The Habit Formation trial of behavioral economic interventions to improve statin use and reduce the risk of cardiovascular disease: Rationale, design and methodologies

BACKGROUND

Low adherence to statin (HMG-CoA reductase inhibitors) medication is common. Here, we report on the design and implementation of the Habit Formation trial. This clinical trial assessed whether the interventions, based on principles from behavioral economics, might improve statin adherence and lipid control in at-risk populations. We describe the rationale and methods for the trial, recruitment, conduct and follow-up. We also report on several barriers we encountered with recruitment and conduct of the trial, solutions we devised and efforts we will make to assess their impact on our study.

METHODS

Habit Formation is a four-arm randomized controlled trial. Recruitment of 805 participants at elevated risk of atherosclerotic cardiovascular disease with evidence of sub-optimal statin adherence and low-density lipoprotein (LDL) control is complete. Initially, we recruited from large employers (Employers) and a national health insurance company (Insurers) using mailed letters; individuals with a statin Medication Possession Ratio less than 80% were invited to participate. Respondents were enrolled if a laboratory measurement of low-density lipoprotein was >130 mg/dL. Subsequently, we recruited participants from the Penn Medicine Health System; individuals with usual-care low-density lipoprotein of >100 mg/dL in the electronic medical record were recruited using phone, text, email, and regular mail. Eligible participants self-reported incomplete medication adherence. During a 6-month intervention period, all participants received a wireless-enabled pill bottle for their statins and daily reminder messages to take their medication. Principles of behavioral economics were used to design three financial incentives, specifically a Simple Daily Sweepstakes rewarding daily medication adherence, a Deadline Sweepstakes where participants received either a full or reduced incentive depending on whether they took their medication before or after a daily reminder or Sweepstakes Plus Deposit Contract with incentives divided between daily sweepstakes and a monthly deposit. Six months post-incentives, we compared the primary outcome, mean change from baseline low-density lipoprotein, across arms.

RESULTS AND LESSONS LEARNED

Health system recruitment yielded substantially better enrollment and was cost-efficient. Despite unexpected systematic failure and/or poor availability of two wireless pill bottles, we achieved enrollment targets and implemented the interventions. For new trials, we will routinely monitor device function and have contingency plans in the event of systemic failure.

CONCLUSION

Interventions used in the Habit Formation trial could be translated into clinical practice. Within a large health system, successful recruitment depended on identification of eligible individuals through their electronic medical record, along with flexible ways of contacting these individuals. Challenges with device failure were manageable. The study will add to our understanding of optimally structuring and implementing incentives to motivate durable behavior change.

Assessment of Medicaid Beneficiaries Included in Community Engagement Requirements in Kentucky

Importance

States are pursuing Section 1115 Medicaid demonstration waiver authority to apply community engagement (CE) requirements (eg, participation in work, volunteer activities, or training) to beneficiaries deemed able-bodied as a condition of coverage. Understanding the size and characteristics of the populations included in these requirements can help inform policy initiatives and anticipate effects.

Objective

To estimate the number and characteristics of Kentucky Medicaid beneficiaries who would have to meet CE requirements.

Design, Setting, and Participants

Cross-sectional study in which administrative records for the entire population of Medicaid beneficiaries in Kentucky as of February 2018 and original survey data, based on responses from 9396 Medicaid beneficiaries included in the waiver program, were analyzed.

Exposures

Eligibility for Kentucky's Medicaid demonstration waiver as of the originally planned implementation date (July 2018).

Main Outcomes and Measures

Number of beneficiaries included in CE requirements, including those already meeting vs not meeting hour quotas and those who may qualify for medical frailty exemptions.

Results

Among the 9396 individuals included in the Section 1115 waiver program who participated in the survey, the mean weighted (SD) age was 36.1 (11.9) years; a weighted 47.2% of respondents were female, and most beneficiaries (weighted percentage, 78.2%) were non-Hispanic white participants. We estimated that 132 790 (95% CI, 129 132-136 449) beneficiaries would have been required to meet CE requirements in July 2018, amounting to 40.2% of Medicaid beneficiaries included in the demonstration waiver. Of this group, 25 422 (95% CI, 23 135-27 710) beneficiaries may have qualified for a medical frailty exemption either by self-attestation (after confirmation by their Medicaid insurer) or by being identified as eligible by physicians or their insurer. Another 58 943 (95% CI, 55 687-62 196) beneficiaries likely would have met CE hour requirements and been required to report compliance. Ultimately, 48 427 (95% CI, 45 281-51 574) individuals would have had to add new activities to meet CE requirements, amounting to 14.7% of those included in the demonstration waiver as a whole and 36.3% of those included in the CE component of the waiver. Beneficiaries in the potentially medically frail group reported worse socioeconomic status, poorer health outcomes, and higher rates of hospital admission and emergency department use than those meeting CE requirements. Similarly, the group currently not meeting and not exempt from CE hour requirements reported worse socioeconomic status than those meeting the CE requirements, although magnitudes of the differences were smaller.

Conclusions and Relevance

Findings suggest that most beneficiaries who would be included in CE programs either already meet activity requirements, which they will be required to proactively report, or may qualify for a medical frailty exemption. Consequently, the outcomes of CE programs will depend on states' processes for addressing health-related, socioeconomic, and administrative barriers to participating in and reporting CE activities and identifying medical frailty.

Association Between the Implementation of a Population-Based Primary Care Payment System and Achievement on Quality Measures in Hawaii

Importance

Hawaii Medical Service Association (HMSA), the Blue Cross Blue Shield of Hawaii, introduced Population-based Payments for Primary Care (3PC), a new capitation-based primary care payment system, in 2016. The effect of this system on quality measures has not been evaluated.

Objective

To evaluate whether the 3PC system was associated with changes in quality, utilization, or spending in its first year.

Design, Setting, and Participants

Observational study using HMSA claims and clinical registry data from January 1, 2012, to December 31, 2016, and a propensity-weighted difference-in-differences method to compare 77 225 HMSA members in Hawaii attributed to 107 primary care physicians (PCPs) and 4 physician organizations participating in the first wave of the 3PC and 222 233 members attributed to 312 PCPs and 14 physician organizations that continued in a fee-for-service model in 2016 but had 3PC start dates thereafter.

Exposures

Participation in the 3PC system.

Main Outcomes and Measures

The primary outcome was the change in a composite measure score reflecting the probability that a member achieved an eligible measure out of 13 pooled Healthcare Effectiveness Data and Information Set quality measures. Primary care visits and total cost of care were among 15 secondary outcomes.

Results

In total, the study included 299 458 HMSA members (mean age, 42.1 years; 51.5% women) and 419 primary care physicians (mean age, 54.9 years; 34.8% women). The risk-standardized composite measure scores for 2012 to 2016 changed from 75.1% to 86.6% (+11.5 percentage points) in the 3PC group and 74.3% to 83.5% (+9.2 percentage points) in the non-3PC group (differential change, 2.3 percentage points [95% CI, 2.1 to 2.6 percentage points]; P < .001). Of 15 prespecified secondary end points for utilization and spending, 11 showed no significant difference. Compared with the non-3PC group, the 3PC system was associated with a significant reduction in the mean number of primary care visits (3.3 to 3.0 visits vs 3.3 to 3.1 visits; adjusted differential change, -3.9 percentage points [95% CI, -4.6 to -3.2 percentage points]; P < .001), but there was no significant difference in mean total cost of care ($3344 to $4087 vs $2977 to $3564; adjusted differential change, 1.0% [95% CI, -1.3% to 3.4%]; P = .39).

Conclusions and Relevance

In its first year, the 3PC population-based primary care payment system in Hawaii was associated with small improvements in quality and a reduction in PCP visits but no significant difference in the total cost of care. Additional research is needed to assess longer-term outcomes as the program is more fully implemented and to determine whether results are generalizable to other health care markets.

Prediction using a randomized evaluation of data collection integrated through connected technologies (PREDICT): Design and rationale of a randomized trial of patients discharged from the hospital to home

BACKGROUND

Hospital readmission prediction models often perform poorly. A critical limitation is that they use data collected up until the time of discharge but do not leverage information on patient behaviors at home after discharge.

METHODS

PREDICT is a two-arm, randomized trial comparing ways to use remotely-monitored patient activity levels after hospital discharge to improve hospital readmission prediction models. Patients are randomly assigned to use a wearable device or smartphone application to track physical activity data. The study collects also validated assessments on patient characteristics as well as disparate data on credit scores and medication adherence. Patients are followed for 6 months. We evaluate whether these data sources can improve prediction compared to standard modelling approaches.

CONCLUSION

The PREDICT Trial tests a novel method of remotely-monitoring patient behaviors after hospital discharge. Findings from the trial could inform new ways to improve the identification of patients at high-risk for hospital readmission.

TRIAL REGISTRATION

Clinicaltrials.gov Identifier: NCT02983812.

Use of financial incentives and text message feedback to increase healthy food purchases in a grocery store cash back program: a randomized controlled trial

Background

The HealthyFood (HF) program offers members up to 25% cash back monthly on healthy food purchases. In this randomized controlled trial, we tested the efficacy of financial incentives combined with text messages in increasing healthy food purchases among HF members.

Methods

Members receiving the lowest (10%) cash back level were randomized to one of six arms: Arm 1 (Usual Care): 10% cash back, no weekly text, standard monthly text; Arm 2: 10% cash back, generic weekly text, standard monthly text; Arm 3: 10% cash back, personalized weekly text, standard monthly text; Arm 4: 25% cash back, personalized weekly text, standard monthly text; Arm 5: 10 + 15%NET cash back, personalized weekly text, standard monthly text; and, Arm 6: 10 + 15%NET cash back, personalized weekly text, unbundled monthly text. In the 10 + 15%NET cash back, the cash back amount was the baseline 10% plus 15% of the net difference between healthy and unhealthy spending. The generic text included information on HF and healthy eating, while the personalized text had individualized feedback on purchases. The standard monthly text contained the cash back amount. The unbundled monthly text included the amount lost due to unhealthy purchases. The primary outcome was the average monthly percent healthy food spending. Secondary outcomes were the percent unhealthy food spending, and the percent healthy and unhealthy food items.

Results

Of the members contacted, 20 opted out, and 2841 met all inclusion criteria. There were no between-arm differences in the examined outcomes. The largest mean (standard deviation) difference in percent healthy spending was between Arm 1 (24.8% [11%]) and Arm 2 (26.8% [13%]), and the largest mean difference in percent unhealthy spending was also between Arm 1 (24.4% [20%]) and Arm 2 (21.7% [17%]), but no differences were statistically significant after correction for multiple comparisons.

Conclusions

None of the tested financial incentive structures or text strategies differentially affected food purchasing. Notably, more than doubling the cash back amount and introducing a financial disincentive for unhealthy purchases did not affect purchasing. These findings speak to the difficulty of changing shopping habits and to the need for innovative strategies to shift complex health behaviors.

Trial registration

NCT02486588 Increasing Engagement with a Healthy Food Benefit. The trial was prospectively registered on July 1, 2015.

Electronic supplementary material

The online version of this article (10.1186/s12889-019-6936-5) contains supplementary material, which is available to authorized users.

Modeling lottery incentives for daily adherence

Many health issues require adherence to recommended daily activities, such as taking medication to manage a chronic condition, walking a certain distance to promote weight loss, or measuring weights to assess fluid balance in heart failure. The cost of nonadherence can be high, with respect to both individual health outcomes and the healthcare system. Incentivizing adherence to daily activities can promote better health in patients and populations and potentially provide long‐term cost savings.

Multiple incentive structures are possible. We focus here on a daily lottery incentive in which payment occurs when both the participant's lottery number matches the number drawn and the participant adheres to the targeted daily behavior.

Our objective is to model the lottery's effect on participants' probability to complete the targeted task, particularly over the short term. We combine two procedures for analyzing such binary time series: a parameter‐driven regression model with an autocorrelated latent process and a comparative interrupted time series. We use the output of the regression model as the control generator for the comparative time series in order to create a quasi‐experimental design.

The association of financial incentives for low density lipoprotein cholesterol reduction with patient activation and motivation

There is growing interest in using financial incentives for patients to improve medication adherence, but few studies have evaluated whether financial incentives are associated with patients' activation and motivation. We analyzed survey data collected as part of a randomized clinical trial conducted from 2011 to 2014 of four financial incentive interventions to reduce low density lipoprotein cholesterol (LDL-C) among patients at risk for atherosclerotic cardiovascular disease. The main trial included 1503 patients aged 18–80 and recruited from primary care practices affiliated with three health systems. Participants were randomized into four groups: patient financial incentives, primary care physicians (PCPs) incentives, patients and PCPs shared incentives, or no incentives for LDL-C control. Patient Activation Measure (PAM) and Treatment Self Regulation Questionnaire (TSRQ) surveys were administered at baseline and 12 months. Clinical outcomes were change in LDL-C at 12 and 15 months and average medication adherence as measured by electronic pill bottle opening. Mean changes in PAM and TSRQ scores were compared between patients eligible and not eligible for incentives. Clinical outcomes were tested against baseline and change in psychosocial measures using bivariate and multivariate regression. Change in PAM score and TSRQ autonomous subscore did not differ significantly between patients eligible and not eligible for incentives. Lower baseline and greater increase in TSRQ autonomous subscore were predictive of greater 15-month decrease in LDL-C. A financial incentive intervention to improve LDL-C control was not associated with changes in patients' activation or autonomous motivation. Increases in patient autonomous motivation are predictive of long-term LDL-C control.

•

Financial incentives for lipid control were not associated with changes in activation or motivation.

•

Participants had high activation and motivation levels at baseline.

•

Increases in autonomous motivation were associated with better lipid control at 15 months.

Sleep and Alertness in a Duty-Hour Flexibility Trial in Internal Medicine

BACKGROUND

A purpose of duty-hour regulations is to reduce sleep deprivation in medical trainees, but their effects on sleep, sleepiness, and alertness are largely unknown.

METHODS

We randomly assigned 63 internal-medicine residency programs in the United States to follow either standard 2011 duty-hour policies or flexible policies that maintained an 80-hour workweek without limits on shift length or mandatory time off between shifts. Sleep duration and morning sleepiness and alertness were compared between the two groups by means of a noninferiority design, with outcome measures including sleep duration measured with actigraphy, the Karolinska Sleepiness Scale (with scores ranging from 1 [extremely alert] to 9 [extremely sleepy, fighting sleep]), and a brief computerized Psychomotor Vigilance Test (PVT-B), with long response times (lapses) indicating reduced alertness.

RESULTS

Data were obtained over a period of 14 days for 205 interns at six flexible programs and 193 interns at six standard programs. The average sleep time per 24 hours was 6.85 hours (95% confidence interval [CI], 6.61 to 7.10) among those in flexible programs and 7.03 hours (95% CI, 6.78 to 7.27) among those in standard programs. Sleep duration in flexible programs was noninferior to that in standard programs (between-group difference, -0.17 hours per 24 hours; one-sided lower limit of the 95% confidence interval, -0.45 hours; noninferiority margin, -0.5 hours; P = 0.02 for noninferiority), as was the score on the Karolinska Sleepiness Scale (between-group difference, 0.12 points; one-sided upper limit of the 95% confidence interval, 0.31 points; noninferiority margin, 1 point; P<0.001). Noninferiority was not established for alertness according to the PVT-B (between-group difference, -0.3 lapses; one-sided upper limit of the 95% confidence interval, 1.6 lapses; noninferiority margin, 1 lapse; P = 0.10).

CONCLUSIONS

This noninferiority trial showed no more chronic sleep loss or sleepiness across trial days among interns in flexible programs than among those in standard programs. Noninferiority of the flexible group for alertness was not established. (Funded by the National Heart, Lung, and Blood Institute and American Council for Graduate Medical Education; ClinicalTrials.gov number, NCT02274818.).

Patient Safety Outcomes under Flexible and Standard Resident Duty-Hour Rules

BACKGROUND

Concern persists that extended shifts in medical residency programs may adversely affect patient safety.

METHODS

We conducted a cluster-randomized noninferiority trial in 63 internal-medicine residency programs during the 2015-2016 academic year. Programs underwent randomization to a group with standard duty hours, as adopted by the Accreditation Council for Graduate Medical Education (ACGME) in July 2011, or to a group with more flexible duty-hour rules that did not specify limits on shift length or mandatory time off between shifts. The primary outcome for each program was the change in unadjusted 30-day mortality from the pretrial year to the trial year, as ascertained from Medicare claims. We hypothesized that the change in 30-day mortality in the flexible programs would not be worse than the change in the standard programs (difference-in-difference analysis) by more than 1 percentage point (noninferiority margin). Secondary outcomes were changes in five other patient safety measures and risk-adjusted outcomes for all measures.

RESULTS

The change in 30-day mortality (primary outcome) among the patients in the flexible programs (12.5% in the trial year vs. 12.6% in the pretrial year) was noninferior to that in the standard programs (12.2% in the trial year vs. 12.7% in the pretrial year). The test for noninferiority was significant (P = 0.03), with an estimate of the upper limit of the one-sided 95% confidence interval (0.93%) for a between-group difference in the change in mortality that was less than the prespecified noninferiority margin of 1 percentage point. Differences in changes between the flexible programs and the standard programs in the unadjusted rate of readmission at 7 days, patient safety indicators, and Medicare payments were also below 1 percentage point; the noninferiority criterion was not met for 30-day readmissions or prolonged length of hospital stay. Risk-adjusted measures generally showed similar findings.

CONCLUSIONS

Allowing program directors flexibility in adjusting duty-hour schedules for trainees did not adversely affect 30-day mortality or several other measured outcomes of patient safety. (Funded by the National Heart, Lung, and Blood Institute and Accreditation Council for Graduate Medical Education; iCOMPARE ClinicalTrials.gov number, NCT02274818.).

Effect of Financial Incentives on Patient Use of Mailed Colorectal Cancer Screening Tests: A Randomized Clinical Trial

Importance

Mailing fecal immunochemical test (FIT) kits to patients' homes has been shown to boost colorectal cancer screening rates, but response rates remain limited, and organized programs typically require repeated outreach attempts. Behavioral economics has shown that offering salient financial incentives to patients may increase participation in preventive health.

Objective

To compare the impact of different financial incentives for mailed FIT outreach.

Design, Setting, and Participants

This 4-parallel-arm randomized clinical trial included patients aged 50 to 75 years who had an established primary care clinician, at least 2 visits in the prior 2 years, and were eligible for colorectal cancer screening and not up-to-date. This study was conducted at urban primary care practices at an academic health system from December 2015 to February 2018. Data analysis was conducted from March 2018 to September 2018.

Interventions

Eligible patients received a letter from their primary care clinician that included a mailed FIT kit and instructions for use. They were randomized in a 1:1:1:1 ratio to receive (1) no financial incentive; (2) an unconditional $10 incentive included with the mailing; (3) a $10 incentive conditional on FIT completion; or (4) a conditional lottery with a 1-in-10 chance of winning $100 after FIT completion.

Main Outcomes and Measures

Fecal immunochemical test completion within 2 and 6 months of initial outreach.

Results

A total of 897 participants were randomized, with a median age of 57 years (interquartile range, 52-62 years); 56% were women, and 69% were black. The overall completion rate across all arms was 23.5% at 2 months. The completion rate at 2 months was 26.0% (95% CI, 20.4%-32.3%) in the no incentive arm, 27.2% (95% CI, 21.5%-33.6%) in the unconditional incentive arm, 23.2% (95% CI, 17.9%-29.3%) in the conditional incentive arm, and 17.7% (95% CI, 13.0%-23.3%) in the lottery incentive arm. None of the arms with an incentive were statistically superior to the arm without incentive. The overall FIT completion rate across all arms was 28.9% at 6 months, and there was also no difference by arm. The completion rate at 6 months was 32.7% (95% CI, 26.6%-39.3%) in the no incentive arm, 31.7% (95% CI, 25.7%-38.2%) in the unconditional incentive arm, 26.8% (95% CI, 21.1%-33.1%) in the conditional incentive arm, and 24.3% (95% CI, 18.9%-30.5%) in the lottery incentive arm.

Conclusions and Relevance

Mailed FIT resulted in high colorectal cancer screening response rates in this population, but different forms of financial incentives of the same expected value ($10) did not incrementally increase FIT completion rates. The incentive value may have been too small or financial incentives may not be effective in this context.

Trial Registration

ClinicalTrials.gov Identifier: NCT02594150.

Transforming Mental Health Delivery Through Behavioral Economics and Implementation Science: Protocol for Three Exploratory Projects

BACKGROUND

Efficacious psychiatric treatments are not consistently deployed in community practice, and clinical outcomes are attenuated compared with those achieved in clinical trials. A major focus for mental health services research is to develop effective and cost-effective strategies that increase the use of evidence-based assessment, prevention, and treatment approaches in community settings.

OBJECTIVE

The goal of this program of research is to apply insights from behavioral economics and participatory design to advance the science and practice of implementing evidence-based practice (EBP) for individuals with psychiatric disorders across the life span.

METHODS

Project 1 (Assisting Depressed Adults in Primary care Treatment [ADAPT]) is patient-focused and leverages decision-making heuristics to compare ways to incentivize adherence to antidepressant medications in the first 6 weeks of treatment among adults newly diagnosed with depression. Project 2 (App for Strengthening Services In Specialized Therapeutic Support [ASSISTS]) is provider-focused and utilizes normative pressure and social status to increase data collection among community mental health workers treating children with autism. Project 3 (Motivating Outpatient Therapists to Implement: Valuing a Team Effort [MOTIVATE]) explores how participatory design can be used to design organizational-level implementation strategies to increase clinician use of EBPs. The projects are supported by a Methods Core that provides expertise in implementation science, behavioral economics, participatory design, measurement, and associated statistical approaches.

RESULTS

Enrollment for project ADAPT started in 2018; results are expected in 2020. Enrollment for project ASSISTS will begin in 2019; results are expected in 2021. Enrollment for project MOTIVATE started in 2018; results are expected in 2019. Data collection had begun for ADAPT and MOTIVATE when this protocol was submitted.

CONCLUSIONS

This research will advance the science of implementation through efforts to improve implementation strategy design, measurement, and statistical methods. First, we will test and refine approaches to collaboratively design implementation strategies with stakeholders (eg, discrete choice experiments and innovation tournaments). Second, we will refine the measurement of mechanisms related to heuristics used in decision making. Third, we will develop new ways to test mechanisms in multilevel implementation trials. This trifecta, coupled with findings from our 3 exploratory projects, will lead to improvements in our knowledge of what causes successful implementation, what variables moderate and mediate the effects of those causal factors, and how best to leverage this knowledge to increase the quality of care for people with psychiatric disorders.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03441399; https://www.clinicaltrials.gov/ct2/show/NCT03441399 (Archived by WebCite at http://www.webcitation.org/74dRbonBD).

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/12121.

Effect of Financial Bonus Size, Loss Aversion, and Increased Social Pressure on Physician Pay-for-Performance: A Randomized Clinical Trial and Cohort Study

Importance

Despite limited effectiveness of pay-for-performance (P4P), payers continue to expand P4P nationally.

Objective

To test whether increasing bonus size or adding the behavioral economic principles of increased social pressure (ISP) or loss aversion (LA) improves the effectiveness of P4P.

Design, Setting, and Participants

Parallel studies conducted from January 1 to December 31, 2016, consisted of a randomized clinical trial with patients cluster-randomized by practice site to an active control group (larger bonus size [LBS] only) or to groups with 1 of 2 behavioral economic interventions added and a cohort study comparing changes in outcomes among patients of physicians receiving an LBS with outcomes in propensity-matched physicians not receiving an LBS. A total of 8118 patients attributed to 66 physicians with 1 of 5 chronic conditions were treated at Advocate HealthCare, an integrated health system in Illinois. Data were analyzed using intention to treat and multiple imputation from February 1, 2017, through May 31, 2018.

Interventions

Physician participants received an LBS increased by a mean of $3355 per physician (LBS-only group); prefunded incentives to elicit LA and an LBS; or increasing proportion of a P4P bonus determined by group performance from 30% to 50% (ISP) and an LBS.

Main Outcomes and Measures

The proportion of 20 evidence-based quality measures achieved at the patient level.

Results

A total of 86 physicians were eligible for the randomized trial. Of these, 32 were excluded because they did not have unique attributed patients. Fifty-four physicians were randomly assigned to 1 of 3 groups, and 33 physicians (54.5% male; mean [SD] age, 57 [10] years) and 3747 patients (63.6% female; mean [SD] age, 64 [18] years) were included in the final analysis. Nine physicians and 864 patients were randomized to the LBS-only group, 13 physicians and 1496 patients to the LBS plus ISP group, and 11 physicians and 1387 patients to the LBS plus LA group. Physician characteristics did not differ significantly by arm, such as mean (SD) physician age ranging from 56 (9) to 59 (9) years, and sex (6 [46.2%] to 6 [66.7%] male). No differences were found between the LBS-only and the intervention groups (adjusted odds ratio [aOR] for LBS plus LA vs LBS-only, 0.86 [95% CI, 0.65-1.15; P = .31]; aOR for LBS plus ISP vs LBS-only, 0.95 [95% CI, 0.64-1.42; P = .81]; and aOR for LBS plus ISP vs LBS plus LA, 1.10 [95% CI, 0.75-1.61; P = .62]). Increased bonus size was associated with a greater increase in evidence-based care relative to the comparison group (risk-standardized absolute difference-in-differences, 3.2 percentage points; 95% CI, 1.9-4.5 percentage points; P < .001).

Conclusions and Relevance

Increased bonus size was associated with significantly improved quality of care relative to a comparison group. Adding ISP and opportunities for LA did not improve quality.

Trial Registration

ClinicalTrials.gov Identifier: NCT02634879.

Randomized evaluation of trial acceptability by INcentive (RETAIN): Study protocol for two embedded randomized controlled trials

INTRODUCTION

The most common and conceptually sound ethical concerns with financial incentives for research participation are that they may (1) represent undue inducements by blunting peoples' perceptions of research risks, thereby preventing fully informed consent; or (2) represent unjust inducements by encouraging enrollment preferentially among the poor. Neither of these concerns has been shown to manifest in studies testing the effects of incentives on decisions to participate in hypothetical randomized clinical trials (RCTs), but neither has been assessed in real RCTs.

METHODS AND ANALYSES

We are conducting randomized trials of real incentives embedded within two parent RCTs. In each of two trials conducted in parallel, we are randomizing 576 participants to one of three incentive groups. Following preliminary determination of patients' eligibility in the parent RCT, we assess patients' research attitudes, demographic characteristics, perceived research risks, time spent reviewing consent documents, ability to distinguish research from patient care, and comprehension of key trial features. These quantitative assessments will be supplemented by semi-structured interviews for a selected group of participants that more deeply explore patients' motivations for trial participation. The trials are each designed to have adequate power to rule out undue and unjust inducement. We are also exploring potential benefits of incentives, including possible increased attention to research risks and cost-effectiveness.

Association of Medicaid Healthy Behavior Incentive Programs With Smoking Cessation, Weight Loss, and Annual Preventive Health Visits

IMPORTANCE

Several states have implemented Healthy Behavior Incentive Programs (HBIPs) in Medicaid through Section 1115 demonstration waivers. These programs use financial incentives to encourage positive behavior changes, such as greater use of preventive services, smoking cessation, and weight loss.

OBJECTIVE

To test for an association between the introduction of HBIPs and the rates of smoking cessation, weight loss, and annual preventive health visits in states that have adopted behavior-specific programs compared with states that have not.

DESIGN, SETTING, AND PARTICIPANTS

A cohort study using a difference-in-differences analysis of the 2011-2016 Behavioral Risk Factor Surveillance Survey Interview Results data, adjusting for demographic conditions, state unemployment rates, state Medicaid expansion, national secular trends, and time invariant state-specific factors, was conducted. Two sets of participants were considered: adults aged 18 to 64 years who had a reported annual household income of less than $25 000 (n = 442 089) or adults aged 18 to 64 years who had completed high school education or less (n = 676 883).

EXPOSURES

Changes in health behavior outcomes in 4 states (Florida, Indiana, Iowa, and Michigan) that implemented behavior-specific HBIPs targeting smoking, obesity, and annual health checkups through a Section 1115 waiver, against changes in control states, including Washington, DC, that did not introduce an HBIP (n = 44).

MAIN OUTCOMES AND MEASURES

Rate of smoking, obesity, and attendance at annual preventive health visits.

RESULTS

Of Behavioral Risk Factor Surveillance Service respondents used for the less than $25 000 annual household income cohort (n = 442 089), the mean (SD) age was 43.1 (0.8) years, and the mean (SD) percentage of women was 58.4% (2.5%). For the cohort of high school education or less (n = 676 883) population, the mean (SD) age was 41.6 (1.1) years, and the mean (SD) percentage of women was 46.6% (0.9%). During a 2-year period after implementation, there were no improvements in smoking and obesity in individuals with a household income of less than $25 000 (2.49 percentage points, 95% CI, 1.75-3.23 percentage points; P < .001 and -1.94 percentage points, 95% CI, -4.42 to 0.55 percentage points; P = .12, respectively) as well as in the population holding a high school education or less (1.74 percentage points, 95% CI, 0.64-2.85 percentage points; P = .003 and -0.73 percentage points, 95% CI, -1.84 to 0.38 percentage points; P = .19). An association was noted between an increase in preventive health visit rates among states adopting behavior-specific HBIPs relative to control states in the less than $25 000 household income population (3.89 percentage points, 95% CI, 2.64-5.14 percentage points; P < .001). However, these associations were substantively small and not robust across the high school education or less population (1.8 percentage points, 95% CI, -0.12 to 3.71 percentage points; P = .07).

CONCLUSIONS AND RELEVANCE

Early postimplementation assessment may indicate that HBIPs were not associated with substantive improvements in incentivized healthy behaviors among populations likely to be Medicaid beneficiaries. The value, format, and timing of the incentive, complexity in delivery, and lack of awareness of incentives among target beneficiaries and clinicians may limit the usefulness of programs even over a longer follow-up period.

Characterizing Tweet Volume and Content About Common Health Conditions Across Pennsylvania: Retrospective Analysis

Background

Tweets can provide broad, real-time perspectives about health and medical diagnoses that can inform disease surveillance in geographic regions. Less is known, however, about how much individuals post about common health conditions or what they post about.

Objective

We sought to collect and analyze tweets from 1 state about high prevalence health conditions and characterize the tweet volume and content.

Methods

We collected 408,296,620 tweets originating in Pennsylvania from 2012-2015 and compared the prevalence of 14 common diseases to the frequency of disease mentions on Twitter. We identified and corrected bias induced due to variance in disease term specificity and used the machine learning approach of differential language analysis to determine the content (words and themes) most highly correlated with each disease.

Results

Common disease terms were included in 226,802 tweets (174,381 tweets after disease term correction). Posts about breast cancer (39,156/174,381 messages, 22.45%; 306,127/12,702,379 prevalence, 2.41%) and diabetes (40,217/174,381 messages, 23.06%; 2,189,890/12,702,379 prevalence, 17.24%) were overrepresented on Twitter relative to disease prevalence, whereas hypertension (17,245/174,381 messages, 9.89%; 4,614,776/12,702,379 prevalence, 36.33%), chronic obstructive pulmonary disease (1648/174,381 messages, 0.95%; 1,083,627/12,702,379 prevalence, 8.53%), and heart disease (13,669/174,381 messages, 7.84%; 2,461,721/12,702,379 prevalence, 19.38%) were underrepresented. The content of messages also varied by disease. Personal experience messages accounted for 12.88% (578/4487) of prostate cancer tweets and 24.17% (4046/16,742) of asthma tweets. Awareness-themed tweets were more often about breast cancer (9139/39,156 messages, 23.34%) than asthma (1040/16,742 messages, 6.21%). Tweets about risk factors were more often about heart disease (1375/13,669 messages, 10.06%) than lymphoma (105/4927 messages, 2.13%).

Conclusions

Twitter provides a window into the Web-based visibility of diseases and how the volume of Web-based content about diseases varies by condition. Further, the potential value in tweets is in the rich content they provide about individuals’ perspectives about diseases (eg, personal experiences, awareness, and risk factors) that are not otherwise easily captured through traditional surveys or administrative data.

A Randomized Controlled Trial of Opt-in Versus Opt-Out Colorectal Cancer Screening Outreach

OBJECTIVES

METHODS:: RESULTS:: Patients randomized to opt-in agreed to participate 23.1% of the time, and only 2.5% of those in opt-out chose not to participate. FIT kits were mailed to 22.4% and 93% of patients in opt-in and opt-out arms, respectively. In intention-to-screen analysis, patients in the opt-out arm had a higher FIT completion rate (29.1%) than in the opt-in arm (9.6%) (absolute difference 19.5%; 95% confidence interval, 10.9-27.9%; P < .001). Results were similar in subgroup analysis of those sent initial messaging through the EHR portal (9.5% opt-in versus 37.5% in opt-out).

CONCLUSIONS

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The Healthy Weigh study of lottery-based incentives and environmental strategies for weight loss: Design and baseline characteristics

Identifying effective strategies for treating obesity is a clinical challenge and a public health priority. The present study is an innovative test of the relative effectiveness of lottery-based financial incentives and environmental strategies on weight loss and maintenance. The Healthy Weigh study is evaluating the comparative effectiveness of behavioral economic financial incentives and environmental strategies, separately and together, in achieving initial weight loss and maintenance of weight loss, in obese urban employee populations. Healthy Weigh is a multi-site, 4-arm randomized controlled trial (RCT) in which 344 employed participants were randomized to one of four arms. The study arms are: 1) standard employee wellness benefits and weigh-ins every 6 months (control arm/usual care); and the control/usual care plus either: 2) daily lottery incentives tied to achievement of weight loss goals (incentive arm); 3) individually tailored environmental strategies around food intake and physical activity (environmental arm); or 4) a combination of incentives and environmental strategies (combined arm). This trial used a web-based platform to enroll, communicate with, and track participant weight change. Wireless scales were used by participants in the three treatment group arms to digitally transmit daily/weekly weights. For females, the baseline median (interquartile range, IQR) for BMI and weight were 37.0 (33.5, 40.6) and 219.9 (198.1, 248.6), respectively; and for males, they were 36.0 (32.8, 39.8) and 247.9 (228.1, 279.5), respectively. The population was generally well-educated. This study demonstrated that multi-site employee-based recruitment for a weight-control intervention study is feasible but may need additional time for coordination between diverse environments.

Increasing participation in a vector control campaign: a cluster randomised controlled evaluation of behavioural economic interventions in Peru

OBJECTIVE

To assess the efficacy of strategies informed by behavioural economics for increasing participation in a vector control campaign, compared with current practice.

DESIGN

Pragmatic cluster randomised controlled trial.

SETTING

Arequipa, Peru.

PARTICIPANTS

4922 households.

INTERVENTIONS

Households were randomised to one of four arms: advanced planning, leader recruitment, contingent group lotteries, or control.

MAIN OUTCOME MEASURES

Participation (allowing the house to be sprayed with insecticide) during the vector control campaign.

RESULTS

In intent-to-treat analyses, none of the interventions increased participation compared with control (advanced planning adjusted OR (aOR) 1.07 (95% CI 0.87 to 1.32); leader recruitment aOR 0.95 (95% CI 0.78 to 1.15); group lotteries aOR 1.12 (95% CI 0.89 to 1.39)). The interventions did not improve the efficiency of the campaign (additional minutes needed to spray house from generalised estimating equation regressions: advanced planning 1.08 (95% CI -1.02 to 3.17); leader recruitment 3.91 (95% CI 1.85 to 5.97); group lotteries 3.51 (95% CI 1.38 to 5.64)) nor did it increase the odds that houses would be sprayed in an earlier versus a later stage of the campaign cycle (advanced planning aOR 0.94 (95% CI 0.76 to 1.25); leader recruitment aOR 0.68 (95% CI 0.55 to 0.83); group lotteries aOR 1.19 (95% CI 0.96 to 1.47)). A post hoc analysis suggested that advanced planning increased odds of participation compared with control among households who had declined to participate previously (aOR 2.50 (95% CI 1.41 to 4.43)).

CONCLUSIONS

Achieving high levels of household participation is crucial for many disease prevention efforts. Our trial was not successful in improving participation compared with the existing campaign. The trial highlights persistent challenges to field experiments as well as lessons about the intervention design process, particularly understanding barriers to participation through a behavioural lens.

TRIAL REGISTRATION NUMBER

American Economic Association AEARCTR-0000620.