Mobile reminders to improve opportunistic screening of type 2 diabetes mellitus: Data documentation and data analysis plan of a randomized trial data.
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ABSTRACT:
SUBMITTER: Shewade HD
PROVIDER: S-EPMC4749946 | biostudies-literature | 2016 Mar
REPOSITORIES: biostudies-literature
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Mobile reminders to improve opportunistic screening of type 2 diabetes mellitus: Data documentation and data analysis plan of a randomized trial data.
Shewade Hemant Deepak HD Kumar Sathish S
Data in brief 20160129
This Data in Brief article contains individual level data of a randomized trial in a primary care setting. This trial offered mobile reminder to follow up for definitive tests during opportunistic screening of diabetes mellitus in Puducherry, India (2014). ("Effect of mobile reminders on screening yield during opportunistic screening for type 2 diabetes mellitus in a primary health care setting: a randomized trial" (Kumar et al., 2015) [1]) Variables collected included the baseline characteristi ...[more]
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Project description:ObjectiveTo determine the potential of opportunistic glycated haemoglobin (HbA1c) testing of pathology samples to detect previously unknown diabetes.DesignPathology samples from participants collected for other reasons and suitable for HbA1c testing were utilised for opportunistic diabetes screening. HbA1c was measured with a Biorad Variant II turbo analyser and HbA1c levels of ?6.5% (48 mmol/mol) were considered diagnostic for diabetes. Confirmation of previously unknown diabetes status was obtained by a review of hospital medical records and phone calls to general practitioners.SettingHospital pathology laboratory receiving samples from hospital-based and community-based (CB) settings.ParticipantsParticipants were identified based on the blood sample collection location in the CB, emergency department (ED) and inpatient (IP) groups. Exclusions pretesting were made based on the electronic patient history of: age <18 years, previous diabetes diagnosis, query for diabetes status in the past 12 months, evidence of pregnancy and sample collected postsurgery or transfusion. Only one sample per individual participant was tested.ResultsOf the 22 396 blood samples collected, 4505 (1142 CB, 1113 ED, 2250 IP) were tested of which 327 (7.3%) had HbA1c levels ?6.5% (48 mmol/mol). Of these 120 (2.7%) were determined to have previously unknown diabetes (11 (1%) CB, 21 (1.9%) ED, 88 (3.9%) IP). The prevalence of previously unknown diabetes was substantially higher (5.4%) in hospital-based (ED and IP) participants aged over 54 years.ConclusionsOpportunistic testing of referred pathology samples can be an effective method of screening for diabetes, especially in hospital-based and older persons.
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Project description:AimsTo develop and validate prediction equations to identify individuals at high risk for type 2 diabetes using existing health plan data.MethodsHealth plan data from 2005 to 2009 from 18,527 members of a Midwestern HMO without diabetes, 6% of whom had fasting plasma glucose (FPG) ?110mg/dL, and health plan data from 2005 to 2006 from 368,025 members of a West Coast-integrated delivery system without diabetes, 13% of whom had FPG ?110mg/dL were analyzed. Within each health plan, we used multiple logistic regression to develop equations to predict FPG ?110mg/dL for half of the population and validated the equations using the other half. We then externally validated the equations in the other health plan.ResultsAreas under the curve for the most parsimonious equations were 0.665 to 0.729 when validated internally. Positive predictive values were 14% to 32% when validated internally and 14% to 29% when validated externally.ConclusionMultivariate logistic regression equations can be applied to existing health plan data to efficiently identify persons at higher risk for dysglycemia who might benefit from definitive diagnostic testing and interventions to prevent or treat diabetes.
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Project description:IntroductionPhysicians enter residency with varied knowledge regarding the purpose of progress notes and proficiency writing them. The objective of this study was to test whether resident knowledge, beliefs, and confidence writing inpatient progress notes improved after a 2.5-hour workshop intervention.MethodsAn educational workshop and note assessment tool was constructed by resident and faculty stakeholders based on a review of literature and institutional best practices. The Progress Note Assessment and Plan Evaluation (PNAPE) tool was designed to assess adherence to best practices in the assessment and plan section of progress notes. Thirty-four residents from a midsized pediatric residency program attended the workshop, which consisted of didactics and small-group work evaluating sample notes using the PNAPE tool. Participants completed a four-question online pre- and postworkshop survey to evaluate their knowledge of progress note components and attitudes regarding note importance. Pre-post analysis was performed with Chi-square testing for true/false questions, and Mann-Whitney testing for Likert scale questions and summative scores.ResultsA majority of pediatric residents completed the preintervention (n = 26, 76% response rate) and postintervention (n = 23, 68% response rate) surveys. Accurate response rate improved in 15 of 20 of the true/false items, with a statistically significant improvement in five items. Resident perceptions of note importance and confidence in note writing also increased.DiscussionA workshop intervention may effectively educate pediatric residents about progress note best practices. Further studies should assess the impact of the intervention on sustained knowledge and beliefs about progress notes and subsequent note quality.
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Project description:BackgroundImprovement in the accuracy of identifying women who are at risk to develop gestational diabetes mellitus (GDM) is warranted, since timely diagnosis and treatment improves the outcomes of this common pregnancy disorder. Although prognostic models for GDM are externally validated and outperform current risk factor based selective approaches, there is little known about the impact of such models in day-to-day obstetric care.MethodsA prognostic model was implemented as a directive clinical prediction rule, classifying women as low- or high-risk for GDM, with subsequent distinctive care pathways including selective midpregnancy testing for GDM in high-risk women in a prospective multicenter birth cohort comprising 1073 pregnant women without pre-existing diabetes and 60 obstetric healthcare professionals included in nine independent midwifery practices and three hospitals in the Netherlands (effectiveness-implementation hybrid type 2 study). Model performance (c-statistic) and implementation outcomes (acceptability, adoption, appropriateness, feasibility, fidelity, penetration, sustainability) were evaluated after 6 months by indicators and implementation instruments (NoMAD; MIDI).ResultsThe adherence to the prognostic model (c-statistic 0.85 (95%CI 0.81-0.90)) was 95% (n = 1021). Healthcare professionals scored 3.7 (IQR 3.3-4.0) on implementation instruments on a 5-point Likert scale. Important facilitators were knowledge, willingness and confidence to use the model, client cooperation and opportunities for reconfiguration. Identified barriers mostly related to operational and organizational issues. Regardless of risk-status, pregnant women appreciated first-trimester information on GDM risk-status and lifestyle advice to achieve risk reduction, respectively 89% (n = 556) and 90% (n = 564)).ConclusionsThe prognostic model was successfully implemented and well received by healthcare professionals and pregnant women. Prognostic models should be recommended for adoption in guidelines.
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Project description:BackgroundDiabetes mellitus, a metabolic disorder characterised by hyperglycaemia and associated with a heavy burden of microvascular and macrovascular complications, frequently remains undiagnosed. Screening of apparently healthy individuals may lead to early detection and treatment of type 2 diabetes mellitus and may prevent or delay the development of related complications.ObjectivesTo assess the effects of screening for type 2 diabetes mellitus.Search methodsWe searched CENTRAL, MEDLINE, LILACS, the WHO ICTRP, and ClinicalTrials.gov from inception. The date of the last search was May 2019 for all databases. We applied no language restrictions.Selection criteriaWe included randomised controlled trials involving adults and children without known diabetes mellitus, conducted over at least three months, that assessed the effect of diabetes screening (mass, targeted, or opportunistic) compared to no diabetes screening.Data collection and analysisTwo review authors independently screened titles and abstracts for potential relevance and reviewed the full-texts of potentially relevant studies, extracted data, and carried out 'Risk of bias' assessment using the Cochrane 'Risk of bias' tool. We assessed the overall certainty of the evidence using the GRADE approach.Main resultsWe screened 4651 titles and abstracts identified by the search and assessed 92 full-texts/records for inclusion. We included one cluster-randomised trial, the ADDITION-Cambridge study, which involved 20,184 participants from 33 general practices in Eastern England and assessed the effects of inviting versus not inviting high-risk individuals to screening for diabetes. The diabetes risk score was used to identify high-risk individuals; it comprised variables relating to age, sex, body mass index, and the use of prescribed steroid and anti-hypertensive medication. Twenty-seven practices were randomised to the screening group (11,737 participants actually attending screening) and 5 practices to the no-screening group (4137 participants). In both groups, 36% of participants were women; the average age of participants was 58.2 years in the screening group and 57.9 years in the no-screening group. Almost half of participants in both groups were on antihypertensive medication. The findings from the first phase of this study indicate that screening compared to no screening for type 2 diabetes did not show a clear difference in all-cause mortality (hazard ratio (HR) 1.06, 95% confidence interval (CI) 0.90 to 1.25, low-certainty evidence). Screening compared to no screening for type 2 diabetes mellitus showed an HR of 1.26, 95% CI 0.75 to 2.12 (low-certainty evidence) for diabetes-related mortality (based on whether diabetes was reported as a cause of death on the death certificate). Diabetes-related morbidity and health-related quality of life were only reported in a subsample and did not show a substantial difference between the screening intervention and control. The included study did not report on adverse events, incidence of type 2 diabetes, glycosylated haemoglobin A1c (HbA1c), and socioeconomic effects.Authors' conclusionsWe are uncertain about the effects of screening for type 2 diabetes on all-cause mortality and diabetes-related mortality. Evidence was available from one study only. We are therefore unable to draw any firm conclusions relating to the health outcomes of early type 2 diabetes mellitus screening. Furthermore, the included study did not assess all of the outcomes prespecified in the review (diabetes-related morbidity, incidence of type 2 diabetes, health-related quality of life, adverse events, socioeconomic effects).
| S-EPMC7259754 | biostudies-literature
Project description:BackgroundMobile health (mHealth) is increasingly advocated for diabetes management. It is unclear if mobile applications are effective in improving glycaemic control, clinical outcomes, quality of life and overall patient satisfaction in patients with type 2 diabetes (T2DM). A new mobile application was specifically built for people with T2DM with the help of the local expertise. The objective of the study was to evaluate the effectiveness of the mobile app.MethodsThe planned study is an ongoing open-label randomised controlled trial in which adults living with T2DM treated with insulin will be randomised 1:1 to the use of this diabetes application versus current standard care. The primary outcome will be the difference in mean HbA1c from baseline to 6 months. Other outcome measures include anthropometric measures, hypoglycaemic events, medication adjustments, number of clinical interactions and missed appointments and patient perceptions of their disease and diabetes self-management. The study will randomise 180 subjects for assessment of the primary outcome.DiscussionWe hypothesise that the diabetes-specific mobile application will improve glycaemic control, increase patient empowerment for self-management of diabetes and improve interaction between patients and healthcare providers. If the Qatar Diabetes Mobile Application Trial (QDMAT) demonstrates this, it will inform clinical services for the future self-management of T2DM.Trial registrationClinicalTrials.gov Identifier: NCT03998267 . Registered on 26 June 2019.
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Project description:Health information technology has been proven to be a successful tool for the management of patients with multiple medical conditions. The purpose of this study was to examine the impact of an enhanced telemedicine system on glucose control and pregnancy outcomes in women with gestational diabetes mellitus (GDM).We used an Internet-based telemedicine system to also allow interactive voice response phone communication between patients and providers and to provide automated reminders to transmit data. Women with GDM were randomized to either the telemedicine group (n=40) or the control group (n=40) and asked to monitor their blood glucose levels four times a day. Women in the intervention group transmitted those values via the telemedicine system, whereas women in the control group maintained paper logbooks, which were reviewed at prenatal visits. Primary outcomes were infant birth weight and maternal glucose control. Data collection included blood glucose records, transmission rates for the intervention group, and chart review.There were no significant differences between the two groups (telemedicine vs. controls) in regard to maternal blood glucose values or infant birth weight. However, adding telephone access and reminders increased transmission rates of data in the intervention group compared with the intervention group in our previous study (35.6±32.3 sets of data vs.17.4±16.9 sets of data; P<0.01).Our enhanced telemedicine monitoring system increased system utilization and contact between women with GDM and their healthcare providers but did not impact upon pregnancy outcomes.
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Project description:BackgroundMobile technology has great potential to improve adherence and treatment outcomes in healthcare settings. However, text messaging and phone calls are unaffordable in many resource-limited areas. This study investigates the use of a no-cost alternative mobile phone technology using missed calls ('buzzing') to act as a patient reminder. The use of missed calls as a patient reminder was evaluated for feasibility and effectiveness as an appointment reminder in the follow-up of newly-diagnosed human immunodeficiency virus (HIV) positive patients in an HIV testing and counselling department in rural Swaziland.MethodsThis pilot study uses a before-and-after operational research study design, with all patients with mobile phones being offered the intervention. The primary outcome was the rate of attendance at the HIV testing and counselling department for collection of results in those with mobile phones before and after the introduction of the intervention.ResultsOver two-thirds, 71.8% (459/639), of patients had a mobile phone. All patients with a mobile phone consented to being buzzed. There was no difference in attendance for follow-up at the clinic before and after the intervention was implemented (80.1% versus 83.3%, p = 0.401), or after adjusting for confounding factors (OR 1.13, p = 0.662).ConclusionThis pilot study illustrates that mobile technology may be feasible in rural, resource-poor settings as there are high rates of mobile phone ownership and the intervention had a 100% uptake rate, with positive feedback from staff and patients. In this particular setting, the intervention did not improve attendance rates. However, further research is planned to investigate the impact on adherence to appointments and medications in other settings, such as HIV chronic care follow-up and as part of an enhanced package to improve adherence.
| S-EPMC3710074 | biostudies-literature
Project description:OBJECTIVE:We evaluated whether regular mobile phone text reminders improved patients' retention in antiretroviral therapy (ART) care in Mozambique. DESIGN:SMSaúde was a randomized control trial of HIV-infected patients on ART who received regular text message reminder vs. standard of care at 3 public health facilities in Maputo Province, Mozambique. The primary outcome was retention in HIV care. Between November 2011 and March 2012, 830 eligible HIV-infected patients on ART were randomized 1:1 to the text reminder intervention or standard of care. METHODS:We used Kaplan-Meier estimators and log-rank tests to compare proportions of patients who received SMS reminders who were retained in HIV care compared to the control group who received standard of care. Post hoc analyses were performed using Cox proportional hazards models stratified by urban/rural facility and when initiated ART (?3 months vs. >3 months). Hazard ratios and confidence intervals (CIs) are reported. Analysis was with intention to treat. RESULTS:Patients who received text messages had lower attrition from HIV care at 12 months, though the difference was nonsignificant (RR: 0.68, 95% CI: 0.41 to 1.13). Among urban patients, text messages improved retention in HIV care (RR: 0.54, 95% CI: 0.31 to 0.95). Intervention patients newly initiated on ART (<3 months) had lower attrition than control patients (HR: 0.54; 95% CI: 0.23 to 0.91), especially urban newly initiated patients (HR: 0.20, 95% CI: 0.06 to 0.64). Text messages had no effect on retention among rural patients. CONCLUSIONS:Text messages did not improve retention in HIV care for all patients on ART but improved retention in care of urban patients and those who recently started ART and received text reminders compared with standard of care.
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Project description:The conventional method for developing health care plan payment systems uses observed data to study alternative algorithms and set incentives for the health care system. In this paper, we take a different approach and transform the input data rather than the algorithm, so that the data used reflect the desired spending levels rather than the observed spending levels. We present a general economic model that incorporates the previously overlooked two-way relationship between health plan payment and insurer actions. We then demonstrate our systematic approach for data transformations in two Medicare applications: underprovision of care for individuals with chronic illnesses and health care disparities by geographic income levels. Empirically comparing our method to two other common approaches shows that the "side effects" of these approaches vary by context, and that data transformation is an effective tool for addressing misallocations in individual health insurance markets.
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