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The American Journal of Managed Care November 2018
A Randomized, Pragmatic, Pharmacist-Led Intervention Reduced Opioids Following Orthopedic Surgery
David H. Smith, PhD, RPh; Jennifer L. Kuntz, PhD; Lynn L. DeBar, PhD, MPH; Jill Mesa; Xiuhai Yang, MS; Jennifer Schneider, MPH; Amanda Petrik, MS; Katherine Reese, PharmD; Lou Ann Thorsness, RPh; David Boardman, MD; and Eric S. Johnson, PhD
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Understanding and Improving Value Frameworks With Real-World Patient Outcomes
Anupam B. Jena, MD, PhD; Jacquelyn W. Chou, MPP, MPL; Lara Yoon, MPH; Wade M. Aubry, MD; Jan Berger, MD, MJ; Wayne Burton, MD; A. Mark Fendrick, MD; Donna M. Fick, RN, PhD; David Franklin, BA; Rebecca Killion, MA; Darius N. Lakdawalla, PhD; Peter J. Neumann, ScD; Kavita Patel, MD, MSHS; John Yee, MD, MPH; Brian Sakurada, PharmD; and Kristina Yu-Isenberg, PhD, MPH, RPh
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Daniel B. Wolfson, MHSA, Executive Vice President and COO, ABIM Foundation
Cost of Pharmacotherapy for Opioid Use Disorders Following Inpatient Detoxification
Kathryn E. McCollister, PhD; Jared A. Leff, MS; Xuan Yang, MPH, MHS; Joshua D. Lee, MD; Edward V. Nunes, MD; Patricia Novo, MPA, MPH; John Rotrosen, MD; Bruce R. Schackman, PhD; and Sean M. Murphy, PhD
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Guneet K. Jasuja, PhD; Omid Ameli, MD, MPH; Donald R. Miller, ScD; Thomas Land, PhD; Dana Bernson, MPH; Adam J. Rose, MD, MSc; Dan R. Berlowitz, MD, MPH; and David A. Smelson, PsyD
Effects of a Community-Based Care Management Model for Super-Utilizers
Purvi Sevak, PhD; Cara N. Stepanczuk, MPP; Katharine W.V. Bradley, PhD; Tim Day, MSPH; Greg Peterson, PhD; Boyd Gilman, PhD; Laura Blue, PhD; Keith Kranker, PhD; Kate Stewart, PhD; and Lorenzo Moreno, PhD
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Kelly Gao; Gene Pellerin, MD; and Laurence Kaminsky, PhD
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Jennifer Elston Lafata, PhD; Carrie A. Miller, PhD, MPH; Deirdre A. Shires, PhD; Karen Dyer, PhD; Scott M. Ratliff, MS; and Michelle Schreiber, MD
Impact of Dementia on Costs of Modifiable Comorbid Conditions
Patricia R. Salber, MD, MBA; Christobel E. Selecky, MA; Dirk Soenksen, MS, MBA; and Thomas Wilson, PhD, DrPH
Hospital Cancer Pain Management by Electronic Health Record–Based Automatic Screening
Jinyoung Shin, MD, PhD; Hyeonyoung Ko, MD, MPH; Jeong Ah Kim, BS; Yun-Mi Song, MD, PhD; Jin Seok Ahn, MD, PhD; Seok Jin Nam, MD, PhD; and Jungkwon Lee, MD, PhD

Understanding and Improving Value Frameworks With Real-World Patient Outcomes

Anupam B. Jena, MD, PhD; Jacquelyn W. Chou, MPP, MPL; Lara Yoon, MPH; Wade M. Aubry, MD; Jan Berger, MD, MJ; Wayne Burton, MD; A. Mark Fendrick, MD; Donna M. Fick, RN, PhD; David Franklin, BA; Rebecca Killion, MA; Darius N. Lakdawalla, PhD; Peter J. Neumann, ScD; Kavita Patel, MD, MSHS; John Yee, MD, MPH; Brian Sakurada, PharmD; and Kristina Yu-Isenberg, PhD, MPH, RPh
New value frameworks should incorporate real-world evidence that reflects patient treatment behavior, adherence to medication, and equity concerns arising from disparities in care.
ABSTRACT

Objectives: To provide recommendations that will improve approaches to measuring the value of new medical technologies to patients.

Study Design: Informed discussion by experts after literature review.

Methods: A working group was formed, and participants discussed how value frameworks should incorporate key features important to patients in evaluating new medical technologies, particularly for chronic diseases.

Results: The working group suggests that new value frameworks should integrate real-world evidence to complement randomized controlled trials, incorporate the ways in which real-world behavior mediates outcomes, and explicitly discuss how therapies affect real-world equity and disparities in care.

Conclusions: Collective stakeholders that include key decision makers within our healthcare system need to recognize the importance of implementing real-world evidence and devote resources to further research into the chronic disease areas in which the impact of human behavior is amplified by the duration of disease and treatment.

Am J Manag Care. 2018;24(11):506-509
Takeaway Points

Steps have been taken to develop critical evaluations of drugs with the creation of value frameworks from organizations such as the Institute for Clinical and Economic Review, American Society of Clinical Oncology, and Memorial Sloan Kettering, but more work can and should be done to further refine these approaches. The Value FORWARD (Frameworks, Outcomes, and Real-World Adherence in Chronic Disease) Committee puts forth the following recommendations:
  • Value frameworks should incorporate real-world effectiveness to complement randomized controlled trial efficacy.
  • Value assessments must explicitly incorporate the ways in which real-world behavior mediates outcomes.
  • Value assessments should explicitly discuss how therapies affect real-world equity and disparities in care.
Policy makers, healthcare payers, patients, employers, and other stakeholders continue to fret about the rising cost of new medical technologies. Many scientific organizations have responded by developing new tools to assess the value of these technologies, commonly called “value frameworks.” For example, the American Society of Clinical Oncology (ASCO),1 Memorial Sloan Kettering,2 and the Institute for Clinical and Economic Review (ICER) have offered alternative approaches to assessing the value of technologies. In principle, better information about value can help moderate growth in the cost of technologies that do not provide sufficient benefit to patients.3

Yet there remains a gap between the goal of measuring value conferred to patients and the available evidence for new medical technologies. Randomized controlled trial (RCT) evidence generated for regulatory approval often incorrectly measures or fails to measure aspects of value that are key to patients. Some of these gaps and limitations are widely understood,4 but others have received too little attention, such as the role of patient behavior in mediating clinical outcomes.5,6 For example, evidence generated by RCTs often reflects outcomes achieved with motivated patients treated in environments in which individual patient behaviors that are critical to driving real-world outcomes, including adherence to medications, are controlled. As a result, interventions that improve adherence may not demonstrate large efficacy benefits in RCTs but may demonstrate larger benefits in real-world settings in which adherence is typically lower.

A working group was formed in partnership with Precision Health Economics and Intarcia Therapeutics in 2017 to make recommendations on how value frameworks should close the gap between evidence and patient behavior when evaluating new medical technologies, particularly for chronic diseases. Our working group recommended that these value frameworks enhance attention to (1) real-world evidence (RWE), (2) the role of adherence, and (3) nonclinical components of the patient experience.

Overview of Value Frameworks

Unlike healthcare systems in countries such as England, Germany, and Australia, where health technology assessment processes are well established,7 the US healthcare system does not have a formalized approach for defining or measuring value. Private organizations have stepped in to fill this gap but offer varying perspectives and approaches. For example, ASCO has released a value framework meant to aid physician communication of cancer treatment options with patients.1 ICER evaluates the cost-effectiveness of drug therapies from a payer and health system perspective.8 Memorial Sloan Kettering’s drug evaluation framework, the Drug Abacus, which evaluates cancer drugs, enables users to input their own preferences on different dimensions of value.2 These value frameworks differ in the perspectives that they use and in the attributes of value that they include in their evaluations. As a result, different value frameworks evaluating the same drug may have different conclusions about what may be considered reasonable value.

Recommendation 1: Value Frameworks Should Incorporate Real-World Effectiveness to Complement RCT Efficacy

Value frameworks have tended to emphasize evidence generated in RCTs, excluding or downplaying the use of RWE. Clinical trial evidence is emphasized as the gold standard for health benefit, although recently, there has been a growing awareness and movement to improve databases and infrastructure for RWE.9,10

Clinical trial populations often fail to mirror real-world populations. This external validity problem is already well documented.11 Clinical trials are conducted in controlled environments where the structure of the environment lends itself to optimal rates of treatment adherence.12 More recently, some prominent researchers have argued that RCTs with smaller samples, often seen in breakthrough treatments with accelerated market approval, suffer from internal validity problems such as misalignment between the characteristics of subjects in the treatment and comparator groups.13

RWE can help address these limitations. To be sure, it also suffers from limitations related to internal validity (eg, persons using novel therapies in the real world are often systematically different from their peers using older drugs at the same time). Methodological solutions exist to control for some of these confounders, and more generally, care must be taken to ensure the highest degree of internal validity in RWE. However, RWE is more than just a second-best alternative to RCT evidence; it provides inferences that are necessarily applicable to real-world populations. One major area of behavior around treatment that can be captured more realistically with RWE is adherence to treatment regimens.14 Our committee recommends explicit evaluation of RWE as a potential input into value assessments.


 
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