1
|
Tseng E, Smith K, Clark JM, Segal JB, Marsteller JA, Maruthur NM. Using the Translating Research into Practice framework to develop a diabetes prevention intervention in primary care: a mixed-methods study. BMJ Open Qual 2024; 13:e002752. [PMID: 38839396 PMCID: PMC11163602 DOI: 10.1136/bmjoq-2024-002752] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Accepted: 05/28/2024] [Indexed: 06/07/2024] Open
Abstract
BACKGROUND Pre-diabetes affects one-third of US adults and increases the risk of type 2 diabetes. Effective evidence-based interventions, such as the Diabetes Prevention Program, are available, but a gap remains in effectively translating and increasing uptake of these interventions into routine care. METHODS We applied the Translating Research into Practice (TRiP) framework to guide three phases of intervention design and development for diabetes prevention: (1) summarise the evidence, (2) identify local barriers to implementation and (3) measure performance. In phase 1, we conducted a retrospective cohort analysis of linked electronic health record claims data to evaluate current practices in the management of pre-diabetes. In phase 2, we conducted in-depth interviews of 16 primary care physicians, 7 payor leaders and 31 patients to elicit common barriers and facilitators for diabetes prevention. In phase 3, using findings from phases 1 and 2, we developed the core elements of the intervention and performance measures to evaluate intervention uptake. RESULTS In phase 1 (retrospective cohort analysis), we found few patients with pre-diabetes received diabetes prevention interventions. In phase 2 (stakeholder engagement), we identified common barriers to include a lack of knowledge about pre-diabetes among patients and about the Diabetes Prevention Program among clinicians. In phase 3 (intervention development), we developed the START Diabetes Prevention Clinical Pathway as a systematic change package to address barriers and facilitators identified in phases 1 and 2, performance measures and a toolkit of resources to support the intervention components. CONCLUSIONS The TRiP framework supported the identification of evidence-based care practices for pre-diabetes and the development of a well-fitted, actionable intervention and implementation plan designed to increase treatment uptake for pre-diabetes in primary care settings. Our change package can be adapted and used by other health systems or clinics to target prevention of diabetes or other related chronic conditions.
Collapse
Affiliation(s)
- Eva Tseng
- Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Welch Center for Prevention, Epidemiology, & Clinical Research, Johns Hopkins University, Baltimore, MD, USA
| | - Katherine Smith
- Department of Health, Behavior and Society, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Jeanne M Clark
- Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Welch Center for Prevention, Epidemiology, & Clinical Research, Johns Hopkins University, Baltimore, MD, USA
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Jodi B Segal
- Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Welch Center for Prevention, Epidemiology, & Clinical Research, Johns Hopkins University, Baltimore, MD, USA
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Health Policy and Management, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
- Center for Drug Safety and Effectiveness, Johns Hopkins University, Baltimore, MD, USA
| | - Jill A Marsteller
- Welch Center for Prevention, Epidemiology, & Clinical Research, Johns Hopkins University, Baltimore, MD, USA
- Health Policy and Management, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Nisa M Maruthur
- Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Welch Center for Prevention, Epidemiology, & Clinical Research, Johns Hopkins University, Baltimore, MD, USA
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
| |
Collapse
|
2
|
Griauzde DH, Turner CD, Othman A, Oshman L, Gabison J, Arizaca-Dileo PK, Walford E, Henderson J, Beckius D, Lee JM, Carter EW, Dallas C, Herrera-Theut K, Richardson CR, Kullgren JT, Piatt G, Heisler M, Kraftson A. A Primary Care-Based Weight Navigation Program. JAMA Netw Open 2024; 7:e2412192. [PMID: 38771575 PMCID: PMC11109771 DOI: 10.1001/jamanetworkopen.2024.12192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 03/18/2024] [Indexed: 05/22/2024] Open
Abstract
Importance Evidence-based weight management treatments (WMTs) are underused; strategies are needed to increase WMT use and patients' weight loss. Objective To evaluate the association of a primary care-based weight navigation program (WNP) with WMT use and weight loss. Design, Setting, and Participants This cohort study comprised a retrospective evaluation of a quality improvement program conducted from October 1, 2020, to September 30, 2021. Data analysis was performed from August 2, 2022, to March 7, 2024. Adults with obesity and 1 or more weight-related condition from intervention and control sites in a large academic health system in the Midwestern US were propensity matched on sociodemographic and clinical factors. Exposure WNP, in which American Board of Obesity Medicine-certified primary care physicians offered weight-focused visits and guided patients' selection of preference-sensitive WMTs. Main Outcomes and Measures Primary outcomes were feasibility measures, including rates of referral to and engagement in the WNP. Secondary outcomes were mean weight loss, percentage of patients achieving 5% or more and 10% or more weight loss, referral to WMTs, and number of antiobesity medication prescriptions at 12 months. Results Of 264 patients, 181 (68.6%) were female and mean (SD) age was 49.5 (13.0) years; there were no significant differences in demographic characteristics between WNP patients (n = 132) and matched controls (n = 132). Of 1159 WNP-eligible patients, 219 (18.9%) were referred to the WNP and 132 (11.4%) completed a visit. In a difference-in-differences analysis, WNP patients lost 4.9 kg more than matched controls (95% CI, 2.11-7.76; P < .001), had 4.4% greater weight loss (95% CI, 2.2%-6.4%; P < .001), and were more likely to achieve 5% or more weight loss (odds ratio [OR], 2.90; 95% CI, 1.54-5.58); average marginal effects, 21.2%; 95% CI, 8.8%-33.6%) and 10% or more weight loss (OR, 7.19; 95% CI, 2.55-25.9; average marginal effects, 17.4%; 95% CI, 8.7%-26.2%). Patients in the WNP group were referred at higher rates to WMTs, including bariatric surgery (18.9% vs 9.1%; P = .02), a low-calorie meal replacement program (16.7% vs 3.8%; P < .001), and a Mediterranean-style diet and activity program (10.6% vs 1.5%; P = .002). There were no between-group differences in antiobesity medication prescribing. Conclusions and Relevance The findings of this cohort study suggest that WNP is feasible and associated with greater WMT use and weight loss than matched controls. The WNP warrants evaluation in a large-scale trial.
Collapse
Affiliation(s)
- Dina H. Griauzde
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
- VA Ann Arbor Healthcare System, Ann Arbor, Michigan
- University of Michigan Institute for Healthcare Policy and Innovation, Ann Arbor
| | - Cassie D. Turner
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
- VA Ann Arbor Healthcare System, Ann Arbor, Michigan
- Department of Learning Health Sciences, University of Michigan Medical School, Ann Arbor
| | - Amal Othman
- Department of Family Medicine, University of Michigan Medical School, Ann Arbor
| | - Lauren Oshman
- University of Michigan Institute for Healthcare Policy and Innovation, Ann Arbor
- Department of Family Medicine, University of Michigan Medical School, Ann Arbor
| | - Jonathan Gabison
- Department of Family Medicine, University of Michigan Medical School, Ann Arbor
| | | | - Eric Walford
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
| | - James Henderson
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
- University of Michigan Institute for Healthcare Policy and Innovation, Ann Arbor
| | - Deena Beckius
- University of Michigan Elizabeth Weiser Caswell Diabetes Institute, Ann Arbor
| | - Joyce M. Lee
- VA Ann Arbor Healthcare System, Ann Arbor, Michigan
- Department of Pediatrics, University of Michigan Medical School, Ann Arbor
| | - Eli W. Carter
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
| | - Chris Dallas
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
- University of Michigan Elizabeth Weiser Caswell Diabetes Institute, Ann Arbor
| | - Kathyrn Herrera-Theut
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
- Department of Pediatrics, University of Michigan Medical School, Ann Arbor
| | - Caroline R. Richardson
- Department of Family Medicine, The Warren Alpert Medical School of Brown University and Care New England, Providence, Rhode Island
| | - Jeffrey T. Kullgren
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
- VA Ann Arbor Healthcare System, Ann Arbor, Michigan
- University of Michigan Institute for Healthcare Policy and Innovation, Ann Arbor
- Department of Health Management and Policy, University of Michigan School of Public Health, Ann Arbor
| | - Gretchen Piatt
- Department of Learning Health Sciences, University of Michigan Medical School, Ann Arbor
- Department of Health Behavior and Health Education, University of Michigan School of Public Health, Ann Arbor
| | - Michele Heisler
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
- VA Ann Arbor Healthcare System, Ann Arbor, Michigan
- University of Michigan Institute for Healthcare Policy and Innovation, Ann Arbor
| | - Andrew Kraftson
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
| |
Collapse
|
3
|
Formagini T, Brooks JV, Roberts A, Bullard KM, Zhang Y, Saelee R, O'Brien MJ. Prediabetes prevalence and awareness by race, ethnicity, and educational attainment among U.S. adults. Front Public Health 2023; 11:1277657. [PMID: 38164446 PMCID: PMC10758124 DOI: 10.3389/fpubh.2023.1277657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 11/20/2023] [Indexed: 01/03/2024] Open
Abstract
Introduction Racial and ethnic minority groups and individuals with limited educational attainment experience a disproportionate burden of diabetes. Prediabetes represents a high-risk state for developing type 2 diabetes, but most adults with prediabetes are unaware of having the condition. Uncovering whether racial, ethnic, or educational disparities also occur in the prediabetes stage could help inform strategies to support health equity in preventing type 2 diabetes and its complications. We examined the prevalence of prediabetes and prediabetes awareness, with corresponding prevalence ratios according to race, ethnicity, and educational attainment. Methods This study was a pooled cross-sectional analysis of the National Health and Nutrition Examination Survey data from 2011 to March 2020. The final sample comprised 10,262 U.S. adults who self-reported being Asian, Black, Hispanic, or White. Prediabetes was defined using hemoglobin A1c and fasting plasma glucose values. Those with prediabetes were classified as "aware" or "unaware" based on survey responses. We calculated prevalence ratios (PR) to assess the relationship between race, ethnicity, and educational attainment with prediabetes and prediabetes awareness, controlling for sociodemographic, health and healthcare-related, and clinical characteristics. Results In fully adjusted logistic regression models, Asian, Black, and Hispanic adults had a statistically significant higher risk of prediabetes than White adults (PR:1.26 [1.18,1.35], PR:1.17 [1.08,1.25], and PR:1.10 [1.02,1.19], respectively). Adults completing less than high school and high school had a significantly higher risk of prediabetes compared to those with a college degree (PR:1.14 [1.02,1.26] and PR:1.12 [1.01,1.23], respectively). We also found that Black and Hispanic adults had higher rates of prediabetes awareness in the fully adjusted model than White adults (PR:1.27 [1.07,1.50] and PR:1.33 [1.02,1.72], respectively). The rates of prediabetes awareness were consistently lower among those with less than a high school education relative to individuals who completed college (fully-adjusted model PR:0.66 [0.47,0.92]). Discussion Disparities in prediabetes among racial and ethnic minority groups and adults with low educational attainment suggest challenges and opportunities for promoting health equity in high-risk groups and expanding awareness of prediabetes in the United States.
Collapse
Affiliation(s)
- Taynara Formagini
- Department of Family Medicine, University of California San Diego, San Diego, CA, United States
- Department of Population Health, University of Kansas School of Medicine, Kansas City, KS, United States
| | - Joanna Veazey Brooks
- Department of Population Health, University of Kansas School of Medicine, Kansas City, KS, United States
- University of Kansas Cancer Center, Kansas City, KS, United States
- Division of Palliative Medicine, University of Kansas School of Medicine, Kansas City, KS, United States
| | - Andrew Roberts
- Department of Population Health, University of Kansas School of Medicine, Kansas City, KS, United States
- Aetion Inc., New York, NY, United States
| | - Kai McKeever Bullard
- Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, CDC, Atlanta, GA, United States
| | - Yan Zhang
- Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, CDC, Atlanta, GA, United States
| | - Ryan Saelee
- Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, CDC, Atlanta, GA, United States
| | - Matthew James O'Brien
- Department of Medicine, Division of General Internal Medicine and Geriatrics, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
| |
Collapse
|
4
|
Harcke K, Graue M, Skinner TC, Olsson CB, Saleh-Stattin N. Making prediabetes visible in primary health care: a qualitative study of health care professionals' perspectives. BMC PRIMARY CARE 2023; 24:266. [PMID: 38087202 PMCID: PMC10717089 DOI: 10.1186/s12875-023-02230-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 11/30/2023] [Indexed: 12/18/2023]
Abstract
BACKGROUND People with prediabetes are at high risk of developing type 2 diabetes and its complications, such as cardiovascular diseases and premature mortality. Primary prevention and health maintenance are therefore imperative. Evidence has shown that prediabetes can be prevented or delayed with behavioural change, mainly in eating habits and physical activity. Interventions that use a person-centered approach can lead to improvements in self-management, quality of life, and health outcomes. Nevertheless, there is a need for further research that engages healthcare professionals and people with prediabetes in constructing and implementing preventive programs. The purpose of this study is to explore and describe how healthcare professionals perceive prediabetes, the current challenges in its detection and treatment, and what is needed to improve quality of care. METHODS This qualitative study was conducted in Region Stockholm. A total of 26 primary health care professionals participated in individual interviews: 15 diabetes nurses and/or district nurses, five general practitioners, five dietitians, and one physiotherapist. Interview transcripts were analyzed with qualitative content analysis. RESULTS The analysis revealed two main themes that emphasize the need to make prediabetes more visible in primary health care. Despite the healthcare professionals' engagement and their motivation to improve prediabetes care, ad hoc practices and the absence of clear screening guidelines and referral pathways made it harder to focus on primary prevention. Supporting professionals in implementing structured care for people with prediabetes might encourage more efficient interprofessional collaboration and contribute to better strategies for promoting behavioural change. CONCLUSIONS Establishing prediabetes care guidelines, supporting health care professionals´ knowledge and skills in prediabetes care, and implementing interprofessional referral pathways are some steps to enhance prediabetes detection and care precedence in primary health care. These steps could lead to more preventive care and ensure patient safety and health care equity.
Collapse
Affiliation(s)
- Katri Harcke
- Department of Neurobiology, Care Sciences and Society, Division of Family Medicine and Primary Care, Karolinska Institutet, Huddinge, Region Stockholm, Sweden.
- Academic Primary Health Care Centre, Solnavägen 1E Torsplan, plan 7, Stockholm, 11365, Region Stockholm, Sweden.
| | - Marit Graue
- Department of Health and Caring Sciences, Western Norway University of Applied Sciences, Bergen, Norway
| | - Timothy Charles Skinner
- Institute of Psychology, University of Copenhagen, Copenhagen, Denmark
- La Trobe Rural Health School, La Trobe University, Bendigo, Australia
- Australian Centre for Behavioural Research in Diabetes, Melbourne, Australia
| | - Christina B Olsson
- Academic Primary Health Care Centre, Solnavägen 1E Torsplan, plan 7, Stockholm, 11365, Region Stockholm, Sweden
- Department of Neurobiology, Care Sciences and Society, Division of Physiotherapy, Karolinska Institutet, Huddinge, Region Stockholm, Sweden
| | - Nouha Saleh-Stattin
- Department of Neurobiology, Care Sciences and Society, Division of Family Medicine and Primary Care, Karolinska Institutet, Huddinge, Region Stockholm, Sweden
- Academic Primary Health Care Centre, Solnavägen 1E Torsplan, plan 7, Stockholm, 11365, Region Stockholm, Sweden
| |
Collapse
|
5
|
Smith MA, Nigro S. Applying Design-Thinking Principles to Practice-Based Pharmacy Research. Ann Pharmacother 2023; 57:1111-1116. [PMID: 36602037 DOI: 10.1177/10600280221147014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
Design thinking is an approach to problem solving that focuses on a solution to a problem. This systematic approach can be applied to practice-based research or implementation projects in your practice setting. It may be useful for starting new projects as well as revisiting past projects that may not have yielded meaningful results. The design-thinking process begins with identifying a problem or knowledge gap and then the steps include: (1) understanding the problem, (2) observing the problem, (3) defining the problem, (4) brainstorming possible solutions, (5) prototyping the best solution, and (6) testing the solution.
Collapse
Affiliation(s)
- Marie A Smith
- Pharmacy Practice, UConn School of Pharmacy, Storrs, CT, USA
| | | |
Collapse
|
6
|
Weiner A, Zhang M, Ren S, Tchang B, Gandica R, Murillo J. Progression from prediabetes to type 2 diabetes mellitus in adolescents: a real world experience. FRONTIERS IN CLINICAL DIABETES AND HEALTHCARE 2023; 4:1181729. [PMID: 37228785 PMCID: PMC10204924 DOI: 10.3389/fcdhc.2023.1181729] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 04/24/2023] [Indexed: 05/27/2023]
Abstract
Background Obesity in pediatric patients is strongly associated with increased vascular and metabolic risk. Prediabetes is present in up to 1 in 5 adolescents, aged 12-18 years-old, though is thought to remit spontaneously in a significant portion. Pediatric patients with type 2 diabetes mellitus (T2D) have a more rapid decline of beta-cell function and progression to treatment failure than adult T2D patients. Thus, there is a strong interest in better understanding the natural history of prediabetes in these youth. We aimed to evaluate the real-world rate of progression of prediabetes to T2D in adolescent patients. Methods This is a retrospective study of 9,275 adolescent subjects aged 12-21 years-old with at least 3 years of de-identified commercial claims data and a new diagnosis of prediabetes during the observation period. Enrollees with a T2D diagnosis and/or diabetes medication use in the 1 year prior to prediabetes diagnosis or a T2D diagnosis in the 1 month following prediabetes diagnosis were excluded. Enrollees with diagnoses of type 1 diabetes (T1D) or polycystic ovarian syndrome over the 3 years were also excluded. Progression to T2D was defined by claims data of two T2D diagnoses at least 7 days apart, HbA1c ≥ 6.5%, and/or prescription of insulin without known T1D. Enrollees were followed for 2 years after prediabetes diagnosis. Results Overall, 232 subjects (2.5%) progressed from prediabetes to T2D. There were no differences found in T2D progression based on sex or age. Progression to T2D occurred at a median of 302 days after prediabetes diagnosis (IQR 123 to 518 days). This study was limited by the lack of laboratory/anthropometric data in administrative claims, as well as the exclusion of 23,825 enrollees for lack of continuous commercial claims data over 3 years. Conclusion In the largest sample to date on adolescent prediabetes, we found a 2.5% progression of prediabetes to T2D over a median duration of about one year.
Collapse
Affiliation(s)
- Alyson Weiner
- Comprehensive Weight Control Center, Division of Endocrinology, Diabetes, and Metabolism Weill Cornell Medicine, New York, NY, United States
| | - Meng Zhang
- Optum Labs, Eden Prairie, MN, United States
| | - Sheng Ren
- Optum Labs, Eden Prairie, MN, United States
| | - Beverly Tchang
- Comprehensive Weight Control Center, Division of Endocrinology, Diabetes, and Metabolism Weill Cornell Medicine, New York, NY, United States
| | - Rachelle Gandica
- Division of Pediatric Endocrinology, Diabetes, and Metabolism Columbia University Irving Medical Center, New York, NY, United States
| | | |
Collapse
|
7
|
Walsh K. Equity Rx: Boston Medical Center's Work to Accelerate Racial Health Justice. Front Health Serv Manage 2022; 39:4-16. [PMID: 36413471 DOI: 10.1097/hap.0000000000000158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
In November 2021, after more than a year of investigating the racial health disparities across its organization, Boston Medical Center launched the Health Equity Accelerator, a system-wide approach to holistically address the root causes of health inequities among people of different races and ethnicities and speed improvements in health outcomes. This article discusses lessons learned during the institution's process of discovery, shares examples of the work to dismantle a structural narrative that impedes health justice, and outlines interventions that can be applied to other healthcare systems across the United States.
Collapse
Affiliation(s)
- Kate Walsh
- Kate Walsh is president and CEO of Boston Medical Center Health System in Boston, Massachusetts
| |
Collapse
|