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Gulanski BI, Goulet JL, Radhakrishnan K, Ko J, Li Y, Rajeevan N, Lee KM, Heberer K, Lynch JA, Streja E, Mutalik P, Cheung KH, Concato J, Shih MC, Lee JS, Aslan M. Metformin prescription for U.S. veterans with prediabetes, 2010-2019. J Investig Med 2024; 72:139-150. [PMID: 37668313 DOI: 10.1177/10815589231201141] [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: 09/06/2023]
Abstract
Affecting an estimated 88 million Americans, prediabetes increases the risk for developing type 2 diabetes mellitus (T2DM), and independently, cardiovascular disease, retinopathy, nephropathy, and neuropathy. Nevertheless, little is known about the use of metformin for diabetes prevention among patients in the Veterans Health Administration, the largest integrated healthcare system in the U.S. This is a retrospective observational cohort study of the proportion of Veterans with incident prediabetes who were prescribed metformin at the Veterans Health Administration from October 2010 to September 2019. Among 1,059,605 Veterans with incident prediabetes, 12,009 (1.1%) were prescribed metformin during an average 3.4 years of observation after diagnosis. Metformin prescribing was marginally higher (1.6%) among those with body mass index (BMI) ≥35 kg/m2, age <60 years, HbA1c≥6.0%, or those with a history of gestational diabetes, all subgroups at a higher risk for progression to T2DM. In a multivariable model, metformin was more likely to be prescribed for those with BMI ≥35 kg/m2 incidence rate ratio [IRR] 2.6 [95% confidence intervals (CI): 2.1-3.3], female sex IRR, 2.4 [95% CI: 1.8-3.3], HbA1c≥6% IRR, 1.93 [95% CI: 1.5-2.4], age <60 years IRR, 1.7 [95% CI: 1.3-2.3], hypertriglyceridemia IRR, 1.5 [95% CI: 1.2-1.9], hypertension IRR, 1.5 [95% CI: 1.1-2.1], Major Depressive Disorder IRR, 1.5 [95% CI: 1.1-2.0], or schizophrenia IRR, 2.1 [95% CI: 1.2-3.8]. Over 20% of Veterans with prediabetes attended a comprehensive structured lifestyle modification clinic or program. Among Veterans with prediabetes, metformin was prescribed to 1.1% overall, a proportion that marginally increased to 1.6% in the subset of individuals at highest risk for progression to T2DM.
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Affiliation(s)
- Barbara I Gulanski
- Department of Medicine, Endocrinology, VA Connecticut Healthcare System, West Haven, CT, USA
- Department of Medicine, Endocrinology, Yale University School of Medicine, New Haven, CT, USA
| | - Joseph L Goulet
- Section of Biomedical Informatics and Data Science, Yale University School of Medicine, New Haven, CT, USA
- Pain, Research, Informatics, Multi-morbidities and Education Center (PRIME), West Haven, CT, USA
| | - Krishnan Radhakrishnan
- National Mental Health and Substance Use Policy Laboratory, Substance Abuse and Mental Health Services Administration, Rockville, MD, USA
| | - John Ko
- VA Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT, USA
| | - Yuli Li
- Section of Biomedical Informatics and Data Science, Yale University School of Medicine, New Haven, CT, USA
- VA Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT, USA
| | - Nallakkandi Rajeevan
- Section of Biomedical Informatics and Data Science, Yale University School of Medicine, New Haven, CT, USA
- VA Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT, USA
| | - Kyung Min Lee
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
| | - Kent Heberer
- VA Palo Alto Cooperative Studies Program Coordinating Center, VA Palo Alto Heath Care System, CA, USA
- Division of Endocrinology, Gerontology, and Metabolism, Department of Medicine, Endocrinology, Stanford University School of Medicine, Stanford, CA, USA
| | - Julie A Lynch
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Internal Medicine, Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Elani Streja
- Department of Medicine, Nephrology, Hypertension and Transplant, University of California-Irvine School of Medicine, Long Beach, CA, USA
| | - Pradeep Mutalik
- Section of Biomedical Informatics and Data Science, Yale University School of Medicine, New Haven, CT, USA
- VA Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT, USA
| | - Kei-Hoi Cheung
- Section of Biomedical Informatics and Data Science, Yale University School of Medicine, New Haven, CT, USA
- VA Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT, USA
- Department of Emergency Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - John Concato
- Department of Medicine, Yale University School of Medicine, New Haven, CT, USA
- Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Mei-Chiung Shih
- VA Palo Alto Cooperative Studies Program Coordinating Center, VA Palo Alto Heath Care System, CA, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
| | - Jennifer S Lee
- VA Palo Alto Cooperative Studies Program Coordinating Center, VA Palo Alto Heath Care System, CA, USA
- Division of Endocrinology, Gerontology, and Metabolism, Department of Medicine, Endocrinology, Stanford University School of Medicine, Stanford, CA, USA
| | - Mihaela Aslan
- VA Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT, USA
- Department of Medicine, Yale University School of Medicine, New Haven, CT, USA
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Arias-Fernández M, Fresneda S, Abbate M, Torres-Carballo M, Huguet-Torres A, Sánchez-Rodríguez C, Bennasar-Veny M, Yañez AM, Busquets-Cortés C. Fatty Liver Disease in Patients with Prediabetes and Overweight or Obesity. Metabolites 2023; 13:metabo13040531. [PMID: 37110189 PMCID: PMC10146012 DOI: 10.3390/metabo13040531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 03/24/2023] [Accepted: 04/04/2023] [Indexed: 04/29/2023] Open
Abstract
Non-alcoholic fatty liver disease (NAFLD) is a global health problem associated with liver morbimortality, obesity, and type 2 diabetes mellitus. This study aimed to analyze the prevalence of NAFLD (defined as a fatty liver index [FLI] ≥ 60) and its association with other cardiovascular risk (CVR) factors in patients with prediabetes and overweight/obesity. The present cross-sectional analysis uses baseline data from an ongoing randomized clinical trial. Sociodemographic and anthropometric characteristics, CVR (assessed by the REGICOR-Framingham risk equation), metabolic syndrome (MetS), and FLI-defined NAFLD (cut-off value of ≥60) were assessed. The prevalence of FLI-defined NAFLD was 78% overall. Men exhibited a worse cardiometabolic profile as compared to women, specifically, with higher values of systolic blood pressure (137.02 ± 13.48 vs. 131.22 ± 14.77 mmHg), diastolic blood pressure (85.33 ± 9.27 vs. 82.3 ± 9.12 mmHg), aspartate aminotransferase (AST) (27.23 ± 12.15 vs. 21.23 ± 10.05 IU/L), alanine aminotransferase (ALT) (34.03 ± 23.31 vs. 21.73 ± 10.80 IU/L), and higher CVR (5.58 ± 3.16 vs. 3.60 ± 1.68). FLI-defined NAFLD was associated with elevated AST, ALT, and the presence of MetS (73.7%) and CVR for the whole sample. People with prediabetes present a high burden of comorbidities related to CVR, despite clinical follow-up, and it is recommended to actively begin working with them to reduce their risks.
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Affiliation(s)
- María Arias-Fernández
- Department of Nursing and Physiotherapy, University of Balearic Islands, 07122 Palma, Spain
- Research Group on Global Health, University of Balearic Islands, 07122 Palma, Spain
- Research Group on Global Health and Lifestyle, Health Research Institute of the Balearic Islands (IdISBa), 07120 Palma, Spain
| | - Sergio Fresneda
- Department of Nursing and Physiotherapy, University of Balearic Islands, 07122 Palma, Spain
- Research Group on Global Health, University of Balearic Islands, 07122 Palma, Spain
- Research Group on Global Health and Lifestyle, Health Research Institute of the Balearic Islands (IdISBa), 07120 Palma, Spain
| | - Manuela Abbate
- Department of Nursing and Physiotherapy, University of Balearic Islands, 07122 Palma, Spain
- Research Group on Global Health, University of Balearic Islands, 07122 Palma, Spain
- Research Group on Global Health and Lifestyle, Health Research Institute of the Balearic Islands (IdISBa), 07120 Palma, Spain
- ADEMA-SALUD Group of IUNICS, University of Balearic Islands, 07009 Palma, Spain
| | - Marina Torres-Carballo
- Department of Nursing and Physiotherapy, University of Balearic Islands, 07122 Palma, Spain
- Research Group on Global Health, University of Balearic Islands, 07122 Palma, Spain
- Primary Care Research Unit of Mallorca, Public Health Service of the Balearic Islands (Ibsalut), 07003 Palma, Spain
| | - Aina Huguet-Torres
- Department of Nursing and Physiotherapy, University of Balearic Islands, 07122 Palma, Spain
- Research Group on Global Health, University of Balearic Islands, 07122 Palma, Spain
| | - Cristian Sánchez-Rodríguez
- Research Group on Global Health, University of Balearic Islands, 07122 Palma, Spain
- Sant Joan de Déu Hospital, 07007 Palma, Spain
| | - Miquel Bennasar-Veny
- Department of Nursing and Physiotherapy, University of Balearic Islands, 07122 Palma, Spain
- Research Group on Global Health, University of Balearic Islands, 07122 Palma, Spain
- Research Group on Global Health and Lifestyle, Health Research Institute of the Balearic Islands (IdISBa), 07120 Palma, Spain
- CIBER de Epidemiología y Salud Pública (CIBERESP), 28029 Madrid, Spain
| | - Aina M Yañez
- Department of Nursing and Physiotherapy, University of Balearic Islands, 07122 Palma, Spain
- Research Group on Global Health, University of Balearic Islands, 07122 Palma, Spain
- Research Group on Global Health and Lifestyle, Health Research Institute of the Balearic Islands (IdISBa), 07120 Palma, Spain
| | - Carla Busquets-Cortés
- Research Group on Global Health, University of Balearic Islands, 07122 Palma, Spain
- ADEMA-SALUD Group of IUNICS, University of Balearic Islands, 07009 Palma, Spain
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3
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Harcke K, Graue M, Skinner TC, Olsson CB, Stattin NS. Prediabetes screening, treatment, and follow‐up in primary health care: a cross‐sectional survey. PRACTICAL DIABETES 2022. [DOI: 10.1002/pdi.2425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Affiliation(s)
- Katri Harcke
- Department of Neurobiology, Care Sciences and Society, Division of Family Medicine and Primary Care, Karolinska Institutet Huddinge Sweden
- Academic Primary Health Care Centre 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 Stockholm Sweden
- Department of Neurobiology, Care Sciences and Society, Division of Physiotherapy, Karolinska Institutet Huddinge Sweden
| | - Nouha Saleh Stattin
- Department of Neurobiology, Care Sciences and Society, Division of Family Medicine and Primary Care, Karolinska Institutet Huddinge Sweden
- Academic Primary Health Care Centre Stockholm Sweden
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O'Brien MJ, Vargas MC, Lopez A, Feliciano Y, Gregory DL, Carcamo P, Mohr L, Mohanty N, Padilla R, Ackermann RT, Persell SD, Feinglass J. Development of a novel clinical decision support tool for diabetes prevention and feasibility of its implementation in primary care. Prev Med Rep 2022; 29:101979. [PMID: 36161117 PMCID: PMC9501986 DOI: 10.1016/j.pmedr.2022.101979] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 08/31/2022] [Accepted: 09/02/2022] [Indexed: 11/12/2022] Open
Abstract
Clinical decision support may represent a strategy for promoting diabetes prevention in primary care. We developed a novel clinical decision support tool with input from primary care providers. This clinician-facing tool was associated with improvements in processes of prediabetes care. Exploratory analyses found small, but nonsignificant weight loss associated with its use.
Prediabetes impacts 88 million U.S. adults, yet uptake of evidence-based treatment with intensive lifestyle interventions and metformin remains exceedingly low. After incorporating feedback from 15 primary care providers collected during semi-structured interviews, we developed a novel Prediabetes Clinical Decision Support (PreDM CDS) from August 2019 to February 2020. This tool included order options enabling prediabetes management in a single location within the electronic health record. We conducted a retrospective observational study examining the feasibility of implementing this tool at Erie Family Health Centers, a large community health center, examining its use and related outcomes among patients for whom it was used vs not. Overall, 7,424 eligible patients were seen during the implementation period (February 2020 to August 2021), and the PreDM CDS was used for 108 (1.5 %). Using the PreDM CDS was associated with higher rates of hemoglobin A1c orders (70.4 % vs 22.2 %; p < 0.001), lifestyle counseling (38.0 % vs 7.8 %; p < 0.001), and metformin prescription orders (5.6 % vs 2.6 %; p = 0.06). Exploratory analyses revealed small, nonsignificant weight loss among patients for whom the PreDM CDS was used. This study demonstrates the feasibility of developing and implementing the PreDM CDS in primary care. Its low use was likely related to not imposing an interruptive ‘pop-up’ alert, as well as major changes in workflows and clinical priorities during the Covid-19 pandemic. Use of the tool was associated with improved process outcomes. Future efforts with the PreDM CDS should follow standard CDS implementation processes that were not possible due to the Covid-19 pandemic.
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Affiliation(s)
- Matthew J O'Brien
- Division of General Internal Medicine and Geriatrics, Department of Medicine, Northwestern University Feinberg School of Medicine. 750 N. Lakeshore Drive, 10 Floor, Chicago, IL 60611, United States.,Institute of Public Health and Medicine, Northwestern University Feinberg School of Medicine. 750 N. Lakeshore Drive, 6 Floor, Chicago, IL 60611, United States.,Department of Preventive Medicine, Northwestern University Feinberg School of Medicine. 680 N. Lakeshore Drive, 14 Floor, Chicago, IL 60611, United States
| | - Maria C Vargas
- Division of General Internal Medicine and Geriatrics, Department of Medicine, Northwestern University Feinberg School of Medicine. 750 N. Lakeshore Drive, 10 Floor, Chicago, IL 60611, United States.,Institute of Public Health and Medicine, Northwestern University Feinberg School of Medicine. 750 N. Lakeshore Drive, 6 Floor, Chicago, IL 60611, United States
| | - Azucena Lopez
- Division of General Internal Medicine and Geriatrics, Department of Medicine, Northwestern University Feinberg School of Medicine. 750 N. Lakeshore Drive, 10 Floor, Chicago, IL 60611, United States.,Institute of Public Health and Medicine, Northwestern University Feinberg School of Medicine. 750 N. Lakeshore Drive, 6 Floor, Chicago, IL 60611, United States
| | - Yury Feliciano
- Division of General Internal Medicine and Geriatrics, Department of Medicine, Northwestern University Feinberg School of Medicine. 750 N. Lakeshore Drive, 10 Floor, Chicago, IL 60611, United States.,Institute of Public Health and Medicine, Northwestern University Feinberg School of Medicine. 750 N. Lakeshore Drive, 6 Floor, Chicago, IL 60611, United States
| | - Dyanna L Gregory
- Division of General Internal Medicine and Geriatrics, Department of Medicine, Northwestern University Feinberg School of Medicine. 750 N. Lakeshore Drive, 10 Floor, Chicago, IL 60611, United States
| | - Paula Carcamo
- Erie Family Health Centers. 1701 W. Superior Street, Chicago, IL 60622, United States
| | - Loretta Mohr
- Erie Family Health Centers. 1701 W. Superior Street, Chicago, IL 60622, United States
| | - Nivedita Mohanty
- Erie Family Health Centers. 1701 W. Superior Street, Chicago, IL 60622, United States.,AllianceChicago. 225 W. Illinois Street, 5 Floor, Chicago, IL 60654, United States
| | - Roxane Padilla
- AllianceChicago. 225 W. Illinois Street, 5 Floor, Chicago, IL 60654, United States
| | - Ronald T Ackermann
- Division of General Internal Medicine and Geriatrics, Department of Medicine, Northwestern University Feinberg School of Medicine. 750 N. Lakeshore Drive, 10 Floor, Chicago, IL 60611, United States.,Institute of Public Health and Medicine, Northwestern University Feinberg School of Medicine. 750 N. Lakeshore Drive, 6 Floor, Chicago, IL 60611, United States
| | - Stephen D Persell
- Division of General Internal Medicine and Geriatrics, Department of Medicine, Northwestern University Feinberg School of Medicine. 750 N. Lakeshore Drive, 10 Floor, Chicago, IL 60611, United States.,Institute of Public Health and Medicine, Northwestern University Feinberg School of Medicine. 750 N. Lakeshore Drive, 6 Floor, Chicago, IL 60611, United States
| | - Joseph Feinglass
- Division of General Internal Medicine and Geriatrics, Department of Medicine, Northwestern University Feinberg School of Medicine. 750 N. Lakeshore Drive, 10 Floor, Chicago, IL 60611, United States.,Institute of Public Health and Medicine, Northwestern University Feinberg School of Medicine. 750 N. Lakeshore Drive, 6 Floor, Chicago, IL 60611, United States
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5
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Comparison of National Data Sources to Assess Preventive Care in the US Population. J Gen Intern Med 2022; 37:318-326. [PMID: 33791937 PMCID: PMC8012018 DOI: 10.1007/s11606-021-06707-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Accepted: 03/09/2021] [Indexed: 11/30/2022]
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Desai J, Saman D, Sperl-Hillen JM, Pratt R, Dehmer SP, Allen C, Ohnsorg K, Wuorio A, Appana D, Hitz P, Land A, Sharma R, Wilkerson L, Crain AL, Crabtree BF, Bianco J, O'Connor PJ. Implementing a prediabetes clinical decision support system in a large primary care system: Design, methods, and pre-implementation results. Contemp Clin Trials 2022; 114:106686. [DOI: 10.1016/j.cct.2022.106686] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Revised: 01/14/2022] [Accepted: 01/18/2022] [Indexed: 11/30/2022]
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Davis-Ajami ML, Lu ZK, Wu J. Delivery of healthcare provider's lifestyle advice and lifestyle behavioural change in adults who were overweight or obese in pre-diabetes management in the USA: NHANES (2013-2018). Fam Med Community Health 2021; 9:fmch-2021-001139. [PMID: 34789536 PMCID: PMC8601075 DOI: 10.1136/fmch-2021-001139] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
OBJECTIVE The purpose of this study is to examine the association between delivery of healthcare provider's advice about lifestyle management and lifestyle behavioural change in pre-diabetes management in adults who were overweight or obese. DESIGN This cross-sectional study included adults with body mass index (BMI) ≥25 kg/m2 and reporting pre-diabetes in USA. Outcomes included the prevalence of receiving provider's advice on lifestyle management and patterns of practicing lifestyle change. The association between delivery of provider's advice and lifestyle-related behavioural change in pre-diabetes management was examined. SETTING US Continuous National Health and Nutrition Examination Survey (2013-2018). PARTICIPANTS A total of 1039 adults with BMI ≥25 kg/m2 reported pre-diabetes. RESULTS Of eligible adults with pre-diabetes, 76.8% received provider's advice about lifestyle change. The advice group showed higher proportions of ongoing lifestyle change than no advice group, including weight reduction/control (80.1% vs 70.9%, p=0.018), exercise (70.9% vs 60.9%, p=0.013) and diet modifications (83.8% vs 61.8%, p<0.001). After adjustment, those receiving provider's advice were more likely to increase exercise (OR 1.63, 95% CI 1.12 to 2.38) and modify diet (OR 3.0, 95% CI 1.82 to 4.96). CONCLUSION Over 75% of US adults who were overweight or obese and reported pre-diabetes received healthcare provider's advice about reducing the risk of diabetes through lifestyle change. Provider's advice increased the likelihood of lifestyle-related behavioural change to exercise and diet.
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Affiliation(s)
- Mary Lynn Davis-Ajami
- Department of Science of Nursing Care, Indiana University School of Nursing, Indianapolis, Indiana, USA
| | - Zhiqiang Kevin Lu
- Department of Clinical Pharmacy and Outcomes Sciences, University of South Carolina College of Pharmacy, Columbia, South Carolina, USA
| | - Jun Wu
- Department of Pharmaceutical and Administrative Sciences, Presbyterian College School of Pharmacy, Clinton, South Carolina, USA
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Speaker SL, Rastogi R, Sussman TA, Hu B, Misra-Hebert AD, Rothberg MB. Treatment of Patients with Prediabetes in a Primary Care Setting 2011-2018: an Observational Study. J Gen Intern Med 2021; 36:923-929. [PMID: 33449282 PMCID: PMC8041989 DOI: 10.1007/s11606-020-06354-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/08/2020] [Accepted: 11/18/2020] [Indexed: 01/21/2023]
Abstract
BACKGROUND Over one third of American adults are at high risk for developing diabetes, which can be delayed or prevented using interventions such as medical nutrition therapy (MNT) or metformin. Physicians' self-reported rates of prediabetes treatment are improving, but patterns of actual referral, prescription, and MNT visits are unknown. OBJECTIVE To characterize treatment of prediabetes in primary care. DESIGN We conducted a retrospective cohort study using electronic health record data. We described patterns of treatment and used multivariable logistic regression to evaluate the association of patient factors and PCP-specific treatment rate with patient treatment. PATIENTS We included overweight or obese outpatients who had a first prediabetes-range hemoglobin A1c (HbA1c) during 2011-2018 and had primary care provider (PCP) follow-up within a year. MAIN MEASURES We collected patient characteristics and the following treatments: metformin prescription; referral to MNT, diabetes education, endocrinology, or bariatric medicine; and MNT visit. We did not capture within-visit physician counseling. KEY RESULTS Of 16,713 outpatients with prediabetes, 20.4% received treatment, including metformin prescriptions (7.8%) and MNT referrals (11.3%), but only 7.4% of referred patients completed a MNT visit. The strongest predictor of treatment was the patient's PCP's treatment rate. Some PCPs never treated prediabetes, but two treated more than half of their patients; 62% had no patients complete a MNT visit. Being younger or female and having higher body mass index or HbA1c were also positively associated with treatment. Compared to white patients, black patients were more likely to receive MNT referral and less likely to receive metformin. CONCLUSIONS Almost 80% of patients with new prediabetes never received treatment, and those who did receive referrals had very poor visit completion. Treatment rates appear to reflect provider rather than patient preferences.
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Affiliation(s)
- Sidra L Speaker
- Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Radhika Rastogi
- Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | | | - Bo Hu
- Quantitative Health Services, Cleveland Clinic, Cleveland, OH, USA
| | - Anita D Misra-Hebert
- Quantitative Health Services, Cleveland Clinic, Cleveland, OH, USA
- Center for Value-Based Care Research, Cleveland Clinic, Cleveland, OH, USA
| | - Michael B Rothberg
- Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH, USA.
- Center for Value-Based Care Research, Cleveland Clinic, Cleveland, OH, USA.
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