Pharmacy & Therapeutics- August 2008 - (Page 466) Monitoring Asthma Control in 2007, key elements on assessing and monitoring asthma have been refined to address severity, control, and responsiveness to treatment as separate but related concepts. These guidelines also include separate recommendations for children in two different age groups: 0 to 4 years and 5 to 11 years. The guidelines include an updated step-care approach of six levels based on asthma severity as well as on age groups. These guidelines should provide a new opportunity for MCOs to integrate claims data with direct monitoring of patients to effectively administer and monitor therapy in the management of this complex and variable disease state. Through this integrated approach, we can identify patients with uncontrolled and difficult-to-treat asthma, thereby providing appropriate care to reduce exacerbations, the need for health care, and costs. care support program. Dis Manag 2005;8(3):144–154. 17. Grana J, Preston S, McDermott PD, Hanchak NA. The use of administrative data to risk-stratify asthmatic patients. Am J Med Qual 1997;12(2):113–119. 18. Li D, German D, Lulla S, et al. Prospective study of hospitalization for asthma: A preliminary risk factor model. Am J Respir Crit Care Med 1995;151(3 Part 1):647–655. 19. Schatz M, Nakahiro R, Jones CH, et al. Asthma population management: Development and validation of a practical 3-level risk stratification scheme. Am J Manag Care 2004;10(1):25–32. 20. Schatz M, Nakahiro R, Crawford W, et al. Asthma quality-of-care markers using administrative data. Chest 2005;128(4):1968–1973. 21. Leone FT, Grana JR. McDermott P, et al. Pharmaceutically based severity stratification of an asthmatic population. Respir Med 1999;93:788–793. 22. Stempel DA, McLaughin TP, Stanford RH, Fuhlbrigge AL. Patterns of asthma control: A 3-year analysis of patient claims. J Allergy Clin Immunol 2005;115(5):935–939. 23. Cabana MD, Slish KK, Nan B, Clark NM. Limits of the HEDIS criteria in determining asthma severity for children. Pediatrics 2004;114(4):1049–1055. 24. Berger WE, Legorreta AP, Blaiss MS, et al. The utility of the Health Plan Employer Data and Information Set (HEDIS) asthma measure to predict asthma-related outcomes. Ann Allergy Asthma Immunol 2004;93(6):538–545. 25. Juniper EF, O’Byrne PM, Guyatt GH, et al. Development and validation of a questionnaire to measure asthma control. Eur Respir J 1999;14(4):902–907. 26. Nathan RA, Sorkness CA, Kosinski M, et al. Development of the asthma control test: A sur vey for assessing asthma control. J Allergy Clin Immunol 2004;113(1):59–65. 27. Vollmer WM, Markson LE, O’Connor E, et al. Association of asthma control with health care utilization and quality of life. Am J Respir Crit Care Med 1999;160(5 Part 1):1647–1652. 28. Disease Management Association of America. DMAA Definition of Disease Management. 2006. Available at: www.dmaa.org/dm_ definition.asp. Accessed September 21, 2007. 29. Buchner DA, Butt LT, De Stefano A, et al. Effects of an asthma management program on the asthmatic member: Patientcentered results of a 2-year study in a managed care organization. Am J Manag Care 1998;4(9):1288–1297. 30. Jones CA, Clement LT, Hanley-Lopez J, et al. The Breathmobile Program: Structure, implementation, and evolution of a largescale, urban, pediatric asthma disease management program. Dis Manag 2005;8(4):205–222. 31. Patel PH, Welsh C, Foggs MB. Improved asthma outcomes using a coordinated care approach in a large medical group. Dis Manag 2004;7(2):102–111. 32. Yurk RA, Diette GB, Skinner EA, et al. Predicting patientreported asthma outcomes for adults in managed care. Am J Manag Care 2004;10(5):321–328. 33. Peters D, Chen C, Markson LE, et al. Using an asthma control questionnaire and administrative data to predict health care utilization. Chest 2006;129(4):918–924. I REFERENCES 1. National Asthma Education and Prevention Program. Expert Panel Report 3: Guidelines for the Diagnosis and Management of Asthma. National Institutes of Health, National Heart, Lung, and Blood Institute; August 2007. 2. Fuhlbrigge AL, Adams RJ, Guilbert TW, et al. The burden of asthma in the United States: Level and distribution are dependent on interpretation of the national asthma education and prevention program guidelines. Am J Respir Crit Care Med 2002;166(8): 1044–1049. 3. Lieu TA, Quesenberry CP, Sorel ME, et al. Computer-based models to identify high-risk children with asthma. Am J Respir Crit Care Med 1998;157(4 Part 1):1173–1180. 4. Israel E. Genetics and the variability of treatment response in asthma. J Allergy Clin Immunol 2005;115(4 Suppl):S532–S538. 5. Szefler SJ, Martin RJ, King TS, et al. Significant variability in response to inhaled corticosteroids for persistent asthma. J Allergy Clin Immunol 2002;109(3):410–418. 6. Wechsler ME, Lehman E, Lazarus SC, et al. Beta-adrenergic receptor polymorphisms and response to salmeterol. Am J Respir Crit Care Med 2006;173(5):519–526. 7. Zeiger RS, Szefler SJ, Phillips BR, et al. Response profiles to fluticasone and montelukast in mild-to-moderate persistent childhood asthma. J Allergy Clin Immunol 2006;117(1):45–52. 8. Weiss KB, Sullivan SD. The health economics of asthma and rhinitis: I. Assessing the economic impact. J Allergy Clin Immunol 2001;107(1):3–8. 9. Bateman ED, Boushey HA, Bousquet J, et al. Can guidelinedefined asthma control be achieved? The Gaining Optimal Asthma ControL study. Am J Respir Crit Care Med 2004;170(8):836–844. 10. Malmstrom K, Rodriguez-Gomez G, Guerra J, et al. Oral montelukast, inhaled beclomethasone, and placebo for chronic asthma: A randomized, controlled trial. Montelukast/Beclomethasone Study Group. Ann Intern Med 1999;130(6):487–495. 11. Israel E, Chervinsky PS, Friedman B, et al. Effects of montelukast and beclomethasone on airway function and asthma control. J Allergy Clin Immunol 2002;110(6):847–854. 12. Tantisira KG, Lake S, Silverman ES, et al. Corticosteroid pharmacogenetics: Association of sequence variants in CRHR1 with improved lung function in asthmatics treated with inhaled corticosteroids. Hum Mol Genet 2004;13(13):1353–1359. 13. Lieu TA, Capra AM, Quesenberry CP, et al. Computer-based models to identify high-risk adults with asthma: Is the glass half empty or half full? J Asthma 1999;36(4):359–370. 14. Juniper EF, Bousquet J, Abetz L, Bateman ED. Identifying ‘wellcontrolled’ and ‘not well-controlled’ asthma using the Asthma Control Questionnaire. Respir Med 2006;100(4):616–621. 15. Cowie RL, Underwood MF, Revitt SG, Field SK. Predicting emergency department utilization in adults with asthma: A cohort study. J Asthma 2001;38(2):179–184. 16. Johnson A, Berg G, Fleegler E, Sauerbrun M. A matched-cohort study of selected clinical and utilization outcomes for an asthma ATTENTION, READERS! Too busy to write an article? Send us your ideas anyway. Contact Sonja Sherritze at: ssherritze@medimedia.com. 466 P&T® • August 2008 • Vol. 33 No. 8 http://www.dmaa.org/dm_definition.asp http://www.dmaa.org/dm_definition.asp
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