Patient satisfaction with out-of-hours primary care in the Netherlands

BACKGROUND: In recent years out-of-hours primary care in the Netherlands has changed from practice-based to large-scale cooperatives. The purpose of this study is to determine patient satisfaction with current out-of-hours care organised in general practitioner (GP) cooperatives, and gain insight in factors associated with this satisfaction. METHODS: From March to June 2003, 2805 questionnaires were sent to patients within three weeks after they had contacted the GP cooperative in their region. The study was conducted in the province of Limburg in the South of the Netherlands. One-third of these questionnaires was sent to patients who had only received telephone advice, one-third to patients who attended the GP cooperative for consultation, and one-third to patients who received a home visit. Four weeks after the first reminder, a non-respondents telephone interview was performed among a random sample of 100 patients. Analyses were performed with respect to the type of consultation. RESULTS: The total response was 42.4% (1160/2733). Sixty-seven percent of patients who received telephone advice only reported to be satisfied with out-of-hours care. About 80% of patients who went to the GP cooperative for consultation or those receiving a home visit, reported to be satisfied. Factors that were strongly associated with overall satisfaction included, the doctor's assistant's attitude on the phone, opinion on GP's treatment, and waiting time. CONCLUSION: Patients seem generally satisfied with out-of-hours primary care as organised in GP cooperatives. However, patients who received telephone advice only are less satisfied compared to those who attended the GP cooperative or those who received a home visit

Follow-up care by patient's own general practitioner after contact with out-of-hours care. A descriptive study

BACKGROUND: Little is known about the care process after patients have contacted a GP cooperative for out-of-hours care. The objective of this study was to determine the proportion of patients who seek follow-up care after contact with a GP cooperative for out-of-hours care, and to gain insight into factors that are related to this follow-up care. METHODS: A total of 2805 patients who contacted a GP cooperative for out-of-hours care were sent a questionnaire. They were asked whether they had attended their own GP within a week after their contact with the cooperative, and for what reason. To investigate whether other variables are related to follow-up care, a logistic regression analysis was applied. Variables that entered in this analysis were patient characteristics (age, gender, etc.) and patient opinion on correctness of diagnosis, urgency and severity of the medical complaint. RESULTS: The response rate was 42%. In total, 48% of the patients received follow-up care from their own GP. Only 20% were referred or advised to attend their own GP. Others attended because their medical condition worsened or because they were concerned about their complaint. Variables that predicted follow-up care were the patient's opinion on the correctness of the diagnosis, patient's health insurance, and severity of the medical problem. CONCLUSION: Almost half of all patients in this study who contacted the GP cooperative for out-of-hours care attended their own GP during office hours within a week, for the same medical complaint. The most important factor that predicted follow-up care from the patient's own GP after an out-of-hours contact was the patient's degree of confidence in the diagnosis established at the GP cooperative. Despite the limited generalisability, this study is a first step in providing insight into the dimension of follow-up care after a patient has contacted the GP cooperative for out-of-hours primary care

A review of health care models for coronary heart disease interventions

This article reviews models for the treatment of coronary heart disease (CHD). Whereas most of the models described were developed to assess the cost effectiveness of different treatment strategies, other models have also been used to extrapolate clinical trials, for capacity and resource planning, or to predict the future population with heart disease. In this paper we investigate the use of modelling techniques in relation to different types of health intervention, and we discuss the assumptions and limitations of these approaches. Many of the models reviewed in this paper use decision tree models for acute or short term interventions, and Markov or state transition models for chronic or long term interventions. Discrete event simulation has, however, been used for more complex whole system models, and for modelling resource-constrained interventions and operational planning. Nearly all of the studies in our review used cohort-based models rather than population based models, and therefore few models could estimate the likely total costs and benefits for a population group. Most studies used de novo purpose built models consisting of only a small number of health states. Models of the whole disease system were less common. The model descriptions were often incomplete. We recommend that the reporting of model structure, assumptions and input parameters is more explicit, to reduce the risk of biased reporting and ensure greater confidence in the model results