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Clinical and Utilization Outcomes for a Pediatric and Adolescent Telephonic Asthma Care Support Program

A Propensity Score-Matched Cohort Study

  • Original Research Article
  • Published:
Disease Management & Health Outcomes

Abstract

Objective

To investigate the effect of an asthma care support program for patients under the age of 18 years.

Study design

A 1:1 matched cohort study design was used. The purpose of matching is to find a similar comparison group in terms of observable variables. The propensity score method of matching was used to find a suitable comparison cohort, which is similar at baseline to the treatment cohort. For each treatment cohort member, a comparison cohort member was selected on the basis of having the closest estimated propensity score. Once a comparison cohort was defined, variables were compared at baseline year to ensure the similarity of the two groups. The Kruskal-Wallis test was used for comparison of variables between the treatment and comparison cohorts due to the non-Gaussian distribution of variables. Finally, variables were compared during the program year to estimate the treatment effects of the disease management program.

Patient groups

318 asthma care support program participants and 318 matched non-participants.

Main outcome measures

The rates of medical service utilization including rates of hospitalization, emergency department (ED) visits, and selected clinical indicators including allergen immunotherapy, chest x-rays, influenza vaccinations, and pneumococcal vaccinations.

Results

Baseline matching resulted in no statistically significant difference between the treatment and matched cohorts. However, during the program period the treatment cohort had 35.6% fewer inpatient admissions (p = 0.045), 32.5% fewer ED visits (p = 0.007), 56.7% fewer asthma-related inpatient admissions (p = 0.008), 50.8% fewer asthma-related ED visits (p < 0.0001), 26.8% fewer chest x-rays (p = 0.036), and 51.6% more influenza immunizations (p = 0.046).

Conclusions

Where controlled randomized clinical trials cannot be performed, the use of propensity scores provides an alternative for the purpose of estimating a treatment effect using observational data. The current study employed a propensity score-matching methodology to select a subset of comparison units most comparable to treatment units. It documented the beneficial clinical outcomes of pediatric and adolescent participation in an asthma care support program which suggested a beneficial impact of monitoring, education, and more rigorous adherence to action plans for program participants.

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References

  1. Centers for Disease Control. Surveillance for Asthma: United States, 1980–1999. MMWR Morb Mortal Wkly Rep 2002; 51(SS-1): 1–30

    Google Scholar 

  2. World Health Organization. Bronchial asthma. WHO Fact Sheet Number 206. Geneva, WHO: 2000 Jan

    Google Scholar 

  3. Maziak W, Behrens T, Brasky TM, et al. Are asthma and allergies in children and adolescents increasing? Results from ISAAC phase I and Phase III surveys in Munster, Germany. Allergy 2003; 58(7): 572–9

    Article  PubMed  CAS  Google Scholar 

  4. National Heart, Lung, and Blood Institute. Morbidity and mortality: 2002 chart book on cardiovascular, lung, and blood diseases. Bethesda (MD): National Institutes of Health, 2002 May

    Google Scholar 

  5. American Lung Association. Trends in asthma morbidity and mortality. New York: American Lung Association, Epidemiology & Statistics Unit, Best Practices and Program Services, 2002

    Google Scholar 

  6. Pappas G, Hadden WC, Kozak LJ, et al. Potentially avoidable hospitalizations: inequalities in rates between US socioeconomic groups. Am J Public Health 1997; 87(5): 811–6

    Article  PubMed  CAS  Google Scholar 

  7. Friday Jr GA, Khine H, Lin MS, et al. Profile of children requiring emergency treatment for asthma. Ann Allergy Asthma Immunol 1997; 78(2): 221–4

    Article  PubMed  Google Scholar 

  8. Hartert TV, Windom HH, Peebles Jr RS, et al. Inadequate outpatient medical therapy for patients with asthma admitted to two urban hospitals. Am J Med 1996; 100(4): 386–94

    Article  PubMed  CAS  Google Scholar 

  9. Anderson RN, Ventura SJ, Peters KD, et al. Births and deaths: United States, July 1996–June 1997. Monthly Vital Statistics Report; vol 46(12). Hyattsville (MD): National Center for Health Statistics, 1988

    Google Scholar 

  10. Hall MJ, Owings MF. 2000 National Hospital Discharge Survey. Adv Data 2002; 329: 1–18

    Article  PubMed  Google Scholar 

  11. Centers for Disease Control. Asthma prevalence, health care use and mortality, 2000–2001 [online]. Available from URL: http://www.cdc.gov/nchs/products/pubs/pubd/hestats/asthma/asthma.htm [Accessed 2003 Feb 27]

  12. Coons SJ. Disease management: definitions and exploration of issues. Clin Ther 1996; 18(6): 1321–6

    Article  PubMed  CAS  Google Scholar 

  13. Rossiter LF, Whitehurst-Cook MY, Small RE, et al. The impact of disease management on outcomes and cost of care: a study of low-income asthma patients. Inquiry 2000; 37(2): 188–202

    PubMed  CAS  Google Scholar 

  14. NCQA News. NCQA announces intention to certify disease management programs [online]. 2000 Jun 6. Available from URL: http://www.ncqa.org/communications/news/disease_management.htm [Accessed 2003 Jul 10]

  15. Frigoletto Jr FD, Lieberman E, Lang JM, et al. A clinical trial of active management of labor. N Engl J Med 1995; 333(12): 745–50

    Article  PubMed  Google Scholar 

  16. Gum PA, Thamilarasan M, Watanabe J, et al. Aspirin use and all-cause mortality among patients being evaluated for known or suspected coronary artery disease: a propensity analysis. JAMA 2001; 286(10): 1187–94

    Article  PubMed  CAS  Google Scholar 

  17. Peterson JG, Topol EJ, Roe MT, et al. Prognostic importance of concomitant hepartin with eptifibatide in acute coronary syndromes. Am J Cardiol 2001; 87(5): 532–6

    Article  PubMed  CAS  Google Scholar 

  18. Connors Jr AF, Speroff T, Dawson NV, et al. The effectiveness of right heart catheterization in the initial care of critically ill patients. JAMA 1996; 276(11): 889–97

    Article  PubMed  Google Scholar 

  19. Rothman KJ, Greenland S. Modern epidemiology. 2nd ed. Philadelphia (PA): Lippincott Williams & Williams, 1998

    Google Scholar 

  20. Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies of causal effect. Biometrika 1983; 76: 41–55

    Article  Google Scholar 

  21. Rosenbaum PR, Rubin DB. Reducing bias in observational studies using subclassification on the propensity score. J Am Stat Assoc 1984; 79: 516–24

    Article  Google Scholar 

  22. Rosenbaum PR, Rubin DB. Constructing a control group using multivariate matched sampling methods that incorporate the propensity score. Am Stat 1985; 39: 33–8

    Google Scholar 

  23. Rubin DB, Thomas N. Matching using estimated propensity scores: relating theory to practice. Biometrics 1996; 52(1): 249–64

    Article  PubMed  CAS  Google Scholar 

  24. Dehejia RH, Wahba S. Propensity score-matching methods for nonexperimental causal studies. Rev Econ Stat 2002; 84(1): 151–61

    Article  Google Scholar 

  25. Medicode. International Classification of Diseases. 5th ed. Salt Lake City (UT): Medicode, Inc., 1996

    Google Scholar 

  26. American Medical Association. Current Procedural Terminology 1997. Chicago (IL): Medicode, Inc., 1996

    Google Scholar 

  27. George MR, O’Dowd LC, Martin I, et al. A comprehensive educational program improves clinical outcome measures in inner-city patients with asthma. Arch Intern Med 1999; 159(15): 1710–6

    Article  PubMed  CAS  Google Scholar 

  28. Kelly CS, Morrow AL, Shults J, et al. Outcomes evaluation of a comprehensive intervention program for asthmatic children enrolled I Medicaid. Pediatrics 2000; 105(5): 1029–35

    Article  PubMed  CAS  Google Scholar 

  29. Krishna S, Francisco BD, Balas EA, et al. Internet-enabled interactive multimedia asthma education program: a randomized trial. Pediatrics 2003; 111(3): 503–10

    Article  PubMed  Google Scholar 

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Acknowledgements

The authors were employed by McKesson Corporation in Broomfield, Colorado, USA, at the time of the study.

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Authors and Affiliations

  1. McKesson Corporation, 335 Interlocken Parkway, Broomfield, Colorado, 80021, USA

    Gregory D. Berg (Senior Research Scientist), Alan Johnson & Edward Fleegler

Authors
  1. Gregory D. Berg
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  2. Alan Johnson
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  3. Edward Fleegler
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Correspondence to Gregory D. Berg.

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Berg, G.D., Johnson, A. & Fleegler, E. Clinical and Utilization Outcomes for a Pediatric and Adolescent Telephonic Asthma Care Support Program. Dis-Manage-Health-Outcomes 11, 737–743 (2003). https://doi.org/10.2165/00115677-200311110-00005

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  • DOI: https://doi.org/10.2165/00115677-200311110-00005

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