scholarly journals Outpatient Electronic Health Records and the Clinical Care and Outcomes of Patients With Diabetes Mellitus

2012 ◽  
Vol 157 (7) ◽  
pp. 482 ◽  
Author(s):  
Mary Reed ◽  
Jie Huang ◽  
Ilana Graetz ◽  
Richard Brand ◽  
John Hsu ◽  
...  
BMC Medicine ◽  
2019 ◽  
Vol 17 (1) ◽  
Author(s):  
B. D. Nicholson ◽  
P. Aveyard ◽  
C. R. Bankhead ◽  
W. Hamilton ◽  
F. D. R. Hobbs ◽  
...  

Abstract Background Excess weight and unexpected weight loss are associated with multiple disease states and increased morbidity and mortality, but weight measurement is not routine in many primary care settings. The aim of this study was to characterise who has had their weight recorded in UK primary care, how frequently, by whom and in relation to which clinical events, symptoms and diagnoses. Methods A longitudinal analysis of UK primary care electronic health records (EHR) data from 2000 to 2017. Descriptive statistics were used to summarise weight recording in terms of patient sociodemographic characteristics, health professional encounters, clinical events, symptoms and diagnoses. Negative binomial regression was used to model the likelihood of having a weight record each year, and Cox regression to the likelihood of repeated weight recording. Results A total of 14,049,871 weight records were identified in the EHR of 4,918,746 patients during the study period, representing 26,998,591 person-years of observation. Around a third of patients had a weight record each year. Forty-nine percent of weight records were repeated within a year with an average time to a repeat weight record of 1.92 years. Weight records were most often taken by nursing staff (38–42%) and GPs (37–39%) as part of a routine clinical care, such as chronic disease reviews (16%), medication reviews (6–8%) and health checks (6–7%), or were associated with consultations for contraception (5–8%), respiratory disease (5%) and obesity (1%). Patient characteristics independently associated with an increased likelihood of weight recording were as follows: female sex, younger and older adults, non-drinkers, ex-smokers, low or high BMI, being more deprived, diagnosed with a greater number of comorbidities and consulting more frequently. The effect of policy-level incentives to record weight did not appear to be sustained after they were removed. Conclusion Weight recording is not a routine activity in UK primary care. It is recorded for around a third of patients each year and is repeated on average every 2 years for these patients. It is more common in females with higher BMI and in those with comorbidity. Incentive payments and their removal appear to be associated with increases and decreases in weight recording.


2017 ◽  
Vol 152 ◽  
pp. 53-70 ◽  
Author(s):  
Santiago Esteban ◽  
Manuel Rodríguez Tablado ◽  
Francisco E. Peper ◽  
Yamila S. Mahumud ◽  
Ricardo I. Ricci ◽  
...  

2019 ◽  
Vol 40 (1) ◽  
pp. 487-500 ◽  
Author(s):  
Hilal Atasoy ◽  
Brad N. Greenwood ◽  
Jeffrey Scott McCullough

Electronic health records (EHRs) adoption has become nearly universal during the past decade. Academic research into the effects of EHRs has examined factors influencing adoption, clinical care benefits, financial and cost implications, and more. We provide an interdisciplinary overview and synthesis of this literature, drawing on work in public and population health, informatics, medicine, management information systems, and economics. We then chart paths forward for policy, practice, and research.


2011 ◽  
Vol 142 (10) ◽  
pp. 1133-1142 ◽  
Author(s):  
James Fricton ◽  
D. Brad Rindal ◽  
William Rush ◽  
Thomas Flottemesch ◽  
Gabriela Vazquez ◽  
...  

BMJ Open ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. e040201 ◽  
Author(s):  
Rathi Ravindrarajah ◽  
David Reeves ◽  
Elizabeth Howarth ◽  
Rachel Meacock ◽  
Claudia Soiland-Reyes ◽  
...  

ObjectivesTo study the characteristics of UK individuals identified with non-diabetic hyperglycaemia (NDH) and their conversion rates to type 2 diabetes mellitus (T2DM) from 2000 to 2015, using the Clinical Practice Research Datalink.DesignCohort study.SettingsUK primary Care Practices.ParticipantsElectronic health records identified 14 272 participants with NDH, from 2000 to 2015.Primary and secondary outcome measuresBaseline characteristics and conversion trends from NDH to T2DM were explored. Cox proportional hazards models evaluated predictors of conversion.ResultsCrude conversion was 4% within 6 months of NDH diagnosis, 7% annually, 13% within 2 years, 17% within 3 years and 23% within 5 years. However, 1-year conversion fell from 8% in 2000 to 4% in 2014. Individuals aged 45–54 were at the highest risk of developing T2DM (HR 1.20, 95% CI 1.15 to 1.25— compared with those aged 18–44), and the risk reduced with older age. A body mass index (BMI) above 30 kg/m2 was strongly associated with conversion (HR 2.02, 95% CI 1.92 to 2.13—compared with those with a normal BMI). Depression (HR 1.10, 95% CI 1.07 to 1.13), smoking (HR 1.07, 95% CI 1.03 to 1.11—compared with non-smokers) or residing in the most deprived areas (HR 1.17, 95% CI 1.11 to 1.24—compared with residents of the most affluent areas) was modestly associated with conversion.ConclusionAlthough the rate of conversion from NDH to T2DM fell between 2010 and 2015, this is likely due to changes over time in the cut-off points for defining NDH, and more people of lower diabetes risk being diagnosed with NDH over time. People aged 45–54, smokers, depressed, with high BMI and more deprived are at increased risk of conversion to T2DM.


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