Objectives: We investigate variations in costs and length of stay (LoS) among hospitals for ten clinical treatments to assess: 1. The extent to which resource use is driven by the characteristics of patients and of the type and quality of care they receive; 2. After taking these characteristics into account, the extent to which resource use is related to the hospital in which treatment takes place; 3. If conclusions are robust to whether resource use is described by costs or by LoS. Data: We analysed patient-level data from the Hospital Episode Statistics (HES) data for 2007/8, which contains approximately 16.5 million inpatient records. This dataset was merged with costs derived from the Reference Cost database. We extracted data on three medical ‘conditions’ (acute myocardial infarction (AMI); childbirth; stroke) and seven surgical treatments (appendectomy; breast cancer (mastectomy); coronary artery bypass graft (CABG); cholecystectomy; inguinal hernia; hip replacement; and knee replacement). Methods: For each treatment, we used a two-stage approach to investigate variations in cost and LoS. In stage I, we ran fixed effects models to explore which patient-level factors explain variations. In stage II, we regressed the fixed effects from stage I against an array of hospital characteristics. Results: The number of patients analysed ranged from 18,875 (CABG) to 549,036 (childbirth), and the number of hospitals ranged from 28 (CABG) to 151 (appendectomy, hernia and hip replacement). Across the ten treatments, patient factors explained between 32% (stroke) and 72% (breast cancer and knee replacement) of the observed variation in costs. In the LoS analyses, the corresponding figures were 28% (stroke) and 63% (hip replacement). A higher number of diagnoses were consistently associated with higher cost and longer LoS. A higher number of procedures had a similar effect for 9 of the 10 treatments. The effects of age and gender were mixed, but higher levels of deprivation were associated with longer stays in 8 of the 10 treatments analysed. LoS was significantly longer for patients who were cared for by more than one hospital doctor, regardless of the treatment received. In the seven surgical interventions, wound infection was always associated with longer stays and usually with higher cost. Emergency admissions increased LoS for all conditions except stroke. After accounting for these patient-level factors, substantial variation in costs and LoS among hospitals was evident for all ten treatments. These variations could not be explained by hospital characteristics such as size, teaching status, and the amount of the treatment in question that the hospital performed. We found that average hospital costs or LoS were correlated across similar types of treatments, notably hernia, cholecystectomy and appendectomy and hip and knee replacement. A small number of hospitals had considerably lower average costs or LoS for most treatments; similarly some hospitals had considerably higher average costs or LoS. Conclusion: The findings suggest that all hospitals have scope to make efficiency savings in at least one of the clinical areas considered by this study. A small number of hospitals have higher average costs or LoS across multiple treatments than their counterparts, and this cannot be explained by the characteristics of their patients or the quality of care. These hospitals are likely to struggle financially under Payment by Results (PbR) and need to consider how to improve their use of resources.
