Investigating Patient Outcome Measures in Mental Health

This report examines the feasibility of incorporating patient outcomes in mental health into a productivity measure. It examines which outcome measures are most commonly used in mental health, the practical issues about collecting these outcome measures, whether they can be converted into a generic measure, whether there is a time series of data available, and whether the data exists to examine changes in the mix of treatments over time. The criteria that were assumed to be important for an outcome measure to be included in a productivity index, were that it should have wide coverage, should be routinely collected, could readily be linked to activity data, could potentially be converted to a generic outcome measure, and would be available as a time-series. The report focuses predominantly on mental health outcomes within the working age population. Literature searches on outcome measurement in mental health covered numerous databases and retrieved over 1500 records. Around 170 full papers were obtained.

Alternative methods to examine hospital efficiency: Data Envelopment Analysis and Stochastic Frontier Analysis

There has been increasing interest in the ability of different methods to rank efficient hospitals over their inefficient counterparts. The UK Department of Health has used three cost indices to benchmark NHS Trusts. This study uses the same dataset and compares the efficiency rankings from the cost indices with those obtained using Data Envelopment Analysis (DEA) and Stochastic Cost Frontier Analysis (SCF). The paper concludes that each method each has particular strengths and weaknesses and potentially measure different aspects of efficiency. Several specifications should be used to develop ranges of inefficiency to act as signalling devices rather than point estimates. There appears to be a large amount of random ‘noise’ in the study which suggests that there are not truly large efficiency differences between Trusts, and savings from bringing up poorer performers would in fact be very modest.efficiency

Towards panel data specifications of efficiency measures for English acute hospitals

This paper reports work undertaken for the Department of Health to explore different approaches of measuring hospital efficiency. The emphasis throughout is on developing adjusted cost-efficiency measures in line with NHS Trusts performance objectives. Previous work described the derivation of three residual-based cost indices (CCI, 2CCI and 3CCI), each with increasing adjustment in terms of case mix, factor prices and environmental factors for a single year’s data (1995/6) (Söderlund & van der Merwe, 1999). This study explores further options based on the previous work by: (1) supplementing hospital level with specialty level data; (2) studying a 4-year panel from 1994/5 to 1997/8; (3) estimating models with non-symmetric error terms and including Trust-specific effects when measuring inefficiency. Although the paper argues that panel data models may have certain advantages over cross-sectional ones, the results suggest that data pooling across years provide robust parameter estimates. Longitudinal fixed effect models may however be useful to construct efficiency indices while stochastic frontier models have the advantage of taking account of random noise. Specialty level models proved inferior to whole hospital estimations. The paper argues that the degree of variation between hospitals in terms of efficiency is not that great and scope for efficiency enhancement is primarily attainable by optimising capacity and activity levels in the long run. Increased activity levels may however have adverse consequences such as increased hospital infection rates, poorer quality of care and a lack of capacity to deal with emergency demand. The paper argues that the Department of Health might consider a shift from the adjusted cost index approach used in this normative benchmarking framework to the more conventional efficiency analysis approach using a total cost function, and more flexible functional forms, allowing for a more defensible interpretation of the residuals as inefficiency.efficiency

A descriptive analysis of general acute Trust star ratings

This paper examines the relationship between acute NHS Trust star ratings in England (generated by the Department of Health) in 2000/01 and 2001/02 with various other Trust characteristics and performance indicators from a Trust level database maintained by the Centre for Health Economics. The Trust star ratings system is a composite performance measure which places Trusts into one of four categories: from three stars, awarded to Trusts with the highest levels of performance to zero stars, awarded to Trusts showing the poorest levels of performance. We examine the descriptive statistics for the various variables in the dataset over the two years, according to each star rating as well as one-way Analysis of Variance (ANOVA) using zero star Trusts as the reference category and then least squares to fit a linear model to each of the variables in the dataset. Although zero star Trusts appear to perform better in terms of clinical outcomes such as death rates and readmissions, this is not statistically significant. However, zero star Trusts do worse than other Trusts across various patient satisfaction measures and financial and efficiency measures. Three star Trusts outperform others on two grounds fairly consistently: waiting times and financial balance suggesting either more efficient management or fewer capacity constraints. The labour market for consultants and nurses also appear to be utilised in different ways across the groups of Trusts. One hypothesis is that the different groups of Trusts focus on different elements of performance. The extent to which differences are due to exogenous factors or internal factors is a question for future research.analysis of variance (ANOVA), star rating, zero star Trusts

Social health insurance systems in European countries: the role of the insurer in the health care system: a comparative study of four European countries

This paper examines the role of social health insurance in four European countries: Germany, Switzerland, France and the Netherlands. It attempts to elucidate the organisational structure, regulation and management of the social insurance schemes, as well as the relationships between the insurers, providers and consumers in the various countries with the aim of uncovering some of the inherent strengths, weaknesses and tradeoffs hich exist within social insurance systems.health care systems, Europe, insurance

Do waiting times reduce hospital costs?

Using a sample of 137 hospitals over the period 1998-2002 in the English National Health Service, we estimate the elasticity of hospital costs with respect to waiting times. Our cross-sectional and panel-data results suggest that at the sample mean (103 days), waiting times have no significant effect on hospital, costs or, at most, a positive one. If significant, the elasticity of cost with respect to waiting time from our cross-sectional estimates is in the range 0.4-1. The elasticity is still positive but lower in our fixed-effects specifications (0.2-0.4). In all specifications, the effect of waiting time on cost is non-linear, suggesting a U-shaped relationship between hospital costs and waiting times: the level of waiting time which minimises total costs is always below ten days.

Public services: are composite measures a robust reflection of performance in the public sector?

A composite indicator is an aggregated index comprising individual performance indicators. Composite indicators integrate a large amount of information in a format that is easily understood and are therefore a valuable tool for conveying a summary assessment of performance in priority areas. This research investigates the degree to which composite measures are an appropriate metric for evaluating performance in the public sector. Do they reflect accurately the performance of organisations? To what degree are they influenced by the uncertainty surrounding underlying indicators on which they are based? Are they robust and stable over time? The construction of composite measures creates specific methodological challenges that make such questions especially pertinent. We address these through a series of quantitative analyses of panel data relating to healthcare (Star ratings of NHS acute Trusts) and local government (Comprehensive Performance Assessment (CPA) ratings of authorities) in England where composites have been widely used. The creation of a composite comprises a number of important steps, each of which requires careful judgement. These include the specification of the choice of indicators, the transformation of measured performance on individual indicators, the specification of a set of weights on individual indicators, and combining the indicators using aggregation methods or decision rules. We use Monte Carlo simulations to examine the robustness of performance judgements to these different technical choices. We show the extent to which composites provide stable performance rankings of organisations over time and assess whether variations are due to genuine performance improvement or merely the result of random statistical variation. The analysis suggests that the judgements that have to be made in the construction of the composite can have a significant impact on the resulting score. Technical and analytical issues in the design of composite indicators have important policy implications. We highlight the issues which need to be considered in the construction of robust composite indicators so that they can be designed in ways which will minimise the potential for producing misleading performance information which may fail to deliver the expected improvements or even induce unwanted side-effects.performance measurement, performance indicators, composite indicators

The Effects of Budgets on Doctors Behaviour: Evidence from a Natural Experiment

In many health care systems primary care physicians act as ‘gatekeepers’ to secondary care. We investigates the impact of the UK fundholding scheme under which general practices could elect to hold a budget to meet the costs of elective surgery for their patients. We use a differences in differences methodology on a large four year panel of English general practices before and after the abolition of fundholding. Fundholding incentives reduced fundholder elective admission rates by 3.3% and accounted for 57% of the difference between fundholder and nonfundholder elective admissions, with 43% a selection effect due to unobservable differences in practice characteristics. Fundholding had no effect on emergency admissions.budgets, health care, fundholding, admission rates

Trends in health care commissioning in the English NHS: an empirical analysis

In recent years there have been marked changes in organisational structures and budgetary arrangements in the English NHS, potentially altering the relationships between purchasers (primary care organisations (PCOs) and general practices) and providers. Using data on elective hospital admissions from 1997/98 to 2002/03 we find that commissioning has become significantly more concentrated at PCO and GP level. There was a reduction in the average number of different providers used by PCOs (16.7 to 14.2), an increase in the average share of admissions accounted for by the main provider (49% to 69%), and an increase in the average Herfindahl index (0.35 to 0.55). About half the increase in concentration arose from the increase in the number of purchasing organisations from 100 to 302. The rest was due to mergers amongst providers and the abolition of fundholding. GP fundholding practices which held budgets for elective admissions had less concentrated admission patterns than non-fundholders whose admissions were paid for by their primary care organisation. There was an increase in concentration of admissions for both types of GP practice but fundholders used more providers, had smaller shares at their main provider, and had smaller Herfindahl indices.concentration, Herfindahl, purchasing, budgets, elective admissions

Exploring the impact of public services on quality of life indicators

The fundamental aim of public services is to improve the quality of life of citizens. The main objective of this study was to investigate the influence of public service organisations (PSOs) on aspects of quality of life (broadly measured) of citizens at a local level. We assembled a rich database using 20 of the 45 quality of life measures developed by the Audit Commission. Those we selected covered broad areas of quality of life such as safety, housing, health, education, and transport and were available at ‘small area’ level. We used a range of advanced statistical methods to analyse the relationships between PSOs and quality of life measures at different hierarchical levels. The techniques were selected to be robust when making comparisons between levels and when looking at associations between quality of life measures. Our descriptive analyses (bivariate correlations, factor analysis and ANOVA) suggested overall some significant correlations between some of the quality of life variables. The SUR model results also indicated that the quality of life indicators are correlated, and therefore that we should look at these measures in a joint modelling approach such as MVML, as envisaged in the study objectives.