Inequalities in the use of eHealth between socioeconomic groups among patients with type 1 and type 2 diabetes : cross-sectional study

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Quality of care for patients with type 2 diabetes in general practice according to patients' ethnic background: a cross-sectional study from Oslo, Norway

<p>Abstract</p> <p>Background</p> <p>In recent decades immigration to Norway from Asia, Africa and Eastern Europe has increased rapidly. The aim of this study was to assess the quality of care for type 2 diabetes mellitus (T2DM) patients from these ethnic minority groups compared with the care received by Norwegians.</p> <p>Methods</p> <p>In 2006, electronic medical record data were screened at 11 practices (49 GPs; 58857 patients). 1653 T2DM patients cared for in general practice were identified. Ethnicity was defined as self-reported country of birth. Chi-squared tests, one-way ANOVAs, multiple regression, linear mixed effect models and generalized linear mixed models were used.</p> <p>Results</p> <p>Diabetes was diagnosed at a younger age in patients from the ethnic minority groups (South Asians (SA): mean age 44.9 years, Middle East/North Africa (MENA): 47.2 years, East Asians (EA): 52.0 years, others: 49.0 years) compared with Norwegians (59.7 years, p < 0.001). HbA1c, systolic blood pressure (SBP) and s-cholesterol were measured in >85% of patients in all groups with minor differences between minority groups and Norwegians. A greater proportion of the minority groups were prescribed hypoglycaemic medications compared with Norwegians (≥79% vs. 72%, p < 0.001). After adjusting for age, gender, diabetes duration, practice and physician unit, HbA1c (geometric mean) for Norwegians was 6.9% compared to 7.3-7.5% in the minority groups (p < 0.05). The proportion with poor glycaemic control (HbA1c > 9%) was higher in minority groups (SA: 19.6%, MENA: 18.9% vs. Norwegians: 5.6%, p < 0.001. No significant ethnic differences were found in the proportions reaching the combined target: HbA1c ≤ 7.5%, SBP ≤ 140 mmHg, diastolic blood pressure (DBP) ≤ 85 mmHg and total s-cholesterol ≤5.0 mmol/L (Norwegians: 25.5%, SA: 24.9%, MENA: 26.9%, EA: 26.1%, others:17.5%).</p> <p>Conclusions</p> <p>Mean age at the time of diagnosis of T2DM was 8-15 years younger in minority groups compared with Norwegians. Recording of important processes of care measures is high in all groups. Only one in four of most patient groups achieved all four treatment targets and prescribing habits may be sub-optimal. Patients from minority groups have worse glycaemic control than Norwegians which implies that it might be necessary to improve the guidelines to meet the needs of specific ethnic groups.</p

Variation between general practitioners in type 2 diabetes processes of care

Aims To explore variation in general practitioners’ (GPs’) performance of six recommended procedures in type 2 diabetes patients <75 years without cardiovascular disease. Methods Cross-sectional study of quality of diabetes care in Norway based on electronic health records from 2014. GPs (clustered in practices) were divided in quintiles based on a composite measure of performance of six processes of care. We fitted a multilevel partial ordinal regression model to identify GP factors associated with being in quintiles with better performance. Results We identified 6015 type 2 diabetes patients from 275 GPs in 77 practices. The GPs performed on average 63.4% of the procedures; on average 46% in the poorest quintile to 81% in the best quintile with a larger range in individual GPs. After adjustments, use of a structured follow-up form was associated with GPs being in upper three quintiles (OR 12.4 (95% CI 2.37–65.1). Routines for reminders were associated with being in a better quintile (OR 2.6 (1.37–4.92). GPs’ age >60 years and heavier workload were associated with poorer performance. Conclusion We found large variations in GPs’ performance of processes of care. Factors reflecting structure and workload were strongly associated with performance.publishedVersio

Clinical reappraisal of SHORT syndrome with PIK3R1 mutations: towards recommendation for molecular testing and management

International audienceSHORT syndrome has historically been defined by its acronym: short stature (S), hyperextensibility of joints and/or inguinal hernia (H), ocular depression (O), Rieger abnormality (R) and teething delay (T). More recently several research groups have identified PIK3R1 mutations as responsible for SHORT syndrome. Knowledge of the molecular etiology of SHORT syndrome has permitted a reassessment of the clinical phenotype. The detailed phenotypes of 32 individuals with SHORT syndrome and PIK3R1 mutation, including eight newly ascertained individuals, were studied to fully define the syndrome and the indications for PIK3R1 testing. The major features described in the SHORT acronym were not universally seen and only half (52%) had 4 or more of the classic features. The commonly observed clinical features of SHORT syndrome seen in the cohort included IUGR \textless 10(th) percentile, postnatal growth restriction, lipoatrophy and the characteristic facial gestalt. Anterior chamber defects and insulin resistance or diabetes were also observed but were not as prevalent. The less specific, or minor features of SHORT syndrome include teething delay, thin wrinkled skin, speech delay, sensorineural deafness, hyperextensibility of joints and inguinal hernia. Given the high risk of diabetes mellitus, regular monitoring of glucose metabolism is warranted. An echocardiogram, ophthalmological and hearing assessments are also recommended

Associations Between the Use of eHealth and Out-of-Hours Services in People With Type 1 Diabetes: Cross-Sectional Study

Background - Despite the increasing prevalence of diabetes and the increasing use of eHealth, little is known about the association between provider-based health services and eHealth among people with diabetes. This is the second study in a project exploring the associations between the use of eHealth and the use of provider-based health services. Objective - The objective of this study was to investigate which eHealth services are used among out-of-hours (OOH) visitors with type 1 diabetes (T1D), and whether the use of eHealth (eg, apps, search engines, video services, and social media) was associated with the use of OOH services. We also wanted to investigate associations between anxiety, reassurance, and change in doctor-seeking behavior because of health information acquired from the Internet, and the use of OOH services. Methods - We used data from a 2018 email survey of members of the Norwegian Diabetes Association (18-89 years old). Respondents with T1D were eligible for analyses. Using descriptive statistics, we estimated the use of OOH services and eHealth. Using logistic regressions, we studied the associations between the use of OOH services and the use of eHealth, as well as associations between the use of OOH services and reported consequences of using Internet-based health information. Results - In the sample of 523 people with T1D (mean age 47 years), 26.7% (129/484) visited OOH services once or more during the previous year. Among the OOH visitors, search engines were used for health purposes by 86.7% (111/128), apps (health apps in general) by 63.6% (82/129), social media by 45.3% (58/128), and video services by 28.4% (36/127). The use of OOH services was positively associated with self-reported anxiety/depression (odds ratio [OR] 4.53, 95% CI 1.43-14.32) and with the use of apps (OR 1.73, 95% CI 1.05-2.85), but not with other types of eHealth. Those who had felt anxious based on information from the Internet were more likely to visit OOH services compared with those who had not felt anxious (OR 2.38, 95% CI 1.50-3.78). People who had decided to consult a doctor based on information from the Internet were more likely to visit OOH services (OR 2.76, 95% CI 1.64-4.66), compared to those who had not made such an Internet-based decision. Conclusions - People with T1D were frequent users of OOH services, and the OOH visitors were frequent users of eHealth. The use of OOH services was positively associated with the use of health apps, with self-reported anxiety/depression, and with feeling anxious based on information from the Internet. Likewise, deciding to consult a doctor based on information from the Internet was positively associated with OOH visits. The use of eHealth seems to have a significant impact on people with T1D

Use of Electronic Health and Its Impact on Doctor-Visiting Decisions Among People With Diabetes: Cross-Sectional Study

Background: Despite the increasing prevalence of diabetes and increasing use of electronic health (eHealth) among people with diabetes, little is known about the association between the use of eHealth and the use of provider-based health services. Objective: The objective of this study was to investigate whether the use of eHealth might change patients’ decisions regarding doctor-seeking behavior and whether information acquired from the internet was discussed with a doctor. Methods: We used email survey data collected in 2018 from members of the Norwegian Diabetes Association (aged 18 to 89 years) diagnosed with diabetes. Using logistic regressions, we studied patients’ internet-triggered changes in decisions regarding doctor visits; whether they discussed information from the internet with a doctor; and whether these topics were associated with gender, age, education, self-rated health, and self-reported anxiety/depression. Results: Among the 895 informants, 75.4% (645/856) had never made an internet-triggered change of decision in any direction regarding visiting a doctor, whereas 16.4% (41/859) had decided to visit and 17.3% (148/856) had decided not to visit. The probability of changing decisions decreased with higher age and increased with the severity of self-reported anxiety/depression. Around half of the study participants (448/858, 52.2%) had never discussed information from the internet with a doctor. The probability of discussing internet information with a doctor was higher for those in bad/very bad self-rated health (odds ratio 2.12, CI 1.15-3.90) and for those with moderate self-reported anxiety/depression (odds ratio 2.30, CI 1.30-4.10). Conclusions: Our findings suggest that using eHealth has a significant impact on doctor-visiting decisions among people with diabetes, especially among people aged 18 to 39 years and among those reporting anxiety/depression. It is of great importance that the information posted is of high quality and that the large differences between internet-users regarding age as well as mental and somatic health status are taken into account. More research is needed to confirm and further explore the findings of this study

Relations between the use of electronic health and the use of general practitioner and somatic specialist visits in patients with type 1 diabetes: Cross-sectional study

Background: The prevalence of diabetes and the use of electronic health (eHealth) are increasing. People with diabetes need frequent monitoring and follow-up of health parameters, and eHealth services can be of great value. However, little is known about the association between the use of eHealth and provider-based health care services among people with diabetes. Objective: The objective of this study was to investigate the use of 4 different eHealth platforms (apps, search engines, video services, and social media sites) and associations with the use of provider-based health care visits among people diagnosed with type 1 diabetes mellitus (T1DM). Methods: We used email survey data collected from 1250 members of the Norwegian Diabetes Association (aged 18 to 89 years) in 2018. Eligible for analyses were the 523 respondents with T1DM. Using descriptive statistics, we estimated the use of eHealth and the use of general practitioners (GPs) and somatic specialist outpatient services. By logistic regressions, we studied the associations between the use of these provider-based health services and the use of eHealth, adjusted for gender, age, education, and self-rated health. Results: Of the sample of 523 people with T1DM, 90.7% (441/486) had visited a GP once or more, and 61.0% (289/474) had visited specialist services during the previous year. Internet search engines (such as Google) were used for health purposes sometimes or often by 84.0% (431/513), apps by 55.4% (285/514), social media (such as Facebook) by 45.2% (232/513), and video services (such as YouTube) by 23.3% (118/506). Participants aged from 18 to 39 years used all forms of eHealth more than people aged 40 years and older, with the exception of social media. The use of search engines was positively associated with the use of somatic specialist services (odds ratio 2.43, 95% CI 1.33-4.45). GP visits were not associated with any kind of eHealth use. Conclusions: eHealth services are now widely used for health support and health information by people with T1DM, primarily in the form of search engines but often in the form of apps and social media as well. We found a positive association between the use of search engines and specialist visits and that people with T1DM are frequent users of eHealth, GPs, and specialist services. We found no evidence that eHealth reduces the use of provider-based health care; these services seem to be additional rather than alternative. Future research should focus on how health care services can meet and adapt to the high prevalence of eHealth use. Our results also indicate that many patients with T1DM do not visit specialist clinics once a year as recommended. This raises questions about collaboration in health care services and needs to be followed up in future research.</p