Which research is needed to support clinical decision-making on integrative medicine?—Can comparative effectiveness research close the gap?

2012 ◽  
Vol 18 (10) ◽  
pp. 723-729 ◽  
Author(s):  
Claudia M. Witt ◽  
Wen-jing Huang ◽  
Lixing Lao ◽  
Berman Bm
Keyword(s):  
Decision Making ◽  
Integrative Medicine ◽  
Comparative Effectiveness Research ◽  
Comparative Effectiveness ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Effectiveness Research

Is comparative effectiveness research emphasized in oncologic residency training programs? Results of a national survey.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. e17577-e17577 ◽  
Author(s):  
Nicholas George Zaorsky ◽  
Jordan Hess ◽  
Robert Benjamin Den ◽  
Voichita Bar-Ad ◽  
Joanne Filicko ◽  
...  
Keyword(s):  
Comparative Effectiveness Research ◽  
Comparative Effectiveness ◽  
Clinical Decision Making ◽  
Training Programs ◽  
Medical Condition ◽  
Clinical Decision ◽  
Effectiveness Research ◽  
Continuous Quality ◽  
Effectiveness And Efficiency ◽  
Strongly Agree

e17577 Background: Comparative effectiveness research (CER) is informally defined as an assessment of all available efficacious options for a specific medical condition, with intent to estimate effectiveness and efficiency in specific subpopulations. The American Recovery and Reinvestment Act of 2009 allocated $1.8 B to increase CER and train physicians in its practice. Although program directors (PDs) of medical oncology (MO) and radiation oncology (RO) training programs know that CER is emphasized nationally, it is unknown if CER is emphasized in oncological training programs themselves. We examine the emphasis of CER in MO and RO training programs. Methods: A web-based, anonymous survey was sent to RO PDs (n = 85) and chief residents (CRs; 98); and MO PDs (99), asking them to forward a link to fellows (Fs; 160). Mean weighted Likerts (MWLs ± standard deviations [SDs]) were calculated from scales (1, strongly disagree; 3, neutral; 5, strongly agree). Results: The response rates for RO PDs, RO CRs, MO PDs, and MO Fs were 20%, 21%, 11%, and 10% (combined, 15%, 68/442). Respondents had mixed beliefs in having a clear definition of CER (MWL, 3.1 ± 1.2); their programs encouraging CER (3.2 ± 1.2); including a course on CER (2.3 ± 0.9); or discussing the differences among efficacy, effectiveness, and efficiency (2.9 ± 0.9). Retrospective cohort studies were easy to perform at institutions (4.3 ± 0.8), but less so CER (3.1 ± 1.3). Respondents believed their programs’ research integrated some core values of CER, including comparing treatments to influence clinical decision making (4.6 ± 0.7). Respondents believed CER was important (4.3 ± 0.7); 47% would divert funding from other types of research toward CER; 35% would, only if funding for other research was unaffected. Conclusions: CER is not emphasized in oncologic training programs, and most PDs and trainees cannot clearly define CER. In the era of health care reform and potential future payment reforms, it is anticipated that CER will become an increasingly important component of evidence-based medicine and continuous quality improvement. This study identifies a need for oncology training programs to incorporate education about CER into their curricula.

Personalized Medicine in the Context of Comparative Effectiveness Research

2013 ◽  
Vol 16 (2) ◽  
pp. S73-S86 ◽  
Author(s):  
Anirban Basu
Keyword(s):  
Decision Making ◽  
Personalized Medicine ◽  
Comparative Effectiveness Research ◽  
Comparative Effectiveness ◽  
Genomic Research ◽  
Future Research ◽  
Effectiveness Research ◽  
Medical Quality ◽  
Clinical Scenarios ◽  
Objective Evidence

Abstract The world of patient-centered outcomes research (PCOR) seems to bridge the previously disjointed worlds of comparative effectiveness research (CER) and personalized medicine (PM). Indeed, theoretical reasoning on how information on medical quality should inform decision making, both at the individual and the policy level, reveals that personalized information on the value of medical products is critical for improving decision making at all levels. However, challenges to generating, evaluating and translating evidence that might lead to personalization need to be critically assessed. In this paper, I discuss two different concepts of personalized medicine – passive personalization (PPM) and active personalization (APM) that are important to distinguish in order to invest efficiently in PCOR and develop objective evidence on the value of personalization that will aid in its translation. APM constitutes the process of actively seeking identifiers, which can be genotypical, phenotypical or even environmental, that can be used to differentiate between the marginal benefits of treatment across patients. In contrast, PPM involves a passive approach to personalization where, in the absence of explicit research to discover identifiers, patients and physicians “learn by doing” mostly due to the repeated use of similar products on similar patients. Benchmarking the current state of PPM sets the bar to which the expected value of any new APM agenda should be evaluated. Exploring processes that enable PPM in practice can help discover new APM agendas, such as those based on developing predictive algorithms based on clinical, phenotypical and preference data, which may be more efficient that trying to develop expensive genetic tests. It can also identify scenarios or subgroups of patients where genomic research would be most valuable since alternative prediction algorithms were difficult to develop in those settings. Two clinical scenarios are discussed where PPM was explored through novel econometric methods. Related discussions around exploring PPM processes, multi-dimensionality of outcomes, and a balanced agenda for future research on personalization follow.

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