When peer comparison information harms physician well-being.

Policymakers and business leaders often use peer comparison information-showing people how their behavior compares to that of their peers-to motivate a range of behaviors. Despite their widespread use, the potential impact of peer comparison interventions on recipients' well-being is largely unknown. We conducted a 5-mo field experiment involving 199 primary care physicians and 46,631 patients to examine the impact of a peer comparison intervention on physicians' job performance, job satisfaction, and burnout. We varied whether physicians received information about their preventive care performance compared to that of other physicians in the same health system. Our analyses reveal that our implementation of peer comparison did not significantly improve physicians' preventive care performance, but it did significantly decrease job satisfaction and increase burnout, with the effect on job satisfaction persisting for at least 4 mo after the intervention had been discontinued. Quantitative and qualitative evidence on the mechanisms underlying these unanticipated negative effects suggest that the intervention inadvertently signaled a lack of support from leadership. Consistent with this account, providing leaders with training on how to support physicians mitigated the negative effects on well-being. Our research uncovers a critical potential downside of peer comparison interventions, highlights the importance of evaluating the psychological costs of behavioral interventions, and points to how a complementary intervention-leadership support training-can mitigate these costs.

Reducing Care Overuse in Older Patients Using Professional Norms and Accountability : A Cluster Randomized Controlled Trial.

BACKGROUND: Effective strategies are needed to curtail overuse that may lead to harm. OBJECTIVE: To evaluate the effects of clinician decision support redirecting attention to harms and engaging social and reputational concerns on overuse in older primary care patients. DESIGN: 18-month, single-blind, pragmatic, cluster randomized trial, constrained randomization. (ClinicalTrials.gov: NCT04289753). SETTING: 60 primary care internal medicine, family medicine and geriatrics practices within a health system from 1 September 2020 to 28 February 2022. PARTICIPANTS: 371 primary care clinicians and their older adult patients from participating practices. INTERVENTION: Behavioral science-informed, point-of-care, clinical decision support tools plus brief case-based education addressing the 3 primary clinical outcomes (187 clinicians from 30 clinics) were compared with brief case-based education alone (187 clinicians from 30 clinics). Decision support was designed to increase salience of potential harms, convey social norms, and promote accountability. MEASUREMENTS: Prostate-specific antigen (PSA) testing in men aged 76 years and older without previous prostate cancer, urine testing for nonspecific reasons in women aged 65 years and older, and overtreatment of diabetes with hypoglycemic agents in patients aged 75 years and older and hemoglobin A1c (HbA1c) less than 7%. RESULTS: At randomization, mean clinic annual PSA testing, unspecified urine testing, and diabetes overtreatment rates were 24.9, 23.9, and 16.8 per 100 patients, respectively. After 18 months of intervention, the intervention group had lower adjusted difference-in-differences in annual rates of PSA testing (-8.7 [95% CI, -10.2 to -7.1]), unspecified urine testing (-5.5 [CI, -7.0 to -3.6]), and diabetes overtreatment (-1.4 [CI, -2.9 to -0.03]) compared with education only. Safety measures did not show increased emergency care related to urinary tract infections or hyperglycemia. An HbA1c greater than 9.0% was more common with the intervention among previously overtreated diabetes patients (adjusted difference-in-differences, 0.47 per 100 patients [95% CI, 0.04 to 1.20]). LIMITATION: A single health system limits generalizability; electronic health data limit ability to differentiate between overtesting and underdocumentation. CONCLUSION: Decision support designed to increase clinicians' attention to possible harms, social norms, and reputational concerns reduced unspecified testing compared with offering traditional case-based education alone. Small decreases in diabetes overtreatment may also result in higher rates of uncontrolled diabetes. PRIMARY FUNDING SOURCE: National Institute on Aging.

A megastudy of text-based nudges encouraging patients to get vaccinated at an upcoming doctor's appointment.

Many Americans fail to get life-saving vaccines each year, and the availability of a vaccine for COVID-19 makes the challenge of encouraging vaccination more urgent than ever. We present a large field experiment (N = 47,306) testing 19 nudges delivered to patients via text message and designed to boost adoption of the influenza vaccine. Our findings suggest that text messages sent prior to a primary care visit can boost vaccination rates by an average of 5%. Overall, interventions performed better when they were 1) framed as reminders to get flu shots that were already reserved for the patient and 2) congruent with the sort of communications patients expected to receive from their healthcare provider (i.e., not surprising, casual, or interactive). The best-performing intervention in our study reminded patients twice to get their flu shot at their upcoming doctor's appointment and indicated it was reserved for them. This successful script could be used as a template for campaigns to encourage the adoption of life-saving vaccines, including against COVID-19.

Evaluation of behavioral economic strategies to raise influenza vaccination rates across a health system: Results from a randomized clinical trial.

Influenza vaccination rates are low. Working with a large US health system, we evaluated three health system-wide interventions using the electronic health record's patient portal to improve influenza vaccination rates. We performed a two-arm RCT with a nested factorial design within the treatment arm, randomizing patients to usual-care control (no portal interventions) or to one or more portal interventions. We included all patients within this health system during the 2020-2021 influenza vaccination season, which overlapped with the COVID-19 pandemic. Through the patient portal, we simultaneously tested: pre-commitment messages (sent September 2020, asking patients to commit to a vaccination); monthly portal reminders (October - December 2020), direct appointment scheduling (patients could self-schedule influenza vaccination at multiple sites); and pre-appointment reminder messages (sent before scheduled primary care appointments, reminding patients about influenza vaccination). The main outcome measure was receipt of influenza vaccine (10/01/2020-03/31/2021). We randomized 213,773 patients (196,070 adults ≥18 years, 17,703 children). Influenza vaccination rates overall were low (39.0%). Vaccination rates for study arms did not differ: Control (38.9%), pre-commitment vs no pre-commitment (39.2%/38.9%), direct appointment scheduling yes/no (39.1%/39.1%), pre-appointment reminders yes/no (39.1%/39.1%); p > 0.017 for all comparisons (p value cut-off adjusted for multiple comparisons). After adjusting for age, gender, insurance, race, ethnicity, and prior influenza vaccination, none of the interventions increased vaccination rates. We conclude that patient portal interventions to remind patients to receive influenza vaccine during the COVID-19 pandemic did not raise influenza immunization rates. More intensive or tailored interventions are needed beyond portal innovations to increase influenza vaccination.

Development of High-Risk Geriatric Polypharmacy Electronic Clinical Quality Measures and a Pilot Test of EHR Nudges Based on These Measures.

BACKGROUND: Inappropriate polypharmacy, prevalent among older patients, is associated with substantial harms. OBJECTIVE: To develop measures of high-risk polypharmacy and pilot test novel electronic health record (EHR)-based nudges grounded in behavioral science to promote deprescribing. DESIGN: We developed and validated seven measures, then conducted a three-arm pilot from February to May 2019. PARTICIPANTS: Validation used data from 78,880 patients from a single large health system. Six physicians were pre-pilot test environment users. Sixty-nine physicians participated in the pilot. MAIN MEASURES: Rate of high-risk polypharmacy among patients aged 65 years or older. High-risk polypharmacy was defined as being prescribed ≥5 medications and satisfying ≥1 of the following high-risk criteria: drugs that increase fall risk among patients with fall history; drug-drug interactions that increase fall risk; thiazolidinedione, NSAID, or non-dihydropyridine calcium channel blocker in heart failure; and glyburide, glimepiride, or NSAID in chronic kidney disease. INTERVENTIONS: Physicians received EHR alerts when renewing or prescribing certain high-risk medications when criteria were met. One practice received a "commitment nudge" that offered a chance to commit to addressing high-risk polypharmacy at the next visit. One practice received a "justification nudge" that asked for a reason when high-risk polypharmacy was present. One practice received both. KEY RESULTS: Among 55,107 patients 65 and older prescribed 5 or more medications, 6256 (7.9%) had one or more high-risk criteria. During the pilot, the mean (SD) number of nudges per physician per week was 1.7 (0.4) for commitment, 0.8 (0.5) for justification, and 1.9 (0.5) for both interventions. Physicians requested to be reminded to address high-risk polypharmacy for 236/833 (28.3%) of the commitment nudges and acknowledged 441 of 460 (95.9%) of justification nudges, providing a text response for 187 (40.7%). CONCLUSIONS: EHR-based measures and nudges addressing high-risk polypharmacy were feasible to develop and implement, and warrant further testing.

Effect of Peer Benchmarking on Specialist Electronic Consult Performance in a Los Angeles Safety-Net: a Cluster Randomized Trial.

BACKGROUND: Since the advent of COVID-19, accelerated adoption of systems that reduce face-to-face encounters has outpaced training and best practices. Electronic consultations (eConsults), structured communications between PCPs and specialists regarding a case, have been effective in reducing face-to-face specialist encounters. As the health system rapidly adapts to multiple new practices and communication tools, new mechanisms to measure and improve performance in this context are needed. OBJECTIVE: To test whether feedback comparing physicians to top performing peers using co-specialists' ratings improves performance. DESIGN: Cluster-randomized controlled trial PARTICIPANTS: Eighty facility-specialty clusters and 214 clinicians INTERVENTION: Providers in the feedback arms were sent messages that announced their membership in an elite group of "Top Performers" or provided actionable recommendations with feedback for providers that were "Not Top Performers." MAIN MEASURES: The primary outcomes were changes in peer ratings in the following performance dimensions after feedback was received: (1) elicitation of information from primary care practitioners; (2) adherence to institutional clinical guidelines; (3) agreement with peer's medical decision-making; (4) educational value; (5) relationship building. KEY RESULTS: Specialists showed significant improvements on 3 of the 5 consultation performance dimensions: medical decision-making (odds ratio 1.52, 95% confidence interval 1.08-2.14, p<.05), educational value (1.86, 1.17-2.96) and relationship building (1.63, 1.13-2.35) (both p<.01). CONCLUSIONS: The pandemic has shed light on clinicians' commitment to professionalism and service as we rapidly adapt to changing paradigms. Interventions that appeal to professional norms can help improve the efficacy of new systems of practice. We show that specialists' performance can be measured and improved with feedback using aspirational norms. TRIAL REGISTRATION: clinicaltrials.gov NCT03784950.

Effect of Personalized Messages Sent by a Health System's Patient Portal on Influenza Vaccination Rates: a Randomized Clinical Trial.

BACKGROUND: Adult influenza vaccination rates are low. Tailored patient reminders might raise rates. OBJECTIVE: Evaluate impact of a health system's patient portal reminders: (1) tailored to patient characteristics and (2) incorporating behavioral science strategies, on influenza vaccination rates among adults. DESIGN: Pragmatic 6-arm randomized trial across a health system during the 2019-2020 influenza vaccination season. The setting was one large health system-53 adult primary care practices. PARTICIPANTS: All adult patients who used the patient portal within 12 months, stratified by the following: young adults (18-64 years, without diabetes), older adults (≥65 years, without diabetes), and those with diabetes (≥18 years). INTERVENTIONS: Patients were randomized within strata to either (1) pre-commitment reminder alone (1 message, mid-October), (2) pre-commitment + loss frame messages, (3) pre-commitment + gain frame messages, (4) loss frame messages alone, (5) gain frame messages alone, or (6) standard of care control. Patients in the pre-commitment group were sent a message in mid-October, asking if they planned on getting an influenza vaccination. Patients in loss or gain frame groups were sent up to 3 portal reminders (late October, November, and December, if no documented influenza vaccination in the EHR) about importance and safety of influenza vaccine. MAIN MEASURES: Receipt of 1 influenza vaccine from 10/01/2019 to 03/31/2020. KEY RESULTS: 196,486 patients (145,166 young adults, 29,795 older adults, 21,525 adults with diabetes) were randomized. Influenza vaccination rates were as follows: for young adults 36.8%, for older adults 55.6%, and for diabetics 60.6%. On unadjusted and adjusted (for age, gender, insurance, race, ethnicity, and prior influenza vaccine history) analyses, influenza vaccination rates were not statistically different for any study group versus control. CONCLUSIONS: Patient reminders sent by a health system's patient portal that were tailored to patient demographics (young adults, older adults, diabetes) and that incorporated two behavioral economic messaging strategies (pre-commitment and loss/gain framing) were not effective in raising influenza vaccination rates. TRIAL REGISTRATION: This trial was registered with ClinicalTrials.gov (NCT04110314).

Impact of a Patient-Centered Behavioral Economics Intervention on Hypertension Control in a Highly Disadvantaged Population: a Randomized Trial.

BACKGROUND: Uncontrolled hypertension contributes to disparities in cardiovascular outcomes. Patient intervention strategies informed by behavioral economics and social psychology could improve blood pressure (BP) control in disadvantaged minority populations. OBJECTIVE: To assess the impact on BP control of an intervention combining short-term financial incentives with promotion of intrinsic motivation among highly disadvantaged patients. DESIGN: Randomized controlled trial. PARTICIPANTS: Two hundred seven adults (98% African American or Latino) aged 18 or older with uncontrolled hypertension attending Federally Qualified Health Centers. INTERVENTION: Six-month intervention, combining financial incentives for measuring home BP, recording medication use, BP improvement, and achieving target BP values with counseling linking hypertension control efforts to participants' personal reasons to stay healthy. MAIN MEASURES: Primary outcomes: percentage achieving systolic BP (SBP) < 140 mmHg, percentage achieving diastolic BP (DBP) < 90 mmHg, and changes in SBP and DBP, all after 6 months. Priority secondary outcomes were SBP < 140 mmHg, DBP < 90 mmHg, and BP change at 12 months, 6 months after the intervention ended. KEY RESULTS: After 6 months, rates of achieving target BP values for intervention and control subjects respectively was 57.1% vs. 40.2% for SBP < 140 mmHg (adjusted odds ratio (AOR) 2.53 (1.13-5.70)), 79.8% vs 70.1% for DBP < 90 mmHg (AOR 2.50 (0.84-7.44)), and 53.6% vs 40.2% for achieving both targets (AOR 2.04 (0.92-4.52)). However, at 12 months, the groups did not differ significantly in these 3 measures: 39.5% vs 35.0% for SBP (AOR 1.20 (0.51-2.83)), 68.4% vs 75.0% for DBP (AOR 0.70 (0.24-2.09)), and 35.5% vs 33.8% for both (AOR 1.03 (0.44-2.42)). Change in absolute SBP and DBP did not differ significantly between the groups at 6 or 12 months. Exploratory post hoc analysis revealed intervention benefit only occurred among individuals whose providers intensified their regimens, but not among those with intensification but no intervention. CONCLUSIONS: The intervention achieved short-term improvement in SBP control in a highly disadvantaged population. Despite attempts to enhance intrinsic motivation, the effect was not sustained after incentives were withdrawn. Future research should evaluate combined patient/provider strategies to enhance such interventions and sustain their benefit. TRIAL REGISTRATION: NCT01402453; http://clinicaltrials.gov/show/NCT01402453.

Social Mobilization.

This article reviews research from several behavioral disciplines to derive strategies for prompting people to perform behaviors that are individually costly and provide negligible individual or social benefits but are meaningful when performed by a large number of individuals. Whereas the term social influence encompasses all the ways in which people influence other people, social mobilization refers specifically to principles that can be used to influence a large number of individuals to participate in such activities. The motivational force of social mobilization is amplified by the fact that others benefit from the encouraged behaviors, and its overall impact is enhanced by the fact that people are embedded within social networks. This article may be useful to those interested in the provision of public goods, collective action, and prosocial behavior, and we give special attention to field experiments on election participation, environmentally sustainable behaviors, and charitable giving.

Impact of a Risk Calculator on Risk Perception and Surgical Decision Making: A Randomized Trial.

OBJECTIVE: The aim of this study was to determine whether exposure to data from a risk calculator influences surgeons' assessments of risk and in turn, their decisions to operate. BACKGROUND: Little is known about how risk calculators inform clinical judgment and decision-making. METHODS: We asked a national sample of surgeons to assess the risks (probability of serious complications or death) and benefits (recovery) of operative and nonoperative management and to rate their likelihood of recommending an operation (5-point scale) for 4 detailed clinical vignettes wherein the best treatment strategy was uncertain. Surgeons were randomized to the clinical vignettes alone (control group; n = 384) or supplemented by data from a risk calculator (risk calculator group; n = 395). We compared surgeons' judgments and decisions between the groups. RESULTS: Surgeons exposed to the risk calculator judged levels of operative risk that more closely approximated the risk calculator value (RCV) compared with surgeons in the control group [mesenteric ischemia: 43.7% vs 64.6%, P < 0.001 (RCV = 25%); gastrointestinal bleed: 47.7% vs 53.4%, P < 0.001 (RCV = 38%); small bowel obstruction: 13.6% vs 17.5%, P < 0.001 (RCV = 14%); appendicitis: 13.4% vs 24.4%, P < 0.001 (RCV = 5%)]. Surgeons exposed to the risk calculator also varied less in their assessment of operative risk (standard deviations: mesenteric ischemia 20.2% vs 23.2%, P = 0.01; gastrointestinal bleed 17.4% vs 24.1%, P < 0.001; small bowel obstruction 10.6% vs 14.9%, P < 0.001; appendicitis 15.2% vs 21.8%, P < 0.001). However, averaged across the 4 vignettes, the 2 groups did not differ in their reported likelihood of recommending an operation (mean 3.7 vs 3.7, P = 0.76). CONCLUSIONS: Exposure to risk calculator data leads to less varied and more accurate judgments of operative risk among surgeons, and thus may help inform discussions of treatment options between surgeons and patients. Interestingly, it did not alter their reported likelihood of recommending an operation.

Surgeon Perception of Risk and Benefit in the Decision to Operate.

OBJECTIVE: To determine how surgeons' perceptions of treatment risks and benefits influence their decisions to operate. BACKGROUND: Little is known about what makes one surgeon choose to operate on a patient and another chooses not to operate. METHODS: Using an online study, we presented a national sample of surgeons (N = 767) with four detailed clinical vignettes (mesenteric ischemia, gastrointestinal bleed, bowel obstruction, appendicitis) where the best treatment option was uncertain and asked them to: (1) judge the risks (probability of serious complications) and benefits (probability of recovery) for operative and nonoperative management and (2) decide whether or not they would recommend an operation. RESULTS: Across all clinical vignettes, surgeons varied markedly in both their assessments of the risks and benefits of operative and nonoperative management (narrowest range 4%-100% for all four predictions across vignettes) and in their decisions to operate (49%-85%). Surgeons were less likely to operate as their perceptions of operative risk increased [absolute difference (AD) = -29.6% from 1.0 standard deviation below to 1.0 standard deviation above mean (95% confidence interval, CI: -31.6, -23.8)] and their perceptions of nonoperative benefit increased [AD = -32.6% (95% CI: -32.8,--28.9)]. Surgeons were more likely to operate as their perceptions of operative benefit increased [AD = 18.7% (95% CI: 12.6, 21.5)] and their perceptions of nonoperative risk increased [AD = 32.7% (95% CI: 28.7, 34.0)]. Differences in risk/benefit perceptions explained 39% of the observed variation in decisions to operate across the four vignettes. CONCLUSIONS: Given the same clinical scenarios, surgeons' perceptions of treatment risks and benefits vary and are highly predictive of their decisions to operate.

Behavioral interventions to reduce inappropriate antibiotic prescribing: a randomized pilot trial.

BACKGROUND: Clinicians frequently prescribe antibiotics inappropriately for acute respiratory infections (ARIs). Our objective was to test information technology-enabled behavioral interventions to reduce inappropriate antibiotic prescribing for ARIs in a randomized controlled pilot test trial. METHODS: Primary care clinicians were randomized in a 2 × 2 × 2 factorial experiment with 3 interventions: 1) Accountable Justifications; 2) Suggested Alternatives; and 3) Peer Comparison. Beforehand, participants completed an educational module. Measures included: rates of antibiotic prescribing for: non-antibiotic-appropriate ARI diagnoses, acute sinusitis/pharyngitis, all other diagnoses/symptoms of respiratory infection, and all three ARI categories combined. RESULTS: We examined 3,276 visits in the pre-intervention year and 3,099 in the intervention year. The antibiotic prescribing rate fell for non-antibiotic-appropriate ARIs (24.7 % in the pre-intervention year to 5.2 % in the intervention year); sinusitis/pharyngitis (50.3 to 44.7 %); all other diagnoses/symptoms of respiratory infection (40.2 to 25.3 %); and all categories combined (38.7 to 24.2 %; all p < 0.001). There were no significant relationships between any intervention and antibiotic prescribing for non-antibiotic-appropriate ARI diagnoses or sinusitis/pharyngitis. Suggested Alternatives was associated with reduced antibiotic prescribing for other diagnoses or symptoms of respiratory infection (odds ratio [OR], 0.62; 95 % confidence interval [CI], 0.44-0.89) and for all ARI categories combined (OR, 0.72; 95 % CI, 0.54-0.96). Peer Comparison was associated with reduced prescribing for all ARI categories combined (OR, 0.73; 95 % CI, 0.53-0.995). CONCLUSIONS: We observed large reductions in antibiotic prescribing regardless of whether or not study participants received an intervention, suggesting an overriding Hawthorne effect or possibly clinician-to-clinician contamination. Low baseline inappropriate prescribing may have led to floor effects. TRIAL REGISTRATION: ClinicalTrials.gov: NCT01454960 .

How psychological framing affects economic market prices in the lab and field.

A fundamental debate in social sciences concerns how individual judgments and choices, resulting from psychological mechanisms, are manifested in collective economic behavior. Economists emphasize the capacity of markets to aggregate information distributed among traders into rational equilibrium prices. However, psychologists have identified pervasive and systematic biases in individual judgment that they generally assume will affect collective behavior. In particular, recent studies have found that judged likelihoods of possible events vary systematically with the way the entire event space is partitioned, with probabilities of each of N partitioned events biased toward 1/N. Thus, combining events into a common partition lowers perceived probability, and unpacking events into separate partitions increases their perceived probability. We look for evidence of such bias in various prediction markets, in which prices can be interpreted as probabilities of upcoming events. In two highly controlled experimental studies, we find clear evidence of partition dependence in a 2-h laboratory experiment and a field experiment on National Basketball Association (NBA) and Federation Internationale de Football Association (FIFA World Cup) sports events spanning several weeks. We also find evidence consistent with partition dependence in nonexperimental field data from prediction markets for economic derivatives (guessing the values of important macroeconomic statistics) and horse races. Results in any one of the studies might be explained by a specialized alternative theory, but no alternative theories can explain the results of all four studies. We conclude that psychological biases in individual judgment can affect market prices, and understanding those effects requires combining a variety of methods from psychology and economics.

Effect of Behavioral Interventions on Inappropriate Antibiotic Prescribing Among Primary Care Practices: A Randomized Clinical Trial.

IMPORTANCE: Interventions based on behavioral science might reduce inappropriate antibiotic prescribing. OBJECTIVE: To assess effects of behavioral interventions and rates of inappropriate (not guideline-concordant) antibiotic prescribing during ambulatory visits for acute respiratory tract infections. DESIGN, SETTING, AND PARTICIPANTS: Cluster randomized clinical trial conducted among 47 primary care practices in Boston and Los Angeles. Participants were 248 enrolled clinicians randomized to receive 0, 1, 2, or 3 interventions for 18 months. All clinicians received education on antibiotic prescribing guidelines on enrollment. Interventions began between November 1, 2011, and October 1, 2012. Follow-up for the latest-starting sites ended on April 1, 2014. Adult patients with comorbidities and concomitant infections were excluded. INTERVENTIONS: Three behavioral interventions, implemented alone or in combination: suggested alternatives presented electronic order sets suggesting nonantibiotic treatments; accountable justification prompted clinicians to enter free-text justifications for prescribing antibiotics into patients' electronic health records; peer comparison sent emails to clinicians that compared their antibiotic prescribing rates with those of "top performers" (those with the lowest inappropriate prescribing rates). MAIN OUTCOMES AND MEASURES: Antibiotic prescribing rates for visits with antibiotic-inappropriate diagnoses (nonspecific upper respiratory tract infections, acute bronchitis, and influenza) from 18 months preintervention to 18 months afterward, adjusting each intervention's effects for co-occurring interventions and preintervention trends, with random effects for practices and clinicians. RESULTS: There were 14,753 visits (mean patient age, 47 years; 69% women) for antibiotic-inappropriate acute respiratory tract infections during the baseline period and 16,959 visits (mean patient age, 48 years; 67% women) during the intervention period. Mean antibiotic prescribing rates decreased from 24.1% at intervention start to 13.1% at intervention month 18 (absolute difference, -11.0%) for control practices; from 22.1% to 6.1% (absolute difference, -16.0%) for suggested alternatives (difference in differences, -5.0% [95% CI, -7.8% to 0.1%]; P = .66 for differences in trajectories); from 23.2% to 5.2% (absolute difference, -18.1%) for accountable justification (difference in differences, -7.0% [95% CI, -9.1% to -2.9%]; P < .001); and from 19.9% to 3.7% (absolute difference, -16.3%) for peer comparison (difference in differences, -5.2% [95% CI, -6.9% to -1.6%]; P < .001). There were no statistically significant interactions (neither synergy nor interference) between interventions. CONCLUSIONS AND RELEVANCE: Among primary care practices, the use of accountable justification and peer comparison as behavioral interventions resulted in lower rates of inappropriate antibiotic prescribing for acute respiratory tract infections. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT01454947.

Nudging physician prescription decisions by partitioning the order set: results of a vignette-based study.

BACKGROUND: Healthcare professionals are rapidly adopting electronic health records (EHRs). Within EHRs, seemingly innocuous menu design configurations can influence provider decisions for better or worse. OBJECTIVE: The purpose of this study was to examine whether the grouping of menu items systematically affects prescribing practices among primary care providers. PARTICIPANTS: We surveyed 166 primary care providers in a research network of practices in the greater Chicago area, of whom 84 responded (51% response rate). Respondents and non-respondents were similar on all observable dimensions except that respondents were more likely to work in an academic setting. DESIGN: The questionnaire consisted of seven clinical vignettes. Each vignette described typical signs and symptoms for acute respiratory infections, and providers chose treatments from a menu of options. For each vignette, providers were randomly assigned to one of two menu partitions. For antibiotic-inappropriate vignettes, the treatment menu either listed over-the-counter (OTC) medications individually while grouping prescriptions together, or displayed the reverse partition. For antibiotic-appropriate vignettes, the treatment menu either listed narrow-spectrum antibiotics individually while grouping broad-spectrum antibiotics, or displayed the reverse partition. MAIN MEASURES: The main outcome was provider treatment choice. For antibiotic-inappropriate vignettes, we categorized responses as prescription drugs or OTC-only options. For antibiotic-appropriate vignettes, we categorized responses as broad- or narrow-spectrum antibiotics. KEY RESULTS: Across vignettes, there was an 11.5 percentage point reduction in choosing aggressive treatment options (e.g., broad-spectrum antibiotics) when aggressive options were grouped compared to when those same options were listed individually (95% CI: 2.9 to 20.1%; p = .008). CONCLUSIONS: Provider treatment choice appears to be influenced by the grouping of menu options, suggesting that the layout of EHR order sets is not an arbitrary exercise. The careful crafting of EHR order sets can serve as an important opportunity to improve patient care without constraining physicians' ability to prescribe what they believe is best for their patients.

The unified tradeoff model.

Evidence is steadily mounting that attribute-based models offer a more accurate description of intertemporal choices than traditional alternative-based models. Among the attribute-based models, the tradeoff model offers the broadest coverage of research findings, but at the cost of considerable complexity: There now are various instantiations of the model dealing with partially overlapping universes of choice options and preference patterns. Moreover, there are reports of preference patterns in intertemporal decisions about monetary losses that contradict all attribute-based models proposed so far. Taking stock of these core challenges, and all other evidence, we develop an account of intertemporal choice, the unified tradeoff model, that is simpler, yet more comprehensive, than all currently available versions of the tradeoff model taken together. It borrows extensively from its predecessors, but it introduces a new element, time bias, that enables it to accommodate an extraordinarily broad range of preference patterns, and also generate new predictions that contradict all existing models of intertemporal choice. We report four studies that test and confirm its predictions regarding delay, interval, sign, and magnitude dependence in choices between single-dated outcomes, and a fifth study that tests and confirms its predictions regarding the relation between delay preference in choices that only involve single-dated payments and duration preference in choices that also involve sequences of payments. Having subjected the unified tradeoff model to an elevated risk of disconfirmation, we discuss its parsimony and scope in relation to yet other phenomena, most notably, preference patterns in consumption decisions, the final frontier for attribute-based models. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Text vs Patient Portal Messaging to Improve Influenza Vaccination Coverage: A Health System-Wide Randomized Clinical Trial.

Importance: Increasing influenza vaccination rates is a public health priority. One method recommended by the US Centers for Disease Control and Prevention and others is for health systems to send reminders nudging patients to be vaccinated. Objective: To evaluate and compare the effect of electronic health record (EHR)-based patient portal reminders vs text message reminders on influenza vaccination rates across a health system. Design, Setting, and Participants: This 3-arm randomized clinical trial was conducted from September 7, 2022, to April 30, 2023, among primary care patients within the University of California, Los Angeles (UCLA) health system. Interventions: Arm 1 received standard of care. The health system sent monthly reminder messages to patients due for an influenza vaccine by portal (arm 2) or text (arm 3). Arm 2 had a 2 × 2 nested design, with fixed vs responsive monthly reminders and preappointment vs no preappointment reminders. Arm 3 had 1 × 2 design, with preappointment vs no preappointment reminders. Preappointment reminders for eligible patients were sent 24 and 48 hours before scheduled primary care visits. Fixed reminders (in October, November, and December) involved identical messages via portal or text. Responsive portal reminders involved a September message asking patients about their plans for vaccination, with a follow-up reminder if the response was affirmative but the patient was not yet vaccinated. Main Outcomes and Measures: The primary outcome was influenza vaccination by April 30, 2023, obtained from the UCLA EHR, including vaccination from pharmacies and other sources. Results: A total of 262 085 patients (mean [SD] age, 45.1 [20.7] years; 237 404 [90.6%] adults; 24 681 [9.4%] children; 149 349 [57.0%] women) in 79 primary care practices were included (87 257 in arm 1, 87 478 in arm 2, and 87 350 in arm 3). At the entire primary care population level, none of the interventions improved influenza vaccination rates. All groups had rates of approximately 47%. There was no statistical or clinically significant improvement following portal vs text, preappointment reminders vs no preappointment reminders (portal and text reminders combined), or responsive vs fixed monthly portal reminders. Conclusions and Relevance: At the population level, neither portal nor text reminders for influenza vaccination were effective. Given that vaccine hesitancy may be a major reason for the lack of impact of portal or text reminders, more intensive interventions by health systems are needed to raise influenza vaccination coverage levels. Trial Registration: ClinicalTrials.gov Identifier: NCT05525494.

Peer Comparison or Guideline-Based Feedback and Postsurgery Opioid Prescriptions: A Randomized Clinical Trial.

Importance: Excess opioid prescribing after surgery can result in prolonged use and diversion. Email feedback based on social norms may reduce the number of pills prescribed. Objective: To assess the effectiveness of 2 social norm-based interventions on reducing guideline-discordant opioid prescribing after surgery. Design, Setting, and Participants: This cluster randomized clinical trial conducted at a large health care delivery system in northern California between October 2021 and October 2022 included general, obstetric/gynecologic, and orthopedic surgeons with patients aged 18 years or older discharged to home with an oral opioid prescription. Interventions: In 19 hospitals, 3 surgical specialties (general, orthopedic, and obstetric/gynecologic) were randomly assigned to a control group or 1 of 2 interventions. The guidelines intervention provided email feedback to surgeons on opioid prescribing relative to institutionally endorsed guidelines; the peer comparison intervention provided email feedback on opioid prescribing relative to that of peer surgeons. Emails were sent to surgeons with at least 2 guideline-discordant prescriptions in the previous month. The control group had no intervention. Main Outcome and Measures: The probability that a discharged patient was prescribed a quantity of opioids above the guideline for the respective procedure during the 12 intervention months. Results: There were 38 235 patients discharged from 640 surgeons during the 12-month intervention period. Control-group surgeons prescribed above guidelines 36.8% of the time during the intervention period compared with 27.5% and 25.4% among surgeons in the peer comparison and guidelines arms, respectively. In adjusted models, the peer comparison intervention reduced guideline-discordant prescribing by 5.8 percentage points (95% CI, -10.5 to -1.1; P = .03) and the guidelines intervention reduced it by 4.7 percentage points (95% CI, -9.4 to -0.1; P = .05). Effects were driven by surgeons who performed more surgeries and had more guideline-discordant prescribing at baseline. There was no significant difference between interventions. Conclusions and Relevance: In this cluster randomized clinical trial, email feedback based on either guidelines or peer comparison reduced opioid prescribing after surgery. Guideline-based feedback was as effective as peer comparison-based feedback. These interventions are simple, low-cost, and scalable, and may reduce downstream opioid misuse. Trial Registration: ClinicalTrials.gov NCT05070338.

Political extremism is supported by an illusion of understanding.

People often hold extreme political attitudes about complex policies. We hypothesized that people typically know less about such policies than they think they do (the illusion of explanatory depth) and that polarized attitudes are enabled by simplistic causal models. Asking people to explain policies in detail both undermined the illusion of explanatory depth and led to attitudes that were more moderate (Experiments 1 and 2). Although these effects occurred when people were asked to generate a mechanistic explanation, they did not occur when people were instead asked to enumerate reasons for their policy preferences (Experiment 2). Finally, generating mechanistic explanations reduced donations to relevant political advocacy groups (Experiment 3). The evidence suggests that people's mistaken sense that they understand the causal processes underlying policies contributes to political polarization.

Using insights from behavioral economics and social psychology to help patients manage chronic diseases.

Despite a revolution in therapeutics, the ability to control chronic diseases remains elusive. We present here a conceptual model of the potential role of behavioral tools in chronic disease control. Clinicians implicitly accept the assumption that patients will act rationally to maximize their self-interest. However, patients may not always be the rational actors that we imagine. Major behavioral barriers to optimal health behavior include patients' fear of threats to health, unwillingness to think about problems when risks are known or data are ambiguous, the discounting of risks that are far in the future, failure to act due to lack of motivation, insufficient confidence in the ability to overcome a health problem, and inattention due to pressures of everyday life. Financial incentives can stimulate initiation of health-promoting behaviors by reducing or eliminating financial barriers, but may not produce long-term behavior change without additional interventions. Strategies have been developed by behavioral economists and social psychologists to address each of these barriers to better decision-making. These include: labeling positive behaviors in ways consistent with patient life goals and priorities; greater focus on more immediate risks of chronic diseases; intermediate subgoals as steps to a large health goal; and implementation of specific plans as to when, where, and how an action will be taken. Such strategies hold promise for improving health behaviors and disease control, but most have not been studied in medical settings. The effectiveness of these approaches should be evaluated for their potential as tools for the clinician.