pinecone/core-2020-05-10-deduplication huggingface dataset:
A bias-adjusted evidence synthesis of RCT and observational data: the case of total hip replacement.

This is the final version of the article. Available from Wiley via the DOI in this record.Evaluation of clinical effectiveness of medical devices differs in some aspects from the evaluation of pharmaceuticals. One of the main challenges identified is lack of robust evidence and a will to make use of experimental and observational studies (OSs) in quantitative evidence synthesis accounting for internal and external biases. Using a case study of total hip replacement to compare the risk of revision of cemented and uncemented implant fixation modalities, we pooled treatment effect estimates from OS and RCTs, and simplified existing methods for bias-adjusted evidence synthesis to enhance practical application. We performed an elicitation exercise using methodological and clinical experts to determine the strength of beliefs about the magnitude of internal and external bias affecting estimates of treatment effect. We incorporated the bias-adjusted treatment effects into a generalized evidence synthesis, calculating both frequentist and Bayesian statistical models. We estimated relative risks as summary effect estimates with 95% confidence/credibility intervals to capture uncertainty. When we compared alternative approaches to synthesizing evidence, we found that the pooled effect size strongly depended on the inclusion of observational data as well as on the use bias-adjusted estimates. We demonstrated the feasibility of using observational studies in meta-analyses to complement RCTs and incorporate evidence from a wider spectrum of clinically relevant studies and healthcare settings. To ensure internal validity, OS data require sufficient correction for confounding and selection bias, either through study design and primary analysis, or by applying post-hoc bias adjustments to the results. © 2017 The Authors. Health Economics published by John Wiley & Sons, Ltd.The research leading to these results has received funding from the European Community's Seventh Framework Programme under grant agreement HEALTH-F3-2012-305694 (Project MedtecHTA ‘Methods for Health Technology Assessment of Medical Devices: a European Perspective’). We are extremely grateful to the clinical and methodological experts who took the time from their busy schedules to participate in the study. Without their support, we would have never achieved the results presented in this manuscript. All errors are ours
Cancelled procedures in the English NHS: Evidence from the 2010 tariff reform

This paper explores the role of incentives in the English NHS. Until financial year 2009/10, elective procedures that were cancelled after admission received a fixed reimbursement associated with a specific healthcare resource group code. We in- vestigate whether this induced trusts to admit and then cancel, rather than cancel before admission and/or to cancel low fee over high fee work. As the tariff was ended in April 2010 we conduct an interrupted time series analysis to examine if their behaviour was affected after the tariff removal. The results indicate a small, yet statistically significant, decline in the probability of a last minute cancellation in the post-tariff period, especially for certain types of patients and diagnoses
Adaptation to Health States: Sick yet better off?

Healthcare funding decisions in the UK rely on health state valuations of the general public. However, it has been shown that there is disparity between the valuation of the impact of hypothetical conditions on health and the reported health by those experiencing them. Patients' adaptation to health states is among the most common explanations for this discrepancy. Being diagnosed with a disease appears to affect individual perception of health over time so that better subjective health may be reported over a disease trajectory. This paper examines adaptation to health states using a longitudinal dataset. We use four waves of the British Cohort Study (BCS70), which tracks a sample of British individuals since birth in 1970 and contains information on self-assessed health (SAH), morbidity, and socioeconomic characteristics. We implement a dynamic ordered probit model controlling for health state dependence. Results are supportive of the existence of adaptation: Time since diagnosis has a positive impact on SAH. Moreover, adaptation happens over relatively long durations. We do not find significant results proving different adaptation paths for patients reporting prior better SAH. The analysis by specific conditions generally supports the existence of adaptation, but results are statistically significant only for a subset of conditions
How should hospital reimbursement be refined to supportconcentration 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
Will you still need me, will you still feed me when I'm 64?

Informal care may substitute for formal long‐term care that is often publicly funded\ud
or subsidized. The costs of informal caregiving are borne by the caregiver and may\ud
consist of worse health outcomes and, if the caregiver has not retired, worse labor\ud
market outcomes.We estimate the impact of providing informal care to one's partner\ud
on the caregiver's health using data from the Survey of Health, Ageing, and Retirement\ud
in Europe. We use statistical matching to deal with selection bias and\ud
endogeneity. We find that in the short run caregiving has a substantial effect on\ud
the health of caregivers and, for female caregivers, on their health care use. These\ud
effects should be taken into account when comparing the costs and benefits of formal\ud
and informal care provision. The health effects may, however, be short‐lived, as\ud
we do not find any evidence that they persist after 4 or 7 years
The wear and tear on health: What is the role of occupation?

Health is well known to show a clear gradient by occupation. Although it may appear evident that occupation can affect health, there are multiple possible sources of selection that can generate a strong association, other than simply a causal effect of occupation on health. We link job characteristics to German panel data spanning 29 years to characterize occupations by their physical and psychosocial burden. Employing a dynamic model to control for factors that simultaneously affect health and selection into occupation, we find that selection into occupation accounts for at least 60% of the association. The effects of occupational characteristics such as physical strain and low job control are negative and increase with age: late-career exposure to 1 year of high physical strain and low job control is comparable to the average health decline from ageing 16 and 6 months, respectively
The effectiveness of medical and vocational interventions for reducing sick leave of self-employed workers

We investigate whether interventions by (i) medical doctors and (ii) occupational specialists are effective in reducing sick leave durations among self-employed workers. Therefore, we exploit unique administrative data comprising all sick leave claims by self-employed workers insured with a major Dutch private insurer between January 2009 and March 2014. We estimate a multivariate duration model dealing with non-random selection into the two intervention types by controlling for observable and unobservable claimant characteristics. We find adverse treatment effects for both interventions, irrespective of whether they are started early or (middle) late in the sickness spell
How effective and fair is user fee removal? Evidence from Zambia using a pooled synthetic control

Despite its high political interest, the impact of removing user charges for health care in low-income settings remains a debatable issue. We try to clear up this contentious issue by estimating the short-term effects of a policy change that occurred in 2006 in Zambia, when 54 of 72 districts removed fees. We use a pooled synthetic control method in order to estimate the causal impact of the policy on health care use, the provider chosen, and out-of-pocket medical expenses. We find no evidence that user fee removal increased health care utilisation, even among the poorest group. However, we find that the policy is likely to have led to a substitution away from the private sector for those using care and that it virtually eliminated medical expenditures, thereby providing financial protection to service users. We estimate that the policy was equivalent to a transfer of US$3.2 per health visit for the 50% richest but of only US$1.1 for the 50% poorest
The impact of long-term care on quality of life

Long-term care (LTC) services are provided to help people manage the consequences of impairment, but their impact goes beyond the meeting of basic needs. Accordingly, the main aim was to explore the marginal effectiveness of care when measured in terms of people’s overall care-related quality of life (CRQoL) and assess changes in marginal effect for increasing intensity. The associated aim was to refine and apply an observational method to estimate marginal effectiveness. A ‘production-function’ approach was used with survey data, including ASCOT-measured CRQoL, whereby we statistically modelled the expected relationship between service utilisation rates and CRQoL. This method seeks to limit endogeneity issues by controlling on observables and using instrumental variable (IV). Using a survey of publicly-funded long-term care service users in England, we found that community-based LTC significantly improved people’s CRQoL but with diminishing marginal effects and effects differentiated by baseline impairment levels. There are implications for how the care system should respond to changes in global public budgets. For example, where there is unmet need, a system aimed to maximise (unadjusted) CRQoL would put more emphasis on access (more recipients) than intensity of support compared to a system operating on a needs basis
Promoting Normal Birth and Reducing Caesarean Section Rates: An Evaluation of the Rapid Improvement Programme

This paper evaluates the impact of the 2008 Rapid Improvement Programme that aimed at promoting normal birth and reducing caesarean section rates in the English NHS. Using Hospital Episode Statistics maternity records for the period 2001-2013 a panel data analysis was performed to determine whether the implementation of the programme reduced caesarean sections rates in participating hospitals. The results obtained using either the unadjusted sample of hospitals or a trimmed sample determined by a propensity score matching approach indicate that the impact of the programme was small. More specifically there were 2.3 to 3.4 fewer caesarean deliveries in participating hospitals, on average, during the post-programme period offering a limited scope for cost reduction. This result mainly comes from the reduction in the number of emergency caesareans as no significant effect was uncovered for planned caesarean deliveries
The eyes have it: using eye tracking to inform information processing strategies in multi‐attributes choices

Although choice experiments (CEs) are widely applied in economics to study choice behaviour, understanding of how individuals process attribute information remains limited. We show how eye‐tracking methods can provide insight\ud
into how decisions are made. Participants completed a CE, while their eye movements were recorded. Results show that although the information presented guided participants' decisions, there were also several processing biases at work. Evidence was found of (a) top‐to‐bottom, (b) left‐to‐right, and (c) first‐to‐last order biases. Experimental factors—whether attributes are defined as “best” or “worst,” choice task complexity, and attribute ordering—also influence information processing. How individuals visually process attribute information was shown to be related to their choices. Implications for the design and analysis of CEs and future research are discussed
Is “end of life” a special case? Connecting Q with survey methods to measure societal support for views on the value of life-extending treatments

Preference elicitation studies reporting societal views on the relative value of end-of-life treatments have produced equivocal results. This paper presents an alternative method, combining Q methodology and survey techniques (Q2S) to determine the distribution of 3 viewpoints on the relative value of end-of-life treatments identified in a previous, published, phase of this work. These were Viewpoint 1, “A population perspective: value for money, no special cases”; Viewpoint 2, “Life is precious: valuing life-extension and patient choice”; and Viewpoint 3, “Valuing wider benefits and opportunity cost: the quality of life and death.”. A Q2S survey of 4,902 respondents across the United Kingdom measured agreement with these viewpoints; 37% most agreed with Viewpoint 1, 49% with Viewpoint 2, and 9% with Viewpoint 3. Regression analysis showed associations of viewpoints with gender, level of education, religion, voting preferences, and satisfaction with the NHS. The Q2S approach provides a promising means to investigate how in-depth views and opinions are represented in the wider population. As demonstrated in this study, there is often more than 1 viewpoint on a topic and methods that seek to estimate that averages may not provide the best guidance for societal decision-making
What factors predict the passage of state-level e-cigarette regulations?

E-cigarettes are controversial products. They may help addicted smokers to consume nicotine in a less harmful manner or to quit tobacco cigarettes entirely, but these products may also entice youth into smoking. This controversy complicates e-cigarette regulation as any regulation may lead to health improvements for some populations, and health declines for other populations. Using data from 2007 to 2016, we examine factors that are plausibly linked with U.S. state e-cigarette regulations. We find that less conservative states are more likely to regulate e-cigarettes and that states with stronger tobacco lobbies are less likely to regulate e-cigarettes. This information can help policymakers as they determine how best to promote public health through regulation
The health benefits of a targeted cash transfer: The UK Winter Fuel Payment.

Each year, the UK records 25,000 or more excess winter deaths, primarily among the elderly. A key policy response is the "Winter Fuel Payment" (WFP), a labelled but unconditional cash transfer to households with a member above the female state pension age. The WFP has been shown to raise fuel spending among eligible households. We examine the causal effect of the WFP on health outcomes, including self-reports of chest infection, measured hypertension, and biomarkers of infection and inflammation. We find a robust, 6 percentage point reduction in the incidence of high levels of serum fibrinogen. Reductions in other disease markers point to health benefits, but the estimated effects are less robust
An exploration of the non-iterative time trade-off method to value health states

Time Trade-Off (TTO) usually relies on “iteration,” which is susceptible to bias. Discrete Choice Experiment with duration (or DCETTO) is free of such bias, but respondents find this cognitively more challenging. This paper explores non-iterative TTO with or without lead time: NI(LT)TTO. In NI(LT)TTO, respondents see a series of independent pairwise choices without iteration (similar to DCETTO), but one of the two scenarios always involves full health for a shorter duration (similar to TTO). We compare three different “types” of NI(LT)TTO relative to DCETTO. Each type is presented in two “modes”: (a) verbally tabulated (as in a DCE) and (b) with visual aids (as in a TTO). The study has 8 survey variants, each with 12 experimental choice tasks and a 13th task with a logically determined answer. Data on the 12 experimental choices from an online survey of 6,618 respondents are modelled, by variant, using conditional logistic regressions. The results indicate that NI(LT)TTO is feasible, but some relatively mild states appear to have implausibly low predicted values, and the range of predicted values is much narrower than in DCETTO. The presentation of NI(LT)TTO tasks needs further improvement
Parametric models for biomarkers based on flexible size distributions

Recent advances in social science surveys include collection of biological samples. Although biomarkers offer a large potential for social science and economic research, they impose a number of statistical challenges, often being distributed asymmetrically with heavy tails. Using data from the UK Household Panel Survey, we illustrate the comparative performance of a set of flexible parametric distributions, which allow for a wide range of skewness and kurtosis: the four‐parameter generalized beta of the second kind (GB2), the three‐parameter generalized gamma, and their three‐, two‐, or one‐parameter nested and limiting cases. Commonly used blood‐based biomarkers for inflammation, diabetes, cholesterol, and stress‐related hormones are modelled. Although some of the three‐parameter distributions nested within the GB2 outperform the latter for most of the biomarkers considered, the GB2 can be used as a guide for choosing among competing parametric distributions for biomarkers. Going “beyond the mean” to estimate tail probabilities, we find that GB2 performs fairly well with some disparities at the very high levels of glycated hemoglobin and fibrinogen. Commonly used linear models are shown to perform worse than almost all the flexible distributions
Ambiguity preferences for health

In most medical decisions, probabilities are ambiguous and not objectively known. Empirical evidence suggests that people's preferences are affected by ambiguity. Health economic analyses generally ignore ambiguity preferences and assume that they are the same as preferences under risk. We show how health preferences can be measured under ambiguity, and we compare them with health preferences under risk. We assume a general ambiguity model that includes many of the ambiguity models that have been proposed in the literature. For health gains, ambiguity preferences and risk preferences were indeed the same. For health losses, they differed with subjects being more pessimistic in decision under ambiguity. Utility and loss aversion were the same for risk and ambiguity. Our results imply that reducing the clinical ambiguity of health losses has more impact than reducing the ambiguity of health gains, that utilities elicited with known probabilities may not carry over to an ambiguous setting, and that ambiguity aversion may impact value of information analyses if losses are involved. These findings are highly relevant for medical decision making, because most medical interventions involve losses
E‐learning and health inequality aversion: a questionnaire experiment

In principle, questionnaire data on public views about hypothetical trade‐offs between improving total health and reducing health inequality can provide useful normative health inequality aversion parameter benchmarks for policymakers faced with real trade‐offs of this kind. However, trade‐off questions can be hard to understand, and one standard type of question finds that a high proportion of respondents—sometimes a majority—appear to give exclusive priority to reducing health inequality. We developed and tested two e‐learning interventions designed to help respondents understand this question more completely. The interventions were a video animation, exposing respondents to rival points of view, and a spreadsheet‐based questionnaire that provided feedback on implied trade‐offs. We found large effects of both interventions in reducing the proportion of respondents giving exclusive priority to reducing health inequality, though the median responses still implied a high degree of health inequality aversion and—unlike the video—the spreadsheet‐based intervention introduced a substantial new minority of non‐egalitarian responses. E‐learning may introduce as well as avoid biases but merits further research and may be useful in other questionnaire studies involving trade‐offs between conflicting values
Prospective payment systems and discretionary coding - Evidence from English mental health providers

Reimbursement of English mental health hospitals is moving away from block contracts and towards activity and outcome‐based payments. Under the new model, patients are categorised into 20 groups with similar levels of need, called clusters, to which prices may be assigned prospectively. Clinicians, who make clustering decisions, have substantial discretion and can, in principle, directly influence the level of reimbursement the hospital receives. This may create incentives for upcoding. Clinicians are supported in their allocation decision by a clinical clustering algorithm, the Mental Health Clustering Tool, which provides an external reference against which clustering behaviour can be benchmarked. The aims of this study are to investigate the degree of mismatch between predicted and actual clustering and to test whether there are systematic differences amongst providers in their clustering behaviour. We use administrative data for all mental health patients in England who were clustered for the first time during the financial year 2014/15 and estimate multinomial multilevel models of over, under, or matching clustering. Results suggest that hospitals vary systematically in their probability of mismatch but this variation is not consistently associated with observed hospital characteristics
Measuring inequalities in health in the presence of multiple-category morbidity indicators

This paper considers the problems which arise in seeking to measure socioeconomic inequalities in health when the health indicator is a categorical variable, such as self-assessed health. It shows that the standard approach - which involves dichotomizing the categorical variable - is unreliable. The degree of measured inequality is found to depend on the cut-off point chosen and the choice of cut-off point to affect the conclusions one can reach about trends in or differences in health inequality. The paper goes on to propose an alternative approach which involves constructing a latent health variable and then measuring inequalities in this latent variable by means of a variant of the health concentration curve