Faculty Bibliography

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.

Background: Older adults with diabetes continue to be overtreated despite current guidelines recommending less aggressive target A1c levels based on life expectancy. The suboptimal management of this vulnerable population could be due to physicians having conflicting beliefs regarding this guideline or simply lacking awareness, and changing these behaviors is challenging. Clinical decision support (CDS) within the electronic health record (EHR) has the potential to address this issue, but effectiveness is undermined by alert fatigue and poor workflow integration. Incorporating behavioral economics into CDS tools is an innovative approach to improve adherence to these guidelines while reducing physician burden, and offers the promise of improving care in this population.
Method(s): We applied a systematic, user-centered approach to incorporate behavioral economic " nudges" into a CDS module and performed user testing in six pilot primary care practices in a large academic medical center. To build the nudges, we conducted: (1) semi-structured interviews with key informants (n=8); (2) a two-hour design thinking workshop to derive and refine initial module ideas; and (3) semi-structured group interviews at each site with clinic leaders and clinicians to elicit feedback on the module components. Clinicians were observed using the module in practice; detailed field notes were collected and summarized by module idea and usability theme for rapid iteration and refinement. Frequency of firing and user action taken were assessed in the first month of implementation via EHR reporting to confirm that module components and reporting were working as expected, and to assess utilization.
Result(s): Insights from key stakeholder and clinician group interviews identified the refill protocol, inbasket lab result, and medication preference list as candidate EHR CDS targets for the module. A new EHR navigator section notification and peer comparison message, derived from the design workshop, were also prototyped and produced. User feedback from site visits confirmed compatibility with clinical workflows, and contributed to refinement of design and content. The initial prototypes were first piloted at two sites, refined, and then activated at an additional four additional sites. Preliminary Results for the six clinics indicate that over approximately 31 weeks: 1) the navigator alert fired 1047 times for 53 unique clinicians, and 2) the refill protocol alert fired 421 times for 53 unique clinicians. Reports for the other " nudges" are in development.
Conclusion(s): Integrating behavioral economic nudges into the EHR is a promising approach to enhancing guideline awareness and adherence for older adults with diabetes. This novel pilot will demonstrate the initial feasibility and preliminary efficacy of this strategy and determine if a full-scale effectiveness trial is warranted

Background: In response to modest impact from quality programs, we worked with the Blue Cross Blue Shield of Hawaii to design and implement the Population-based Payments for Primary Care (3PC) system. This system was designed using behavioral economic insights and implemented in a staggered rollout across all Medicare, Medicaid, and commercial members starting in April 2016.
Method(s): We analyzed 2012-2016 claims and quality registry data for 77,225 HMSA members attributed to 107 primary care physicians (PCPS) and 4 organizations (POs) participating in the 1st wave of the 3PC and for 222,233 members attributed to 312 PCPS in 14 POs that continued in fee-for service in 2016 but had staggered 3PC start dates thereafter. We used a propensity-weighted, difference-in-differences design to compare risk-adjusted changes in quality, cost, and utilization among patients in the 3PC group to those in the non-3PC group-after confirming parallel pre-intervention trends. We used generalized linear models with an identity link for quality, log link and gamma distribution for cost, and log link and negative binomial distribution for utilization, with standard errors clustered by PCP.
Result(s): The groups exhibited small baseline differences in demographics, risk scores, and socioeconomic characteristics. Adjusted analysis indicated an association between the 3PC group and increases in quality in 2016 (differential change in risk-standardized quality scores of 2.3 percentage points (p.p.), 95% CI 2.1 to 2.6 p.p., p< 0.001). In secondary analyses, performance on 5 quality measures improved, 2 measures worsened, with no changes for six measures (see Figure). There were significant differential reductions in primary care cost (-3.9%, 95% CI-4.8% to-2.9%, p< 0.001), but not total cost of care (1.0%, 95% CI-1.3% to 3.4%, p=0.39). Prescription drug cost differentially increased by 20.1% (95% CI 10.2% to 32.5%, p< 0.001). Changes in utilization by category were similar in magnitude to changes in cost by category.
Conclusion(s): The 3PC was associated with improvements in quality in its first year. Reduction in primary care visits and costs indicate shifts in practice patterns away from visit-based care. This study offers early evidence on the feasibility and effectiveness of shifting to a population-based primary care payment system across commercial, Medicare, and Medicaid populations in a fragmented market, which may have generalizable implications for other markets with similar characteristics nationwide. [Figure Presented]

Background: Peer comparisons, providing feedback on clinician performance relative to peers, have been tested successfully in narrow settings such as increasing guideline-based antibiotic and opioid prescribing. However, there are no studies evaluating the effectiveness of peer comparisons on broader quality measures in the setting of alternative payment models.
Method(s): We conducted a cluster randomized trial with the Blue Cross Blue Shield of Hawaii to examine the impact of providing peer comparison feedback to its primary care practitioners (PCPs) on the quality of care. This study included patients of 86 PCPs randomized to receiving peer comparisons plus individual feedback (intervention group) versus individual feedback alone (control group). Feedback was provided on quality, cost, and utilization performance. All PCPs were also simultaneously moved to a new population-based primary care payment system. The primary outcome was the probability of achieving national benchmark thresholds on thirteen primary care focused quality metrics that included preventative and chronic disease measures. We analyzed the primary outcome using a generalized linear model, adjusting for patient characteristics, PCP characteristics, baseline proportion of measures achieved by the patient, and a quality measure fixed-effect, clustering standard errors at the PCP.
Result(s): The RCT included 27,930 patients and 31 PCPs in the control group and 46,694 patients and 55 PCPs in the intervention group. Patients nor PCPs exhibited large differences across groups, with small differences in demographics and panel size, respectively. In primary analysis, the patients in the peer comparisons intervention group experienced a 2.4 percentage point (pp) increase in the probability of achieving an eligible quality measure (95% CI 0.3 pp to 4.6 pp, p=0.03). Secondary analysis of individual measures indicated that Breast Cancer Screening (3.9 pp, 95% CI 0.2 to 6.0 pp, p< 0.001), Cervical Cancer Screening (2.4 pp, 95% CI 0.01to 4.8 pp, p=0.05), Colorectal Cancer Screening (2.8 pp, 95% CI 0.3 to 5.2 pp, p=0.03), Diabetes Care-Eye Exam (5.6 pp, 95% CI 1.6 to 9.5 pp, p = 0.006), Diabetes Care-Medical Attention for Nephrop-athy (2.5 pp, 95% CI 0.4 to 4.6 pp, p=0.02) and Review of Chronic Conditions (4.9 pp, 95% CI 0.0 to 9.8 pp, p=0.05) likely accounted for the increased overall quality score. Other measures demonstrated trends toward differential improvement, but associations were not significant. Cost and utilization did not demonstrate differences between arms.
Conclusion(s): A peer comparisons intervention that displayed quality information in a real-time dashboard in the setting of a broad primary care payment system change improved quality scores by over 2 percentage points. This highlights the ability of peer comparisons to influence clinician practice in broad endpoints and is reassuring in light of new payment programs that have begun sharing comparative feedback

Background/Objective: Growing evidence suggests that tumor immune-microenvironment influences breast cancer carcinogenesis and prognosis. Density of tumor-infiltrating lymphocytes (TILs) within invasive breast cancer correlates with response to therapy, especially in triple-negative disease. The clinical relevance and outcomes of TILs within ductal carcinoma in situ (DCIS) is less understood.
Method(s): Our institutional database was queried for pure DCIS from 2010-2018 (n=668). Local recurrences (n=13) were matched 1:4 to patients without recurrence. TILs were evaluated by the International TILs Working Group Guidelines. Percentage of TILs was assessed from the densest focus in 1 high-power field of stroma touching the basement membrane. Statistical methods included cluster analyses, logistic, and Cox regression models.
Result(s): Sixty-nine patients, including the 13 recurrences were evaluated. Fifty-four (78%) were treated by breast-conserving surgery (BCS). The median follow-up was 6.7 years. TILs were defined as sparse (<45%) and dense (>=45%). Dense TILs was associated with younger age (p=0.045), larger tumor size (p<0.001), high nuclear grade (p<0.001), comedo histology (p=0.016), necrosis (p=0.038), and recurrence (p=0.001). Nine patients with dense TILs had a mean time to recurrence of 74 months compared to 4 patients with sparse TILs who had a mean time to recurrence of 93 months (p=0.044) (Figure).
Conclusion(s): We found that dense TILs in DCIS was significantly associated with age, tumor size, grade, and histology. Most importantly, dense TILs are a significant predictor of recurrence in patients with DCIS, which underlies the prognostic importance of the immune microenvironment of early breast cancers. (Figure Presented)

PURPOSE/OBJECTIVE:The CDK 4/6 inhibitor palbociclib rapidly and reversibly inhibits the cell cycle. The goal of this study was to exploit the cell cycle through intermittent, alternating dosing with palbociclib/paclitaxel to enhance efficacy. We determined the combination dose-limiting toxicity (DLT) in patients with Rb protein-expressing, advanced breast cancer. PATIENTS AND METHODS/METHODS:This open-label, phase I trial (NCT01320592) enrolled patients to sequential cohorts of palbociclib orally dosed intermittently between days 1 and 19 of a 28-day cycle alternating with weekly paclitaxel. Dose escalation proceeded in a standard 3 + 3 design. Ten additional patients received the combination at the recommended phase II dose (RP2D). Those who reached response plateau ≥6 cycles could continue on palbociclib alone on a 3 week on/1 week off schedule at one dose level above their combination dose. RESULTS:paclitaxel. During C1, the most common adverse event was NTP, occurring in 15 patients (55.6%); grade 1 or 2 nausea and peripheral neuropathy were also observed in 8 patients each (29.6%). The clinical benefit rate was 55% at the RP2D; benefit was observed across all receptor subtypes. CONCLUSIONS:breast cancer regardless of subtype; efficacy trials are warranted.

Introduction: Using the National Health and Aging Trends Study (NHATS), we examined use of sleeping medication, difficulty falling asleep, and trouble falling back asleep among individuals with and without cognitive impairment.
Method(s): Binomial logistic regression examined sleep medication use and insomnia symptoms (difficulty falling asleep or falling back asleep after awakening) by cognitive impairment (no dementia and possible or probable dementia). Sleep-related variables were collected on frequency scales ranging from 1 (every day) to 5 (never). Of the sample, 71.1% were White (n=3,369), 20.7% were Black (n=982), 5.0% were Hispanic (n=235), and 2.4% other (n=113); 60.4% were female (n=2,662) and 39.6% were male (n=1,875).
Result(s): Respondents were classified as having no dementia (63.7%), possible dementia (8.5%), or probable dementia (12.9%). Of the sample, 10.7% reported medication use every night, 2.5% 5-6 nights/week, 5.7% 2-4 nights/week, 6.6% once/week and 59.4% reported no use. Of the respondents, 8.3% reported difficulty sleeping every night, 8.0% reported 5-6 nights/week, 21.4% reported 2-4 nights/week, 22.9% reported rarely, and 23.5% reported never experiencing difficulty sleeping. Regarding difficulty falling back asleep, 4.9% reported difficulty every night, 7.4% reported 5-6 nights/week, 26.0% reported 2-4 nights/week, 20.4% reported rarely, and 24.3% reported never. Compared to individuals who reported never using sleep medications, those reporting nightly use were significantly more likely to be cognitively impaired (OR=1.44,95%CI: 1.14-1.82). Compared to individuals reporting never having difficulty falling asleep, those reporting difficulty falling asleep nightly were not more likely to have cognitive impairment (OR=0.74 95%CI: 0.67 to 1.19). Compared to individuals reporting never having difficulty falling back asleep after awakening, those frequently reporting difficulty falling back asleep were less likely to be cognitively impaired (OR=0.44,95%CI:0.22 to 0.64).
Conclusion(s): Cognitive impairment was positively associated with sleep medication use in adjusted models, but not with trouble falling asleep or difficulty falling back asleep after awakening. Our findings are consistent with the literature on deleterious consequences of sleep medications

BACKGROUND:Congestive heart failure is a major cause of morbidity, mortality, and cost. Disease management programs have shown promise but lack firm evidence of effectiveness and scalability. We describe the motivation, design, and planned analyses of EMPOWER (Electronic Monitoring of Patients Offers Ways to Enhance Recovery), a randomized clinical trial of an innovative intervention incorporating behavioral economic principles with remote monitoring technology embedded within a healthcare system. METHODS AND RESULTS/RESULTS:EMPOWER is an ongoing, pragmatic, randomized clinical trial comparing usual care to an automated hovering intervention that includes patient-level incentives for daily weight monitoring and diuretic adherence combined with automated feedback into the clinical care pathway, enabling real-time response to concerning clinical symptoms. Identification of eligible patients began in May 2016, and implementation of the intervention is feasible. Trial processes are embedded into existing clinical pathways. The primary outcome is time to readmission for any cause. Cost-effectiveness analyses are planned to evaluate the healthcare costs and health outcomes of the approach. CONCLUSIONS:The EMPOWER trial incorporates leading-edge approaches in human motivation, derived from behavioral economics, with contemporary technology to provide scale and exception handling at low cost. The trial is also implemented within the naturalized environment of a health system, as much as possible taking advantage of the existing journeys of patients and workflows of clinicians. A goal of this pragmatic design is to limit resource utilization and also to test an intervention that would need minimal modification to be translated from research into a new way of practice. CLINICAL TRIAL REGISTRATION/BACKGROUND:URL: https://www.clinicaltrials.gov . Unique identifier: NCT02708654.

BACKGROUND:Treatment for opioid use disorder (OUD) is highly effective, yet it remains dramatically underutilized. Individuals with OUD have disproportionately high rates of hospitalization and low rates of addiction treatment. Hospital-based addiction consult services offer a potential solution by using multidisciplinary teams to evaluate patients, initiate medication for addiction treatment (MAT) in the hospital, and connect patients to post-discharge care. We are studying the effectiveness of an addiction consult model [Consult for Addiction Treatment and Care in Hospitals (CATCH)] as a strategy for engaging patients with OUD in treatment as the program rolls out in the largest municipal hospital system in the US. The primary aim is to evaluate the effectiveness of CATCH in increasing post-discharge initiation and engagement in MAT. Secondary aims are to assess treatment retention, frequency of acute care utilization and overdose deaths and their associated costs, and implementation outcomes. METHODS:A pragmatic trial at six hospitals, conducted in collaboration with the municipal hospital system and department of health, will be implemented to study the CATCH intervention. Guided by the RE-AIM evaluation framework, this hybrid effectiveness-implementation study (Type 1) focuses primarily on effectiveness and also measures implementation outcomes to inform the intervention's adoption and sustainability. A stepped-wedge cluster randomized trial design will determine the impact of CATCH on treatment outcomes in comparison to usual care for a control period, followed by a 12-month intervention period and a 6- to 18-month maintenance period at each hospital. A mixed methods approach will primarily utilize administrative data to measure outcomes, while interviews and focus groups with staff and patients will provide additional information on implementation fidelity and barriers to delivering MAT to patients with OUD. DISCUSSION/CONCLUSIONS:Because of their great potential to reduce the negative health and economic consequences of untreated OUD, addiction consult models are proliferating in response to the opioid epidemic, despite the absence of a strong evidence base. This study will provide the first known rigorous evaluation of an addiction consult model in a large multi-site trial and promises to generate knowledge that can rapidly transform practice and inform the potential for widespread dissemination of these services. TRIAL REGISTRATION/BACKGROUND:NCT03611335.

Importance/UNASSIGNED:Despite limited effectiveness of pay-for-performance (P4P), payers continue to expand P4P nationally. Objective/UNASSIGNED: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/UNASSIGNED: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/UNASSIGNED: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/UNASSIGNED:The proportion of 20 evidence-based quality measures achieved at the patient level. Results/UNASSIGNED: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/UNASSIGNED: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/UNASSIGNED:ClinicalTrials.gov Identifier: NCT02634879.