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The American Journal of Managed Care February 2012
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Nurse-Run, Telephone-Based Outreach to Improve Lipids in People With Diabetes
Henry H. Fischer, MD; Sheri L. Eisert, PhD; Rachel M. Everhart, MS; Michael J. Durfee, MSPH; Susan L. Moore, MSPH; Stanley Soria, RN; Diana I. Stell, RN; Cecilia M. Rice-Peterson, RN, BSN; Thomas D. MacKenzie, MD, MSPH; and Raymond O. Estacio, MD
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Henry H. Fischer, MD; Susan L. Moore, MSPH; David Ginosar, MD; Arthur J. Davidson, MD, MSPH; Cecilia M. Rice-Peterson, RN, BSN; Michael J. Durfee, MSPH; Thomas D. MacKenzie, MD, MSPH; Raymond O. Estacio, MD; and Andrew W. Steele, MD, MPH, MSc
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Nurse-Run, Telephone-Based Outreach to Improve Lipids in People With Diabetes

Henry H. Fischer, MD; Sheri L. Eisert, PhD; Rachel M. Everhart, MS; Michael J. Durfee, MSPH; Susan L. Moore, MSPH; Stanley Soria, RN; Diana I. Stell, RN; Cecilia M. Rice-Peterson, RN, BSN; Thomas D. MacKenzie, MD, MSPH; and Raymond O. Estacio, MD
Nurses can improve lipid control in people with diabetes in a primarily indigent population through telephone care using moderately complex algorithms. Telephone-based outreach may decrease resource utilization.
A limitation of this study is the possibility that participants may have used services in other healthcare centers, resulting in an underestimate of total costs. This is unlikely to affect the comparison of the intervention with the control patients since both groups were equally likely or unlikely to obtain outside medical care. Furthermore, our patient population had high rates of uninsurance and Medicaid coverage, making it difficult to seek care in other healthcare facilities. We did not include medication analyses or medication side effect and adherence data, given our incomplete medication database, as only our uninsured patients, making up less than half the cohort, had financial incentives to fill at DHMC pharmacies. Although the nurses tracked statin initiations, titrations, and side effects, we did not include these data, as the nurses admit to not always recording these data for every patient contact. Another limitation was that the study was performed at 1 site in which the 3 study nurses shared 0.75 FTE. Given that the nurses also interacted with control patients, contamination of the intervention was a possibility, thus diluting the effect of the intervention. Furthermore, investigators doing the analysis of the data were not blinded to control versus intervention patients. There is also an increased risk of fi nding differences by chance (type 1 error) when performing multiple hypotheses at a set P value,23 as seen in these analyses. It should be noted that our primary end point is lipid control, and that the other secondary end points are informative, but that further analyses with separate data sources are necessary to better assess their merit. Also, while over 90% of our diabetes population is type 2, we did not distinguish between Type 1 and Type 2 in our analysis.

This intervention took place in a safety-net health organization that serves a predominantly indigent and Latino population. The intervention was facilitated by the presence of a diabetes registry with a software interface for identifying patients not meeting recommended diabetes guidelines. The use of motivational interviewing techniques and the promotion of patient self-management were key components of this intervention. The results must be interpreted in this context and are most relevant to other community health centers that participate in diabetes collaboratives and serve primarily indigent populations.

Acknowledgments

This study was in part funded by the American Diabetes Association. Data from this study were presented at the American Diabetes Association annual meeting (June 2008) and at the Society of General Internal Medicine annual meeting (April 2006). Adrienne Welsh assisted with the writing of the introduction section. Kevin McCullen helped with the data analysis.


Author Affiliations: From Denver Health and Hospital Authority (HHF, SLE, RME, MJD, SLM, SS, DIS, CMR-P, TDM, ROE), Denver, CO; Colorado School of Public Health (SLE), University of Colorado Denver, Denver, CO; University of Colorado Denver School of Medicine (HHF, SLE, TDM, ROE), Denver, CO.


Funding Source: This study was funded by the American Diabetes Association.


Author Disclosures: The authors (HHF, SLE, RME, MJD, SLM, SS, DIS, CMR-P, TDM, ROE) report no relationship or financial interest with any entity that would pose a confl ict of interest with the subject matter of this article.


Authorship Information: Concept and design (HHF, SLE, DIS, CMR-P, TDM, ROE); acquisition of data (HHF); analysis and interpretation of data (HHF, SLE, RME, MJD, TDM); drafting of the manuscript (HHF, RME, MJD, SLM); critical revision of the manuscript for important intellectual content (HHF, RME, MJD, SLM, ROE); statistical analysis (RME, MJD); provision of study materials or patients (HHF, CMR-P); obtaining funding (HHF, SLE, ROE); administrative, technical, or logistic support (SLM, SS, TDM, ROE); and supervision (TDM).


Address correspondence to: Henry H. Fischer, MD, WFHC Adult Clinic, 1100 Federal Blvd, Denver, CO 80204. E-mail: henry.fi scher@dhha.org.
1. American Diabetes Association. Economic costs of diabetes in the U.S. in 2007. Diabetes Care. 2008;31(3):596-615.

2. Wild S, Roglic G, Green A, Sicree R, King H. Global prevalence of diabetes: estimates for the year 2000 and projections for 2030. Diabetes Care. 2004;27(5):1047-1053.

3. Hogan P, Dall T, Nikolov P; American Diabetes Association. Economic costs of diabetes in the US in 2002. Diabetes Care. 2003;26(3):917-932.

4. Smith DG. Epidemiology of dyslipidemia and economic burden on the healthcare system. Am J Manag Care. 2007;13(suppl 3):S68-S71.

5. Saaddine JB, Cadwell B, Gregg EW, et al. Improvements in diabetes processes of care and intermediate outcomes: United States, 1988-2002. Ann Intern Med. 2006;144(7):465-474.

6. UK Prospective Diabetes Study (UKPDS) Group. Intensive bloodglucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). Lancet. 1998;352(9131):837-853.

7. The Diabetes Control and Complications Trial Research Group. The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med. 1993;329(14):977-986.

8. Rothman AA, Wagner EH. Chronic illness management: what is the role of primary care? Ann Intern Med. 2003;138(3):256-261.

9. Holman H, Lorig K. Patient self-management: a key to effectiveness and efficiency in care of chronic disease. Public Health Reports. 2004;119(3):239-243.

10. Mangione CM, Gerzoff RB, Williamson DF, et al; TRIAD Study Group. The association between quality of care and the intensity of diabetes disease management programs. Ann Intern Med. 2006;145(2):107-116.

11. Shojania KG, Ranji SR, McDonald KM, et al. Effects of quality improvement strategies for type 2 diabetes on glycemic control: a meta-regression analysis. JAMA. 2006;296(4):427-440.

12. Piette JD, Weinberger M, Kraemer FB, McPhee SJ. Impact of automated calls with nurse follow-up on diabetes treatment outcomes in a Department of Veterans Affairs Health Care System: a randomized controlled trial. Diabetes Care. 2001;24(2):202-208.

13. Shea S, Weinstock RS, Starren J, et al. A randomized trial comparing telemedicine case management with usual care in older, ethnically diverse, medically underserved patients with diabetes mellitus. J Am Med Inform Assoc. 2006;13(1):40-51.

14. Kim HS, Oh JA. Adherence to diabetes control recommendations: impact of nurse telephone calls. J Adv Nurs. 2003;44(3):256-261.

15. Stone RA, Rao RH, Sevick MR, et al. Active care management supported by home telemonitoring in veterans with type 2 diabetes: the DiaTel randomized controlled trial. Diabetes Care. 2010;33(3):478-484.

16. Fischer H, Mackenzie T, McCullen K, Everhart R, Estacio RO. Design of a nurse-run, telephone-based intervention to improve lipids in diabetes. Contemp Clin Trials. 2008;29(5):809-816.

17. National Heart Lung and Blood Institute. Third Report of the Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). http://www.nhlbi.nih.gov/guidelines/cholesterol/. Accessed October 4, 2011.

18. American Diabetes Association. Standards of medical care in diabetes. Diabetes Care. 2005;28(suppl 1):S4-S36.

19. National Heart Lung and Blood Institute. The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure - Complete Report. http://www.nhlbi.nih.gov/guidelines/hypertension/jnc7full.htm. Accessed November 4, 2009.

20. Kronick R, Gilmer T, Dreyfus T, Lee L. Improving health-based payment for Medicaid benefi ciaries: CDPS. Health Care Financ Rev. 2000;21(3):29-64.

21. Piette, JD, Weinberger M, McPhee SH, Mah CA, Kraemer FB, Crapo LM. Do automated calls with nurse follow-up improve self-care and glycemic control among vulnerable patients with diabetes? Am J Med. 2000;108(1):20-27.

22. Bodenheimer T. The future of primary care: transforming practice. N Engl J Med. 2008;359(20):2086, 2089.

23. Feise RJ. Do multiple outcome measures require P-value adjustment? BMC Med Res Methodol. 2002;2:8.
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