Organisational determinants of production and efficiency in general practice: a population-based study.

OBJECTIVE: Shortage of general practitioners (GPs) and an increased political focus on primary care have enforced the interest in efficiency analysis in the Danish primary care sector. This paper assesses the association between organisational factors of general practices and production and efficiency. METHODS: We assume that production and efficiency can be modelled using a behavioural production function. We apply the Battese and Coelli (Empir Econ 20:325-332, 1995) estimator to accomplish a decomposition of exogenous variables to determine the production frontier and variables determining the individual GPs distance to this frontier. Two different measures of practice outputs (number of office visits and total production) were applied and the results compared. RESULTS: The results indicate that nurses do not substitute GPs in the production. The production function exhibited constant returns to scale. The mean level of efficiency was between 0.79 and 0.84, and list size was the most important determinant of variation in efficiency levels. CONCLUSIONS: Nurses are currently undertaking other tasks than GPs, and larger practices do not lead to increased production per GP. However, a relative increase in list size increased the efficiency. This indicates that organisational changes aiming to increase capacity in general practice should be carefully designed and tested.

[Association between productivity, list size, patient and practice characteristics in general practice]. / Sammenhaeng mellem produktivitet, listestørrelse, patient- og praksiskarakteristika i almen praksis.

INTRODUCTION: Due to shortage of general practitioners, it may be necessary to improve productivity. We assess the association between productivity, list size and patient- and practice characteristics. MATERIAL AND METHODS: A regression approach is used to perform productivity analysis based on national register data and survey data for 1,758 practices. Practices are divided into four groups according to list size and productivity. Statistical tests are used to assess differences in patient- and practice characteristics. RESULTS: There is a significant, positive correlation between list size and productivity (p < 0.01). Nevertheless, 19% of the practices have a list size below and a productivity above mean sample values. These practices have relatively demanding patients (older, low socioeconomic status, high use of pharmaceuticals) and they are frequently located in areas with limited access to specialized care and have a low use of assisting personnel. 13% of the practices have a list size above and a productivity below mean sample values. These practices have relatively less demanding patients, are located in areas with good access to specialized care, and have a high use of assisting personnel. CONCLUSIONS: Lists and practice characteristics have substantial influence on both productivity and list size. Adjusting list size to external factors seems to be an effective tool to increase productivity in general practice.

Comparing hospital costs: what is gained by accounting for more than a case-mix index?

We explore what effect controlling for various patient characteristics beyond a case-mix index (DRG) has on inferences drawn about the relative cost performance of hospital departments. We estimate fixed effect cost models in which 3754 patients are clustered within six Danish vascular departments. We compare a basic model including a DRG index only with models also including age and gender, health related characteristics, such as smoking status, diabetes, and American Society of Anesthesiogists score (ASA-score), and socioeconomic characteristics such as income, employment and whether the patient lives alone. We find that the DRG index is a robust and important explanatory factor and adding other routinely collected characteristics such as age and gender and other health related or socioeconomic characteristics do not seem to alter the results significantly. The results are more sensitive to choice of functional form, i.e. in particular to whether costs are log transformed. Our results suggest that the routinely collected characteristics such as DRG index, age and gender are sufficient when drawing inferences about relative cost performance. Adding health related or socioeconomic patient characteristics only slightly improves our model in terms of explanatory power but not when drawing inferences about relative performance. The results are, however, sensitive to whether costs are log transformed.

Association between general practice referral rates and patients' socioeconomic status and access to specialised health care a population-based nationwide study.

OBJECTIVES: To explore the association between patients' socioeconomic status and their referral from general practice to specialised health care. METHODS: Multiple regression analysis was used on cross-sectional data on general practice referral rates for all Danish general practices in year 2006. RESULTS: Our models explained between 26% and 45% of the variation in general practice referral to specialised care. Adjusting for access to specialised care (local supply of hospitals and practicing specialists) reduced the association between socioeconomic factors and referral rates. The results suggest that persons with high socioeconomic status are referred more to practicing specialist than persons with low socioeconomic status and that the latter are referred more to hospital care than the former. CONCLUSIONS: Our results indicate that the influence of socioeconomic factors may be overstated failing to control for access to specialised care. Still, a socioeconomic gradient was observed in GPs' referral pattern to different sorts of health care after adjusting for access. The association between socioeconomic status and referral pattern can both be rooted in morbidity variation and to the ability of persons with high socioeconomic status to influence general practitioners' (GPs') decision making.