Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.
ADVANCED SEARCH
Log in
Top
BMC Primary Care
Published in: BMC Primary Care 1/2018

Open Access 01-12-2018 | Research article

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

Authors: Lisa D. M. Verberne, Markus M. J. Nielen, Chantal J. Leemrijse, Robert A. Verheij, Roland D. Friele

Published in: BMC Primary Care | Issue 1/2018

Login to get access

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.
Appendix
Available only for authorised users
Literature
1.
Booth HP, Prevost AT, Gulliford MC. Impact of body mass index on prevalence of multimorbidity in primary care: cohort study. Fam Pract. 2014;31(1):38–43.CrossRef
2.
van Dijk L, Otters HB, Schuit AJ. Moderately overweight and obese patients in general practice: a population based survey. BMC Fam Pract. 2006;7:43.CrossRef
3.
4.
van der Bij S, Khan N, Ten Veen P, de Bakker DH, Verheij RA. Improving the quality of EHR recording in primary care: a data quality feedback tool. J Am Med Inform Assoc. 2017;24(1):81–7.CrossRef
5.
Baer HJ, Karson AS, Soukup JR, Williams DH, Bates DW. Documentation and diagnosis of overweight and obesity in electronic health records of adult primary care patients. JAMA Intern Med. 2013;173(17):1648–52.CrossRef
6.
Bhaskaran K, Forbes HJ, Douglas I, Leon DA, Smeeth L. Representativeness and optimal use of body mass index (BMI) in the UK clinical practice research datalink (CPRD). BMJ Open. 2013;3(9):e003389.CrossRef
7.
Booth HP, Prevost AT, Gulliford MC. Epidemiology of clinical body mass index recording in an obese population in primary care: a cohort study. J Public Health (Oxf). 2013;35(1):67–74.CrossRef
8.
Dalton AR, Bottle A, Okoro C, Majeed A, Millett C. Implementation of the NHS health checks programme: baseline assessment of risk factor recording in an urban culturally diverse setting. Fam Pract. 2011;28(1):34–40.CrossRef
9.
Rose SA, Turchin A, Grant RW, Meigs JB. Documentation of body mass index and control of associated risk factors in a large primary care network. BMC Health Serv Res. 2009;9:236.CrossRef
10.
Turner LR, Harris MF, Mazza D. Obesity management in general practice: does current practice match guideline recommendations? Med J Aust. 2015;202(7):370–2.CrossRef
11.
Gillam SJ, Siriwardena AN, Steel N. Pay-for-performance in the United Kingdom: impact of the quality and outcomes framework: a systematic review. Ann Fam Med. 2012;10(5):461–8.CrossRef
12.
de Bakker DH, Struijs JN, Baan CB, Raams J, de Wildt JE, Vrijhoef HJ, et al. Early results from adoption of bundled payment for diabetes care in the Netherlands show improvement in care coordination. Health Aff (Millwood). 2012;31(2):426–33.CrossRef
13.
Verberne LDM, Leemrijse CJ, Swinkels ICS, van Dijk CE, de Bakker DH, Nielen MMJ. Overweight in patients with chronic obstructive pulmonary disease needs more attention: a cross-sectional study in general practice. NPJ Prim Care Respir Med. 2017;27(1):63.CrossRef
14.
15.
Slottje P, Yzermans CJ, Korevaar JC, Hooiveld M, Vermeulen RC. The population-based occupational and environmental health prospective cohort study (AMIGO) in the Netherlands. BMJ Open. 2014;4(11):e005858.CrossRef
16.
Yoong SL, Carey ML, Sanson-Fisher RW, D'Este CA, Mackenzie L, Boyes A. A cross-sectional study examining Australian general practitioners’ identification of overweight and obese patients. J Gen Intern Med. 2014;29(2):328–34.CrossRef
17.
McLaughlin JC, Hamilton K, Kipping R. Epidemiology of adult overweight recording and management by UK GPs: a systematic review. Br J Gen Pract. 2017;67(663):e676–83.CrossRef
18.
Kloek CJ, Tol J, Veenhof C, van der Wulp I, Swinkels IC. Dutch general Practitioners' weight management policy for overweight and obese patients. BMC Obes. 2014;1:2.CrossRef
19.
20.
Badenbroek IF, Stol DM, Nielen MM, Hollander M, Kraaijenhagen RA, de Wit GA, et al. Design of the INTEGRATE study: effectiveness and cost-effectiveness of a cardiometabolic risk assessment and treatment program integrated in primary care. BMC Fam Pract. 2014;15(1):90.CrossRef
21.
Verberne LD, Hendriks MR, Rutten GM, Spronk I, Savelberg HH, Veenhof C, et al. Evaluation of a combined lifestyle intervention for overweight and obese patients in primary health care: a quasi-experimental design. Fam Pract. 2016;33(6):671–7.CrossRef
22.
Waring ME, Roberts MB, Parker DR, Eaton CB. Documentation and management of overweight and obesity in primary care. J Am Board Fam Med. 2009;22(5):544–52.CrossRef
23.
Post RE, Mainous AG, Gregorie SH, Knoll ME, Diaz VA, Saxena SK. The influence of physician acknowledgment of patients' weight status on patient perceptions of overweight and obesity in the United States. Arch Intern Med. 2011;171(4):316–21.CrossRef
24.
Henderson E. Obesity in primary care: a qualitative synthesis of patient and practitioner perspectives on roles and responsibilities. Br J Gen Pract. 2015;65(633):e240–7.CrossRef
25.
van Dillen SM, Noordman J, van Dulmen S, Hiddink GJ. Examining the content of weight, nutrition and physical activity advices provided by Dutch practice nurses in primary care: analysis of videotaped consultations. Eur J Clin Nutr. 2014;68(1):50–6.CrossRef
Metadata
Title
Recording of weight in electronic health records: an observational study in general practice
Authors
Lisa D. M. Verberne
Markus M. J. Nielen
Chantal J. Leemrijse
Robert A. Verheij
Roland D. Friele
Publication date
01-12-2018
Publisher
BioMed Central
Published in
BMC Primary Care / Issue 1/2018
Electronic ISSN: 2731-4553
DOI
https://doi.org/10.1186/s12875-018-0863-x

Other articles of this Issue 1/2018

BMC Primary Care 1/2018 Go to the issue

Research article

Difficult medical encounters and job satisfaction - results of a cross sectional study with general practitioners in Germany

Research article

Development of the Japanese version of the general practice assessment questionnaire: measurement of patient experience and testing of data quality

Research article

Clinical effectiveness of care managers in collaborative care for patients with depression in Swedish primary health care: a pragmatic cluster randomized controlled trial

Research article

Effect of administrative information on visit rate of frequent attenders in primary health care: ten-year follow-up study

Research article

Factors contributing to the recognition of anxiety and depression in general practice

Research article

Patient capacity for self-care in the medical record of patients with chronic conditions: a mixed-methods retrospective study