Dataset Information

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

ABSTRACT:

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.

SUBMITTER: Verberne LDM

PROVIDER: S-EPMC6240309 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Verberne Lisa D M LDM Nielen Markus M J MMJ Leemrijse Chantal J CJ Verheij Robert A RA Friele Roland D RD

BMC family practice 20181117 1

<h4>Background</h4>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 ...[more]

PMID: 30447691

Similar Datasets

Project description:BackgroundHypertension is the most common condition seen in Australian general practice. Despite hypertension being amenable to lifestyle modifications and pharmacological treatment, only around half of these patients have controlled blood pressure levels (< 140/90 mmHg), placing them at an increased risk of cardiovascular disease.ObjectiveWe aimed to estimate the health and acute hospitalisation costs of uncontrolled hypertension among patients attending general practice.MethodsWe used population data and electronic health records from 634,000 patients aged 45-74 years who regularly attended an Australian general practice between 2016 and 2018 (MedicineInsight database). An existing worksheet-based costing model was adapted to calculate the potential cost savings for acute hospitalisation of primary cardiovascular disease events by reducing the risk of a cardiovascular event over the next 5 years through improved systolic blood pressure control. The model estimated the number of expected cardiovascular disease events and associated acute hospital costs under current levels of systolic blood pressure and compared this estimate with the expected number of cardiovascular disease events and costs under different levels of systolic blood pressure control.ResultsThe model estimated that across all Australians aged 45-74 years who visit their general practitioner (n = 8.67 million), 261,858 cardiovascular disease events can be expected over the next 5 years at current systolic blood pressure levels (mean 137.8 mmHg, standard deviation = 12.3 mmHg), with a cost of AUD$1813 million (in 2019-20). By reducing the systolic blood pressure of all patients with a systolic blood pressure greater than 139 mmHg to 139 mmHg, 25,845 cardiovascular disease events could be avoided with an associated reduction in acute hospital costs of AUD$179 million. If systolic blood pressure is lowered further to 129 mmHg for all those with systolic blood pressure greater than 129 mmHg, 56,169 cardiovascular disease events could be avoided with potential cost savings of AUD$389 million. Sensitivity analyses indicate that potential cost savings range from AUD$46 million to AUD$1406 million and AUD$117 million to AUD$2009 million for the two scenarios, respectively. Cost savings by practice range from AUD$16,479 for small practices to AUD$82,493 for large practices.ConclusionsThe aggregate cost effects of poor blood pressure control in primary care are high, but cost implications at the individual practice level are modest. The potential cost savings improve the potential to design cost-effective interventions, but such interventions may be best targeted at a population level rather than at individual practices.

Project description:ImportanceShort-term studies suggest antidepressants are associated with modest weight gain but little is known about longer-term effects and differences between individual medications in general clinical populations.ObjectiveTo estimate weight gain associated with specific antidepressants over the 12 months following initial prescription in a large and diverse clinical population.Design, setting, and participantsWe identified 22,610 adult patients who began receiving a medication of interest with available weight data in a large New England health care system, including 2 academic medical centers and affiliated outpatient primary and specialty care clinics. We used electronic health records to extract prescribing data and recorded weights for any patient with an index antidepressant prescription including amitriptyline hydrochloride, bupropion hydrochloride, citalopram hydrobromide, duloxetine hydrochloride, escitalopram oxalate, fluoxetine hydrochloride, mirtazapine, nortriptyline hydrochloride, paroxetine hydrochloride, venlafaxine hydrochloride, and sertraline hydrochloride. As measures of assay sensitivity, additional index prescriptions examined included the antiasthma medication albuterol sulfate and the antiobesity medications orlistat, phentermine hydrochloride, and sibutramine hydrochloride. Mixed-effects models were used to estimate rate of weight change over 12 months in comparison with the reference antidepressant, citalopram.Main outcome and measureClinician-recorded weight at 3-month intervals up to 12 months.ResultsCompared with citalopram, in models adjusted for sociodemographic and clinical features, significantly decreased rate of weight gain was observed among individuals treated with bupropion (β [SE]: -0.063 [0.027]; P = .02), amitriptyline (β [SE]: -0.081 [0.025]; P = .001), and nortriptyline (β [SE]: -0.147 [0.034]; P < .001). As anticipated, differences were less pronounced among individuals discontinuing treatment prior to 12 months.Conclusions and relevanceAntidepressants differ modestly in their propensity to contribute to weight gain. Short-term investigations may be insufficient to characterize and differentiate this risk.

Dataset Information

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

Background

Methods

Results

Conclusions

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets