nach oben

Current Diabetes Reports

Erschienen in:

01.11.2018 | Health Care Delivery Systems and Implementation in Diabetes (ME McDonnell and AR Sadhu, Section Editors)

Building Toward a Population-Based Approach to Diabetes Screening and Prevention for US Adults

verfasst von: Michael E. Bowen, Julie A. Schmittdiel, Jeffrey T. Kullgren, Ronald T. Ackermann, Matthew J. O’Brien

Erschienen in: Current Diabetes Reports | Ausgabe 11/2018

Einloggen, um Zugang zu erhalten

Abstract

Purpose of review

Evidence-based treatments for prediabetes can prevent and delay the development of type 2 diabetes in adults. In this review, we propose a framework for population-based diabetes prevention that links screening and prevention activities across key stakeholders. We also discuss gaps in current practice, while highlighting opportunities to improve diabetes screening and prevention efforts population-wide.

Recent findings

Awareness of diabetes risk is low, and many adults with prediabetes are not identified through existing screening efforts. Accumulating evidence and policies support expansion of the Diabetes Prevention Program (DPP) into clinical and community settings. However, the infrastructure to facilitate referrals and promote data exchange among patients, clinical settings, and community-based DPP programs is lacking.

Summary

Development of evidence-driven, scalable processes for assessing diabetes risk, screening eligible adults, and delivering preventive treatments are needed to effectively improve the glycemic health of the US adult population.

Centers for Disease Control and Prevention. National Diabetes Statistics Report: Estimates and Its Burden in the United States. In: The U.S. Department of Health and Human Services, editor. Atlanta, GA. 2017.

Gregg EW, Li Y, Wang J, Burrows NR, Ali MK, Rolka D, et al. Changes in diabetes-related complications in the United States, 1990-2010. N Engl J Med. 2014;370(16):1514–23. https://doi.org/10.1056/NEJMoa1310799.CrossRefPubMed

Holman RR, Paul SK, Bethel MA, Matthews DR, Neil HAW. 10-year follow-up of intensive glucose control in type 2 diabetes. N Engl J Med. 2008;359(15):1577–89. https://doi.org/10.1056/NEJMoa0806470.CrossRef

Gerstein HC, Santaguida P, Raina P, Morrison KM, Balion C, Hunt D, et al. Annual incidence and relative risk of diabetes in people with various categories of dysglycemia: a systematic overview and meta-analysis of prospective studies. Diabetes Res Clin Pract. 2007;78(3):305–12.CrossRef

Nathan DM, Davidson MB, DeFronzo RA, Heine RJ, Henry RR, Pratley R, et al. Impaired fasting glucose and impaired glucose tolerance implications for care. Diabetes Care. 2007;30(3):753–9.CrossRef

•• Menke A, Casagrande S, Geiss L, Cowie CC. Prevalence of and Trends in Diabetes Among Adults in the United States, 1988–2012. JAMA. 2015;314(10):1021–9. https://doi.org/10.1001/jama.2015.10029. This study of NHANES data estimates trends in diabetes prevalence among U.S. adults over more than 2 decades. CrossRefPubMed

Centers for Disease Control and Prevention. Awareness of prediabetes--United States, 2005–2010. MMWR Morb Mortal Wkly Rep. 2013;62(11):209.

Pan XR, Li G, Hu YH, Wang JX, Yang WY, An ZX, et al. Effects of diet and exercise in preventing NIDDM in people with impaired glucose tolerance: the Da Qing IGT and diabetes study. Diabetes Care. 1997;20(4):537–44. https://doi.org/10.2337/diacare.20.4.537.CrossRefPubMed

Tuomilehto J, Lindström J, Eriksson JG, Valle TT, Hämäläinen H, Ilanne-Parikka P, et al. Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. N Engl J Med. 2001;344(18):1343–50. https://doi.org/10.1056/NEJM200105033441801.CrossRefPubMed

10.

•• Knowler W, Barrett-Connor E, Fowler S, Hamman RF, Lachin J, Walker E, et al. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med. 2002;346(6):393–403. https://doi.org/10.1056/NEJMoa012512. This seminal clinical trial tested the comparative efficacy of the Diabetes Prevention Program lifestyle intervention vs. metformin vs. placebo in adults with prediabetes, providing most of the data about diabetes prevention in U.S. adults. CrossRefPubMed

11.

Ramachandran A, Snehalatha C, Mary S, Mukesh B, Bhaskar A, Vijay V. The Indian diabetes prevention programme shows that lifestyle modification and metformin prevent type 2 diabetes in Asian Indian subjects with impaired glucose tolerance (IDPP-1). Diabetologia. 2006;49(2):289–97. https://doi.org/10.1007/s00125-005-0097-z.CrossRefPubMed

12.

Li G, Zhang P, Wang J, Gregg EW, Yang W, Gong Q, et al. The long-term effect of lifestyle interventions to prevent diabetes in the China Da Qing diabetes prevention study: a 20-year follow-up study. Lancet. 2008;371(9626):1783–9. https://doi.org/10.1016/s0140-6736(08)60766-7.CrossRefPubMed

13.

•• Knowler W, Fowler S, Hamman R, Christophi C, Hoffman H, Brenneman A, et al. 10-year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program Outcomes Study. Lancet. 2009;374(9702):1677. https://doi.org/10.1016/S0140-6736(09)61457-4. This follow-up study of participants in the Diabetes Prevention Program clinical trial demonstrated durable reductions in diabetes incidence with both intensive lifestyle intervention and metformin. CrossRefPubMed

14.

Gong Q, Gregg EW, Wang J, An Y, Zhang P, Yang W, et al. Long-term effects of a randomised trial of a 6-year lifestyle intervention in impaired glucose tolerance on diabetes-related microvascular complications: the China Da Qing diabetes prevention outcome study. Diabetologia. 2011;54(2):300–7. https://doi.org/10.1007/s00125-010-1948-9.CrossRefPubMed

15.

Li G, Zhang P, Wang J, An Y, Gong Q, Gregg EW, et al. Cardiovascular mortality, all-cause mortality, and diabetes incidence after lifestyle intervention for people with impaired glucose tolerance in the Da Qing diabetes prevention study: a 23-year follow-up study. Lancet Diabetes Endocrinol. 2014;2(6):474–80. https://doi.org/10.1016/s2213-8587(14)70057-9.CrossRefPubMed

16.

Diabetes Prevention Program Research Group. Long-term effects of lifestyle intervention or metformin on diabetes development and microvascular complications over 15-year follow-up: the diabetes prevention program outcomes study. Lancet Diabetes Endocrinol. 2015;3(11):866–75. https://doi.org/10.1016/s2213-8587(15)00291-0.CrossRefPubMedCentral

17.

Herman WH, Hoerger TJ, Brandle M, Hicks K, Sorensen S, Zhang P, et al. The cost-effectiveness of lifestyle modification or metformin in preventing type 2 diabetes in adults with impaired glucose tolerance. Ann Intern Med. 2005;142(5):323–32.CrossRef

18.

•• Hafez D, Fedewa A, Moran M, O’Brien M, Ackermann R, Kullgren JT. Workplace interventions to prevent type 2 diabetes mellitus: a narrative review. Curr Diab Rep. 2017;17(2):9. https://doi.org/10.1007/s11892-017-0840-0. The paper reviewed the literature on employer-based programs aimed at preventing type 2 diabetes among adults, both those following the Diabetes Prevention Program curriculum and alternate intervention models. CrossRefPubMedPubMedCentral

19.

• American Diabetes Association. Standards of Medical Care in Diabetes-2018. Diabetes Care. 2018;41(Suppl 1):S1–S150. This paper outlines expert guidelines for diabetes screening, prevention, and management that are updated annually.

20.

Handelsman Y, Bloomgarden ZT, Grunberger G, Umpierrez G, Zimmerman RS, Bailey TS, et al. American Association of Clinical Endocrinologists and American College of endocrinology—clinical practice guidelines for developing a diabetes mellitus comprehensive care plan - 2015. Endocr Pract. 2015;21(Suppl 1):1–87. https://doi.org/10.4158/ep15672.gl.CrossRefPubMedPubMedCentral

21.

Centers for Medicare & Medicaid Services. Medicare Provides Coverage of Diabetes Screening Tests. Medicare-Learning-Network-MLN, American Medical Association, Baltimore, MD. 2018. https://www.cms.gov/Outreach-and-Education/Medicare-Learning-Network-MLN/MLNMattersArticles/downloads/se0821.pdf. Accessed July 31 2018.

22.

Lenters-Westra E, Slingerland RJ. Three of 7 hemoglobin A1c point-of-care instruments do not meet generally accepted analytical performance criteria. Clin Chem. 2014;60(8):1062–72. https://doi.org/10.1373/clinchem.2014.224311.CrossRefPubMed

23.

Hirst JA, McLellan JH, Price CP, English E, Feakins BG, Stevens RJ, et al. Performance of point-of-care HbA1c test devices: implications for use in clinical practice—a systematic review and meta-analysis. Clin Chem Lab Med. 2017;55(2):167–80. https://doi.org/10.1515/cclm-2016-0303.CrossRefPubMed

24.

•• Bowen ME, Xuan L, Lingvay I, Halm EA. Performance of a random glucose case-finding strategy to detect undiagnosed diabetes. Am J Prev Med. 2017;52(6):710–6. https://doi.org/10.1016/j.amepre.2017.01.023. This analysis of NHANES data examines the clinical performance (i.e. sensitivity and specificity) of using random glucose to identify cases of undiagnosed diabetes and compares performance with commonly used U.S. diabetes screening guidelines. CrossRefPubMedPubMedCentral

25.

Steyerberg EW. Clinical prediction models : a practical approach to development, validation, and updating. New York, NY: Springer; 2009.CrossRef

26.

American Diabetes Association. Diabetes Risk Test. American Diabetes Association, Alexandria, VA. 2018. http://main.diabetes.org/dorg/PDFs/risk-test-paper-version.pdf. . Accessed July 26 2018.

27.

Bang H, Edwards AM, Bomback AS, Ballantyne CM, Brillon D, Callahan MA, et al. Development and validation of a patient self-assessment score for diabetes risk. Ann Intern Med. 2009;151:775–83. https://doi.org/10.7326/0003-4819-151-11-200912010-00005.CrossRefPubMedPubMedCentral

28.

National Diabetes Prevention Program. CDC prediabetes screening test. Centers for Disease Control and Prevention 2016. http://www.cdc.gov/diabetes/prevention/pdf/prediabetestest.pdf. Accessed July 31 2018.

29.

Bullard KM, Ali MK, Imperatore G, Geiss LS, Saydah SH, Albu JB, et al. Receipt of glucose testing and performance of two US diabetes screening guidelines, 2007-2012. PLoS One. 2015;10(4):e0125249. https://doi.org/10.1371/journal.pone.0125249.CrossRefPubMedPubMedCentral

30.

•• O'Brien MJ, Bullard KM, Zhang Y, Gregg EW, Carnethon MR, Kandula NR, et al. Performance of the 2015 US Preventive Services Task Force Screening Criteria for Prediabetes and Undiagnosed Diabetes. J Gen Intern Med. 2018; https://doi.org/10.1007/s11606-018-4436-4. This analysis of NHANES data examines the clinical performance of the 2015 USPSTF screening criteria for identifying U.S. adults with prediabetes and diabetes, including estimates of sensitivity and specificity by racial/ethnic groups. CrossRef

31.

Wilson PW, Meigs JB, Sullivan L, Fox CS, Nathan DM, D'Agostino RB Sr. Prediction of incident diabetes mellitus in middle-aged adults: the Framingham offspring study. Arch Intern Med. 2007;167(10):1068–74. https://doi.org/10.1001/archinte.167.10.1068.CrossRefPubMed

32.

Mann DM, Bertoni AG, Shimbo D, Carnethon MR, Chen H, Jenny NS, et al. Comparative validity of 3 diabetes mellitus risk prediction scoring models in a multiethnic US cohort. Am J Epidemiol. 2010;171(9):980–8. https://doi.org/10.1093/aje/kwq030.CrossRefPubMedPubMedCentral

33.

Kahn HS, Cheng YJ, Thompson TJ, Imperatore G, Gregg EW. Two risk-scoring systems for predicting incident diabetes mellitus in US adults age 45 to 64 years. Ann Intern Med. 2009;150(11):741.CrossRef

34.

Schmidt MI, Duncan BB, Bang H, Pankow JS, Ballantyne CM, Golden SH, et al. Identifying individuals at high risk for diabetes: the atherosclerosis risk in communities study. Diabetes Care. 2005;28(8):2013–8.CrossRef

35.

Mainous AG 3rd, Diaz VA, Everett CJ. Assessing risk for development of diabetes in young adults. Ann Fam Med. 2007;5(5):425–9. https://doi.org/10.1370/afm.705.CrossRefPubMedPubMedCentral

36.

• Noble D, Mathur R, Dent T, Meads C, Greenhalgh T. Risk models and scores for type 2 diabetes: systematic review. BMJ. 2011;343:d7163. https://doi.org/10.1136/bmj.d7163. This systematic review of diabetes risk models evaluates the large body of literature on predicting diabetes risk, while highlighting opportunities and challenges to their implementation in practice. CrossRefPubMedPubMedCentral

37.

Collins GS, Mallett S, Omar O, Yu LM. Developing risk prediction models for type 2 diabetes: a systematic review of methodology and reporting. BMC Med. 2011;9:103. https://doi.org/10.1186/1741-7015-9-103.CrossRefPubMedPubMedCentral

38.

American Medical Association. Prevent Diabetes STAT. 2015. https://preventdiabetesstat.org/. Accessed July 26 2018.

39.

Nhim K, Khan T, Gruss SM, Wozniak G, Kirley K, Schumacher P, et al. Primary care providers' prediabetes screening, testing, and referral behaviors. Am J Prev Med. 2018;55(2):e39–47. https://doi.org/10.1016/j.amepre.2018.04.017.CrossRefPubMed

40.

Noble D, Mathur R, Dent T, Meads C, Greenhalgh T. Risk models and scores for type 2 diabetes: systematic review. BMJ. 2011;343:d7163.CrossRef

41.

Ealovega MW, Tabaei BP, Brandle M, Burke R, Herman WH. Opportunistic screening for diabetes in routine clinical practice. Diabetes Care. 2004;27(1):9–12.CrossRef

42.

• O'Brien MJ, Lee JY, Carnethon MR, Ackermann RT, Vargas MC, Hamilton A, et al. Detecting dysglycemia using the 2015 United States Preventive Services Task Force Screening Criteria: a cohort analysis of community health center patients. PLoS Med. 2016;13(7):e1002074. https://doi.org/10.1371/journal.pmed.1002074. This national analysis of EHR data from safety-net community health centers evaluates the clinical performance of the 2015 USPSTF diabetes screening criteria in a minority-predominant patient population. CrossRefPubMedPubMedCentral

43.

Bowen ME, Merchant Z, Abdullah K, Bhat D, Fish J, Halm EA. Patient, provider, and system factors associated with failure to follow-up elevated glucose results in patients without diagnosed diabetes. Health Serv Res Manag Epidemiol. 2017;4:2333392817721647. https://doi.org/10.1177/2333392817721647.CrossRefPubMedPubMedCentral

44.

•• Bowen ME, Xuan L, Lingvay I, Halm EA. Random blood glucose: a robust risk factor for type 2 diabetes. J Clin Endocrinol Metab. 2015;100(4):1503–10. https://doi.org/10.1210/jc.2014-4116. This study uses NHANES data to describe the association between non-diagnostic random glucose values and undiagnosed type 2 diabetes and prediabetes in the U.S. population. CrossRefPubMedPubMedCentral

45.

Bowen ME, Xuan L, Lingvay I, Halm EA. Doc, I just ate: interpreting random blood glucose values in patients with unknown glycemic status. J Gen Intern Med. 2018;33(2):142–4. https://doi.org/10.1007/s11606-017-4213-9.CrossRefPubMed

46.

Bowen ME, Sanders J, Zhang S, Santini NO, Lingvay I, Halam E. Derivation of an EMR-based dysglycemia risk score. Diabetes. 2018;67(Supplement 1) https://doi.org/10.2337/db18-1497-P.CrossRef

47.

• Selvin E, Wang D, Matsushita K, Grams ME, Coresh J. Prognostic implications of single-sample confirmatory testing for undiagnosed diabetes: a prospective cohort study. Ann Intern Med. 2018; https://doi.org/10.7326/M18-0091. This study supports the concurrent measurement of hemoglobin A1c and fasting glucose on a single blood sample to identify undiagnosed diabetes and confirm diagnosis. CrossRef

48.

Simmons RK, Echouffo-Tcheugui JB, Sharp SJ, Sargeant LA, Williams KM, Prevost AT, et al. Screening for type 2 diabetes and population mortality over 10 years (ADDITION-Cambridge): a cluster-randomised controlled trial. Lancet. 2012;380(9855):1741–8. https://doi.org/10.1016/s0140-6736(12)61422-6.CrossRefPubMedPubMedCentral

49.

Law M. "Opportunistic" screening. J Med Screen. 1994;1(4):208.

50.

Whitley HP, Hanson C, Parton JM. Systematic diabetes screening using point-of-care HbA1c testing facilitates identification of Prediabetes. Ann Fam Med. 2017;15(2):162–4. https://doi.org/10.1370/afm.2035.CrossRefPubMedPubMedCentral

51.

Herman WH, Taylor GW, Jacobson JJ, Burke R, Brown MB. Screening for prediabetes and type 2 diabetes in dental offices. J Public Health Dent. 2015;75(3):175–82. https://doi.org/10.1111/jphd.12082.CrossRefPubMedPubMedCentral

52.

Krass I, Carter R, Mitchell B, Mohebbi M, Shih STF, Trinder P, et al. Pharmacy diabetes screening trial: protocol for a pragmatic cluster-randomised controlled trial to compare three screening methods for undiagnosed type 2 diabetes in Australian community pharmacy. BMJ Open. 2017;7(12):e017725. https://doi.org/10.1136/bmjopen-2017-017725.CrossRefPubMedPubMedCentral

53.

• Siu AL. Screening for abnormal blood glucose and type 2 diabetes mellitus: U.S. preventive services task force recommendation statement. Ann Intern Med. 2015;163(11):861–8. https://doi.org/10.7326/m15-2345. This paper is the full report outlining the most recent diabetes screening guideline by the USPSTF. CrossRefPubMed

54.

Piper MA, Evans CV, Burda BU, Margolis KL, O'Connor E, Whitlock EP. Diagnostic and predictive accuracy of blood pressure screening methods with consideration of rescreening intervals: a systematic review for the U.S. preventive services task force. Ann Intern Med. 2015;162(3):192–204. https://doi.org/10.7326/m14-1539.CrossRefPubMed

55.

Ali MK, Echouffo-Tcheugui J, Williamson DF. How effective were lifestyle interventions in real-world settings that were modeled on the diabetes prevention program? Health Aff (Millwood). 2012;31(1):67–75. https://doi.org/10.1377/hlthaff.2011.1009.CrossRef

56.

Dunkley AJ, Bodicoat DH, Greaves CJ, Russell C, Yates T, Davies MJ, et al. Diabetes prevention in the real world: effectiveness of pragmatic lifestyle interventions for the prevention of type 2 diabetes and of the impact of adherence to guideline recommendations: a systematic review and meta-analysis. Diabetes Care. 2014;37(4):922–3. https://doi.org/10.2337/dc13-2195/-/DC1.CrossRefPubMed

57.

Mudaliar U, Zabetian A, Goodman M, Echouffo-Tcheugui JB, Albright AL, Gregg EW, et al. Cardiometabolic risk factor changes observed in diabetes prevention programs in US settings: a systematic review and meta-analysis. PLoS Med. 2016;13(7):e1002095. https://doi.org/10.1371/journal.pmed.1002095.CrossRefPubMedPubMedCentral

58.

Haw JS, Galaviz KI, Straus AN, Kowalski AJ, Magee MJ, Weber MB, et al. Long-term sustainability of diabetes prevention approaches: a systematic review and meta-analysis of randomized clinical trials. JAMA Intern Med. 2017;177(12):1808–17. https://doi.org/10.1001/jamainternmed.2017.6040.CrossRefPubMed

59.

Azar KM, Xiao L, Ma J. Baseline obesity status modifies effectiveness of adapted diabetes prevention program lifestyle interventions for weight management in primary care. Biomed Res Int. 2013;2013:191209–7. https://doi.org/10.1155/2013/191209.CrossRefPubMedPubMedCentral

60.

Sepah SC, Jiang L, Peters AL. Translating the diabetes prevention program into an online social network: validation against CDC standards. Diabetes Educ. 2014;40(4):435–43. https://doi.org/10.1177/0145721714531339.CrossRefPubMed

61.

Trief PM, Weinstock RS, Cibula D, Delahanty LM. Sustained weight loss one year after group telephone intervention: 3-year results from the SHINE study. Diabetes Res Clin Pract. 2014;106(3):e74–8. https://doi.org/10.1016/j.diabres.2014.09.032.CrossRefPubMedPubMedCentral

62.

Chen F, Su W, Becker SH, Payne M, Castro Sweet CM, Peters AL, et al. Clinical and economic impact of a digital, remotely-delivered intensive behavioral counseling program on Medicare beneficiaries at risk for diabetes and cardiovascular disease. PLoS One. 2016;11(10):e0163627. https://doi.org/10.1371/journal.pone.0163627.CrossRefPubMedPubMedCentral

63.

Vadheim LM, Patch K, Brokaw SM, Carpenedo D, Butcher MK, Helgerson SD, et al. Telehealth delivery of the diabetes prevention program to rural communities. Transl Behav Med. 2017;7(2):286–91. https://doi.org/10.1007/s13142-017-0496-y.CrossRefPubMedPubMedCentral

64.

LeFevre ML, U. S. Preventive services task force. Behavioral counseling to promote a healthful diet and physical activity for cardiovascular disease prevention in adults with cardiovascular risk factors: U.S. preventive services task force recommendation statement. Ann Intern Med. 2014;161(8):587–93. https://doi.org/10.7326/M14-1796.CrossRefPubMed

65.

Diabetes Prevention Program Research Group. The diabetes prevention program: design and methods for a clinical trial in the prevention of type 2 diabetes. Diabetes Care. 1999;22(4):623–34.CrossRef

66.

Marrero DG, Palmer KN, Phillips EO, Miller-Kovach K, Foster GD, Saha CK. Comparison of commercial and self-initiated weight loss programs in people with Prediabetes: a randomized control trial. Am J Public Health. 2016;106(5):949–56. https://doi.org/10.2105/ajph.2015.303035.CrossRefPubMedPubMedCentral

67.

Albright AL, Gregg EW. Preventing type 2 diabetes in communities across the US: the National Diabetes Prevention Program. Am J Prev Med. 2013;44(4):S346–S51.CrossRef

68.

Vojta D, Koehler TB, Longjohn M, Lever JA, Caputo NF. A coordinated national model for diabetes prevention: linking health systems to an evidence-based community program. Am J Prev Med. 2013;44(4 Suppl 4):S301–6. https://doi.org/10.1016/j.amepre.2012.12.018.CrossRefPubMed

69.

YMCA's Diabetes Prevention Program. Diabetes prevention program FACT SHEET: January 2018. YMCA of the USA: Chicago, IL; 2018.

70.

Center for Disease Control and Prevention. National Diabetes Prevention Program. U.S. Department of Health and Human Services, Atlanta, GA. 2018. https://www.cdc.gov/diabetes/prevention/index.html. Accessed July 31 2018.

71.

• Ely EK, Gruss SM, Luman ET, Gregg EW, Ali MK, Nhim K, et al. A national effort to prevent type 2 diabetes: participant-level evaluation of CDC's national diabetes prevention program. Diabetes Care. 2017;40(10):1331–41. https://doi.org/10.2337/dc16-2099. This study analyzed data from 14,747 participants in the DPP nationwide, including those who enrolled from 2012-2016. CrossRefPubMedPubMedCentral

72.

Vanderwood KK, Hall TO, Harwell TS, Butcher MK, Helgerson SD. Implementing a state-based cardiovascular disease and diabetes prevention program. Diabetes Care. 2010;33(12):2543–5. https://doi.org/10.2337/dc10-0862.CrossRefPubMedPubMedCentral

73.

Brokaw SM, Carpenedo D, Campbell P, Butcher MK, Furshong G, Helgerson SD, et al. Effectiveness of an adapted diabetes prevention program lifestyle intervention in older and younger adults. J Am Geriatr Soc. 2015;63(6):1067–74. https://doi.org/10.1111/jgs.13428.CrossRefPubMed

74.

Moin T, Damschroder LJ, AuYoung M, Maciejewski ML, Datta SK, Weinreb JE, et al. Diabetes prevention program translation in the veterans health administration. Am J Prev Med. 2017;53(1):70–7. https://doi.org/10.1016/j.amepre.2016.11.009.CrossRefPubMed

75.

Tseng E, Yeh HC, Maruthur NM. Metformin use in Prediabetes among U.S. adults, 2005-2012. Diabetes Care. 2017;40(7):887–93. https://doi.org/10.2337/dc16-1509.CrossRefPubMedPubMedCentral

76.

•• Schmittdiel JA, Gopalan A, Lin MW, Banerjee S, Chau CV, Adams AS. Population health management for diabetes: health care system-level approaches for improving quality and addressing disparities. Curr Diab Rep. 2017;17(5):31. https://doi.org/10.1007/s11892-017-0858-3. This narrative review highlights the role of several strategies to improve population-level management of type 2 diabetes, including electronic health record tools, practice redesign, and new payment models. CrossRefPubMedPubMedCentral

77.

Moin T, Li J, Duru OK, Ettner S, Turk N, Keckhafer A, et al. Metformin prescription for insured adults with prediabetes from 2010 to 2012: a retrospective cohort study. Ann Intern Med. 2015;162(8):542–8. https://doi.org/10.7326/M14-1773.CrossRefPubMedPubMedCentral

78.

Desai JR. Reducing CV Risk in Prediabetes patients using EHR-based decision support. National Institutes of Health, U.S. Department of Health and Human Services, Research Portfolio Online Reporting Tools. 2018. https://projectreporter.nih.gov/project_info_description.cfm?aid=9327055&icde=40170194. Accessed July 31 2018.

79.

National Association of Chronic Disease Directors (NACDD), Leavitt Partners L. Advancing Chronic Disease Prevention and Management Programs: Building a Third-Party Organization to Support Managed Care Coverage of Services in Community-Based Organizations in Illinois. Atlanta, GA 2018.

80.

• Nowinski Konchak J, Moran MR, O’Brien MJ, Kandula NR, Ackermann RT. The state of diabetes prevention policy in the USA following the Affordable Care Act. Curr Diab Rep. 2016;16(6):55. https://doi.org/10.1007/s11892-016-0742-6. This paper highlighted all provisions of the Affordable Care Act that may promote diabetes prevention, including gaps and opportunities in current practice. CrossRefPubMedCentral

Titel: Building Toward a Population-Based Approach to Diabetes Screening and Prevention for US Adults
verfasst von: Michael E. Bowen
Julie A. Schmittdiel
Jeffrey T. Kullgren
Ronald T. Ackermann
Matthew J. O’Brien
Publikationsdatum: 01.11.2018
Verlag: Springer US
Erschienen in: Current Diabetes Reports / Ausgabe 11/2018
Print ISSN: 1534-4827
Elektronische ISSN: 1539-0829
DOI: https://doi.org/10.1007/s11892-018-1090-5

Leitlinien kompakt für die Innere Medizin

Mit medbee Pocketcards sicher entscheiden.

^{Seit 2022 gehört die medbee GmbH zum Springer Medizin Verlag}

Kostenlos registrieren

Neu im Fachgebiet Innere Medizin

Notfall-TEP der Hüfte ist auch bei 90-Jährigen machbar

26.04.2024 Hüft-TEP Nachrichten

Ob bei einer Notfalloperation nach Schenkelhalsfraktur eine Hemiarthroplastik oder eine totale Endoprothese (TEP) eingebaut wird, sollte nicht allein vom Alter der Patientinnen und Patienten abhängen. Auch über 90-Jährige können von der TEP profitieren.

Niedriger diastolischer Blutdruck erhöht Risiko für schwere kardiovaskuläre Komplikationen

25.04.2024 Hypotonie Nachrichten

Wenn unter einer medikamentösen Hochdrucktherapie der diastolische Blutdruck in den Keller geht, steigt das Risiko für schwere kardiovaskuläre Ereignisse: Darauf deutet eine Sekundäranalyse der SPRINT-Studie hin.

Bei schweren Reaktionen auf Insektenstiche empfiehlt sich eine spezifische Immuntherapie

25.04.2024 Allergien und Intoleranzreaktionen Nachrichten

Insektenstiche sind bei Erwachsenen die häufigsten Auslöser einer Anaphylaxie. Einen wirksamen Schutz vor schweren anaphylaktischen Reaktionen bietet die allergenspezifische Immuntherapie. Jedoch kommt sie noch viel zu selten zum Einsatz.

Therapiestart mit Blutdrucksenkern erhöht Frakturrisiko

25.04.2024 Hypertonie Nachrichten

Beginnen ältere Männer im Pflegeheim eine Antihypertensiva-Therapie, dann ist die Frakturrate in den folgenden 30 Tagen mehr als verdoppelt. Besonders häufig stürzen Demenzkranke und Männer, die erstmals Blutdrucksenker nehmen. Dafür spricht eine Analyse unter US-Veteranen.

Update Innere Medizin

Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert.

Newsletter bestellen

Springer Medizin

Abstract

Purpose of review

Recent findings

Summary

Bitte loggen Sie sich ein, um Zugang zu diesem Inhalt zu erhalten

Weitere Artikel der Ausgabe 11/2018

Glycemic Outcomes of Islet Autotransplantation

The Effect of Age on the Progression and Severity of Type 1 Diabetes: Potential Effects on Disease Mechanisms

Biopsychosocial Factors Associated With Satisfaction and Sustained Use of Artificial Pancreas Technology and Its Components: a Call to the Technology Field

Enteroviral Infections as a Trigger for Type 1 Diabetes

Lifestyle Factors Affecting the Gut Microbiota’s Relationship with Type 1 Diabetes

Epigenetics Variation and Pathogenesis in Diabetes