Rotterdam general practitioners report (ROHAPRO): a computerised network of general practices in Rotterdam, The Netherlands. Rotterdam's HuisArtsen Project (original) (raw)
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Quality of preventive performance in general practice: the use of routinely collected data
Clin Pharmacokinet, 2005
Chapter 1 services) are outlined by the college (NHG) and the association (LHV) of Dutch GPs [5]. Nearly all Dutch citizens are registered with a general practice. General practices have quite complete EMRs for their patients because most patients are registered with the same practice for long periods of time. Dutch GPs play a key role in health care delivery, and they are the gatekeepers of the health care system. The publicly insured patients require a referral from the GP before going to a consultant/specialist; privately insured patients do not, but GPs usually act as the gatekeeper for most privately insured patients as well. Consultants/specialists usually report back to general practices. Dutch GPs are partly paid by capitation (for about 60% of their patients, the publicly insured ones) and partly by fees for services (for the privately insured patients). In January 2004, there were 2392 residents for each full-time-equivalent GP in the Netherlands (16,254,933 residents and 6795 full-time-equivalent GPs). In total, there were 8209 GPs, of whom 31% were women and 79% were 40 years old or older. The GPs work in 4564 general practices, of which 60.7% were single-handed, 26.4% were shared (two GPs) and 12.9% were group practices (Table 1) [6]. 12 Chapter 1 Box 2. Cervical cancer screening and the Dutch population-based approach Population-based cervical cancer screening 'Cervical cancer" is cancer in the cervix, the lower, narrow part of the uterus (womb) Cancer of the cervix is the second most common cancer in women worldwide, and it is a leading cause of cancer-related death of women in underdeveloped countries. Worldwide, approximately 500,000 cases of cervical cancer are diagnosed each year. Early cervical cancer is often asymptomatic In women who receive regular screening, the first sign of the disease is usually an abnormal Pap test result [24] Cervical cancer is preventable and curable if it is detected early, so screening for precancerous changes in the uterine cervix, or cervical cancer itself, by examination of a cervical smear is widely recognised as instrumental in reducing both morbidity and mortality [25-27]. Appropriate management of precursor lesions detected by cervical screening reduces the risk of developing cervical cancer. The failure of women with abnormal Pap smears to return for follow-up care can increase morbidity, mortality, and the cost of health care [28] Not only is high attendance important; a high follow-up rate of cytological abnormalities is also required for an effective population-based screening programme for cervical cancer [26,27,29-32] Screening programmes were started in some European countries and North America in the 1960s [25]. Cervical cancer screening was introduced around 1970 in the Netherlands, and in 1976, an experimental massscreening programme was started in part of the country. The current Dutch cervical screening programme is nationwide and primary care based; the smears (initial and follow-up) are taken in a general practice setting [33]. The target population includes women between 30 and 60 years of age, and the screening interval is 5 years. Three main systems for inviting and reminding the women are in operation, each with a different invitation and reminder approach, namely, a fully authority-based approach, a general-practicebased approach and a combination approach in which the authonty invites the women and the GP reminds them if necessary [34] Population-based smears are free of charge to the patients, and GPs are paid for taking the smears. Furthermore, to facilitate the necessary organisation, a computer programme is available to search databases for women in the target population, inviting the eligible women, and managing the data pertaining to the smears. To spread the workload in general practices and the laboratories, invitations are spread over the year General introduction 13 facilitate the organisation; it was linked to the EMRs. This software made the organisation of both the influenza immunisation campaign and the populationbased screening easier. The software makes it easier for GPs to make lists of the target population and create personal letters to invite and remind the target group. Computers in general practice: routine data Thus, the attention to programmed prevention in general practice has accompanied further computerisation of Dutch general practices in recent years. Computers are used more and more for registration purposes, and information communication and technology, or ICT, has also become a normal part of Dutch general practice. The Dutch College of General Practitioners (NHG) and the Dutch National Association of General Practitioners (LHV) started the Working Group for Coordination, Automation, and Computerization (WCIA). The WCIA formulated reference models, which describe the minimum requirements for a General Practice Information System (GPIS) [36]. In 1994, 22% of the GPs did not have a computer at all, and only 37% made use of EMRs. In 1997, 93% of the practices were computerised and 80% used EMRs [37]. Now, almost all Dutch general practices (97%) are computerised [38]. Most GPs have replaced the paper-based patient records with EMRs in daily practice, and they are using more and more functions of the EMR systems. Patient data are entered into the computer directly during the patient encounters. Computerised EMRs can be used for many purposes, including individual patient care, management, health services research, and research on the quality of care provided to patients. General practices possess a wealth of information about the health of their patients. The central role of Dutch GPs in the delivery of health care and the stable relationship between GPs and their patients suggest that general practice records could be a very useful information source for research, education, or management [39]. General-practice-based health information has proved to be helpful for solving epidemiological and health policy questions in various studies [40], and primary care research networks are very important in building research capacity and output in primary care [41]. Therefore, we were interested to see whether such information could be used to monitor the results of the programmatic prevention activities. The Dutch National Information Network of General Practice (LINH) is available to gather data on this issue routinely. We investigated whether this network is able to 14 Chapter 1 monitor the results of the programmatic prevention activities, and whether it can be used to detect points for improvement.
Revista Panamericana De Salud Publica-pan American Journal of Public Health, 2008
Dungen, C. van den, Hoeymans, N., Gijsen, R., Akker, M. van den, Boesten, J., Brouwer, H., Smeets, H., Veen, W.J. van der, Verheij, R., Waal, M. de, Schellevis, F., Westert, G. What factors explain the differences in morbidity estimations among general practice registrations networks in the Netherlands? A first analysis.
What went and what came? Morbidity trends in general practice from the Netherlands
European Journal of General Practice, 2008
Background: Fourty years of morbidity registration in general practice is a milestone urging to present an overview of outcomes. This paper provides insight into the infrastructure and methods of the oldest practice-based research network in the Netherlands and offers an overview of morbidity in a general practice population. Changes in morbidity and some striking trends in morbidity are presented. Methods: The CMR (Continuous Morbidity Registration) collects morbidity data in four practices, in and around Nijmegen, the Netherlands. The recording is anchored in the Dutch healthcare system, which is primary care based, and where every citizen is listed with a personal GP. Trends over the period 1985Á2006 are presented as a three year moving average. As an indicator for 20-year prevalence trends we used the annual percentage change (APC). We restricted ourselves to morbidity, which is presented to the family physician on a frequent basis (overall prevalence rates 1.0/1000/year). Results: The age distribution of the CMR population is comparable to the general Dutch population. Overall incidence figures vary between 1500/1000 ptyrs (men) and 2000/1000 ptyrs (women). They are quite stable over the years, whereas overall prevalence figures are rising gradually to 1500/2500 ptyrs (men) and 2000/3500 ptyrs (women). Increase in prevalence rates for chronic conditions is diffuse and gradual with a few striking exceptions. Conclusion: For morbidity patterns, the CMR database serves as a mirror of general practice. Practice-based research networks are indispensable for the development and maintenance of general practice as an academic discipline.
Scandinavian Journal of Public Health, 2002
In this article the development of the Rotterdam Local Health Information System is sketched. Started as an oVspring of the Healthy Cities Project of the WHO, the focus was very much on neighbourhoods. The data were presented by a software program, REBUS Vision. It was relatively new to gather information at the neighbourhood level, so not much consideration was given to the relative importance of data for research questions. This led to the need to condense the vast amount of data into some summary gure, the health barometer, which chose the 27 most important available neighbourhood indicators and divided these data into six groups leading to six scores in which a neighbourhood could be compared with the city mean, other neighbourhoods, or itself in time. Although REBUS Vision and the health barometer were reasonably successful, a frequently occurring criticism was that there was too much emphasis on the signalling of public health problems. This has led to the development of a health monitor that not only signals public health problems but also tries to identify determinants and to oVer solutions on a health policy and promotion level.
Background Within the Dutch health care system the focus is shifting from a disease oriented approach to a more population based approach. Since every inhabitant in the Netherlands is registered with one general practice, this offers a unique possibility to perform Population Health Management analyses based on general practitioners’ (GP) registries. The Johns Hopkins Adjusted Clinical Groups (ACG) System is an internationally used method for predictive population analyses. The model categorizes individuals based on their complete health profile, taking into account age, gender, diagnoses and medication. However, the ACG system was developed with non-Dutch data. Consequently, for wider implementation in Dutch general practice, the system needs to be validated in the Dutch healthcare setting. In this paper we show the results of the first use of the ACG system on Dutch GP data. The aim of this study is to explore how well the ACG system can distinguish between different levels of GP ...
BMC Public Health, 2011
Background: General practice based registration networks (GPRNs) provide information on morbidity rates in the population. Morbidity rate estimates from different GPRNs, however, reveal considerable, unexplained differences. We studied the range and variation in morbidity estimates, as well as the extent to which the differences in morbidity rates between general practices and networks change if socio-demographic characteristics of the listed patient populations are taken into account. Methods: The variation in incidence and prevalence rates of thirteen diseases among six Dutch GPRNs and the influence of age, gender, socio economic status (SES), urbanization level, and ethnicity are analyzed using multilevel logistic regression analysis. Results are expressed in median odds ratios (MOR). Results: We observed large differences in morbidity rate estimates both on the level of general practices as on the level of networks. The differences in SES, urbanization level and ethnicity distribution among the networks' practice populations are substantial. The variation in morbidity rate estimates among networks did not decrease after adjusting for these socio-demographic characteristics. Conclusion: Socio-demographic characteristics of populations do not explain the differences in morbidity estimations among GPRNs.
European Journal of Epidemiology, 1994
The Réseau National Télé-informatique de surveillance et d'information sur les Maladies Transmissibles (RNTMT) (French communicable diseases computerised surveillance network) comprises a network of sentinel general practitioners (SGP). These benevolent volunteers are responsible for the weekly epidemiological surveillance. Since its creation, 1,700 SGPs have participated in the RNTMT, representing a total of more than 120,000 connections to the RNTMT telematic service center. The principal motivation of these benevolent SGPs was to ‘actively participate in public health’, although only a minority of them (17.6%) had any training in this field. Such a system, based on the benevolent and voluntary activity of SGPs, requires a good understanding of SGPs' attitudes towards epidemiological surveillance in general and the tool used, in order to quantitatively and qualitatively follow their participation and to provide regular and useful feedback to the surveillance actors.
Use of E-Health in Dutch General Practice during the COVID-19 Pandemic
International Journal of Environmental Research and Public Health, 2021
The COVID-19 pandemic has forced general practices to search for possibilities to provide healthcare remotely (e.g., e-health). In this study, the impact of the pandemic on the use of e-health in general practices in the Netherlands was investigated. In addition, the intention of practices to continue using e-health more intensively and differences in the use of e-health between practice types were investigated. For this purpose, web surveys were sent to general practices in April and July 2020. Descriptive data analysis was performed and differences in the use of e-health between practice types were tested using one-way ANOVA. Response rates were 34% (n = 1433) in April and 17% (n = 719) in July. The pandemic invoked an increased use of several (new) e-health applications. A minority of practices indicated the intention to maintain this increased use. In addition, small differences in the use of e-health between the different practice types were found. This study showed that althou...