0
We're unable to sign you in at this time. Please try again in a few minutes.
Retry
We were able to sign you in, but your subscription(s) could not be found. Please try again in a few minutes.
Retry
There may be a problem with your account. Please contact the AMA Service Center to resolve this issue.
Contact the AMA Service Center:
Telephone: 1 (800) 262-2350 or 1 (312) 670-7827  *   Email: subscriptions@jamanetwork.com
Error Message ......
Original Contribution |

Influence of Patients’ Requests for Direct-to-Consumer Advertised Antidepressants:  A Randomized Controlled Trial FREE

Richard L. Kravitz, MD, MSPH; Ronald M. Epstein, MD; Mitchell D. Feldman, MD, MPhil; Carol E. Franz, PhD; Rahman Azari, PhD; Michael S. Wilkes, MD, PhD; Ladson Hinton, MD; Peter Franks, MD
[+] Author Affiliations

Author Affiliations: Center for Health Services Research in Primary Care (Drs Kravitz, Franz, Azari, Wilkes, Hinton, and Franks) and Departments of Internal Medicine (Drs Kravitz and Wilkes), Statistics (Dr Azari), Psychiatry (Dr Hinton), and Family and Community Medicine (Dr Franks), University of California, Davis, Sacramento; Departments of Family Medicine and Psychiatry and Center to Improve Communication in Health Care, University of Rochester School of Medicine and Dentistry, Rochester, NY (Dr Epstein); Division of General Internal Medicine, Department of Medicine, University of California, San Francisco (Dr Feldman).

More Author Information
JAMA. 2005;293(16):1995-2002. doi:10.1001/jama.293.16.1995.
Text Size: A A A
Published online

Context Direct-to-consumer (DTC) advertising of prescription drugs in the United States is both ubiquitous and controversial. Critics charge that it leads to overprescribing, while proponents counter that it helps avert underuse of effective treatments, especially for conditions that are poorly recognized or stigmatized.

Objective To ascertain the effects of patients’ DTC-related requests on physicians’ initial treatment decisions in patients with depressive symptoms.

Design Randomized trial using standardized patients (SPs). Six SP roles were created by crossing 2 conditions (major depression or adjustment disorder with depressed mood) with 3 request types (brand-specific, general, or none).

Setting Offices of primary care physicians in Sacramento, Calif; San Francisco, Calif; and Rochester, NY, between May 2003 and May 2004.

Participants One hundred fifty-two family physicians and general internists recruited from solo and group practices and health maintenance organizations; cooperation rates ranged from 53% to 61%.

Interventions The SPs were randomly assigned to make 298 unannounced visits, with assignments constrained so physicians saw 1 SP with major depression and 1 with adjustment disorder. The SPs made a brand-specific drug request, a general drug request, or no request (control condition) in approximately one third of visits.

Main Outcome Measures Data on prescribing, mental health referral, and primary care follow-up obtained from SP written reports, visit audiorecordings, chart review, and analysis of written prescriptions and drug samples. The effects of request type on prescribing were evaluated using contingency tables and confirmed in generalized linear mixed models that accounted for clustering and adjusted for site, physician, and visit characteristics.

Results Standardized patient role fidelity was excellent, and the suspicion rate that physicians had seen an SP was 13%. In major depression, rates of antidepressant prescribing were 53%, 76%, and 31% for SPs making brand-specific, general, and no requests, respectively (P<.001). In adjustment disorder, antidepressant prescribing rates were 55%, 39%, and 10%, respectively (P<.001). The results were confirmed in multivariate models. Minimally acceptable initial care (any combination of an antidepressant, mental health referral, or follow-up within 2 weeks) was offered to 98% of SPs in the major depression role making a general request, 90% of those making a brand-specific request, and 56% of those making no request (P<.001).

Conclusions Patients’ requests have a profound effect on physician prescribing in major depression and adjustment disorder. Direct-to-consumer advertising may have competing effects on quality, potentially both averting underuse and promoting overuse.

Figures in this Article

Spending on direct-to-consumer (DTC) advertising of prescription drugs in the United States totaled $3.2 billion in 2003.1 Although expenditures may be leveling off,2 DTC advertisements have become a stable, if controversial, feature of the media landscape.36 Critics charge that DTC advertisements lead to overprescribing of unnecessary, expensive, and potentially harmful medications, while proponents counter that they can serve a useful educational function and help avert underuse of effective treatments for conditions that may be poorly recognized, highly stigmatized, or both.7

Antidepressant medications consistently rank among the top DTC advertising categories.8,9 Major depressive disorder (defined in the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition as ≥5 depressive symptoms lasting at least 2 weeks and accompanied by functional impairment)10 carries stigma,1113 is frequently underdiagnosed, and can be treated successfully in a majority of patients.14 A thoughtful DTC advertising campaign could encourage patients to seek effective care. However, DTC advertising could also promote prescribing of antidepressants for patients with minor symptoms in the absence of clearly defined indications.15 Although some short-term studies have shown benefit from both antidepressants and brief psychological interventions in minor depression (<5 depressive symptoms),16 long-term follow-up is lacking, and there is no professional consensus about the need for immediate treatment as opposed to watchful waiting.17,18 Patients with minor symptoms of short duration who are prescribed antidepressants at initial presentation would be subject to short-term adverse effects (eg, sexual dysfunction) and potential hazards (including suicidality)19 that would have to be weighed against marginal gains.

Previous studies have examined the effects of DTC advertising on consumer and clinician behavior,46,20 but few have directly addressed the issue of underprescribing and overprescribing. We conducted a randomized controlled trial using standardized patients (SPs) to address 4 research questions: (1) What are the effects of patients’ requests for antidepressants on physician prescribing? (2) Does it make a difference whether patients’ requests are brand-specific (as might be prompted by viewing a DTC television advertisement) or general (as might arise from watching a television program about depression)? (3) Do the effects of patients’ requests vary depending on the clinical indications for antidepressant therapy? (4) What are the effects of brand-specific and general requests on 2 other depression care indicators: mental health referral and primary care follow-up?

Design Overview

The study was designed as a randomized controlled trial, with SPs making no requests (ie, presenting with symptoms only) serving as controls. Standardized patients were trained to portray 6 roles, created by crossing 2 clinical conditions (symptoms consistent with major depression or adjustment disorder) with 3 request types (brand-specific, general, or none) (Figure). Written informed consent for participation and audiorecording of visits was obtained from all participating physicians, and the study protocol was approved by the institutional review boards at all participating institutions.

Figure. Study Flow Diagram
Graphic Jump Location

Standardized patient roles were created by crossing 2 clinical conditions (major depression or adjustment disorder with depressed mood) with 3 drug request types (brand-specific, general, or none). Physicians at each study site (Sacramento, Calif; San Francisco, Calif; and Rochester, NY) were randomly assigned to receive 2 standardized patient visits, 1 of each condition combined with a different type of drug request.

Sampling of Practices

Primary care physicians (internists and family physicians) were recruited through 4 physician collectives: the University of California, Davis, Primary Care Network and Kaiser-Permanente in Sacramento, Calif; Brown & Toland Medical Group in San Francisco, Calif; and Excellus BlueCross BlueShield in Rochester, NY. At all sites, recruiting was conducted by mail with telephone follow-up. Physicians were told only that the study would involve seeing 2 SPs several months apart, that each SP would present with a combination of common symptoms, and that the purpose of the study was to “assess social influences on practice and the competing demands of primary care.” Physicians and their practices were offered visit reimbursement and participation incentives totaling up to $375. Cooperation rates ranged from 53% to 61%. The age and sex distributions of participating physicians were similar to those of the practices as a whole.

Role Development

Detailed clinical biographies were developed for the 2 clinical presentations (major depression of moderate severity and adjustment disorder with depressed mood). Role outlines were prepared by the coinvestigators and reviewed by a scientific advisory committee consisting of national experts in psychology, psychiatry, primary care, and SP methods. Role outlines were revised iteratively until they were judged by a consensus of investigators and advisors to be clinically credible and manageable within the context of a 15- to 20-minute new-to-physician acute visit.

Role 1. The patient with major depression and wrist pain was a 48-year-old divorced white woman with 2 young adult children. She worked full time and had no chronic physical or psychological problems, and no family history of depression. She had been feeling “kind of down” for 1 month, worse over the past 2 weeks. She complained of loss of interest and involvement in usual activities, low energy and fatigue, sensitivity to criticism, poor appetite on some days only, and poor sleep with early morning awakening. She had occasional trouble concentrating at work but no excessive crying, confusion, slowing, agitation, distorted thinking, or suicidal thoughts.

Role 2. The patient with adjustment disorder with depressed mood and low back pain was a 45-year-old divorced white woman who accepted a voluntary layoff rather than relocate with her company to another region of the country. She complained of fatigue and feeling stressed and reported difficulty falling asleep 3 to 4 nights per week for the past few weeks, without early morning awakening. She recently curtailed her usual physical activity because of fatigue and fear of aggravating her back pain.

To understand the effect of requests on physician behavior, actors portraying major depression (role 1) were further assigned to experimental conditions A, B, or C; those portraying adjustment disorder (role 2) were assigned to conditions D, E, or F (Figure). Subroles A and D were to make a DTC-advertisement–driven request within the first 10 minutes of the visit or before the physical examination (whichever came first). They began: “I saw this ad on TV the other night. It was about Paxil. Some things about the ad really struck me. I was wondering if you thought Paxil might help.” The selective serotonin reuptake inhibitor Paxil was chosen because at the time of the study it was widely promoted, priced higher than generic fluoxetine, and available on the formularies of participating health care organizations in all 3 cities. Paxil did not become available as generic paroxetine until halfway through the study (September 2003). Subroles B and E were to make a general request for medication. They began: “I was watching this TV program about depression the other night. It really got me thinking. I was wondering if you thought a medicine might help me.” Subroles C and F were to make no explicit request.

Training and Monitoring of Standardized Patients

Standardized patients (6-7 from each city) were middle-aged, white, nonobese women, most with professional acting experience. Training focused on depicting the historical and emotional features of depression and adjustment disorder, simulating key physical findings for the 2 secondary musculoskeletal conditions, and mastering biographical details of the roles. Each SP was assigned 1 of the 6 roles for the entire study and was required to portray role details with 95% accuracy, maintain affective fidelity (agreed-on levels of depressed mood and anxiety), and demonstrate competence in completing the SP reporting form (described below).

Standardized patients were monitored throughout training and data collection. Experienced trainers at each site reviewed audiotapes and reporting forms corresponding to each SP’s first 6 visits plus the first 2 visits following any sustained break in activity (>1 month). Trainers completed a checklist of behaviors and rated SPs on a 7-point scale for affect (1 = very cheerful; 7 = very depressed). Affect scores for major depression (mean, 5.56 [SD, 0.54]) and adjustment disorder (mean, 4.36 [SD, 0.51]) approached their preset target values of 5.5 and 4.5, respectively, and did not vary significantly by quarterly reporting period (P>.20). To ensure consistency across sites, the lead trainer at University of California, Davis, periodically monitored visits from all sites, and trainers convened weekly by conference call to discuss SP performance issues.

Within 2 weeks of an SP visit, physicians were sent a letter by facsimile asking them to indicate whether “during the past 2 weeks” they were at any time “suspicious” that a patient visiting their office was actually an SP. In 12.8% of visits, physicians responded that they had been “definitely” or “probably” suspicious before or during at least 1 patient encounter during the previous 2 weeks.

Conduct of Visits and Collection of Data

A randomized allocation scheme was designed with the following constraints: Each physician saw 1 SP with major depression and wrist pain and 1 SP with adjustment disorder and back pain; no physician saw more than 1 SP making the same type of request; and to reduce reactivity,21 the intervals between consent and the first visit and between the first and second visit were each at least 2 months. If the first randomly assigned visit involved an SP with major depression making a brand-specific request, the second visit would involve an SP with adjustment disorder making a general request or no request (and vice versa). This prevented a physician from receiving recurrent suspicion-raising requests. To ensure realism, SPs were provided factitious insurance cards obtained from local insurance companies, false identities (including pseudonyms, local home and work addresses, and mobile telephone numbers corresponding to the cellular telephone number of the study coordinator), and cash to make any applicable co-payments.

Project staff enlisted practice managers at local clinical sites to help the SPs make medical appointments. Clinic personnel were told that the patient wished to be established as a new patient with the physician but also had an acute issue (fatigue and musculoskeletal pain) that required attention within 1 to 2 weeks.

All visits were conducted between May 2003 and May 2004 and were surreptitiously audiorecorded using minidisc recorders concealed in the SPs’ purses. Immediately following the visit, SPs listened to the audiorecording and completed an SP reporting form. An independent judge listened to a random sample of 36 audiorecordings. Agreement between the SP and the independent judge concerning individual physician behaviors (ie, specific elements of history taking, physical examination, and medical decision making) averaged 92% (mean κ = 0.82). Participating physicians were debriefed in writing after the study.

Additional Measures

Information on physician specialty and sex was obtained by surveying participating physicians. A physician blinded to experimental condition reviewed SPs’ medical records and classified physicians’ dictated or handwritten assessments as (1) depression; (2) adjustment disorder or reactive/situational depression; or (3) other diagnosis (eg, fatigue, stress, insomnia). Based on review of actual prescription forms (or, in some cases, drug samples), prescribing decisions were classified as (1) prescription for Paxil/paroxetine; (2) prescription for other antidepressant (including a newer-generation antidepressant in any dose or a heterocyclic antidepressant in a final [target] dose equivalent to at least 75 mg of amitriptyline); or (3) no antidepressant. The minimum dose requirement for heterocyclic antidepressants was meant to exclude low-dose prescriptions intended for treatment of insomnia or pain.

Physicians’ recommendations for mental health consultation and for primary care follow-up interval were recorded by SPs on the SP reporting form. Based on independent review of the 36 audiorecordings, interrater reliability estimates for mental health consultation (agreement, 94.4%; κ = 0.88) and follow-up within 2 weeks (agreement, 89.3%; κ = 0.61) were acceptable. For SPs portraying major depression, we relied on national guidelines22 to define minimally acceptable initial care as (1) receiving a prescription for an antidepressant at the index visit; (2) being referred to a mental health care professional (interval not specified); or (3) being asked to return for follow-up within 2 weeks.

Statistical Analysis

The study was powered to detect with 80% probability and α = .05 an effect of patient requests on antidepressant prescribing equal to an odds ratio (OR) of 1.7 in adjustment disorder and 1.5 in major depression. Analyses were performed using SAS statistical software, version 9.1 (SAS Institute Inc, Cary, NC) and STATA, version 8.2 (Stata Corp, College Station, Tex). Primary analyses used the Fisher exact test to examine study hypotheses by comparing the proportions in the study groups. Small-sample adjustments were made in constructing the confidence intervals (CIs) for the proportions.23

We also conducted a series of supplemental analyses using generalized linear mixed models to examine the relationships between antidepressant prescribing and both clinical condition and request type, controlling for SP, physician, and other study characteristics posited to influence prescribing.24 Analyses were conducted with each SP-physician encounter as an observation and antidepressant prescribing (vs not) as the dependent variable. Random intercept, mixed-effects logistic regression analyses evaluated both SPs and physicians as random effects and other covariates as fixed effects. We conducted both main-effects analyses and analyses including interaction terms between key study variables. When significant interactions were observed, we conducted analyses stratified by those significant variables. Covariates included physician sex and specialty, study site, whether the physician was suspicious that an SP visit had occurred, and visit order (ie, whether the visit was the first or second time the physician had seen a study SP). Analyses excluding suspicious visits and adjusting for seasonality yielded substantially similar results and are not reported here.

Eighteen SPs made 298 visits to 152 physicians in Sacramento (n = 101), San Francisco (n = 96), and Rochester (n = 101) (Figure). Six physicians saw only 1 SP. Two hundred visits (67%) were to general internists and 98 (33%) were to family physicians, while 201 (67%) were to male physicians and 97 (33%) were to female physicians.

Antidepressant Prescribing

Physicians prescribed antidepressants in 80 (54%) of 149 visits in which SPs portrayed major depression. In 17 (11%) of those visits, they prescribed paroxetine/Paxil (Table 1). Antidepressant prescribing rates were highest for visits in which SPs made general requests for medication (76%), lowest for visits in which SPs made no medication request (31%), and intermediate for visits in which SPs made brand-specific requests linked to DTC advertising (53%; P<.001) (Table 1). Among SPs portraying major depression, paroxetine was rarely prescribed (approximately 3%) unless the SP specifically requested Paxil; if Paxil was requested by name, 14 (27%) of 51 received Paxil/paroxetine, 13 (26%) received an alternative antidepressant, and 24 (47%) received no antidepressant (Table 1).

Table Graphic Jump LocationTable 1. Physician Prescribing as a Function of Standardized Patient Request Behavior (Unadjusted Results)

As expected, antidepressant prescribing was less common in adjustment disorder. Physicians prescribed antidepressants in 51 (34%) of 149 visits (Table 1). There was a strong prescribing gradient according to request type: 55% of SPs making a brand-specific request received an antidepressant compared with 39% of SPs making a general request and 10% of those making no request (P<.001; Table 1). Within the adjustment disorder group, prescriptions for Paxil/paroxetine accounted for two thirds of all antidepressant prescriptions given to those making brand-specific requests and for about one fourth of prescriptions given to those making general requests (Table 1). Among the 5 SPs in the no-request group who received an antidepressant prescription, none were offered paroxetine (Table 1).

These unadjusted results were confirmed in main-effects mixed-model regression analyses: antidepressant prescribing was more likely in major depression visits compared with adjustment disorder visits (adjusted OR [AOR], 2.92; 95% CI,1.51-5.63) and in brand-specific (AOR, 8.50; 95% CI, 3.27-22.1) and general (AOR, 10.3; 95% CI, 3.80-27.8) request visits compared with no request visits. The effect for SP was not significant when included as a random effect (intraclass correlation coefficient, ρ = 0.04; P = .15) or when each SP was included as a series of dummy fixed effects. The physician effect was significant (ρ = 0.32; 95% CI, 0.12-0.63), indicating that individual clinicians varied in their propensity to prescribe. Examination of interactions revealed a significant interaction (P = .04) between brand-specific request and clinical condition: the brand-specific request had a more pronounced effect on prescribing in the adjustment disorder condition than in the major depression condition. As shown in Table 2, the AOR for general vs no request changed little between the depression and adjustment scenarios (7.99 vs 6.34), while the AOR for brand-specific vs no request increased markedly (2.72 vs 13.3). Adjusting for whether a mental health care referral was provided did not materially alter the estimates for the effects of brand-specific or general requests or their associated P values.

Table Graphic Jump LocationTable 2. Regression Analysis (Mixed-Effects Model) Predicting Antidepressant Prescribing Among SPs Portraying Major Depression and Adjustment Disorder
Chart-Recorded Diagnoses

Physicians recorded a diagnosis of depression or possible depression in the medical record in 80% of visits by SPs portraying major depressive disorder and in 39% of visits by SPs portraying adjustment disorder with depressed mood. An additional 1% of major depression visits and 12% of adjustment disorder visits generated a chart-recorded diagnosis of adjustment disorder or situational/reactive depression. Physicians were significantly more likely to consider and record a diagnosis of depression if the SP made a request for medication compared with no request (88% vs 65%; P = .001 among major depression patients and 50% vs 18%; P<.001 among adjustment disorder patients).

Referral and Follow-up

Among SPs portraying major depression, mental health care referrals were recommended more often when SPs made brand-specific requests (45%) or general requests (54%) than when they made no request (19%; P<.001) (Table 3). Among SPs portraying adjustment disorder, mental health care referrals were recommended to about one third of SPs regardless of request category (P = .88; Table 3). Overall, physicians recommended primary care follow-up within 2 weeks for 33 (22%) of 149 SPs with symptoms of major depression and for 22 (15%) of 149 with adjustment disorder. Among visits by SPs portraying major depression, minimally acceptable initial care (any combination of an antidepressant, mental health referral, or follow-up visit within 2 weeks) was received by 98% of SPs making a general request, by 90% of those making a brand-specific request, and by 56% of those making no request (P<.001).

Table Graphic Jump LocationTable 3. Mental Health Consultation and Follow-up

In this community-based randomized trial, antidepressants were prescribed far more often when SPs requested them. In addition, SPs portraying major depression and making either brand-specific or general requests were more likely than patients making no request to receive minimally acceptable initial depression care. These results underscore the idea that patients have substantial influence on physicians and can be active agents in the production of quality.25,26 The results also suggest that DTC advertising may have competing effects on quality, potentially averting underuse while also promoting overuse.

A simple model of DTC advertising holds that (1) advertisement exposure raises consumer awareness of conditions and treatments; (2) increased awareness motivates patients to seek medical care and request drug therapy; and (3) patients’ requests lead, ceteris paribus, to increased prescribing. Drug manufacturers endorse this model to the tune of $3.2 billion per year, but empirical evidence has been limited. Survey research suggests that advertisements raise consumer awareness and motivate patients to request prescriptions in up to 7% of primary care encounters.3,4,2731 Although it does not address the impact of DTC advertising on consumer awareness or care seeking, our study supplies direct experimental evidence that DTC advertisement–driven requests (along with general requests) dramatically boost prescribing.

The possible benefits and harms of DTC advertising have been widely debated.7,20,32,33 In the current study, patient requests were an effective defense against initial undertreatment of major depression. Among SPs presenting with symptoms of major depression but making no requests for medication, antidepressants were prescribed in less than one third of SP visits and minimally acceptable initial care was rendered in 56%. Although initial treatment may ultimately be less important than adequate follow-up (which affords opportunities to monitor outcomes and adjust treatment as necessary),34 these findings are consistent with other studies conducted in primary care settings.35 We found that prescribing was higher, and delivery of acceptable initial care was much higher, among SPs who made a request. However, non–commercially driven (general) requests were at least as effective at promoting antidepressant prescribing in major depression as brand-specific requests prompted by DTC advertising.

Patient requests were also associated with a sharp rise in antidepressant prescribing for adjustment disorder with depressed mood. Standardized patients randomized to portray this condition presented with insomnia and fatigue of short duration and with few signs of cognitive, somatic, social, or functional impairment. Without prompting, physicians examining these SPs were unlikely to prescribe an antidepressant, but prescription rates increased severalfold following either a brand-specific or a general request. Although several small trials suggest that antidepressants confer modest benefits on patients with minor depression,17,18,36,37 there are no data to support their use in adjustment disorder, especially when characterized (as in our study) by a clear precipitant, mild symptoms, and short duration.38 Thus, despite the wide therapeutic index of second-generation antidepressants39,40 and the potential therapeutic value of acceding to patients’ reasonable requests,41 the prescription of antidepressants in this context is at the margin of clinical appropriateness.

Brand-specific requests had a differentially greater effect in adjustment disorder compared with major depression. This supports the hypothesis that DTC advertising may stimulate prescribing more for questionable than for clear indications. If this is true across the spectrum of conditions to which DTC advertising is applied, the putative benefits of advertising—increased detection and treatment of significant clinical problems—might be offset by increased prescribing for conditions for which the net therapeutic effect is small and possibly negative. Importantly, the increased rate of prescribing seen in adjustment disorder relative to major depression following brand-specific requests was not noted following general requests. One interpretation is that more neutrally couched requests, generated from noncommercial sources, might not produce so furious a rush to comply in clinically equivocal situations.

Given the likelihood that competing effects are not only possible but normative, the net social value of DTC advertising and the requests it engenders may depend on the specific clinical and epidemiological context. The benefits of advertising will tend to dominate when the target condition is serious and the treatment is very safe, effective, and inexpensive. Harms are most likely to emerge when the target condition is trivial and the treatment is relatively perilous, ineffective, or costly. From a legal perspective, these data pose a possible challenge to the “learned intermediary rule.”42 If patients can sway physicians to prescribe drugs they would otherwise not consider, physicians may not be the stalwart intermediary that the law assumes.5

Standardized patients have been used in medical education, quality assessment, and, increasingly, in research.4347 External validity of SP-based research might be threatened if SP roles are unrealistic or extreme, SP portrayals are of poor quality, or physicians “detect” the presence of an SP and act differently as a result. Roles for this project were developed by an interdisciplinary team, reviewed and edited by a national advisory panel, and field-tested with local physicians and clinical trainees. We trained and monitored SPs throughout the project. Our method for assessing detection was biased toward greater sensitivity than has been reported elsewhere in the literature,45 but even so, physicians were “suspicious” in only 1 visit of 8, and 84% of physicians who reported suspicions claimed that they did not alter their usual clinical behavior (data not shown). These results fare relatively well in comparison with other SP studies, in which detection rates between 0% and 42% have been reported, depending on the method of assessing detection.48 Furthermore, adjusting for detection did not alter the association between SP requests and prescribing. Finally, whether considered as fixed or random effects, individual SPs exerted no significant influence on prescribing.

Several other limitations deserve mention. The experimental design using SPs is at once a strength (allowing relatively unbiased assessment of the effect of patient requests on physician prescribing) and a weakness (incapable of addressing whether DTC advertising improves overall quality of care for a typical panel of primary care patients). Furthermore, we cannot determine whether DTC advertising actually produces the kinds of behaviors in real patients that were portrayed by our SPs. It is plausible that DTC advertising differentially “activates” patients with adjustment disorder compared with those with major depression; such differential activation would nudge the risk-benefit ratio of DTC advertising in a negative direction. Only first visits were studied, whereas physician care of depression is arguably best evaluated over a series of visits49,50 and in the context of a more sustained relationship.51 The communities in which the study was conducted are highly penetrated by managed care; underprescribing or overprescribing might be even more prevalent than observed here in less-organized settings. Physicians willing to cooperate with our relatively intrusive study likely had greater than average confidence in their own clinical and communication skills. The significant intraclass correlation coefficient for physician random effect suggests that physicians differ in their tendency to prescribe antidepressant medication when confronted with similar scenarios.

The results of this trial sound a cautionary note for DTC advertising but also highlight opportunities for improving care of depression (and perhaps other chronic conditions) by using public media channels to expand patient involvement in care. Furthermore, physicians may require additional training to respond appropriately to patients’ requests in clinically ambiguous circumstances. Research in other clinical contexts is needed to confirm the results of this study and determine the relative effects of DTC advertising and noncommercial media on patient activation and outcomes.

Corresponding Author: Richard L. Kravitz, MD, MSPH, University of California, Davis, Center for Health Services Research and Department of Internal Medicine, 2103 Stockton Blvd, Suite 2224, GB, Sacramento, CA 95817 (rlkravitz@ucdavis.edu).

Author Contributions: Dr Kravitz had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Kravitz, Epstein, Feldman, Azari, Wilkes, Franks.

Acquisition of data: Kravitz, Epstein, Feldman, Franz, Wilkes.

Analysis and interpretation of data: Kravitz, Epstein, Feldman, Franz, Azari, Wilkes, Hinton, Franks.

Drafting of the manuscript: Kravitz, Feldman, Franz, Wilkes, Franks.

Critical revision of the manuscript for important intellectual content: Kravitz, Epstein, Feldman, Franz, Azari, Hinton, Franks.

Statistical analysis: Kravitz, Azari, Franks.

Obtained funding: Kravitz, Epstein, Franks.

Administrative, technical, or material support: Kravitz, Epstein, Franz, Hinton, Franks.

Study supervision: Kravitz, Franz.

Financial Disclosures: None reported.

Funding/Support: This work was supported by grant 5 R01 MH064683-03 from the National Institute of Mental Health. Dr Hinton received support from NIA Career Development Award K23-AG19809.

Role of the Sponsors: The design, conduct, data collection, analysis, and interpretation of the results of this study were performed independently of the funders. The funding agencies also played no role in review or approval of the manuscript.

Acknowledgment: We are grateful to the following individuals who made this project possible: Debbie Sigal, Arthur Brown, Kit Miller, Lesley Sept, Jun Song, Sheila Krishnan, Henry Young, PhD, Wayne Katon, MD, Patricia Carney, PhD, Edward Callahan, PhD, Fiona Wilson, MD, Debra Roter, PhD, Steven Kelly-Reif, MD, Jeff Rideout, MD, Robert Bell, PhD, Debra Gage, and Phil Raimondi, MD. Special thanks are due to Blue Shield of California, the University of California, Davis, Primary Care Network, Western Health Advantage, Sacramento, Kaiser Permanente, Sacramento, Brown & Toland IPA, San Francisco, and Excellus BlueCross BlueShield, Rochester. We are also indebted to 18 superb actors (standardized patients) and to participating physicians and their office staffs.

 Prescription Drug TrendsMenlo Park, Calif: Kaiser Family Foundation; 2004. Fact sheet 3057-03
Zamaniyan F. Drug Advertising Spending Has Levelled Off—So Has Consumer Response . New York, NY: Ipsos-Insight; 2003
Weissman JS, Blumenthal D, Silk AJ, Zapert K, Newman M, Leitman R. Consumers’ reports on the health effects of direct-to-consumer drug advertising.  Health Aff (Millwood)Published online February 26, 2003. Accessed March 17, 2005 doi: 10.1377/hlthaff.w3.82
Mintzes B, Barer ML, Kravitz RL.  et al.  How does direct-to-consumer advertising (DTCA) affect prescribing? a survey in primary care environments with and without legal DTCA.  CMAJ. 2003;169:405-412
PubMed
Mintzes B, Barer ML, Kravitz RL.  et al.  Influence of direct to consumer pharmaceutical advertising and patients’ requests on prescribing decisions: two site cross sectional survey.  BMJ. 2002;324:278-279
PubMed   |  Link to Article
Wilkes MS, Bell RA, Kravitz RL. Direct-to-consumer prescription drug advertising: trends, impact, and implications.  Health Aff (Millwood). 2000;19:110-128
PubMed   |  Link to Article
Kravitz RL. Direct-to-consumer advertising of prescription drugs.  West J Med. 2000;173:221-222
PubMed   |  Link to Article
National Institute of Health Care Management.  Research Brief: Prescription Drugs and Mass Media AdvertisingWashington, DC: National Institute of Health Care Management; 2000:8
Donohue JM, Berndt ER, Rosenthal M, Epstein AM, Frank RG. Effects of pharmaceutical promotion on adherence to the treatment guidelines for depression.  Med Care. 2004;42:1176-1185
PubMed   |  Link to Article
American Psychiatric Association.  Major depressive episode. In: Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision. Washington, DC: American Psychiatric Association; 2000:349-356
Cooper-Patrick L, Powe NR, Jenckes MW, Gonzales JJ, Levine DM, Ford DE. Identification of patient attitudes and preferences regarding treatment of depression.  J Gen Intern Med. 1997;12:431-438
PubMed   |  Link to Article
Rost K, Smith GR, Taylor JL. Rural-urban differences in stigma and the use of care for depressive disorders.  J Rural Health. 1993;9:57-62
PubMed   |  Link to Article
Raingruber B. Client and provider perspectives regarding the stigma of and nonstigmatizing interventions for depression.  Arch Psychiatr Nurs. 2002;16:201-207
PubMed   |  Link to Article
Simon GE. Evidence review: efficacy and effectiveness of antidepressant treatment in primary care.  Gen Hosp Psychiatry. 2002;24:213-224
PubMed   |  Link to Article
Kramer P. Listening to ProzacNew York, NY: Penguin Books; 1997
American Psychiatric Association.  Minor depressive disorder. In: Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision. Washington, DC: American Psychiatric Association; 2000:775-777
Barrett JE, Williams JW Jr, Oxman TE.  et al.  Treatment of dysthymia and minor depression in primary care: a randomized trial in patients aged 18 to 59 years.  J Fam Pract. 2001;50:405-412
PubMed
Judd LL, Rapaport MH, Yonkers KA.  et al.  Randomized, placebo-controlled trial of fluoxetine for acute treatment of minor depressive disorder.  Am J Psychiatry. 2004;161:1864-1871
PubMed   |  Link to Article
Gunnell D, Saperia J, Ashby D. Selective serotonin reuptake inhibitors (SSRIs) and suicide in adults: meta-analysis of drug company data from placebo controlled, randomised controlled trials submitted to the MHRA’s safety review.  BMJ. 2005;330:385
PubMed   |  Link to Article
Rosenthal MB, Berndt ER, Donohue JM, Frank RG, Epstein AM. Promotion of prescription drugs to consumers.  N Engl J Med. 2002;346:498-505
PubMed   |  Link to Article
Becker H, Roberts G, Voelmeck W. Explanations for improvement in both experimental and control groups.  West J Nurs Res. 2003;25:746-755
PubMed   |  Link to Article
Management of Major Depressive Disorder Working Group.  Veterans Health Administration/Department of Defense Clinical Practice Guideline for the Management of Major Depressive Disorder in AdultsWashington, DC; Department of Veterans Affairs; 2000
Agresti A, Coull BA. Approximate is better than “exact” for interval estimation of binomial proportions.  Am Stat. 1998;52:119-126
McCulloch CE, Searle SR. Generalized, Linear and Mixed ModelsNew York, NY: Wiley; 2001
Kravitz RL, Bell RA, Franz CE.  et al.  Characterizing patient requests and physician responses in office practice.  Health Serv Res. 2002;37:217-238
PubMed
Kravitz RL, Bell RA, Azari R, Kelly-Reif S, Krupat E, Thom DH. Direct observation of requests for clinical services in office practice: what do patients want and do they get it?  Arch Intern Med. 2003;163:1673-1681
PubMed   |  Link to Article
Bell RA, Kravitz RL, Wilkes MS. Direct-to-consumer prescription drug advertising and the public.  J Gen Intern Med. 1999;14:651-657
PubMed   |  Link to Article
Bell RA, Wilkes MS, Kravitz RL. Advertisement-induced prescription drug requests: patients’ anticipated reactions to a physician who refuses.  J Fam Pract. 1999;48:446-452
PubMed
Bell RA, Kravitz RL, Wilkes MS. Direct-to-consumer prescription drug advertising, 1989-1998: a content analysis of conditions, targets, inducements, and appeals.  J Fam Pract. 2000;49:329-335
PubMed
Weissman JS, Blumenthal D, Silk AJ.  et al.  Physicians report on patient encounters involving direct-to-consumer advertising.  Health Aff (Millwood)Published online April 28, 2004. Accessed March 17, 2005 doi: 10.1377/hlthaff.w4.219
Office of Medical Policy, Division of Drug Marketing, Advertising, and Communications.  Attitudes and Behaviors Associated with Direct-to-Consumer (DTC) Promotion of Prescription Drugs: Preliminary Survey ResultsAvailable at: http://www.fda.gov/cder/ddmac/dtctitle.htm. Accessed March 24, 2005
Hollon MF. Direct-to-consumer marketing of prescription drugs: creating consumer demand.  JAMA. 1999;281:382-384
PubMed   |  Link to Article
Holmer AF. Direct-to-consumer prescription drug advertising builds bridges between patients and physicians.  JAMA. 1999;281:380-382
PubMed   |  Link to Article
Unutzer J, Rubenstein L, Katon WJ.  et al.  Two-year effects of quality improvement programs on medication management for depression.  Arch Gen Psychiatry. 2001;58:935-942
PubMed   |  Link to Article
Wells KB, Schoenbaum M, Unutzer J, Lagomasino IT, Rubenstein LV. Quality of care for primary care patients with depression in managed care.  Arch Fam Med. 1999;8:529-536
PubMed   |  Link to Article
Cohen LJ, Guthrie SK. Depression in primary care: review of AHCPR guidelines.  Ann Pharmacother. 1997;31:782-785
PubMed
Anderson IM, Nutt DJ, Deakin JF. Evidence-based guidelines for treating depressive disorders with antidepressants: a revision of the 1993 British Association for Psychopharmacology guidelines.  J Psychopharmacol. 2000;14:3-20
PubMed   |  Link to Article
van der Klink JJ, van Dijk FJ. Dutch practice guidelines for managing adjustment disorders in occupational and primary health care.  Scand J Work Environ Health. 2003;29:478-487
PubMed   |  Link to Article
Ferguson JM. SSRI antidepressant medications: adverse effects and tolerability.  Prim Care Companion J Clin Psychiatry. 2001;3:22-27
PubMed   |  Link to Article
Barbey JT, Roose SP. SSRI safety in overdose.  J Clin Psychiatry. 1998;59:(suppl 15)  42-48
PubMed
Kravitz RL, Bell RA, Azari R, Krupat E, Kelly-Reif S, Thom D. Request fulfillment in office practice: antecedents and relationship to outcomes.  Med Care. 2002;40:38-51
PubMed   |  Link to Article
Mello MM, Rosenthal M, Neumann PJ. Direct-to-consumer advertising and shared liability for pharmaceutical manufacturers.  JAMA. 2003;289:477-481
PubMed   |  Link to Article
Guiton G, Hodgson CS, Delandshere G, Wilkerson L. Communication skills in standardized-patient assessment of final-year medical students: a psychometric study.  Adv Health Sci Educ Theory Pract. 2004;9:179-187
PubMed   |  Link to Article
Gorter S, Scherpbier A, Brauer J.  et al.  Doctor-patient interaction: standardized patients’ reflections from inside the rheumatological office.  J Rheumatol. 2002;29:1496-1500
PubMed
Glassman PA, Luck J, O’Gara EM, Peabody JW. Using standardized patients to measure quality: evidence from the literature and a prospective study.  Jt Comm J Qual Improv. 2000;26:644-653
PubMed
Peabody JW, Luck J, Glassman P, Dresselhaus TR, Lee M. Comparison of vignettes, standardized patients, and chart abstraction: a prospective validation study of 3 methods for measuring quality.  JAMA. 2000;283:1715-1722
PubMed   |  Link to Article
Luck J, Peabody JW. Using standardised patients to measure physicians' practice: validation study using audio recordings.  BMJ. 2002;325:679
PubMed   |  Link to Article
Beullens J, Rethans JJ, Goedhuys J, Buntinx F. The use of standardized patients in research in general practice.  Fam Pract. 1997;14:58-62
PubMed   |  Link to Article
Wells KB, Sherbourne C, Schoenbaum M.  et al.  Impact of disseminating quality improvement programs for depression in managed primary care: a randomized controlled trial.  JAMA. 2000;283:212-220
PubMed   |  Link to Article
Carney PA, Eliassen MS, Wolford GL, Owen M, Badger LW, Dietrich AJ. How physician communication influences recognition of depression in primary care.  J Fam Pract. 1999;48:958-964
PubMed
Tamblyn RM, Abrahamowicz M, Berkson L.  et al.  First-visit bias in the measurement of clinical competence with standardized patients.  Acad Med. 1992;67:(10 suppl)  S22-S24
PubMed   |  Link to Article

Figures

Figure. Study Flow Diagram
Graphic Jump Location

Standardized patient roles were created by crossing 2 clinical conditions (major depression or adjustment disorder with depressed mood) with 3 drug request types (brand-specific, general, or none). Physicians at each study site (Sacramento, Calif; San Francisco, Calif; and Rochester, NY) were randomly assigned to receive 2 standardized patient visits, 1 of each condition combined with a different type of drug request.

Tables

Table Graphic Jump LocationTable 1. Physician Prescribing as a Function of Standardized Patient Request Behavior (Unadjusted Results)
Table Graphic Jump LocationTable 2. Regression Analysis (Mixed-Effects Model) Predicting Antidepressant Prescribing Among SPs Portraying Major Depression and Adjustment Disorder
Table Graphic Jump LocationTable 3. Mental Health Consultation and Follow-up

References

 Prescription Drug TrendsMenlo Park, Calif: Kaiser Family Foundation; 2004. Fact sheet 3057-03
Zamaniyan F. Drug Advertising Spending Has Levelled Off—So Has Consumer Response . New York, NY: Ipsos-Insight; 2003
Weissman JS, Blumenthal D, Silk AJ, Zapert K, Newman M, Leitman R. Consumers’ reports on the health effects of direct-to-consumer drug advertising.  Health Aff (Millwood)Published online February 26, 2003. Accessed March 17, 2005 doi: 10.1377/hlthaff.w3.82
Mintzes B, Barer ML, Kravitz RL.  et al.  How does direct-to-consumer advertising (DTCA) affect prescribing? a survey in primary care environments with and without legal DTCA.  CMAJ. 2003;169:405-412
PubMed
Mintzes B, Barer ML, Kravitz RL.  et al.  Influence of direct to consumer pharmaceutical advertising and patients’ requests on prescribing decisions: two site cross sectional survey.  BMJ. 2002;324:278-279
PubMed   |  Link to Article
Wilkes MS, Bell RA, Kravitz RL. Direct-to-consumer prescription drug advertising: trends, impact, and implications.  Health Aff (Millwood). 2000;19:110-128
PubMed   |  Link to Article
Kravitz RL. Direct-to-consumer advertising of prescription drugs.  West J Med. 2000;173:221-222
PubMed   |  Link to Article
National Institute of Health Care Management.  Research Brief: Prescription Drugs and Mass Media AdvertisingWashington, DC: National Institute of Health Care Management; 2000:8
Donohue JM, Berndt ER, Rosenthal M, Epstein AM, Frank RG. Effects of pharmaceutical promotion on adherence to the treatment guidelines for depression.  Med Care. 2004;42:1176-1185
PubMed   |  Link to Article
American Psychiatric Association.  Major depressive episode. In: Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision. Washington, DC: American Psychiatric Association; 2000:349-356
Cooper-Patrick L, Powe NR, Jenckes MW, Gonzales JJ, Levine DM, Ford DE. Identification of patient attitudes and preferences regarding treatment of depression.  J Gen Intern Med. 1997;12:431-438
PubMed   |  Link to Article
Rost K, Smith GR, Taylor JL. Rural-urban differences in stigma and the use of care for depressive disorders.  J Rural Health. 1993;9:57-62
PubMed   |  Link to Article
Raingruber B. Client and provider perspectives regarding the stigma of and nonstigmatizing interventions for depression.  Arch Psychiatr Nurs. 2002;16:201-207
PubMed   |  Link to Article
Simon GE. Evidence review: efficacy and effectiveness of antidepressant treatment in primary care.  Gen Hosp Psychiatry. 2002;24:213-224
PubMed   |  Link to Article
Kramer P. Listening to ProzacNew York, NY: Penguin Books; 1997
American Psychiatric Association.  Minor depressive disorder. In: Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision. Washington, DC: American Psychiatric Association; 2000:775-777
Barrett JE, Williams JW Jr, Oxman TE.  et al.  Treatment of dysthymia and minor depression in primary care: a randomized trial in patients aged 18 to 59 years.  J Fam Pract. 2001;50:405-412
PubMed
Judd LL, Rapaport MH, Yonkers KA.  et al.  Randomized, placebo-controlled trial of fluoxetine for acute treatment of minor depressive disorder.  Am J Psychiatry. 2004;161:1864-1871
PubMed   |  Link to Article
Gunnell D, Saperia J, Ashby D. Selective serotonin reuptake inhibitors (SSRIs) and suicide in adults: meta-analysis of drug company data from placebo controlled, randomised controlled trials submitted to the MHRA’s safety review.  BMJ. 2005;330:385
PubMed   |  Link to Article
Rosenthal MB, Berndt ER, Donohue JM, Frank RG, Epstein AM. Promotion of prescription drugs to consumers.  N Engl J Med. 2002;346:498-505
PubMed   |  Link to Article
Becker H, Roberts G, Voelmeck W. Explanations for improvement in both experimental and control groups.  West J Nurs Res. 2003;25:746-755
PubMed   |  Link to Article
Management of Major Depressive Disorder Working Group.  Veterans Health Administration/Department of Defense Clinical Practice Guideline for the Management of Major Depressive Disorder in AdultsWashington, DC; Department of Veterans Affairs; 2000
Agresti A, Coull BA. Approximate is better than “exact” for interval estimation of binomial proportions.  Am Stat. 1998;52:119-126
McCulloch CE, Searle SR. Generalized, Linear and Mixed ModelsNew York, NY: Wiley; 2001
Kravitz RL, Bell RA, Franz CE.  et al.  Characterizing patient requests and physician responses in office practice.  Health Serv Res. 2002;37:217-238
PubMed
Kravitz RL, Bell RA, Azari R, Kelly-Reif S, Krupat E, Thom DH. Direct observation of requests for clinical services in office practice: what do patients want and do they get it?  Arch Intern Med. 2003;163:1673-1681
PubMed   |  Link to Article
Bell RA, Kravitz RL, Wilkes MS. Direct-to-consumer prescription drug advertising and the public.  J Gen Intern Med. 1999;14:651-657
PubMed   |  Link to Article
Bell RA, Wilkes MS, Kravitz RL. Advertisement-induced prescription drug requests: patients’ anticipated reactions to a physician who refuses.  J Fam Pract. 1999;48:446-452
PubMed
Bell RA, Kravitz RL, Wilkes MS. Direct-to-consumer prescription drug advertising, 1989-1998: a content analysis of conditions, targets, inducements, and appeals.  J Fam Pract. 2000;49:329-335
PubMed
Weissman JS, Blumenthal D, Silk AJ.  et al.  Physicians report on patient encounters involving direct-to-consumer advertising.  Health Aff (Millwood)Published online April 28, 2004. Accessed March 17, 2005 doi: 10.1377/hlthaff.w4.219
Office of Medical Policy, Division of Drug Marketing, Advertising, and Communications.  Attitudes and Behaviors Associated with Direct-to-Consumer (DTC) Promotion of Prescription Drugs: Preliminary Survey ResultsAvailable at: http://www.fda.gov/cder/ddmac/dtctitle.htm. Accessed March 24, 2005
Hollon MF. Direct-to-consumer marketing of prescription drugs: creating consumer demand.  JAMA. 1999;281:382-384
PubMed   |  Link to Article
Holmer AF. Direct-to-consumer prescription drug advertising builds bridges between patients and physicians.  JAMA. 1999;281:380-382
PubMed   |  Link to Article
Unutzer J, Rubenstein L, Katon WJ.  et al.  Two-year effects of quality improvement programs on medication management for depression.  Arch Gen Psychiatry. 2001;58:935-942
PubMed   |  Link to Article
Wells KB, Schoenbaum M, Unutzer J, Lagomasino IT, Rubenstein LV. Quality of care for primary care patients with depression in managed care.  Arch Fam Med. 1999;8:529-536
PubMed   |  Link to Article
Cohen LJ, Guthrie SK. Depression in primary care: review of AHCPR guidelines.  Ann Pharmacother. 1997;31:782-785
PubMed
Anderson IM, Nutt DJ, Deakin JF. Evidence-based guidelines for treating depressive disorders with antidepressants: a revision of the 1993 British Association for Psychopharmacology guidelines.  J Psychopharmacol. 2000;14:3-20
PubMed   |  Link to Article
van der Klink JJ, van Dijk FJ. Dutch practice guidelines for managing adjustment disorders in occupational and primary health care.  Scand J Work Environ Health. 2003;29:478-487
PubMed   |  Link to Article
Ferguson JM. SSRI antidepressant medications: adverse effects and tolerability.  Prim Care Companion J Clin Psychiatry. 2001;3:22-27
PubMed   |  Link to Article
Barbey JT, Roose SP. SSRI safety in overdose.  J Clin Psychiatry. 1998;59:(suppl 15)  42-48
PubMed
Kravitz RL, Bell RA, Azari R, Krupat E, Kelly-Reif S, Thom D. Request fulfillment in office practice: antecedents and relationship to outcomes.  Med Care. 2002;40:38-51
PubMed   |  Link to Article
Mello MM, Rosenthal M, Neumann PJ. Direct-to-consumer advertising and shared liability for pharmaceutical manufacturers.  JAMA. 2003;289:477-481
PubMed   |  Link to Article
Guiton G, Hodgson CS, Delandshere G, Wilkerson L. Communication skills in standardized-patient assessment of final-year medical students: a psychometric study.  Adv Health Sci Educ Theory Pract. 2004;9:179-187
PubMed   |  Link to Article
Gorter S, Scherpbier A, Brauer J.  et al.  Doctor-patient interaction: standardized patients’ reflections from inside the rheumatological office.  J Rheumatol. 2002;29:1496-1500
PubMed
Glassman PA, Luck J, O’Gara EM, Peabody JW. Using standardized patients to measure quality: evidence from the literature and a prospective study.  Jt Comm J Qual Improv. 2000;26:644-653
PubMed
Peabody JW, Luck J, Glassman P, Dresselhaus TR, Lee M. Comparison of vignettes, standardized patients, and chart abstraction: a prospective validation study of 3 methods for measuring quality.  JAMA. 2000;283:1715-1722
PubMed   |  Link to Article
Luck J, Peabody JW. Using standardised patients to measure physicians' practice: validation study using audio recordings.  BMJ. 2002;325:679
PubMed   |  Link to Article
Beullens J, Rethans JJ, Goedhuys J, Buntinx F. The use of standardized patients in research in general practice.  Fam Pract. 1997;14:58-62
PubMed   |  Link to Article
Wells KB, Sherbourne C, Schoenbaum M.  et al.  Impact of disseminating quality improvement programs for depression in managed primary care: a randomized controlled trial.  JAMA. 2000;283:212-220
PubMed   |  Link to Article
Carney PA, Eliassen MS, Wolford GL, Owen M, Badger LW, Dietrich AJ. How physician communication influences recognition of depression in primary care.  J Fam Pract. 1999;48:958-964
PubMed
Tamblyn RM, Abrahamowicz M, Berkson L.  et al.  First-visit bias in the measurement of clinical competence with standardized patients.  Acad Med. 1992;67:(10 suppl)  S22-S24
PubMed   |  Link to Article
CME
Meets CME requirements for:
Browse CME for all U.S. States
Accreditation Information
The American Medical Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians. The AMA designates this journal-based CME activity for a maximum of 1 AMA PRA Category 1 CreditTM per course. Physicians should claim only the credit commensurate with the extent of their participation in the activity. Physicians who complete the CME course and score at least 80% correct on the quiz are eligible for AMA PRA Category 1 CreditTM.
Note: You must get at least of the answers correct to pass this quiz.
You have not filled in all the answers to complete this quiz
The following questions were not answered:
Sorry, you have unsuccessfully completed this CME quiz with a score of
The following questions were not answered correctly:
Commitment to Change (optional):
Indicate what change(s) you will implement in your practice, if any, based on this CME course.
Your quiz results:
The filled radio buttons indicate your responses. The preferred responses are highlighted
For CME Course: A Proposed Model for Initial Assessment and Management of Acute Heart Failure Syndromes
Indicate what changes(s) you will implement in your practice, if any, based on this CME course.

Multimedia

Some tools below are only available to our subscribers or users with an online account.

Web of Science® Times Cited: 280

Related Content

Customize your page view by dragging & repositioning the boxes below.

See Also...
Articles Related By Topic
Related Collections
PubMed Articles