Dataset Information

A Framework for Evaluating the Implementation of Biosimilar Drugs.

ABSTRACT:

Background

The introduction of biosimilar drugs has significant effects on health care systems, and a variety of approaches are required to support acceptance, adoption, and use of these drugs. Literature exists on the enablers of, and barriers to, biosimilar implementation, but frameworks that support the evaluation of biosimilar implementation strategies are currently lacking.

Objective

To develop an evaluation framework for assessing the effects of biosimilar implementation strategies on patients, clinicians, and publicly funded drug programs.

Methods

The scope of the evaluation was determined by a pan-Canadian working group through the creation of a logic model of activities and expected outcomes associated with biosimilar implementation. Each component of the logic model was considered under the RE-AIM framework, which led to a set of evaluation questions and indicators. Feedback to inform the final framework was sought from stakeholders through focus group sessions and written responses.

Results

An evaluation framework was created that articulates evaluation questions and indicators across 5 priority areas: stakeholder engagement, patient experience, patient outcomes, clinician experience, and system sustainability and affordability. Stakeholder feedback was obtained through 9 focus group sessions with a total of 87 participants. Feedback was used to refine the framework on the basis of stakeholder priorities and feasibility.

Conclusions

Through extensive stakeholder consultation, an evaluation framework was developed to measure and monitor the effects of biosimilar implementation on the 5 identified priority areas, as well as to inform future biosimilar implementations. This framework can be used as a starting point for evaluating the implementation of biosimilars across health care systems.

SUBMITTER: Milgram L

PROVIDER: S-EPMC10049771 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Framework for Evaluating the Implementation of Biosimilar Drugs.

Milgram Lisa L Wheeler Sarah S Adamic Andrea A Loncar Mirhad M Guirguis Micheal M McCabe Betty Jo BJ

The Canadian journal of hospital pharmacy 20230301 2

<h4>Background</h4>The introduction of biosimilar drugs has significant effects on health care systems, and a variety of approaches are required to support acceptance, adoption, and use of these drugs. Literature exists on the enablers of, and barriers to, biosimilar implementation, but frameworks that support the evaluation of biosimilar implementation strategies are currently lacking.<h4>Objective</h4>To develop an evaluation framework for assessing the effects of biosimilar implementation str ...[more]

PMID: 36998755

Similar Datasets

Project description:BackgroundChronic obstructive pulmonary disease (COPD) is a prevalent chronic disease that requires comprehensive approaches to manage; it accounts for a significant portion of Canada's annual healthcare spending. Interprofessional teams are effective at providing chronic disease management that meets the needs of patients. As part of an ongoing initiative, a COPD management program, the Best Care COPD program was implemented in a primary care setting. The objectives of this research were to determine site-specific factors facilitating or impeding the implementation of a COPD program in a new setting, while evaluating the implementation strategy used.MethodsA qualitative case study was conducted using interviews, focus groups, document analysis, and site visits. Data were deductively analyzed using the Consolidated Framework for Implementation Research (CFIR) to assess the impact of each of its constructs on Best Care COPD program implementation at this site.ResultsEleven CFIR constructs were determined to meaningfully affect implementation. Five were identified as the most influential in the implementation process. Cosmopolitanism (partnerships with other organizations), networks and communication (amongst program providers), engaging (key individuals to participate in program implementation), design quality and packaging (of the program), and reflecting and evaluating (throughout the implementation process). A peer-to-peer implementation strategy included training of registered respiratory therapists (RRT) as certified respiratory educators and the establishment of a communication network among RRTs to discuss experiences, collectively solve problems, and connect with the program lead.ConclusionsThis study provides a practical example of the various factors that facilitated the implementation of the Best Care COPD program. It also demonstrates the potential of using a peer-to-peer implementation strategy. Focusing on these factors will be useful for informing the continued spread and success of the Best Care COPD program and future implementation of other chronic care programs.

Project description:BackgroundThe PARiHS framework (Promoting Action on Research Implementation in Health Services) has proved to be a useful practical and conceptual heuristic for many researchers and practitioners in framing their research or knowledge translation endeavours. However, as a conceptual framework it still remains untested and therefore its contribution to the overall development and testing of theory in the field of implementation science is largely unquantified.DiscussionThis being the case, the paper provides an integrated summary of our conceptual and theoretical thinking so far and introduces a typology (derived from social policy analysis) used to distinguish between the terms conceptual framework, theory and model - important definitional and conceptual issues in trying to refine theoretical and methodological approaches to knowledge translation. Secondly, the paper describes the next phase of our work, in particular concentrating on the conceptual thinking and mapping that has led to the generation of the hypothesis that the PARiHS framework is best utilised as a two-stage process: as a preliminary (diagnostic and evaluative) measure of the elements and sub-elements of evidence (E) and context (C), and then using the aggregated data from these measures to determine the most appropriate facilitation method. The exact nature of the intervention is thus determined by the specific actors in the specific context at a specific time and place. In the process of refining this next phase of our work, we have had to consider the wider issues around the use of theories to inform and shape our research activity; the ongoing challenges of developing robust and sensitive measures; facilitation as an intervention for getting research into practice; and finally to note how the current debates around evidence into practice are adopting wider notions that fit innovations more generally.SummaryThe paper concludes by suggesting that the future direction of the work on the PARiHS framework is to develop a two-stage diagnostic and evaluative approach, where the intervention is shaped and moulded by the information gathered about the specific situation and from participating stakeholders. In order to expedite the generation of new evidence and testing of emerging theories, we suggest the formation of an international research implementation science collaborative that can systematically collect and analyse experiences of using and testing the PARiHS framework and similar conceptual and theoretical approaches. We also recommend further refinement of the definitions around conceptual framework, theory, and model, suggesting a wider discussion that embraces multiple epistemological and ontological perspectives.

Project description:ImportanceBiologic drugs account for a growing share of US pharmaceutical spending. Competition from follow-on biosimilar products (subsequent versions that have no clinically meaningful differences from the original biologic) has led to modest reductions in US health care spending, but these savings may not translate to lower out-of-pocket (OOP) costs for patients.ObjectiveTo investigate whether biosimilar competition is associated with lower OOP spending for patients using biologics.Design, setting, and participantsThis cohort study used a national commercial claims database (Optum Clinformatics Data Mart) to identify outpatient claims for 1 of 7 clinician-administered biologics (filgrastim, infliximab, pegfilgrastim, epoetin alfa, bevacizumab, rituximab, and trastuzumab) from January 2009 through March 2022. Claims by commercially insured patients younger than 65 years were included.ExposureYear relative to first biosimilar availability and use of original or biosimilar version.Main outcomes and measuresPatients' annual OOP spending on biologics for each calendar year was determined, and OOP spending per claim between reference biologic and biosimilar versions was compared. Two-part regression models assessed for differences in OOP spending, adjusting for patient and clinical characteristics (age, sex, US Census region, health plan type, diagnosis, and place of service) and year relative to initial biosimilar entry.ResultsOver 1.7 million claims from 190 364 individuals (median [IQR] age, 53 [42-59] years; 58.3% females) who used at least 1 of the 7 biologics between 2009 and 2022 were included in the analysis. Over 251 566 patient-years of observation, annual OOP costs increased before and after biosimilar availability. Two years after the start of biosimilar competition, the adjusted odds ratio of nonzero annual OOP spending was 1.08 (95% CI, 1.04-1.12; P < .001) and average nonzero annual spending was 12% higher (95% CI, 10%-14%; P < .001) compared with the year before biosimilar competition. After biosimilars became available, claims for biosimilars were more likely than reference biologics to have nonzero OOP costs (adjusted odds ratio, 1.13 [95% CI, 1.11-1.16]; P < .001) but had 8% lower mean nonzero OOP costs (adjusted mean ratio, 0.92 [95% CI, 0.90-0.93; P < .001). Findings varied by drug.Conclusions and relevanceFindings of this cohort study suggest that biosimilar competition was not consistently associated with lower OOP costs for commercially insured outpatients, highlighting the need for targeted policy interventions to ensure that the savings generated from biosimilar competition translate into increased affordability for patients who need biologics.

Project description:BackgroundAn application-oriented implementation framework designed for clinicians and based on the Diffusion of Innovations theory included 81 implementation strategies with suggested timing for use within four implementation phases. The purpose of this research was to evaluate and strengthen the framework for clinician use and propose its usefulness in implementation research.MethodsA multi-step, iterative approach guided framework revisions. Individuals requesting the use of the framework over the previous 7 years were sent an electronic questionnaire. Evaluation captured framework usability, generalizability, accuracy, and implementation phases for each strategy. Next, nurse leaders who use the framework pile sorted strategies for cultural domain analysis. Last, a panel of five EBP/implementation experts used these data and built consensus to strengthen the framework.ResultsParticipants (n = 127/1578; 8% response) were predominately nurses (94%), highly educated (94% Master's or higher), and from across healthcare (52% hospital/system, 31% academia, and 7% community) in the USA (84%). Most (96%) reported at least some experience using the framework and 88% would use the framework again. A 4-point scale (1 = not/disagree to 4 = very/agree) was used. The framework was deemed useful (92%, rating 3-4), easy to use (72%), intuitive (67%), generalizable (100%), flexible and adaptive (100%), with accurate phases (96%), and accurate targets (100%). Participants (n = 51) identified implementation strategy timing within four phases (Cochran's Q); 54 of 81 strategies (66.7%, p < 0.05) were significantly linked to a specific phase; of these, 30 (55.6%) matched the original framework. Next, nurse leaders (n = 23) completed a pile sorting activity. Anthropac software was used to analyze the data and visualize it as a domain map and hierarchical clusters with 10 domains. Lastly, experts used these data and implementation science to refine and specify each of the 75 strategies, identifying phase, domain, actors, and function. Strategy usability, timing, and groupings were used to refine the framework.ConclusionThe Iowa Implementation for Sustainability Framework offers a typology to guide implementation for evidence-based healthcare. This study specifies 75 implementation strategies within four phases and 10 domains and begins to validate the framework. Standard use of strategy names is foundational to compare and understand when implementation strategies are effective, in what dose, for which topics, by whom, and in what context.

Project description:BackgroundOver the past few decades, numerous forecasting methods have been proposed in the field of epidemic forecasting. Such methods can be classified into different categories such as deterministic vs. probabilistic, comparative methods vs. generative methods, and so on. In some of the more popular comparative methods, researchers compare observed epidemiological data from the early stages of an outbreak with the output of proposed models to forecast the future trend and prevalence of the pandemic. A significant problem in this area is the lack of standard well-defined evaluation measures to select the best algorithm among different ones, as well as for selecting the best possible configuration for a particular algorithm.ResultsIn this paper we present an evaluation framework which allows for combining different features, error measures, and ranking schema to evaluate forecasts. We describe the various epidemic features (Epi-features) included to characterize the output of forecasting methods and provide suitable error measures that could be used to evaluate the accuracy of the methods with respect to these Epi-features. We focus on long-term predictions rather than short-term forecasting and demonstrate the utility of the framework by evaluating six forecasting methods for predicting influenza in the United States. Our results demonstrate that different error measures lead to different rankings even for a single Epi-feature. Further, our experimental analyses show that no single method dominates the rest in predicting all Epi-features when evaluated across error measures. As an alternative, we provide various Consensus Ranking schema that summarize individual rankings, thus accounting for different error measures. Since each Epi-feature presents a different aspect of the epidemic, multiple methods need to be combined to provide a comprehensive forecast. Thus we call for a more nuanced approach while evaluating epidemic forecasts and we believe that a comprehensive evaluation framework, as presented in this paper, will add value to the computational epidemiology community.

Dataset Information

A Framework for Evaluating the Implementation of Biosimilar Drugs.

Background

Objective

Methods

Results

Conclusions

Publications

A Framework for Evaluating the Implementation of Biosimilar Drugs.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets