The Importance of Multimorbidity in Explaining Utilisation and Costs Across Health and Social Care Settings: Evidence from South Somerset’s Symphony Project – University of York, Centre for Health Economics – February 2014

Posted on March 12, 2014. Filed under: Chronic Disease Mgmt, Health Economics | Tags: , |

The Importance of Multimorbidity in Explaining Utilisation and Costs Across Health and Social Care Settings: Evidence from South Somerset’s Symphony Project – University of York, Centre for Health Economics – February 2014

Abstract

Aims
Since the inception of the NHS, an ever-present challenge has been to improve integration of care within the health care system and with social care. Many people have complex and ongoing care needs and require support from multiple agencies and various professionals. But care is often fragmented and uncoordinated, with no one agency taking overall responsibility, so it is often left to individuals and their families to negotiate the system as best they can. South Somerset’s Symphony is designed to establish greater collaboration between primary, community, acute and social care, particularly for people with complex conditions.

Methods
We examine patterns of health and social care utilisation and costs for the local population to identify which groups of people would most benefit from better integrated care. We analyse data to identify groups of people according to the frequency of occurrence of underlying conditions; the cost of care; and utilisation of services across diverse settings. The empirical identification strategy is supplemented by local intelligence gained through workshops with health and social care professionals about the appropriateness of existing patterns of provision. We employ two-part regression models to explain variability in individual health and social costs, in total and in each setting.

Data
The Symphony Project has an anonymised individual-level dataset, spanning primary, community, acute, mental health and social care. This includes activity, costs, clinical conditions, age, sex and ward of residence for the entire population of 114,874 people in 2012. Each person’s morbidity profile is described using the United Health’s Episode Treatment Groups (ETG), which build upon ICD and Read codes.

Results
We identify the frequency of conditions and co-morbidity profile of the entire population and, for the most frequent conditions, we assess utilization and costs of care across health and social care settings. For example, for those with asthma and diabetes, hospital costs account for the largest proportion of costs; in contrast, costs for those with dementia occur mostly in social care, mental health care and community care settings. For the population as a whole, we find that costs of health and social care are driven more by an individual’s morbidity profile than by their age. Data for those with the most frequent conditions were reviewed by local health and social care professionals and managers. It was decided to undertake more detailed analyses for those with diabetes or dementia. 5,676 people are recorded as having diabetes in South Somerset, with hypertension being the most common comorbidity. For those with a sole diagnosis of diabetes, costs are around £1,000 on average but as people are recorded as having more diagnoses, average costs increase progressively. Costs are also higher for older people and women.People with dementia account for only 0.92% of the South Somerset population, but the average annual cost for the 1,062 people with dementia is around £12,000. A high proportion of these costs are related to the provision of mental health, social and continuing care. Costs are higher the more co-morbidities a person has, and for people from more deprived areas. Age and gender do not explain variation in costs for people with dementia.

Conclusions
This work forms a basis for identifying groups that would most benefit from improved integrated care, which might be facilitated by integrated financial arrangements and better pathway management. The more co-morbidities that a person has, the more likely they are to require care across diverse settings, and the higher their costs. Our analysis identifies those groups of the population which are the highest users of services by activity and cost and provides baseline information to allow budgetary arrangements to be developed for these targeted groups.

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The importance of multimorbidity in explaining utilisation and costs across health and social care settings: evidence from South Somerset’s Symphony Project – University of York, Centre for Health Economics – February 2014

Posted on March 5, 2014. Filed under: Chronic Disease Mgmt, Health Economics | Tags: , |

The importance of multimorbidity in explaining utilisation and costs across health and social care settings: evidence from South Somerset’s Symphony Project – University of York, Centre for Health Economics – February 2014

Panos Kasteridis, Andrew Street, Matthew Dolman, Lesley Gallier, Kevin Hudson, Jeremy Martin and Ian Wyer

“Abstract
Aims
Since the inception of the NHS, an ever-present challenge has been to improve integration of care within the health care system and with social care. Many people have complex and ongoing care needs and require support from multiple agencies and various professionals. But care is often fragmented and uncoordinated, with no one agency taking overall responsibility, so it is often left to individuals and their families to negotiate the system as best they can. South Somerset’s Symphony is designed to establish greater collaboration between primary, community, acute and social care, particularly for people with complex conditions.”

… continues on the sites

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The influence of cost-effectiveness and other factors on NICE decisions – Centre for Health Economics, University of York – November 2013

Posted on December 10, 2013. Filed under: Evidence Based Practice, Health Economics, Health Mgmt Policy Planning, Health Policy | Tags: , |

The influence of cost-effectiveness and other factors on NICE decisions – Centre for Health Economics, University of York – November 2013

“Abstract

Background: The National Institute for Health and Care Excellence (NICE) emphasises that costeffectiveness is not the only consideration in health technology appraisal and is increasingly explicit about other factors considered relevant. Observing NICE decisions and the evidence considered in each appraisal allows us to ‘reveal’ its implicit weights.

Objectives: This study aims to investigate the influence of cost-effectiveness and other factors on NICE decisions and to investigate whether NICE’s decision-making has changed through time.

Methods: We build on and extend the modelling approaches in Devlin and Parkin (2004) and Dakin et al (2006). We model NICE’s decisions as binary choices: i.e. recommendations for or against use of a healthcare technology in a specific patient group. Independent variables comprised: the clinical and economic evidence regarding that technology; the characteristics of the patients, disease or treatment; and contextual factors affecting the conduct of health technology appraisal. Data on all NICE decisions published by December 2011 were obtained from HTAinSite [www.htainsite.com].

Results: Cost-effectiveness alone correctly predicted 82% of decisions; few other variables were significant and alternative model specifications led to very small variations in model performance. The odds of a positive NICE recommendation differed significantly between musculoskeletal disease, respiratory disease, cancer and other conditions. The accuracy with which the model predicted NICE recommendations was slightly improved by allowing for end of life criteria, uncertainty, publication date, clinical evidence, only treatment, paediatric population, patient group evidence, appraisal process, orphan status, innovation and use of probabilistic sensitivity analysis, although these variables were not statistically significant. Although there was a non-significant trend towards more recent decisions having a higher chance of a positive recommendation, there is currently no evidence that the threshold has changed over time. The model with highest prediction accuracy suggested that a technology costing £40,000 per quality-adjusted life-year (QALY) would have a 50% chance of NICE rejection (75% at £52,000/QALY; 25% at £27,000/QALY).

Discussion: Past NICE decisions appear to have been based on a higher threshold than the £20,000 – £30,000/QALY range that is explicitly stated. However, this finding may reflect consideration of other factors that drive a small number of NICE decisions or cannot be easily quantified.”

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Attributing a monetary value to patients’ time: A contingent valuation approach – Centre for Health Economics, University of York, UK – September 2013

Posted on September 12, 2013. Filed under: Health Economics, Patient Participation | Tags: |

Attributing a monetary value to patients’ time: A contingent valuation approach – Centre for Health Economics, University of York, UK – September 2013

“Abstract

It is hard to ignore the importance of patient time investment in the production of health since the influential paper by Grossman (1972). Patient time includes time to admission, travel time, waiting time, and treatment time and can be substantial. Time to admission is the time between the first referral and the moment that the treatment actually starts. Travel time is the time that a patient needs to travel between the place where the patient lives and the medical care centre where the patient is treated. Waiting time is the time that the patient waits at the medical care centre before treatment. Treatment time is the time spent getting active treatment for example by a doctor or a nurse. Patient time is, however, often ignored in economic analyses. This may lead to biased results and inappropriate policy recommendations, which may eventually influence patients’ health, wellbeing and welfare.

How to value patient time is not straightforward. It is even less straightforward for patients who are not participating in the labour market. Although there is some emerging literature on the monetary valuation of patient time, an important challenge remains to develop an approach that can be used to monetarily value time of patients not participating in the labour market. We aim to contribute to the health economics literature by describing and empirically illustrating how to monetarily value patients’ time comprehensively, using the contingent valuation method. Comprehensively means including various types of patient time (time to admission, travel time, waiting time, and treatment time) as the previous literature focused mainly on valuing a particular type of patient time, for instance waiting time.

This paper describes the development of the contingent valuation survey. The survey is added as an appendix to this paper. This paper also presents the first empirical results of applying our survey approach in a sample of patients in the Netherlands not participating in the labour market. These results show that the monetary value of waiting time was the highest (€30.10/£34.76 per hour) and travel and treatment time were equally valued (respectively €13.20/£11.43 and €13.32/£11.54 per hour).”

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Does a hospital’s quality depend on the quality of other hospitals? A spatial econometrics approach to investigating hospital quality competition – University of York, Centre for Health Economics – January 2013

Posted on February 5, 2013. Filed under: Clin Governance / Risk Mgmt / Quality, Health Economics | Tags: |

Does a hospital’s quality depend on the quality of other hospitals? A spatial econometrics approach to investigating hospital quality competition – University of York, Centre for Health Economics – January 2013

Hugh Gravelle, Rita Santos, Luigi Siciliani

“We examine whether a hospital’s quality is affected by the quality provided by other hospitals in the same market. We first set out a theoretical model with regulated prices which specifies conditions on demand and cost functions which determine whether a hospital will have higher quality when its rivals have higher quality. We then apply spatial econometric methods to a sample of English hospitals in 2009-10 and a set of 16 quality measures including mortality rates, readmission, revision and redo rates and three patient reported indicators to examine to examine the relationship between the quality of hospitals. We find that a hospital’s quality is positively associated with the quality of its rivals for seven out of the sixteen quality measures and that in no case is there a negative association. In those cases where there is a positive association, an increase in rivals’ quality by 10% increases a hospital’s quality by 1.7% to 2.9%.”

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Hospital Quality Competition Under Fixed Prices – Centre for Health Economics – November 2012

Posted on November 21, 2012. Filed under: Health Economics | Tags: |

Hospital Quality Competition Under Fixed Prices – Centre for Health Economics – November 2012

Hugh Gravelle, Rita Santos, Luigi Siciliani, Rosalind Goudie

Extract:

“The relationship between the quality of health care and the extent of competition amongst providers has been the subject of intense policy interest and debate. As part of the ESHCRU programme we are undertaking a set of related investigations into this relationship in the hospital sector, in primary care (general practices) and in social care. In this initial report on competition amongst hospitals we

review the theoretical economics literature on competition and quality,
briefly describe the relevant empirical literature on
o whether choice of hospital is influenced by quality
o whether greater competition is associated with higher quality
report on preliminary empirical analyses of
o the correlations amongst 16 hospital quality measures
o the association between distance based measures of competition and these quality measures.

We conclude by describing our future research suggested by the theoretical and empirical literature reviews and our initial empirical analyses.”

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English hospitals can improve their use of resources: analysis of costs and length of stay for ten treatments – University of York, Centre for Health Economics – 12 July 2012

Posted on July 18, 2012. Filed under: Health Economics | Tags: , , |

English hospitals can improve their use of resources: analysis of costs and length of stay for ten treatments – University of York, Centre for Health Economics – 12 July 2012

“With the NHS facing severe funding constraints, it has been suggested that the greatest potential savings may come from increasing efficiencies and by reducing variations in clinical practices. When comparing hospitals, variations in practice of any form are often cited as evidence of inefficiency or poor performance and that the overall efficiency of the health system would improve if all hospitals were able to meet the standards of the best.  CHE researchers assessed whether or not the higher cost or length of stay is due to the type of patients that hospitals treat.

For ten conditions, the researchers examined the cost and length of stay for every patient admitted to English hospitals during 2007/8. They looked at three medical conditions (acute myocardial infarction; childbirth; stroke) and seven surgical treatments (appendectomy; breast cancer (mastectomy); coronary artery bypass graft; cholecystectomy; inguinal hernia repair; hip replacement; and knee replacement).

Even after taking account of age, disease severity and other characteristics, patients in some hospitals still had substantially higher costs or longer length of stay than others. This pattern was evident in all ten clinical areas. Furthermore, these variations could not be explained by hospital characteristics such as size, teaching status, and how specialised the hospital was.”

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Coverage with evidence development, only in research, risk sharing or patient access scheme? A framework for coverage decisions – University of York, Centre for Health Economics – 10 April 2012

Posted on April 24, 2012. Filed under: Evidence Based Practice, Health Economics, Health Technology Assessment | Tags: |

Coverage with evidence development, only in research, risk sharing or patient access scheme? A framework for coverage decisions – University of York, Centre for Health Economics – 10 April 2012

This research paper has been published simultaneously with a shortened version of the paper in Value in Health

“Context
Until recently, purchasers’ options regarding whether to pay for the use of technologies have been binary in nature: a treatment is covered or not covered. However, policies have emerged which expand the options – for example, linking coverage to evidence development, an option increasingly used for new treatments with limited/uncertain evidence. There has been little effort to reconcile the features of technologies with the available options in a way that reflects purchasers’ ranges of authority.

Methods
We developed a framework within which different options can be evaluated. We distinguished two sources of value in terms of health: the value of the technology per se; and the value of reducing decision uncertainty. The costs of reversing decisions are also considered.

Findings
Purchasers should weigh the expected benefits of coverage against the possibility the decision may need to be reversed and the possibility adoption will hinder/prevent evidence generation. Based on the purchaser’s range of authority and the features of the technology different decisions may be appropriate. The framework clarifies the assessments needed to establish the appropriateness of
different decisions. A taxonomy of coverage decisions consistent with the framework is suggested.

Conclusions
A range of coverage options permit paying for use of promising medical technologies despite their limited/uncertain evidence bases. It is important that the option chosen be based upon not only the expected value of a technology but also the value of further research, the anticipated effect of coverage on further research, and the costs associated with reversing the decision.”

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Productivity of the English National Health Service 2003-4 to 2009-10 – Centre for Health Economics, University of York – 30 March 2012

Posted on April 3, 2012. Filed under: Health Economics | Tags: , , |

Productivity of the English National Health Service 2003-4 to 2009-10 – Centre for Health Economics, University of York – 30 March 2012

media release

Chris Bojke, Adriana Castelli, Rosalind Goudie, Andrew Street, Padraic Ward

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Analysing hospital variation in health outcome at the level of EQ-5D dimensions – Centre for Health Economics, University of York – January 2012

Posted on February 13, 2012. Filed under: Clin Governance / Risk Mgmt / Quality, Health Economics, Surgery | Tags: |

Analysing hospital variation in health outcome at the level of EQ-5D dimensions – Centre for Health Economics, University of York – January 2012

by Nils Gutacker, Chris Bojke, Silvio Daidone, Nancy Devlin, Andrew Street

Abstract

“The English Department of Health has introduced routine collection of patient-reported health outcome data for selected surgical procedures (hip and knee replacement, hernia repair, varicose vein surgery) to facilitate patient choice and increase provider accountability. The EQ-5D has been chosen as the preferred generic instrument and the current risk-adjustment methodology is based on the EQ-5D index score to measure variation across hospital providers.

There are two potential problems with this. First, using a population value set to generate the index score may not be appropriate for purposes of provider performance assessment because it introduces an exogenous source of variation and assumes identical preferences for health dimensions among patients. Second, the multimodal distribution of the index score creates statistical problems that are not yet resolved. Analysing variation for each dimension of the EQ-5D dimensions (mobility, self care, usual activities, pain/discomfort, anxiety/depression) seems therefore more appropriate and promising.

For hip replacement surgery, we explore a) the impact of treatment on each EQ-5D dimension b) the extent to which treatment impact varies across providers c) the extent to which treatment impact across EQ-5D dimensions is correlated within providers.

We combine information on pre- and post-operative EQ-5D outcomes with Hospital Episode Statistics for the financial year 2009/10. The overall sample consists of 25k patients with complete pre- and post-operative responses.

We employ multilevel ordered probit models that recognise the hierarchical nature of the data (measurement points nested in patients, which themselves are nested in hospital providers) and the response distributions. The treatment impact is modelled as a random coefficient that varies at hospital-level. We obtain provider-specific Empirical Bayes (EB) estimates of this coefficient. We estimate separate models for each of the five EQ-5D dimensions and analyse correlations of the EB estimates across dimensions.

Our analysis suggests that hospital treatment is indeed associated with improvements in health and that variability in treatment impact is generally more pronounced on the dimensions mobility, usual activity and pain/discomfort than on others. The pairwise correlation between the provider EB estimates is substantial, suggesting a) that certain providers are better in improving health across multiple EQ-5D dimensions than others and b) multivariate models are appropriate and should be further investigated.”

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Twenty years of using economic evaluations for reimbursement decisions. What have we achieved? – Centre for Health Economics, University of York – 2012

Posted on February 13, 2012. Filed under: Health Economics, Pharmacy | Tags: |

Twenty years of using economic evaluations for reimbursement decisions. What have we achieved? – Centre for Health Economics, University of York –  2012

by Michael Drummond

Abstract
“The objective of this paper is to examine the impact of economic evaluation on the reimbursement process for pharmaceuticals. Before the introduction of economic evaluation, a range of arrangements existed across different jurisdictions, varying from reimbursement based on clinical criteria alone and price controls, to a total absence of controls over price or reimbursement. The changes in the structure of reimbursement policies necessary to incorporate economic  evaluation have been accomplished without major difficulty in most jurisdictions. However, several methodological differences in international guidelines for economic evaluation exist, only some of which can easily be justified. A number of beneficial changes in reimbursement processes have also been observed, such as a trend towards requiring the measurement of more meaningful clinical endpoints and increased engagement between manufacturers, drug regulators and payers. A consistent finding in studies of reimbursement decisions is that economic considerations have been influential, second only to the strength of the clinical evidence for the drug of interest. The impact of economic evaluation on the allocation of healthcare resources is hard to ascertain because of the difficulties in specifying the counterfactual and the fact that little is known about the extent to which reimbursement decisions actually lead to changes in healthcare practice. However, there is evidence that economic evaluation has assisted price negotiations and enabled reimbursement agencies to target drugs to those patients who will benefit the most. In publicly financed healthcare systems, an evidence-based system of pricing and reimbursement for drugs, considering societal willingness-topay, is a reasonable policy objective to pursue.”

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Estimating the costs of specialised care: updated analysis using data for 2009/10 – Centre for Health Economics, University of York – 15 December 2011

Posted on December 19, 2011. Filed under: Health Economics | Tags: |

Estimating the costs of specialised care: updated analysis using data for 2009/10 – Centre for Health Economics, University of York – 15 December 2011

“Research by the Centre for Health Economics at the University of York shows hospitals should receive additional funding in recognition of the higher costs associated with providing some types of specialised care. 

The researchers analyse the impact that specialised care has on costs for 12.9 million NHS patients treated in hospital during 2009/10. Many types of specialised care do not impose significant additional costs. But for some services, patients who received specialised care had higher costs than otherwise similar patients who do not. For example, specialised care for children increases costs by 20%.

Professor Andrew Street, from the University’s Centre for Health Economics, said: “These findings are broadly consistent with what was found when analysing the data for 2008/9. This provides further evidence to support the Department of Health’s direction of travel in setting top-up payments for specialised care.” “

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Uncertainty, evidence and irrecoverable costs: informing approval, pricing and research decisions for health technologies – Centre for Health Economics University of York – October 2011

Posted on October 19, 2011. Filed under: Evidence Based Practice, Health Economics, Health Technology Assessment | Tags: |

Uncertainty, evidence and irrecoverable costs: informing approval, pricing and research decisions for health technologies – Centre for Health Economics University of York – October 2011

by Karl Claxton, Stephen Palmer, Louise Longworth, Laura Bojke, Susan Griffin, Claire McKenna, Marta Soares, Eldon Spackman and Jihee Youn
CHE Research Paper 69

“Abstract
The general issue of balancing the value of evidence about the performance of a technology and the value of access to a technology can be seen as central to a number of policy questions. Establishing the key principles of what assessments are needed, as well as how they should be made, will enable them to be addressed in an explicit and transparent manner. This report presents the key finding from MRC and NHIR funded research which aimed to: i) Establish the key principles of what assessments are needed to inform an only in research (OIR) or Approval with Research (AWR) recommendation. ii) Evaluate previous NICE guidance where OIR or AWR recommendations were made or considered. iii) Evaluate a range of alternative options to establish the criteria, additional information and/or analysis which could be made available to help the assessment needed to inform an OIR or AWR recommendation. iv) Provide a series of final recommendations, with the involvement of key stakeholders, establishing both the key principles and associated criteria that might guide OIR and AWR recommendations, identifying what, if any, additional information or analysis might be included in the Technology Appraisal process and how such  ecommendations might be more likely to be implemented through publicly funded and sponsored research. The key principles and the assessments and judgments required are discussed in Section 2. The sequence of assessment and judgment is represented as an algorithm, which can also be summarised as a simple set of explicit criteria or a seven point checklist of assessments. The application of the check list of assessment to a series of four case studies in Section 3 can inform considerations of whether such assessments can be made based on existing information and analysis in current NICE appraisal and in what circumstances could additional information and/or analysis be useful. In Section 4, some of the implications that this more explicit assessment of OIR and AWR might have for policy (e.g., NICE guidance and drug pricing), the process of appraisal (e.g., greater involvement of research commissioners) and methods of appraisal (e.g., should additional information, evidence and analysis be required) are drawn together.”

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Truly inefficient or providing better quality of care? Analysing the relationship between risk adjusted hospital costs and patients’ health outcomes – Centre for Health Economics, University of York – 14 October 2011

Posted on October 18, 2011. Filed under: Clin Governance / Risk Mgmt / Quality, Health Economics | Tags: , |

Truly inefficient or providing better quality of care? Analysing the relationship between risk adjusted hospital costs and patients’ health outcomes – Centre for Health Economics, University of York – 14 October 2011
CHE Research Paper 68

Extract from the introduction

“Any health system that aims to make the best use of its scarce resources will be concerned about variations in costs between different providers of the same health care. If providers can reduce costs to the level of best practice, resources might be released to provide benefits elsewhere. But in analysing variations in provision, it is important to ensure that an assessment of best practice includes not just costs but also patient outcomes. High costs are not always simply due to inefficiency and may be associated with better outcomes. Low costs may sometimes be a symptom of low quality care leading to poor outcomes.

Comparative cost analysis in a multiple regression framework can help to address the question of ‘which variation in cost is justifiable’ (Keeler, 1990). By benchmarking providers against each other on the basis of their observed costs, a regulator can gain insights into the cost structure and identify the resource implications of heterogeneity (Shleifer, 1985). Over the past three decades, several hundred studies have conducted comparative analyses of hospital costs (Hollingsworth, 2008). While these have contributed to a better understanding of provider heterogeneity with respect to patient case-mix and production constraints, they have not convincingly addressed the issue of variations in quality and, particularly, health outcome as a potential explanation for observed costs (Newhouse, 1994, Jacobs et al., 2006). As a consequence, high quality hospitals may be incorrectly deemed inefficient and vice versa.

Since April 2009, all providers of publicly-funded care in the English National Health Service (NHS) are required to collect patient-reported outcome measures (PROMs) for four elective procedures: unilateral hip and knee replacements, varicose vein surgery, and groin hernia repairs (Department of Health, 2008a). Standardised questionnaires, including both generic (the EQ-5D) and conditionspecific instruments, are collected from all eligible inpatients before and 3 or 6 months after surgery.

Building on this initiative, this paper has two aims. First, we wish to explore to what extent variation in health outcomes are associated with observed cost variation in the provision of care that remains after controlling for case-mix and production constraints. Second, we investigate whether the new information on health outcomes changes our judgement of provider cost performance. We perform sensitivity analysis to assess the degree to which our findings depend on the choice of PROM instrument.”

… continues

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Improving the Productivity of the English NHS – Centre for Health Economics Research Bulletin – January 2011

Posted on January 20, 2011. Filed under: Health Economics | Tags: |

Improving the Productivity of the English NHS – Centre for Health Economics Research Bulletin – January 2011

“The NHS is required to make efficiency savings of £5bn a year, to be re-invested in front-line services. Reductions in the variation of productivity across England would go some way to achieving the government’s ambition. Let’s see why.”  …continues on the site

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An Economic Framework for Analysing the Social Determinants of Health and Health Inequalities – October 2009

Posted on November 17, 2009. Filed under: Health Economics, Public Hlth & Hlth Promotion | Tags: , |

An Economic Framework for Analysing the Social Determinants of Health and Health Inequalities – October 2009
CHE Research Paper 52 – University of York – Centre for Health Economics

“Summary

Reducing health inequalities is an important part of health policy in most countries. This paper discusses from an economic perspective how government policy can influence health inequalities, particularly focusing on the outcome of performance targets in England, and the role of sectors of the economy outside the health service – the ‘social determinants’ of health – in delivering these targets.”

This paper is the outcome of work commissioned by the Department of Health and the Review of Health Inequalities in England.

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