| Literature DB >> 33195294 |
Lylia Chachoua1, Monique Dabbous1, Clément François1,2, Claude Dussart3, Samuel Aballéa1,2, Mondher Toumi1,2.
Abstract
Objectives: Inclusion of patient preference (PP) data in decision making has been largely discussed in recent years. Healthcare decision makers-regulatory and health technology assessment (HTA)-are more and more conscious of the need for a patient-centered approach to decide on optimal allocation of scarce money, time, and technological resources. This literature review aims to examine the use of and recommendations for the integration of PP in decision making.Entities:
Keywords: benefit-risk assessment; decision-making; health technology assessment; patient preference; preference measurement
Year: 2020 PMID: 33195294 PMCID: PMC7649266 DOI: 10.3389/fmed.2020.543046
Source DB: PubMed Journal: Front Med (Lausanne) ISSN: 2296-858X
Search strategy.
| S1 | Patient preferences | (((((((((((((“patient preference” OR “patient preference/choice”))) OR “patients preferences”) OR “patient preferences”) OR “patients preference”) OR ((“patient input” OR “patient inputs”))) OR “patients input”) OR “patient choice”) OR ((“patients choice” OR “patients choices”))) OR “patient choices”) OR “patient perspective”) OR ((“patients perspective” OR “patients perspectives”))) OR “patient perspectives” | 23,208 |
| S2 | Preference measurement methods and tools | ((((((((((((((((“interview”) OR “survey”) OR ((“focus group” OR “focus group/consultation” OR “focus group/interview” OR “focus group/interview data” OR “focus group/interview questions” OR “focus group/interview transcripts” OR “focus group/interviews”))) OR “patient panel”) OR “preference measurement”) OR “preference elicitation”) OR ((“preference measure” OR “preference measurements” OR “preference measures”))) OR ((“preference rate” OR “preference rates” OR “preference rating” OR “preference ratings”))) OR ((“preference rank” OR “preference ranking” OR “preference rankings” OR “preference ranks”))) OR ((“pairwise comparison” OR “pairwise comparison experiment” OR “pairwise comparison method” OR “pairwise comparison methods” OR “pairwise comparison procedure” OR “pairwise comparison survey” OR “pairwise comparison test” OR “pairwise comparison testing” OR “pairwise comparison tests”))) OR “choice based”) OR ((“time trade off” OR “time trade off elicitation” OR “time trade off preference” OR “time trade off preferences”))) OR “discrete choice”) OR ((“standard gamble” OR “standard gamble preference”))) OR “swing weighting”) OR “best worst”) OR “contingent valuation” | 639,175 |
| S3 | Decision making | (((“decision making”) OR “multicriteria decision”) OR “multi criteria decision”) OR “mcda” | 191,923 |
| S4 | Medicinal product life cycle phase | ((((((((((((“benefit risk” OR “benefit risk assessment” OR “benefit risk assessment method” OR “benefit risk assessment methods” OR “benefit risk assessments” OR “benefit risk preferences”))) OR “health technology/technology assessment”) OR “biomedical technology assessment”) OR “hta”) OR “reimbursement”) OR ((“reimbursement decision” OR “reimbursement decision making” OR “reimbursement decisions”))) OR((“pricing” OR “pricing/reimbursement” OR “pricing and reimbursement”))))) OR ((“european medicine agency” OR “european medicines agency” OR “european medicines agency ema”))) OR ((“food and drug administration” OR “food and drug administration fda”)) | 127,178 |
| S5 | S3 OR S4 | 314,637 | |
| S6 | S1 AND S2 AND S5 | 1,246 | |
| S7 | Excluded concept | “Shared decision making” | 6,749 |
| S8 | S6 NOT S7 | 983 |
Figure 1PRISMA flow diagram for study selection.
Figure 2Distribution of the articles identified by region and year of publication.
Type and methodology of PP studies identified in the SLR.
| Vennedey et al. (2018) | Europe (Germany) | HTA, Reimbursement | - | DCE | Periodontal disease | Cost, Convenience, QoL | ( |
| Holmes et al. (2018) | Europe (UK) | BRA | - | DCE | Epilepsy | Efficacy, Safety, QoL | ( |
| Fifer et al. (2018) | Australia | HTA, Pricing/Reimbursement | - | DCE | Diabetes | Efficacy, Safety, Cost, Convenience | ( |
| Postmus et al. (2018) | Europe (UK) | BRA | - | DCE | Multiple myeloma | Efficacy, Safety | ( |
| Milovanovic et al. (2017) | Europe (Italy) | HTA | Survey/Questionnaire | - | Anemia/inflammatory bowel disease | Efficacy, Safety Convenience | ( |
| Von Arx et al. (2016) | Europe (Denmark) | BRA | - | DCE | Diabetes | Efficacy, Safety | ( |
| Eliasson et al. (2017) | Europe (France, Germany, UK) | BRA | - | DCE | Oncology | Efficacy, Safety, Convenience, QoL | ( |
| Eliasson et al. (2017) | Europe (UK) | BRA, HTA | - | DCE | Psoriasis | Efficacy, Safety, Cost, Convenience | ( |
| Muhlbacher et al. (2017) | Europe (Germany) | HTA | - | DCE | Hepatitis C | Efficacy, Safety, Cost, Convenience | ( |
| Janssen et al. (2016) | Europe (Germany) | HTA | - | VAS | Kidney diseases | Efficacy, Safety, Convenience, QoL | ( |
| Hollin et al. (2016) | USA | BRA | - | BWS | Duchene muscular dystrophy | Efficacy, Safety, QoL | ( |
| Hollin et al. (2017) | USA | BRA | - | BWS + DCE | Duchene muscular dystrophy | Efficacy, Safety, Convenience | ( |
| Morel et al. (2016) | Europe (UK) | BRA | - | DCE | Rare diseases | Efficacy, Safety, Convenience, QoL | ( |
| Hauber et al. (2016) | USA | BRA | - | DCE | Eczema | Efficacy, Safety | ( |
| Janssen et al. (2016) | USA | BRA, Pricing | - | BWS + DCE | Diabetes | Efficacy, Safety, Cost, Convenience | ( |
| Muhlbacher et al. (2016) | Europe (Germany) | HTA | - | DCE | Hepatitis C | Efficacy, Safety, Convenience | ( |
| Postmus et al. (2015) | Europe | BRA | - | MCDA | Oncology | Efficacy, Safety | ( |
| Roy et al. (2015) | USA | HTA, Pricing | - | DCE | Insomnia | Efficacy, Safety, Cost, Convenience | ( |
| Ho et al. (2015) | USA | BRA | - | DCE | Obesity | Efficacy, Safety, Convenience | ( |
| Mol et al. (2014) | Europe (Netherlands) | BRA | - | DCE | Diabetes | Efficacy, Safety | ( |
| Peay et al. (2014) | USA | BRA | - | BWS | Duchene muscular dystrophy | Efficacy, Safety | ( |
| Danner et al. (2011) | Europe (Germany) | HTA | - | AHP | Depression | Efficacy, Safety, QoL | ( |
| Johnson et al. (2010) | USA | BRA | - | DCE | Irritable bowel syndrome | Efficacy, Safety | ( |
| Aristides et al. (2004) | Europe (France, Germany, Italy, Spain, UK) | HTA, Pricing/Reimbursement | - | DCE | Diabetes | Efficacy, Safety, Cost, Convenience | ( |
| Sorum (1999) | US | Pricing | - | Rating scale + SG | ORL/infection | Efficacy, Safety, Cost | ( |
BRA, benefit–risk assessment; HTA, health technology assessment; MPLC, medicinal product life cycle; DCE, discrete choice experiment; VAS, visual analog scale; BWS, best–worst scaling; AHP, analytic hierarchy process; SG, standard gamble; MCDA, multicriteria decision analysis; QoL, quality of life.
Figure 3Chronological chart of main initiatives undertaken for integration of PPs in BRA and HTA decision-making. BRA, benefit–risk assessment; HTA, health technology assessment; IMI, Innovative Medicines Initiative; EMA, European Medicines Agency; FDA, US Food and Drug Administration; CDRH, Center for Devices and Radiological Health; MDIC, Medical device Innovation Consortium; PPMDag, Parent Project Muscular Dystrophy advocacy group; EUPATI, European Patients' Academy; IQWiG, Institute for Quality and Efficiency in Health Care; NICE, National Institute for Health and Care Excellence; Fimea, Finnish Medicines Agency; PBAC, Pharmaceutical Benefits Advisory Committee.
Initiatives for incorporation of PPs in BRA decision making.
| Governmental agencies | USA | FDA (CDRH) | 2012 | Pilot study (DCE eliciting PPs regarding a weight loss) to explore feasibility of PP studies and implementation of quantitative PPs in BRA | ( |
| 2013–2017 | Financial support for establishing CDER's Patient-Focused Drug Development initiativePublication of priority list of 20 disease areas that could benefit from the initiative | ( | |||
| FDA | 2015 | Guidance on DMD and related disorders mentioning consideration of patient and caregiver risk tolerance in light of the life-threatening nature of the condition | ( | ||
| Europe | EMA | 2009 | Coordination of PROTECT collaborative project in partnership with IMINo specific guidance issued by the EMA | ( | |
| 2013–2015 | EMA Patients' and Consumers' Organizations meeting conduction of a pilot study to assess feasibility and usefulness of systematically eliciting PPs for inclusion in BRA | ( | |||
| Private/public partnerships | Europe | IMI | 2009 | Launch of PROTECT collaborative project including two work packages dedicated to public/patient involvement in BRARecommendation of DCEs as preferred “utility survey technique” | ( |
| 2015 | Launch of the 5th Call under IMI 2: Patient perspective elicitation on benefits and risks of medicinal products, from development through the entire life cycle, to inform the decision-making process by regulators and HTA bodies (PREFER project) | ( | |||
| EUPATI | 2016 | Patient training modules and guidance document development on PP elicitation and use in decision making (R&D, BRA, and HTA) | ( | ||
| USA | MDIC | 2012 | A framework to support FDA and industry in integration of PP in BRA of innovative medical devicesMDIC Methods Catalog: a general overview of available methods to quantify PP for BRA | ( | |
| Patient organizations and advocacy groups | USA | Parent Project Muscular Dystrophy Advocacy Group | 2013 | Development of the first patient-advocacy-initiated draft guidance for inclusion of PPs in regulatory decision making | ( |
| 2015 | PP pilot study that elicits preferences for a therapeutic agent that has demonstrated pulmonary benefit in a phase III clinical trial | ( |
FDA, US Food and Drug Administration; EMA, European Medicines Agency; IMI, Innovative Medicines Initiative; EUPATI, European Patients' Academy; MDIC, Medical Device Innovation Consortium; CDRH, Center for Devices and Radiological Health; DMD, Duchenne muscular dystrophy; DCE, discrete choice experiment; BRA, benefit–risk assessment; HTA, health technology assessment; R&D, research and development; PP, patient preference.
Initiatives for incorporation of PPs in HTA, pricing, and reimbursement decision making.
| Governmental agencies | Germany | IQWiG | 2010 | Pilot study: Use of PP studies (AHP) to weigh patient-relevant outcome within IQWiG appraisal in order to drive reimbursable prices for new medications | ( |
| 2010 | Pilot study: Use of PPs (DCE) to identify, weigh, and prioritize multiple patient-relevant outcomesInclusion of PPs in evidence-based decision making on the approval and pricing of innovations | ( | |||
| 2016 | Adaptation of the concept of the efficiency frontier to serve as a framework for the evaluation of cost-effectiveness and indirectly for the pricing and reimbursement of health technologies | ( | |||
| Finland | Fimea | 2012 | National recommendation consisting in a step-by-step guidance on how to conduct qualitative interviews (individual or focus groups) for integration of patients' voices into the HTA process of new pharmaceuticals | ( | |
| Australia | PBAC | 2013 | Positive recommendation (exenatide 2 mg once weekly) following a DCE revealing potential health benefits from likely improved adherence | ( | |
| UK | NICE | 2017–2019 | Funding a 2-year exploratory project to explore how to quantitatively capture and incorporate PPs in decision modeling as part of the HTA process (in collaboration with Myeloma UK) | ( | |
| Private/public partnerships | Europe | INTEGRATE-HTA | 2013–2015 | INTEGRATE-HTA work package 4 advocates for integration of social, cultural, ethical, legal, and organizational issues as well as patients' heterogeneity and preferences with effectiveness and cost-effectiveness in HTA | ( |
| IMI | 2015 | Launch of PREFER project: development of a systematic approach for considering the use of PPs across the medical treatment life cycle (time frame: 2016–2021) | ( | ||
| EUPATI | 2016 | Patient training modules and guidance documents development on PP election and use in decision making (R&D, BRA, and HTA) | ( |
IQWiG, Institute for Quality and Efficiency in Health Care; NICE, National Institute for Health and Care Excellence; Fimea, Finnish Medicines Agency; PBAC, Pharmaceutical Benefits Advisory Committee; IMI, Innovative Medicines Initiative; EUPATI, European Patients' Academy; PP, patient preference; DCE, discreate-choice experiment; BRA, benefit–risk assessment; HTA, health technology assessment; R&D, research and development; AHP, analytic hierarchy process.
Summary of the methods used to assess patient preferences.
| Ranking and rating | Direct scaling methods asking patient to rank or score attributes that distinguish treatment | • Feasibility of their implementation | • Lack of direct explicit trade-offs between benefits and harms | ( |
| Visual analogue scale | Raking method: Assign preference for a health state on a line anchored by perfect health and death | • Collection and valuation of several outcomes | • Use of ill-defined anchors which limit comparison between individuals | ( |
| Standard gamble | Choose either a gamble between perfect health and death or a certain but intermediate health state | • Estimation of quality-adjusted life-years (QALYs) | • Cognitively burdensome if several scenarios | ( |
| Time trade-off | Choose either an intermediate health state for time | • Estimation of QALYs | • Emotionally challenging for parents to consider their children having less years of life | ( |
| Discrete choice experiment | Choose between scenarios that describe a health state by different levels of attributes of that health state | • Valuation of hypothetical scenarios | • Require large sample sizes to produce statistically significant utilities | ( |
| Best-worst scaling | Direct valuation of best and worst scenario or profile | • Less cognitively taxing on its participants | • Does not allow for “indifferent” choice | ( |
| Multicriteria decision analysis | Direct consideration of an explicit set of criteria and their relative importance | • Decision based on several features simultaneously | • Potential cognitive burden | ( |
| Analytic hierarchy process | Type of MCDA: Choose between multiple attributes or criteria in a pairwise compared manner | • Simplify complex decision making with multiple criteria, by reducing the trade-offs made at one time by presenting the choice as a pairwise comparison | • Valuation of limited number of outcomes | ( |
| Swing weighting | Type of MCDA: First, patients rank the scale swings and afterwards allocate points that indicate the trade-off ratios | • Does not require econometric modeling: preferences are assumed to be directly captured with the elicitation task | • Potential cognitive burden requiring direct numerical assessment | ( |