Diabetes Health Information Technology Innovation to Improve Quality of Life for Health Plan Members in Urban Safety Net

Ratanawongsa, Neda; Handley, Margaret A.; Sarkar, Urmimala; Quan, Judy; Pfeifer, Kelly; Soria, Catalina; Schillinger, Dean

doi:10.1097/jac.0000000000000019

Cited by 17 publications

(34 citation statements)

References 53 publications

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“…The first limitation, as mentioned, is that the study likely was underpowered for economic outcomes, as the sample size was generated to detect differences in patient-centered outcomes, not economic outcomes. 16 In their previous costeffectiveness analysis involving a prior version of ATSM, 26 the investigators were able to focus on a range of values that met the threshold for cost-effectiveness. However, the current study did not evaluate cost-effectiveness, but differential costs and utilization.…”

Section: Discussionmentioning

confidence: 99%

“…Because the investigators' prior research revealed similar benefits for SMARTSteps-ONLY and SMARTSteps-PLUS participants, 16 for the current analysis these groups were combined and compared to the combined wait-listed groups.…”

Section: Discussionmentioning

confidence: 99%

“…16,27 Briefly, participants were recruited from 4 clinics in the Community Health Network of San Francisco (CHNSF) 26,28,29 SFHP members with diabetes who participated in SMARTSteps were randomized to one of 4 groups: SMARTSteps-ONLY, SMARTSteps-PLUS, or a wait-list for either intervention. The intervention focused on improving selfmanagement related to behaviors such as taking medications appropriately, eating a healthy diet, exercising and being physically active, depressive symptoms, and checking one's blood sugar level and one's feet for wounds and sores.…”

Section: Study Design and Participantsmentioning

confidence: 99%

“…[15][16][17][18] Automated telephone self-management support (ATSM) has been highlighted by the US Department of Health and Human Services as a potentially viable strategy to augment care for LHL and LEP populations with chronic conditions. However, few studies have rigorously evaluated the effects of diabetes self-management support on the health care costs among low-income populations.…”

Section: Introductionmentioning

confidence: 99%

“…The 27-week (6-month) intervention has previously been reported to improve patients' health-related quality of life and specific health behaviors, but was found to have no impact on cardiometabolic measures relative to waitlisted participants (NIH trial registration NCT00683020). 16 The purpose of the current study is to compare the health care utilization and costs of individuals in the ATSM intervention to those of wait-listed individuals during the 6-month period following randomization. This study took place within the University of California, San Francisco (UCSF) Collaborative Research Network (http://accelerate.ucsf.edu/community/ sfbaycrn), a primary care practice-based research network in the Northern California area, and received approval from the UCSF Institutional Review Board.…”

mentioning

confidence: 99%

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Automated Telephone Self-Management Support for Diabetes in a Low-Income Health Plan: A Health Care Utilization and Cost Analysis

Quan

Lee

Handley

et al. 2015

Population Health Management

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The objective was to determine whether automated telephone self-management support (ATSM) for lowincome, linguistically diverse health plan members with diabetes affects health care utilization or cost. A government-sponsored managed care plan for low-income patients implemented a demonstration project between 2009 and 2011 that involved a 6-month ATSM intervention for 362 English-, Spanish-, or Cantonesespeaking members with diabetes from 4 publicly funded clinics. Participants were randomized to immediate intervention or a wait-list. Medical and pharmacy claims used in this analysis were obtained from the managed care plan. Medical claims included hospitalizations, ambulance use, emergency department visits, and outpatient visits. In the 6-month period following enrollment, intervention participants generated half as many emergency department visits and hospitalizations (rate ratio 0.52, 95% CI 0.26, 1.04) compared to wait-listed participants, but these differences did not reach statistical significance (P = 0.06). With adjustment for prior year cost, intervention participants also had a nonsignificant reduction of $26.78 in total health care costs compared to wait-listed individuals (P = 0.93). The observed trends suggest that ATSM could yield potential health service benefits for health plans that provide coverage for chronic disease patients in safety net settings. ATSM should be further scaled up to determine whether it is associated with a greater reduction in health care utilization and costs. (Population Health Management 2015;18:412-420)

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Study Design and Participantsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Automated Telephone Self-Management Support for Diabetes in a Low-Income Health Plan: A Health Care Utilization and Cost Analysis

Quan

Lee

Handley

et al. 2015

Population Health Management

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Quality improvement strategies for diabetes care: Effects on outcomes for adults living with diabetes

Yogasingam

Konnyu

Lépine

et al. 2023

Cochrane Database of Systematic Reviews

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Background There is a large body of evidence evaluating quality improvement (QI) programmes to improve care for adults living with diabetes. These programmes are often comprised of multiple QI strategies, which may be implemented in various combinations. Decision‐makers planning to implement or evaluate a new QI programme, or both, need reliable evidence on the relative effectiveness of different QI strategies (individually and in combination) for different patient populations. Objectives To update existing systematic reviews of diabetes QI programmes and apply novel meta‐analytical techniques to estimate the effectiveness of QI strategies (individually and in combination) on diabetes quality of care. Search methods We searched databases (CENTRAL, MEDLINE, Embase and CINAHL) and trials registers (ClinicalTrials.gov and WHO ICTRP) to 4 June 2019. We conducted a top‐up search to 23 September 2021; we screened these search results and 42 studies meeting our eligibility criteria are available in the awaiting classification section. Selection criteria We included randomised trials that assessed a QI programme to improve care in outpatient settings for people living with diabetes. QI programmes needed to evaluate at least one system‐ or provider‐targeted QI strategy alone or in combination with a patient‐targeted strategy. ‐ System‐targeted: case management (CM); team changes (TC); electronic patient registry (EPR); facilitated relay of clinical information (FR); continuous quality improvement (CQI). ‐ Provider‐targeted: audit and feedback (AF); clinician education (CE); clinician reminders (CR); financial incentives (FI). ‐ Patient‐targeted: patient education (PE); promotion of self‐management (PSM); patient reminders (PR). Patient‐targeted QI strategies needed to occur with a minimum of one provider or system‐targeted strategy. Data collection and analysis We dual‐screened search results and abstracted data on study design, study population and QI strategies. We assessed the impact of the programmes on 13 measures of diabetes care, including: glycaemic control (e.g. mean glycated haemoglobin (HbA1c)); cardiovascular risk factor management (e.g. mean systolic blood pressure (SBP), low‐density lipoprotein cholesterol (LDL‐C), proportion of people living with diabetes that quit smoking or receiving cardiovascular medications); and screening/prevention of microvascular complications (e.g. proportion of patients receiving retinopathy or foot screening); and harms (e.g. proportion of patients experiencing adverse hypoglycaemia or hyperglycaemia). We modelled the association of each QI strategy with outcomes using a series of hierarchical multivariable meta‐regression models in a Bayesian framework. The previous version of this review identified that different strategies were more or less effective depending on baseline levels of outco...

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Peer Support in Prevention, Chronic Disease Management, and Well-Being

Fisher

Bhushan

Coufal³

et al. 2018

Principles and Concepts of Behavioral Medicine

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Diabetes Health Information Technology Innovation to Improve Quality of Life for Health Plan Members in Urban Safety Net

Cited by 17 publications

References 53 publications

Automated Telephone Self-Management Support for Diabetes in a Low-Income Health Plan: A Health Care Utilization and Cost Analysis

Automated Telephone Self-Management Support for Diabetes in a Low-Income Health Plan: A Health Care Utilization and Cost Analysis

Quality improvement strategies for diabetes care: Effects on outcomes for adults living with diabetes

Peer Support in Prevention, Chronic Disease Management, and Well-Being

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