NHS input and productivity growth 2003/4 - 2007/8

Productivity growth is measured by comparing the rate of output growth with the rate of input growth. In an earlier report we calculated output growth in the English NHS for the period 2003/4 to 2006/7 (Castelli et al., 2008). This report concentrates on input growth, detailing methods and calculating growth from 2003/4 to 2007/8.

Regional variation in the productivity of the English National Health Service

At a time when there are severe pressures on reducing public spending there is increasing emphasis on determining which parts of the country secure best value for money in the NHS. By linking together large scale and routinely collected datasets we produce and compare productivity estimates across the ten Strategic Health Authorities in England in 2007/08.

Why do patients having coronary artery bypass grafts have different costs or length of stay? : An analysis across ten European countries

We analyse variations in costs or lengths of stay (LoS) for 66,587 patients from ten European countries receiving a coronary artery bypass graft (CABG) procedure. In five of these countries, variations in cost are analysed using log-linear models. In the other five countries, negative binomial regression models are used to explore variations in LoS. We compare how well each country’s Diagnosis Related Group (DRG) system and a set of patient-level characteristics explain these variations. The most important explanatory factors are the total number of diagnoses and procedures, although no clear effects are evident for our CABG-specific diagnostic and procedural variables. Wound infections significantly increase length of stay and costs in all countries. There is no evidence that countries using larger numbers of DRGs to group CABG patients were better at explaining variations in cost or LoS. However, refinements to the construction of DRGs to group CABG patients might recognise first and subsequent CABGs or other specific surgical procedures, such as multiple valve repair

How well do DRGs for appendectomy explain variations in resource use? : An analysis of patient-level data from 10 European countries

Appendectomy is a common and relatively simple procedure to remove an inflamed appendix, but the rate of appendectomy varies widely across Europe. This paper investigates factors that explain differences in resource use for appendectomy. We analysed 106,929 appendectomy patients treated in 939 hospitals in ten European countries. In stage one, we tested the performance of three models in explaining variation in the (log of) cost of the inpatient stay (seven countries) or length-of-stay (three countries). The first model used only the Diagnosis Related Groups (DRGs) to which patients were coded; the second used a core set of general patient-level and appendectomy-specific variables; and the third model combined both sets of variables. In stage two, we investigated hospital-level variation. In classifying appendectomy patients, most DRG systems take account of complex diagnoses and comorbidities, but use different numbers of DRGs (range: 2 to 8). The capacity of DRGs and patient-level variables to explain patient-level cost variation ranges from 34% in Spain to over 60% in England and France. All DRG systems can make better use of administrative data such as the patient’s age, diagnoses and procedures, and all countries have outlying hospitals that could improve their management of resources for appendectomy

English hospitals can improve their use of resources : an analysis of costs and length of stay for ten treatments

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 wa

NHS productivity from 2004/5 to 2010/11

2010/11 was the first full financial year of a Coalition government committed to meeting the so called “Nicholson challenge” of making £20bn efficiency savings in projected NHS expenditure by 2015. Securing improvements in NHS productivity is seen as a key element in meeting this challenge. In what follows we report year-on-year changes in productivity from 2004/5 to 2010/1

Examining variations in hospital productivity in the english nhs

Numerous papers have measured hospital efficiency, mainly using a technique known as data envelopment analysis (DEA). A shortcoming of this technique is that the number of outputs for each hospital generally outstrips the number of hospitals. In this paper, we propose an alternative approach, involving the use of explicit weights to combine diverse outputs into a single index, thereby avoiding the need for DEA. Hospital productivity is measured as the ratio of outputs to inputs. Outputs capture quantity and quality of care for hospital patients; inputs include staff, equipment, and capital resources applied to patient care. Ordinary least squares regression is used to analyse why output and productivity varies between hospitals. We assess whether results are sensitive to consideration of quality. Hospital productivity varies substantially across hospitals but is highly correlated year on year. Allowing for quality has little impact on relative productivity. We find that productivity is lower in hospitals with greater financial autonomy, and where a large proportion of income derives from education, research and development, and training activities. Hospitals treating greater proportions of children or elderly patients also tend to be less productive. We have set out a means of assessing hospital productivity that captures their multiple outputs and inputs. We find substantial variation in productivity among English hospitals, suggesting scope for productivity improvement

Examining variations in hospital productivity in the English NHS

Numerous papers have measured hospital efficiency, mainly using a technique known as data envelopment analysis (DEA). A shortcoming of this technique is that the number of outputs for each hospital generally outstrips the number of hospitals. In this paper, we propose an alternative approach, involving the use of explicit weights to combine diverse outputs into a single index, thereby avoiding the need for DE

Regional Variation in the Productivity of the English National Health Service CHE Research Paper 57Regional variation in the productivity of the English National Health Service Report for the Department of Health

CHE Discussion Papers (DPs) began publication in 1983 as a means of making current research material more widely available to health economists and other potential users. So as to speed up the dissemination process, papers were originally published by CHE and distributed by post to a worldwide readership. The CHE Research Paper series takes over that function and provides access to current research output via web-based publication, although hard copy will continue to be available (but subject to charge)