Project description:OBJECTIVES:To examine the association between financial performance as measured by operating margin (surplus/deficit as a proportion of turnover) and clinical outcomes in English National Health Service (NHS) trusts. SETTING:Longitudinal, observational study in 149 acute NHS trusts in England between the financial years 2011 and 2016. PARTICIPANTS:Our analysis focused on outcomes at individual NHS Trust-level (composed of one or more acute hospitals). PRIMARY AND SECONDARY OUTCOMES:Outcome measures included readmissions, inpatient satisfaction score and the following process measures: emergency department (Accident and Emergency (A&E)) waiting time targets, cancer referral and treatment targets and delayed transfers of care (DTOCs). RESULTS:There was a progressive increase in the proportion of trusts in financial deficit: 22% in 2011, 27% in 2012, 28% in 2013, 51% in 2014, 68% in 2015 and 91% in 2016. In linear regression analyses, there was no significant association between operating margin and clinical outcomes (readmission rate or inpatient satisfaction score). There was, however, a significant association between operating margin and process measures (DTOCs, A&E breaches and cancer waiting time targets). Between the best and worst financially performing Trusts, there was an approximately 2-fold increase in A&E breaches and DTOCs overall although this variation decreased over the 6 years. Between the best and worst performing trusts on cancer targets, the magnitude of difference was smaller (1.16 and 1.15-fold), although the variation slowly rose during the 6 years. CONCLUSIONS:Operating margins in English NHS trusts progressively worsened during 2011-2016, and this change was associated with poorer performance on several process measures but not with hospital readmissions or inpatient satisfaction. Significant variation exists between the best and worst financially performing Trusts. Further research is needed to examine the causal nature of relationships between financial performance, process measures and outcomes.
Project description:Prescribing errors are a source of preventable harm in healthcare, which may be mitigated using Electronic Prescribing (EP) systems. Anyone who routinely prescribes medication could benefit from digitally assisted automated checks to identify whether a prescription should potentially not be allowed (e.g. drug allergy). National Health Service (NHS) Trusts have implemented a range of EP systems; however, their performance has not hitherto been evaluated. We developed the web-based Electronic Prescribing Risk and Safety Evaluation (ePRaSE) tool, which comprises a bank of prescribing scenarios to evaluate the performance of EP systems. We solicited ePRaSE testing: 68 pharmacists from across 45 English NHS Trusts, utilising 13 different EP systems volunteered for the study. We found considerable variability in mitigation performance (systems correctly identifying risk of error when prescribing) across both NHS Trusts and EP systems. Moreover, we found that mitigation performance varied considerably across NHS Trusts using the same EP system, strongly suggesting there are opportunities to optimise performance within systems. The ePRaSE tool is effective in identifying variability in risk management between NHS Trusts and EP systems. Wider use of this tool may facilitate improvements in EP system configurations, thus minimising potential harm from prescribing errors.
Project description:ObjectivesNumerous 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.MethodsHospital 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.ResultsHospital 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.ConclusionsWe 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.
Project description:We investigate the extent to which small hospitals are associated with lower quality. We first take a patient perspective, and test if, controlling for casemix, patients admitted to small hospitals receive lower quality than those admitted to larger hospitals. We then investigate if differences in quality between large and small hospitals can be explained by hospital characteristics such as hospital type and staffing. We use a range of quality measures including hospital mortality rates (overall and for specific conditions), hospital acquired infection rates, waiting times for emergency patients, and patient perceptions of the care they receive. We find that small hospitals, with fewer than 400 beds, are generally not associated with lower quality before or after controlling for hospital characteristics. The only exception is heart attack mortality, which is generally higher in small hospitals.
Project description:Systems and processes for prescribing, supplying and administering inpatient medications can have substantial impact on medication administration errors (MAEs). However, little is known about the medication systems and processes currently used within the English National Health Service (NHS). This presents a challenge for developing NHS-wide interventions to increase medication safety. We therefore conducted a cross-sectional postal census of medication systems and processes in English NHS hospitals to address this knowledge gap.The chief pharmacist at each of all 165 acute NHS trusts was invited to complete a questionnaire for medical and surgical wards in their main hospital (July 2011). We report here the findings relating to medication systems and processes, based on 18 closed questions plus one open question about local medication safety initiatives. Non-respondents were posted another questionnaire (August 2011), and then emailed (October 2011).One hundred (61% of NHS trusts) questionnaires were returned. Most hospitals used paper-based prescribing on the majority of medical and surgical inpatient wards (87% of hospitals), patient bedside medication lockers (92%), patients' own drugs (89%) and 'one-stop dispensing' medication labelled with administration instructions for use at discharge as well as during the inpatient stay (85%). Less prevalent were the use of ward pharmacy technicians (62% of hospitals) or pharmacists (58%) to order medications on the majority of wards. Only 65% of hospitals used drug trolleys; 50% used patient-specific inpatient supplies on the majority of wards. Only one hospital had a pharmacy open 24 hours, but all had access to an on-call pharmacist. None reported use of unit-dose dispensing; 7% used an electronic drug cabinet in some ward areas. Overall, 85% of hospitals had a double-checking policy for intravenous medication and 58% for other specified drugs. "Do not disturb" tabards/overalls were routinely used during nurses' drug rounds on at least one ward in 59% of hospitals.Inter- and intra-hospital variations in medication systems and processes exist, even within the English NHS; future research should focus on investigating their potential effects on nurses' workflow and MAEs, and developing NHS-wide interventions to reduce MAEs.
Project description:BackgroundHealth care systems in OECD countries are increasingly facing economic challenges and funding pressures. These normally demand interventions (political, financial and organisational) aimed at improving the efficiency of the health system as a whole and its single components. In 2009, the English NHS Chief Executive, Sir David Nicholson, warned that a potential funding gap of £20 billion should be met by extensive efficiency savings by March 2015. Our study investigates possible drivers of differential Trust performance (productivity) for the financial years 2010/11-2012/13.MethodsFollowing accounting practice, we define Productivity as the ratio of Outputs over Inputs. We analyse variation in both Total Factor and Labour Productivity using ordinary least squares regressions. We explicitly included in our analysis factors of differential performance highlighted in the Nicholson challenge as the sources were the efficiency savings should come from. Explanatory variables include efficiency in resource use measures, Trust and patient characteristics, and quality of care.ResultsWe find that larger Trusts and Foundation Trusts are associated with lower productivity, as are those treating a greater proportion of both older and/or younger patients. Surprisingly treating more patients in their last year of life is associated with higher Labour Productivity.
Project description:Recent substantive reforms to the English National Health Service expanded patient choice and encouraged hospitals to compete within a market with fixed prices. This study investigates whether these reforms led to improvements in hospital quality. We use a difference-in-difference-style estimator to test whether hospital quality (measured using mortality from acute myocardial infarction) improved more quickly in more competitive markets after these reforms came into force in 2006. We find that after the reforms were implemented, mortality fell (i.e. quality improved) for patients living in more competitive markets. Our results suggest that hospital competition can lead to improvements in hospital quality.