Preference assessment method affects decision-analytic recommendations: A prostate cancer treatment example
ABSTRACT To evaluate the effect of preference assessment method on treatment recommended by an individualized decision-analytic model for early prostate cancer.
Health state preferences were elicited by time tradeoff, rating scale, and a power transformation of the rating scale from 63 men ages 55 to 75. The authors used these values in a Markov model to determine whether radical prostatectomy or watchful waiting yielded the greater quality-adjusted life expectancy.
Time tradeoff and transformed rating scale recommendations differed widely. Time tradeoff and transformed rating scale utilities differed in their treatment recommendation for 21% to 52% of men, and the mean difference in quality-adjusted life years varied from less than 0.5 to greater than 1.0.
Treatment recommendations from the prostate cancer decision model were sensitive to the method of preference assessment. If decision analysis is used to counsel individual patients, careful consideration must be given to the method of preference elicitation.
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- "Medicine Midwifery/nursing Social Sciences (Sociology, Anthropology, Statistics) Driffield and Smith (2007) Bryers and van Teijlingen (2010) Oakley (2004) Penson (2009) Everly (2012) van Teijlingen (2005) Scott (2005) Romano (2009) Simonds (2002) Bolaji and Meehan (1993) Jordan and Farley (2008) Rayment (2011) Nelson et al. (2009) Kennedy and Lyndon (2008) Koblinsky et al. (2006) Elkin et al. (2004) Davis and Walker (2010) Davis (2006) Rosenbaum (2011) Brucker (2001) McCourt (2009a) Boers et al. (2010) McCourt (2009c,b), McCourt and Dykes (2009), Downe and Dykes (2009), Winter and Duff (2009) Maso et al. (2011) "
ABSTRACT: This paper is a report of an analysis of the concept of watchful waiting. Little is known about differences between the intrapartum care processes of midwives and physicians. In this time of growing rates of surgical birth outcomes, intrapartum care processes are a key area for research and improvement. Watchful waiting is a common care plan used by both midwives and physicians that involves the timing of interventions in labour. Rodgers' Evolutionary Model was used to conduct a concept analysis of the term watchful waiting. Scientific literature authored by, and about, midwives and physicians, as located via an intrapartum-focused database search inclusive of years 1922-May 2012. Thirty English-language articles from nine different countries were located, representing the midwifery and physician scientific literature focusing on watchful waiting in labour and provider decision-making processes. Attributes, consequences, antecedents and affecting themes were identified through a thematic analysis of the identified articles. Data analysis reveals that many midwives and physicians define watchful waiting differently, based on their philosophies of care. The care of women in labour is complicated as a result of different understandings by some providers of common processes of intrapartum care.Journal of Advanced Nursing 07/2013; DOI:10.1111/jan.12209 · 1.69 Impact Factor
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ABSTRACT: The authors examine how a constructive preferences perspective might change the prevailing view of medical decision making by suggesting that the methods used to measure preferences for medical treatments can change the preferences that are reported. The authors focus on 2 possible techniques that they believe would result in better outcomes. The 1st is the wise selection of default options. Defaults may be best applied when strong clinical evidence suggests a treatment option to be correct for most people but preserving patient choice is appropriate. The 2nd is the use of environments that explicitly facilitate the optimal construction of preferences. This seems most appropriate when choice depends on a patient's ability to understand and represent probabilities and outcomes. For each technique, the authors describe the background and literature, provide a case study, and discuss applications.Health Psychology 08/2005; 24(4 Suppl):S17-22. DOI:10.1037/0278-6133.24.4.S17 · 3.95 Impact Factor