Abstract
Introduction
Patients with clinically localized prostate cancer are typically eligible for 3 types of treatment: surveillance (either active surveillance or watchful waiting), radiation therapy, and prostatectomy. Side effects of prostatectomy and radiation can include erectile, bladder, and bowel dysfunction, whereas surveillance may require follow-up testing and may cause anxiety about living with cancer.1,2 The tradeoffs between potential benefits and side effects make this a preference-sensitive decision. A recent decision analysis of patients with clinically localized prostate cancer concluded that for 65-year-old men in average health, surgery resulted in 0.3 additional years of life expectancy at the expense of 1.6 additional years of impotence or incontinence, a net difference of 0.05 fewer quality adjusted life-years. Increased age and poorer health status favored surveillance. 3
Patient decision aids (DAs) that describe treatment options and the critical risk–benefit tradeoffs in early-stage prostate cancer have been available since 1998.4,5,6 Based on their effectiveness in preparing patients for decision making, DAs have been commonly implemented as stand-alone interventions prior to the decision-making encounter. However, despite growing support for shared decision making in practice guidelines and continual tool development, the extent to which the actual clinical encounters achieve informed patient participation is poorly understood.7,8
Few studies have directly assessed patient–clinician communication to measure shared decision making. Previous studies of decisions made in conjunction with a DA use patient recall 9 or direct observation of decision making when a physician actively used a DA in the encounter.10–14 To our knowledge, only two previous studies have provided direct observation of physicians and decision-aid-informed patients making treatment decisions.12,14 This is the first such study in urology. We examined decision making in urology outpatient clinics at 4 geographically dispersed Veterans Affairs (VA) medical sites at the time of the discussion of newly diagnosed, clinically localized prostate cancer. We analyzed transcripts of audio-recorded office visits to evaluate the completeness of informed decision-making physician behavior.
Methods
Data Set
Audio recordings were collected in a multisite clinical trial comparing two prostate cancer DAs. 15 The trial was designed to test the impact of a plain-language and a high-literacy DA on patient preferences.16,17 Because the present study’s focus was on physician behavior, the encounters were analyzed as 1 group. Participants were recruited from 4 VA Health Systems (Ann Arbor, Michigan; Durham, North Carolina; Pittsburgh, Pennsylvania; and San Francisco, California). Recruitment occurred between September 2008 and May 2012.
Patients with clinically localized cancer (Gleason score 6 or 7, prostate-specific antigen [PSA] <20 ng/ml) were asked to participate in an audio recording of the first postbiopsy encounter at which diagnosis and treatment options were discussed. A research associate set up an audio recorder in the exam room at the start of each visit and then waited outside the exam room until the visit was complete. Spoken HIPAA identifiers (e.g., names, dates, and locations; such information is kept private by law under the U.S. Health Insurance Portability and Accountability Act of 1996 [HIPAA]) were deleted from the recordings before recordings were transcribed. Of 256 transcripts recorded and transcribed, 252 transcripts were available for inclusion. Two transcripts were excluded because of recorder malfunction; 2 other encounters were only to obtain a referral to radiation oncology. Time in the encounter was measured directly from the audio recordings. Time when the physician was out of the room was subtracted from total time to yield the net time the physician was in the room with the patient. Physician participants were urology residents and attending physicians. All provided demographic data at the time of recruitment. The study was approved by the VA Institutional Review Boards at each participating, site and written informed consent was obtained from each patient and physician participant. The funding agencies had no role in conduct or reporting of the study.
Analytic Approach
Coding systems for analyzing patient–physician encounters to evaluate shared decision making have been developed previously. We selected the Informed Decision Making (IDM) coding system for this investigation. The Braddock system describes physician behavior across key elements of IDM and shared decision making.18-20 The system and its measurement properties have been described previously. 20 The 9 IDM elements measure the extent to which the physician discusses 1) the patient’s role in decision making; 2) the treatment’s impact on daily life; 3) the nature of the decision or clinical problem; 4) treatment options; 5) the benefits and risks of options, including the severity and probability of each; 6) treatment uncertainties; 7) assessment of the patient’s understanding; 8) the patient’s desire to receive input from others; and 9) elicitation and exploration of treatment preference. These reflect patient decision making (elements 1 and 2), information disclosure for consent (elements 3, 4, 5, and 6), and physicians engaging patients in preference clarification (elements 7, 8, and 9).
The IDM criteria represent a synthesis of the bioethics literature and professional consensus, validated and expanded by patient input. 21 The model reflects the concepts of informed consent and capacity for medical decision making. It also contains the core concepts previously identified among 15 models of shared decision making. 22 IDM is also consistent with the set of essential and ideal shared decision-making criteria developed by Makoul and Clayman from a comprehensive review of the shared decision-making literature, with 4 exceptions. 23 In addition to the IDM essential elements, Makoul and Clayman included discussion of patient self-efficacy, discussion of physician knowledge and recommendation, execution or explicit deferral of the decision, and arrangement of follow-up. In our study, the primary goal was discussion of biopsy results and treatment options. Thus, the IDM system was well suited to the present study. We will use the term IDM to refer to scores on the Braddock scale, but we will use shared decision making to describe the field.
Transcripts were analyzed using the IDM scoring method, with each element scored as 0 (absent), 1 (basic: a partial or brief mention, mostly a one-way discussion rather than dialogue), or 2 (complete: an explicit clear discussion of the element and a two-way discussion). The IDM score is a sum of the 9 elements. 21 We defined core IDM elements that are necessary for adequate shared decision making to be a 2 on balanced presentation of options, their benefits and risks, and patients’ preferences (elements 4, 5, and 9). Note that the difference between a score of 1 and 2 on patient preferences (see Table 1, Element 9) is that a score of 2 indicates that the clinician “acknowledges by repeating patient’s treatment preference and asking for confirmation, AND after arriving at agreed on decision, discusses next steps to implement the stated preference.” A score of 1 is limited to eliciting or acknowledging the patient’s preference.
IDM Definitions
Coding was completed in Dedoose, 24 identifying the key utterances that supported presence and level of completeness (0–2). Dedoose is a Rich Internet Application (RIA) that allows data analysis and handling from mixed-methods research. Tests of similarity and difference were performed with SPSS 25 and Excel. 26 The initial codebook was tested in 3 pilot samples coded by all members of the coding team. Coding definitions in Table 1 were developed by 6 coders and 3 expert team members (CB, VK, and DRR) using a training set of 6 transcripts. A test set of 10 transcripts was coded independently by all 6 coders with high reliability (Cronbach’s α = .93). Paired coding with consensus was used for the remaining transcripts. Physician behavior was the unit of analysis.
To examine the relationship of IDM score to treatment received, we used latent variable models for ordinal data (using the diagonally weighted least-squares estimation procedure provided by R’s lavaan package 27 ). The relationship to receipt of active treatment was assessed by a probit regression of the latent IDM variable on treatment decision, which was a binary variable that equaled 1 if the decision was “surveillance” and 0 otherwise. Results are based on individual IDM items (as opposed to a single scale score) and provide evidence about whether IDM is related to active treatment. Treatment received was abstracted from the medical record.
Results
The mean age of the patient sample was 63.3 years (SD = 5.9); 33% were nonwhite, and 40% had high school education or less. The mean age of 45 treating physicians was 33 years (SD = 7.2); 20% were female, and 34% were nonwhite. On average, each physician was recorded in 6 clinical encounters (SD = 4.3) and was 10 years post graduation.
IDM scores ranged from 0 to 15 out of a possible 18, showing substantial variability in informed decision making (see Figure 1). Mean IDM scores showed modest quality (7.6±2.4), with no differences in IDM scores by physician gender. Years since medical school graduation were positively but weakly correlated with IDM score (r = 0.10). Which DA patients received was unrelated to IDM score.

Distribution of mean informed decision-making (IDM) scores by physician (n = 45).
Disclosure and Engagement Elements
Consent-related disclosure elements (nature of the decision, alternatives, risks, and uncertainty) were all present, at least at the partial level, in greater than 75% of encounters. Treatment options were presented in 95%, but they were only at the partial level in 36% of the total sample. Table 2 provides examples of partial and complete descriptions of key elements.
Examples of Partial and Complete IDM Elements
Because of the importance of treatment options in this decision, we further investigated the option discussions coded as partial or absent. Twelve cases were coded as absent because the physician recommended only one option out of the 3 possible ones, although sometimes with reference to the existence of others. Among the single-option discussions, there were 2 types of comments. Either the patient came in with his mind made up (the physician checked the patient’s understanding of the procedure elected), or the physician recommended what he or she thought best based on risk factors. Among those coded as a partial set of options, one patient had independently elected to pursue prostatectomy. In the other 90 out of the 91 partial discussions, the physicians listed all 3 options, but then removed surveillance from consideration. For this group of encounters, the IDM score was 6.76 (±1.85), which is lower than for the group as a whole (t = −3.02, p = 0.001). Seventy-seven of the 90 instances of removing surveillance from consideration (86%) occurred in men with intermediate-risk (Gleason 7) disease, and the other 13 occurred in men with low-risk cancers. For these men with low-risk cancer (Gleason 6), most statements were nonspecific comments indicating that although surveillance was an option, the physician felt it was not appropriate for the patient, sometimes because of young age or good health. Statements in intermediate-risk cases were similar but usually added a statement that the patient’s risk level made surveillance inappropriate. Table 3 provides examples of physician statements that removed surveillance from consideration.
Removing Surveillance from Consideration
Patient decision and engagement elements occurred less frequently than disclosure, and usually at the partial level. Half of encounters included discussion of the impact of prostate cancer treatment on daily life or explicit discussion of the patient’s role in the decision. The exception was eliciting the patient’s treatment preference, which was included, at least at the partial level, in 73% of encounters.
Figure 2 shows the distribution of scores by IDM element and by level of completeness. Level 2 indicates exemplary discussions. Complete discussion of treatment options occurred in 59%, benefits and risks in 21%, and preferences in 30%. All three core shared decision-making elements were scored as complete in 7.5% of transcripts. High-quality shared decision making occurred in 19 transcripts, representing 13 physicians out of 45 (29%).

Level of informing by IDM element.
Time in encounters was highly variable, and largely unrelated to IDM scores. The range of encounter times was 3–59 min., with a mean and SD of 22±9. Correlation between encounter time and IDM scores was 0.237 (p = .01). This modest correlation suggests that more time in the encounter did not account for much of the variance in IDM scores.
Relationship to Treatment Received
Forty-seven percent of men received surveillance, 32% received surgery, 20% received radiation, and 3% received hormone treatment. Exploratory probit regression analysis, using the latent IDM variable to predict surveillance compared with all active treatments, showed that IDM score was significantly correlated to surveillance (β = 1.1, p = .04). The model estimates imply that an encounter IDM score 1 standard deviation higher than the mean had 7% greater odds of the patient receiving surveillance, as compared to an encounter with an IDM score at the mean. Inspection of individual site data suggests the effect differs across sites. However, we cannot make accurate statistical assessments by site, given the small sample size at 2 sites.
Discussion
In this data set, we found that physicians usually informed patients of options, risks, and benefits but infrequently engaged them in core shared decision-making processes. Despite patients having received DAs, physicians rarely provided an opportunity for preference-driven decision making. The general approach to treatment options was to offer at least surgery and radiation options to patients. In 59% of encounters, physicians thoroughly discussed surgery, radiation, and surveillance as options. From the standpoint of shared decision making, however, the communication was incomplete. In only 7.5% of encounters were the core shared decision-making elements (options, risks and benefits, and preferences) all discussed at the complete level. This does, however, represent at least one high-quality shared decision-making encounter among 29% of physicians in our sample. In 70% of encounters, patient preferences did not guide treatment plans (less than a score of 2 on preferences). The problem of lack of attention to preferences is amplified by the constrained set of choices offered. In 36% of encounters, physicians indicated that surveillance was not an option for the patient. The reasons provided were frequently that patients’ younger age and good health make it important to actively treat. In single-option encounters, the rationale was similar. The exception was when the patient came in with his mind made up about treatment. Even in this case, discussing preferences is important because it provides an opportunity to check not only that the patient understands the procedure but also that he is choosing the treatment that is most consistent with his outcome goals and expectations. We suggest that the predominant practice of tailoring to risk factors, but not patient preferences and treatment goals, diminishes the decision quality and potentially quality of life.
The impact of DAs on treatment decisions in prior studies is highly variable. Two meta-analyses have shown a null net effect in comparisons between DA intervention and control.4,28 The underlying studies cited in Lin et al. include some showing a decrease in surgery, some showing a decrease in patients choosing the recommended treatment, and some showing no difference. Our data suggest that DAs alone may contribute little to achieving preference-driven decision making. Although information has been shown to help patients formulate outcome preferences, explicit physician discussion of all the relevant elements appears necessary. The association in our study of IDM scores with surveillance suggests more complete informed decision making in patients who ultimately received surveillance. This is interesting in view of the concern, throughout several decades, about potential overtreatment of localized prostate cancer. A recent study suggests that patient DAs and publicly reporting individual practice patterns at the provider level could decrease the overtreatment of low-risk prostate cancer. 29 However, this may be overly optimistic unless full shared decision making becomes routine practice.
The ongoing professional debate about how aggressively to treat low- and intermediate-risk prostate cancers may provide context for understanding the variability in discussion of options found in our data. American Urological Association (AUA) guidelines indicate that active surveillance, interstitial prostate brachytherapy, external beam radiotherapy, and radical prostatectomy are appropriate monotherapy treatment options for the patient with low-risk localized prostate cancer and that study outcomes data do not provide clear-cut evidence for the superiority of any one treatment. The AUA standard states that “patient preferences and health conditions related to urinary, sexual, and bowel function should be considered in decision making.” 30 National Comprehensive Cancer Network (NCCN) guidelines are similar, with the exception that they recommend surveillance only in low-risk cancers (Gleason <6). 17 Both guidelines recommend avoiding active treatment in men with a <10-year life expectancy or poor health that would obviate any potential benefit of treatment. Both guidelines have patient versions that advise that not all prostate cancer patients require treatment, and recommend a thorough discussion with the physician to arrive at a decision.
Overall, IDM scores reported here represent more thorough informed decision-making discussions than those reported previously in the primary care literature.18,20 The 2011 report by Leader of IDM scores in prostate cancer screening was similar to our study in including a patient intervention. Their dichotomized mean IDM score was half the mean IDM score found in our study. This difference may be at least partially explained by the fact that primary care visits often cover multiple agendas, whereas the post-prostate biopsy visit in urology is clearly focused on treatment.
Our results should be considered in the context of several limitations. The data set is cross-sectional, only describing the first post-biopsy visit. This encounter was chosen because it is when shared decision making should begin. However, the full trajectory of treatment decision making may extend from the biopsy or pre-biopsy appointment through follow-up discussion following radiation oncology or second-opinion referrals. This means the IDM scores might be higher if all patient–physician contacts were analyzed. Although it would be ideal to capture the whole trajectory, it was cost prohibitive due to the complexity of logistics and data collection. At the same time, IDM scores in our study may be inflated over usual care, because physicians knew they were being audio-recorded in a DA study. In terms of generalizability, this study was completed in VA settings where physicians were salaried, arguably removing physician financial incentives in patient decisions. Nambudiri et al. 31 found large variability among VA sites, and higher rates of no intervention in the VA compared with Medicare fee-for-service. Generalizability is enhanced by the geographic dispersion of sites but limited to training settings. Despite these limitations, generalizability may be quite high in terms of surveillance rates, because rates are similar to the 49% found in a prospective cohort study in Michigan that collected extensive clinical data during a 23-month period. 32 We feel that our study identifies an important avenue for quality improvement in the post-prostate-biopsy physician–patient encounter. The outstanding performance of a minority of physicians in our study shows the feasibility of shared decision making in practice. DAs improve knowledge and prepare patients to articulate their preferences and goals to engage in treatment decision making. However, if the physician does not offer the opportunity for discussion and shared decision making, it is still unlikely to happen. 33
Conclusions
Overall, the quality of physician communication with patients about clinically localized prostate cancer diagnosis and treatment was modest by the criteria of informed decision making. At the same time, high-quality shared decision making shown among a substantial minority of physicians suggests that shared decision making is feasible in routine practice. The modest correlation between encounter length and IDM score suggests that shared decision making can be conducted with minimal additional time. Our study identifies specific areas for improved physician performance. In particular, improved patient preference discussions may provide a critical path beyond a simple description of treatment options and their consequences. Universal guideline support for decision making tailored to patient preferences may encourage full implementation of patient-centered approaches to preference-sensitive decisions in clinical practice.
Footnotes
Acknowledgements
We wish to thank John T. Wei, MD, for critical feedback on the manuscript; and Clarence H Braddock III, MD, MPH, for expert consultation in adapting IDM coding to prostate cancer decisions. We wish to thank Tracy DeKoekkoek, BS; Benjamin Mast, BA; Emily Ellsworth; and Adetola Masha, BA, for assistance in transcript coding for which they received compensation. We also thank volunteers Lisa Mei for data-cleaning assistance and Karen Kelly-Blake, PhD, for feedback at all stages as well as coding assistance. A detailed coding description and further examples of coded content are available from the corresponding author on request.
Presented in part at the annual meeting of the Society for Medical Decision Making, October 19–23, 2013, Baltimore, MD.
Note: Financial support for this study was provided in part by a grant to Dr. Holmes-Rovner from the Agency for Healthcare Research and Quality (R03 HS021764) and by an IIR (Investigator-Initiated Research) Merit Award from the U.S. Department of Veterans Affairs (IIR 05-283) to Dr. Fagerlin. The public domain decision aids used in the study were provided free of charge by the producers of the tools (Michigan Cancer Consortium [MCC] provided the plain-language decision aid, and the American Cancer Society provided the higher-literacy decision aid). The funding agreement ensured the authors’ independence in designing the study, interpreting the data, writing, and publishing the report.
