Research and Reports Assessing Medicare Beneficiaries’ Willingness-to-Pay for Medication Therapy Management Services Joseph A. Woelfel, Sian M. Carr-Lopez, Melanie Delos Santos, Ann Bui, Rajul A. Patel, Mark P. Walberg, Suzanne M. Galal Objectives: To assess Medicare beneficiaries’ willingnessto-pay (WTP) for medication therapy management (MTM) services and determine sociodemographic and clinical characteristics influencing this payment amount. Design: A cross-sectional, descriptive study design was adopted to elicit Medicare beneficiaries’ WTP for MTM. Setting: Nine outreach events in cities across Central/Northern California during Medicare’s 2011 open-enrollment period. Participants: A total of 277 Medicare beneficiaries participated in the study. Interventions: Comprehensive MTM was offered to each beneficiary. Pharmacy students conducted the MTM session under the supervision of licensed pharmacists. At the end of each MTM session, beneficiaries were asked to indicate their WTP for the service. Medication, self-reported chronic conditions, and beneficiary demographic data were collected and recorded via a survey during the session. Results: The mean WTP for MTM was $33.15 for the 277 beneficiaries receiving the service and answering the WTP question. WTP by low-income subsidy recipients (mean ± standard deviation; $12.80 ± $24.10) was significantly lower than for nonsubsidy recipients ($41.13 ± $88.79). WTP was significantly (positively) correlated with number of medications regularly taken and annual out-of-pocket drug costs. Conclusion: The mean WTP for MTM was $33.15. WTP for MTM significantly varied by race, subsidy status, and number of prescription medications taken. WTP was significantly higher for nonsubsidy recipients than subsidy recipients, and significantly positively correlated with the number of medications regularly taken and the beneficiary rating of the delivered services. Key Words: Out-of-pocket, Medicare Part D, Medication therapy management, Willingness-to-pay.
104
Abbreviations: CMS = Centers for Medicare & Medicaid
Services, MTM = Medication therapy management, OOP = Out-of-pocket, QOL = Quality of life, WTP = Willingness-to-pay. Consult Pharm 2014;29:104-9.
Introduction Medication therapy management (MTM) is a service that optimizes individual patient therapeutic outcomes by managing drug therapy. The goal of MTM programs is to identify, prevent, and resolve medication-related problems.1 The Centers for Medicare & Medicaid Services (CMS) view MTM as a clinical service and require Medicare Part D plan sponsors to establish a MTM program. While provided services and interventions may vary across MTM program models, the eligibility criteria cannot.2 In order to meet the CMS-mandated eligibility criteria for receipt of MTM through a Medicare Part D plan, beneficiaries must have multiple chronic conditions, take multiple Medicare Part D drugs, and be likely to incur annually covered Medicare Part D drug costs exceeding a predetermined level ($3,144 in 2013). A 1995 landmark study projected the cost associated with drug therapy problems amounted to $76.6 billion, later updated to $177.4 billion.3,4 Community pharmacist MTM was beneficial in reducing physician visits, emergency department visits, and hospital admissions.5 Prior studies have addressed patients’, 18 years of age and older, willingness-to-pay (WTP) for MTM services.6,7 Unlike previous studies, our study assesses a Medicare population’s WTP for MTM. We examined WTP after receipt of such services and WTP as a function of different sociodemographic and health-related variables.
Objectives The purposes of this study were to investigate and quantify WTP for MTM in a Medicare beneficiary population. Additionally, the study sought to determine if WTP for MTM varies as a function of the number of medications taken, the number of self-reported chronic conditions, the patient’s physical and mental quality-of-life, his or her out-of-pocket (OOP) drug costs, rating of our efforts, time spent with beneficiaries, and various sociodemographic
The Consultant Pharmacist FEbruary 2014 Vol. 29, No. 2
Medicare Beneficiaries’ Willingness-to-Pay for MTM Services
variables. We hypothesized that beneficiaries would be willing to pay for MTM; however, their WTP would be dependent on various sociodemographic and clinical variables.
Methods Study Design A cross-sectional study design was conducted to elicit Medicare beneficiaries’ WTP for MTM. Nine outreach events in four urban Central/Northern Californian cities (Lodi, Modesto, San Jose, Stockton) were held during the 2011 Medicare Part D annual enrollment period during which 401 beneficiaries were assisted. The outreach events were publically advertised by flyers and newspaper advertisements, as well as radio and television announcements. Outreach/Data Collection Forty student pharmacists, trained in a specialized Medicare elective courses, (didactic education and casebased simulations) conducted MTM for beneficiaries under the supervision of licensed pharmacists. A standardized data collection tool was used to record de-identified beneficiary data. The tool included open-ended questions, visible to and read to each participant by students. The data-collection tool was designed to identify beneficiaries’ sociodemographic and clinical data, along with their quantified WTP for MTM. Patients’ self-reported chronic conditions and their complete medication profiles were used to identify those with cognitive impairment. The WTP question was asked after provision of MTM. The study was conducted under a University of the Pacificapproved institutional review board protocol. Interventions Demographic data were collected prior to starting the MTM intervention. Each beneficiary was administered the SF-36v2 Heath Survey-Standard Recall (SF-36v2; Quality Metric Incorporated [Lincoln, RI]) to assess their quality of life (QOL).
During the MTM session, beneficiaries’ specific prescription drugs and over-the-counter medications were analyzed for: expired medications, drug-drug interactions, side effects, contraindications, 2003 Beers criteria drugs, therapeutic duplication, and untreated conditions. Electronic drug information resources, Lexicomp, Micromedex, E-facts, and/or Clinical Pharmacology, were used during the intervention as online references. Whenever severe medication-related issues or cost-savings opportunities were identified, and with the beneficiary’s permission, his or her pharmacy and/or prescriber were contacted with specific findings/recommendations. At the end of the MTM intervention each beneficiary was asked, “If offered by your pharmacist or pharmacy, how much would you be willing to pay to have someone go through all of your medications as we did today?” Before leaving, each beneficiary was asked to rate the MTM services, using a 5-point Likert scale (1 = Excellent and 5 = Poor).
Data Analysis Descriptive statistics were recorded for beneficiary and interventional data. The normality of numerical data was tested by the K-S statistic. Mann-Whitney U (for pairwise comparisons) or Kruskal Wallis (for three or more groups) tests were used to determine differences in WTP between different demographic categories. Pairwise Mann-Whitney U tests were performed if Kruskal Wallis tests were significant using a Bonferroni-corrected P-value. Spearman’s rho was used to determine the correlation between WTP and variables of interest. Statistical analyses were conducted using SPSS version 18.0 (SPSS Inc., Chicago, IL).
Results A total of 277 (69% response rate) beneficiaries answered the study questions and comprised the study sample. The mean (standard deviation) WTP was $33.15 ($77.33). Forty-four percent (121/277) of respondents were not willing to pay for MTM. Demographic data and WTP for MTM as a function of demographic characteristics are displayed in Table 1. Significant differences in WTP were observed for race (white versus nonwhite individuals [P < 0.001]), subsidy status (recipients versus nonrecipients
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Research and Reports [P < 0.001]), number of prescription medications (individuals taking more than six medications compared with those taking five to six [P < 0.006]). Table 2 reports the bivariate relationship between beneficiaries’ WTP for MTM and number of medications, number of self-reported chronic conditions, physical and mental component summary scores (QOL), educational attainment, OOP drug costs (estimated annual cost), and rating of our efforts. Significant positive correlations were seen between WTP and number of medications regularly taken (P = 0.030), annual OOP drug costs (P < 0.001), and rating of services offered (P = 0.005). Bivariate data analysis identified additional variables that were significantly correlated with WTP. These included: race (white versus nonwhite), subsidy status, number of prescription medications taken, and rating of our efforts (Table 2). Age, gender, education level, number of self-reported chronic conditions, physical and mental quality-of-life measures, and amount of time spent with a beneficiary during MTM were not significantly related to beneficiaries’ WTP. Mean WTP was significantly higher for nonsubsidy recipients than subsidy-receiving beneficiaries. The fact that subsidy recipients’ WTP for MTM was significantly lower may be expected, given the economic constraints of those with limited incomes. As seen in Table 2, WTP was significantly positively correlated with the number of medications that the beneficiary reported taking. It can be speculated that the greater the number of medications taken by a beneficiary and, therefore, the greater the complexity of his or her medication regimen, the greater the perceived worth of such services. This finding is similar to those of Brooks et al., where older adults with complex medication regimens were more likely to desire MTM and perceive its value.8 Higher beneficiary OOP drug costs were associated with higher WTP for MTM. A cross-sectional study of patients, 18 years of age and older, found that 70% of their sample population had a WTP of 20% of the total OOP cost for a pharmacist’s cognitive (MTM and educational) services.6 The respondents’ WTP amount was correlated with insurance coverage and OOP expense. Findings in
106
our Medicare population are dissimilar to these findings where younger respondents’ WTP for cognitive services increased as OOP payments decreased. Rating of our efforts was positively correlated with beneficiaries’ WTP. It reasons that the greater the satisfaction with delivered services, the greater WTP for such services. Therefore, our speculation of a significant correlation between the rating of our interventional efforts and WTP was confirmed through the study. Though our study population beneficiaries’ WTP was solicited after each MTM, the issue of whether beneficiaries would actually pay OOP remains. Also, would the amount they are willing to pay be sufficient to compensate pharmacists or other health care professionals for provision of this service? Of the 44% (121) of beneficiaries not willing to pay for MTM, 40% (48/121) were subsidy recipients and 39% (47/121) were nonsubsidy recipients, with estimated 2011 annual OOP drug costs less than $1,000. The percentage of subsidy recipients in our population was 28.1% (78/277), potentially significantly deflating the average WTP. Our study findings indicate that Medicare beneficiaries are willing to pay for MTM. Researchers are challenged to conduct further studies for beneficiaries in other geographic areas and analyze additional WTP covariables within populations. Additional studies are warranted to identify WTP pre-MTM and post-MTM.
Limitations The primary study limitation was that our urban population was confined to Central/Northern California. Therefore, beneficiaries outside of this geographic area may have different opinions regarding the value of or WTP for MTM. Additionally, all beneficiaries served were ambulatory, community-dwelling seniors. California has the highest percentage of subsidy recipients (12.4%) compared with other states or regions.9 The percentage of subsidy recipients in our population (28.1%) significantly deflated the average WTP. Hence, our data may not accurately represent the beneficiaries across the United States or subpopulations in other locales. Results from prior WTP studies may differ from our study in that
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Medicare Beneficiaries’ Willingness-to-Pay for MTM Services
Table 1. Beneficiary Characteristics and WTP for MTM Services Characteristic Age (N = 264) Median, years 73 Mean ± SD, years 75 ± 9.6 No. (%) < 65 17 (6.4) 65-74 123 (46.6) 75-84 73 (27.7) 85+ 51 (19.3) Gender (N = 276) No. (%) Male 112 (40.6) Female 164 (59.4) Race (N = 274) No. (%) White 185 (67.5) Nonwhite 89 (32.5) Education (N = 267) No. (%) Less than 8th grade 33 (12.4) Some high school 21 (7.9) High school diploma/GED 45 (16.9) Some college/associates degree 73 (27.3) Bachelor’s degree or higher 95 (35.6) Subsidy Recipient† (N = 277) No. (%) Yes 78 No 199 Prescription Medications (N = 277) 1-2 3-4 5-6 6+
(28.2) (71.8) No. (%) 49 (17.7) 71 (25.6) 73 (26.4) 84 (30.3)
Mean ± SD WTP
P-value
$30.00 ± $28.56 $28.68 ± $55.94 $50.55 ± $126.82 $26.59 ± $34.44
0.45
$26.67 + $37.88 $37.78 ± $95.35
0.694
$40.68 ± $90.88 $18.06 ± $33.32
< 0.001
$50.00 ± $173.02 $26.24 ± $42.45 $34.41 ± $43.25 $23.97 ± $38.86 $37.52 ± $68.32
0.618
$12.80 ± $24.10 $41.13 ± $88.79
< 0.001
$36.02 ± $77.51 $27.78 ± $44.67 $20.46 ± $40.37
0.006††
$47.05 ± $113.79
Beneficiaries receiving Medicaid or low-income subsidy. WTP was significantly higher for individuals taking 6+ medications compared with those taking 5-6 medications via pairwise Mann-Whitney U. †
††
Abbreviations: GED = General education equivalent test, MTM = Medication therapy management, No. = Number, SD = Standard deviation, WTP = Willingness-to-pay.
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Table 2. Correlation between WTP for MTM and Beneficiary Characteristics Variable of Interest Demographic Age Education level Health-Related Number of medications Number of self-reported chronic conditions QOL (physical) QOL (mental) Miscellaneous Out-of-pocket drug costs Rating of our efforts Time spent performing MTM
P-value
Correlation Coefficient
0.071 0.042
0.249 0.495
0.130 0.055 -0.022 0.079
0.030 0.364 0.736 0.225
0.288 0.171 0.035
< 0.001 0.005 0.680
Abbreviations: MTM = Medication therapy management, QOL = Quality of life, WTP = Willingness-to-pay.
their patient populations included more diverse populations (e.g., younger patients), whereas our study solely focused on Medicare beneficiaries.6 Furthermore, our population was asked their WTP after receiving the MTM concurrently with Medicare Part D enrollment/re-enrollment assistance. As such, their perceived economic value of services reflects their perception of the delivered services. Additionally, pharmacy students, under the supervision of a pharmacist, provided our services. The outcome impact of this design is not clear since a control group with pharmacist-provided MTM was not included. The 141 beneficiaries, not willing to pay for MTM, were not questioned as to why.
Conclusions The results identified that WTP for MTM, performed by specially trained students under the supervision of a pharmacist, was valued by most (56.3%) of the study’s beneficiaries. WTP for MTM significantly varied by race,
108
subsidy status, and the number of prescription medications taken. WTP was significantly higher for white beneficiaries and nonsubsidy recipients, significantly positively correlated with number of medications taken regularly, higher OOP drug costs, and satisfaction with delivered services. WTP was not significantly related to level of education. Pharmacists are challenged to identify beneficiaries in need of MTM, to promote MTM benefits, to and document clinical, economic, and humanistic outcomes. With the growing numbers of nonpharmacist MTM providers (nurses, case managers, physicians), pharmacists must strengthen their positions as preferred providers of MTM. Policymakers should consider adoption of MTM as part of the standard Medicare Part D benefit, with less restrictive MTM qualification criteria, and recognize pharmacists as paid providers to bridge the impending shortage of primary care providers.10
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Medicare Beneficiaries’ Willingness-to-Pay for MTM Services
Joseph A. Woelfel, PhD, RPh, FASCP, is vice chair and associate professor, Department of Pharmacy Practice; director of pharmaceutical care clinics; and coordinator for geriatric introductory pharmacy practice experiences, University of the Pacific, Thomas J. Long School of Pharmacy and Health Sciences, Stockton, California. Sian M. Carr-Lopez, PharmD, is professor, Department of Pharmacy Practice, and assistant dean for experiential programs, University of the Pacific, Thomas J. Long School of Pharmacy and Health Sciences. Stockton. Melanie Delos Santos, PharmD, is pharmacist-in-charge, Longs Drugs Pharmacy, Maui, Hawaii. Ann Bui, PharmD, is ambulatory care pharmacist, Kaiser Permanente, Vallejo, California. Rajul A. Patel, PharmD, PhD, is associate professor, Department of Pharmacy Practice, University of the Pacific, Thomas J. Long School of Pharmacy and Health Sciences. Mark P. Walberg, PharmD, PhD, is assistant professor, Department of Pharmacy Practice, University of the Pacific, Thomas J. Long School of Pharmacy and Health Sciences. Suzanne M. Galal, PharmD is assistant professor, Department of Pharmacy Practice, University of the Pacific, Thomas J. Long School of Pharmacy and Health Sciences. For correspondence: Joseph A. Woelfel, PhD, RPh, FASCP, University of the Pacific, Thomas J. Long School of Pharmacy and Health Sciences, Department of Pharmacy Practice 3601 Pacific Avenue, Stockton, CA 95211; Phone:209-946-2374; Fax: 209-9463192; E-mail: [email protected]. Disclosure: No funding was received for the development of this manuscript. The authors have no potential conflicts of interest. © 2014 American Society of Consultant Pharmacists, Inc. All rights reserved.
References 1. American Pharmacists Association. Medication therapy management MTM central. Updated 2011. Available at http://www.pharmacist. com/AM/Template.cfm?Section=MTM&Template=/TaggedPage/ TaggedPageDisplay.cfm&TPLID=87&ContentID=22413#nogo. Accessed March 4, 2011. 2. Centers for Medicare and Medicaid Services. Contract year 2013 medication therapy management program guidance and submission instructions,. April 10, 2012. Available at http://www.cms.gov/Medicare/ Prescription-Drug-Coverage/PrescriptionDrugCovGenIn/Downloads/ Memo-Contract-Year-2013-Medication-Therapy-Management-MTMProgram-Submission-v041012.pdf. Accessed October 1, 2012. 3. Johnson JA, Bootman JL. Drug-related morbidity and mortality: a costof-illness model. Arch Intern Med 1995;155:1949-56. 4. Ernst FR, Grizzle AJ. Drug-related morbidity and mortality: updating the cost-of-illness model. J Am Pharm Assoc 2001;41:192-9. 5. Barnett MJ, Frank J, Wehring H et al. Analysis of pharmacist-provided medication therapy management (MTM) services in community pharmacies over 7 years. J Manag Care Pharm 2009;15:18-31. 6. Schuh MJ, Droege M. Cognitive services provided by pharmacists: Is the public willing to pay for them? Consult Pharm 2008;23:223-30. 7. Friedrich M, Zgarrick D, Masood A, Montuoro J. Patients’ needs and interests in a self-pay medication therapy management service. J Am Pharm Assoc 2010;50:72-7. 8. Brooks JM, Unni EJ, Klepser DG et al. Factors affecting demand among older adults for medication therapy management services. Res Social Adm Pharm 2008;4:309-19. 9. Summer L, Hoadley J, Hargrave E. The Medicare Part D low-income subsidy program: experience to date and policy issues for consideration. The Kaiser Family Foundation, September 2010. Available at http://www. kff.org/medicare/upload/8094.pdf. Accessed February 29, 2012. 10. Association of American Medical Colleges. Physician shortages to worsen without increases in residency training. June 2010. Available at https://www.aamc.org/download/286592/data/. Accessed January 3, 2014.
Doi:10.4140/TCP.n.2014.104.
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104
Abbreviations: CMS = Centers for Medicare & Medicaid
Services, MTM = Medication therapy management, OOP = Out-of-pocket, QOL = Quality of life, WTP = Willingness-to-pay. Consult Pharm 2014;29:104-9.
Introduction Medication therapy management (MTM) is a service that optimizes individual patient therapeutic outcomes by managing drug therapy. The goal of MTM programs is to identify, prevent, and resolve medication-related problems.1 The Centers for Medicare & Medicaid Services (CMS) view MTM as a clinical service and require Medicare Part D plan sponsors to establish a MTM program. While provided services and interventions may vary across MTM program models, the eligibility criteria cannot.2 In order to meet the CMS-mandated eligibility criteria for receipt of MTM through a Medicare Part D plan, beneficiaries must have multiple chronic conditions, take multiple Medicare Part D drugs, and be likely to incur annually covered Medicare Part D drug costs exceeding a predetermined level ($3,144 in 2013). A 1995 landmark study projected the cost associated with drug therapy problems amounted to $76.6 billion, later updated to $177.4 billion.3,4 Community pharmacist MTM was beneficial in reducing physician visits, emergency department visits, and hospital admissions.5 Prior studies have addressed patients’, 18 years of age and older, willingness-to-pay (WTP) for MTM services.6,7 Unlike previous studies, our study assesses a Medicare population’s WTP for MTM. We examined WTP after receipt of such services and WTP as a function of different sociodemographic and health-related variables.
Objectives The purposes of this study were to investigate and quantify WTP for MTM in a Medicare beneficiary population. Additionally, the study sought to determine if WTP for MTM varies as a function of the number of medications taken, the number of self-reported chronic conditions, the patient’s physical and mental quality-of-life, his or her out-of-pocket (OOP) drug costs, rating of our efforts, time spent with beneficiaries, and various sociodemographic
The Consultant Pharmacist FEbruary 2014 Vol. 29, No. 2
Medicare Beneficiaries’ Willingness-to-Pay for MTM Services
variables. We hypothesized that beneficiaries would be willing to pay for MTM; however, their WTP would be dependent on various sociodemographic and clinical variables.
Methods Study Design A cross-sectional study design was conducted to elicit Medicare beneficiaries’ WTP for MTM. Nine outreach events in four urban Central/Northern Californian cities (Lodi, Modesto, San Jose, Stockton) were held during the 2011 Medicare Part D annual enrollment period during which 401 beneficiaries were assisted. The outreach events were publically advertised by flyers and newspaper advertisements, as well as radio and television announcements. Outreach/Data Collection Forty student pharmacists, trained in a specialized Medicare elective courses, (didactic education and casebased simulations) conducted MTM for beneficiaries under the supervision of licensed pharmacists. A standardized data collection tool was used to record de-identified beneficiary data. The tool included open-ended questions, visible to and read to each participant by students. The data-collection tool was designed to identify beneficiaries’ sociodemographic and clinical data, along with their quantified WTP for MTM. Patients’ self-reported chronic conditions and their complete medication profiles were used to identify those with cognitive impairment. The WTP question was asked after provision of MTM. The study was conducted under a University of the Pacificapproved institutional review board protocol. Interventions Demographic data were collected prior to starting the MTM intervention. Each beneficiary was administered the SF-36v2 Heath Survey-Standard Recall (SF-36v2; Quality Metric Incorporated [Lincoln, RI]) to assess their quality of life (QOL).
During the MTM session, beneficiaries’ specific prescription drugs and over-the-counter medications were analyzed for: expired medications, drug-drug interactions, side effects, contraindications, 2003 Beers criteria drugs, therapeutic duplication, and untreated conditions. Electronic drug information resources, Lexicomp, Micromedex, E-facts, and/or Clinical Pharmacology, were used during the intervention as online references. Whenever severe medication-related issues or cost-savings opportunities were identified, and with the beneficiary’s permission, his or her pharmacy and/or prescriber were contacted with specific findings/recommendations. At the end of the MTM intervention each beneficiary was asked, “If offered by your pharmacist or pharmacy, how much would you be willing to pay to have someone go through all of your medications as we did today?” Before leaving, each beneficiary was asked to rate the MTM services, using a 5-point Likert scale (1 = Excellent and 5 = Poor).
Data Analysis Descriptive statistics were recorded for beneficiary and interventional data. The normality of numerical data was tested by the K-S statistic. Mann-Whitney U (for pairwise comparisons) or Kruskal Wallis (for three or more groups) tests were used to determine differences in WTP between different demographic categories. Pairwise Mann-Whitney U tests were performed if Kruskal Wallis tests were significant using a Bonferroni-corrected P-value. Spearman’s rho was used to determine the correlation between WTP and variables of interest. Statistical analyses were conducted using SPSS version 18.0 (SPSS Inc., Chicago, IL).
Results A total of 277 (69% response rate) beneficiaries answered the study questions and comprised the study sample. The mean (standard deviation) WTP was $33.15 ($77.33). Forty-four percent (121/277) of respondents were not willing to pay for MTM. Demographic data and WTP for MTM as a function of demographic characteristics are displayed in Table 1. Significant differences in WTP were observed for race (white versus nonwhite individuals [P < 0.001]), subsidy status (recipients versus nonrecipients
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Research and Reports [P < 0.001]), number of prescription medications (individuals taking more than six medications compared with those taking five to six [P < 0.006]). Table 2 reports the bivariate relationship between beneficiaries’ WTP for MTM and number of medications, number of self-reported chronic conditions, physical and mental component summary scores (QOL), educational attainment, OOP drug costs (estimated annual cost), and rating of our efforts. Significant positive correlations were seen between WTP and number of medications regularly taken (P = 0.030), annual OOP drug costs (P < 0.001), and rating of services offered (P = 0.005). Bivariate data analysis identified additional variables that were significantly correlated with WTP. These included: race (white versus nonwhite), subsidy status, number of prescription medications taken, and rating of our efforts (Table 2). Age, gender, education level, number of self-reported chronic conditions, physical and mental quality-of-life measures, and amount of time spent with a beneficiary during MTM were not significantly related to beneficiaries’ WTP. Mean WTP was significantly higher for nonsubsidy recipients than subsidy-receiving beneficiaries. The fact that subsidy recipients’ WTP for MTM was significantly lower may be expected, given the economic constraints of those with limited incomes. As seen in Table 2, WTP was significantly positively correlated with the number of medications that the beneficiary reported taking. It can be speculated that the greater the number of medications taken by a beneficiary and, therefore, the greater the complexity of his or her medication regimen, the greater the perceived worth of such services. This finding is similar to those of Brooks et al., where older adults with complex medication regimens were more likely to desire MTM and perceive its value.8 Higher beneficiary OOP drug costs were associated with higher WTP for MTM. A cross-sectional study of patients, 18 years of age and older, found that 70% of their sample population had a WTP of 20% of the total OOP cost for a pharmacist’s cognitive (MTM and educational) services.6 The respondents’ WTP amount was correlated with insurance coverage and OOP expense. Findings in
106
our Medicare population are dissimilar to these findings where younger respondents’ WTP for cognitive services increased as OOP payments decreased. Rating of our efforts was positively correlated with beneficiaries’ WTP. It reasons that the greater the satisfaction with delivered services, the greater WTP for such services. Therefore, our speculation of a significant correlation between the rating of our interventional efforts and WTP was confirmed through the study. Though our study population beneficiaries’ WTP was solicited after each MTM, the issue of whether beneficiaries would actually pay OOP remains. Also, would the amount they are willing to pay be sufficient to compensate pharmacists or other health care professionals for provision of this service? Of the 44% (121) of beneficiaries not willing to pay for MTM, 40% (48/121) were subsidy recipients and 39% (47/121) were nonsubsidy recipients, with estimated 2011 annual OOP drug costs less than $1,000. The percentage of subsidy recipients in our population was 28.1% (78/277), potentially significantly deflating the average WTP. Our study findings indicate that Medicare beneficiaries are willing to pay for MTM. Researchers are challenged to conduct further studies for beneficiaries in other geographic areas and analyze additional WTP covariables within populations. Additional studies are warranted to identify WTP pre-MTM and post-MTM.
Limitations The primary study limitation was that our urban population was confined to Central/Northern California. Therefore, beneficiaries outside of this geographic area may have different opinions regarding the value of or WTP for MTM. Additionally, all beneficiaries served were ambulatory, community-dwelling seniors. California has the highest percentage of subsidy recipients (12.4%) compared with other states or regions.9 The percentage of subsidy recipients in our population (28.1%) significantly deflated the average WTP. Hence, our data may not accurately represent the beneficiaries across the United States or subpopulations in other locales. Results from prior WTP studies may differ from our study in that
The Consultant Pharmacist FEbruary 2014 Vol. 29, No. 2
Medicare Beneficiaries’ Willingness-to-Pay for MTM Services
Table 1. Beneficiary Characteristics and WTP for MTM Services Characteristic Age (N = 264) Median, years 73 Mean ± SD, years 75 ± 9.6 No. (%) < 65 17 (6.4) 65-74 123 (46.6) 75-84 73 (27.7) 85+ 51 (19.3) Gender (N = 276) No. (%) Male 112 (40.6) Female 164 (59.4) Race (N = 274) No. (%) White 185 (67.5) Nonwhite 89 (32.5) Education (N = 267) No. (%) Less than 8th grade 33 (12.4) Some high school 21 (7.9) High school diploma/GED 45 (16.9) Some college/associates degree 73 (27.3) Bachelor’s degree or higher 95 (35.6) Subsidy Recipient† (N = 277) No. (%) Yes 78 No 199 Prescription Medications (N = 277) 1-2 3-4 5-6 6+
(28.2) (71.8) No. (%) 49 (17.7) 71 (25.6) 73 (26.4) 84 (30.3)
Mean ± SD WTP
P-value
$30.00 ± $28.56 $28.68 ± $55.94 $50.55 ± $126.82 $26.59 ± $34.44
0.45
$26.67 + $37.88 $37.78 ± $95.35
0.694
$40.68 ± $90.88 $18.06 ± $33.32
< 0.001
$50.00 ± $173.02 $26.24 ± $42.45 $34.41 ± $43.25 $23.97 ± $38.86 $37.52 ± $68.32
0.618
$12.80 ± $24.10 $41.13 ± $88.79
< 0.001
$36.02 ± $77.51 $27.78 ± $44.67 $20.46 ± $40.37
0.006††
$47.05 ± $113.79
Beneficiaries receiving Medicaid or low-income subsidy. WTP was significantly higher for individuals taking 6+ medications compared with those taking 5-6 medications via pairwise Mann-Whitney U. †
††
Abbreviations: GED = General education equivalent test, MTM = Medication therapy management, No. = Number, SD = Standard deviation, WTP = Willingness-to-pay.
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Table 2. Correlation between WTP for MTM and Beneficiary Characteristics Variable of Interest Demographic Age Education level Health-Related Number of medications Number of self-reported chronic conditions QOL (physical) QOL (mental) Miscellaneous Out-of-pocket drug costs Rating of our efforts Time spent performing MTM
P-value
Correlation Coefficient
0.071 0.042
0.249 0.495
0.130 0.055 -0.022 0.079
0.030 0.364 0.736 0.225
0.288 0.171 0.035
< 0.001 0.005 0.680
Abbreviations: MTM = Medication therapy management, QOL = Quality of life, WTP = Willingness-to-pay.
their patient populations included more diverse populations (e.g., younger patients), whereas our study solely focused on Medicare beneficiaries.6 Furthermore, our population was asked their WTP after receiving the MTM concurrently with Medicare Part D enrollment/re-enrollment assistance. As such, their perceived economic value of services reflects their perception of the delivered services. Additionally, pharmacy students, under the supervision of a pharmacist, provided our services. The outcome impact of this design is not clear since a control group with pharmacist-provided MTM was not included. The 141 beneficiaries, not willing to pay for MTM, were not questioned as to why.
Conclusions The results identified that WTP for MTM, performed by specially trained students under the supervision of a pharmacist, was valued by most (56.3%) of the study’s beneficiaries. WTP for MTM significantly varied by race,
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subsidy status, and the number of prescription medications taken. WTP was significantly higher for white beneficiaries and nonsubsidy recipients, significantly positively correlated with number of medications taken regularly, higher OOP drug costs, and satisfaction with delivered services. WTP was not significantly related to level of education. Pharmacists are challenged to identify beneficiaries in need of MTM, to promote MTM benefits, to and document clinical, economic, and humanistic outcomes. With the growing numbers of nonpharmacist MTM providers (nurses, case managers, physicians), pharmacists must strengthen their positions as preferred providers of MTM. Policymakers should consider adoption of MTM as part of the standard Medicare Part D benefit, with less restrictive MTM qualification criteria, and recognize pharmacists as paid providers to bridge the impending shortage of primary care providers.10
The Consultant Pharmacist FEbruary 2014 Vol. 29, No. 2
Medicare Beneficiaries’ Willingness-to-Pay for MTM Services
Joseph A. Woelfel, PhD, RPh, FASCP, is vice chair and associate professor, Department of Pharmacy Practice; director of pharmaceutical care clinics; and coordinator for geriatric introductory pharmacy practice experiences, University of the Pacific, Thomas J. Long School of Pharmacy and Health Sciences, Stockton, California. Sian M. Carr-Lopez, PharmD, is professor, Department of Pharmacy Practice, and assistant dean for experiential programs, University of the Pacific, Thomas J. Long School of Pharmacy and Health Sciences. Stockton. Melanie Delos Santos, PharmD, is pharmacist-in-charge, Longs Drugs Pharmacy, Maui, Hawaii. Ann Bui, PharmD, is ambulatory care pharmacist, Kaiser Permanente, Vallejo, California. Rajul A. Patel, PharmD, PhD, is associate professor, Department of Pharmacy Practice, University of the Pacific, Thomas J. Long School of Pharmacy and Health Sciences. Mark P. Walberg, PharmD, PhD, is assistant professor, Department of Pharmacy Practice, University of the Pacific, Thomas J. Long School of Pharmacy and Health Sciences. Suzanne M. Galal, PharmD is assistant professor, Department of Pharmacy Practice, University of the Pacific, Thomas J. Long School of Pharmacy and Health Sciences. For correspondence: Joseph A. Woelfel, PhD, RPh, FASCP, University of the Pacific, Thomas J. Long School of Pharmacy and Health Sciences, Department of Pharmacy Practice 3601 Pacific Avenue, Stockton, CA 95211; Phone:209-946-2374; Fax: 209-9463192; E-mail: [email protected]. Disclosure: No funding was received for the development of this manuscript. The authors have no potential conflicts of interest. © 2014 American Society of Consultant Pharmacists, Inc. All rights reserved.
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