Doctors and Patients' Susceptibility to Framing Bias: A Randomized Trial

ABSTRACT: BACKGROUND: Framing of risk influences the perceptions of treatment benefit. OBJECTIVE: To determine which risk framing format corresponds best to comprehensive multi-faceted information, and to compare framing bias in doctors and in patients. DESIGN: Randomized mail surveys. PARTICIPANTS: One thousand four hundred and thirty-one doctors (56% response rate) and 1121 recently hospitalized patients (65% response rate). INTERVENTION: Respondents were asked to interpret the results of a hypothetical clinical trial comparing an old and a new drug. They were randomly assigned to the following framing formats: absolute survival (new drug: 96% versus old drug: 94%), absolute mortality (4% versus 6%), relative mortality reduction (reduction by a third) or all three (fully informed condition). The new drug was reported to cause more side-effects. MAIN MEASURE: Rating of the new drug as more effective than the old drug. RESULTS: The proportions of doctors who rated the new drug as more effective varied by risk presentation format (abolute survival 51.8%, absolute mortality 68.3%, relative mortality reduction 93.8%, and fully informed condition 69.8%, p  0.1). In comparison to the fully informed condition, the odds ratio of greater perceived effectiveness was 0.45 for absolute survival (p < 0.001), 0.89 for absolute mortality (p = 0.29), and 4.40 for relative mortality reduction (p < 0.001). CONCLUSIONS: Framing bias affects doctors and patients similarly. Describing clinical trial results as absolute risks is the least biased format, for both doctors and patients. Presenting several risk formats (on both absolute and relative scales) should be encourage

Patient reports of undesirable events during hospitalization

BACKGROUND: Thus far, incident reporting in health care has relied on health professionals. However, patients too may be able to signal the occurrence of undesirable events. OBJECTIVE: To estimate the frequency of undesirable events reported by recently discharged patients, and to identify correlates of undesirable events. DESIGN: Mailed patient survey. SETTING: Swiss public teaching hospital. PARTICIPANTS: Adult patients (N=1,518) discharged from hospital. MEASUREMENTS: Self-reports of 27 undesirable events during hospitalization, including 9 medical complications, 9 interpersonal problems, and 9 incidents related to the health care process. RESULTS: Most survey respondents (1,433, 94.4%) completed the section about undesirable events, and 725 (50.6%) reported at least 1 event. The most frequent events were phlebitis (11.0%), unavailable medical record (9.5%), failure to respect confidentiality (8.4%), and hospital-acquired infection (8.2%). The odds of an unfavorable rating increased with each additional interpersonal problem (odds ratio [OR] 1.6, 95% confidence interval [CI] 1.3 to 1.8), each additional process-related problem (OR 1.5, 95% CI 1.3 to 1.9), but not with each additional medical complication (OR 1.0, 95% CI 0.9 to 1.2). Longer duration of stay, poor health, and depressed mood were all related to a greater reported frequency of undesirable events. CONCLUSION: Patients are able to report undesirable events that occur during hospital care. Such events occur in about a half of the hospitalizations, and have a negative impact on satisfaction with car

Does Prevalence Matter to Physicians in Estimating Post-test Probability of Disease? A Randomized Trial

ABSTRACT: BACKGROUND: The probability of a disease following a diagnostic test depends on the sensitivity and specificity of the test, but also on the prevalence of the disease in the population of interest (or pre-test probability). How physicians use this information is not well known. OBJECTIVE: To assess whether physicians correctly estimate post-test probability according to various levels of prevalence and explore this skill across respondent groups. DESIGN: Randomized trial. PARTICIPANTS: Population-based sample of 1,361 physicians of all clinical specialties. INTERVENTION: We described a scenario of a highly accurate screening test (sensitivity 99% and specificity 99%) in which we randomly manipulated the prevalence of the disease (1%, 2%, 10%, 25%, 95%, or no information). MAIN MEASURES: We asked physicians to estimate the probability of disease following a positive test (categorized as 99.9%). Each answer was correct for a different version of the scenario, and no answer was possible in the "no information” scenario. We estimated the proportion of physicians proficient in assessing post-test probability as the proportion of correct answers beyond the distribution of answers attributable to guessing. KEY RESULTS: Most respondents in each of the six groups (67%-82%) selected a post-test probability of 95-99.9%, regardless of the prevalence of disease and even when no information on prevalence was provided. This answer was correct only for a prevalence of 25%. We estimated that 9.1% (95% CI 6.0-14.0) of respondents knew how to assess correctly the post-test probability. This proportion did not vary with clinical experience or practice setting. CONCLUSIONS: Most physicians do not take into account the prevalence of disease when interpreting a positive test result. This may cause unnecessary testing and diagnostic error

Values and preferences of men for undergoing prostate-specific antigen screening for prostate cancer: a systematic review

To investigate men's values and preferences regarding prostate-specific antigen (PSA)-based screening for prostate cancer. Systematic review. We searched MEDLINE, EMBASE, PsycINFO and grey literature up to 2 September 2017. Primary studies of men's values and preferences regarding the benefits and harms of PSA screening. Two independent reviewers extracted data and assessed risk of bias with a modified version of a risk of bias tool for values and preferences studies, the International Patient Decision Aid Standards instrument V.3 and the Cochrane Collaboration risk of bias tool. We identified 4172 unique citations, of which 11 studies proved eligible. Five studies investigated PSA screening using a direct choice study design, whereas six used decisions aids displaying patient-important outcomes. The direct choice studies used different methodologies and varied considerably in the reporting of outcomes. Two studies suggested that men were willing to forego screening with a small benefit in prostate cancer mortality if it would decrease the likelihood of unnecessary treatment or biopsies. In contrast, one study reported that men were willing to accept a substantial overdiagnosis to reduce their risk of prostate cancer mortality. Among the six studies involving decision aids, willingness to undergo screening varied substantially from 37% when displaying a hypothetical reduction in mortality of 10 per 1000 men, to 44% when displaying a reduction in mortality of 7 per 1000. We found no studies that specifically investigated whether values and preferences differed among men with family history, of African descent or with lower socioeconomic levels. The variability of men's values and preferences reflect that the decision to screen is highly preference sensitive. Our review highlights the need for shared decision making in men considering prostate cancer screening

Self-rated health: analysis of distances and transitions between response options

Purpose: We explored health differences between population groups who describe their health as excellent, very good, good, fair, or poor. Methods: We used data from a population-based survey which included self-rated health (SRH) and three global measures of health: the SF36 general health score (computed from the 4 items other than SRH), the EQ-5D health utility, and a visual analogue health thermometer. We compared health characteristics of respondents across the five health ratings. Results: Survey respondents (N=1.844, 49.2% response) rated their health as excellent (12.2%), very good (39.1%), good (41.9%), fair (6.0%), or poor (0.9%). The means of global health assessments were not equidistant across these five groups, for example, means of the health thermometer were 95.8 (SRH excellent), 88.8 (SRH very good), 76.6 (SRH good), 49.7 (SRH fair), and 33.5 (SRH poor, p<0.001). Recoding the SRH to reflect these mean values substantially improved the variance explained by the SRH, for example, the linear r 2 increased from 0.50 to 0.56 for the health thermometer if the SRH was coded as poor=1, fair=2, good=3.7, very good=4.5, and excellent=5. Furthermore, transitions between response options were not explained by the same health-related characteristics of the respondents. Conclusions: The adjectival SRH is not an evenly spaced interval scale. However, it can be turned into an interval variable if the ratings are recoded in proportion to the underlying construct of health. Possible improvements include the addition of a rating option between good and fair or the use of a numerical scale instead of the classic adjectival scal

Self-rated health: analysis of distances and transitions between response options

Purpose: We explored health differences between population groups who describe their health as excellent, very good, good, fair, or poor. Methods: We used data from a population-based survey which included self-rated health (SRH) and three global measures of health: the SF36 general health score (computed from the 4 items other than SRH), the EQ-5D health utility, and a visual analogue health thermometer. We compared health characteristics of respondents across the five health ratings. Results: Survey respondents (N=1.844, 49.2% response) rated their health as excellent (12.2%), very good (39.1%), good (41.9%), fair (6.0%), or poor (0.9%). The means of global health assessments were not equidistant across these five groups, for example, means of the health thermometer were 95.8 (SRH excellent), 88.8 (SRH very good), 76.6 (SRH good), 49.7 (SRH fair), and 33.5 (SRH poor, p<0.001). Recoding the SRH to reflect these mean values substantially improved the variance explained by the SRH, for example, the linear r 2 increased from 0.50 to 0.56 for the health thermometer if the SRH was coded as poor=1, fair=2, good=3.7, very good=4.5, and excellent=5. Furthermore, transitions between response options were not explained by the same health-related characteristics of the respondents. Conclusions: The adjectival SRH is not an evenly spaced interval scale. However, it can be turned into an interval variable if the ratings are recoded in proportion to the underlying construct of health. Possible improvements include the addition of a rating option between good and fair or the use of a numerical scale instead of the classic adjectival scal

Decision aids linked to evidence summaries and clinical practice guidelines : results from user-testing in clinical encounters

Acknowledgements We thank Frankie Achille (interaction designer/developer), Rob Fracisco (designer/developer), and Deno Vichas and Chris Degiere (developers) for their contributions in development of the online authoring and publication platform (www.magicevidence.org). Funding AFH was fnancially supported by a PhD fellowship from Innlandet Hospital Trust and have received innovation grants from South-Eastern Norway Regional Health Authority. TA was fnancially supported by a fellowship for prospective researchers Grant No P3SMP3-155290/1 from the Swiss National Science Foundation. The funding body had no role in design of the study, collection, analysis, and interpretation of data or in writing the manuscript.Peer reviewedPublisher PD

Development of a patient-centred tool for use in total hip arthroplasty

Background: The aim of this project was to develop a tool using the experience of previous patients to inform patient-centred clinical decision-making in the context of total hip arthroplasty (THA). We sought out the patients’ views on what is important for them, leveraging registry data, and providing outcome information that is perceived as relevant, understandable, adapted to a specific patient’s profile, and readily available. Methods: We created the information tool “Patients like me” in four steps. (1) The knowledge basis was the systematically collected detailed exposure and outcome information from the Geneva Arthroplasty Registry established 1996. (2) From the registry we randomly selected 275 patients about to undergo or having already undergone THA and asked them via interviews and a survey which benefits and harms associated with the operation and daily life with the prosthesis they perceived as most important. (3) The identified relevant data (39 predictor candidates, 15 outcomes) were evaluated using Conditional Inference Trees analysis to construct a classification algorithm for each of the 15 outcomes at three different time points/periods. Internal validity of the results was tested using bootstrapping. (4) The tool was designed by and pre-tested with patients over several iterations. Results: Data from 6836 primary elective THAs operated between 1996 and 2019 were included. The trajectories for the 15 outcomes from the domains pain relief, activity improvement, complication (infection, dislocation, peri-prosthetic fracture) and what to expect in the future (revision surgery, need for contralateral hip replacement) over up to 20 years after surgery were presented for all patients and for specific patient profiles. The tool was adapted to various purposes including individual use, group sessions, patient-clinician interaction and surgeon information to complement the preoperative planning. The pre-test patients’ feedback to the tool was unanimously positive. They considered it interesting, clear, complete, and complementary to other information received. Conclusion: The tool based on a survey of patients’ perceived concerns and interests and the corresponding long-term data from a large institutional registry makes past patients’ experience accessible, understandable, and visible for today’s patients and their clinicians. It is a comprehensive illustration of trajectories of relevant outcomes from previous “Patients like me”. This principle and methodology can be applied in other medical fields