Could the rise in mortality rates since 2015 be explained by changes in the number of delayed discharges of NHS patients?

A decade of outsourcing in health and social care in England: What was it meant to achieve?

The increased private provision of publicly funded health and social care over the last 75 years has been one of the most contentious topics in UK public policy. In the last decades, health and social care policies in England have consistently promoted the outsourcing of public services to private for-profit and non-profit companies with the assumption that private sector involvement will reduce costs and improve service quality and access. However, it is not clear why outsourcing often fails to improve quality of care, and which of the underlying assumptions behind marketising care are not supported by research. This article provides an analysis of key policy and regulatory documents preceding or accompanying outsourcing policies in England (e.g., policy document relating to the 2012 and 2022 Health and Social Care Acts and the 2014 Care Act), and peer-reviewed research on the impact of outsourcing within the NHS, adult's social care, and children's social care. We find that more regulation and market oversight appear to be associated with less poor outcomes and slower growth of for-profit provision. However, evidence on the NHS suggests that marketisation does not seem to achieve the intended objectives of outsourcing, even when accompanied with heavy regulation and oversight. Our analysis suggests that there is little evidence to show that the profit motive can be successfully tamed by public commissioners. This article concludes with how policymakers should address, or readdress, the underlying assumptions behind the outsourcing of care services.

How International Health System Austerity Responses to the 2008 Financial Crisis Impacted Health System and Workforce Resilience - A Realist Review

BACKGROUND

The Great Recession, following the 2008 financial crisis, led many governments to adopt programmes of austerity. This had a lasting impact on health system functionality, resources, staff (numbers, motivation and morale) and patient outcomes. This study aimed to understand how health system resilience was impacted and how this affects readiness for subsequent shocks.

METHODS

A realist review identified legacies associated with austerity (proximal outcomes) and how these impact the distal outcome of health system resilience. EMBASE, CINAHL, MEDLINE, EconLit and Web of Science were searched (2007-May 2021), resulting in 1081 articles. Further theory-driven searches resulted in an additional 60 studies. Descriptive, inductive, deductive and retroductive realist analysis (utilising excel and Nvivo) aided the development of context-mechanism-outcome configurations (CMOCs), alongside stakeholder engagement to confirm or refute emerging results. Causal pathways, and the interplay between context and mechanisms that led to proximal and distal outcomes, were revealed. The refined CMOCs and policy recommendations focused primarily on workforce resilience.

RESULTS

Five CMOCs demonstrated how austerity-driven policy decisions can impact health systems when driven by the priorities of external agents. This created a real or perceived shift away from the values and interests of health professionals, a distrust in decision-making processes and resistance to change. Their values were at odds with the realities of implementing such policy decisions within sustained restrictive working conditions (rationing of staff, consumables, treatment options). A diminished view of the profession and an inability to provide high-quality, equitable, and needs-led care, alongside stagnant or degraded working conditions, led to moral distress. This can forge legacies that may adversely impact resilience when faced with future shocks.

CONCLUSION

This review reveals the importance of transparent, open communication, in addition to co-produced policies in order to avoid scenarios that can be detrimental to workforce and health system resilience.

The influence of home care supply on delayed discharges from hospital in England

BACKGROUND

Delayed transfers of care (DTOC) of patients from hospital to alternative care settings are a longstanding problem in England and elsewhere, having negative implications for patient outcomes and costs to health and social care systems. In England, a large proportion of DTOC are attributed to a delay in receiving suitable home care. We estimated the relationship between home care supply and delayed discharges in England from 2011 to 2016.

METHODS

Reduced form fixed effects OLS models of annual DTOC attributed to social care at local authority (LA)-level from 2011 to 2016 were estimated, using both number of days and patients as the dependent variable. A count of home care providers at LA-level was utilised as the measure of home care supply. Demand (e.g. population, health, income) and alternative supply (e.g. care home places, local unemployment) measures were included as controls. Instrumental Variable (IV) methods were used to control for any simultaneity in the relationship between DTOC and home care supply. Models for DTOC attributed to NHS and awaiting a home care package were used to assess the adequacy of the main model.

RESULTS

We found that home care supply significantly reduced DTOC. Each extra provider per 10 sq. km. in the average local authority decreased DTOC by 14.9% (equivalent to 449 days per year), with a per provider estimate of 1.6% (48 days per year). We estimated cost savings to the public sector over the period of analysis from reduced DTOC due to increased home care provision between £73 m and £274 m (95% CI: £0.24 m to £545.3 m), with a per provider estimate of savings per year of £12,600 (95% CI: £900 to £24,500).

CONCLUSION

DTOC are reduced in LAs with better supply of home care, and this reduces costs to the NHS. Further savings could be achieved through improved outcomes of people no longer delayed. Appropriate levels of social care supply are required to ensure efficiency in spending for the public sector overall.

Pre-stroke disability and stroke severity as predictors of discharge destination from an acute stroke ward

BACKGROUND AND RATIONALE

Reliable prediction of discharge destination in acute stroke informs discharge planning and can determine the expectations of patients and carers. There is no existing model that does this using routinely collected indices of pre-morbid disability and stroke severity.

METHODS

Age, gender, pre-morbid modified Rankin Scale (mRS) and National Institutes of Health Stroke Scale (NIHSS) were gathered prospectively on an acute stroke unit from 1,142 consecutive patients. A multiclass random forest classifier was used to train and validate a model to predict discharge destination.

RESULTS

Used alone, the mRS is the strongest predictor of discharge destination. The NIHSS is only predictive when combined with our other variables. The accuracy of the final model was 70.4% overall with a positive predictive value (PPV) and sensitivity of 0.88 and 0.78 for home as the destination, 0.68 and 0.88 for continued inpatient care, 0.7 and 0.53 for community hospital, and 0.5 and 0.18 for death, respectively.

CONCLUSION

Pre-stroke disability rather than stroke severity is the strongest predictor of discharge destination, but in combination with other routinely collected data, both can be used as an adjunct by the multidisciplinary team to predict discharge destination in patients with acute stroke.

Why were there 231 707 more deaths than expected in England between 2010 and 2018? An ecological analysis of mortality records

BACKGROUND

Policy responses to the Global Financial Crisis emphasized wide-ranging fiscal austerity measures, many of which have been found to negatively impact health outcomes. This paper investigates change in patterns of mortality at local authority level in England (2010-11 to 2017-18) and the relation with fiscal austerity measures.

METHODS

Data from official local authority administrative records are used to quantify the gap between observed deaths and what was anticipated in the 2010-based subnational population projections. Regression analyses are used to explore the relation between excess deaths, austerity and wider process of population change at local authority level.

RESULTS

We estimate 231 707 total excess deaths, the majority of which occurred since 2014-15 (89%) across the majority of local authorities (91%). Austerity is positively associated with excess deaths. For working age adults, there is a clear gradient to the impact of austerity, whereas for older adults, the impact is more uniform.

CONCLUSIONS

Fiscal austerity policies contributed to an excess of deaths for older people and widened social inequalities for younger populations. These results call for an end to all austerity measures and require further research into areas with the highest total excess deaths as a priority following the COVID-19 pandemic.

Delayed discharge after major surgical procedures in Ontario, Canada: a population-based cohort study

BACKGROUND

Addressing nonmedical reasons for delays in hospital discharge is important for improving the flow of patients through acute care hospital beds. Because this problem is understudied among adult surgical patients, we examined the incidence of and identified factors associated with delayed hospital discharge after major elective and emergency surgical procedures in acute care institutions.

METHODS

Using health administrative data, we retrospectively compared adults with and without delayed discharge after 18 major elective and emergency surgical procedures between 2006 and 2016 in Ontario hospitals. We identified delayed discharge using the alternate level of care code, applied to patients who are medically fit for discharge but remain in an acute care hospital bed. We used hierarchical logistic regression modelling to determine factors associated with delayed discharge.

RESULTS

Our cohort included 595 782 patients who underwent elective procedures and 180 478 who underwent emergency procedures. Delayed discharge accounted for 635 607 hospital days, of which 81.7% were related to admissions for emergency surgery. Delayed discharge affected 3.1% of patients who underwent elective surgery and 19.6% of those who underwent emergency procedures. Days attributed to delayed discharge formed about one-third of patients' total hospital stay for both surgical groups. The rate of delayed discharge across surgical specialties showed high variability (from 0.9% for lung resection or nephrectomy to 9.3% for peripheral arterial disease procedures in the elective surgery group, and from 3.8% for cardiac procedures to 33.8% for peripheral arterial disease procedures in the emergency surgery group). Risk factors for delayed discharge were older age, female sex, chronic disease burden and increasing hospital size.

INTERPRETATION

Delayed discharge for nonmedical reasons was more common after emergency surgery than after elective surgery, and rates varied across surgery type. Optimizing early discharge planning, evaluating the variation in delayed discharge at the hospital level and improving local access to community care services could be next steps to addressing this problem.

Can changes in spending on health and social care explain the recent mortality trends in Scotland? A protocol for an observational study

INTRODUCTION

There have been steady reductions in mortality rates in the majority of high-income countries, including Scotland, since 1945. However, reductions in mortality rates have slowed down since 2012-2014 in these nations; and have reversed in some cases. Deaths among those aged 55+ explain a large amount of these changing mortality trends in Scotland. Increased pressures on health and social care services have been suggested as one factor explaining these changes. This paper outlines a protocol for the approach to testing the extent to which health and social care pressures can explain recent mortality trends in Scotland. Although a slower rate of mortality improvements have affected people of all ages, certain ages have been more negatively affected than the others. The current analyses will be run by age-band to test if the service pressure-mortality link varies across age-group.

METHODS AND ANALYSIS

This will be an observational ecological study based on the Scottish population. The exposures of interest will be the absolute (primary outcome) and percentage (secondary outcome) change in real terms per capita spending on social and healthcare services between 2011 and 2017. The outcome of interest will be the absolute (primary outcome) and percentage (secondary outcome) change in age-standardised mortality rate between 2012 and 2018 for men and women separately. The units of analysis will be the 32 local authorities and the 14 territorial health boards. The analyses will be run for both all age-groups combined and for the following age bands: <1, 1-15, 16-44, 45-64, 65-74, 75-84 and 85+.A series of descriptive analyses will summarise the distribution of health and social care expenditure and mortality trends between 2011 and 2018. Linear regression analysis will be used to investigate the direct association between health care spending and mortality rates.

ETHICS AND DISSEMINATION

The data used in this study will be publicly available and aggregated and will not be individually identifiable; therefore, ethical committee approval is not needed. This work will not result in the creation of a new data set. On completion, the study will be stored within the National Health Service research governance system. All of the results will be published once they have been shared with partner agencies.

Life Expectancy: Frequently Used, but Hardly Understood

Period life expectancy is one of the most used summary indicators for the overall health of a population. Its levels and trends direct health policies, and researchers try to identify the determining risk factors to assess and forecast future developments. The use of period life expectancy is often based on the assumption that it directly reflects the mortality conditions of a certain year. Accordingly, the explanation for changes in life expectancy are typically sought in factors that have an immediate impact on current mortality conditions. It is frequently overlooked, however, that this indicator can also be affected by at least three kinds of effects, in particular in the situation of short-term fluctuations: cohort effects, heterogeneity effects, and tempo effects. We demonstrate their possible impact with the example of the almost Europe-wide decrease in life expectancy in 2015, which caused a series of reports about an upsurge of a health crisis, and we show that the consideration of these effects can lead to different conclusions. Therefore, we want to raise an awareness concerning the sensitivity of life expectancy to sudden changes and the menaces a misled interpretation of this indicator can cause.

Recent trends in life expectancy across high income countries: retrospective observational study

OBJECTIVES

To assess whether declines in life expectancy occurred across high income countries during 2014-16, to identify the causes of death contributing to these declines, and to examine the extent to which these declines were driven by shared or differing factors across countries.

DESIGN

Demographic analysis using aggregated data.

SETTING

Vital statistics systems of 18 member countries of the Organisation for Economic Co-operation and Development.

PARTICIPANTS

18 countries with high quality all cause and cause specific mortality data available in 2014-16.

MAIN OUTCOME MEASURES

Life expectancy at birth, 0-65 years, and 65 or more years and cause of death contributions to changes in life expectancy at birth.

RESULTS

The majority of high income countries in the study experienced declines in life expectancy during 2014-15; of the 18 countries, 12 experienced declines in life expectancy among women and 11 experienced declines in life expectancy among men. The average decline was 0.21 years for women and 0.18 years for men. In most countries experiencing declines in life expectancy, these declines were predominantly driven by trends in older age (≥65 years) mortality and in deaths related to respiratory disease, cardiovascular disease, nervous system disease, and mental disorders. In the United States, declines in life expectancy were more concentrated at younger ages (0-65 years), and drug overdose and other external causes of death played important roles in driving these declines.

CONCLUSIONS

Most of the countries that experienced declines in life expectancy during 2014-15 experienced robust gains in life expectancy during 2015-16 that more than compensated for the declines. However, the United Kingdom and the United States appear to be experiencing stagnating or continued declines in life expectancy, raising questions about future trends in these countries.

Why is life expectancy in England and Wales 'stalling'?

Several independent analyses, by both epidemiologists and actuaries, have concluded that the previous rate of improvement of life expectancy in England and Wales has now slowed markedly, and at older ages may even be reversing. However, although these findings have led the pension industry to reduce estimates of future liabilities, they have failed to elicit any significant concern in the Department of Health and Social Care. In this essay, we review the evidence on changing life expectancy, noting that the problems are greatest among older women. We then estimate the gap between what life expectancy is now and what it might have been had previous trends continued. At age 85, the gap is 0.34 years for women and 0.23 for men. We argue that recent changes cannot be dismissed as a temporary aberration. While the causes of this phenomenon are contested, there is growing evidence to point to the austerity policies implemented in recent years as at least a partial explanation. We conclude by calling for a fully independent enquiry to ascertain what is happening to life expectancy in England and Wales and what should be done about it.