Medical Specialist Care Utilization Prior to the Explantation of Cosmetic Silicone Breast Implants: A Nationwide Retrospective Data Linkage Study.

BACKGROUND: Explantation is the proposed treatment for breast implant illness (BII). Little is known about which medical specialists are visited and what diagnoses are made before explantation is provided as the treatment. OBJECTIVES: This study investigated medical specialist care utilization in women with cosmetic breast implants who underwent explantation compared to women who chose breast implant replacement surgery and to women without breast implants. METHODS: Retrospective cohort study using data linkage with the Dutch Breast Implant Registry and the Dutch health insurance claims database. Visits to medical specialists were examined over the 3 years before explantation. A total of 832 explantation patients were matched and compared to 1463 breast implant replacement patients and 1664 women without breast implants. RESULTS: Explantation patients were more likely to have visited > 5 different medical specialties compared to both replacement patients (12.3% vs. 5.7%; p < 0.001) and women without breast implants (12.3% vs. 3.7%; p < 0.001). Among explantation patients, women who underwent explantation because of BII were more likely to have visited > 5 different medical specialties compared to women who underwent explantation because of other reasons (25.0% vs. 11.0%; p < 0.001). CONCLUSIONS: Women who underwent explantation of breast implants had higher utilization of medical specialist care in the years before explantation compared to women who underwent breast implant replacement surgery and women without breast implants. Medical specialist care use was especially high among women for whom BII was the registered reason for explantation. These findings suggest further research is needed into the link between BII and the use of medical specialist care. LEVEL OF EVIDENCE III: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

What can we learn from experiences in general practice during the COVID-19 pandemic? A qualitative study.

BACKGROUND: Experiences with organizational changes in daytime general practices and out-of-hours (OOH) services during the COVID-19 pandemic may help to address the challenges in general practice care that were already a concern before the crisis. This study aimed to describe these experiences and the potential usefulness of the organizational changes for future general practice care and any future pandemics. METHODS: Semi-structured interviews were performed among 11 directors of OOH services, and 19 (locum) general practitioners (GPs) or practice managers, who were purposively sampled. Video or telephone interviews were performed in two rounds: between November 2020 and January 2021 and between May 2021 and August 2021. The data were analyzed using thematic analysis methods. RESULTS: Three themes emerged from the data: (1) Changes in the triage procedures; in GP practices and OOH services, stricter triage criteria were implemented, and GPs were more actively involved in the triage process. These measures helped to reduce the number of 'low urgency' face-to-face consultations. (2) Changes in GP care; there was a shift towards video and telephone consultations, allowing GPs to spend more time with patients during the remaining face-to-face consultations. For chronic patients, the shift towards telemonitoring appeared to encourage self-care, and postponing face-to-face consultations for regular checkups appeared to be unproblematic for stable patients. (3) Coordination of GP care and information communication flow during the COVID-19 pandemic; OOH directors perceived a lack of consistency in the information from various governmental and non-governmental parties on containment measures and guidelines related to COVID-19, making it difficult to act on them. The COVID-19 pandemic intensified collaboration between GPs, OOH services, and other healthcare professionals. CONCLUSIONS: The results of this study indicate that some of the organizational changes, such as stricter triage, remote consultations, and changes in managed care of chronic patients, may help in tackling the pre-existing challenges in GP care from before the COVID-19 pandemic. However, more extensive research and continuous monitoring are necessary to establish the effects on patients and their health outcomes. To navigate future pandemics, the intensified collaboration between health professionals should be maintained, while there is considerable room for improvement in the provision of unambiguous information.

Opt-In and Opt-Out Consent Procedures for the Reuse of Routinely Recorded Health Data in Scientific Research and Their Consequences for Consent Rate and Consent Bias: Systematic Review.

BACKGROUND: Scientific researchers who wish to reuse health data pertaining to individuals can obtain consent through an opt-in procedure or opt-out procedure. The choice of procedure may have consequences for the consent rate and representativeness of the study sample and the quality of the research, but these consequences are not well known. OBJECTIVE: This review aimed to provide insight into the consequences for the consent rate and consent bias of the study sample of opt-in procedures versus opt-out procedures for the reuse of routinely recorded health data for scientific research purposes. METHODS: A systematic review was performed based on searches in PubMed, Embase, CINAHL, PsycINFO, Web of Science Core Collection, and the Cochrane Library. Two reviewers independently included studies based on predefined eligibility criteria and assessed whether the statistical methods used in the reviewed literature were appropriate for describing the differences between consenters and nonconsenters. Statistical pooling was conducted, and a description of the results was provided. RESULTS: A total of 15 studies were included in this meta-analysis. Of the 15 studies, 13 (87%) implemented an opt-in procedure, 1 (7%) implemented an opt-out procedure, and 1 (7%) implemented both the procedures. The average weighted consent rate was 84% (60,800/72,418 among the studies that used an opt-in procedure and 96.8% (2384/2463) in the single study that used an opt-out procedure. In the single study that described both procedures, the consent rate was 21% in the opt-in group and 95.6% in the opt-out group. Opt-in procedures resulted in more consent bias compared with opt-out procedures. In studies with an opt-in procedure, consenting individuals were more likely to be males, had a higher level of education, higher income, and higher socioeconomic status. CONCLUSIONS: Consent rates are generally lower when using an opt-in procedure compared with using an opt-out procedure. Furthermore, in studies with an opt-in procedure, participants are less representative of the study population. However, both the study populations and the way in which opt-in or opt-out procedures were organized varied widely between the studies, which makes it difficult to draw general conclusions regarding the desired balance between patient control over data and learning from health data. The reuse of routinely recorded health data for scientific research purposes may be hampered by administrative burdens and the risk of bias.

Setting up a Governance Framework for Secondary Use of Routine Health Data in Nursing Homes: Development Study Using Qualitative Interviews.

BACKGROUND: In the nursing home sector, reusing routinely recorded data from electronic health records (EHRs) for knowledge development and quality improvement is still in its infancy. Trust in appropriate and responsible reuse is crucial for patients and nursing homes deciding whether to share EHR data for these purposes. A data governance framework determines who may access the data, under what conditions, and for what purposes. This can help obtain that trust. Although increasing attention is being paid to data governance in the health care sector, little guidance is available on development and implementation of a data governance framework in practice. OBJECTIVE: This study aims to describe the development process of a governance framework for the "Registry Learning from Data in Nursing Homes," a national registry for EHR data on care delivered by nursing home physicians (in Dutch: specialist ouderengeneeskunde) in Dutch nursing homes-to allow data reusage for research and quality improvement of care. METHODS: Relevant stakeholders representing practices, policies, and research in the nursing home sector were identified. Semistructured interviews were conducted with 20 people from 14 stakeholder organizations. The main aim of the interviews was to explore stakeholders' perspectives regarding the Registry's aim, data access criteria, and governing bodies' tasks and composition. Interview topics and analyses were guided by 8 principles regarding governance for reusing health data, as described in the literature. Interview results, together with legal advice and consensus discussions by the Registry's consortium partners, were used to shape the rules, regulations, and governing bodies of the governance framework. RESULTS: Stakeholders valued the involvement of nursing home residents and their representatives, nursing home physicians, nursing homes' boards of directors, and scientists and saw this as a prerequisite for a trustworthy data governance framework. For the Registry, involvement of these groups can be achieved through a procedure in which residents can provide their consent or objection to the reuse of the data, transparency about the decisions made, and providing them a position in a governing body. In addition, a data request approval procedure based on predefined assessment criteria indicates that data reuse by third parties aligns with the aims of the Registry, benefits the nursing home sector, and protects the privacy of data subjects. CONCLUSIONS: The stakeholders' views, expertise, and knowledge of other frameworks and relevant legislation serve to inform the application of governance principles to the contexts of both the nursing home sector and the Netherlands. Many different stakeholders were involved in the development of the Registry Learning from Data in Nursing Homes' governance framework and will continue to be involved. Engagement of the full range of stakeholders in an early stage of governance framework development is important to generate trust in appropriate and responsible data reuse.

The use of out-of-hours primary care during the first year of the COVID-19 pandemic.

BACKGROUND: In the Netherlands, General Practitioners (GP) are usually the first point of contact with a health professional for most health problems. Out-of-hours (OOH) primary care is provided by regional OOH services. Changes in consultation rates at OOH services may be regarded as a warning system for failures elsewhere in the healthcare system. Therefore in this study, we investigated how the COVID-19 pandemic changed the use of primary care OOH services during the first year of the pandemic. METHODS: Routine electronic health records data were used from 60% of OOH services in the Netherlands, collected by the Nivel Primary Care Database. We compared consultation rates per week (2020) for COVID-19-like symptoms and other health problems (e.g. small traumas, urinary tract infections), for different age groups, the proportion of remote consultations, and different levels of urgency during the pandemic compared to the same period in 2019. RESULTS: The number of consultations for COVID-19-like symptoms peaked at the start of the COVID-19 pandemic, while consultations for other health problems decreased. These changes in consultation rates differed between age groups. Remote consultations took place more frequently for all health problems, while the proportion of non-urgent health problems increased. CONCLUSION: There were significant changes in the number of consultations and the proportion that were remote for COVID-19-like symptoms and other health problems. Especially care for babies and young children decreased, while the number of consultations for older adults remained stable. The continued use of OOH services by older adults suggests there were unmet care needs elsewhere in our healthcare system.

Psychotropic drug prescription rates in primary care for people with dementia from recorded diagnosis onwards.

BACKGROUND: Psychotropic drugs are frequently prescribed to people with dementia in nursing homes although severe adverse events and side effects are common. Less is known about the prevalence and types of psychotropic drug prescription in primary care for people with dementia. OBJECTIVE: This study examined the prevalence of psychotropic drug prescriptions in primary care among persons with dementia from the year of diagnosis onwards. METHODS: A longitudinal observational study using electronic health record (EHR) data was conducted. People with dementia were selected from EHR data of 451 general practices in the Netherlands. Age and gender-adjusted psychotropic drug prescription rates were calculated per 1000 person-years from the year the dementia diagnosis was first recorded in general practice up to 8 years after diagnosis. RESULTS: Data of 15,687 patients were analyzed. The prescription rate of psychotropic drugs (not including antidementia drugs) was 420 per 1000 person-years (95% CI 409; 431) in the first year after the recorded dementia diagnosis, which increased to 801 per 1000 person-years (95% CI 649; 989) in the eighth year. The most frequently prescribed drugs were antidepressants, antipsychotics, and antidementia drugs, followed by anxiolytics, hypnotics, and antiepileptics. CONCLUSIONS: After a dementia diagnosis is recorded in general practice, the prevalence of psychotropic drug prescriptions is substantial and increases steadily during the disease trajectory of persons with dementia. Although the (in)appropriateness of prescribing was not assessed, these insights may stimulate primary care clinicians to (re)consider their prescription policy of psychotropics for people with dementia more carefully.

Immediate and long-term health impact of exposure to gas-mining induced earthquakes and related environmental stressors.

BACKGROUND: Little is known about the public health impact of chronic exposure to physical and social stressors in the human environment. Objective of this study was to investigate the immediate and long-term health effects of living in an environment with gas-mining induced earthquakes and related stressors in the Netherlands. METHODS: Data on psychological, somatic and social problems recorded routinely in electronic health records by general practitioners during a 6-year period (2010-2015) were combined with socioeconomic status and seismicity data. To assess immediate health effects of exposure to ML≥1.5 earthquakes, relative risk ratios were calculated for patients in the week of an earthquake and the week afterwards, and compared to the week before the earthquake. To analyse long-term health effects, relative risks of different groups, adjusted for age, sex and socioeconomic status, were computed per year and compared. RESULTS: Apart from an increase in suicidality, few immediate health changes were found in an earthquake week or week afterwards. Generally, the prevalence of health problems was higher in the mining province in the first years, but dropped to levels equal to or even below the control group in subsequent years, with lower relative risks observed in more frequently exposed patients. CONCLUSIONS: From a public health perspective, the findings are fascinating. Contrary to our expectation, health problems presented in general practice in the earthquake province decreased during the study period. More frequently exposed populations reported fewer health issues to general practitioners, which might point at health adaptation to chronic exposure to stressors.

Income-related differences in out-of-hours primary care telephone triage using national registration data.

BACKGROUND: Telephone triage is used to facilitate efficient and adequate acute care allocation, for instance in out-of-hours primary care services (OPCSs). Remote assessment of health problems is challenging and could be impeded by a patient's ambiguous formulation of his or her healthcare need. Socioeconomically vulnerable patients may experience more difficulty in expressing their healthcare need. We aimed to assess whether income differences exist in the patient's presented symptoms, assessed urgency and allocation of follow-up care in OPCS. METHOD: Data were derived from Nivel Primary Care Database encompassing electronic health record data of 1.3 million patients from 28 OPCSs in 2017 in the Netherlands. These were linked to sociodemographic population registry data. Multilevel logistic regression analyses (contacts clustered in patients), adjusted for patient characteristics (eg, age, sex), were conducted to study associations of symptoms, urgency assessment and follow-up care with patients' income (standardised for household size as socioeconomic status (SES) indicator). RESULTS: The most frequently presented symptoms deduced during triage slightly differed across SES groups, with a larger relative share of trauma in the high-income groups. No SES differences were observed in urgency assessment. After triage, low income was associated with a higher probability of receiving telephone advice and home visits, and fewer consultations at the OPCS. CONCLUSIONS: SES differences in the patient's presented symptom and in follow-up in OPCS suggest that the underlying health status and the ability to express care needs affect the telephone triage process . Further research should focus on opportunities to better tailor the telephone triage process to socioeconomically vulnerable patients.

Socioeconomic inequalities in out-of-hours primary care use: an electronic health records linkage study.

BACKGROUND: Low socioeconomic position (SEP) is related to higher healthcare use in out-of-hours primary care services (OPCSs). We aimed to determine whether inequalities persist when taking the generally poorer health status of socioeconomically vulnerable individuals into account. To put OPCS use in perspective, this was compared with healthcare use in daytime general practice (DGP). METHODS: Electronic health record (EHR) data of 988 040 patients in 2017 (251 DGPs, 27 OPCSs) from Nivel Primary Care Database were linked to socio-demographic data (Statistics, The Netherlands). We analyzed associations of OPCS and DGP use with SEP (operationalized as patient household income) using multilevel logistic regression. We controlled for demographic characteristics and the presence of chronic diseases. We additionally stratified for chronic disease groups. RESULTS: An income gradient was observed for OPCS use, with higher probabilities within each lower income group [lowest income, reference highest income group: odds ratio (OR) = 1.48, 95% confidence interval (CI): 1.45-1.51]. Income inequalities in DGP use were considerably smaller (lowest income: OR = 1.17, 95% CI: 1.15-1.19). Inequalities in OPCS were more substantial among patients with chronic diseases (e.g. cardiovascular disease lowest income: OR = 1.60, 95% CI: 1.53-1.67). The inequalities in DGP use among patients with chronic diseases were similar to the inequalities in the total population. CONCLUSIONS: Higher OPCS use suggests that chronically ill patients with lower income had additional healthcare needs that have not been met elsewhere. Our findings fuel the debate how to facilitate adequate primary healthcare in DGP and prevent vulnerable patients from OPCS use.

Time from diagnosis to institutionalization and death in people with dementia.

INTRODUCTION: Reliable estimates of time from diagnosis until institutionalization and death in people with dementia from routine nationally representative databases are lacking. METHODS: We selected 9230 people with dementia and 24,624 matched controls from family physicians' electronic records linked with national administrative databases to analyze time until institutionalization and death and associated factors. RESULTS: Median time from recorded diagnosis until institutionalization and until death for people with dementia was 3.9 and 5.0 years, respectively, which was considerably shorter than for controls. Once institutionalized, median time to death was longer for persons with dementia (2.5 years) than for controls (1.2 years). Older age and receiving home care were the strongest predictors of shorter time until institutionalization and death in people with dementia. Gender, cohabitation, migration status, frailty, polypharmacy, and dementia medication were other significant factors. DISCUSSION: The estimates could help to inform patients, their families, and policymakers about probable trajectories.

Calculating incidence rates and prevalence proportions: not as simple as it seems.

BACKGROUND: Incidence rates and prevalence proportions are commonly used to express the populations health status. Since there are several methods used to calculate these epidemiological measures, good comparison between studies and countries is difficult. This study investigates the impact of different operational definitions of numerators and denominators on incidence rates and prevalence proportions. METHODS: Data from routine electronic health records of general practices contributing to NIVEL Primary Care Database was used. Incidence rates were calculated using different denominators (person-years at-risk, person-years and midterm population). Three different prevalence proportions were determined: 1 year period prevalence proportions, point-prevalence proportions and contact prevalence proportions. RESULTS: One year period prevalence proportions were substantially higher than point-prevalence (58.3 - 206.6%) for long-lasting diseases, and one year period prevalence proportions were higher than contact prevalence proportions (26.2 - 79.7%). For incidence rates, the use of different denominators resulted in small differences between the different calculation methods (-1.3 - 14.8%). Using person-years at-risk or a midterm population resulted in higher rates compared to using person-years. CONCLUSIONS: All different operational definitions affect incidence rates and prevalence proportions to some extent. Therefore, it is important that the terminology and methodology is well described by sources reporting these epidemiological measures. When comparing incidence rates and prevalence proportions from different sources, it is important to be aware of the operational definitions applied and their impact.

Does shared decision-making reduce antibiotic prescribing in primary care?

Background: Increasing antibiotic resistance is recognized as a major threat to global health and is related to antibiotic prescription rates in primary care. Shared decision-making (SDM), the process in which patients and doctors participate together in making decisions, is argued to possibly promote more appropriate use of antibiotics and reduce prescribing. However, it is unknown whether in practice fewer antibiotics are prescribed where more SDM takes place. Objectives: To investigate whether more SDM is related to less antibiotic prescribing and whether this relationship differs between subgroups of patients (male/female and age groups). Patients and methods: A questionnaire survey was conducted among 2670 members of the Dutch Health Care Consumer Panel to measure SDM (response rate 45%). Average practice-level SDM scores were calculated for 15 general practices. Data from routine electronic health records of 8192 adult patients of these general practices participating in the Nivel Primary Care Database were used to assess relevant illness episodes (acute cough, acute rhinosinusitis and urinary tract infection), the indication for antibiotics and antibiotic prescriptions. Logistic multilevel regression analyses were performed to investigate the relationship between practice-level SDM and patient-level antibiotic prescriptions. Results: In practices where more SDM takes place, general practitioners prescribed fewer antibiotics for adult patients under the age of 40 years in preference-sensitive situations (i.e. situations in which antibiotics could be considered according to clinical guidelines). Conclusions: SDM can be a framework to reduce the prescribing of antibiotics and thus to control antibiotic resistance.

Recording of weight in electronic health records: an observational study in general practice.

BACKGROUND: Routine weight recording in electronic health records (EHRs) could assist general practitioners (GPs) in the identification, prevention, and management of overweight patients. However, the extent to which weight management is embedded in general practice in the Netherlands has not been investigated. The purpose of this study was to evaluate the frequency of weight recording in general practice in the Netherlands for patients who self-reported as being overweight. The specific objectives of this study were to assess whether weight recording varied according to patient characteristics, and to determine the frequency of weight recording over time for patients with and without a chronic condition related to being overweight. METHODS: Baseline data from the Occupational and Environmental Health Cohort Study (2012) were combined with data from EHRs of general practices (2012-2015). Data concerned 3446 self-reported overweight patients who visited their GP in 2012, and 1516 patients who visited their GP every year between 2012 and 2015. Logistic multilevel regression analyses were performed to identify associations between patient characteristics and weight recording. RESULTS: In 2012, weight was recorded in the EHRs of a quarter of patients who self-reported as being overweight. Greater age, lower education level, higher self-reported body mass index, and the presence of diabetes mellitus, chronic obstructive pulmonary disease, and/or cardiovascular disorders were associated with higher rates of weight recording. The strongest association was found for diabetes mellitus (adjusted OR = 10.3; 95% CI [7.3, 14.5]). Between 2012 and 2015, 90% of patients with diabetes mellitus had at least one weight measurement recorded in their EHR. In the group of patients without a chronic condition related to being overweight, this percentage was 33%. CONCLUSIONS: Weight was frequently recorded for overweight patients with a chronic condition, for whom regular weight measurement is recommended in clinical guidelines, and for which weight recording is a performance indicator as part of the payment system. For younger patients and those without a chronic condition related to being overweight, weight was less frequently recorded. For these patients, routine recording of weight in EHRs deserves more attention, with the aim to support early recognition and treatment of overweight.

Possible Sources of Bias in Primary Care Electronic Health Record Data Use and Reuse.

BACKGROUND: Enormous amounts of data are recorded routinely in health care as part of the care process, primarily for managing individual patient care. There are significant opportunities to use these data for other purposes, many of which would contribute to establishing a learning health system. This is particularly true for data recorded in primary care settings, as in many countries, these are the first place patients turn to for most health problems. OBJECTIVE: In this paper, we discuss whether data that are recorded routinely as part of the health care process in primary care are actually fit to use for other purposes such as research and quality of health care indicators, how the original purpose may affect the extent to which the data are fit for another purpose, and the mechanisms behind these effects. In doing so, we want to identify possible sources of bias that are relevant for the use and reuse of these type of data. METHODS: This paper is based on the authors' experience as users of electronic health records data, as general practitioners, health informatics experts, and health services researchers. It is a product of the discussions they had during the Translational Research and Patient Safety in Europe (TRANSFoRm) project, which was funded by the European Commission and sought to develop, pilot, and evaluate a core information architecture for the learning health system in Europe, based on primary care electronic health records. RESULTS: We first describe the different stages in the processing of electronic health record data, as well as the different purposes for which these data are used. Given the different data processing steps and purposes, we then discuss the possible mechanisms for each individual data processing step that can generate biased outcomes. We identified 13 possible sources of bias. Four of them are related to the organization of a health care system, whereas some are of a more technical nature. CONCLUSIONS: There are a substantial number of possible sources of bias; very little is known about the size and direction of their impact. However, anyone that uses or reuses data that were recorded as part of the health care process (such as researchers and clinicians) should be aware of the associated data collection process and environmental influences that can affect the quality of the data. Our stepwise, actor- and purpose-oriented approach may help to identify these possible sources of bias. Unless data quality issues are better understood and unless adequate controls are embedded throughout the data lifecycle, data-driven health care will not live up to its expectations. We need a data quality research agenda to devise the appropriate instruments needed to assess the magnitude of each of the possible sources of bias, and then start measuring their impact. The possible sources of bias described in this paper serve as a starting point for this research agenda.

Determinants of first-time utilization of long-term care services in the Netherlands: an observational record linkage study.

BACKGROUND: Since in an ageing society more long-term care (LTC) facilities are needed, it is important to understand the main determinants of first-time utilization of (LTC) services. METHODS: The Andersen service model, which distinguishes predisposing, enabling and need factors, was used to develop a model for first-time utilization of LTC services among the general population of the Netherlands. We used data on 214,821 persons registered in a database of general practitioners (NIVEL Primary Care Database). For each person the medical history was known, as well as characteristics such as ethnicity, income, home-ownership, and marital status. Utilization data from the national register on long-term care was linked at a personal level. Generalized Linear Models were used to determine the relative importance of factors of incident LTC-service utilization. RESULTS: Top 5 determinants of LTC are need, measured as the presence of chronic diseases, age, household size, household income and homeownership. When controlling for all other determinants, the presence of an additional chronic disease increases the probability of utilizing any LTC service by 45% among the 20+ population (OR = 1.45, 95% CI: 1.41-1.49), and 31% among the 65+ population (OR = 1.31, 95% CI: 1.27-1.36). With respect to the 20+ population, living in social rent (OR = 2.45, 95% CI = 2.25-2.67, ref. = home-owner) had a large impact on utilizing any LTC service. In a lesser degree this was the case for living alone (OR = 1.63, 95% CI = 1.52-1.75, ref. = not living alone). A higher household income was linked with a lower utilization of any LTC service. CONCLUSIONS: All three factors of the Anderson model, predisposing, enabling, and need determinants influence the likelihood of future LTC service utilization. This implies that none of these factors can be left out of the analysis of what determines this use. New in our analysis is the focus on incident utilization. This provides a better estimate of the effects of predictors than a prevalence based analysis, as there is less confounding by changes in determinants occurring after LTC initiation. Especially the need of care is a strong factor. A policy implication of this relative importance of health status is therefore that LTC reforms should take health aspects into account.

Adverse events recording in electronic health record systems in primary care.

BACKGROUND: Adequate record keeping of medication adverse events in electronic health records systems is important for patient safety. Events that remain unrecorded cannot be communicated from one health professional to another. In the absence of a gold standard, we investigate the variation between Dutch general practices in the extent to which they record medication adverse events. METHODS: Data were derived from electronic health records (EHR) of Dutch general practices participating in NIVEL Primary Care Database (NIVEL-PCD) in 2014, including 308 general practices with a total practice population of 1,256,049 listed patients. Medication adverse events were defined as recorded ICPC-code A85 (adverse effect medical agent). Between practice variation was studied using multilevel logistic regression analysis corrected for age, gender, number of different medicines prescriptions and number of chronic diseases. RESULTS: In 2014 there were 8330 patients with at least one medication adverse event recorded. This corresponds to 6.9 medication adverse events per 1000 patients and is higher for women, elderly, patients with polypharmacy and for patients with comorbidity. Corrected for these patient characteristics the median odds ratio (MOR = 1.92) suggests an almost twofold difference between general practices in recorded medication adverse events. CONCLUSION: Our results suggest that improvement in terms of uniformity in recording medication adverse events is possible, preventing potential damage for patients. We suggest that creating a learning health system by individual practice feedback on the number of recordings of adverse events would help practitioners to improve their recording habits.

Compliance with referrals to medical specialist care: patient and general practice determinants: a cross-sectional study.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.

The association between adolescents' health and disparities in school career: a longitudinal cohort study.

BACKGROUND: Literature suggests that children's educational achievement is associated with their health status and the socioeconomic position of their parents. Few studies have investigated this association in adolescence, while this is an important period affecting future life trajectories. Our study investigates the relationship between adolescents' health and their subsequent school career, taking into account their parents' socioeconomic position. METHODS: Data of all Dutch adolescents who entered secondary education in 2003, according to the national education register, were linked to electronic health records from general practices and to data from the Dutch population register on a patient by patient basis. Secondary school career data of 2455 adolescents were available for several years, resulting in a longitudinal prospective cohort. School career was measured by the completion of secondary education within the research period. RESULTS: For most health problems, adolescents' health status at the moment of entering secondary education showed no association with the subsequent course of their school career. However, adolescents who had more frequent contact with their general practitioner for acute psychosocial problems (e.g. enuresis or overactive/hyperkinetic disorder), were less likely to complete their secondary education, also after adjustment for parental socioeconomic position. They were also less likely to complete their secondary education at the level of entry. CONCLUSIONS: Adolescents' secondary school career is negatively affected by the presence of acute psychosocial health problems, but not by the presence of physical health problems. This underlines the importance of adequately addressing mental health problems in adolescence.

Healthcare utilization in general practice before and after psychological treatment: a follow-up data linkage study in primary care.

OBJECTIVE: Literature suggests that serious mental health problems increase the use of health services and psychological interventions can reduce this effect. This study investigates whether this effect is also found in primary care patients with less serious mental health problems. DESIGN/SETTING: Routine electronic health records (EHR) from a representative sample of 128 general practices were linked to patient files from 150 primary care psychologists participating in the NIVEL Primary Care Database, using a trusted third party. Data were linked using the date of birth, gender, and postcode. This yielded 503 unique data pairs that were listed in one of the participating GP practices in 2008-2010, for people who had psychological treatment from a psychologist that ended in 2009. MAIN OUTCOME MEASURES: The number of contacts, health problems presented, and prescribed medication in general practice were analysed before and after the psychological treatment. RESULTS: Nearly all 503 patients consulted their GP during the six months preceding the psychological treatment (90.9%) and also in the six months after this treatment had ended (83.7%). The frequency of contacts was significantly higher before than after the psychological treatment (6.1 vs. 4.8). Fewer patients contacted their GPs specifically for psychological or social problems (46.3% vs. 38.8%) and fewer patients had anxiolytic drug prescriptions (15.5% vs. 7.6%) after psychological treatment. CONCLUSION: After psychological treatment, patients contact their GPs less often and present fewer psychological or social problems. Although contact rates seem to decrease, clients of psychologists are still frequent GP attenders.

Lessons learned from the development of a national registry on dementia care and support based on linked national health and administrative data.

Introduction: This paper provides insight into the development of the Dutch Dementia Care and Support Registry and the lessons that can be learned from it. The aim of this Registry was to contribute to quality improvement in dementia care and support. Methods: This paper describes how the Registry was set up in four stages, reflecting the four FAIR principles: the selection of data sources (Findability); obtaining access to the selected data sources (Accessibility); data linkage (Interoperability); and the reuse of data (Reusability). Results: The linkage of 16 different data sources, including national routine health and administrative data appeared to be technically and legally feasible. The linked data in the Registry offers rich information about (the use of) care for persons with dementia across various healthcare settings, including but not limited to primary care, secondary care, long-term care and medication use, that cannot be obtained from single data sources. Conclusions: A key lesson learned is that in order to reuse the data for quality improvement in practice, it is essential to involve healthcare professionals in setting up the Registry and to guide them in the interpretation of the data.