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Abstract

Summary:
Introduction: Understanding patient preferences facilitates doctor-patient communication and enhances patient-centered care. Urethral stricture, which has no definitive treatment guidelines favoring endoscopic incision or open reconstruction, exemplifies a condition in which consideration of patient preference is especially important in making a treatment choice. There are no previous studies that assess factors that patients value when choosing a treatment option.
Methods: We employ choice-based conjoint analysis to assess patient preferences for treatment of urethral stricture disease. Male patients undergoing treatment or followup examination were recruited through a University Medical Practice. We included 169 patients in the analysis. Six attributes of both risk and benefit were examined: treatment type, success rate, number of future procedures, post-treatment catheter duration, recovery time, and copayment amount. Results: The treatment success rate was, by far, the most important attribute. Relative to a 25% success rate (OR = 1) an 85% success rate (OR = 26.72, p<.01) increased patient preference by approximately 27 times. Furthermore, patients are willing to pay a $10,000 copayment to double the success rate from 25% to 50%. Patients demonstrated a strong aversion to time with a urinary catheter. Catheter duration for 1 week or less (OR = .67, p<.01) reduced patient preference by about 1.5 times when compared to requiring no catheter. We also found that patients place low importance on both how invasive the treatment seems and low copayment amounts but are willing to pay $10,000 copayment for an open reconstruction surgery compared with an endoscopic incision procedure. Conclusion: The findings highlight the importance of shared and detailed physician/patient discussions of all the risk and benefits of each treatment choice and suggest that conjoint analysis may be helpful as a decision aid to guide discussions with individual patients deciding on a treatment.
Keywords: Urethral stricture disease, open reconstruction, urethroplasty, endoscopic incision, direct vision internal urethrotomy (DVIU), choice based conjoint analysis, patient-centered care, patient preference, United States.
Citation: Wilson L, Lin TK, Hampson L, Oh A, Ting J, Gaither TW, Allen I, Breyer B. Use of conjoint analysis to determine patient preferences for surgical treatment of urethral stricture disease. J Participat Med. 2017 Jan 14; 9:e1.
Published: January 14, 2017.
Competing Interests: Lindsay Hampson has received funding from a California Urology Foundation and University of California CTSI Research Funding Grant; Benjamin Breyer has received funding from the National Institute of Diabetes and Digestive and Kidney Diseases (K12DK083021).

Introduction

In 2001, the Institute of Medicine Report[1] introduced patient-centered care as one of the fundamental approaches to improving the quality of health care in the US. [2] The Patient Protection and Affordable Care Act (ACA) has reinforced this patient-centeredness with its policies of outcome-based payments, emphasis on patient satisfaction, and focus on prevention. [3] To encourage patient participation and facilitate patient-centered care, it is important for clinicians to consider patient preferences. Conjoint analysis is one of the most comprehensive ways to analyze patients’ decision-making process. [4] This method advances the understanding of patient preferences.[5][6][7][8][9][10][11][12][13] It has also been used by the United States Food and Drug Administration to collect evidence and incorporate patient preference into regulatory decision making. [14] In this study, we used a choice-based conjoint analysis (CBC) methodology to examine preferences for treatment characteristics of patients with urethral stricture disease.

Male urethral stricture is common with a prevalence rate of 0.6% in susceptible populations. [15] Ten out of 100,000 men in their youth, 20 out of 100,000 men by the age of 55 years, and 100 out of 100,000 men over the age of 65 years are likely to experience urethral stricture, which can severely influence quality of life. [16] Without adequate treatment, it can result in significant complications such as infection, bladder stones, and renal failure. In 2000, the cost of the disease was approximately $200 million, excluding medication costs. [15]

There are no definitive guidelines for treating urethral stricture disease. [16] Endoscopic incision (also called direct visual internal urethrotomy (DVIU)) and open reconstruction (also called urethroplasty) are the two most common treatments. They differ by procedure invasiveness, costs, side effects, surgical recovery, and long-term outcomes. [17] When deciding on a treatment, urologists consider patients’ treatment history, the length and location of the stricture, and the etiology of the stricture.[18][19] Many patients are potential candidates for either open reconstruction or endoscopic incision. Therefore, patient participation and preference are an important determinant of selected treatment and its associated risks and benefits. Patients engaged in shared decision making are found to have greater knowledge and satisfaction in care. [20]

Thus far, there have been no studies assessing patient preference when choosing a urethral stricture treatment option. This allows urologists to provide a more personalized approach, rather than a “one size fits all” recommendation. The aim of this study is to compare patient preferences for the two main treatments for urethral stricture disease: endoscopic incision and open reconstruction.

Material and Methods

Study Sample

Male patients undergoing treatment or follow-up examination for urethral stricture disease were recruited from a single surgeon’s reconstructive clinic between July 22, 2014 and November 13, 2014. These patients were invited to participate in an online choice-based conjoint analysis exercise which was based on input from urologists and patient interviews. The sample goal was 250 patients. Two hundred and three patients agreed to participate and 183 patients completed the online survey. Fourteen patients were excluded from the final analysis as they did not answer the two questions designed to demonstrate understanding of the survey, resulting in 169 patients in the final analysis. Patients completing the survey were entered into a raffle to receive an iPad as an incentive for participation. The University Committee on Human Research approved the study.

Development of CBC Preferences

The CBC survey was developed using web-based Sawtooth Software[21][22] and followed the good practice guideline. [23] A random, full profile balanced overlap CBC design was adopted to maximize obtainable information for each response. The CBC survey (Appendix A) presented participants with a series of eighteen different pairs of treatment scenarios and asked them to choose the preferred treatment of each pair (Figure 1). Two fixed scenarios were designed; one which compared all “desirable” with all “not desirable” attributes to determine who did not understand the conjoint exercise. The other one was a realistic scenario designed to assess which treatment patients would choose between all endoscopic incision attributes and all open reconstruction attributes. Patients who illogically and incorrectly answered the fixed choice pair purposely skewed towards one choice based on rational and reasonable decision-making were removed. Before completing the CBC, participants reviewed the educational materials describing the attributes of the two treatment options. Participants also received a reference guide (Appendix B) of definitions used during the CBC.

Choice-based conjoint analysis is a method to evaluate patient preference in health care decision making. [6][19][21] This method systematically elicits risk-benefit tradeoffs and quantifies the relative preferences and risk acceptance for attributes of medical interventions. [24][25] Choice-based conjoint analysis is based on the theory that patients will choose the combination of attributes that maximizes their utility. A patient choice is associated with the total utility, which is a summation of the utilities of each attribute. As such, patient choices and preference for attributes chosen during CBC surveys implicitly reveal the relative preferences for specific characteristics of a medical intervention. [6] Our CBC survey was constructed to mimic the decision making process of patients with urethral stricture disease choosing a treatment procedure.

Figure 1: Case-based conjoint analysis scenarios.

Wilson et al Figure 1

Administration of CBC

In the computer based CBC survey, patients indicated their preferences by choosing between two hypothetical profiles, which consist of randomly selected levels within each fixed set of the six attributes. The levels of attributes within each hypothetical choice pair were created employing a balanced overlap method, which purposely forgoes some efficiency to allow for some overlap in choice tasks. The overlap presents an advantage as it improves the efficiency for detection of first-level interaction effects. [6] The overlap is also advantageous in that it accounts for respondents who simplify the decision-making task always to select based on one attribute; the overlap forces these respondents to make a choice using other attributes. [26]

Determination of Attributes and Levels

Clinician surgeons identified the attributes of both risk and benefit that were the most important to patients with urethral stricture disease (Appendix C). These factors were presented to a series of patients who had urethral stricture disease and had undergone treatment, to determine what attributes were the most important to this class of patients. The process led to a revision and resulted in the final six attributes, which include three risk attributes: 1) extent of procedure (more or less invasive), 2) number of possible future procedures, 3) post-treatment catheter duration; and two benefit attributes: 1) long-term success rate, 2) time to recovery; and a cost attribute, the copayment amount. The levels under each attribute were selected to include realistic rates and amounts as well as to allow for assessment above and below the actual realistic levels to check for linearity. We also kept both the number of attributes to six and the number of levels within each attribute to three or four in order to increase validity by making the choice tasks easier for the patients.

Description of Instrument Content

Each patient was presented with choices across the same six attributes, but different attribute levels and included 1) nature of procedure (open reconstruction, ie urethroplasty; and endoscopic incision, ie direct visual internal urethrotomy); 2) success rate (25%, 50%, 85%); 3) number of possible future repeat procedures (zero, one, five, and 10); 4) post-treatment catheter duration (no catheter needed, catheter needed for 1 week or less, and catheter needed for 3 weeks); 5) time to recovery (immediate, 2 weeks, 6 weeks, and 12 weeks); and 6) the copayment amount ($0, $100, $1,000, and $10,000). The levels and attributes were chosen to reflect the characteristics of open reconstruction and endoscopic incision procedures.

Data Analysis

A mixed-effects logistic regression model was used to analyze the CBC preferences. Mixed-effects logistic regression is logistic regression containing both fixed effects and random effects. [27] Mixed-effects models allow the slope of variables in the model to be random effects and calculated for subgroups or individuals before the slopes of variables for the population are estimated. This characteristic controls the within-group differences prior to estimating the between group effects. For this model, patient attributes were considered random effects. The model was chosen to account for the inter- and intraperson variability due to each patient answering multiple choice pairs. [6] A logistic regression was employed due to the dichotomous nature of the decision tasks. Both the beta coefficient from the mixed effects logistic regression reflecting the estimated utility of each level of each attribute and also the odds ratio by calculating the exponential of the beta coefficients were presented. The odds ratio (OR), represents the relative increased and decreased likelihood of a patient’s choice for a level within an attribute. The baseline level OR was a value of 1. ORs greater than 1 indicate a positive preference and an increased likelihood of choice by a patient over the reference case, while ORs lower than 1 indicate a negative preference and a decreased likelihood of choice over the reference case. [6] The relative preferences for the levels within the six attributes are presented in term of beta coefficients and odds ratio (Table 2 Model 1 and Figure 3).

Results

Patient Characteristics

Table 1 contains information on patient demographics and past treatments. The mean age is 59.2 years old. The majority are white (72.2%) with 9.5% Asians, 5.9% African-Americans, and 12.5% other or unknown. Most patients have college or higher education, though 32.5% are educated at high school or less and 10.7% are technical school graduates. Most (45.6%) of the patients are employed and have incomes greater than $100,000, although, 29.0% of the patients in the sample have income less than $50,000 annually. Lastly, most patients had some type of previous urethral procedure with 43.8% having has a previous urethral dilation, 42.6% an internal urethrotomy, and 50.9% a urethroplasty.

Table 1: Participant demographic and treatment data. [28]
Wilson et al Table 1

Patient Preferences

In order to evaluate patients’ preference for attributes, we calculated the relative attribute preferences. The coefficients for the levels within each attribute are not considered comparable across attributes; so we obtained the mean relative importance of each attribute by calculating the difference between the most important level and the reference level for each attribute and normalized to a value of ten, making them comparable despite the different attribute ranges. Figure 2 shows that among the six attributes studied, the treatment success rate was by far the most important attribute. The next most important attributes were copayment, and number of future procedures that would be needed, followed by catheter duration. The attributes of least importance were recovery time and procedure type. Patients’ preference for no future procedure and patients’ placement of low importance for recovery time indicates that patients would favor open reconstruction, which requires no future procedures but have a longer recovery time than endoscopic incision. Relative attribute preferences thus provide a direct comparison of what patients weigh the most, which helps initiate physician-patient discussion.

Figure 2: Relative attribute preferences (normalized to a value of 10).
Wilson et al Figure 2

To further understand how patient preference varies across levels within each attribute we evaluated OR of each level. Patient preferences are statistically significant in the following attributes: success rate, future procedure, catheter duration, procedure type, and most of the levels within the copayment attribute. Relative to the lowest (25%) success rate (OR = 1) an 85% success rate (OR = 26.72, p<.01) increased patient preference by approximately 27 times, while anticipating a 50% success rate (OR=4.91, p<.01) increased patient preference by approximately 5 times. Patients clearly show that an 85% success rate is most strongly preferred and is also their most heavily preferred attribute. Additionally, of the risk attributes, patients demonstrated the strongest aversion to time with a urinary catheter, which is commonly required after both endoscopic incision (typically for less than 1 week) and open reconstruction (for 3 weeks on average). Catheter duration for 1 week or less (OR = .665, p<.01) reduced patient preference by about 1.5 times when compared to requiring no catheter. The decrease in patient preference between a 1 week and 3 week catheter duration, however, was less strong but patients showed a strong preference for avoiding catheterization. Patients clearly showed decreasing preference as the number of procedures increased, but a stronger negative preference for going from one to five future procedures than going from zero to one future procedure, and then less negative preference going from five to 10 future procedures (Figure 3). Patients disliked five future procedures (OR=.345, p<.01) more strongly than one (OR=.759, p<.01) and, of course, least prefer 10 (OR=.245, p<.01). This pattern of non-linearity in preference for future procedure suggests that patients primarily prefer to avoid the first catheter procedure, but once it is required, they are more indifferent to the subsequent ones.                                                                                                                                  Figure 3: Preferences for levels within each attribute compared to a reference level.
Wilson et al Figure 3

The invasiveness of a procedure was one of the least important attributes of patient preference. Patients showed a positive preference for open reconstruction (OR=1.23, p<.01). Nevertheless, the difference in patient preference was not as large as when compared to other attributes, making the preference to avoid an invasive treatment least important to patients except for recovery time. This finding suggests that patients are willing to look past this general description of the invasiveness of the procedures to make their decisions based on a more comprehensive set of attributes. Related to this, the long-term outcome benefits were clearly more preferred than the type of procedures invasiveness as demonstrated by patients’ strong preference for 0 future procedure and high success rate. Copayment was included to reflect whether or not this would affect one’s choice of treatment procedure or its attributes. Patients’ negative preference for copayment amount was not statistically significant until the copayment amount reached $1,000. Relative to no copayment, a $1,000 copayment (OR=.699, p<.01) decreased patient preference by approximately 1.4 (1.0/.699) times, while $10,000 (OR =.228, p<.01) decreased patient preference by about 4.4 (1.0/.228) times. Patients did not have a statistically significant preference for time to recovery, which ranged from immediate to six weeks until recovery. Compared to the baseline of immediate recovery time, patients prefer 2 weeks recovery time (OR=1.043, p=.1), followed by 12 weeks (OR=.95, p=.09), then 6 weeks (OR= .87, p=.08), which is somewhat counterintuitive.                                            Table 2: Mixed effects logit model.
Wilson et al Table 2

Willingness to Pay


Our analysis demonstrates that patients were willing to make tradeoffs between benefits and risks related to a treatment decision as demonstrated by comparing their utility weights. The beta coefficients from the logistic regression (Table 2 Model 2) can be interpreted as preference or utility weights, which measure the effect of the attributes on utility when all other attributes are held constant. [27] A positive beta coefficient indicates that the attribute is associated with higher willingness to pay preference whereas negative coefficients are associated with lower willingness to pay type preference.

While the invasiveness of the procedure is not the most important attribute, we found that individuals are willing accept a $1,000 copayment (=-.36, p<.01) for an open reconstruction surgery (=.21, p<.01) rather than undergoing endoscopic incision. In addition, individuals are willing to pay $10,000 (=-1.48, p<.01) to double their success rate from 25% to 50% (=1.59, p<.01). In addition to willingness to pay, we also evaluated disutility tradeoffs. We find that undergoing 10 future procedures (=-1.41, p<.01) has a similar disutility as having the copayment of $10,000 (=-1.48, p<.01). Furthermore, having a catheter for 1 week or less (=-.41, p<.01) has a similar disutility as copayment of $1,000 (=-.36, p<.01). In summary, while the estimates reflecting patient preferences were generally consistent with the natural ordering of the levels within the attributes based on the expected risks and benefits, some of their attribute preferences were surprising. All levels for treatment type, success rate, future procedures, and catheter duration attributes were statistically significant. For the copayment attribute, we found that a low copayment value of $100 did not significantly impact preferences, but for very high copays ($10,000) patients had a strong negative preference. The treatment benefits were most important, avoiding the risks of treatment (catheterization, and time to recovery, and treatment invasiveness) were also weighted as important, but with consideration for gaining the overall long-term positive outcome. Patients demonstrated that they were willing to undergo and pay for an invasive procedure for the longer outcome success gained. This finding has implications for the patient-surgeon communications around explanations of treatment options in preparation for the best treatment choice for each patient.

Realistic Treatment Groups


To examine which treatment procedure has characteristics that patients prefer, we adjusted the baseline for each attribute to reflect realistic scenarios for the risks and benefits likely for each actual treatment choice; open reconstruction and the less invasive endoscopic incision treatment. Table 3 shows the results from using open reconstruction and its most likely associated characteristics as the baseline comparator; that is, 85% success rate, 0 future procedures, 3 weeks of catheter use, and 6 weeks recovery time as baseline. The results show that with the exception of catheter duration, patients prefer all the characteristics associated with the more invasive open reconstruction procedure. It is important to note that the decrease in patient preference between a 1 week and 3 week catheter duration, however, was less severe as compared with not needing catheter at all, clearly showing a strong preference for avoiding the need for a catheter at all. The data show that, overall, patients prefer the attributes associated with open reconstruction compared to endoscopic incision.

Looking at the beta coefficients in Table 3, endoscopic incision has a similar tradeoff in preference to the catheter duration of 1 week or less. That is, patients are willing to give up choosing endoscopic incision as a treatment if the catheter duration is 1 week or less. Similarly, the tradeoff between endoscopic incision and one future procedure is comparable. The results suggest that patients would trade the preference for treatment type of shorter catheter duration and less future procedures. The finding highlights that patients care less about the invasiveness of the treatment than they do about the outcome of the treatment.

Table 3: Mixed Effects Logit Baseline Model: Open Reconstruction Treatment as Baseline.
Wilson et al Table 3

Discussion

Our findings have two important implications. First, we show that patients place low importance on the type of treatment procedure itself or how invasive it is. Patients make their decisions based on weighing the risks and benefits of all of the other attributes of the treatment choices rather than just wanting to avoid an invasive procedure at any cost. For example, patients show they might be willing to trade their preference for treatment type for fewer future repeat procedures. This finding illustrates the importance for the physician and patient to discuss in detail the risk/benefit characteristics of each treatment type, rather than relying on just describing the nature and invasiveness of the treatment. It is crucial for physicians and other healthcare providers to communicate the accompanying risk and benefit characteristics of each procedure when assisting patients in medical decision making.

Second, our study highlights that the long-term success rate is the most important consideration for patients as shown by their willingness to pay $10,000 to double the success rate from 25% to 50%. As Figure 3 illustrates, the preference is not linear throughout the range of success rates. There is a more significant increase from 50% to 85% success rate than from 25% to 50% success rate, which indicates that patients are willing to pay the copayment of more than $10,000 to increase the success rate from 50% to 85%.

We also find that patients do not place high importance on the copayment amount until it is very high. We also find that patients are not overly concerned about recovery time for the procedure. This may be because our patient population was overrepresented by retired or unemployed individuals (55.5%). Patients have a strong aversion to requiring repeat procedures or having any catheter time post-procedure (primarily attributes associated with endoscopic surgery). This pattern suggests that patients are willing to bear current discomfort and financial payments to avoid prolonged discomfort as long as the overall outcome is better.

One of the potential limitations of our study is that, in order to obtain a large enough sample size, we included both patients who were considering treatment for the first time, and those that had already undergone treatment for urethral stricture. In our sample, 74 (43.8%) patients had urethral dilation, 72 (42.6%) patients had internal urethrotomy, and 86 (50.9%) patients had previous urethroplasty. Therefore, the results may not be comparable to a previously untreated population. Another possible limitation, as with all conjoint analyses, is how the different attributes were interpreted by each patient. For example, if patients had been informed about infections risks associated with catheter use, it may have affected their catheter time post-procedure. The attributes were explained to the patient prior to undergoing the survey, and they also had a description of the attributes in front of them as they were taking the survey. Therefore, we felt the patient had adequate opportunity to interpret the attributes as we defined them.

Conclusion

This study contributes to the understanding of patient decision-making and highlights the importance of shared and detailed physician/patient discussions of all the risk and benefits of each treatment choice, including costs, and shows a preference for open reconstruction. Utilizing conjoint analysis, a methodology for incorporating patient participation and patient preference, we demonstrate that patients with urethral stricture do not place importance on the treatment type description itself (invasive surgery or less invasive endoscopic surgery). Instead, patients highly value the expected outcome and characteristics involving prolonged discomfort (catheterization) and need for repeat procedures. We quantified and compared the importance of different risk and benefit attributes associated with treatments for urethral stricture disease and show that high success rate and absence of future procedures are most preferred by patients and these are more commonly associated with patient preference for an open reconstruction procedure. We suggest that this conjoint measure may be helpful as a decision aid, furthering the aim of the National Quality Forum[29] and providing the risk/benefit characteristics of each treatment type, to guide discussions with individual patients deciding on a treatment for strictures. We plan on a follow-up study to determine if completing this conjoint decision-making exercise prior to the visit with his physician may help in their shared decision-making discussions. Patient preferences may differ for each individual patient, and therefore listening to each patient’s preference after discussions around these six attributes may assist each patient to make his best treatment choice.

References

  1. Institute of Medicine. Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, DC: National Academy Press; 2001.
  2. Barry MJ, Edgman-Levitan S. Shared decision making — pinnacle of patient-centered care. N Engl J Med. 2012 Mar 1;366(9):780-1.
  3. Millenson ML, Macri J. Will the affordable care act move patient-centeredness to center stage? timely analysis of immediate health policy issues. Washington, DC: Urban Institute; 2012. Available at: http://www.rwjf.org/en/library/research/2012/03/will-the-affordable-care-act-move-patient-centeredness-to-center.html. Accessed July 15, 2015.
  4. Ryan M, Farrar S. Using conjoint analysis to elicit preferences for health care. BMJ. 2000 Jun 3; 320(7248): 1530–1533.
  5. Phillips KA, Maddala T, Johnson FR. Measuring preferences for health care interventions using conjoint analysis: an application to HIV testing. Health Serv Res. 2002 Dec; 37(6): 1681–1705.
  6. Wilson LS, Loucks A, Gipson G, et al. Patient preferences for attributes of multiple sclerosis disease-modifying therapies: development and results of a ratings-based conjoint analysis. Int J MS Care. 2015 Mar-Apr; 17(2): 74–82.
  7. Pignone MP, Brenner AT, Hawley S, et al. Conjoint analysis versus rating and ranking for values elicitation and clarification in colorectal cancer screening. J Gen Intern Med. 2012;27(1):45–50. doi:10.1007/s11606-011-1837-z.
  8. Bridges JFP, Mohamed AF, Finnern HW, Woehl A, Hauber AB. Patients’ preferences for treatment outcomes for advanced non-small cell lung cancer: a conjoint analysis. Lung Cancer. 2012;77(1):224–231. doi:10.1016/j.lungcan.2012.01.016.
  9. Wouters H, Maatman GA, Van Dijk L, et al. Tradeoff preferences regarding adjuvant endocrine therapy among women with estrogen receptor-positive breast cancer. Ann Oncol. 2013;24(9):2324–2329. doi:10.1093/annonc/mdt195
  10. Johnson FR, Hauber AB, Ozdemir S, Lynd L. Quantifying women’s stated benefit-risk tradeoff preferences for IBS treatment outcomes. Value Health. 2010;13(4):418–423. doi:10.1111/j.1524-4733.2010.00694.x.
  11. Silverman S, Calderon A, Kaw K, et al. Patient weighting of osteoporosis medication attributes across racial and ethnic groups: a study of osteoporosis medication preferences using conjoint analysis. Osteoporos Int. 2013;24(7):2067–2077. doi:10.1007/s00198-012-2241-1.
  12. Pieterse AH, Stiggelbout AM, Marijnen CAM. Methodologic evaluation of adaptive conjoint analysis to assess patient preferences: an application in oncology. Health Expect. 2010;13(4):392–405. doi:10.1111/j.1369-7625.2010.00595.x.
  13. Joy SM, Blauvelt BM, Tuncer MA, et al. Stakeholder perspectives on European priorities for comprehensive liver cancer control: a conjoint analysis. Eur J Public Health. 2013. doi:10.1093/eurpub/cks173.
  14. Ho MP, Gonzalez JM, Lerner HP, Neuland CY, Whang JM, McMurry-Heath M, Hauber AB, Irony T. Incorporating patient-preference evidence into regulatory decision making. Surg Endosc. 2015 Oct;29(10):2984-93.
  15. Santucci RA, Joyce GF, Wise M. Male Urethral Stricture Disease. The Journal of Urology. 2007;177(5):1667–1674.
  16. Ivaz SL, Bugeja S, Andrich DE. Urethral stricture disease in men. Trends in Urology & Men’s Health. 2015; 6(4):21-24.
  17. Granieri MA, Peterson AC. The management of bulbar urethral stricture disease before referral for definitive repair: have practice patterns changed? Urology. 2014 Oct;84(4):946-9.
  18. Hampson L, Gaither T, Wilson L, et al. Patient-centered treatment decisions: using conjoint analysis as an aid for shared decision-making for urethral stricture treatment. The Journal of Urology. 2015; 193(4)(suppl):e106–e107.
  19. Hampson LA, McAninch JW, Breyer B. Male urethral strictures and their management. Nature Reviews Urology. 2014; 11(1):43-50.
  20. AUA White Paper on Implementation of Shared Decision Making Into Urological Practice. Available at: https://www.auanet.org/common/pdf/education/clinical-guidance/Shared-Decision-Making.pdf. Accessed December 5, 2016.
  21. Sawtooth Software. The Basics of Interpreting Conjoint Utilities. Available at: http://www.sawtoothsoftware.com/support/technical-papers/general-conjoint-analysis/the-basics-of-interpreting-conjoint-utilities. Accessed June 1, 2015.
  22. Bridges JF, Hauber AB, Marshall D, et al. Conjoint analysis applications in health—a checklist: a report of the ISPOR Good Research Practices for Conjoint Analysis Task Force. Value Health. 2011 Jun;14(4):403-13.
  23. Szeinbach S, Harpe S, Flynn T, et al. Understanding conjoint analysis applications in health. ISPOR Connections. 2011; 17(1). Available at: http://www.ispor.org/news/articles/jan-feb2011/understanding-conjoint-analysis_print.asp. Accessed June 1, 2015.
  24. Bridges J, Onukwugha E, Johnson F, et al. Patient preference methods—a patient centered evaluation paradigm. ISPOR Connect 2007;13:4–7.
  25. Orme B. Getting Started with Conjoint Analysis. 2nd ed. Madison, Wisconsin: Research Publishers LLC; 2008.
  26. Longitudinal-Data/Panel-Data Reference Manual, Release 12. College Station, Texas: Stata Press; 2011.
  27. Hampson LA, Allen IE, Gaither TW, et al. Patient-centered treatment decisions for urethral stricture: conjoint analysis improves surgical decision-making. Urology. 2016;Jan;99:246-253.
  28. National Quality Forum. NQF to Develop National Standards, Measurement for Patient Decision Aids. Available at: http://www.qualityforum.org/Helping_Patients_Make_More_Informed_Decisions.aspx. Accessed December 5, 2016.

Copyright: © 2017 Leslie Wilson, Tracy Kuo Lin, Lindsay Hampson, Anna Oh, Jie Ting, Thomas W Gaither, Isabel Allen, Benjamin Breyer. Published here under license by The Journal of Participatory Medicine. Copyright for this article is retained by the authors, with first publication rights granted to the Journal of Participatory Medicine. All journal content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 License. By virtue of their appearance in this open-access journal, articles are free to use, with proper attribution, in educational and other non-commercial settings.

 

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