Impact of electronic diabetes registry 'meaningful use' on quality of care and hospital utilization

Journal of the American Medical Informatics Association

Volumn 23, Issue 2, 2016, Pages 242-247

  Han, Wencui ^a   Sharman, Raj ^b   Heider, Arvela ^c   Maloney, Nancy ^c   Yang, Min ^b   Singh, Ranjit ^b  

^a UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

^b UNIVERSITY AT BUFFALO   (United States)

^c HEALTHeLINK   (United States)

Author keywords

Diabetes; Hospital utilization; Meaningful use; Quality of care; Registry

Indexed keywords

ADULT; AMBULATORY CARE; ARTICLE; CLINICAL PRACTICE; CONTROLLED STUDY; COST CONTROL; DIABETES REGISTRY; DIABETIC PATIENT; DISEASE REGISTRY; EMERGENCY WARD; FEMALE; HEALTH CARE COST; HEALTH CARE QUALITY; HEALTH INSURANCE; HOSPITAL UTILIZATION; HUMAN; INSULIN DEPENDENT DIABETES MELLITUS; LABORATORY TEST; MAJOR CLINICAL STUDY; MALE; MEANINGFUL USE CRITERIA; MIDDLE AGED; NON INSULIN DEPENDENT DIABETES MELLITUS; OUTCOME ASSESSMENT; PRIMARY MEDICAL CARE; RETINA EXAMINATION; TOTAL QUALITY MANAGEMENT; URBAN AREA; BLOOD; DIABETES MELLITUS; DIABETES MELLITUS, TYPE 1; DIABETES MELLITUS, TYPE 2; HEALTH PROMOTION; HOSPITALIZATION; REGISTER; REMINDER SYSTEM; SEX DIFFERENCE; STATISTICS AND NUMERICAL DATA;

DIABETES MELLITUS; DIABETES MELLITUS, TYPE 1; DIABETES MELLITUS, TYPE 2; FEMALE; HEALTH PROMOTION; HOSPITALIZATION; HUMANS; MALE; MEANINGFUL USE; MIDDLE AGED; QUALITY OF HEALTH CARE; REGISTRIES; REMINDER SYSTEMS; SEX FACTORS;

EID: 84963715783     PISSN: 10675027     EISSN: 1527974X     Source Type: Journal    
DOI: 10.1093/jamia/ocv040     Document Type: Article

References (27)

1. Schmittdiel J, Bodenheimer T, Solomon NA, et al. Brief report: the prevalence and use of chronic disease registries in physician organizations. J Gen Int Med. 2005;20(9):855-858.
2. Metzger J. Using Computerized Registries in Chronic Disease Care. California HealthCare Foundation; 2004. http://www.chcf.org/publications/2004/02/using-computerized-registries-in-chronic-disease-care. Accessed April 30, 2015.
3. Ortiz DD. Using a simple patient registry to improve your chronic disease care. Fam Pract Manag. 2006;13(4):47-48, 51-52.
4. Maizlish NA, Herrera L. A record linkage protocol for a diabetes registry at ethnically diverse community health centers. JAMIA. 2005;12(3):331-337.
5. FIDIS. Privacy by credential-based identity management. Secondary Privacy by credential-based identity management 2013. http://www.fidis.net/resources/ deliverables/mobility-and-identity/int-d111000/doc/45/. Accessed April 30, 2015.
6. American_Diabetes_Association. Economic costs of diabetes in the US in 2012. Diabetes Care. 2013;36(4):1033-1046.
7. Harris MF, Priddin D, Ruscoe W, et al. Quality of care provided by general practitioners using or not using Division-based diabetes registers. Med J Aust. 2002;177(5):250-252.
8. Renders CM, Valk GD, Griffin SJ, et al. Interventions to improve the management of diabetes in primary care, outpatient, and community settings: a systematic review. Diabetes Care. 2001;24(10):1821-1833.
9. Stroebel RJ, Scheitel SM, Fitz JS, et al. A randomized trial of three diabetes registry implementation strategies in a community internal medicine practice. Jt Comm J Qual Improv. 2002;28(8):441-450.
10. Bu D, Pan E, Walker J, et al. Benefits of information technology-enabled diabetes management. Diabetes Care. 2007;30(5):1137-1142.
11. Winzelberg AJ, Classen C, Alpers GW, et al. Evaluation of an internet support group for women with primary breast cancer. Cancer. 2003;97(5): 1164-1173.
12. Wang SJ, Middleton B, Prosser LA, et al. A cost-benefit analysis of electronic medical records in primary care. Am J Med. 2003;114(5):397-403.
13. Young AS, Chaney E, Shoai R, et al. Information technology to support improved care for chronic illness. J Gen Int Med. 2007;22(3):425-430.
14. Chaudhry B, Wang J, Wu S, et al. Systematic review: impact of health information technology on quality, efficiency, and costs of medical care. Ann Int Med. 2006;144(10):742-752.
15. Hillestad R, Bigelow J, Bower A, et al. Can electronic medical record systems transform health care? Potential health benefits, savings, and costs. Health Aff. 2005;24(5):1103-1117.
16. Statements P. Standards of medical care in diabetes-2012. Diabetes Care. 2012;35(Suppl 1):S11-S63.
17. Basu J, Friedman B, Burstin H. Primary care, HMO enrollment, and hospitalization for ambulatory care sensitive conditions: a new approach. Med Care. 2002;40(12):1260-1269.
18. Charlson ME, Charlson RE, Peterson JC, et al. The Charlson comorbidity index is adapted to predict costs of chronic disease in primary care patients. J Clin Epidemiol. 2008;61(12):1234-1240.
19. D'Hoore W, Sicotte C, Tilquin C. Risk adjustment in outcome assessment: the Charlson comorbidity index. Methods Inform Med. 1993;32(5):382-387.
20. Gans D, Kralewski J, Hammons T, et al. Medical groups' adoption of electronic health records and information systems. Health Aff. 2005;24(5): 1323-1333.
21. Ketcham JD, Baker LC, MacIsaac D. Physician practice size and variations in treatments and outcomes: evidence from Medicare patients with AMI. Health Aff. 2007;26(1):195-205.
22. Wang Y, O'Donnell CA, Mackay DF, et al. Practice size and quality attainment under the new GMS contract: a cross-sectional analysis. Brit J General Pract. 2006;56(532):830-835.
23. Raudenbush SW, Bryk AS. Hierarchical Linear Models: Application and Data Analysis. Thousand Oaks, Newbury Park, CA: Sage; 2002.
24. Dall TM, Mann SE, Zhang Y, et al. Distinguishing the economic costs associated with type 1 and type 2 diabetes. Popul Health Manag. 2009;12(2): 103-110.
25. Drotar D, Ievers C. Age differences in parent and child responsibilities for management of cystic fibrosis and insulin-dependent diabetes mellitus. J Dev Behav Pediatr. 1994;15(4):265-272.
26. Juutilainen A, Kortelainen S, Lehto S, et al. Gender difference in the impact of type 2 diabetes on coronary heart disease risk. Diabetes Care 2004; 27(12):2898-2904.
27. Huxley R, Barzi F, Woodward M. Excess risk of fatal coronary heart disease associated with diabetes in men and women: meta-analysis of 37 prospective cohort studies. BMJ. 2006;332(7533):73-78.