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Cost Effectiveness of an Adherence-Improving Programme in Hypertensive Patients

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Abstract

Background

Non-adherence to antihypertensive drugs is high, and the economic consequences of non-adherence may be substantial. The Medication Events Monitoring System (MEMS), which is a method to improve adherence, has been shown to be a useful tool for the management of adherence problems.

Objective

To assess the cost effectiveness of the MEMS compared with usual care in a population of hypertensive patients with poor adherence. The MEMS programme consisted of provision of containers fitted with electronic caps together with adherence training if indicated.

Methods

In a randomised controlled trial, 164 hypertensive patients in the experimental strategy and 89 patients in the usual care strategy were followed for 5 months. Patients who had a systolic blood pressure (SBP) ≥160mm Hg and/or diastolic BP (DBP) ≥95mm Hg despite the use of antihypertensive drugs were eligible. Patients were recruited by a GP, and treatment took place in general practice.

In the experimental strategy, electronic monitoring of the intake of antihypertensive drugs was introduced without change of medication. Unsatisfactory adherence was defined as <85% of days with the number of doses taken as prescribed. In the usual care strategy, antihypertensive treatment was intensified by the addition or change of antihypertensive drugs, if necessary, without provision of an electronic monitor.

Outcome parameters included the proportion of patients with normalised blood pressure (NBP) at 5 months and QALYs. Costs were quantified from the healthcare and societal perspective. Non-parametric bootstrap simulations were per formed to quantify the uncertainty around the mean estimates and cost-effectiveness acceptability curves were presented. In addition, a number of univariate sensitivity analyses were performed on deterministic variables.

Results

At 5 months, 3.1% (95% UI [uncertainty interval] −9.7%, +15.8%) more patients had NBP, and 0.003 (95% UI −0.005, +0.010) more QALYs were generated in the experimental strategy. A statistically significant lower percentage of patients had a dose escalation in the experimental strategy. Irrespective of the ceiling ratio for cost effectiveness, the cost-effectiveness probability was between 75% and 80% for the analysis from the healthcare perspective using proportion of patients with NBP as the outcome parameter. For the analysis from the societal perspective using QALYs as the outcome parameter, this probability was between 45% and 51%.

Conclusion

For a time horizon of 5 months, a difference in both cost and effect could not be detected between an adherence-improving programme compared with usual care for hypertensive patients. The probability that the adherence-improving programme is cost effective is at best moderate. Moreover, the costeffectiveness result is surrounded with considerable uncertainty and large-scale implementation warrants additional research into the economic consequences of this intervention. Patients may benefit from the use of a MEMS monitor in situations where BP targets are not reached because of suspected non-adherence and both patient and GP are reluctant to increase the dose or number of antihypertensive drugs.

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References

  1. Hunt JS, Siemienczuk J, Touchette D, et al. Impact of educational mailing on the BP of primary care patients with mild hypertension. J Gen Intern Med 2004; 19: 925–930

    Article  PubMed  Google Scholar 

  2. Urquhart J. Patient non-compliance with drug regimens: measurement, clinical correlates, economic impact. Eur Heart J 1996; 17 Suppl. A: 8–15

    Article  PubMed  Google Scholar 

  3. Gascón JJ, Sánchez-Ortuno M, Llor B, et al. for the Treatment Compliance in Hypertension Study Group. Why hypertensive patients do not comply with the treatment: results from a qualitative study. Fam Pract 2004; 21 (2): 125–130

    Article  PubMed  Google Scholar 

  4. Herings RMC, Leufkens HGM, Heerdink ER, et al. Chronic pharmacotherapy continued: pharmo report [in Dutch]. The Hague: CIP data Royal Library, 2002

    Google Scholar 

  5. Psaty BM, Koepsell TD, Yanez ND, et al. Temporal patterns of antihypertensive medication use among older adults, 1989 through 1992: an effect of the major clinical trials on clinical practice? JAMA 1995; 273: 1436–1438

    Article  CAS  PubMed  Google Scholar 

  6. Caro JJ, Speckman JL, Salas M, et al. Effect of initial drug choice on the persistence with antihypertensive treatment: the importance of actual practice data. Can Med Assoc J 1999; 16: 41–46

    Google Scholar 

  7. Wolf-Maier K, Cooper RS, Banegas JR, et al. Hypertension prevalence and BP levels in 6 European countries, Canada, and the United States. JAMA 2003; 289: 2363–2369

    Article  PubMed  Google Scholar 

  8. Rudd P, Byyny RL, Zachary V, et al. Pill count measures of compliance in a drug trial: variability and suitability. Am J Hypertens 1988; 1: 309–312

    Article  CAS  PubMed  Google Scholar 

  9. Maenpaa H, Manninen V, Heinonen OP. Comparison of the digoxin marker with capsule counting and compliance questionnaire methods for measuring compliance to medication in a clinical trial. Eur J Clin Pharmacol 1990; 38: 561–565

    Article  Google Scholar 

  10. Roter DL. Hall JA, Merisca R, et al. Effectiveness of interventions to improve patient compliance: a meta-analysis. Med Care 1998; 36: 1138–1161

    Article  CAS  PubMed  Google Scholar 

  11. Schroeder K, Fahey T, Ebrahim S. How can we improve adherence to BP lowering medication in ambulatory care? Systematic review of randomized controlled trials. Arch Intern Med 2004; 164: 722–732

    Article  PubMed  Google Scholar 

  12. Takiya LN, Peterson AM, Finley RS. Meta-analysis of interventions for medication adherence to antihypertensives. Ann Pharmacother 2004; 38: 1617–1624

    Article  PubMed  Google Scholar 

  13. Urquhart J. The electronic medication event monitoring: lessons for pharmacotherapy. Clin Pharmacokinet 1997; 32: 245–256

    Article  Google Scholar 

  14. Burnier M, Schneider MP, Chiolero A, et al. Electronic adherence monitoring in resistant hypertension: the basis for rational therapeutic decisions. J Hypertens 2001; 19: 335–341

    Article  CAS  PubMed  Google Scholar 

  15. Waeber B, Vetter W, Darioli R, et al. Improved BP control by monitoring adherence with antihypertensive treatment. Int J Clin Pract 1999; 53: 37–38

    CAS  PubMed  Google Scholar 

  16. Cramer JA, Ouelette VL, Mattson RH. Effect of microelectronic observation on compliance. Epilepsia 1990; 31: 617–618

    Google Scholar 

  17. Bertholet N, Favrat B, Fallab-Studbi CL, et al. Why objective monitoring of compliance is important in the management of hypertension. J Clin Hypertens 2000; 2 (4): 258–262

    Google Scholar 

  18. Bovet P, Burnier M, Madelaine G, et al. Monitoring one-year compliance to antihypertension medication in the Seychelles. Bull World Health Organ 2002; 80: 33–39

    PubMed  Google Scholar 

  19. Leenen FHH, Wilson TW, Bolli P, et al. Patterns of compliance with once versus twice daily antihypertensive drug therapy in primary care: a randomized clinical trial using electronic monitoring. Can J Cardiol 1997; 13 (10): 914–920

    CAS  PubMed  Google Scholar 

  20. Schwed A, Fallab C-L, Burnier M, et al. Electronic monitoring of compliance to lipid-lowering therapy in clinical practice. J Clin Pharmacol 1999; 39: 402–409

    Article  CAS  PubMed  Google Scholar 

  21. Mallion JM, Dutrey-Dupagne C, Vaur L, et al. Benefits of electronic pillboxes in evaluating treatment compliance of patients with mild to moderate hypertension. J Hypertens, 1996; 14: 137–144

    CAS  PubMed  Google Scholar 

  22. Cramer JA, Rosenbeck R. Enhancing medication compliance for people with serious mental illness. J Nerv Ment Dis 1999; 187: 53–55

    Article  CAS  PubMed  Google Scholar 

  23. Elixhauser A, Eisen SA, Romeis JC, et al. The effects of monitoring and feedback on compliance. Med Care 1990; 28: 882–893

    Article  CAS  PubMed  Google Scholar 

  24. Nides MA, Tadhkin DP, Simmons MS, et al. Improving inhaler adherence in a clinical trail through the use of the nebulizer chronology. Chest 1993; 104: 501–507

    Article  CAS  PubMed  Google Scholar 

  25. Schmitz JM, Sayre SL, Stotts AL, et al. Medication compliance during a smoking cessation trial: a brief intervention using MEMS feedback. J Behav Med 2005; 28 (2): 139–147

    Article  PubMed  Google Scholar 

  26. Cantor JC, Morisky DE, Green LW, et al. Cost-effectiveness of educational interventions to improve patient outcomes in BP control. Prevent Med 1985; 14: 782–800

    Article  CAS  Google Scholar 

  27. Eastaugh SR, Hatcher ME. Improving compliance among hypertensives: a triage criterion with cost-benefit implications. Med Care 1982; 20: 1001–1007

    Article  CAS  PubMed  Google Scholar 

  28. Logan AG, Milne BJ, Achber C, et al. Cost-effectiveness of a worksite hypertension treatment program. Hypertension 1981; 3: 211–218

    Article  CAS  PubMed  Google Scholar 

  29. Friedman RH, Kazis L, Jette A, et al. A telecommunications system for monitoring and counseling patients with hypertension: impact on medication adherence and BP control. Am J Hypertens 1996; 9: 285–292

    Article  CAS  PubMed  Google Scholar 

  30. Zarnke KB, Feagen BG, Mahon J, et al. A randomized study comparing a patient-directed hypertension management strategy with usual office-based care. Am J Hypertens 1997; 10: 58–57

    Article  CAS  PubMed  Google Scholar 

  31. Chobanian AV, Bakris GL, Black HR, et al. The seventh report of the Joint National Committee on Prevention, Detection, Evaluation and Treatment of High Blood Pressure: the JNC 7 report. JAMA 2003; 289: 2560–2572

    Article  CAS  PubMed  Google Scholar 

  32. Wetzels GEC, Nelemans PJ, Schouten JSAG, et al. Electronic monitoring of adherence as a tool to improve blood pressure control: a randomized controlled trial. Ann J Hypertens 2007 Feb; 20 (2): 119–125

    Article  Google Scholar 

  33. Hughes DA, Bagust A, Haycox A, et al. The impact of non-compliance on the cost-effectiveness of pharmaceuticals: a review of the literature. Health Econ 2001; 10: 601–615

    Article  CAS  PubMed  Google Scholar 

  34. Gold MR, Siegel JE, Russell LB, et al. Cost-effectiveness in health and medicine. Oxford: Oxford University Press, 1996

    Google Scholar 

  35. Drummond MF, O’Brien B, Stoddart GL, et al. Methods for the economic evaluation of health care programs. 3rd ed. Toronto: Oxford University Press, 2005

    Google Scholar 

  36. Goossens MEJB, Rutten-van Molken MP, Laeyen JW, et al. The cost diary: a method to measure direct and indirect costs in cost effectiveness research. J Clin Epidemiol 2000; 53: 688–695

    Article  CAS  PubMed  Google Scholar 

  37. Health Insurance Board (in Dutch) [online]. Available from URL: http://www.medicijnkosten.nl [Accessed 2005 May 25]

  38. Kenniscentrum voor leren in de praktijk [online]. http://www.gobnet.nl [Accessed 2007 Jan 28]

  39. Oostenbrink JB, Bouwmans CAM, Koopmanschap MA, et al. Manual for cost research, methods and standard cost prices for economic evaluations in health care. Diemen: Health Insurance Board, 2004

    Google Scholar 

  40. Klungel OH, de Boer A, Paes AHP, et al. Undertreatment of hypertension in a population-based study in The Netherlands. J Hypertens 1998; 16: 1371–1378

    Article  CAS  PubMed  Google Scholar 

  41. Koopmanschap MA, Rutten FF. A practical guide for calculating indirect costs of disease. Pharmacoeconomics 1996; 10 (5): 460–466

    Article  CAS  PubMed  Google Scholar 

  42. EuroQol-Group. EuroQol: a new facility for the measurement of health-related quality of life. Health Policy 1990; 16 (3): 199–208

    Article  Google Scholar 

  43. Dolan P. A social tariff for EuroQol: results from a UK population survey. York: University of York, 1995

    Google Scholar 

  44. Russell LB, Gold MR, Siegel JE, et al. The role of cost-effectiveness analysis in health and medicine. Panel on Cost-Effectiveness in Health and Medicine. JAMA 1996; 276: 1172–1177

    Article  CAS  PubMed  Google Scholar 

  45. Manca A, Hawkins N, Sculpher MJ. Estimating mean QALYs in trial-based cost-effectiveness analysis: the importance of controlling for baseline utility. Health Econ 2005; 14 (5): 487–496

    Article  PubMed  Google Scholar 

  46. Little R, Rubin D. Statistical analysis with missing data. New York: Wiley, 1987

    Google Scholar 

  47. Briggs AH, Wonderling DE, Mooney CZ. Pulling cost-effectiveness analysis up by its bootstraps: a non-parametric approach to confidence interval estimation. Health Econ 1997; 6 (4): 327–340

    Article  CAS  PubMed  Google Scholar 

  48. van Hout BA, Al MJ, Gordon GS, et al. Costs, effects and C/E-ratios alongside a clinical trial. Health Econ 1994; 3 (5): 309–319

    Article  PubMed  Google Scholar 

  49. Stinnett AA, Mullahy J. Net health benefits: a new framework for the analysis of uncertainty in cost-effectiveness analysis. Med Decis Making 1998; Suppl. 18: S68–S80

    Google Scholar 

  50. O’Brien BJ, Gertsen K, Willan AR, et al. Is there a kink in consumer’s threshold value for cost-effectiveness in health care? Health Econ 2002; 11: 175–180

    Article  PubMed  Google Scholar 

  51. Severens JL, Brunenberg DEM, Fenwick EAL, et al. Cost-effectiveness acceptability curves and a reluctance to lose. Pharmacoeconomics 2005; 23 (12): 1207–1214

    Article  PubMed  Google Scholar 

  52. Briggs AH, O’Brien BJ. The death of cost-minimization analysis? Health Econ 2001; 10 (2): 179–184

    Article  CAS  PubMed  Google Scholar 

  53. Welte R, Feenstra T, Jager H, et al. Decision chart for assessing and improving the transferability of economic evaluation results between countries. Pharmacoeconomics 2004; 22 (13): 85–76

    Article  Google Scholar 

Download references

Acknowledgements

This study was funded by an unconditional grant from the Health Care Insurance Board. The funding organisation had no role in design and conduct of the study, data collection and management, data analysis, interpretation of the data or preparation of the manuscript. The authors have no conflicts of interest that are directly relevant to the content of this study. The authors would like to thank Claudia Gulikers for data collection and data management, and all participating GPs and patients for their cooperation and effort.

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Brunenberg, D.E.M., Wetzels, G.E.C., Nelemans, P.J. et al. Cost Effectiveness of an Adherence-Improving Programme in Hypertensive Patients. Pharmacoeconomics 25, 239–251 (2007). https://doi.org/10.2165/00019053-200725030-00006

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