Financial incentives for diabetes prevention in a Medicaid population: Study design and baseline characteristics

Desai, Jay; Taylor, Gretchen; Vazquez‐Benitez, Gabriela; Vine, Sara; Anderson, Julie D.; Garrett, Joyce E.; Gilmer, Todd; Vue‐Her, Houa; Schiff, Jeff; Rinn, Sarah; Engel, Katelyn; Michael, Amy; O’Connor, Patrick J.

doi:10.1016/j.cct.2016.11.007

Cited by 19 publications

(34 citation statements)

References 51 publications

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“…Various systematic reviews have covered the effect of incentives and cash rewards on lifestyle behaviours [36][37][38][39] , but none of these reviews evaluated its impact on type 2 diabetes mellitus. Other trials have explored or are exploring the effect of individual versus group financial incentives for reducing weight loss in high-income settings, with rewards up to $520 USD 19,40 , much larger than the ones provided in our study. In the UK, Relton et al 41 assessed an NHS-commissioned financial incentive weight loss program, aiming to reduce between 6.8 to 22.7 kg in 3 to 7 months, with incentives ranging from £70 to £425.…”

Section: Discussionmentioning

confidence: 95%

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The effect of individual and mixed rewards on diabetes management: A feasibility randomized controlled trial

Miranda¹,

Lazo-Porras²,

Bernabé‐Ortiz³

et al. 2018

Wellcome Open Res

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Background: Incentives play a role in introducing health-related benefits, but no interventions using mixed incentives, i.e. a combination of individual and group incentives, have been tested in individuals with type 2 diabetes mellitus (T2DM). We evaluated the feasibility of implementing individual- and mixed-incentives, with and without a supportive partner, on glycated haemoglobin (HbA1c) control and weight loss among patients with T2DM. Methods: This is a feasibility, sex-stratified, single-blinded, randomized controlled study in individuals with T2DM. All participants received diabetes education and tailored goal setting for weight and glycated haemoglobin (HbA1c). Participants were randomly assigned into three arms: individual incentives (Arm 1), mixed incentives-altruism (Arm 2), and mixed incentives-cooperation (Arm 3). Participants were accompanied by a diabetes educator every other week to monitor targets, and the intervention period lasted 3 months. The primary outcome was the change in HbA1c at 3 months from baseline. Weight and change body mass index (BMI) were considered as secondary outcomes. Results: Out of 783 patients screened, a total of 54 participants, 18 per study arm, were enrolled and 44 (82%) completed the 3-month follow-up. Mean baseline HbA1c values were 8.5%, 7.9% and 8.2% in Arm 1, Arm 2, and Arm 3, respectively. At 3 months, participants in all three study arms showed reductions in HbA1c ranging from -0.9% in Arm 2 to -1.4% in Arm 1. Weight and BMI also showed reductions. Conclusions: Individual and mixed cash incentives show important reductions in HbA1c, weight and BMI in patients with type 2 diabetes mellitus after 3 months. Recruitment and uptake of the intervention were successfully accomplished demonstrating feasibility to conduct larger effectiveness studies to test individual and mixed economic incentives for diabetes management. Registration: ClinicalTrials.gov Identifier NCT02891382

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Section: Discussionmentioning

confidence: 95%

“…Altruism lies at the opposite end of competition. Testing mixed or group-based approaches for diabetes prevention or management is relatively new, and some studies are being conducted 10,19 .…”

Section: Introductionmentioning

confidence: 99%

The effect of individual and mixed rewards on diabetes management: A feasibility randomized controlled trial

Miranda¹,

Lazo-Porras²,

Bernabé‐Ortiz³

et al. 2018

Wellcome Open Res

View full text Add to dashboard Cite

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“…In the last 18 months, clinic staff and community health workers formally trained by certified DPP Master Trainers also delivered the DPP to participants (Desai et al. ).…”

Section: Methodsmentioning

confidence: 99%

“…As part of the MIPCD program, Minnesota Department of Human Services and Minnesota Department of Health conducted the We Can Prevent Diabetes (WCPD) study to increase delivery of the DPP lifestyle program to Minnesota Medicaid enrollees with prediabetes (Desai et al. ). The WCPD study examined the effects of a DPP intervention that included two reward‐based financial incentive designs (one individually earned incentive and another a hybrid of individual‐ and group‐earned incentive) versus the effects of a DPP intervention without financial incentives on weight loss and related metabolic parameters.…”

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confidence: 99%

Cost‐Effectiveness of a Community‐Based Diabetes Prevention Program with Participation Incentives for Medicaid Beneficiaries

Gilmer

O’Connor

Schiff

et al. 2018

Health Services Research

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“…Also, with respect to the CAD frameworks [10] to help clinicians in their procedure of basic direction has expanded, along these lines encouraging speedier and increasingly exact demonstrative choices with less discrepancy. Particularly, radiomics-driven CAD [11] [12] has turn out across the board territories of research center, in which radiomic successions including of countless picture subordinate highlights are extricated and help clinicians to plan increasingly educated choices, and offer a virtual second estimation. Then again, ordinary radiomic sequences incorporate essentially of nonexclusive, hand-crafted qualities that may be restricting in depicting typical disease practices [13] [14].…”

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confidence: 99%

Tri Concomitant Local Feature Learning for Diabetic Retinopathy Classification

Randive,

Senapati

2019

IJEAT

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In this paper, we have proposed a new technique entitled as Transformed Directional Tri Concomitant Triplet Patterns with Artificial Neural Network is proposed for Diabetic Retinopathy Classification. TdtCTp consist of three stages to obtain detail directional information about pixel progression. In first stage, structural rule based approach is proposed to extract directional information in various direction. Further, in second stage, microscopic information and correlation between each sub-structural element are extracted by using concomitant conditions. Finally, minute directional intensity variation information and correlation between the sub-structural elements are extracted by integrating first two stages. After feature extraction, the extracted feature is used as input to the artificial neural network. To the best of our knowledge, this is the first learning based approach for diabetic retinopathy classification. Effectiveness of the proposed method is evaluated in terms of average precision and compared with existing state-of-the-art methods. The experimental analysis shows that the proposed method is achieved significant performance compared to other methods.

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Financial incentives for diabetes prevention in a Medicaid population: Study design and baseline characteristics

Cited by 19 publications

References 51 publications

The effect of individual and mixed rewards on diabetes management: A feasibility randomized controlled trial

The effect of individual and mixed rewards on diabetes management: A feasibility randomized controlled trial

Cost‐Effectiveness of a Community‐Based Diabetes Prevention Program with Participation Incentives for Medicaid Beneficiaries

Tri Concomitant Local Feature Learning for Diabetic Retinopathy Classification

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