Dataset Information

Undiagnosed diabetes from cross-sectional GP practice data: an approach to identify communities with high likelihood of undiagnosed diabetes.

ABSTRACT:

Objectives

To estimate undiagnosed diabetes prevalence from general practitioner (GP) practice data and identify areas with high levels of undiagnosed and diagnosed diabetes.

Design

Data from the North-West Adelaide Health Survey (NWAHS) were used to develop a model which predicts total diabetes at a small area. This model was then applied to cross-sectional data from general practices to predict the total level of expected diabetes. The difference between total expected and already diagnosed diabetes was defined as undiagnosed diabetes prevalence and was estimated for each small area. The patterns of diagnosed and undiagnosed diabetes were mapped to highlight the areas of high prevalence.

Setting

North-West Adelaide, Australia.

Participants

This study used two population samples-one from the de-identified GP practice data (n=9327 active patients, aged 18?years and over) and another from NWAHS (n=4056, aged 18?years and over).

Main outcome measures

Total diabetes prevalence, diagnosed and undiagnosed diabetes prevalence at GP practice and Statistical Area Level 1.

Results

Overall, it was estimated that there was one case of undiagnosed diabetes for every 3-4 diagnosed cases among the 9327 active patients analysed. The highest prevalence of diagnosed diabetes was seen in areas of lower socioeconomic status. However, the prevalence of undiagnosed diabetes was substantially higher in the least disadvantaged areas.

Conclusions

The method can be used to estimate population prevalence of diabetes from general practices wherever these data are available. This approach both flags the possibility that undiagnosed diabetes may be a problem of less disadvantaged social groups, and provides a tool to identify areas with high levels of unmet need for diabetes care which would enable policy makers to apply geographic targeting of effective interventions.

SUBMITTER: Bagheri N

PROVIDER: S-EPMC4120432 | biostudies-literature | 2014 Jul

REPOSITORIES: biostudies-literature

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Publications

Undiagnosed diabetes from cross-sectional GP practice data: an approach to identify communities with high likelihood of undiagnosed diabetes.

Bagheri Nasser N McRae Ian I Konings Paul P Butler Danielle D Douglas Kirsty K Del Fante Peter P Adams Robert R

BMJ open 20140723 7

<h4>Objectives</h4>To estimate undiagnosed diabetes prevalence from general practitioner (GP) practice data and identify areas with high levels of undiagnosed and diagnosed diabetes.<h4>Design</h4>Data from the North-West Adelaide Health Survey (NWAHS) were used to develop a model which predicts total diabetes at a small area. This model was then applied to cross-sectional data from general practices to predict the total level of expected diabetes. The difference between total expected and alrea ...[more]

PMID: 25056976

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Project description:Background:A common belief is that one quarter to one third of all diabetes cases remain undiagnosed. However, such prevalence estimates may be overstated by epidemiologic studies that do not use confirmatory testing, as recommended by clinical diagnostic criteria. Objective:To provide national estimates of undiagnosed diabetes by using a confirmatory testing strategy, in line with clinical practice guidelines. Design:Cross-sectional study. Setting:National Health and Nutrition Examination Survey results from 1988 to 1994 and 1999 to 2014. Participants:U.S. adults aged 20 years and older. Measurements:Confirmed undiagnosed diabetes was defined as elevated levels of fasting glucose (?7.0 mmol/L [?126 mg/dL]) and hemoglobin A1c (?6.5%) in persons without diagnosed diabetes. Results:The prevalence of total (diagnosed plus confirmed undiagnosed) diabetes increased from 5.5% (9.7 million adults) in 1988 to 1994 to 10.8% (25.5 million adults) in 2011 to 2014. Confirmed undiagnosed diabetes increased during the past 2 decades (from 0.89% in 1988 to 1994 to 1.2% in 2011 to 2014) but has decreased over time as a proportion of total diabetes cases. In 1988 to 1994, the percentage of total diabetes cases that were undiagnosed was 16.3%; by 2011 to 2014, this estimate had decreased to 10.9%. Undiagnosed diabetes was more common in overweight or obese adults, older adults, racial/ethnic minorities (including Asian Americans), and persons lacking health insurance or access to health care. Limitation:Cross-sectional design. Conclusion:Establishing the burden of undiagnosed diabetes is critical to monitoring public health efforts related to screening and diagnosis. When a confirmatory definition is used, undiagnosed diabetes is a relatively small fraction of the total diabetes population; most U.S. adults with diabetes (about 90%) have received a diagnosis of the condition. Primary Funding Source:National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases and National Heart, Lung, and Blood Institute.

Project description:BackgroundPrevious studies of inter-practice variation of the prevalence of hypertension and diabetes mellitus showed wide variations between practices. However, in these studies inter-practice variation was calculated without controlling for clustering of patients within practices and without adjusting for patient and practice characteristics. Therefore, in the present study inter-practice variation of diagnosed hypertension and diabetes mellitus prevalence rates was calculated by 1) using a multi-level design and 2) adjusting for patient and practice characteristics.MethodsData were used from the Netherlands Information Network of General Practice (LINH) in 2004. Of all 168.045 registered patients, the presence of hypertension, diabetes mellitus and all available ICPC coded symptoms and diseases related to hypertension and diabetes, were determined. Also, the characteristics of practices were used in the analyses. Multilevel logistic regression analyses were performed.ResultsThe 95% prevalence range for the practices for the prevalence of diagnosed hypertension and diabetes mellitus was 66.3 to 181.7 per 1000 patients and 22.2 to 65.8 per 1000 patients, respectively, after adjustment for patient and practice characteristics. The presence of hypertension and diabetes was best predicted by patient characteristics. The most important predictors of hypertension were obesity (OR = 3.5), presence of a lipid disorder (OR = 3.0), and diabetes mellitus (OR = 2.6), whereas the presence of diabetes mellitus was particularly predicted by retinopathy (OR = 8.5), lipid disorders (OR = 2.8) and hypertension (OR = 2.7).ConclusionAlthough not the optimal case-mix could be used in this study, we conclude that even after adjustment for patient (demographic variables and risk factors for hypertension and diabetes mellitus) and practice characteristics (practice size and presence of a practice nurse), there is a wide difference between general practices in the prevalence rates of diagnosed hypertension and diabetes mellitus.

Project description:BACKGROUND: Electronic diabetes registers promote structured care and enable identification of undiagnosed diabetes, but they require consistent coding of the diagnosis in electronic medical records. We investigated the potential of electronic medical records to identify undiagnosed diabetes and to support diabetes management in a large primary care population in the United States. METHODS: We conducted a cross-sectional study and retrospective observational cohort analysis of primary care electronic medical records from a nationally representative US database (GE Centricity). We tested the feasibility of identifying patients with undiagnosed diabetes by applying simple algorithms to the electronic medical record data. We compared the quality of care provided to patients in the United States who had diabetes (coded and uncoded) for at least 15 months with the quality of care provided in England using a set of 16 indicators. RESULTS: We included 11 540 454 electronic medical records from more than 9000 primary care clinics across the United States. Of the 1 110 398 records indicating diagnosed diabetes, only 61.9% contained a diagnostic code. Of the 10 430 056 records for nondiabetic patients, 0.4% (n = 40 359) had at least 2 abnormal fasting or random blood glucose values, and 0.2% (n = 23 261) of the remaining records had at least 1 documented glycated hemoglobin (HbA1c) value of 6.5% or higher. Among the 622 260 patients for whom information on quality-of-care indicators was available, those with a coded diagnosis of diabetes had a significantly higher level of quality of care than those with uncoded diabetes (p < 0.01); however, the quality of care was generally lower than that indicated in England. INTERPRETATION: We were able to identify a substantial number of patients with uncoded diabetes and probable undiagnosed diabetes using simple algorithms applied to the primary care electronic records. Electronic coding of the diagnosis was associated with improved quality of care. Electronic diabetes registers are underused in US primary care and provide opportunities to facilitate the systematic, structured approach that is established in England.

Project description:ObjectiveGlobally, 8.8% of adults were estimated to have diabetes mellitus, with the low-and middle-income countries sharing the largest burden. However, the research evidence for targeted interventions is lacking in sub-Saharan Africa, particularly in Ethiopia. Therefore, this study aimed to assess the prevalence of diabetes mellitus, disaggregated by the epidemiology of diabetes mellitus morbidity and associated factors among adults in Dire Dawa town, Eastern Ethiopia.MethodsData from a total of 872 randomly sampled adults aged 25-64 years were obtained for analysis using the World Health Organization STEPwise approach to non-communicable disease risk factors surveillance instruments. We estimated the prevalence of diabetes mellitus disaggregated by the previous diabetes mellitus diagnosis status and by the current blood sugar level control status. The bivariable and multivariable binary logistic regression model was used to identify correlates of diabetes mellitus, along with STATA version 14.2 for data management and analysis. All statistical tests were declared significant at p-value < 0.05.Results14.9% (95% confidence interval: 12.1, 17.4) of adults aged 25-64 years had diabetes mellitus in the study sample with 58.5% (95% confidence interval: 49.7, 66.7) on diabetes mellitus medication. Among adults currently taking diabetes mellitus medications, 30.3% (95% confidence interval: 19.8, 45.6) had uncontrolled diabetes mellitus. The magnitude of previously undiagnosed diabetes mellitus was 6.2% (95% confidence interval: 4.8, 8.0) in the study sample and 41.5% (95% confidence interval: 33.3, 50.3) among the diabetics. The odds of diabetes mellitus were higher among adults over the age of 55 years (adjusted odds ratio = 2.1, 95% confidence interval: 1.2, 3.6), currently married adults (adjusted odds ratio = 2.3, 95% confidence interval: 1.2, 4.4), and overweight adults (adjusted odds ratio = 1.6, 95% confidence interval: 1.1, 2.1). Adults with primary education (adjusted odds ratio = 0.4, 95% confidence interval: 0.2, 0.8) and no formal education (adjusted odds ratio = 0.5, 95% confidence interval: 0.2, 0.9) had lower odds of diabetes mellitus.ConclusionThe prevalence of diabetes mellitus among adults was high in Dire Dawa, with a third of the diabetics having poor control of their blood sugar levels and, nearly four in ten were previously undiagnosed. Adults who were overweight, currently married, and those over 55 years need to be targeted for regular diabetes health checkups and community-based screening. Also, a mechanism should be instituted to track a patient's adherence to medications and promote diabetes self-care management.

Project description:OBJECTIVE:To explore diabetes-related behaviours and their influencing factors among elderly individuals with pre-diabetes in rural areas of China. DESIGN, SETTING AND PARTICIPANTS:A cross-sectional survey was conducted among elderly individuals (?60 years) in rural communities in Yiyang City of China. Multistaged cluster random sampling was carried out to select 42 areas, and interviews were conducted among 434 elderly individuals with pre-diabetes (fasting plasma glucose 6.1-7.0?mmol/L and/or 2-hour post-glucose load of 7.8-11.1?mmol/L) using questionnaires on diabetes-related behaviours. The diabetes-related behaviours included eight categories: average daily sedentary time; frequency of physical activities per week; regular or irregular diet; whether paying attention to diet control or not; daily dietary preferences; frequency of physical examinations per year; current smoking status; and current consumption of alcohol. Each of the risky behaviours was scored -1 and each of the healthy behaviours was scored +1. Each individual's score of diabetes-related behaviours was the sum of the score for all behaviours. MAIN OUTCOME MEASURES:Participants were asked about general information (age, gender, marital status, history of hyperglycaemia, family history of diabetes mellitus, presence of other diseases, body mass index, waist-to-hip ratio and education) and their diabetes-related behaviours. Multivariate linear regression analysis was performed to identify the risk factors for diabetes-related behaviour among elderly individuals with pre-diabetes. RESULTS:The average score of diabetes-related behaviours of elderly individuals with pre-diabetes in rural China was 2.7. The prevalences of risky diabetes-related behaviours were as follows: <1 physical examination per year (57.6%), insufficient physical activities (55.3%), lack of attention paid to diet control (51.4%), high-salt and high-fat diets (41.0%), sedentary lifestyle (35.9%), smoking (22.8%), regular alcohol uptake (15.0%) and irregular diet (3.9%). Gender and a history of hyperglycaemia were found to be influencing factors of the diabetes-related behaviour score. CONCLUSIONS:The prevalence of risky diabetes-related behaviours was high among pre-diabetic elderly individuals in rural China. More effort should be made to promote the prevention and control of diabetes in rural China. Future studies should be undertaken on diabetes prevention strategies tailored specially for this population. TRIAL REGISTRATION NUMBER:ChiCTR-IOR-15007033; Results.

Project description:BACKGROUND:Due to the perennial shortage of diabetes specialists, primary care physicians (PCPs) constitute the largest diabetes care manpower in Nigeria. However, the competence of the PCPs to undertake this task is not known. This study was aimed at evaluating diabetes care knowledge and practice among PCPs in Southeastern part of Nigeria. METHODS:This was a cross-sectional study among PCPs in Southeastern Nigeria. Diabetes care knowledge and practices were evaluated using a structured self administered questionnaire. RESULTS:A total of 64 PCPs with mean duration of practice of 17.3 ± 11.6 years completed the study. 65.6% were in private practice and 50% attended to between 11 and 20 persons living with diabetes (PLWD) weekly. Majority (78.1%) had not participated in any diabetes training since graduation from medical school and 79.9% were not aware of any diabetes clinical practice guideline. The PCPs had adequate knowledge of classical symptoms of diabetes. However, they had very poor knowledge of glycemic thresholds for diagnosis of diabetes which was 26.6, 45.3 and 10.9% for fasting blood glucose (FBG), random blood glucose (RBG) and glycated hemoglobin (A1c) respectively. We observed serious gaps in diabetes care practice such that only 18.8% of the respondents performed foot examination on newly diagnosed PLWD while 28.1 and 39.1% provided counseling on foot care and hypoglycemia respectively. Annual comprehensive foot examination was conducted by only 12.5%, none of the physicians ever screened for microalbuminuria and only 21.9% conducted annual dilated eye examination. Majority (57.8%) rated their confidence in prescribing insulin as "low" and only 23.4% had ever prescribed outpatient insulin for type 2 diabetes in their practice. Glycemic monitoring was largely limited to FBG and only 17.2% monitored A1c. Duration of practice more than 10 years (OR 10.1; P 0.034) and non participation in diabetes training (OR 6.5; P 0.027) were significant predictors of poor diabetes care knowledge. CONCLUSION:Diabetes care knowledge and practice were poor among PCPs in Southeast Nigeria. There is an urgent need to improve their capacity to provide diabetes care through periodic training.

Dataset Information

Undiagnosed diabetes from cross-sectional GP practice data: an approach to identify communities with high likelihood of undiagnosed diabetes.

Objectives

Design

Setting

Participants

Main outcome measures

Results

Conclusions

Publications

Undiagnosed diabetes from cross-sectional GP practice data: an approach to identify communities with high likelihood of undiagnosed diabetes.

Similar Datasets

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