Dinny H. de Bakker

Measuring the working hours of general practitioners (GPs) is an important but complex task due to the effects of bias related to self-reporting, recall, and stress. In this paper we describe the deployment, feasibility, and implementation of an innovative method for measuring, in real time, GPs’ working time, plus the response to the study. A Short Message Service (SMS) application was developed which sent messages at random to GPs during their working week. Approximately nineteen GPs participated each week during a period of 57 weeks. The text messages asked if GPs were doing activities related to patients, directly, indirectly, or not at all, at the moment of sending. Participants were requested to reply by SMS. Approximately 27,000 messages were sent to 1051 GPs over more than one year. The SMS system was functioning 99.9% of the time. GPs replied to 94% of all the messages sent. Only a few participants dropped out of the study. The data was available in real time enabling the researchers to monitor the response and overall quality of the data each day. The SMS method offers advantages over other instruments of measurement because it allows a better response, ease of use and avoids recall bias. This makes it a feasible method to collect valid data about GPs working time.

In several countries, the number of hours worked by general practitioners (GPs) has decreased, raising concern about current and impending workforce shortages. This shorter working week has been ascribed both to the feminisation of the workforce and to a younger generation of GPs who prefer more flexible working arrangements. There is, however, limited insight into how the impact of these determinants interact. We investigated the relative importance of differences in GPs’ working hours in relation to gender, age, and employment position. An analysis was performed on real-time monitoring data collected by sending SMS text messages to 1051 Dutch GPs, who participated during a 1-week time use study. We used descriptive statistics, independent sample t-tests, and one-way ANOVA analysis to compare the working time of different GP groups. A path analysis was conducted to examine the difference in working time by gender, age, employment position, and their combinations. Female GPs worked significantly fewer hours than their male peers. GPs in their 50s worked the highest number of hours, followed by GPs age 60 and older. GPs younger than 40 worked the lowest number of hours. This relationship between working hours and age was not significantly different for women and men. As shown by path analysis, female GPs consistently worked fewer hours than their male counterparts, regardless of their age and employment position. The relationship between age and working hours was largely influenced by gender and employment position. The variation in working hours among GPs can be explained by the combination of gender, age, and employment position. Gender appears to be the most important predictor as the largest part of the variation in working hours is explained by a direct effect of this variable. It has previously been reported that the difference in working hours between male and female GPs had decreased over time. However, our findings suggest that gender remains a critical factor for variation in time use and for policy instruments such as health workforce planning.

Our research is based on a technique for time sampling, an innovative method for measuring the working hours of Dutch general practitioners (GPs), which was deployed in an earlier study. In this study, 1051 GPs were questioned about their activities in real time by sending them one SMS text message every 3 h during 1 week. The required sample size for this study is important for health workforce planners to know if they want to apply this method to target groups who are hard to reach or if fewer resources are available. In this time-sampling method, however, standard power analyses is not sufficient for calculating the required sample size as this accounts only for sample fluctuation and not for the fluctuation of measurements taken from every participant. We investigated the impact of the number of participants and frequency of measurements per participant upon the confidence intervals (CIs) for the hours worked per week. Statistical analyses of the time-use data we obtained from GPs were performed. Ninety-five percent CIs were calculated, using equations and simulation techniques, for various different numbers of GPs included in the dataset and for various frequencies of measurements per participant. Our results showed that the one-tailed CI, including sample and measurement fluctuation, decreased from 21 until 3 h between one and 50 GPs. As a result of the formulas to calculate CIs, the increase of the precision continued and was lower with the same additional number of GPs. Likewise, the analyses showed how the number of participants required decreased if more measurements per participant were taken. For example, one measurement per 3-h time slot during the week requires 300 GPs to achieve a CI of 1 h, while one measurement per hour requires 100 GPs to obtain the same result. The sample size needed for time-use research based on a time-sampling technique depends on the design and aim of the study. In this paper, we showed how the precision of the measurement of hours worked each week by GPs strongly varied according to the number of GPs included and the frequency of measurements per GP during the week measured. The best balance between both dimensions will depend upon different circumstances, such as the target group and the budget available.

The sports club is seen as a new relevant setting to promote health-enhancing physical activity (HEPA) among inactive population groups. Little is known about the effectiveness of strategies and activities implemented in the sports club setting on increasing HEPA levels. This study investigated the effects of Start2Bike, a six-week training program for inactive adults and adult novice cyclers, on HEPA levels of participants in the Netherlands. To measure physical activity, the Short QUestionnaire to ASsess Health-enhancing physical activity was used (SQUASH). Start2Bike participants were measured at baseline, six weeks and six months. A matched control group was measured at baseline and six months. The main outcome measure was whether participants met the Dutch Norm for Health-enhancing Physical Activity (DNHPA: 30 min of moderate-intensity activity on five days a week); Fit-norm (20 min of vigorous-intensity activity on three days a week); and Combi-norm (meeting the DNHPA and/or Fit-norm). Other outcome measures included: total minutes of physical activity per week; and minutes of physical activity per week per domain and intensity category. Statistical analyses consisted of McNemar tests and paired t-tests (within-group changes); and multiple logistic and linear regression analyses (between-group changes). In the Start2Bike group, compliance with Dutch physical activity norms increased significantly, both after six weeks and six months. Control group members did not alter their physical activity behavior. Between-group analyses showed that participants in the Start2Bike group were more likely to meet the Fit-norm at the six-month measurement compared to the control group (odds ratio = 2.5; 95% confidence interval (CI) = 1.1–5.8, p = 0.03). This was due to the Start2Bike participants spending on average 193 min/week more in vigorous-intensity activities (b = 193; 95% CI = 94–293, p < 0.001) and 130 min/week more in sports activities (b = 130; 95% CI = 82–178, p < 0.001) than control group members. Start2Bike positively influences HEPA levels of participants by increasing participation in sport. A relatively short sporting program, offered by a sports club, can be used to encourage less active people to engage in and continue sport at HEPA levels. Overall, sport can contribute to health through increased HEPA and the sports club can serve as a setting to stimulate this.

In a gatekeeper system, primary care physicians and patients jointly decide whether or not medical specialist care is needed. However, it is the patient who decides to actually use the referral. Referral non-compliance could delay diagnosis and treatment. The objective of this study was to assess patient compliance with a referral to medical specialist care and identify patient and practice characteristics that are associated with it. Observational study using data on 48,784 referrals to medical specialist care derived from electronic medical records of 58 general practices for the period 2008–2010. Referral compliance was based on claims data of medical specialist care. Logistic multilevel regression analyses were conducted to determine associations between patient and general practice characteristics and referral compliance. In 86.6 % of the referrals, patients complied. Patient and not practice characteristics were significantly associated with compliance. Patients from deprived urban areas and patients aged 18–44 years were less likely to comply, whereas patients aged 65 years and older were more likely to comply. About 1 in 8 patients do not use their referral. These patients may not receive adequate care. Demographic and socio-economic factors appear to affect compliance. The results of this study may be used to make general practitioners more aware that some patients are more likely to be noncompliant with referrals.

Shoulder complaints are common and have an unfavourable prognosis in many patients. Prognostic information is helpful for both patients and clinicians in managing the complaints. The research question was which factors have prognostic value on (un)favourable outcome in patients with shoulder complaints in primary care, secondary care and occupational settings. Update of a systematic review in primary care, secondary care and occupational settings. Nine articles were published since the original review in 2004. Six were of high quality covering a wide variety of prognostic factors and outcome measures. Four studies were conducted in primary care settings. A best evidence synthesis, including the results of the previous systematic review on this topic shows that there is strong evidence that higher shoulder pain intensity, concomitant neck pain and a longer duration of symptoms predict poorer outcome in primary care settings. In secondary care populations, strong evidence was found for the association between greater disability and poorer outcome and between the existence of previous shoulder pain and poorer outcome. Clinicians may take these factors into account in the management of their patients. Those with a worse prognosis may be monitored more frequently and the treatment plan modified if complaints persist.

General practitioners have an ideal position to motivate inactive patients to increase their physical activity. Most patients are able to exercise in regular local facilities outside the health care setting. The purpose of this study was to get insight into general practitioners perceptions and current practices regarding referral of patients to local exercise facilities. Furthermore, collaboration with exercise providers in the community was investigated, and motivators and barriers for referral. A written questionnaire sent to a representative random sample of 800 Dutch general practitioners. Descriptive statistics and Chi2 tests were used. All responding general practitioners (340) recommend their patients to take more exercise when necessary and 87 % say to refer patients sometimes. Limited motivation of the patient (44 %) and reduced health status (34 %) are the most mentioned barriers for advising patients to increase physical activity. When referred, most patients are send to a physical therapist (69 %) but also local exercise facilities were mentioned (54 %). The most important barrier for referring patients to local exercise activities are patients limited financial possibilities (46 %). Restricted knowledge of local exercise- or sport facilities was an additional barrier (19 %). There is little structural collaboration between general practitioners and exercise providers, but when collaboration exists general practitioners refer more often. Positive experiences of patients (67 %), affordable offers (59 %) and information of local exercise facilities (46 %) are seen as important promoting factors for referral. Although 32 % of the general practitioners think that good collaboration would be stimulating, regular meetings with sports and exercise providers were considered the least important for increasing referral (3 %). Dutch physicians have a positive attitude towards stimulating physical activity but referral to local exercise facilities is low. Referral is partly hindered by restricted knowledge of local exercise facilities. Although general practitioners think that collaboration is important for physical activity promotion, it should not cost them much extra time. A coordinator with knowledge of the local situation can facilitate contacts between GP practices and sports providers.

A multidisciplinary, guideline-based Stepped-Care-Strategy (SCS), has recently been developed to improve the management of hip and knee osteoarthritis (OA). To date, it is unknown to what extent current Dutch OA care is consistent with the SCS, both with respect to the content of care as well as the sequence of care. Furthermore, there is a lack of clarity regarding the role of different health care providers in the performance of OA care according to the SCS. Therefore, the main purpose of this study is to describe the content of primary care in patients with hip/knee OA, including the compliance to the SCS and taking into account the introduction of patient self-referral to physical therapy. Data were used from NIVEL Primary Care Database. In total, 12.118 patients with hip/knee OA who visited their GP or physical therapist were selected. Descriptive statistics were used to compare the content of care in GP-referred and self-referred patients to physical therapy. Content of care performed by GPs mostly concerned consultations, followed by NSAID prescriptions and referrals to secondary care. Both prescriptions of acetaminophen and referrals to physical therapy respectively dietary therapy were rarely mentioned. Nevertheless, still 65% of the patients in physical therapy practice were referred by their GP. Compared to GP-referred patients, self-referred patients more often presented recurrent complaints and were treated less often by activity-related exercise therapy. Education was rarely registered as singular intervention, neither in GP-referred nor in self-referred patients. In accordance with the SCS, less advanced interventions are more often applied than more advanced interventions. To optimize the adherence to the SCS, GPs could reconsider the frequent use of NSAIDs instead of analgesics and the low referral rate to allied health care. Self-referral to physical therapy partially distorts both the low referral rate in general practice and the low application rate of education as singular intervention in physical therapy practice. Further research is recommended to evaluate the effects of task-shifting in OA care, taking into account the content of the SCS.

The organized sports sector has received increased attention as a setting to promote health-enhancing physical activity (HEPA) to the general population. For significant public health impact, it is important that successful HEPA programs are widely adopted, implemented and continued as ongoing practice. The importance of evaluating the context in which programs are implemented has been identified as critical. However, little research has focused on understanding the organized sports implementation context, including factors facilitating and impeding implementation. In this study, the main factors influencing implementation of HEPA programs in the organized sports setting were studied. Fourteen sporting programs in the Netherlands aimed at increasing participation in sports by inactive population groups and funded within the National Action Plan for Sport and Exercise (NAPSE) were investigated. The programs were developed by ten Dutch National Sports Federations (NSFs) and implemented by different sports clubs in the Netherlands over a 3-year implementation period (June 2008–June 2011). The qualitative research component involved yearly face-to-face interviews (i.e. fourteen interviews each year, n = 12 program coordinators) and a group meeting with the program coordinators of the NSFs (n = 8). Cross-case comparisons and thematic analyses were performed to identify and categorize important facilitating and impeding factors respectively. The quantitative research component, used to identify the most important facilitating and impeding factors across all sporting programs, consisted of ranking of factors according to importance by the program coordinators (n = 12). Different factors act during six identified (implementation) phases. When comparing factors across phases, several key learnings were evident. Successful implementation relied, for example, on program design and enthusiastic individuals within sporting organizations. On the other hand, inactive people were hard to reach and participation of sports clubs was not self-evident. The findings were discussed in a broader context. This study adds to the knowledge base concerning the implementation of sporting programs, aimed at inactive people, in the organized sports setting. The main factors facilitating and impeding implementation were identified. The results of this study can be used by sports practitioners and policy makers when developing and implementing HEPA programs in this setting.

In the Netherlands, primary out-of-hours (OOH) care is provided by large scale General Practitioner (GP) cooperatives. GP cooperatives can be contacted by patients living in the area surrounding the GP cooperative (catchment area) at hours when the patient’s own general practice is closed. The frequency of primary OOH care use substantially differs between GP cooperative catchment areas. To enable a better match between supply and demand of OOH services, understanding of the factors associated with primary OOH care use is essential. The present study evaluated the contribution of sociodemographic composition of the neighbourhood in explaining differences in primary OOH care use between GP cooperative catchment areas. Data about patients’ contacts with primary OOH services (n = 1,668,047) were derived from routine electronic health records of 21 GP cooperatives participating in the NIVEL Primary Care Database in 2012. The study sample is representative for the Dutch population (for age and gender). Data were matched with sociodemographic characteristics (e.g. gender, age, low-income status, degree of urbanisation) on postcode level. Multilevel linear regression models included postcode level (first level), nested within GP cooperative catchment areas (second level). We investigated whether contacts in primary OOH care were associated with neighbourhood sociodemographic characteristics. The demand of primary OOH care was significantly higher in neighbourhoods with more women, low-income households, non-Western immigrants, neighbourhoods with a higher degree of urbanisation, and low neighbourhood socioeconomic status. Conversely, lower demand was associated with neighbourhoods with more 5 to 24 year old inhabitants. Sociodemographic neighbourhood characteristics explained a large part of the variation between GP cooperatives (R-squared ranging from 8% to 52%). Nevertheless, the multilevel models also showed that a considerable amount of variation in demand between GP cooperatives remained unexplained by sociodemographic characteristics, particularly regarding high-urgency contacts. Although part of the variation between GP cooperatives could not be attributed to neighbourhood characteristics, the sociodemographic composition of the neighbourhood is a fair predictor of the demand of primary OOH care. Accordingly, this study provides a useful starting point for an improved planning of the supply of primary OOH care.