Currently Viewing:
The American Journal of Managed Care June 2018
Prevalence and Predictors of Hypoglycemia in South Korea
Sun-Young Park, PhD; Eun Jin Jang, PhD; Ju-Young Shin, PhD; Min-Young Lee, PhD; Donguk Kim, PhD; and Eui-Kyung Lee, PhD
Initial Results of a Lung Cancer Screening Demonstration Project: A Local Program Evaluation
Angela E. Fabbrini, MPH; Sarah E. Lillie, PhD, MPH; Melissa R. Partin, PhD; Steven S. Fu, MD, MSCE; Barbara A. Clothier, MS, MA; Ann K. Bangerter, BS; David B. Nelson, PhD; Elizabeth A. Doro, BS; Brian J. Bell, MD; and Kathryn L. Rice, MD
Currently Reading
A Longitudinal Examination of the Asthma Medication Ratio in Children
Annie Lintzenich Andrews, MD, MSCR; Daniel Brinton, MHA, MAR; Kit N. Simpson, DrPH; and Annie N. Simpson, PhD
Simply Delivered Meals: A Tale of Collaboration
Sarah L. Martin, PhD; Nancy Connelly, MBA; Cassandra Parsons, PharmD; and Katlyn Blackstone, MS, LSW
Placement of Selected New FDA-Approved Drugs in Medicare Part D Formularies, 2009-2013
Bruce C. Stuart, PhD; Sarah E. Tom, PhD; Michelle Choi, PharmD; Abree Johnson, MS; Kai Sun, MS; Danya Qato, PhD; Engels N. Obi, PhD; Christopher Zacker, PhD; Yujin Park, PharmD; and Steve Arcona, PhD
Identifying Children at Risk of Asthma Exacerbations: Beyond HEDIS
Jonathan Hatoun, MD, MPH, MS; Emily K. Trudell, MPH; and Louis Vernacchio, MD, MS
Assessing Markers From Ambulatory Laboratory Tests for Predicting High-Risk Patients
Klaus W. Lemke, PhD; Kimberly A. Gudzune, MD, MPH; Hadi Kharrazi, MD, PhD, MHI; and Jonathan P. Weiner, DrPH
Satisfaction With Care After Reducing Opioids for Chronic Pain
Adam L. Sharp, MD, MS; Ernest Shen, PhD; Yi-Lin Wu, MS; Adeline Wong, MPH; Michael Menchine, MD, MS; Michael H. Kanter, MD; and Michael K. Gould, MD, MS
Cost Sharing for Antiepileptic Drugs: Medication Utilization and Health Plan Costs
Nina R. Joyce, PhD; Jesse Fishman, PharmD; Sarah Green, BA; David M. Labiner, MD; Imane Wild, PhD, MBA; and David C. Grabowski, PhD

A Longitudinal Examination of the Asthma Medication Ratio in Children

Annie Lintzenich Andrews, MD, MSCR; Daniel Brinton, MHA, MAR; Kit N. Simpson, DrPH; and Annie N. Simpson, PhD
This longitudinal examination of the asthma medication ratio in a national sample of children has determined the predictive accuracy of a rolling 3-month ratio.
DISCUSSION

This longitudinal analysis of the AMR in a large cohort of privately insured children with asthma supports the rolling AMR calculation as a practical approach to risk assessment. This approach is superior to a cross-sectional fixed-AMR calculation period approach as it allows for risk category assignment based on the most recent available claims data. When applied to this cohort of privately insured children with asthma, the rolling 3-month calculation approach identified approximately 5% of the population as being at high risk for exacerbation in any given period.

As the AMR calculation period decreases (from 12 to 6 to 3 months), a larger proportion of patients have missing AMRs in any given period. To have a missing AMR, the patient must not have any claims for rescue or controller medications in the AMR calculation period. The higher proportion of patients with missing AMRs in the 3-month approach suggests that the 6-month AMR calculation approach might be superior to the 3-month approach. However, further investigation supports the 3-month approach. First, we demonstrated that children with missing AMRs are less likely to have an ED visit or hospitalization for asthma compared with children with both low-risk and high-risk AMRs. These children appear to have relatively inactive asthma, illustrated by their absence of asthma medication claims and low rate of emergent care visits. This raises the idea that some children do not necessarily remain persistent asthmatics for long periods, reflecting variation in their asthma control. They may require controller medications most of the time, but they may also have periods of disease inactivity where they do fine without controller medications. Recognizing these patients clinically will be a challenge, however. We suggest that children with missing AMRs can be treated like children with low-risk AMRs in future interventional studies. Second, our regression analysis illustrates that the 3-month AMR has a stronger relationship to the outcome of ED visit or hospitalization for asthma compared with the 6-month AMR. However, both are statistically significant, suggesting that a 6-month AMR approach would be valid and acceptable.

Differences in adherence patterns between patients with ICS versus those with ICS/LABA raise the question of whether or not these 2 populations can be handled the same way in an AMR-based intervention study. There are several potential reasons that the latter group has better controller medication adherence than the ICS group. The NHLBI Guidelines for the Diagnosis and Management of Asthma recommend subspecialist consultation for any child requiring “Step 4” therapy, which includes ICS/LABAs.19 Therefore, these children are likely to have more severe baseline disease and to have been seen by a subspecialist than are children on ICS therapy alone. The cumulative medication adherence messaging that ICS/LABA patients receive might be more extensive and more effective than the messaging that ICS patients receive.

Because of our method of index date assignment, our study highlights the issue of AMR inflation. In a rolling approach with shorter AMR calculation periods, an initial month with a controller claim would be dropped as soon as the next month’s claims data are available, allowing for a more accurate AMR-based risk assessment. There is less potential for inflation with shorter rolling calculation periods.

Limitations

This study has several limitations. First, we used administrative claims data for this analysis. Claims data lack the clinical detail that might be found in other data sources, such as electronic health records. However, claims data remain the most accurate source for determining medication adherence patterns in large populations of patients. Our method of cohort identification is novel; therefore, our findings cannot be directly compared with those of previous AMR studies that have used HEDIS criteria for cohort identification. As outlined above, we feel that the presence of an ICS claim in the absence of a cystic fibrosis diagnosis will identify an appropriate cohort of children with asthma who could potentially benefit from AMR monitoring in addition to monitoring of the National Quality Forum Medication Management for People with Asthma measure of the percentage of persistent asthmatics who were dispensed an asthma controller medication that they remained on for at least 75% of their treatment period.20 As with all research that utilizes administrative claims data, we do not know what happened before the first day in our database. It is likely that many of the children who were assigned an index date in January 2013 (the first month of our data) had controller claims well before that date. This may have affected our subgroup analysis by season. Unfortunately, there is no way to mitigate this challenge of working with administrative claims data. We do not feel that this issue significantly impacts our primary findings. We were not able to determine prescription writing patterns from these data; therefore, we do not know to what degree a patient’s filling behavior contributes to controller medication nonadherence. Prescriptions that are not paid by the insurance company (ie, free samples or those paid out-of-pocket by the caregiver) would not be included in these data. We are unable to generalize our findings to publicly insured populations, as this analysis was limited to privately insured patients. Finally, the MarketScan database does not include a race or ethnicity variable; therefore, we are unable to determine differences in AMR patterns by race or ethnicity.

CONCLUSIONS

In this longitudinal examination of the AMR in a large cohort of privately insured children with asthma, we determined that the rolling 3-month AMR approach will identify approximately 5% of children as high-risk in any given period. Patients with no asthma medication claims in any given AMR calculation period appear to be at low risk for exacerbation, suggesting that their asthma is inactive. These findings lay the groundwork for future asthma medication adherence interventional studies utilizing real-time monitoring of pharmacy dispensing data embedded within the electronic health record.

Author Affiliations: Department of Pediatrics, College of Medicine (ALA), and Department of Healthcare Leadership and Management, College of Health Professions (DB, KNS, ANS), Medical University of South Carolina, Charleston, SC.

Source of Funding: This research was supported by the South Carolina Clinical and Translational Research (SCTR) Institute, with an academic home at the Medical University of South Carolina, National Institutes of Health/National Center for Advancing Translational Sciences (grants KL2 TR001452 and UL1 TR001450) and the Doris Duke Charitable Foundation (grant 2015209).

Author Disclosures: The authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (ALA, KNS, ANS); acquisition of data (ALA, KNS); analysis and interpretation of data (ALA, DB, ANS); drafting of the manuscript (ALA, ANS); critical revision of the manuscript for important intellectual content (ALA, DB, KNS, ANS); statistical analysis (ALA, DB, ANS); obtaining funding (ALA); and supervision (KNS).

Address Correspondence to: Annie Lintzenich Andrews, MD, MSCR, Medical University of South Carolina, 135 Rutledge Ave, MSC 561, Charleston, SC 29425. Email: andrewsan@musc.edu.
REFERENCES

1. Akinbami LJ, Moorman JE, Bailey C, et al. Trends in asthma prevalence, health care use, and mortality in the United States, 2001-2010. NCHS Data Brief. 2012;(94):1-8.

2. Adams RJ, Fuhlbrigge A, Finkelstein JA, et al. Impact of inhaled antiinflammatory therapy on hospitalization and emergency department visits for children with asthma. Pediatrics. 2001;107(4):706-711. doi: 10.1542/peds.107.4.706.

3. Cloutier MM, Hall CB, Wakefield DB, Bailit H. Use of asthma guidelines by primary care providers to reduce hospitalizations and emergency department visits in poor, minority, urban children. J Pediatr. 2005;146(5):591-597. doi: 10.1016/j.jpeds.2004.12.017.

4. Rachelefsky G. Inhaled corticosteroids and asthma control in children: assessing impairment and risk. Pediatrics. 2009;123(1):353-366. doi: 10.1542/peds.2007-3273.

5. Andrews AL, Teufel RJ 2nd, Basco WT Jr. Low rates of controller medication initiation and outpatient follow-up after emergency department visits for asthma. J Pediatr. 2012;160(2):325-330. doi: 10.1016/j.jpeds.2011.07.037.

6. Lintzenich A, Teufel RJ 2nd, Basco WT Jr. Under-utilization of controller medications and poor follow-up rates among hospitalized asthma patients. Hosp Pediatr. 2011;1(1):8-14. doi: 10.1542/hpeds.2011-0002.

7. Kenyon CC, Rubin DM, Zorc JJ, Mohamad Z, Faerber JA, Feudtner C. Childhood asthma hospital discharge medication fills and risk of subsequent readmission. J Pediatrics. 2015;166(5):1121-1127. doi: 10.1016/j.jpeds.2014.12.019.

8. Andrews AL, Bundy DG, Simpson KN, Teufel RJ 2nd, Harvey J, Simpson AN. Inhaled corticosteroid claims and outpatient visits after hospitalization for asthma among commercially insured children. Acad Pediatr. 2017;17(2):212-217. doi: 10.1016/j.acap.2016.10.016.

9. Schatz M, Nakahiro R, Crawford W, Mendoza G, Mosen D, Stibolt TB. Asthma quality-of-care markers using administrative data. Chest. 2005;128(4):1968-1973. doi: 10.1378/chest.128.4.1968.

10. Schatz M, Zeiger RS, Vollmer WM, et al. The controller-to-total asthma medication ratio is associated with patient-centered as well as utilization outcomes. Chest. 2006;130(1):43-50. doi: 10.1378/chest.130.1.43.

11. Stanford RH, Shah MB, D’Souza AO, Schatz M. Predicting asthma outcomes in commercially insured and Medicaid populations? Am J Manag Care. 2013;19(1):60-67.

12. Andrews AL, Simpson AN, Basco WT Jr, Teufel RJ 2nd. Asthma medication ratio predicts emergency department visits and hospitalizations in children with asthma. Medicare Medicaid Res Rev. 2013;3(4):mmrr.003.04.a05. doi: 10.5600/mmrr.003.04.a05.

13. Broder MS, Gutierrez B, Chang E, Meddis D, Schatz M. Ratio of controller to total asthma medications: determinants of the measure. Am J Manag Care. 2010;16(3):170-178.

14. Vernacchio L, Trudell EK, Muto JM. Correlation of care process measures with childhood asthma exacerbations. Pediatrics. 2012;131(1):e136-e143. doi: 10.1542/peds.2012-1144.

15. Beck AF, Bradley CL, Huang B, Simmons JM, Heaton PC, Kahn RS. The pharmacy-level asthma medication ratio and population health. Pediatrics. 2015;135(6):1009-1017. doi: 10.1542/peds.2014-3796.

16. Fuhlbrigge A, Carey VJ, Adams RJ, et al. Evaluation of asthma prescription measures and health system performance based on emergency department utilization. Med Care. 2004;42(5):465-471. doi: 10.1097/01.mlr.0000124249.84045.d7.

17. Schatz M, Zeiger RS, Yang SJ, et al. Relationship of asthma control to asthma exacerbations using surrogate markers within a managed care database. Am J Manag Care. 2010;16(5):327-333.

18. Mosen DM, Macy E, Schatz M, et al. How well do the HEDIS asthma inclusion criteria identify persistent asthma? Am J Manag Care. 2005;11(10):650-654.

19. National Asthma Education and Prevention Program. Expert Panel Report 3 (EPR-3): Guidelines for the Diagnosis and Management of Asthma-summary report 2007 [update in J Allergy Clin Immunol. 2008;121(6):1330. doi: 10.1016/j.jaci.2008.04.033]. J Allergy Clin Immunol. 2007;120(suppl 5):S94-S138. doi: 10.1016/j.jaci.2007.09.043.

20. Medication management for people with asthma: percentage of members 5 to 85 years of age during the measurement year who were identified as having persistent asthma and who were dispensed an asthma controller medication that they remained on for at least 75% of their treatment period. Agency for Healthcare Research and Quality website. qualitymeasures.ahrq.gov/summaries/summary/49707/medication-management-for-people-with-asthma-percentage-of-members-5-to-85-years-of-age-during-the-measurement-year-who-were-identified-as-having-persistent-asthma-and-who-were-dispensed-an-asthma-controller-medication-that-they-remained-on-for-at-least-75-of-. Published October 2015. Accessed September 28, 2017.
PDF
 
Copyright AJMC 2006-2019 Clinical Care Targeted Communications Group, LLC. All Rights Reserved.
x
Welcome the the new and improved AJMC.com, the premier managed market network. Tell us about yourself so that we can serve you better.
Sign Up