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Financial Reinforcers for Improving Medication Adherence: Findings from a Meta-analysis

      Abstract

      Background

      Increasingly, financial reinforcement interventions based on behavioral economic principles are being applied in health care settings, and this study examined the use of financial reinforcers for enhancing adherence to medications.

      Methods

      Electronic databases and bibliographies of relevant references were searched, and a meta-analysis of identified trials was conducted. The variability in effect size and the impact of potential moderators (study design, duration of intervention, magnitude of reinforcement, and frequency of reinforcement) on effect size were examined.

      Results

      Fifteen randomized studies and 6 nonrandomized studies examined the efficacy of financial reinforcement interventions for medication adherence. Financial reinforcers were applied for adherence to medications for tuberculosis, substance abuse, human immunodeficiency virus, hepatitis, schizophrenia, and stroke prevention. Reinforcement interventions significantly improved adherence relative to control conditions with an overall effect size of 0.77 (95% confidence interval, 0.70-0.84; P<.001). Nonrandomized studies had a larger average effect size than randomized studies, but the effect size of randomized studies remained significant at 0.44 (95% confidence interval, 0.35-0.53; P<.001). Interventions that were longer in duration, provided an average reinforcement of $50 or more per week, and reinforced patients at least weekly resulted in larger effect sizes than those that were shorter, provided lower reinforcers, and reinforced patients less frequently.

      Conclusion

      These results demonstrate the efficacy of medication adherence interventions and underscore principles that should be considered in designing future adherence interventions. Financial reinforcement interventions hold potential for improving medication adherence and may lead to benefits for both patients and society.

      Keywords

      SEE RELATED EDITORIAL AND RELATED ARTICLE pp. 841 and 882
      Behavioral economics is the study of psychologic and cognitive factors related to the decision-making processes. This field is applied increasingly in healthcare settings, often in the context of providing clinicians with incentives for meeting performance guidelines.
      • Conrad D.A.
      • Perry L.
      Quality-based financial incentives in health care: can we improve quality by paying for it?.
      Patients also can receive reinforcers for meeting criteria associated with health outcomes, and randomized trials demonstrate the efficacy of financial reinforcers for reducing alcohol
      • Petry N.M.
      • Martin B.
      • Cooney J.L.
      • Kranzler H.R.
      Give them prizes, and they will come: contingency management for treatment of alcohol dependence.
      and illicit drug use,
      • Higgins S.T.
      • Budney A.J.
      • Bickel W.K.
      • et al.
      Incentives improve outcome in outpatient behavioral treatment of cocaine dependence.
      • Petry N.M.
      • Peirce J.M.
      • Stitzer M.L.
      • et al.
      Effect of prize-based incentives on outcomes in stimulant abusers in outpatient psychosocial treatment programs: a national drug abuse treatment clinical trials network study.
      decreasing smoking,
      • Volpp K.G.
      • Troxel A.B.
      • Pauly M.V.
      • et al.
      A randomized controlled trial of financial incentives for smoking cessation.
      and losing weight.
      • Petry N.M.
      • Barry D.
      • Pescatello L.
      • White W.B.
      A Low-cost reinforcement procedure improves short-term weight loss outcomes.
      • Volpp K.G.
      • John L.K.
      • Troxel A.B.
      • et al.
      Financial incentive-based approaches for weight loss: a randomized trial.
      • Increasingly, financial reinforcement interventions based on behavioral economic principles are being applied in health care settings.
      • Financial reinforcement interventions are beneficial for improving medication adherence with an overall mean effect size of 0.77.
      • Financial reinforcement interventions hold potential for improving medication adherence and may lead to benefits for both patients and society.
      A problem relevant to many patient populations is poor medication adherence. Estimates indicate that 28% of new prescriptions are unfilled,
      • Fischer M.A.
      • Stedman M.R.
      • Lii J.
      • et al.
      Primary medication non-adherence: analysis of 195,930 electronic prescriptions.
      and among patients who do obtain medications, adherence rates are often less than 50%.
      • Haynes R.B.
      • McDonald H.P.
      • Garg A.X.
      Helping patients follow prescribed treatment: clinical applications.
      Lack of adherence interferes with therapeutic benefits of medications and can lead to additional diagnostic and treatment procedures, resulting in greater health care costs.
      National Council on Patient Information and Education
      Enhancing Prescription Medicine Adherence A National Action Plan.
      Poor adherence to antimicrobials can increase disease spread and lead to the development of drug-resistant strains, which are transmitted to the public. Consequently, some providers are reluctant to prescribe medications to patients presumed to be nonadherent.
      • Bogart L.M.
      • Kelly J.A.
      • Catz S.L.
      • Sosman J.M.
      Impact of medical and nonmedical factors on physician decision making for HIV/AIDS antiretroviral treatment.
      Interventions based on behavioral economic principles may be useful for improving medication adherence. The only prior review of this literature
      • Giuffrida A.
      • Torgerson D.J.
      Should we pay the patient: review of financial incentives to enhance patient compliance.
      found few studies that applied financial reinforcers for medication adherence. Among the 11 studies included, most applied reinforcers for appointment-keeping alone, and only 1 study
      • Morisky D.E.
      • Malotte C.K.
      • Choi P.
      • et al.
      A patient education program to improve adherence rates with antituberculosis drug regimens.
      reinforced medication adherence in patients with tuberculosis. Reinforcing patients for behavior change has gained popularity.
      • Promberger M.
      • Brown R.C.
      • Ashcroft R.E.
      • Marteau T.
      Acceptability of financial incentives to improve health outcomes in UK and US samples.
      We examined the published research on financial reinforcers to improve medication adherence, and a meta-analysis ascertained the effect size of these interventions. Furthermore, analyses evaluated the impact of reinforcement parameters on effect sizes to elucidate conditions under which beneficial effects of financial reinforcement adherence interventions may be best realized.

      Materials and Methods

      Identification of Studies

      PubMed and PsychInfo databases were searched through April 2011 for matches in titles, abstracts and descriptors, for the terms: medication and (compliance or adhere*) and (incentive* or cash* or money or token* or payment*). Reference lists of retrieved articles also were examined.

      Study Inclusion and Exclusion Criteria

      Article titles and abstracts were screened independently. If either suggested that the article might be appropriate, the article was retrieved. Financially based reinforcers for medication adherence were defined as money, goods (eg, bus tokens and food), or vouchers redeemable for goods (eg, food and clothes). Both randomized and nonrandomized (eg, comparison with historical controls or reversal designs) trials were included.
      Studies that provided access to treatment (including methadone doses) or reductions or eliminations of copayments as reinforcers were excluded. Studies that reinforced appointment-keeping alone, when not linked to medication ingestion, and those using a single incentive for medication ingestion (eg, single vaccination, initial visit to a clinic) were excluded. Studies solely using reimbursement payments (eg, for travel expenses or patient time) also were not included. Studies that did not provide adequate information to derive an effect size were excluded. Disagreement between raters was resolved by consensus.

      Data Analysis

      Information about the population, study design, sample size, reinforcement intervention, duration of intervention, maximal reinforcement, frequency of reinforcement, and adherence data were tabulated. Two independent samples and reinforcement interventions were described within 1 publication,
      • Morisky D.E.
      • Malotte C.K.
      • Choi P.
      • et al.
      A patient education program to improve adherence rates with antituberculosis drug regimens.
      which are treated as 2 separate studies for these analyses. Objective adherence data (eg, observed doses, Medication Event Monitoring System cap readings, medication completion) are reported as defined within studies.
      Effect sizes were computed via d=(M1M2)/SD, where M1 and M2 refer to means of the experimental and control groups, respectively, and SD is the pooled standard deviation. In order of preference, raw data, means and SDs, or test statistics (t or F) were used to calculate effect size.
      • Lipsey M.W.
      • Wilson D.B.
      Practical Meta-Analysis.
      If a study had more than 1 reinforcement (or comparison) condition, values were averaged before determining effect size.
      The effect sizes for main adherence outcomes were calculated in each study. Consistent with recommendations,
      • Lipsey M.W.
      • Wilson D.B.
      Practical Meta-Analysis.
      multiple effect sizes were averaged when a study had more than 1 adherence outcome to create 1 effect size per sample (N=21) for use in subsequent analyses. Hedge's correction
      • Lipsey M.W.
      • Wilson D.B.
      Practical Meta-Analysis.
      provided unbiased effect size estimates and was applied before analyses. These estimates can be interpreted using Cohen's
      • Cohen J.
      A power primer.
      conventions for small (0.20), medium (0.50), and large (0.80) effect sizes.
      Analyses initially evaluated whether financial reinforcement interventions affected adherence outcomes using inverse variance weighted mean effect sizes.
      • Lipsey M.W.
      • Wilson D.B.
      Practical Meta-Analysis.
      Publication bias was assessed using the failsafe N,
      • Orwin R.
      A fail-safe N for effect size in meta-analysis.
      which estimates the number of studies with null effects needed to lower the obtained effect size to a small effect (d=0.20). Cochran's Q statistic
      • Cochran W.G.
      The combination of estimates from different experiments.
      tested for heterogeneity in effect sizes, and when significant, it indicates variability in effect sizes that may be explained by moderators. In addition, the inconsistency index (I2) is reported, which estimates the proportion of variance due to heterogeneity rather than chance.
      • Higgins J.P.T.
      • Thompson S.G.
      • Deeks J.J.
      • Altman D.G.
      Measuring inconsistency in meta-analyses.
      Analyses also evaluated whether moderators explained heterogeneity in effect sizes. Randomization status of the study design and 3 variables related to specific behavioral principles (ie, duration, magnitude, and frequency of reinforcement) were included as moderators. Randomization was coded as a dichotomous variable (yes/no). Duration was included as a continuous variable in weeks; for studies in which duration varied across participants, the average duration was used. For 2 studies,
      • Morisky D.E.
      • Malotte C.K.
      • Ebin V.
      • et al.
      Behavioral interventions for the control of tuberculosis among adolescents.
      • Tulsky J.P.
      • Pilote L.
      • Hahn J.A.
      • et al.
      Adherence to isoniazid prophylaxis in the homeless: a randomized controlled trial.
      the planned duration of 24 weeks was used, although reinforcement may have extended beyond 24 weeks for some participants. The other 2 behavioral moderators were dichotomized because of an inability to specifically quantify these variables in several studies. Consistent with other reinforcement literature,
      • Lussier J.P.
      • Heil S.H.
      • Mongeon J.A.
      • et al.
      A meta-analysis of voucher-based reinforcement therapy for substance use disorders.
      • Prendergast M.
      • Podus D.
      • Finney J.
      • et al.
      Contingency management for treatment of substance use disorders: a meta-analysis.
      magnitudes were dichotomized into low to moderate (<$50/week; n=16) versus high (≥$50/week; n=5). Reinforcement magnitudes were derived by dividing the total (or estimated total) reinforcement by the reinforcement duration. When ranges were reported (eg, 2 reinforcement conditions), the average magnitude was calculated. In 2 cases,
      • Morisky D.E.
      • Malotte C.K.
      • Ebin V.
      • et al.
      Behavioral interventions for the control of tuberculosis among adolescents.
      • Martins N.
      • Morris P.
      • Kelly P.M.
      Food incentives to improve completion of tuberculosis treatment: randomised controlled trial in Dili, Timor-Leste.
      food or other individually selected reinforcers (eg, clothing) were provided, both of which were presumed low to moderate in magnitude given the study designs. Reinforcement frequency was dichotomized into at least weekly (n=15) or less frequently than weekly (n=6). Modified weighted least-squares regression
      • Lipsey M.W.
      • Wilson D.B.
      Practical Meta-Analysis.
      assessed the effects of these design parameters, with the 4 variables entered into the regression simultaneously. Analyses were conducted in SPSS 19.0 (SPSS Inc, Chicago, Ill) using Wilson's
      • Wilson D.B.
      SPSS for Windows meta-analysis macros.
      and Hoffmann's
      • Hoffmann W.
      Extension of SPSS for Windows Meta-Analysis Macros.
      macros.

      Results

      Electronic searches identified 621 articles containing the keywords. After review of the titles and abstracts, 46 articles were retrieved as potentially meeting the study inclusion criteria, and 32 additional articles were found through references contained in source articles. Of the 78 retrieved articles, 18 were excluded because they were reviews, 10 discussed ethical issues about payments, 8 did not provide financial reinforcers to patients, 8 did not reinforce medication ingestion, 5 provided only a single reinforcer, and 2 described designs of ongoing projects. An additional 4 studies were excluded because they compared different reinforcement interventions without a nonreinforcement control, 2 did not provide any comparison condition, and 1 nonrandomized study did not provide sufficient data from which an effect size could be derived.
      Table 1 outlines the 21 studies evaluating financial reinforcement interventions for improving medication adherence. Tuberculosis was the medical condition for which the greatest number of studies were identified,
      • Morisky D.E.
      • Malotte C.K.
      • Choi P.
      • et al.
      A patient education program to improve adherence rates with antituberculosis drug regimens.
      • Morisky D.E.
      • Malotte C.K.
      • Ebin V.
      • et al.
      Behavioral interventions for the control of tuberculosis among adolescents.
      • Tulsky J.P.
      • Pilote L.
      • Hahn J.A.
      • et al.
      Adherence to isoniazid prophylaxis in the homeless: a randomized controlled trial.
      • Martins N.
      • Morris P.
      • Kelly P.M.
      Food incentives to improve completion of tuberculosis treatment: randomised controlled trial in Dili, Timor-Leste.
      • Bock N.N.
      • Sales R.M.
      • Rogers T.
      • DeVoe B.
      A spoonful of sugar improving adherence to tuberculosis treatment using financial incentives.
      • Malotte C.K.
      • Hollingshead J.R.
      • Larro M.
      Incentives vs outreach workers for latent tuberculosis treatment in drug users.
      • Jakubowiak W.M.
      • Bogorodskaya E.M.
      • Borisov E.S.
      • et al.
      Risk factors associated with default among new pulmonary TB patients and social support in six Russian regions.
      and adherence was most often determined by directly observed therapy. Reinforcers were generally cash ($5-$10 per dose, week or month). However, 1 study with adolescents
      • Morisky D.E.
      • Malotte C.K.
      • Ebin V.
      • et al.
      Behavioral interventions for the control of tuberculosis among adolescents.
      used individual reinforcement contracts with parents, and 1 study in Timor-Leste
      • Martins N.
      • Morris P.
      • Kelly P.M.
      Food incentives to improve completion of tuberculosis treatment: randomised controlled trial in Dili, Timor-Leste.
      used meals as the reinforcers. This study's results were affected by civil conflicts in the region, with treatment completion rates reduced substantially during the conflict period regardless of treatment assignment. All studies providing cash reinforcement (but not those using meals or parental contracts) found significant benefits on at least 1 adherence measure.
      Table 1Studies Reinforcing Adherence to Medications
      First Author, YearDesignnCondition(s)Duration (wk)Reinforcement MaximumReinforcement FrequencyOutcome(s)dAveraged
      Tuberculosis
       Morisky 1990R
      • 43
      • 45
      • (a) $10 in tokens, gift cards, or cash/clinic medication visit
      • (b) Usual care (active cases)
      24-36VariedMonthly (or weekly)
      • Took>95% of doses:
      • (a) 71% vs (b) 57% (P < .01)
      • Finished treatment:
      • (a) 98% vs (b) 91% (P=.36)
      • Appointments kept:
      • (a) 88% vs (b) 81% (P=.08)
      • 0.33
      • 0.78
      • 0.41
      0.50
       Morisky 1990R
      • 58
      • 59
      • (a) $5 in tokens, gift cards, or cash/clinic medication visit
      • (b) Usual care (preventive cases)
      36-52VariedMonthly (or weekly)
      • Took>95% of doses:
      • (a) 42% vs (b) 14% (P < .001)
      • Finished treatment:
      • (a) 64% vs (b) 27% (P < .001)
      • Appointments kept:
      • (a) 64% vs (b) 47% (P=.003)
      • 0.81
      • 0.86
      • 0.56
      0.74
       Tulsky 2000R
      • 43
      • 37
      • 38
      • (a) $5/DOT
      • (b) Peer health advisor
      • (c) Usual care
      24$240Twice weekly
      • Median months on medication:
      • (a) 5 vs (bc) 2 (P < .05)
      • Completed treatment:
      • (a) 44% vs (bc) 23% (P < .05)
      • NEI
      • 0.55
      0.55
       Bock 2001NR
      • 55
      • 52
      • (a) $5 voucher/DOT and physician appointment
      • (b) Historical controls
      32-52 (estimated)$160-$260 (estimated)Not stated, but appeared more than weekly
      • Completed treatment (52 wks):
      • (a) 89% vs (b) 52% (P < .05)
      1.121.12
       Malotte 2001R
      • 53
      • 55
      • 55
      • (a) $5/biweekly DOT+outreach
      • (b) $5/biweekly DOT
      • (c) Biweekly DOT+outreach
      24-52$240-$520Twice weekly
      • Doses ingested on time:
      • (ab) 70% vs (c) 12% (P < .001)
      • Completed treatment:
      • (ab) 56% vs (b) 4% (P < .001)
      • 1.84
      • 1.95
      1.89
       Morisky 2001R
      • 196
      • 204
      • 199
      • 195
      • (a) Peer counseling+parental contracting/taking medication and attending clinic visits
      • (b) Parental contracting
      • (c) Peer counseling
      • (d) Usual care
      24VariedVaried (recommended 3× in total)
      • Completed treatment:
      • (ab) 81% vs (bc) 79% (n.s.)
      0.050.05
       Jakubowiak 2007NR
      • 829
      • 698
      • (a) Food, clothing, travel funds, toiletries/DOT
      • (b) Usual care
      ≥24$60-$180 food packagesVaried, appeared to be frequent
      • Treatment success:
      • (a) 99% vs (b) 90% (P < .001)
      1.241.24
       Martins 2009R
      • 136
      • 129
      • (a) Meals and food packages/visit
      • (b) Nutritional information
      32Not statedDaily weeks 1-8, not stated weeks 9-32
      • Completed treatment:
      • (a) 76% vs (b) 78% (n.s.)
      • Compliance:
      • (a) 98.2% vs (b) 98.3% (n.s.)
      • −0.05
      • −0.02
      −0.03
      Drug abuse
       Grabowski 1979NR
      • 9
      • 126
      • (a) $3.35/DOT 3×/wk.
      • (b) $10.05/wk on set day (regardless of DOT other days)
      • (c) $10.50/every 3rd DOT
      • (d) $10.50/every 3rd DOT on average


      (e) Historical controls
      20(a) $200

      (b) $200

      (c) $200

      (d) $200
      1-3×/wk
      • Retained 1 mo:
      • (abcd) 89% vs (e) 59% (P < .01)
      0.940.94
       Preston 1999R
      • 19
      • 19
      • 20
      • (a) ≥$2.50 vouchers/DOT, increases with adherence
      • (b) Yoked control vouchers
      • (c) No vouchers
      12(a) $11553×/wk
      • Doses ingested:
      • (a) 21.4 vs (bc) 7.8 (P < .05)
      • Weeks in treatment:
      • (a) 7.4 vs (bc) 3.6 (P < .05)
      • Completed treatment:
      • (a) 42% vs (bc) 13% (P < .05)
      • Maximum consecutive doses:
      • (a) 19.6 vs (bc) 5.5 (P < .01)
      • 1.13
      • 0.88
      • 0.88
      • 1.36
      1.06
       Carroll 2001R
      • 35
      • 48
      • 44
      • (a) ≥$0.80 vouchers/DOT and/drug-negative sample
      • (b) Above+significant other counseling
      • (c) Standard care+cognitive behavioral therapy
      12(a) $561

      (b) $561
      3×/wk
      • Doses ingested:
      • (ab) 18.7 vs (c) 14.2 (P = .06)
      • Weeks in treatment:
      • (ab) 7.4 vs (c) 5.6 (P = .05)
      • Completed treatment:
      • (ab) 45% vs (c) 26% (P < .05)
      • 0.35
      • 0.37
      • 0.48
      0.40
       Carroll 2002R
      • 17
      • 20
      • 18
      • (a) ≥$0.80 vouchers/DOT and/drug-negative sample
      • (b) ≥$2.00 vouchers/DOT and/drug-negative sample
      • (c) Standard care
      12(a) $561

      (b) $1152
      3×/wk
      • Doses ingested:
      • (ab) 20.9 vs (c) 14.4 (P = .08)
      • Weeks in treatment:
      • (ab) 8.0 vs (c) 6.2 (P = .17)
      • 0.52
      • 0.40
      0.46
       Nunes 2006R
      • 36
      • 33
      • (a) Motivational enhancement, cognitive-behavioral, significant other, community reinforcement therapy+$2 voucher/DOT and/negative sample.
      • (b) Adherence therapy (psychoeducation, problem solving, 12-step)
      24(a) $6722×/wk
      • Ingested >70% doses:
      • (a) 55.6% vs (b) 45.5% (P = .40)
      • Weeks in treatment:
      • (a) 11.9 vs (b) 7.2 (P = .04)
      • Completed treatment:
      • (a) 22.2% vs (b) 9.1% (P = .04)
      • 0.22
      • 0.50
      • 0.58
      0.43
      HIV
       Rigsby 2000R
      • 15
      • 18
      • 22
      • (a) Cue dose training+$2-$10/primary medication (±2 h) via MEMS
      • (b) Cue dose training
      • (c) Adherence counseling
      4$280Weekly
      • Doses of primary medication:
      • (a) 90% v (bc) 69% (P < .05)
      • Doses of secondary medication:
      • (a) 86% v (bc) 71% (P < .05)
      • 1.87
      • 2.25
      2.06
       Rosen 2007R
      • 28
      • 28
      • (a) Adherence counseling+$1-$100 prizes for ingestion (±3 h) via MEMS
      • (b) Adherence counseling
      16$800Weekly
      • Doses of primary medication:
      • (a) 76% v (b) 44% (P=.01)
      • Doses of secondary medication:
      • (a) 77% v (b) 45% (P=.09)
      • >95% adherent:
      • (a) 18% vs (b) 0% (P < .05)
      • 1.30
      • 1.39
      • 3.85
      2.18
       Sorensen 2007R
      • 34
      • 32
      • (a) Adherence counseling+≥$1 voucher/d for adherence (±2 h) via MEMS
      • (b) Adherence counseling+chance to win $1-$80 prizes for attending
      12$1172Up to 2×/wk
      • Doses of primary medication:
      • (a) 78% vs (b) 56% (P < .001)
      • Pill count adherence:
      • (a) 86% vs (b) 75% (P=.02)
      • Days of continuous adherence:
      • (a) 21 vs (b) 9 (P < .001)
      • 1.09
      • 0.63
      • 0.87
      0.86
      Hepatitis
       Seal 2003R
      • 48
      • 48
      • (a) $20/mo visit (3 visits were DOT)
      • (b) Weekly outreach+reminders
      24$120Each visit, DOT
      • Received all doses:
      • (a) 69% vs (b) 23% (P < .001)
      1.101.10
       Stitzer 2010R
      • 13
      • 13
      • (a) $10/visit for transportation, $1-$80 prizes for attending, and >$20 for DOT
      • (b) $10/visit for transportation
      24$486 prizes+$265 DOTEach weekly visit and DOT visits
      • Doses received:
      • (a) 91% vs (b) 78% (P=.22)
      • Doses received on time:
      • (a) 74% vs (b) 51% (P=.02)
      • Received all doses:
      • (a) 77% vs (b) 46% (P=.11)
      • Weeks attended:
      • (a) 82% vs (b) 64% (P=.14)
      • Consecutive weeks attended:
      • (a) 17 vs (b) 12 (P=.10)
      • 0.54
      • 1.11
      • 0.75
      • 0.65
      • 0.70
      0.75
      Psychosis
       Claassen 2007NR4
      • (a) £5-15/DOT (depending on frequency of DOT)
      • (b) Past 2-y records of same patients
      3-24VariedEach DOT
      • Days hospitalized:
      • (a) 9.3 vs (b) 214.5
      1.511.51
       Staring 2010NR5
      • (a) €10-20/DOT (depending on frequency of DOT)
      • (b) Past year's records of same patients
      52$260Each DOT
      • Injections received:
      • (a) 100% vs (b) 44%
      • Days hospitalized:
      • (a) 3.4 vs (b) 100.2
      • 1.24
      • 0.34
      0.79
      Stroke Prevention
       Volpp 2008NR
      • 10
      • 10
      • 25
      • (a) Chance to win $10-$100/d ($5/d average) for MEMS adherence
      • (b) Chance to win $10-$100/d ($3/d average) for MEMS adherence
      • (c) Historical patients
      12
      • (a) $420
      • (b) $252
      Informed of earnings daily
      • Days correct pill taking:
      • (a) 97.7% vs (c) 78.0%
      • (b) 98.4% vs (c) 82.9%
      • Plasma levels out of range:
      • (a) 12.2% vs (c) 35.0%
      • (b) 40.4% vs (c) 65.0%
      • NEI
      • NEI
      • 0.75
      • 0.56
      0.65
      d=effect size; average d is unadjusted and unweighted; R=randomized; NR=not randomized; DOT=directly observed therapy; MEMS=Medication Event Monitoring System; NEI=not enough information to calculate effect sizes.
      For Morisky et al (2001), the N analyzed differs from N randomized (794 vs 767). In Martins et al (2009), results from the study were greatly affected by civil conflict in the study region. In Grabowski et al (1979), the 9 reinforcement patients each received 2 conditions. For Rigsby et al (2000), estimates were derived from a figure. For Claassen et al (2007), the treatment and comparison periods were not equivalent across patients. For Jakubowiak et al (2007), reinforcement magnitude was calculated on the basis of available data (monthly estimates for food packages only). Estimates for treatment completion in Preston et al (1999) were reported in Nunes et al (2006).
      One nonrandomized
      • Grabowski J.
      • O'Brien C.P.
      • Greenstein R.
      • Ternes J.
      Effects of contingent payment on compliance with a naltrexone regimen.
      and 4 randomized
      • Preston K.L.
      • Silverman K.
      • Umbricht A.
      • et al.
      Improvement in naltrexone treatment compliance with contingency management.
      • Carroll K.M.
      • Ball S.A.
      • Nich C.
      • et al.
      Targeting behavioral therapies to enhance naltrexone treatment of opioid dependence: efficacy of contingency management and significant other involvement.
      • Carroll K.M.
      • Sinha R.
      • Nich C.
      • et al.
      Contingency management to enhance naltrexone treatment of opioid dependence: a randomized clinical trial of reinforcement magnitude.
      • Nunes E.V.
      • Rothenberg J.
      • Sullivan M.
      • et al.
      Behavioral therapy to augment oral naltrexone for opioid dependence: a ceiling on effectiveness?.
      studies reinforced adherence to naltrexone, a medication used to prevent relapse to opioid dependence. Reinforcement was contingent on directly observed therapy, and all studies used cash or vouchers, exchangeable for retail goods and services, as reinforcers. All found significant effects or trends (P < .10) of the reinforcement intervention on 1 or more adherence measure.
      Three randomized studies
      • Rigsby M.O.
      • Rosen M.I.
      • Beauvais J.
      • et al.
      Cue-dose training with monetary reinforcement: pilot study of an antiretroviral adherence intervention.
      • Rosen M.I.
      • Dieckhaus K.
      • McMahon J.T.
      • et al.
      Improved adherence with contingency management.
      • Sorensen J.L.
      • Haug N.A.
      • Delucchi K.L.
      • et al.
      Voucher reinforcement improves medication adherence in HIV-positive methadone patients: a randomized trial.
      reinforced medication adherence in patients with human immunodeficiency virus (HIV), each using Medication Event Monitoring System caps to assess adherence. Significant effects were noted with respect to the primary adherence outcomes in all studies.
      Two randomized studies reinforced adherence to hepatitis vaccines.
      • Seal K.H.
      • Kral A.H.
      • Lorvick J.
      • et al.
      A randomized controlled trial of monetary incentives vs outreach to enhance adherence to the hepatitis B vaccine series among injection drug users.
      • Stitzer M.L.
      • Polk T.
      • Bowles S.
      • Kosten T.
      Drug users' adherence to a 6-month vaccination protocol: effects of motivational incentives.
      Both found significant benefits for overall adherence or timely receipt of injections, but Stitzer et al's
      • Stitzer M.L.
      • Polk T.
      • Bowles S.
      • Kosten T.
      Drug users' adherence to a 6-month vaccination protocol: effects of motivational incentives.
      study only found trends with respect to other outcomes.
      Two nonrandomized studies
      • Claassen D.
      • Fakhoury W.K.
      • Ford R.
      Money for medication: financial incentives to improve medication adherence in assertive outreach.
      • Staring A.B.P.
      • Van der Gaag M.
      • Koopmans G.T.
      • et al.
      Treatment adherence therapy in people with psychotic disorders: randomised controlled trial.
      applied financial reinforcers for adherence to antipsychotic depot injections. Both demonstrated high rates of adherence or improvements in functioning related to medication administration (eg, fewer hospitalizations) relative to pre-reinforcement periods.
      One study
      • Volpp K.G.
      • Loewenstein G.
      • Troxel A.B.
      • et al.
      A test of financial incentives to improve warfarin adherence.
      reinforced warfarin adherence in patients at risk of stroke. Compared with historical controls, benefits of reinforcement were noted, with no differences between the 2 conditions that slightly varied probabilities and magnitudes of reinforcement.
      Figure 1 shows effect sizes and confidence intervals (CIs) derived from each of the 21 studies. Studies are organized by disease entity and then by publication date. By using the overall effect size calculated for each study, the average corrected effect size across the 21 studies was 0.77 (standard error [SE]=.03). This effect size was statistically significant (P < .001; 95% CI, 0.70-0.84), showing benefits of financial reinforcement for improving adherence measures. The Failsafe N indicated that 60 studies finding no effect of financial reinforcement interventions would be necessary to lower the obtained mean effect size of 0.77 to a small effect size of 0.20.
      Figure thumbnail gr1
      Figure 1Effect sizes (d) and 95% CIs by disease state and study. Studies are listed by the disease state for which adherence to treatment was reinforced. Morisky 1990 (a) refers to an active sample of patients with tuberculosis, and Morisky 1990 (p) refers to a preventive sample of tuberculosis cases. The total effect size represents all 21 studies. CI=confidence interval; HIV=human immunodeficiency virus.
      Significant heterogeneity was present (Q [20]=291.55, P < .001), and the inconsistency index (I2) suggested that 93% of the variability was due to true heterogeneity rather than sampling error. In the moderator analysis exploring this heterogeneity, randomization status and the 3 behavioral parameters explained significant variability in effect sizes (model Q [4]=172.05, P < .001, R2=0.59).
      All 4 moderators were significant predictors. Randomized studies (n=15) had a significantly smaller average effect size (M=0.44, SE=0.05) than nonrandomized studies (M=1.22, SE=0.05; B=−0.62, P < .001). Nevertheless, the effect size of randomized studies remained significant (P < .001; 95% CI, 0.35-0.53).
      In terms of parameters of the reinforcement interventions, duration of reinforcement was significantly and positively associated with effect size (B=0.16, P=.02). Mean effect size for studies providing $50 or more in weekly reinforcement was 1.18 (SE=0.14) compared with a mean effect size of 0.74 (SE=0.04) for studies with weekly reinforcement of less than $50 (B=0.38, P < .001). Studies providing at least weekly reinforcement had a significantly higher effect size (M=1.00; SE=0.04) than studies with less frequent reinforcement (M=0.25, SE = 0.06; B = 0.20, P=.009).

      Discussion

      Financial reinforcement interventions are beneficial for improving medication adherence with an overall mean effect size of 0.77. An additional 60 studies would need to have been conducted, and to have found nonsignificant effects, to reverse the conclusion drawn. All 4 moderators evaluated significantly impact effect sizes. Compared with nonrandomized studies, randomized studies had a smaller, but statistically significant, effect size in the moderate range. Consistent with behavioral economic principles,
      • Dallery J.
      • Silverman K.
      • Chutuape M.A.
      • et al.
      Voucher-based reinforcement of opiate plus cocaine abstinence in treatment-resistant methadone patients: effects of reinforcer magnitude.
      • Silverman K.
      • Chutuape M.A.
      • Bigelow G.E.
      • Stitzer M.L.
      Voucher-based reinforcement of cocaine abstinence in treatment-resistant methadone patients: effects of reinforcement magnitude.
      greater magnitudes of reinforcement engendered larger effect sizes. Further, studies that reinforced patients at least weekly had large mean effect size, whereas those with less frequent reinforcement resulted in a small mean effect size. Similar issues influence effect sizes in studies of reinforcement interventions for treating substance use disorders
      • Lussier J.P.
      • Heil S.H.
      • Mongeon J.A.
      • et al.
      A meta-analysis of voucher-based reinforcement therapy for substance use disorders.
      • Prendergast M.
      • Podus D.
      • Finney J.
      • et al.
      Contingency management for treatment of substance use disorders: a meta-analysis.
      and suggest that reinforcement magnitude and frequency should be considered in designing reinforcement interventions to enhance medication adherence.
      A positive association was found between reinforcement duration and effect size. One meta-analysis of reinforcement interventions did not find that intervention duration influences effect size,
      • Lussier J.P.
      • Heil S.H.
      • Mongeon J.A.
      • et al.
      A meta-analysis of voucher-based reinforcement therapy for substance use disorders.
      but another found intervention duration was inversely associated with effect size in substance-abusing populations.
      • Prendergast M.
      • Podus D.
      • Finney J.
      • et al.
      Contingency management for treatment of substance use disorders: a meta-analysis.
      Differences across populations may occur because of the truncated durations of most substance-abuse treatment trials (usually12 weeks) relative to medication trials. The longer durations in which reinforcers were applied in some medication adherence studies likely related to the intended duration of medication administration. For time-limited medications for tuberculosis and vaccine series, financial reinforcers were often in place throughout the duration of the medication period, 24 to 52 weeks. In other cases, reinforcers were applied during treatment initiation (eg, naltrexone for opioid dependence) or for relatively short durations once poor adherence was identified (eg, HIV, stroke prevention). The larger effect size in longer duration studies suggests that additional research should evaluate reinforcement duration and its impact on outcomes systematically.
      For chronic medication administration, 3 studies in HIV-positive patients
      • Rigsby M.O.
      • Rosen M.I.
      • Beauvais J.
      • et al.
      Cue-dose training with monetary reinforcement: pilot study of an antiretroviral adherence intervention.
      • Rosen M.I.
      • Dieckhaus K.
      • McMahon J.T.
      • et al.
      Improved adherence with contingency management.
      • Sorensen J.L.
      • Haug N.A.
      • Delucchi K.L.
      • et al.
      Voucher reinforcement improves medication adherence in HIV-positive methadone patients: a randomized trial.
      and 1 study in patients at risk for stroke
      • Volpp K.G.
      • Loewenstein G.
      • Troxel A.B.
      • et al.
      A test of financial incentives to improve warfarin adherence.
      evaluated post-treatment effects on adherence. In the HIV trials, patients who earlier received reinforcement had numeric increases in adherence compared with those who did not receive reinforcement, but none revealed statistically significant benefits throughout follow-up. The lack of sustained effects on adherence may relate to sample size, because studies were not powered to detect significance in post-intervention periods. Some studies of financial reinforcers to reduce substance use likewise failed to achieve significant long-term benefits,
      • Higgins S.T.
      • Heil S.H.
      • Dantona R.
      • et al.
      Effects of varying the monetary value of voucher-based incentives on abstinence achieved during and following treatment among cocaine-dependent outpatients.
      • Petry N.M.
      • Alessi S.M.
      • Marx J.
      • et al.
      Vouchers versus prizes: contingency management treatment of substance abusers in community settings.
      • Petry N.M.
      • Alessi S.M.
      • Hanson T.
      • Sierra S.
      Randomized trial of contingent prizes versus vouchers in cocaine-using methadone patients.
      • Rawson R.A.
      • Huber A.
      • McCann M.
      • et al.
      A comparison of contingency management and cognitive-behavioral approaches during methadone maintenance treatment for cocaine dependence.
      but others found enduring benefits.
      • Iguchi M.Y.
      • Belding M.A.
      • Morral A.R.
      • et al.
      Reinforcing operants other than abstinence in drug abuse treatment: an effective alternative for reducing drug use.
      • Petry N.M.
      • Martin B.
      Low-cost contingency management for treating cocaine- and opioid-abusing methadone patients.
      • Petry N.M.
      • Martin B.
      • Simcic F.
      Prize reinforcement contingency management for cocaine dependence: integration with group therapy in a methadone clinic.
      A robust predictor of long-term effects in substance-abuse treatment trials is the longest duration of continuous behavior change during treatment.
      • Petry N.M.
      • Alessi S.M.
      • Marx J.
      • et al.
      Vouchers versus prizes: contingency management treatment of substance abusers in community settings.
      • Petry N.M.
      • Alessi S.M.
      • Hanson T.
      • Sierra S.
      Randomized trial of contingent prizes versus vouchers in cocaine-using methadone patients.
      • Petry N.M.
      • Martin B.
      • Simcic F.
      Prize reinforcement contingency management for cocaine dependence: integration with group therapy in a methadone clinic.
      • Higgins S.T.
      • Badger G.J.
      • Budney A.J.
      Initial abstinence and success in achieving longer term cocaine abstinence.
      • Petry N.M.
      • Alessi S.M.
      • Carroll K.M.
      • et al.
      Contingency management treatments: reinforcing abstinence versus adherence with goal-related activities.
      To date, only 1 medication adherence study
      • Sorensen J.L.
      • Haug N.A.
      • Delucchi K.L.
      • et al.
      Voucher reinforcement improves medication adherence in HIV-positive methadone patients: a randomized trial.
      reported on continuous days of adherence, but it did not evaluate associations between this variable and long-term adherence. More research is needed to examine conditions under which financial reinforcers engender sustained effects for diseases that require chronic medication administration.
      Across populations, different techniques were used to ascertain adherence. Directly observed therapy (oral or injection) was used for medications with less than daily administration and Medication Event Monitoring System caps for more frequent dosing schedules. Advantages of directly observed therapy are that providers can be assured the medication was ingested, a concern for medications with significant side effect profiles and those for which nonadherence may have a substantial impact on public health (ie, infectious diseases). Primary disadvantages of reinforcing directly observed therapy relate to patient inconvenience for travel to the clinic and administrative costs for staff monitoring. These difficulties are minimized when patients are attending clinics regularly for other reasons (eg, methadone) or when limited doses are required (eg, a 3-part vaccine or time-limited therapy). The key advantage of electronic pill caps is that patients can take medications in their natural environments. Concerns relate to the need to download data at the clinic, which places a delay between the behavior and the reinforcer. In addition, patients can open containers without ingesting medication. Nevertheless, studies that reinforced Medication Event Monitoring System cap openings
      • Rigsby M.O.
      • Rosen M.I.
      • Beauvais J.
      • et al.
      Cue-dose training with monetary reinforcement: pilot study of an antiretroviral adherence intervention.
      • Rosen M.I.
      • Dieckhaus K.
      • McMahon J.T.
      • et al.
      Improved adherence with contingency management.
      • Sorensen J.L.
      • Haug N.A.
      • Delucchi K.L.
      • et al.
      Voucher reinforcement improves medication adherence in HIV-positive methadone patients: a randomized trial.
      • Volpp K.G.
      • Loewenstein G.
      • Troxel A.B.
      • et al.
      A test of financial incentives to improve warfarin adherence.
      included alternate measures of adherence and found associations between Medication Event Monitoring System openings, self-reports, and biological indicators.
      A limitation of this study is that outcomes were not consistently defined across studies, and effect sizes were derived on the basis of the outcome data provided. Relatively few studies included biological indicators of medication adherence, disease progression, or remission status.
      Despite these limitations, this is the most comprehensive review of the literature on the use of financial reinforcement to improve medication adherence. It included a large array of patient populations and used multiple effect sizes per study to provide the most complete and unbiased overall effect size per study. Overall, the effect size of financial reinforcement interventions for improving medication adherence was moderate to large.
      Behavioral economic studies find that individuals place a disproportionate emphasis on immediate outcomes, and they discount delayed and probabilistic events.
      • Chapman G.B.
      • Elstein A.S.
      Valuing the future: temporal discounting of health and money.
      • Madden G.J.
      • Petry N.M.
      • Johnson P.S.
      Pathological gamblers discount probabilistic rewards less steeply than matched controls.
      • Petry N.M.
      Discounting of money, health, and freedom in substance abusers and controls.
      In the context of medication adherence, immediate inconveniences associated with medication ingestion or its side effects may be heavily weighted while the long-term and probabilistic outcomes of disability and death are devalued. By placing more direct and immediate beneficial consequences on medication ingestion via financial reinforcers, adherence increases, resulting in potential benefits for patients and society.
      One of the studies identified in this review reported on the cost-effectiveness of financial reinforcement procedures.
      • Kominski G.F.
      • Varon S.F.
      • Morisky D.E.
      • et al.
      Costs and cost-effectiveness of adolescent compliance with treatment for latent tuberculosis infection: results from a randomized trial.
      Further evaluation of cost-effectiveness and cost-benefits of these approaches may reveal conditions under which and populations for whom financial reinforcement interventions for adherence ultimately may become a part of standard care and a reimbursable or publicly covered cost.
      • Sokol M.C.
      • McGuigan K.A.
      • Verbrugge R.R.
      • Epstein R.S.
      Impact of medication adherence on hospitalization risk and healthcare cost.
      For example, Buchanan
      • Buchanan R.J.
      Compliance with tuberculosis drug regimens: incentives and enablers offered by public health departments.
      reported that 16 states provide cash reinforcers for patients with tuberculosis to comply with medications, and more than 40 states provide meals or clothing for tuberculosis medication adherence. Other medical conditions for which financial reinforcement interventions may be useful to enhance adherence include hypertension, high cholesterol, asthma, and type 2 diabetes.

      Conclusions

      Despite demonstrated successes, providing patients with financial reinforcers is highly controversial.
      • Promberger M.
      • Brown R.C.
      • Ashcroft R.E.
      • Marteau T.
      Acceptability of financial incentives to improve health outcomes in UK and US samples.
      An ongoing study using these approaches with patients under psychiatric care in the United Kingdom
      • Priebe S.
      • Burton A.
      • Ashby D.
      • et al.
      Financial incentives to improve adherence to anti-psychotic maintenance medication in non-adherent patients—a cluster randomized controlled trial (FIAT).
      has been met with considerable skepticism. Decisions about which patients receive financial reinforcers require careful consideration to balance concerns about equitability, possibilities of unintended behaviors, and costs and benefits of treatment. Results from this meta-analysis indicate that ethical and logistic issues should be addressed, because providing financial reinforcers has pronounced benefits for improving medication adherence.

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