Over the last few years, economic evaluation of health technologies has become a major tool used by European health policy decision-makers to create strategies for prioritizing the allocation of health resources and the approval of new technologies. Spain was a pioneer in proposing the standardization of methodology applicable to economic evaluation studies. However, because health policy decision-makers refused to support the initiative, the methodology was never put into practice. In the medium term, evidence of the economic value of new health technologies financed by the national health system will probably be increasingly required. At that time, stakeholders and decision-makers will have to agree upon a clear and concise set of rules on the technical and methodological issues that must be followed by economic evaluations of health technologies. Consequently, we have provided guidelines and recommendations for producing first-rate economic evaluations. The recommendations appear under seventeen headings or sections. In each case, the recommended requirements to be satisfied by an economic evaluation of health technologies are provided and each recommendation is followed by a commentary, providing a justification and comparing and contrasting the proposal with other available alternatives.

It was postulated that home hospitalisation (HH) of selected chronic obstructive pulmonary disease (COPD) exacerbations admitted at the emergency room (ER) could facilitate a better outcome than conventional hospitalisation.To this end, 222 COPD patients (3.2% female; 71±10 yrs (mean±sd)) were randomly assigned to HH (n=121) or conventional care (n=101). During HH, integrated care was delivered by a specialised nurse with the patient's free-phone access to the nurse ensured for an 8‐week follow-up period.Mortality (HH: 4.1%; controls: 6.9%) and hospital readmissions (HH: 0.24±0.57; controls: 0.38±0.70) were similar in both groups. However, at the end of the follow-up period, HH patients showed: 1) a lower rate of ER visits (0.13±0.43versus0.31±0.62); and 2) a noticeable improvement of quality of life (Δ St George's Respiratory Questionnaire (SGRQ), −6.9versus−2.4). Furthermore, a higher percentage of patients had a better knowledge of the disease (58%versus27%), a better self-management of their condition (81%versus48%), and the patient's satisfaction was greater. The average overall direct cost per HH patient was 62% of the costs of conventional care, essentially due to fewer days of inpatient hospitalisation (1.7±2.3versus4.2±4.1 days).A comprehensive home care intervention in selected chronic obstructive pulmonary disease exacerbations appears as cost effective. The home hospitalisation intervention generates better outcomes at lower costs than conventional care.

Hospitals represent a significant proportion of health expenditures in Uganda, accounting for about 26 % of total health expenditure. Improving the technical efficiency of hospitals in Uganda can result in large savings which can be devoted to expand access to services and improve quality of care. This paper explores the technical efficiency of referral hospitals in Uganda during the 2012/2013 financial year. This was a cross sectional study using secondary data. Input and output data were obtained from the Uganda Ministry of Health annual health sector performance report for the period July 1, 2012 to June 30, 2013 for the 14 public sector regional referral and 4 large private not for profit hospitals. We assumed an output-oriented model with Variable Returns to Scale to estimate the efficiency score for each hospital using Data Envelopment Analysis (DEA) with STATA13. Using a Tobit model DEA, efficiency scores were regressed against selected institutional and contextual/environmental factors to estimate their impacts on efficiency. The average variable returns to scale (Pure) technical efficiency score was 91.4 % and the average scale efficiency score was 87.1 % while the average constant returns to scale technical efficiency score was 79.4 %. Technically inefficient hospitals could have become more efficient by increasing the outpatient department visits by 45,943; and inpatient days by 31,425 without changing the total number of inputs. Alternatively, they would achieve efficiency by for example transferring the excess 216 medical staff and 454 beds to other levels of the health system without changing the total number of outputs. Tobit regression indicates that significant factors in explaining hospital efficiency are: hospital size (p < 0.01); bed occupancy rate (p < 0.01) and outpatient visits as a proportion of inpatient days (p < 0.05). Hospitals identified at the high and low extremes of efficiency should be investigated further to determine how and why production processes are operating differently at these hospitals. As policy makers gain insight into mechanisms promoting hospital services utilization in hospitals with high efficiency they can develop context-appropriate strategies for supporting hospitals with low efficiency to improve their service and thereby better address unmet needs for hospital services in Uganda.