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Background General practitioners (GPs) can be considered the designated professionals to identify high fall risk and to guide older people to fall preventive care. Currently it is not exactly known how GPs treat this risk. This study aims to investigate GPs’ daily practice regarding fall preventive care for frail older patients. Methods Sixty-five GPs from 32 Dutch practices participated in this study for a period of 12 months. When a GP entered specific International Classification of Primary Care-codes related to frailty and/or high fall risk in their Electronic Health Records, a pop-up appeared asking “Is this patient frail?”. If the GP confirmed this, the GP completed a short questionnaire about patient’s fall history and fear of falling (FOF), and the fall preventive care provided. Results The GPs completed questionnaires regarding 1394 frail older patients aged ≥75. Of 20% of these patients, the GPs did not know whether they had experienced a fall or not. The GPs did not know whether a FOF existed in even more patients (29%). Of the patients with a fall history and/or a FOF (N = 726), 37% (N = 271) received fall preventive care. Two main reasons for not offering fall preventive care to these patients were: I) the patient finds treatment too intensive or too much of a hassle (37%), and II) the GP identified a high fall risk but the patient did not acknowledge this (14%). When patients were treated for high fall risk, the GP and the physiotherapist were the most frequently involved health care providers. The involved health care providers most often treated mobility limitations, cardiovascular risk factors, and FOF. Conclusions The results from this study show that GPs were frequently not aware of their frail patient’s fall history and/or FOF and that the majority of the frail older patients with a fall history and/or FOF did not receive fall preventive care. Developing systematic screening strategies for the primary care setting enhancing the identification of high fall risk and the provision of fall preventive care may improve patients’ quality of life and reduce health care costs.

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. Electronic supplementary material The online version of this article (10.1186/s12875-018-0863-x) contains supplementary material, which is available to authorized users.

Background There is a growing emphasis on self-monitoring applications that allow patients to measure their own physical health parameters. A prerequisite for achieving positive effects is patients’ willingness to self-monitor. The controllability of disease types, patients’ perceived self-efficacy and health problems could play an essential role in this. The purpose of this study is to investigate the relationship between patients’ willingness to self-monitor and a range of disease and patient specific variables including controllability of disease type, patients’ perceived self-efficacy and health problems. Methods Data regarding 627 participants with 17 chronic somatic disease types from a Dutch panel of people with chronic diseases have been used for this cross-sectional study. Perceived self-efficacy was assessed using the general self-efficacy scale, perceived health problems using the Physical Health Composite Score (PCS). Participants indicated their willingness to self-monitor. An expert panel assessed for 17 chronic disease types the extent to which patients can independently keep their disease in control. Logistic regression analyses were conducted. Results Patients’ willingness to self-monitor differs greatly among disease types: patients with diabetes (71.0%), asthma (59.6%) and hypertension (59.1%) were most willing to self-monitor. In contrast, patients with rheumatism (40.0%), migraine (41.2%) and other neurological disorders (42.9%) were less willing to self-monitor. It seems that there might be a relationship between disease controllability scores and patients’ willingness to self-monitor. No evidence is found of a relationship between general self-efficacy and PCS scores, and patients’ willingness to self-monitor. Conclusions This study provides the first evidence that patients’ willingness to self-monitor might be associated with disease controllability. Further research should investigate this association more deeply and should focus on how disease controllability influences willingness to self-monitor. In addition, since willingness to self-monitor differed greatly among patient groups, it should be taken into account that not all patient groups are willing to self-monitor. Electronic supplementary material The online version of this article (doi:10.1186/s12875-017-0615-3) contains supplementary material, which is available to authorized users.

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.