analysis, we estimated the impact of the pandemic (from April 2020) on missed diagnoses and on the percentage change in medicines prescribed for these conditions. Finally, we described changes in treatment indicators against Public Health England 2029 cardiovascular risk targets. RESULTS: We observed 143,822 fewer (-143,822, 95%CI:-226,144, -61,500, p = 0.001) diagnoses of hypertension, 60,330 fewer (-60,330, 95%CI: -83,216, -37,444, p = 0.001) diagnoses of AF and 1.79% fewer (-1.79%, 95%CI: -2.37%, -1.22%), p < 0.0001) prescriptions for these conditions over the COVID-19 impact period. There was substantial variation across geography in England in terms of the indirect impact of the COVID-19 pandemic on the diagnosis, prescription, and treatment rates of hypertension and AF. 20% of Sub Integrated Care Boards account for approximately 62% of all missed diagnoses of hypertension. The percentage of individuals who had their hypertension controlled fell from 75.8% in 2019/20 to 64.1% in 2021/22 and the percentage of individuals with AF who were risk assessed fell from 97.2% to 90.7%. CONCLUSIONS: Hypertension and AF detection and management were disrupted during the COVID-19 pandemic. The disruption varied considerably across diseases and geography. This highlights the utility of administrative and geographically granular datasets to inform targeted efforts to mitigate the indirect impacts of the pandemic through applied secondary prevention measures.

How Denmark, England, Estonia, France, Germany, and the USA Pay for Variable, Specialized and Low Volume Care: A Cross-country Comparison of In-patient Payment Systems.

BACKGROUND: Diagnosis-related group (DRG)-based hospital payment can potentially be inadequately low (or high) for highly variable, highly specialized, and/or low volume care. DRG-based payment can be combined with other payment mechanisms to avoid unintended consequences of inadequate payment. The aim of this study was to analyze these other payment mechanisms for acute inpatient care across six countries (Germany, Denmark, England, Estonia, France, the United States [Medicare]). METHODS: Information was collected about elements excluded from DRG-based payment, the rationale for exclusions, and payment mechanisms complementing DRG-based payment. A conceptual framework was developed to systematically describe, visualise and compare payment mechanisms across countries. RESULTS: Results show that the complexity of exclusion mechanisms and associated additional payment components differ across countries. England and Germany use many different additional mechanisms, while there are only few exceptions from DRG-based payment in the Medicare program in the United States. Certain areas of care are almost always excluded (eg, certain areas of cancer care or specialized pediatrics). Denmark and England use exclusion mechanisms to steer service provision for highly complex patients to specialized providers. CONCLUSION: Implications for researchers and policy-makers include: (1) certain areas of care might be better excluded from DRG-based payment; (2) exclusions may be used to incentivize the concentration of highly specialized care at specialized institutions (as in Denmark or England); (3) researchers may apply our analytical framework to better understand the specific design features of DRG-based payment systems.

Association between efficiency and quality of care of public healthcare facilities: Evidence from Pakistan.

BACKGROUND: Maternal and child health is an important component of the Sustainable Development Goals. Pakistan has one of the worst maternal and neonatal health outcomes in the world. This is despite significant health system investments across the country. AIMS: The objectives of this study are twofold. First, the study estimates the technical efficiency of the public healthcare facilities in Pakistan, defined as the number of obstetric deliveries compared to the number of medical specialists, nurses, and other health and non-health staff members. Second, the study evaluates the relationship between efficiency and quality of care; the latter is measured in terms of maternal and neonatal mortality. MATERIALS & METHODS: The data were taken from the Pakistan Health Facility Assessment Survey. Efficiency score was calculated for 843 public healthcare facilities, using Stochastic Frontier Analysis. We then used two-stage residual inclusion approach with bootstrapping to evaluate the relationship between efficiency and quality. RESULTS AND DISCUSSION: The average efficiency score was 0.48 (range: 0-1) and none of the public healthcare facilities were on the frontier, implying that efficiency gains can be made across the board. The relationship between efficiency and quality is found to be positive and statistically significant, that is, more efficient healthcare facilities also had lower rates of maternal and neonatal mortality. CONCLUSION: We conclude that more efficient public healthcare facilities also had lower mortality rates, probably due to better infrastructure and health system financing.

Paying for efficiency: Incentivising same-day discharges in the English NHS.

We study a pay-for-efficiency scheme that encourages hospitals to admit and discharge patients on the same calendar day when clinically appropriate. Since 2010, hospitals in the English NHS are incentivised by a higher price for patients treated as same-day discharge than for overnight stays, despite the former being less costly. We analyse administrative data for patients treated during 2006-2014 for 191 conditions for which same-day discharge is clinically appropriate - of which 32 are incentivised. Using difference-in-difference and synthetic control methods, we find that the policy had generally a positive impact with a statistically significant effect in 14 out of the 32 conditions. The median elasticity is 0.24 for planned and 0.01 for emergency conditions. Condition-specific design features explain some, but not all, of the differential responses.

How health policy shapes healthcare sector productivity? Evidence from Italy and UK.

The English (NHS) and the Italian (SSN) healthcare systems share many similar features: basic founding principles, financing, organization, management, and size. Yet the two systems have faced diverging policy objectives since 2000, which may have affected differently healthcare sector productivity in the two countries. In order to understand how different healthcare policies shape the productivity of the systems, we assess, using the same methodology, the productivity growth of the English and Italian healthcare systems over the period from 2004 to 2011. Productivity growth is measured as the rate of change in outputs over the rate of change in inputs. We find that the overall NHS productivity growth index increased by 10% over the whole period, at an average of 1.39% per year, while SSN productivity increased overall by 5%, at an average of 0.73% per year. Our results suggest that different policy objectives are reflected in differential growth rates for the two countries. In England, the NHS focused on increasing activity, reducing waiting times and improving quality. Italy focused more on cost containment and rationalized provision, in the hope that this would reduce unjustified and inappropriate provision of services.

Identifying positive deviants in healthcare quality and safety: a mixed methods study.

Objective Solutions to quality and safety problems exist within healthcare organisations, but to maximise the learning from these positive deviants, we first need to identify them. This study explores using routinely collected, publicly available data in England to identify positively deviant services in one region of the country. Design A mixed methods study undertaken July 2014 to February 2015, employing expert discussion, consensus and statistical modelling to identify indicators of quality and safety, establish a set of criteria to inform decisions about which indicators were robust and useful measures, and whether these could be used to identify positive deviants. Setting Yorkshire and Humber, England. Participants None - analysis based on routinely collected, administrative English hospital data. Main outcome measures We identified 49 indicators of quality and safety from acute care settings across eight data sources. Twenty-six indicators did not allow comparison of quality at the sub-hospital level. Of the 23 remaining indicators, 12 met all criteria and were possible candidates for identifying positive deviants. Results Four indicators (readmission and patient reported outcomes for hip and knee surgery) offered indicators of the same service. These were selected by an expert group as the basis for statistical modelling, which supported identification of one service in Yorkshire and Humber showing a 50% positive deviation from the national average. Conclusion Relatively few indicators of quality and safety relate to a service level, making meaningful comparisons and local improvement based on the measures difficult. It was possible, however, to identify a set of indicators that provided robust measurement of the quality and safety of services providing hip and knee surgery.

How should hospital reimbursement be refined to support concentration of complex care services?

The English National Health Service is promoting concentration of the treatment of patients with relatively rare and complex conditions into a limited number of specialist centres. If these patients are more costly to treat, the prospective payment system based on Healthcare Resource Groups (HRGs) may need refinement because these centres will be financially disadvantaged. To assess the funding implications of this concentration policy, we estimate the cost differentials associated with caring for patients that receive complex care and examine the extent to which complex care services are concentrated across hospitals and HRGs. We estimate random effects models using patient-level activity and cost data for all patients admitted to English hospitals during the 2013/14 financial year and construct measures of the concentration of complex services. Payments for complex care services need to be adjusted if they have large cost differentials and if provision is concentrated within a few hospitals. Payments can be adjusted either by refining HRGs or making top-up payments to HRG prices. HRG refinement is preferred to top-payments the greater the concentration of services among HRGs.

Productivity Growth in the English National Health Service from 1998/1999 to 2013/2014.

Productivity growth is a key measure against which National Health Service (NHS) achievements are judged. We measure NHS productivity growth as a set of paired year-on-year comparisons from 1998/1999-1999/2000 through 2012/2013-2013/2014, which are converted into a chained index that summarises productivity growth over the entire period. Our measure is as comprehensive as data permit and accounts for the multitude of diverse outputs and inputs involved in the production process and for regular revisions to the data used to quantify outputs and inputs. Over the full-time period, NHS output increased by 88.96% and inputs by 81.58%, delivering overall total factor productivity growth of 4.07%. Productivity growth was negative during the first two terms of Blair's government, with average yearly growth rate of -1.01% per annum (pa) during the first term (to 2000/2001) and -1.49% pa during the second term (2000/2001-2004/2005). Productivity growth was positive under Blair's third term (2004/2005-2007/2008) at 1.41% pa and under the Brown government (2007/2008-2010/2011), averaging 1.13% pa. Productivity growth remained positive under the Coalition (2010/2011-2013/2014), averaging 1.56% pa. © 2016 The Authors Health Economics Published by John Wiley & Sons Ltd.

Using Linked Electronic Health Records to Estimate Healthcare Costs: Key Challenges and Opportunities.

This paper discusses key challenges and opportunities that arise when using linked electronic health records (EHR) in health economics and outcomes research (HEOR), with a particular focus on estimating healthcare costs. These challenges and opportunities are framed in the context of a case study modelling the costs of stable coronary artery disease in England. The challenges and opportunities discussed fall broadly into the categories of (1) handling and organising data of this size and sensitivity; (2) extracting clinical endpoints from datasets that have not been designed and collected with such endpoints in mind; and (3) the principles and practice of costing resource use from routinely collected data. We find that there are a number of new challenges and opportunities that arise when working with EHR compared with more traditional sources of data for HEOR. These call for greater clinician involvement and intelligent use of sensitivity analysis.

Paying for the quantity and quality of hospital care: the foundations and evolution of payment policy in England.

Prospective payment arrangements are now the main form of hospital funding in most developed countries. An essential component of such arrangements is the classification system used to differentiate patients according to their expected resource requirements. In this article we describe the evolution and structure of Healthcare Resource Groups (HRGs) in England and the way in which costs are calculated for patients allocated to each HRG. We then describe how payments are made, how policy has evolved to incentivise improvements in quality, and how prospective payment is being applied outside hospital settings.