Impact of prevention in primary care on costs in primary and secondary care for people with serious mental illness.

A largely unexplored part of the financial incentive for physicians to participate in preventive care is the degree to which they are the residual claimant from any resulting cost savings. We examine the impact of two preventive activities for people with serious mental illness (care plans and annual reviews of physical health) by English primary care practices on costs in these practices and in secondary care. Using panel two-part models to analyze patient-level data linked across primary and secondary care, we find that these preventive activities in the previous year are associated with cost reductions in the current quarter both in primary and secondary care. We estimate that there are large beneficial externalities for which the primary care physician is not the residual claimant: the cost savings in secondary care are 4.7 times larger than the cost savings in primary care. These activities are incentivized in the English National Health Service but the total financial incentives for primary care physicians to participate were considerably smaller than the total cost savings produced. This suggests that changes to the design of incentives to increase the marginal reward for conducting these preventive activities among patients with serious mental illness could have further increased welfare.

Labor supply and informal care responses to health shocks within couples: Evidence from the UK.

Shocks to health have been shown to reduce labor supply for the individual affected. Less is known about household self-insurance through a partner's response. Previous studies have presented inconclusive empirical evidence on the existence of a health-related Added Worker Effect, and results limited to labor and income responses. We use UK longitudinal data to investigate within households both the labor supply and informal care responses of an individual to the event of an acute health shock to their partner. Relying on the unanticipated timing of shocks, we combine Coarsened Exact Matching and Entropy Balancing algorithms with parametric analysis and exploit lagged outcomes to remove bias from observed confounders and time-invariant unobservables. We find no evidence of a health-related Added Worker Effect but a significant and sizable Informal Carer Effect. This holds irrespective of spousal labor market position or household financial status and ability to purchase formal care provision, suggesting that partners' substitute informal care provision for time devoted to leisure activities.

Exploring mental health disability gaps in the labour market: the UK experience during COVID-19.

People with long-term mental health problems that affect their daily activities are a growing proportion of the UK working population and they have a particularly low employment rate. We analyse gaps in labour market outcomes between mental health disabled and non-disabled people during the COVID-19 pandemic in the UK. We also decompose the outcome gaps in order to explore the relative importance of different factors in explaining these gaps. Our results suggest that the employment effects of the pandemic for mental health disabled people may have been temporary. However, they were more likely to be away from work and/or working reduced hours than people without a disability. Workers with mental health disability were over-represented in part-time work and in caring, leisure and other service occupations, which were disproportionately affected by COVID-19 and the economic response. This is important new evidence on the contribution of segmentation and segregation in explaining the labour market position of people with mental health disability. The longer term effects of the pandemic were still not apparent at the end of our analysis period (2021:Q3), but the concentration of disabled workers in cyclically sensitive sectors and part-time work means that they will always be particularly vulnerable to economic downturns.

Multimorbidity combinations, costs of hospital care and potentially preventable emergency admissions in England: A cohort study.

BACKGROUND: Patients with multimorbidities have the greatest healthcare needs and generate the highest expenditure in the health system. There is an increasing focus on identifying specific disease combinations for addressing poor outcomes. Existing research has identified a small number of prevalent "clusters" in the general population, but the limited number examined might oversimplify the problem and these may not be the ones associated with important outcomes. Combinations with the highest (potentially preventable) secondary care costs may reveal priority targets for intervention or prevention. We aimed to examine the potential of defining multimorbidity clusters for impacting secondary care costs. METHODS AND FINDINGS: We used national, Hospital Episode Statistics, data from all hospital admissions in England from 2017/2018 (cohort of over 8 million patients) and defined multimorbidity based on ICD-10 codes for 28 chronic conditions (we backfilled conditions from 2009/2010 to address potential undercoding). We identified the combinations of multimorbidity which contributed to the highest total current and previous 5-year costs of secondary care and costs of potentially preventable emergency hospital admissions in aggregate and per patient. We examined the distribution of costs across unique disease combinations to test the potential of the cluster approach for targeting interventions at high costs. We then estimated the overlap between the unique combinations to test potential of the cluster approach for targeting prevention of accumulated disease. We examined variability in the ranks and distributions across age (over/under 65) and deprivation (area level, deciles) subgroups and sensitivity to considering a smaller number of diseases. There were 8,440,133 unique patients in our sample, over 4 million (53.1%) were female, and over 3 million (37.7%) were aged over 65 years. No clear "high cost" combinations of multimorbidity emerged as possible targets for intervention. Over 2 million (31.6%) patients had 63,124 unique combinations of multimorbidity, each contributing a small fraction (maximum 3.2%) to current-year or 5-year secondary care costs. Highest total cost combinations tended to have fewer conditions (dyads/triads, most including hypertension) affecting a relatively large population. This contrasted with the combinations that generated the highest cost for individual patients, which were complex sets of many (6+) conditions affecting fewer persons. However, all combinations containing chronic kidney disease and hypertension, or diabetes and hypertension, made up a significant proportion of total secondary care costs, and all combinations containing chronic heart failure, chronic kidney disease, and hypertension had the highest proportion of preventable emergency admission costs, which might offer priority targets for prevention of disease accumulation. The results varied little between age and deprivation subgroups and sensitivity analyses. Key limitations include availability of data only from hospitals and reliance on hospital coding of health conditions. CONCLUSIONS: Our findings indicate that there are no clear multimorbidity combinations for a cluster-targeted intervention approach to reduce secondary care costs. The role of risk-stratification and focus on individual high-cost patients with interventions is particularly questionable for this aim. However, if aetiology is favourable for preventing further disease, the cluster approach might be useful for targeting disease prevention efforts with potential for cost-savings in secondary care.

Does commuting mode choice impact health?

Governments around the world are encouraging people to switch away from sedentary modes of travel towards more active modes, including walking and cycling. The aim of these schemes is to improve population health and to reduce emissions. There is considerable evidence on the latter, but relatively little on the former. This paper investigates the impact of mode choice on physical and mental health. Using data from the UK Household Longitudinal Study, we exploit changes in mode of commute to identify health outcome responses. Individuals who change modes are matched with those whose mode remains constant. Overall we find that mode switches affect both physical and mental health. When switching from car to active travel we see an increase in physical health for women and in mental health for both genders. In contrast, both men and women who switch from active travel to car are shown to experience a significant reduction in their physical health and health satisfaction, and a decline in their mental health when they change from active to public transport.

Healthcare Cost Regressions: Going Beyond the Mean to Estimate the Full Distribution.

Understanding the data generating process behind healthcare costs remains a key empirical issue. Although much research to date has focused on the prediction of the conditional mean cost, this can potentially miss important features of the full distribution such as tail probabilities. We conduct a quasi-Monte Carlo experiment using the English National Health Service inpatient data to compare 14 approaches in modelling the distribution of healthcare costs: nine of which are parametric and have commonly been used to fit healthcare costs, and five others are designed specifically to construct a counterfactual distribution. Our results indicate that no one method is clearly dominant and that there is a trade-off between bias and precision of tail probability forecasts. We find that distributional methods demonstrate significant potential, particularly with larger sample sizes where the variability of predictions is reduced. Parametric distributions such as log-normal, generalised gamma and generalised beta of the second kind are found to estimate tail probabilities with high precision but with varying bias depending upon the cost threshold being considered.

Do public smoking bans have an impact on active smoking? Evidence from the UK.

The literature on the effects of public smoking bans on smoking behaviour presents conflicting results and there is limited evidence on their impact on active smoking. This paper evaluates the impact of smoking bans on active smoking using data from the British Household Panel Survey and exploiting the policy experiment provided by the differential timing of the introduction of the bans in Scotland and England. We assess the short-term impact of the smoking bans by employing a series of flexible difference-in-differences fixed effects panel data models. We find that the introduction of the public smoking bans in England and Scotland had limited short-run effects on both smoking prevalence and the total level of smoking. Although we identify significant differences in trends in smoking consumption across the survey period by population sub-groups, we find insufficient evidence to conclude that these were affected by the introduction of the smoking bans. These results challenge those found in the public health literature but are in line with the most recent strand of economic literature indicating that there is no firm evidence on the effects of smoking bans on smoking.

The Influence of Cost-Effectiveness and Other Factors on Nice Decisions.

The National Institute for Health and Care Excellence (NICE) emphasises that cost-effectiveness is not the only consideration in health technology appraisal and is increasingly explicit about other factors considered relevant but not the weight attached to each. The objective of this study is to investigate the influence of cost-effectiveness and other factors on NICE decisions and whether NICE's decision-making has changed over time. We model NICE's decisions as binary choices for or against a health care technology in a specific patient group. Independent variables comprised of the following: clinical and economic evidence; characteristics of patients, disease or treatment; and contextual factors potentially affecting decision-making. Data on all NICE decisions published by December 2011 were obtained from HTAinSite [www.htainsite.com]. Cost-effectiveness alone correctly predicted 82% of decisions; few other variables were significant and alternative model specifications had similar performance. There was no evidence that the threshold has changed significantly over time. The model with highest prediction accuracy suggested that technologies costing £40 000 per quality-adjusted life-year (QALY) have a 50% chance of NICE rejection (75% at £52 000/QALY; 25% at £27 000/QALY). Past NICE decisions appear to have been based on a higher threshold than £20 000-£30 000/QALY. However, this may reflect consideration of other factors that cannot be easily quantified. © 2014 The Authors. Health Economics published by John Wiley & Sons Ltd.

Need, demand, supply in health care: working definitions, and their implications for defining access.

Effective policymaking in health care systems begins with a clear typology of the terminology - need, demand, supply and access to care - and their interrelationships. However, the terms are contested and their meaning is rarely stated explicitly. This paper offers working definitions of need, demand and supply. We draw on the international literature and use a Venn diagram to explain the terms. We then define access to care, reviewing alternative and competing definitions from the literature. We conclude by discussing potential applications of our conceptual framework to help to understand the interrelationships and trade-offs between need, demand, supply and access in health care.

Comparing costs and outcomes across programmes of health care.

This paper examines the expenditure choices of local health authorities operating under fixed budget constraints. It applies a theoretical model of budgeting to a data set from 303 English Primary Care Trusts (PCTs) across ten broad programmes of health care to derive estimates of the elasticity of expenditure in each programme with respect to the total income of the PCT. The results suggest quite similar income elasticities across most programmes, in the range 0.644-1.128. The only outlier is the musculoskeletal programme with an elasticity of about 0.46. The modelling also derives estimates of spending elasticities with respect to medical needs and thereby permits calculation of the implicit cost of saving a life year in five programmes of care. The results are important as they indicate to policy makers how specific programme areas might be affected by general budgetary reductions.

Cuts to local government spending, multimorbidity and health-related quality of life: A longitudinal ecological study in England.

Background: Population health has stagnated or is declining in many high-income countries. We analysed whether nationally administered austerity cuts in England were associated with prevalence of multimorbidity (individuals with two or more long-term conditions) and health-related quality of life. Methods: We conducted an observational, longitudinal study on 147 local authorities in England. We examined associations of changes in spending over time (2009/10-2017/18), in total and by budget line, with (i) prevalence of multimorbidity, 2+ conditions (2011/12-2017/18), and (ii) health-related quality of life (EQ-5D-5L) score (2012/13-2016/17). We estimated linear, log-log regression models, incorporating local authority fixed-effects, time-varying demographic and socio-economic confounders, and time trends. Findings: All local authorities experienced real spending cuts, varying from 42% (Barking and Dagenham) to 0·3% (Sefton). A 1% cut in per capita total service expenditure was associated with a 0·10% (95% CI 0·03 to 0·16) increase in prevalence of multimorbidity. We found no association (0·003%; 95% CI -0·01 to 0·01) with health-related quality of life. By budget line, after controlling for other spending, a 1% cut in public health expenditure was associated with a 0·15% (95% CI 0·11 to 0·20) increase in prevalence of multimorbidity, and a 1% cut in adult social care expenditure was associated with a 0·01% (95% CI 0·002 to 0·02) decrease in average health-related quality of life. Interpretation: Fiscal austerity is associated with worse multimorbidity and health-related quality of life. Policymakers should consider the potential health consequences of local government expenditure cuts and knock-on effects for health systems. Funding: Medical Research Council.

The role of the staff MFF in distributing NHS funding: taking account of differences in local labour market conditions.

The National Health Service (NHS) in England distributes substantial funds to health-care providers in different geographical areas to pay for the health care required by the populations they serve. The formulae that determine this distribution reflect populations' health needs and local differences in the prices of inputs. Labour is the most important input and area differences in the price of labour are measured by the Staff Market Forces Factor (MFF). This Staff MFF has been the subject of much debate. Though the Staff MFF has operated for almost 30 years this is the first academic paper to evaluate and test the theory and method that underpin the MFF. The theory underpinning the Staff MFF is the General Labour Market method. The analysis reported here reveals empirical support for this theory in the case of nursing staff employed by NHS hospitals, but fails to identify similar support for its application to medical staff. The paper demonstrates the extent of spatial variation in private sector and NHS wages, considers the choice of comparators and spatial geography, incorporates vacancy modelling and illustrates the effect of spatial smoothing.

Acute health shocks and labour market outcomes: Evidence from the post crash era.

We investigate the labour supply response to an acute health shock for individuals of all working ages, in the post crash era, combining coarsened exact matching and entropy balancing to preprocess data prior to undertaking parametric regression. Identification exploits uncertainty in the timing of an acute health shock, defined by the incidence of cancer, stroke, or heart attack, based on data from Understanding Society. The main finding implies a substantial increase in the baseline probability of labour market exit along with reduced hours and earnings. Younger workers display a stronger labour market attachment than older counterparts, conditional on a health shock. Impacts are stronger for women, older workers, and those who experience more severe limitations and impairments. This is shown to be robust to a broad range of approaches to estimation. Sensitivity tests based on pre-treatment outcomes and using future health shocks as a placebo treatment support our identification strategy.

Patterns of emergency admissions for ambulatory care sensitive conditions: a spatial cross-sectional analysis of observational data.

OBJECTIVES: To examine the spatial and temporal patterns of English general practices' emergency admissions for Ambulatory Care Sensitive Conditions (ACSCs). DESIGN: Observational study of practice level annual hospital emergency admissions data for ACSCs for all English practices from 2004-2017. PARTICIPANTS: All patients with an emergency admission to a National Health Service hospital in England who were registered with an English general practice. MAIN OUTCOME MEASURE: Practice level age and gender indirectly standardised ratios (ISARs) for emergency admissions for ACSC. RESULTS: In 2017, 41.8% of the total variation in ISARs across practices was between the 207 Clinical Commissioning Groups (CCGs) (the administrative unit for general practices) and 58.2% was across practices within CCGs. ACSC ISARs increased by 4.7% between 2004 and 2017, while those for conditions incentivised by the Quality and Outcomes Framework (QOF) fell by 20%. Practice ISARs are persistent: practices with high rates in 2004 also had high rates in 2017. Standardising by deprivation as well as age and gender reduced the coefficient of variation of practice ISARs in 2017 by 22%. CONCLUSIONS: There is persistent spatial pattern of emergency admissions for ACSC across England both within and across CCGs. We illustrate the reduction in ACSCs emergency admissions across the study period for conditions incentivised by the QOF but find that this was not accompanied by a reduction in variation in these admissions across practices. The observed spatial pattern persists when admission rates are standardised by deprivation. The persistence of spatial clusters of high emergency admissions for ACSCs within and across CCG boundaries suggests that policies to reduce potentially unwarranted variation should be targeted at practice level.

Trends in and drivers of healthcare expenditure in the English NHS: a retrospective analysis.

BACKGROUND: In England, rises in healthcare expenditure consistently outpace growth in both GDP and total public expenditure. To ensure the National Health Service (NHS) remains financially sustainable, relevant data on healthcare expenditure are needed to inform decisions about which services should be delivered, by whom and in which settings. METHODS: We analyse routine data on NHS expenditure in England over 9 years (2008/09 to 2016/17). To quantify the relative contribution of the different care settings to overall healthcare expenditure, we analyse trends in 14 healthcare settings under three broad categories: Hospital Based Care (HBC), Diagnostics and Therapeutics (D&T) and Community Care (CC). We exclude primary care and community mental health services settings due to a lack of consistent data. We employ a set of indices to aggregate diverse outputs and to disentangle growth in healthcare expenditure that is driven by activity from that due to cost pressures. We identify potential drivers of the observed trends from published studies. RESULTS: Over the 9-year study period, combined NHS expenditure on HBC, D&T and CC rose by 50.2%. Expenditure on HBC rose by 54.1%, corresponding to increases in both activity (29.2%) and cost (15.7%). Rises in expenditure in inpatient (38.5%), outpatient (57.2%), and A&E (59.5%) settings were driven predominately by higher activity. Emergency admissions rose for both short-stay (45.6%) and long-stay cases (26.2%). There was a switch away from inpatient elective care (which fell by 5.1%) and towards day case care (34.8% rise), likely reflecting financial incentives for same-day discharges. Growth in expenditure on D&T (155.2%) was driven by rises in the volume of high cost drugs (270.5%) and chemotherapy (110.2%). Community prescribing grew by 45.2%, with costs falling by 24.4%. Evidence on the relationship between new technologies and healthcare expenditure is mixed, but the fall in drug costs could reflect low generic prices, and the use of health technology assessment or commercial arrangements to inform pricing of new medicines. CONCLUSIONS: Aggregate trends in HCE mask enormous variation across healthcare settings. Understanding variation in activity and cost across settings is an important initial step towards ensuring the long-term sustainability of the NHS.

Association Between Antipsychotic Polypharmacy and Outcomes for People With Serious Mental Illness in England.

OBJECTIVE: Although U.K. and international guidelines recommend monotherapy, antipsychotic polypharmacy among patients with serious mental illness is common in clinical practice. However, empirical evidence on its effectiveness is scarce. Therefore, the authors estimated the effectiveness of antipsychotic polypharmacy relative to monotherapy in terms of health care utilization and mortality. METHODS: Primary care data from Clinical Practice Research Datalink, hospital data from Hospital Episode Statistics, and mortality data from the Office of National Statistics were linked to compile a cohort of patients with serious mental illness in England from 2000 to 2014. The antipsychotic prescribing profile of 17,255 adults who had at least one antipsychotic drug record during the period of observation was constructed from primary care medication records. Survival analysis models were estimated to identify the effect of antipsychotic polypharmacy on the time to first occurrence of each of three outcomes: unplanned hospital admissions (all cause), emergency department (ED) visits, and mortality. RESULTS: Relative to monotherapy, antipsychotic polypharmacy was not associated with increased risk of unplanned hospital admission (hazard ratio [HR]=1.14; 95% confidence interval [CI]=0.98-1.32), ED visit (HR=0.95; 95% CI=0.80-1.14), or death (HR=1.02; 95% CI=0.76-1.37). Relative to not receiving antipsychotic medication, monotherapy was associated with a reduced hazard of unplanned admissions to the hospital and ED visits, but it had no effect on mortality. CONCLUSIONS: The study results support current guidelines for antipsychotic monotherapy in routine clinical practice. However, they also suggest that when clinicians have deemed antipsychotic polypharmacy necessary, health care utilization and mortality are not affected.

Impact of family practice continuity of care on unplanned hospital use for people with serious mental illness.

OBJECTIVE: To investigate whether continuity of care in family practice reduces unplanned hospital use for people with serious mental illness (SMI). DATA SOURCES: Linked administrative data on family practice and hospital utilization by people with SMI in England, 2007-2014. STUDY DESIGN: This observational cohort study used discrete-time survival analysis to investigate the relationship between continuity of care in family practice and unplanned hospital use: emergency department (ED) presentations, and unplanned admissions for SMI and ambulatory care-sensitive conditions (ACSC). The analysis distinguishes between relational continuity and management/ informational continuity (as captured by care plans) and accounts for unobserved confounding by examining deviation from long-term averages. DATA COLLECTION/EXTRACTION METHODS: Individual-level family practice administrative data linked to hospital administrative data. PRINCIPAL FINDINGS: Higher relational continuity was associated with 8-11 percent lower risk of ED presentation and 23-27 percent lower risk of ACSC admissions. Care plans were associated with 29 percent lower risk of ED presentation, 39 percent lower risk of SMI admissions, and 32 percent lower risk of ACSC admissions. CONCLUSIONS: Family practice continuity of care can reduce unplanned hospital use for physical and mental health of people with SMI.

Does health care spending improve health outcomes? Evidence from English programme budgeting data.

Empirical evidence has hitherto been inconclusive about the strength of the link between health care spending and health outcomes. This paper uses programme budgeting data prepared by 295 English Primary Care Trusts to model the link for two specific programmes of care: cancer and circulatory diseases. A theoretical model is developed in which decision-makers must allocate a fixed budget across programmes of care so as to maximize social welfare, in the light of a health production function for each programme. This yields an expenditure equation and a health outcomes equation for each programme. These are estimated for the two programmes of care using instrumental variables methods. All the equations prove to be well specified. They suggest that the cost of a life year saved in cancer is about 13,100 pounds, and in circulation about 8000 pounds. These results challenge the widely held view that health care has little marginal impact on health. From a policy perspective, they can help set priorities by informing resource allocation across programmes of care. They can also help health technology agencies decide whether their cost-effectiveness thresholds for accepting new technologies are set at the right level.

Persistence in health limitations: a European comparative analysis.

This paper investigates the persistence in health limitations for individuals within the member states of the European Union. We use the full eight waves of data available in the European Community Household Panel (ECHP) to explore the relative contributions of state dependence, unobserved heterogeneity and socioeconomic characteristics, in particular income, education and activity status, and how these vary across countries. We focus on binary measures of health limitations, constructed from the answers to the question: "Are you hampered in your daily activities by any physical or mental health problem, illness or disability?". Dynamic non-linear panel data models are specified and estimated using both pooled and random effects probit and logit models together with complementary log-log models. The random effects probit specifications are preferred. Results reveal high state dependence of health limitations, which remains after controlling for measures of socioeconomic status. There is heterogeneity in the socioeconomic gradient across countries.

Analysis of consultants' NHS and private incomes in England in 2003/4.

OBJECTIVE: Consultants employed by the NHS in England are allowed to undertake private practice to supplement their NHS income. Until the introduction of a new contract from October 2003, those employed on full-time contracts were allowed to earn private incomes no greater than 10% of their NHS income. In this paper we investigate the magnitude and determinants of consultants' NHS and private incomes. DESIGN: Quantitative analysis of financial data. SETTING: A unique, anonymized, non-disclosive dataset derived from tax returns for a sample of 24,407 consultants (92.3% of the total) in England for the financial year 2003/4. MAIN OUTCOME METHODS: The conditional mean total, NHS and private incomes earned by age group, type of contract, specialty and region of place of work. RESULTS: The mean annual total, NHS and private incomes across all consultants in 2003/4 were pound 110,773, pound 76,628 and pound 34,144, respectively. Incomes varied by age, type of contract, specialty and region of place of work. The ratio of mean private to NHS income for consultants employed on a full-time contract was 0.26. The mean private income across specialties ranged from pound 5,144 (for paediatric neurology) to pound 142,723 (plastic surgery). There was a positive association between mean private income and NHS waiting lists across specialties. CONCLUSIONS: Consultants employed on full-time contracts on average exceeded the limits on private income stipulated by the 10% rule. Specialty is a more important determinant of income than the region in which the consultant works. Further work is required to explore the association between mean private income and waiting lists.