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Background Since 1999 the Advisory Committee on Medical Manpower Planning (ACMMP) advises the Dutch government on the medical workforce capacity and the intake in training programs, as to achieve or maintain a balance on the labour market. One of the key parameters the ACMMP uses when calculating the required intake in training programs, is the attrition rate. Methods In total 11,579 trainees enrolled in hospital-based programs from January 1st 2003 until 31st of December 2012, for 26 specialisms. To explore possible explanations for the gender differences in attrition rate per specialty, additional information was gathered: the percentage of males per program, the total number of specialists in training, the duration of the training and the percentage of males currently working in that specialty. Results One training program was excluded, due to the small size of that training program (62 trainees) and the large outliers it produced. Regression analyses were done, showing significant explanations of the variation in the difference between male and female attrition rates (Y1), for the proportion of males working in the profession per 01-01-2003 (R2: .545, F(27,60), p 2: .417, F(16,01), p 2: .163, F(4,46), p 2: .299, F(9,85), p

Van Hassel DTP, Van der Velden LFJ, Batenburg RS. Diversiteit in de tijdsbestedingvan huisartsen. Huisarts Wet 2016;59(4):150-4. Het NIVEL heeft in opdracht van het Capaciteitsorgaan voor medische en tandheelkundige vervolgopleidingen de tijdsbesteding van huisartsen op een nieuwe manier gemeten. Het betreft een variant op de multi-momentopnametechniek, waarbij we sms’jes als observatiemethode hebben gebruikt. Gedurende 57 weken, van december 2012 tot en met januari 2014, hebben we elke week gemiddeld negentien huisartsen op willekeurige momenten via sms gevraagd of ze werkten, en zo ja, of ze op dat moment met een direct, indirect of niet-patientgebonden activiteit bezig waren. In totaal hebben 1051 huisartsen deelgenomen en hebben we 61.320 meetmomenten gerealiseerd. Bijna 10% van alle huisartsen in Nederland heeft aan het onderzoek meegedaan en vrijwel niemand haakte gedurende het onderzoek af. Een gemiddelde huisarts werkt 44 uur per week. Van deze uren besteedt hij of zij 56% aan direct patientgebonden activiteiten, 26% aan indirect patientgebonden activiteiten en 18% aan niet-patientgebonden activiteiten. Er zijn aanzienlijke verschillen in tijdsbesteding tussen mannelijke en vrouwelijke zelfstandig gevestigde huisartsen, huisartsen-in-dienst-van-een-huisarts (HIDHA) en huisartsen die waarnemen. Zelfstandig gevestigde mannelijke huisartsen werken met 51,6 uur het meest en mannelijke waarnemers met 26,7 uur het minst. De verschillen tussen groepen huisartsen naar functie en geslacht kunnen we voor een deel verklaren aan de hand van het aantal fte dat de huisartsen werkten. Met de gehanteerde methode kunnen we betrouwbare uitspraken doen over de tijdsbesteding van verschillende groepen huisartsen, waarbij de belasting voor de deelnemers minimaal was.

Website with surveys and instructions for the SMS week. (DOCX 16 kb)

Time sampling frame applied for sending activity messages to GPs, during one week. (DOCX 16 kb)

Van Hassel DTP, Van der Velden LFJ, Batenburg RS. Veranderingen in de loopbanen van huisartsen. Huisarts Wet 2016;59(1):6-8. Voor het landelijk opleidings- en arbeidsmarktbeleid is het van belang om te weten hoe de loopbanen van huisartsen zich door de tijd hebben ontwikkeld. Voor ons onderzoek hebben we gegevens van de NIVEL-huisartsenregistratie geanalyseerd. Deze hebben betrekking op de werksituatie van nagenoeg alle afgestudeerde huisartsen van 1981 tot en met 2011. Voor de cohortanalyse hebben we de werksituaties van huisartsen na een en zo mogelijk ook na vijf en tien jaar na afstuderen vergeleken. Daarbij hebben we ingezoomd op zeven specifieke afstudeercohorten, die elk een andere periode vertegenwoordigen van de arbeidsmarkt voor huisartsen in de afgelopen dertig jaar. De vergelijking van afstudeercohorten door de tijd laat zien dat vanaf begin jaren negentig van de vorige eeuw tot het jaar 2000 een steeds groter deel van de huisartsen zich binnen tien jaar zelfstandig heeft gevestigd. Deze ontwikkeling gaat samen met een kleiner deel dat heeft afgezien van het werk als huisarts, in een periode dat de duur van de huisartsopleiding werd verlengd. Na het jaar 2000 kiezen huisartsen vaker en langer voor een werksituatie als huisarts in dienst van een andere huisarts (HIDHA). In de afgelopen jaren zien we daarnaast de nieuwe trend dat huisartsen vaker en langer als waarnemer werken. Door onderscheid te maken in cohorten kunnen we nader onderzoeken wat de veranderende samenstelling van de huisartsenpopulatie is in relatie tot arbeidsmarktomstandigheden. Zo zien we in de periode 1981-2011 dat het aandeel huisartsen dat langer als HIDHA of waarnemer blijft werken is gegroeid. Hiermee moet men bij de capaciteitsplanning rekening houden, aangezien deze ontwikkeling van invloed is op het aantal werkzame uren en uitstroompercentages.

Parttime werken is gemeengoed geworden. Ook in de huisartsgeneeskunde. Het gevolg kan zijn dat een patient er niet altijd op kan rekenen, dat hij of zij de eigen huisarts treft. Dit speelt vooral in groepspraktijken.

Van de vijf huisartsen zijn er na vijf jaar nog vier werkzaam in dezelfde praktijk. De arbeidsmobiliteit hangt af van leeftijd en geslacht van de huisarts. Naast de oudere huisartsen die vaak de praktijk verlaten, veranderen ook jonge, vooral vrouwelijke huisartsen relatief vaak van praktijk.

Background The high cost of training and the relatively long period of training for physicians make it beneficial to stimulate physicians to retire later. Therefore, a better understanding of the link between the factors influencing the decision to retire and actual turnover would benefit policies designed to encourage later retirement. This study focuses on actual GP turnover and the determining factors for this in the Netherlands. The period 2003–2007 saw fewer GPs retiring from general practice than the period 1998–2002. In addition, GPs’ retirement age was higher in 2003–2007. For these two periods, we analysed work perception, objective workload and reasons for leaving, and related these with the probability that GPs would leave general practice at an early age. Methods In 2003, a first retrospective survey was sent to 520 self-employed GPs who had retired between 1998 and 2002. In 2008, the same survey was sent to 405 GPs who had retired between 2003 and 2007. The response rates were 60% and 54%, respectively. Analyses were done to compare work perception, objective workload, external factors and personal reasons for retiring. Results For both male and female GPs, work perception was different in the periods under scrutiny: both groups reported greater job satisfaction and a lower degree of emotional exhaustion in the later period, although there was no notable difference in subjective workload. The objective workload was lower in the second period. Moreover, most external factors and personal reasons that may contribute to the decision to retire were reported as less important in the second period. There was a stronger decrease in the probability that female GPs leave general practice within one year than for male GPs. This underscores the gender differences and the need for disaggregated data collection. Conclusions The results of this study suggest that the decrease in the probability of GPs leaving general practice within one year and the increasing retirement age are caused by a decrease in the objective workload, a change in GPs’ work perception, external factors and personal reasons. Based on the results of this study, we consider workload reduction policies are the most useful instruments to control retention and retirement.

Background Primary care nurses play an important role in diabetes care, and were introduced in GP-practice partly to shift care from hospital to primary care. The aim of this study was to assess whether the referral rate for hospital treatment for diabetes type II (T2DM) patients has changed with the introduction of primary care nurses, and whether these changes were related to the number of diabetes-related contacts in a general practice. Methods Healthcare utilisation was assessed for a period of 365 days for 301 newly diagnosed and 2124 known T2DM patients in 2004 and 450 and 3226 patients in 2006 from general practices that participated in the Netherlands Information Network of General Practice (LINH). Multilevel logistic and linear regression analyses were used to analyse the effect of the introduction of primary care nurses on referrals to internists, ophthalmologists and cardiologists and diabetes-related contact rate. Separate analyses were conducted for newly diagnosed and known T2DM patients. Results Referrals to internists for newly diagnosed T2DM patients decreased between 2004 and 2006 (OR:0.44; 95%CI:0.22-0.87) in all practices. For known T2DM patients no overall decrease in referrals to internists was found, but practices with a primary care nurse had a lower trend (OR:0.59). The number of diabetes-related contacts did not differ between practices with and without primary care nurses. Cardiologists' and ophthalmologists' referral rate did not change. Conclusions The introduction of primary care nurses seems to have led to a shift of care from internists to primary care for known diabetes patients, while the diabetes-related contact rate seem to have remained unchanged.

Background For the further development of palliative care, it is relevant to gain insight into trends in non-acute mortality. The aim of this article is twofold: (a) to provide insight into ten-year trends in the characteristics of patients who died from cancer or other chronic diseases in the Netherlands; (b) to show how national death statistics, derived from physicians' death certificates, can be used in this type of investigations. Methods Secondary analysis of data from 1996 to 2006 on the "primary" or "underlying" cause of death from official death certificates filled out by physicians and additional data from 2003 to 2006 on the place of death from these certificates. Results Of the 135,000 people who died in the Netherlands in 2006, 77,000 (or 57%) died from a chronic disease. Cancer was the most frequent cause of death (40,000). Stroke accounted for 10,000 deaths, dementia for 8,000 deaths and COPD and heart failure each accounted for 6,000 deaths. Compared to 1996, the number of people who died from chronic diseases has risen by 6%. Of all non-acute deaths, almost three quarters were at least 70 years old when they died. Almost one third of the people died at home (31%), 28% in a hospital, 25% in a nursing home and 16% somewhere else. Conclusion Further investments to facilitate dying at home are desirable. Death certificate data proved to be useful to describe and monitor trends in non-acute deaths. Advantages of the use of death certificate data concern the reliability of the data, the opportunities for selection on the basis of the ICD-10, and the availability and low cost price of the data.

Inleiding: Voor de vormgeving van beleid op het gebied van palliatieve zorg is het van belang inzicht te hebben in kenmerken van mensen die overlijden aan een niet-acute aandoening. Daarom is onderzoek verricht naar het aandeel van de sterfte dat is veroorzaakt door niet-acute aandoeningen, het aandeel daarin van verschillende aandoeningen en naar waar de niet-acute sterfte plaatsvindt. Methode: Analyse van sterftecijfers van het Centraal Bureau voor de Statistiek. Resultaten: In 2006 overleden ongeveer 135.000 personen, waarvan 73.000 (54%) aan een chronische aandoening. Kanker was veruit de meest voorkomende niet-acute doodsoorzaak (ongeveer 40.000 overledenen). CVA (na correctie voor acute sterfte), COPD, dementie en hartfalen waren ook frequente niet-acute doodsoorzaken, met elk rond de 6.000 overledenen in 2006. Bijna 90% van de niet-acuut overledenen was van Nederlandse herkomst, 8% was westers allochtoon en 2% was niet-westers allochtoon. Vrijwel eenderde van de mensen overleed thuis, 27% in een ziekenhuis, 25% in een verpleeghuis en 15% elders. Ten opzichte van 1996 is de sterfte aan chronische aandoeningen met 0,7% per jaar gestegen. Discussie: Een verdere groei van de niet-acute sterfte is te verwachten. Het aantal niet-westerse allochtonen dat aan een chronische aandoening zal sterven, zal gaan groeien.

Background An increasing number of newly trained Dutch GPs prefer to work in a group practice and as a non-principal rather than in a single-handed practice. In view of the greater number of female doctors, changing practice preferences, and discussions on future workforce problems, the question is whether male and female GPs were able to realise their initial preferences in the past and will be able to do so in the future. Methods We have conducted longitudinal cohort study of all GPs in the Netherlands seeking a practice between 1980 and 2004. The Netherlands Institute of Health Services Research (NIVEL) in Utrecht collected the data used in this study by means of a postal questionnaire. The overall mean response rate was 94%. Results Over the past 20 years, an increasing proportion of GPs, both male and female, were able to achieve their preference for working in a group practice and/or in a non-principal position. Relatively more women than men have settled in group practices, and more men than women in single-handed practices; however, the practice preference of men and women is beginning to converge. Dropout was highest among the GPs without any specific practice preference. Conclusion The overwhelming preference of male and female GPs for working in group practices is apparently being met by the number of positions (principal or non-principal) available in group practices. The preference of male and female GPs regarding the type of practice and job conditions is expected to converge further in the near future.

Background Health workforce projections are important instruments to prevent imbalances in the health workforce. For both the tenability and further development of these projections, it is important to evaluate the accuracy of workforce projections. In the Netherlands, health workforce projections have been done since 2000 to support health workforce planning. What is the accuracy of the techniques of these Dutch general practitioner workforce projections? Methods We backtested the workforce projection model by comparing the ex-post projected number of general practitioners with the observed number of general practitioners between 1998 and 2011. Averages of historical data were used for all elements except for inflow in training. As the required training inflow is the key result of the workforce planning model, and has actually determined past adjustments of training inflow, the accuracy of the model was backtested using the observed training inflow and not an average of historical data to avoid the interference of past policy decisions. The accuracy of projections with different lengths of projection horizon and base period (on which the projections are based) was tested. Results The workforce projection model underestimated the number of active Dutch general practitioners in most years. The mean absolute percentage errors range from 1.9% to 14.9%, with the projections being more accurate in more recent years. Furthermore, projections with a shorter projection horizon have a higher accuracy than those with a longer horizon. Unexpectedly, projections with a shorter base period have a higher accuracy than those with a longer base period. Conclusions According to the results of the present study, forecasting the size of the future workforce did not become more difficult between 1998 and 2011, as we originally expected. Furthermore, the projections with a short projection horizon and a short base period are more accurate than projections with a longer projection horizon and base period. We can carefully conclude that health workforce projections can be made with data based on relatively short base periods, although detailed data are still required to monitor and evaluate the health workforce.

In de afgelopen tien jaar is het aantal huisartsen in dienst van een huisarts (HIDHA’s) meer dan verdubbeld. Hoe komt dat? Zijn er meer net afgestudeerde huisartsen die HIDHA worden? Is er een tendens om langer HIDHA te blijven? Kortom, waar komen al die HIDHA’s vandaan?