Methodology for calculating the "proportion of days covered" to determine adherence to pharmacotherapy using data from the accounting of implemented electronic prescriptions of the EMIAS

Adherence is one of the crucial determinants of high-quality and effective pharmacotherapy. Along with the search for optimal methods to improve adherence and with the study of factors influencing it, it remains an equally urgent task to choose the optimal method to evaluate it. In the context of the digitalization of healthcare systems that is actively taking place in many countries, including Russia, the approach based on the analysis of prescription data is of the greatest interest among all known methods of measuring adherence. The calculation of the «proportion of days covered» (PDC) has become the most widespread among the variants of this approach. However, the local adoption of foreign experience of assessing adherence by PDC turned out to be hampered by the presence of significant problems associated with insufficient standardization of the calculation methodology and interpreting the results obtained. The purpose of this work was to develop the standard PDC calculation method based on the EMIAS prescription claims data to increase compliance with the requirements for qualitative studies of medication adherence. The analysis of the literature made it possible to identify and describe the following most significant elements of PDC calculation methodology: (1) minimum fill criterion; (2) evaluation period; (3) method for identifying fill date; (4) calculation of the total number of days in the evaluation period; (5) calculation of the number of days covered with prescriptions; (6) interpretation of PDC calculation results; (7) assessment of multiple adherences. Based on the results of the literature analysis and on the experience of conducted pilot study, in the summary of this paper, an optimal list of recommendations was presented that allows for a qualitative assessment of adherence by PDC methodology.

1. Hughes D, Cowell W, Koncz T, et al. Methods for integrating medication compliance and persistence in pharmacoeconomic evaluations. Value Health. 2007 Nov-Dec;10(6):498-509. doi: 10.1111/j.1524-4733.2007.00205.x.

2. De Geest S, Sabaté E. Adherence to long-term therapies: evidence for action. Eur J Cardiovasc Nurs. 2003 Dec;2(4):323. doi: 10.1016/S1474-5151 (03)00091-4.

3. Basu S, Garg S, Sharma N, Singh MM. Improving the assessment of medication adherence: Challenges and considerations with a focus on low-resource settings. Ci Ji Yi Xue Za Zhi. 2019 Apr-Jun;31(2):73-80. doi: 10.4103/tcmj.tcmj_177_18.

4. Lam WY, Fresco P. Medication Adherence Measures: An Overview. Biomed Res Int. 2015;2015:217047. doi: 10.1155/2015/217047.

5. Williams AB, Amico KR, Bova C, Womack JA. A proposal for quality standards for measuring medication adherence in research. AIDS Behav. 2013 Jan;17(1):284-97. doi: 10.1007/s10461-012-0172-7.

6. Lehmann A, Aslani P, Ahmed R, et al. Assessing medication adherence: options to consider. Int J Clin Pharm. 2014 Feb;36(1):55-69. doi: 10.1007/s11096-013-9865-x.

7. Canfield SL, Zuckerman A, Anguiano RH, et al. Navigating the Wild West of Medication Adherence Reporting in Specialty Pharmacy. J Manag Care Spec Pharm. 2019 Oct;25(10):1073-1077. doi: 10.18553/jmcp.2019.25.10.1073.

8. Loucks J, Zuckerman AD, Berni A, et al. Proportion of days covered as a measure of medication adherence. Am J Health Syst Pharm. 2022 Mar 7;79(6):492-496. doi: 10.1093/ajhp/zxab392.

9. Zabolotnaya NV, Gatilova IN, Zabolotny AT. Digitalization of health: achievements and prospects for development. Economics. Information technologies. 2020;47(2):380-389. (In Russ.)]. doi: 10.18413/2687-0932-2020-47-2-380-389.

10. The application "EMIAS.INFO" is recognized as one of the best experts of the international award. Moscow 2021 website. (In Russ.)]. https://www.mos.ru/news/item/98533073/ (accessed October 13, 2024).

11. Andrade SE, Kahler KH, Frech F, Chan KA. Methods for evaluation of medication adherence and persistence using automated databases. Pharmacoepidemiol Drug Saf. 2006 Aug;15(8):565-74; discussion 575-7. doi: 10.1002/pds.1230.

12. Hess LM, Raebel MA, Conner DA, Malone DC. Measurement of adherence in pharmacy administrative databases: a proposal for standard definitions and preferred measures. Ann Pharmacother. 2006 JulAug;40(7-8):1280-88. doi: 10.1345/aph.1H018.

13. Arnet I, Kooij MJ, Messerli M, et al. Proposal of Standardization to Assess Adherence With Medication Records: Methodology Matters. Ann Pharmacother. 2016 May;50(5):360-8. doi: 10.1177/1060028016634106.

14. Dima AL, Dediu D. Computation of adherence to medication and visualization of medication histories in R with AdhereR: Towards transparent and reproducible use of electronic healthcare data. PLoS One. 2017 Apr 26;12(4):e0174426. doi: 10.1371/journal.pone.0174426.

15. Vollmer WM, Xu M, Feldstein A, et al. Comparison of pharmacy-based measures of medication adherence. BMC Health Serv Res. 2012 Jun 12;12:155. doi: 10.1186/1472-6963-12-155.

16. Nau DP. Proportion of Days Covered (PDC) as a Preferred Method of Measuring Medication Adherence. Published 2011. http://ep.yimg.com/ty/cdn/epill/pdcmpr.pdf (accessed October 13, 2024).

17. Wilke T, Groth A, Mueller S, et al. How to use pharmacy claims data to measure patient nonadherence? The example of oral diabetics in therapy of type 2 diabetes mellitus. Eur J Health Econ. 2013 Jun;14(3):551-68. doi: 10.1007/s10198-012-0410-y.

18. Pednekar PP, Ágh T, Malmenäs M, et al. Methods for Measuring Multiple Medication Adherence: A Systematic Review-Report of the ISPOR Medication Adherence and Persistence Special Interest Group. Value Health. 2019 Feb;22(2):139-156. doi: 10.1016/j.jval.2018.08.006.

19. Steiner JF, Prochazka AV. The assessment of refill compliance using pharmacy records: methods, validity, and applications. J Clin Epidemiol. 1997 Jan;50(1):105-16. doi: 10.1016/s0895-4356(96)00268-5.

20. Spreafico M, Gasperoni F, Barbati G, et al. Adherence to Disease-Modifying Therapy in Patients Hospitalized for HF: Findings from a Community-Based Study. Am J Cardiovasc Drugs. 2020 Apr;20(2):179-190. doi: 10.1007/s40256-019-00367-z.

21. NASP 2019 Annual Meeting & Expo 4th Annual Specialty Pharmacy Law Conference 2019. https://www.quarles.com/newsroom/events/nasp-2019-annual-meeting-expo-4th-annual-specialty-pharmacy-law-conference (accessed October 13, 2024).

22. Andrew Repp. Python, Parallelism, and Medication Adherence. Andrew@ theinternet. https://andrewrepp.com/multipr_pdc_python (accessed October 13, 2024).

23. Habibi M, Kuttab HM. Management of multiple sclerosis and the integration of related specialty pharmacy programs within health systems. Am J Health Syst Pharm. 2016 Jun 1;73(11):811-9. doi: 10.2146/ajhp150723.

24. Paolella D, Cherry E, Jolly JA, et al. Closing the Gap: Identifying Rates and Reasons for Nonadherence in a Specialty Population. J Manag Care Spec Pharm. 2019 Nov;25(11):1282-1288. doi: 10.18553/jmcp.2019.25.11.1282.

25. Order of the Ministry of Health of the Russian Federation No. 911n dated December 24, 2018. On approval of requirements for state information systems in the field of healthcare of the subjects of the Russian Federation, medical information systems of medical organizations and information systems of pharmaceutical organizations. Registered with the Ministry of Justice of the Russian Federation on June 19, 2019 N 54963. (In Russ.)]. Available from: https://docs.cntd.ru/document/552196746 (accessed October 13, 2024).

26. Fitilev SB, Vozzhaev AV, Shkrebniova II, et al. Electronic medical information and analytical system (EMIAS) as a tool for the new level of understanding and diagnosis of medication adherence in patients with myocardial infarction in primary care practice in Moscow. Kachestvennaya Klinicheskaya Praktika = Good Clinical Practice. 2024;(2):16-32. (In Russ.)]. doi: 10.37489/2588-0519-2024-2-16-32.

27. DeClercq J, Choi L. Statistical considerations for medication adherence research. Curr Med Res Opin. 2020;36(9):1549-1557. doi: 10.1080/03007995.2020.1793312.

28. Dalli LL, Kilkenny MF, Arnet I, et al. Towards better reporting of the proportion of days covered method in cardiovascular medication adherence: A scoping review and new tool TEN-SPIDERS. Br J Clin Pharmacol. 2022 Oct;88(10):4427-4442. doi: 10.1111/bcp.15391.

29. Blaschke TF, Osterberg L, Vrijens B, Urquhart J. Adherence to medications: insights arising from studies on the unreliable link between prescribed and actual drug dosing histories. Annu Rev Pharmacol Toxicol. 2012;52:275-301. doi: 10.1146/annurev-pharmtox-011711-113247.

30. Cramer JA, Roy A, Burrell A, et al. Medication compliance and persistence: terminology and definitions. Value Health. 2008 Jan-Feb;11(1):44-7. doi: 10.1111/j.1524-4733.2007.00213.x.

31. Более 37 млн электронных рецептов с QR-кодом выписали московские врачи за два года. TACC. 3 марта 2023. [More than 37 million electronic prescriptions with a QR code were prescribed by Moscow doctors in two years. TASS. March 3, 2023. (In Russ.)]. https://tass.ru/obschestvo/17190617 (accessed October 13, 2024).

32. Raebel MA, Schmittdiel J, Karter AJ, et al. Standardizing terminology and definitions of medication adherence and persistence in research employing electronic databases. Med Care. 2013 Aug;51(8 Suppl 3):S11-21. doi: 10.1097/MLR.0b013e31829b1d2a.

33. Sattler EL, Lee JS, Perri M 3rd. Medication (re)fill adherence measures derived from pharmacy claims data in older Americans: a review of the literature. Drugs Aging. 2013 Jun;30(6):383-99. doi: 10.1007/s40266-013-0074-z.

34. Caetano PA, Lam JM, Morgan SG. Toward a standard definition and measurement of persistence with drug therapy: Examples from research on statin and antihypertensive utilization. Clin Ther. 2006 Sep;28(9):1411-24; discussion 1410. doi: 10.1016/j.clinthera.2006.09.021.

35. Stauffer ME, Hutson P, Kaufman AS, Morrison A. The Adherence Rate Threshold is Drug Specific. Drugs R D. 2017 Dec;17(4):645-653. doi: 10.1007/s40268-017-0216-6.

36. Baumgartner PC, Haynes RB, Hersberger KE, Arnet I. A Systematic Review of Medication Adherence Thresholds Dependent of Clinical Outcomes. Front Pharmacol. 2018 Nov 20;9:1290. doi: 10.3389/fphar.2018.01290.

37. Karve S, Cleves MA, Helm M, et al. Good and poor adherence: optimal cut-point for adherence measures using administrative claims data. Curr Med Res Opin. 2009 Sep;25(9):2303-10. doi: 10.1185/03007990903126833.

38. Oleen-Burkey MA, Dor A, Castelli-Haley J, Lage MJ. The relationship between alternative medication possession ratio thresholds and outcomes: evidence from the use of glatiramer acetate. J Med Econ. 2011;14(6):73947. doi: 10.3111/13696998.2011.618517.

39. Watanabe JH, Bounthavong M, Chen T. Revisiting the medication possession ratio threshold for adherence in lipid management. Curr Med Res Opin. 2013 Mar;29(3):175-80. doi: 10.1185/03007995.2013.766164.

40. Wu JR, Moser DK, De Jong MJ, et al. Defining an evidence-based cutpoint for medication adherence in heart failure. Am Heart J. 2009 Feb;157(2):285-91. doi: 10.1016/j.ahj.2008.10.001.

41. Lo-Ciganic WH, Donohue JM, Thorpe JM, et al. Using machine learning to examine medication adherence thresholds and risk of hospitalization. Med Care. 2015 Aug;53(8):720-8. doi: 10.1097/MLR.0000000000000394.

42. Govani SM, Noureldin M, Higgins PDR, et al. Defining an Optimal Adherence Threshold for Patients Taking Subcutaneous Anti-TNFs for Inflammatory Bowel Diseases. Am J Gastroenterol. 2018 Feb;113(2):276-282. doi: 10.1038/ajg.2017.438.

43. PQA Adherence Measures. https://www.pqaalliance.org/adherence-measures (accessed October 13, 2024).