Evaluation of the Clinical and Economic Effects of a Primary Care Anchored, Collaborative, Electronic Health Lifestyle Coaching Program in Denmark: Protocol for a Two-Year Randomized Controlled Trial.

BACKGROUND: Obesity is linked to a number of chronic health conditions, such as type 2 diabetes, heart disease, and cancer, and weight loss interventions are often expensive. Recent systematic reviews concluded that app and web-based interventions can improve lifestyle behaviors and weight loss at a reasonable cost, but long-term sustainability needs to be demonstrated. OBJECTIVE: This study protocol is for a 2-year randomized controlled trial that aims to evaluate the clinical and economic effects of a primary care, anchored, collaborative, electronic health (eHealth) lifestyle coaching program (long-term Lifestyle change InterVention and eHealth Application [LIVA] 2.0) in obese participants with and without type 2 diabetes. The program's primary outcome is weight loss. Its secondary outcome is the hemoglobin A1c (HbA1c) level, and its tertiary outcomes are retention rate, quality of life (QOL), and cost effectiveness. Analytically, the focus is on associations of participant characteristics with outcomes and sustainability. METHODS: We conduct a multicenter trial with a 1-year intervention and 1-year retention. LIVA 2.0 is implemented in municipalities within administrative regions in Denmark, specifically eight municipalities located within the Region of Southern Denmark and two municipalities located within the Capital Region of Denmark. The participants are assessed at baseline and at 6-, 12-, and 24-month follow-ups. Individual data from the LIVA 2.0 platform are combined with clinical measurements, questionnaires, and participants' usage of municipality and health care services. The participants have a BMI ≥30 but ≤45 kg/m2, and 50% of the participants have type 2 diabetes. The participants are randomized in an approximately 60:40 manner, and based on sample size calculations on weight loss and intention-to-treat statistics, 200 participants are randomized to an intervention group and 140 are randomized to a control group. The control group is offered the conventional preventive program of the municipality, and it is compared to the intervention group, which follows the LIVA 2.0 in addition to the conventional preventive program. RESULTS: The first baseline assessments have been carried out in March 2018, and the 2-year follow-up will be carried out between March 2020 and April 2021. The hypothesis is that the trial results will demonstrate decreased body weight and that the number of patients who show normalization of their HbA1c levels in the intervention group will be much higher than that in the control group. The participants in the intervention group are also expected to show a greater decrease in their use of glucose-lowering medication and a greater improvement in their QOL when compared with the control group. Operational costs are expected to be lower than standard care, and the intervention is expected to be cost-effective. CONCLUSIONS: This is the first time that an app and web-based eHealth lifestyle coaching program implemented in Danish municipalities will be clinically and economically evaluated. If the LIVA 2.0 eHealth lifestyle coaching program is proven to be effective, there is great potential for decreasing the rates of obesity, diabetes, and related chronic diseases. TRIAL REGISTRATION: ClinicalTrials.gov NCT03788915; https://clinicaltrials.gov/ct2/show/NCT03788915. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/19172.

Predicting Dropouts From an Electronic Health Platform for Lifestyle Interventions: Analysis of Methods and Predictors.

BACKGROUND: The increasing prevalence and economic impact of chronic diseases challenge health care systems globally. Digital solutions can potentially improve efficiency and quality of care, but these initiatives struggle with nonusage attrition. Machine learning methods have been proven to predict dropouts in other settings but lack implementation in health care. OBJECTIVE: This study aimed to gain insight into the causes of attrition for patients in an electronic health (eHealth) intervention for chronic lifestyle diseases and evaluate if attrition can be predicted and consequently prevented. We aimed to build predictive models that can identify patients in a digital lifestyle intervention at high risk of dropout by analyzing several predictor variables applied in different models and to further assess the possibilities and impact of implementing such models into an eHealth platform. METHODS: Data from 2684 patients using an eHealth platform were iteratively analyzed using logistic regression, decision trees, and random forest models. The dataset was split into a 79.99% (2147/2684) training and cross-validation set and a 20.0% (537/2684) holdout test set. Trends in activity patterns were analyzed to assess engagement over time. Development and implementation were performed iteratively with health coaches. RESULTS: Patients in the test dataset were classified as dropouts with an 89% precision using a random forest model and 11 predictor variables. The most significant predictors were the provider of the intervention, 2 weeks inactivity, and the number of advices received from the health coach. Engagement in the platform dropped significantly leading up to the time of dropout. CONCLUSIONS: Dropouts from eHealth lifestyle interventions can be predicted using various data mining methods. This can support health coaches in preventing attrition by receiving proactive warnings. The best performing predictive model was found to be the random forest.

Electronic Health Lifestyle Coaching Among Diabetes Patients in a Real-Life Municipality Setting: Observational Study.

BACKGROUND: Internet and mobile interventions aiming to promote healthy lifestyle have attracted much attention because of their scalability and accessibility, low costs, privacy and user control, potential for use in real-life settings, as well as opportunities for real-time modifications and interactive advices. A real-life electronic health (eHealth) lifestyle coaching intervention was implemented in 8 Danish municipalities between summer 2016 and summer 2018. OBJECTIVE: The aim of this study was to assess the effects associated with the eHealth intervention among diabetes patients in a real-life municipal setting. The eHealth intervention is based on an initial meeting, establishing a strong empathic relationship, followed by digital lifestyle coaching and collaboration supported by a Web-based community among patients. METHODS: We conducted an observational study examining the effect of an eHealth intervention on self-reported weight change among 103 obese diabetes patients in a real-life municipal setting. The patients in the study participated in the eHealth intervention between 3 and 12 months. A weight change was observed at 6, 9, and 12 months. We used regression methods to estimate the impacts of the intervention on weight change. RESULTS: We found that the eHealth intervention significantly reduced weight among diabetes patients, on average 4.3% of the initial body mass, which corresponds to 4.8 kg over a mean period of 7.3 months. Patients who were in intervention for more than 9 months achieved a weight reduction of 6.3% or 6.8 kg. CONCLUSIONS: This study brings forward evidence of a positive effect of a real-life eHealth lifestyle intervention on diabetes patients' lifestyle in a municipal setting. Future research is needed to show if the effect is sustainable from a long-term perspective.

Effect of screening for type 2 diabetes on healthcare costs: a register-based study among 139,075 individuals diagnosed with diabetes in Denmark between 2001 and 2009.

AIMS/HYPOTHESIS: Trials have not demonstrated benefits to the population of screening for type 2 diabetes. However, there may be cost savings for those found to have diabetes. We therefore aimed to compare healthcare costs among individuals with incident type 2 diabetes in a screened group with those in an unscreened group. METHODS: In this register-based, non-randomised controlled trial, eligible individuals were men and women aged 40-69 years without known diabetes who were registered with a general practice in Denmark (n = 1,912,392). Between 2001 and 2006, 153,107 individuals registered with 181 practices participating in the Anglo-Danish-Dutch Study of Intensive Treatment in People with Screen Detected Diabetes in Primary Care (ADDITION)-Denmark study were sent a diabetes risk-score questionnaire. Individuals with a moderate-to-high risk were invited to visit their family doctor for assessment of diabetes status and cardiovascular risk (screening group). The 1,759,285 individuals registered with all other practices in Denmark constituted the retrospectively constructed no-screening (control) group. In this post hoc analysis, we identified individuals from the screening and no-screening groups who were diagnosed with diabetes between 2001 and 2009 (n = 139,075). Using national registry data, we quantified the cost of healthcare services in these two groups between 2001 and 2012. From a healthcare sector perspective, we estimated the potential healthcare cost savings for individuals with diabetes that were attributable to the screening programme. RESULTS: In the screening group, 27,177 of 153,107 individuals (18% of those sent a risk-score questionnaire) attended for screening, 1533 of whom were diagnosed with diabetes. Between 2001 and 2009, 13,992 people were newly diagnosed with diabetes in the screening group (including those diagnosed by screening) and 125,083 in the no-screening group. Healthcare costs were significantly lower in the screening group compared with the no-screening group (difference in mean total annual healthcare costs -€889 per individual with incident diabetes; 95% CI -€1196, -€581). The screening programme was associated with a cost saving per person with incident diabetes over a 5-year period of €2688 (95% CI €1421, €3995). CONCLUSIONS/INTERPRETATION: Healthcare costs were lower among individuals with incident type 2 diabetes in the screened group compared with the unscreened group. The relatively modest cost of screening per person discovered to have developed diabetes was offset within 2 years by savings in the healthcare system.

Social inequality in diabetes patients' morbidity patterns from diagnosis to death - A Danish register-based investigation.

AIM: Measuring socioeconomic inequalities in health and health care, and understanding determinants of such inequalities, are critical for achieving higher equity in health. Equity in health is a prerequisite for public health and welfare. The aim of the paper is (1) to quantify inequality in diabetes morbidity patterns over patients' entire life span, and (2) to compare levels of inequality measured through income and educational level, respectively, as proxies for socioeconomic status (SES). METHOD: Historic individual register data on the entire Danish diabetes population alive in 2011 were gathered. Cox survival analysis and a concentration index decomposition approach were applied to analyse relevant morbidity indicators reflecting patients' health state at diagnosis and throughout their lives with diabetes. RESULTS: Patients with high education have approximately 26% lower mortality hazard when diagnosed with diabetes and 10-15% lower hazard of developing complications as compared with patients with short education. The outcome variables: 'severe complications at diagnosis' and 'years with severe complications' inhibit the highest negative concentration index value, indicating that morbidity is concentrated among the lower SES groups, whereas the outcome variables 'years without complications' and 'duration of diabetes' concentrate among the socioeconomically better-off patients. CONCLUSIONS: Significant differences in diabetes patients' morbidity patterns and survival indicate that diabetes impacts harder on patients of lower SES; these patients experience more severe complications and die earlier. Hence to reduce inequality in health, it is important to invest in efforts targeted towards socially vulnerable groups.

Socioeconomic inequality of diabetes patients' health care utilization in Denmark.

Understanding socioeconomic inequalities in health care is critical for achieving health equity. The aim of this paper is threefold: 1) to quantify inequality in diabetes health care service utilization; 2) to understand determinants of these inequalities in relation to socio-demographic and clinical morbidity factors; and 3) to compare the empirical outcome of using income level and educational level as proxies for Socio Economic Status (SES).Data on the entire Danish population of diabetes patients in 2011 (N = 318,729) were applied. Patients' unique personal identification number enabled individual patient data from several national registers to be linked. A concentration index approach with decomposition into contributing factors was applied. Differences in diabetes patients' health care utilization patterns suggest that use of services differ among patients of lower and higher SES, despite the Danish universal health care system. Especially, out-patient services, rehabilitation and specialists in primary care show different utilization patterns according to SES. Comparison of the empirical outcome from using educational level and income level as proxy for patients' SES indicate important differences in inequality estimates. While income, alike other measures of labor market attachment, to a certain extent is explained by morbidity and thus endogenous, education is more decisive for patients' ability to take advantage of the more specialized services provided in a universal health care system.

Incidence, morbidity, mortality, and prevalence of diabetes in Denmark, 2000-2011: results from the Diabetes Impact Study 2013.

PURPOSE: As part of the Danish Diabetes Impact Study 2013, we present trends in the incidence, morbidity, mortality, and prevalence of diabetes in Denmark for the period 2000 through 2011. PATIENTS AND METHODS: The Danish National Diabetes Register was established in 2006 and is assumed to cover all patients with diabetes, alive as of the end of 1996, and all subsequent new cases. The present study is based on the content of the register as of July 3, 2013 (n=497,232 patients). Using the personal identification code assigned to all Danish inhabitants, all available supplementary information from the Danish National Patient Register and the Danish Civil Registration Service was used to define the date of diagnosis of diabetes and the first date of experiencing complications (grouped according to impact and severity). RESULTS: During the period of 2000 to 2011, the incidence rate of diabetes increased approximately 5% annually. During the same period, decreasing trends were observed for both the rates of progression in complications and of the complication-specific mortality. During the same period, the prevalence of diabetes doubled. CONCLUSION: The increasing prevalence of diabetes in Denmark is driven by increasing incidence combined with decreasing morbidity and mortality in the population of patients with diabetes. These mechanisms will be explored further as part of the Diabetes Impact Study 2013, together with investigations into the socioeconomic and health economic aspects of diabetes.

Validation of the danish national diabetes register.

The Danish National Diabetes Register (NDR) was established in 2006 and builds on data from Danish health registers. We validated the content of NDR, using full information from the Danish National Patient Register and data from the literature. Our study indicates that the completeness in NDR is ≥95% concerning ascertainment from data sources specific for diabetes, ie, prescriptions with antidiabetic drugs and diagnoses of diabetes in the National Patient Register. Since the NDR algorithm ignores diabetes-related hospital contacts terminated before 1990, the establishment of the date of inclusion is systematically delayed for ≥10% of the registrants in general and for ≥30% of the inclusions before 1997 in particular. This bias is enhanced for ascertainment by chiropody services and by frequent measurements of blood glucose because the date of reimbursement of services, rather than the date of encounter, has been taken as the date of inclusion in NDR. We also find that some 20% of the registrations in NDR may represent false positive inclusions of persons with frequent measurements of blood glucose without having diabetes. We conclude that NDR is a novel initiative to support research in the epidemiological and public health aspects of diabetes in Denmark, but we also present a list of recommended changes for improving validity, by reducing the impact of current sources of bias and misclassifications.

Resources allocation and health care needs in diabetes care in Danish GP clinics.

BACKGROUND: In several countries, morbidity burdens have prompted authorities to change the system for allocating resources among patients from a demographic-based to a morbidity-based casemix system. In Danish general practice clinics, there is no morbidity-based casemix adjustment system. AIM: The aim of this paper was to assess what proportions of the variation in fee-for-service (FFS) expenditures are explained by type 2 diabetes mellitus (T2DM) patients' co-morbidity burden and illness characteristics. METHODS AND DATA: We use patient morbidity characteristics such as diagnostic markers and co-morbidity casemix adjustments based on resource utilisation bands and FFS expenditures for a sample of 6706 T2DM patients in 59 general practices for the year 2010. We applied a fixed-effect approach. RESULTS: Average annual FFS expenditures were approximately 398 euro per T2DM patient. Expenditures increased progressively with the patients' degree of co-morbidity and were higher for patients who suffered from diagnostic markers. A total of 17-25% of the expenditure variation was explained by age, gender and patients' morbidity patterns. CONCLUSION: T2DM patient morbidity characteristics are significant patient related FFS expenditure drivers in diabetes care. To address the specific health care needs of T2DM patients in GP clinics, our study indicates that it may be advisable to introduce a morbidity based casemix adjustment system.

The Danish Centre for Strategic Research in Type 2 Diabetes (DD2) study: expected outcome from the DD2 project and two intervention studies.

The overall aim of the Danish Centre for Strategic Research in Type 2 Diabetes (DD2) is to near-normalize metabolic control in newly diagnosed patients with type 2 diabetes (T2D) using an individualized treatment approach. We hypothesize that this will not only prevent complications and improve quality of life for T2D patients but also result in increased cost efficiency compared with current treatment modalities. This paper provides an overview of the expected outcomes from DD2, focusing on the two main intervention studies. The main data for the DD2 project are collected during patient enrollment and stored using the individual civil registration number. This enables subsequent linking to other national databases where supplemental data can be obtained. All data will be used for designing treatment guidelines and continuously monitoring the development of diabetic complications, thereby obtaining knowledge about predictors for the long-term outcome and identifying targets for new interventions. Further data are being collected from two intervention studies. The aim of the first intervention study is to improve T2D treatment using an individualized treatment modality optimizing medication according to individual metabolic responses and phenotypic characteristics. The aim of the second intervention study is to develop an evidence-based training protocol to be implemented as a treatment modality for T2D and used for initiating lifelong changes in physical activity levels in patients with T2D. An initial pilot study evaluating an interval-based walking protocol is ongoing, and preliminary results indicate that this protocol is an optimal "free-living" training intervention. An initial health-economic analysis will also be performed as a basis for analysis of the data collected during the project. A cost-benefit analysis of the two intervention studies will be conducted. The DD2 project is expected to lead to improved treatment modalities and increased knowledge about existing treatment guidelines, and will also provide a solid base for health-economic decision-making.

Database on Danish population-based registers for public health and welfare research.

Population-based studies with information from registers can take place in Denmark due to linkage between registers at the individual level by means of a unique personal identification number (CPR-number), which all persons with residence in Denmark have. Registers with information on health can be linked to other population registers containing information on, for example, transfer payments, education, housing, income, and socioeconomic position. This article introduces a database and search engine, which is available for public health and welfare researchers as an aid to seek information on the content of important Danish registers.