183 research outputs found

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

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    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

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

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    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. (aut. ref.

    Cardiovascular disease prevalence in patients with inflammatory arthritis, diabetes mellitus and osteoarthritis: a cross-sectional study in primary care

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    <p>Abstract</p> <p>Background</p> <p>There is accumulating evidence for an increased cardiovascular burden in inflammatory arthritis, but the true magnitude of this cardiovascular burden is still debated. We sought to determine the prevalence rate of non-fatal cardiovascular disease (CVD) in inflammatory arthritis, diabetes mellitus and osteoarthritis (non-systemic inflammatory comparator) compared to controls, in primary care.</p> <p>Methods</p> <p>Data on CVD morbidity (ICPC codes K75 (myocardial infarction), K89 (transient ischemic attack), and/or K90 (stroke/cerebrovascular accident)) from patients with inflammatory arthritis (n = 1,518), diabetes mellitus (n = 11,959), osteoarthritis (n = 4,040) and controls (n = 158,439) were used from the Netherlands Information Network of General Practice (LINH), a large nationally representative primary care based cohort. Data were analyzed using multi-level logistic regression analyses and corrected for age, gender, hypercholesterolemia and hypertension.</p> <p>Results</p> <p>CVD prevalence rates were significantly higher in inflammatory arthritis, diabetes mellitus and osteoarthritis compared with controls. These results attenuated - especially in diabetes mellitus - but remained statistically significant after adjustment for age, gender, hypertension and hypercholesterolemia for inflammatory arthritis (OR = 1.5 (1.2-1.9)) and diabetes mellitus (OR = 1.3 (1.2-1.4)). The association between osteoarthritis and CVD reversed after adjustment (OR = 0.8 (0.7-1.0)).</p> <p>Conclusions</p> <p>These results confirm an increased prevalence rate of CVD in inflammatory arthritis to levels resembling diabetes mellitus. By contrast, lack of excess CVD in osteoarthritis further suggests that the systemic inflammatory load is critical to the CVD burden in inflammatory arthritis.</p

    Understanding the use of email consultation in primary care using a retrospective observational study with data of Dutch electronic health records

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    OBJECTIVES: It is unclear why the use of email consultation is not more widespread in Dutch general practice, particularly because, since 2006, its costs can be reimbursed. To encourage further implementation, it is needed to understand the current use of email consultations. This study aims to understand the use of email consultation by different patient groups, compared with other general practice (GP) consultations. SETTING: For this retrospective observational study, we used Dutch routine electronic health record data obtained from NIVEL Primary Care Database for the years 2010 and 2014. PARTICIPANTS: 200 general practices were included in 2010 (734 122 registered patients) and 434 in 2014 (1 630 386 registered patients). PRIMARY OUTCOME MEASURES: The number and percentage of email consultations and patient characteristics (age, gender, neighbourhood socioeconomic status and diagnoses) of email consultation users were investigated and compared with those who had a telephone or face-to-face consultation. General practice characteristics were also taken into account. RESULTS: 32.0% of the Dutch general practices had at least one email consultation in 2010, rising to 52.8% in 2014. In 2014, only 0.7% of the GP consultations were by email (the others comprised home visits, telephone and face-to-face consultations). Its use highly varied among general practices. Most email consultations were done for psychological (14.7%); endocrine, metabolic and nutritional (10.9%); and circulatory (10.7%) problems. These diagnosis categories appeared less frequently in telephone and face-to-face consultations. Patients who had an email consultation were older than patients who had a telephone or face-to-face consultation. In contrast, patients with diabetes who had an email consultation were younger. CONCLUSION: Even though email consultation was done in half the general practices in the Netherlands in 2014, the actual use of it is extremely low. Patients who had an email consultation differ from those who had a telephone or face-to-face consultation. In addition, the use of email consultation by patients is dependent on its provision by GPs

    Педагогическая эвристика в структуре личностно ориентированного образования

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    Цель статьи: провести анализ различных трактовок педагогической эвристики, определить ее задачи, основные структурные элементы и уровни в системе личностно ориентированного образования.This article is devoted to the pedagogical heurist in the personal oriented education that is the analyses of different approaches to the interpretation of pedagogical heurist is done, the tasks, methods and the main structural elements are determined. The peculiarities of theoretical, methodological, individual-practical levels of pedagogical heurist are examined. The functions of personality are determined on every level, principles of government with heuristic activity are revealed. Important conclusions are done

    Natural language processing systems for extracting information from electronic health records about activities of daily living. A systematic review

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    ObjectiveNatural language processing (NLP) can enhance research on activities of daily living (ADL) by extracting structured information from unstructured electronic health records (EHRs) notes. This review aims to give insight into the state-of-the-art, usability, and performance of NLP systems to extract information on ADL from EHRs.Materials and MethodsA systematic review was conducted based on searches in Pubmed, Embase, Cinahl, Web of Science, and Scopus. Studies published between 2017 and 2022 were selected based on predefined eligibility criteria.ResultsThe review identified 22 studies. Most studies (65%) used NLP for classifying unstructured EHR data on 1 or 2 ADL. Deep learning, combined with a ruled-based method or machine learning, was the approach most commonly used. NLP systems varied widely in terms of the pre-processing and algorithms. Common performance evaluation methods were cross-validation and train/test datasets, with F1, precision, and sensitivity as the most frequently reported evaluation metrics. Most studies reported relativity high overall scores on the evaluation metrics.DiscussionNLP systems are valuable for the extraction of unstructured EHR data on ADL. However, comparing the performance of NLP systems is difficult due to the diversity of the studies and challenges related to the dataset, including restricted access to EHR data, inadequate documentation, lack of granularity, and small datasets.ConclusionThis systematic review indicates that NLP is promising for deriving information on ADL from unstructured EHR notes. However, what the best-performing NLP system is, depends on characteristics of the dataset, research question, and type of ADL

    Predicting sepsis-related mortality and ICU admissions from telephone triage information of patients presenting to out-of-hours GP cooperatives with acute infections:A cohort study of linked routine care databases

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    BackgroundGeneral practitioners (GPs) often assess patients with acute infections. It is challenging for GPs to recognize patients needing immediate hospital referral for sepsis while avoiding unnecessary referrals. This study aimed to predict adverse sepsis-related outcomes from telephone triage information of patients presenting to out-of-hours GP cooperatives.MethodsA retrospective cohort study using linked routine care databases from out-of-hours GP cooperatives, general practices, hospitals and mortality registration. We included adult patients with complaints possibly related to an acute infection, who were assessed (clinic consultation or home visit) by a GP from a GP cooperative between 2017–2019. We used telephone triage information to derive a risk prediction model for sepsis-related adverse outcome (infection-related ICU admission within seven days or infection-related death within 30 days) using logistic regression, random forest, and neural network machine learning techniques. Data from 2017 and 2018 were used for derivation and from 2019 for validation.ResultsWe included 155,486 patients (median age of 51 years; 59% females) in the analyses. The strongest predictors for sepsis-related adverse outcome were age, type of contact (home visit or clinic consultation), patients considered ABCD unstable during triage, and the entry complaints”general malaise”, “shortness of breath” and “fever”. The multivariable logistic regression model resulted in a C-statistic of 0.89 (95% CI 0.88–0.90) with good calibration. Machine learning models performed similarly to the logistic regression model. A “sepsis alert” based on a predicted probability &gt;1% resulted in a sensitivity of 82% and a positive predictive value of 4.5%. However, most events occurred in patients receiving home visits, and model performance was substantially worse in this subgroup (C-statistic 0.70).ConclusionSeveral patient characteristics identified during telephone triage of patients presenting to out-of-hours GP cooperatives were associated with sepsis-related adverse outcomes. Still, on a patient level, predictions were not sufficiently accurate for clinical purposes

    Healthcare utilization patterns for knee and hip osteoarthritis before and after changes in national health insurance coverage:A data linkage study from the Netherlands

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    Introduction: Medical guidelines aim to stimulate stepped care for knee and hip osteoarthritis, redirecting treatments from hospitals to primary care. In the Netherlands, this development was supported by changing health insurance coverage for physio/exercise therapy. The aim of this study was to evaluate healthcare utilization patterns before and after health changes in health insurance coverage. Method: We analyzed electronic health records and claims data from patients with osteoarthritis in the knee (N =32,091) and hip (N = 16,313). Changes between 2013 and 2019 in the proportion of patients treated by the general practitioner, physio/exercise therapist or orthopedic surgeon within 6 months after onset were assessed. Results: Joint replacement surgeries decreased for knee (OR 0.47 [0.41–0.54]) and hip (OR 0.81 [0.71–0.93]) osteoarthritis between 2013–2019. The use of physio/exercise therapy increased (knee: OR 1.38 [1.24–1.53], hip: OR 1.26 [1.08–1.47]). However, the proportion treated by a physio/exercise therapist decreased for patients that had not depleted their annual deductibles (knee: OR 0.86 [0.79 – 0.94], hip: OR 0.90 [0.79 – 1.02]). This might be affected by the inclusion of physio/exercise therapy in basic health insurance in 2018. Conclusion:We have found a shift from hospitals to primary care in knee and hip osteoarthritis care. However, the use of physio/exercise therapy declined after changes in insurance coverage for patients that had not depleted their deductibles

    Связи изменений среднемесячных ОСО над Антарктикой и площади теплого тропического бассейна Тихого океана при современном потеплении климата

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    Объектом данного исследования выбраны изменения распределения среднемесячных значений ОСО над Антарктикой, а также площади ТТБ в западном полушарии. Предметом исследования есть изменения статистических связей между указанными процессами, происходившими за период современного потепления климата. Целью работы есть выявление их связей, которые на протяжении периода современного потепления климата усиливались устойчиво и ныне являются значимыми
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