Exploring the feasibility of Conjoint Analysis as a tool for prioritizing innovations for implementation

Using implementation science to operate as a learning health system to improve outcomes in early psychosis

AIM

Early interventions are well understood to improve psychosis outcomes, but their successful implementation remains limited. This article introduces a three-step roadmap for advancing the implementation of evidence-based practices to operate as a learning health system, which can be applied to early interventions for psychosis and is intended for an audience that is relatively new to systematic approaches to implementation.

METHODS

The roadmap is grounded in implementation science, which specializes in methods to promote routine use of evidence-based innovations. The roadmap draws on learning health system principles that call for commitment of leadership, application of evidence, examination of care experiences, and study of health outcomes. Examples are discussed for each roadmap step, emphasizing both data- and stakeholder-related considerations applicable throughout the roadmap.

CONCLUSIONS

Early psychosis care is a promising topic through which to discuss the critical need to move evidence into practice. Despite remarkable advances in early psychosis interventions, population-level impact of those interventions is yet to be realized. By providing an introduction to how implementation science principles can be operationalized in a learning health system and sharing examples from early psychosis care, this article prompts inclusion of a wider audience in essential discourse on the role that implementation science can play for moving evidence into practice for other realms of psychiatric care as well. To this end, the proposed roadmap can serve as a conceptual guiding template and framework through which various psychiatric services can methodically pursue timely implementation of evidence-based interventions for higher quality care and improved outcomes.

Preferences and decisional considerations relating to opioid agonist therapy among Ukrainian people who use drugs: A conjoint analysis survey

Scaling up opioid agonist therapies (OAT) is the most effective strategy to control combined HIV and opioid epidemics, especially in Eastern Europe and Central Asia (EECA), where HIV incidence and mortality continue to increase. Patient concerns about OAT, however, have undermined scale-up. The objective of this study is to understand Ukrainian opioid use disorder patient preferences about OAT to guide the development of an evidence-informed decision aid for clinical decision-making. We conducted a conjoint-based choice (CBC) survey. Participants were asked to about their preferences relating to 7 attributes of OAT (cost, dosing frequency, concerns about withdrawal symptoms, adverse side effects, improvements in quality of life, precipitation of withdrawal and legislative requirements to be registered as a drug dependent person) and 20 attribute levels for receiving OAT under differing potential treatment constraints. Data were analyzed using Hierarchical Bayesian models. Using respondent-driven sampling and random sampling, we recruited 2,028 people who inject drugs with opioid use disorder. Relative importance (RIS) and partial-worth utility scores (PWUS) were used to assess preferences for attributes and thresholds within each attribute. Cost and dosing frequency were the most important attributes (RIS = 39.2% and RIS = 25.2%, respectively) to potential patients, followed by concerns about withdrawal symptoms (RIS = 10.8%), adverse side effects (RIS = 9.0%), quality-of-life improvement (RIS = 7.5%), precipitation of euphoria (5.2%) and requirement to be registered as a drug- dependent person (RIS = 3.1%). The monthly cost-threshold for willingness-to-pay was 1,900 UAH ($70 USD). In Ukraine, where both governmental and private OAT clinics have emerged and provide markedly different delivery strategies, preferences are mostly driven by out-of-pocket expenses, despite many patients being willing to pay for OAT. Programmatic demands (flexibility and ease of acquiring medications) remain an important consideration while for a minority, clinical concerns about withdrawal symptoms, adverse side effects and OAT impact on life play a smaller role.

Factors Influencing Patient Receptivity to Brief Alcohol Interventions in Primary Care: An Application of Conjoint Analysis

Background: Brief alcohol interventions (BAIs) are an evidence-based practice for addressing hazardous alcohol use in primary care settings. However, numerous barriers to implementation of BAIs in routine practice have been identified, including concerns about patient receptivity to BAIs. Despite this being a commonly identified barrier to BAI implementation, little BAI implementation research has focused on patient receptivity. Objectives: This study aimed to identify the treatment preferences of primary care patients who screened positive for hazardous alcohol use and to evaluate factors that may influence patients' receptivity to BAIs delivered in primary care. We conducted a mailed survey of primary care patients (N = 245) who screened positive for hazardous alcohol use on annual screening measures based on electronic medical record data. Patients completed measures assessing treatment preferences and a conjoint analysis questionnaire designed to evaluate the relative importance of three factors (focus of the BAI, tailoring of the BAI, and familiarity with the provider delivering the BAI) for patient receptivity. Results: Conjoint analysis results revealed that familiarity with provider (with patients preferring BAIs delivered by providers they have previously met) was the most important factor in predicting patients' receptivity to BAIs. Additionally, patients preferred to discuss alcohol use in the context of another concern (focus of the BAI) and preferred personalized information tailored based on their specific health concerns (tailoring of the BAI), although these factors were not statistically significant when accounting for familiarity with provider. Conclusions: Findings of the present study have potential to inform future research on implementation of BAIs.

Preferences in medications for patients seeking treatment for opioid use disorder: A conjoint analysis

INTRODUCTION

The opioid epidemic continues to be a public health crisis that has worsened during the COVID-19 pandemic. Medications for opioid use disorder (MOUD) are the most effective way to reduce complications from opioid use disorder (OUD), but uptake is limited by both structural and individual factors. To inform strategies addressing individual factors, we evaluated patients' preferences and trade-offs in treatment decisions using conjoint analysis.

METHOD

We developed a conjoint analysis survey evaluating patients' preferences for FDA-approved MOUDs. We recruited patients with OUD presenting to initiate treatment. This survey included five attributes: induction, location and route of administration, impact on mortality, side effects, and withdrawal symptoms with cessation. Participants performed 12 choice sets, each with two hypothetical profiles and a "none" option. We used Hierarchical Bayes to identify relative importance of each attribute and part-worth utility scores of levels, which we compared using chi-squared analysis. We used the STROBE checklist to guide our reporting of this cross-sectional observational study.

RESULTS

Five-hundred and thirty participants completed the study. Location with route of administration was the most important attribute. Symptom relief during induction and withdrawal was a second priority. Mortality followed by side effects had lowest relative importance. Attribute levels with highest part-worth utilities showed patients preferred monthly pick-up from a pharmacy rather than daily supervised dosing; and oral medications more than injection/implants, despite the latter's infrequency.

CONCLUSION

We measured treatment preferences among patients seeking to initiate OUD treatment to inform strategies to scale MOUD treatment uptake. Patients prioritize the route of administration in treatment preference-less frequent pick up, but also injections and implants were less preferred despite their convenience. Second, patients prioritize symptom relief during the induction and withdrawal procedures of medication. These transition periods influence the sustainability of treatment. Although health professionals prioritize mortality, it did not drive decision-making for patients. To our knowledge, this is the largest study on patients' preferences for MOUD among treatment-seeking people with OUD to date. Future analysis will evaluate patient preference heterogeneity to further target program planning, counseling, and decision aid development.

Health System Transformation Playbook and Unified Care Model: an integrated design, systems & complexity thinking approach to health system transformation

Health system transformation is a complex journey that often results in unintended consequences. Existing methods to drive health system transformation have intrinsic limitations which impede successful implementation in local contexts. The Health System Transformation Playbook is a design-, systems-, and complexity-thinking enabled methodology to systematically design, prioritize and test health system and services transformation actions, anchored on iterative story telling, model building and pathfinding processes that tackles the scale of socially and technologically complex adaptive systems through time. The Unified Care Model and its associated cascade of models are examples of ongoing application of Health System Transformation Playbook in a regional population health system in Singapore. Use of Health System Transformation Playbook enables stewards of health systems to gain a more systematic and coherent understanding of health systems and services planning and organization development, to accelerate transformation towards people-centered, integrated and value-driven health systems.

Development of attributes and levels of mental health insurance services using a discrete choice experiment

BACKGROUND

Despite the fact that mental illness is among the ten top diseases with the highest burden, the health services required by these patients do not have adequate insurance coverage. The purpose of this study is to develop the attributes and levels of mental health insurance services using a discrete choice experiment (DCE).

MATERIALS AND METHOD

This study involved a qualitative phase of the DCE that was conducted in Iran in 2020-2021 and included several stages. First, during a literature review, the attributes and levels were determined. Then, the attributes of health insurance were identified and weighed through virtual and in-person interviews with 16 mental health insurance professionals and policymakers in this field who were selected by purposive sampling. Finally, after a few sessions, through review studies, interviews, and a group of the expert panel, attributes and levels were finalized.

RESULTS

This study showed that coverage of inpatient services, outpatient services, place of receiving services, use of online internet services, limitation of services, and monthly premiums were the most important attributes of mental health insurance services.

CONCLUSION

To promote mental health insurance, policymakers and health insurance organizations should pay attention to premiums to be commensurate with the payment of people, packages of mental health services, and the ability of people to pay in appropriation with inflation. Identifying these attributes can determine people's willingness to pay and preferences for mental health insurance and lead to better planning for more comprehensive coverage for patients and increase the desirability of individuals in receiving services.

Determinants of preference for telehealth versus in-person treatment for substance use disorders: A discrete choice experiment

INTRODUCTION

Access to substance use disorder (SUD) treatment remains a significant issue in the United States. Telehealth has potential for increasing access to services; however, it is underutilized in SUD treatment compared to mental health treatment. This study uses a discrete choice experiment (DCE) to examine stated preferences for telehealth (videoconferencing, text-based + video, text only) versus in-person SUD treatment (community-based, in-home) and the attributes (location, cost, therapist choice, wait time, evidence-based practices) most important when choosing between modalities. Subgroup analyses are reported about preference differences based on type of substance and substance use severity.

METHODS

Four hundred participants completed a survey containing a DCE with eighteen choice sets, the alcohol use disorders inventory test, drug abuse screening test, and a brief demographic questionnaire. The study collected data between April 15, 2020, and April 22, 2020. Conditional logit regression provided a measure of strength for participant preferences for technology-assisted treatment compared to in-person care. The study provides willingness to pay estimates as a real-world measure for the importance of each attribute in participants' decision-making.

RESULTS

Telehealth options that include a video conference option were equally preferrable to in-person care modalities. Text-only treatment was significantly less preferable to all other modalities of care. The ability to choose one's own therapist was a significant driver of treatment preference beyond modality, while wait time did not appear significant in making decisions. Participants with the most severe substance use differed in that they were open to text-based care without video conferencing, did not express a preference for evidence-based care, and valued therapist choice significantly more than those with only moderate substance use.

CONCLUSIONS

Telehealth for SUD treatment is equally preferable to in-person care offered in the community or at home, signifying preference is not a barrier for utilization. Text-only modalities may be enhanced by offering videoconference options for most individuals. Individuals with the most severe substance use issues may be willing to engage in text-based support without synchronous meetings with a provider. This approach may offer a less intensive method to engage individuals in treatment who may not otherwise access services.

Tailoring Implementation Strategies for Cardiovascular Disease Risk Calculator Adoption in Primary Care Clinics

INTRODUCTION

When implementing interventions in primary care, tailoring implementation strategies to practice barriers can be effective, but additional work is needed to understand how to best select these strategies. This study sought to identify clinicians' contributions to the process of tailoring implementation strategies to barriers in clinical settings.

METHODS

We conducted a modified nominal group exercise involving 8 implementation scientists and 26 primary care clinicians in the WWAMI region Practice and Research Network. Each group identified implementation strategies it felt would best address barriers to using a cardiovascular disease (CVD) risk calculator previously identified across 44 primary care clinics from the Healthy Hearts Northwest pragmatic trial (2015 to 2018). These barriers had been mapped beforehand to the Consolidated Framework for Implementation Research (CFIR) domains. We examined similarities and differences in the strategies that 30% or more of each group identified (agreed-on strategies) for each barrier and for barriers in each CFIR domain. We used the results to demonstrate how strategies might be tailored to individual clinics.

RESULTS

Clinicians selected 23 implementation strategies to address 1 or more of the 13 barriers; implementation scientists selected 35. The 2 groups agreed on at least 1 strategy for barriers in each CFIR domain: Inner Setting, Outer Setting, Intervention Characteristics, Characteristics of Individuals, and Process. Conducting local needs assessment and assessing for readiness/identifying barriers and facilitators were the 2 most common implementation strategies chosen only by clinicians.

CONCLUSIONS

Clinician stakeholders identified implementation strategies that augmented those chosen by implementation scientists, suggesting that codesign of implementation processes between implementation scientists and clinicians may strengthen the process of tailoring strategies to overcome implementation barriers.

Prioritizing evidence-based practices for acute respiratory distress syndrome using digital data: an iterative multi-stakeholder process

BACKGROUND

Evidence-based practices (EBPs) for patients receiving invasive mechanical ventilation vary in the quality of their underlying evidence and ease of implementation.

RESEARCH QUESTION

How do researchers and clinicians prioritize EBPs to help guide clinical decision-making and focus implementation efforts to improve patient care using existing, validated measures?

STUDY DESIGN AND METHODS

We developed a 4-step rapid method using existing criteria to prioritize EBPs associated with lower mortality and/or shorter duration of invasive mechanical ventilation for patients suffering from acute respiratory failure or acute respiratory distress syndrome. Using different types of data including surveys, we (1) identified relevant EBPs, (2) rated EBPs using the Guideline Implementability Appraisal (GLIA) tool, (3) surveyed practicing ICU clinicians from different hospital systems using a subset of GLIA criteria, and (4) developed metrics to assess EBP performance. In this paper, we describe steps 2 and 3.

RESULTS

In step 2, we prioritized 11 EBPs from an initial list of 30, using surveys and ratings among a small group of clinician researchers. In step 3, 42 clinicians from 8 different hospital systems provided assessments of these 11 EBPs which inform the final step of metric development.

INTERPRETATION

Our prioritization process allowed us to identify 11 EBPs out of a larger group that clinicians perceive is most likely to help optimize invasive mechanical ventilation and improve the outcomes of this vulnerable patient population. While this method was developed in critical care related to adults receiving invasive mechanical ventilation, it is adaptable to other health contexts.

Preferences Toward Attributes of Disease-Modifying Therapies: The Role of Nurses in Multiple Sclerosis Care

ABSTRACT

BACKGROUND: Nurses play an essential role in coordinating the care of patients with multiple sclerosis (MS) throughout their disease trajectory in a complex treatment landscape. The aim of this study was to assess nurses' preferences toward different disease-modifying therapy attributes. METHODS: We conducted a multicenter, noninterventional, cross-sectional study in collaboration with the Sociedad Española de Enfermería Neurológica. Nurses actively involved in MS care were invited to participate in the study. Prevention of disability progression, preservation of cognitive function, side effect profile and safety monitoring, and method of administration were the treatment attributes tested. Conjoint analysis was used to assess preferences in 8 simulated treatment options and rank them from most to least preferred. RESULTS: A total of 98 nurses were included in the study. The mean (SD) age was 44.7 (9.8) years, and 91.8% were female with a mean (SD) time of experience in MS care of 7.5 (5.4) years. Participants prioritized preservation of cognition (38.6%), followed by preventing disability progression (35.2%) and side effect risk and safety monitoring (13.5%). Route and frequency of administration were the least preferred attributes (7.4% and 5.3%, respectively). Estimated utilities were consistent across the sample according to sociodemographic and professional practice characteristics. CONCLUSIONS: Nurses' preferences toward treatments were mainly driven by efficacy attributes. This information may support the role of nurses in the multidisciplinary management of MS facilitating shared decision making.

Climate Smart Agriculture Implementation on Coffee Smallholders in Indonesia and Strategy to Accelerate

Sustainable coffee production is significantly threatened by climate change. While implementing CSA practices offers numerous benefits, adoption rates remain low. Coffee plantations are dominated by smallholders and located in rural areas, making them more complex and requiring a comprehensive analysis and intervention. This study used an exploratory approach to assess farmers’ preferences for CSA practices, identify barriers to implement, and design a support system model. The investigation focused on Arabica and Robusta farmers, with case studies from two Indonesian production centres. Preferences assessment used conjoint analysis, barriers evaluation used Mann–Whitney analysis, model development used synthetic approaches, and priority analysis used the Analytical Hierarchy Process. The study revealed that diversification is more desirable than cultivation, soil management, and water management. Arabica farmers preferred intercropping with annual crops, whereas Robusta farmers preferred perennials crops. Robusta farmers assessed that agricultural inputs, such as labor, capital, climatic data, and farm equipment and machinery, existed as barriers. However, these represent a lesser issue for Arabica farmers. We proposed agricultural innovation support system, consisting of innovation support facilities and services, as a comprehensive support system model to accelerate CSA implementation. Further analysis showed that the priority strategy for Arabica farmers is support services that focus on network development, while for Robusta farmers is support facilities that focus on climate information system development.

Co-designing implementation strategies for the WALK-Cph intervention in Denmark aimed at increasing mobility in acutely hospitalized older patients: a qualitative analysis of selected strategies and their justifications

BACKGROUND

Selecting appropriate strategies to target barriers to implementing interventions represents a considerable challenge in implementation research and practice. The aim was to investigate what categories of implementation strategies were selected by health care practitioners and their managers in a co-design process and how they justified these strategies aimed at facilitating the implementation of the WALK-Cph intervention.

METHODS

The study used a qualitative research design to explore what implementation strategies were selected and the justifications for selecting these strategies. Workshops were used because this qualitative method is particularly well suited for studying co-design processes that involve substantial attention to social interaction and the context. Data were 1) analyzed deductively based on the Proctor et al. taxonomy of implementation strategies, 2) categorized in accordance with the ERIC compilation of implementation strategies by Powell et al., and 3) analyzed to examine the justification for the selected strategies by the Proctor et al. framework for justifications of implementation strategies.

RESULTS

Thirteen different types of implementation strategies were chosen across two hospitals. The deductive analysis showed that selection of implementation strategies was based on pragmatic and theoretical justifications. The contents of the two types of justifications were thematized into nine subthemes.

CONCLUSION

This study contributes with knowledge about categories and justification of implementation strategies selected in a co-design process. In this study, implementation strategies were selected through pragmatic and theoretical justifications. This points to a challenge in balancing strategies based on practice-based and research-based knowledge and thereby selection of strategies with or without proven effectiveness.

Prioritizing guideline recommendations for implementation: a systematic, consumer-inclusive process with a case study using the Australian Clinical Guidelines for Stroke Management

BACKGROUND

Implementation of evidence-based care remains a key challenge in clinical practice. Determining "what" to implement can guide implementation efforts. This paper describes a process developed to identify priority recommendations from clinical guidelines for implementation, incorporating the perspectives of both consumers and health professionals. A case study is presented where the process was used to prioritize recommendations for implementation from the Australian Stroke Clinical Guidelines.

METHODS

The process was developed by a multidisciplinary group of researchers following consultation with experts in the field of implementation and stroke care in Australia. Use of the process incorporated surveys and facilitated workshops. Survey data were analysed descriptively; responses to ranking exercises were analysed via a graph theory-based voting system.

RESULTS

The four-step process to identify high-priority recommendations for implementation comprised the following: (1) identifying key implementation criteria, which included (a) reliability of the evidence underpinning the recommendation, (b) capacity to measure change in practice, (c) a recommendation-practice gap, (d) clinical importance and (e) feasibility of making the recommended changes; (2) shortlisting recommendations; (3) ranking shortlisted recommendations and (4) reaching consensus on top priorities. The process was applied to the Australian Stroke Clinical Guidelines between February 2019 and February 2020. Seventy-five health professionals and 16 consumers participated. Use of the process was feasible. Three recommendations were identified as priorities for implementation from over 400 recommendations.

CONCLUSION

It is possible to implement a robust process which involves consumers, clinicians and researchers to systematically prioritize guideline recommendations for implementation. The process is generalizable and could be applied in clinical areas other than stroke and in different geographical regions to identify implementation priorities. The identification of three clear priority recommendations for implementation from the Australian Stroke Clinical Guidelines will directly inform the development and delivery of national implementation strategies.

Assessing Pharmacists' Preferences towards Efficacy Attributes of Disease-Modifying Therapies in Relapsing-Remitting Multiple Sclerosis

Introduction: Hospital pharmacists are increasingly playing a critical role in the care of patients with multiple sclerosis (MS). However, little is known about their preferences and perspectives towards different attributes of disease-modifying therapies (DMTs). The objective of this research was to assess pharmacists´ preferences for DMT efficacy attributes. Methods: A multicenter, non-interventional, cross-sectional, web-based study was conducted. Preventing relapses, delaying disease progression, controlling radiological activity, and preserving health-related quality of life (HRQoL) and cognition were the attributes selected based on a literature review and a focus group with six hospital pharmacists. Conjoint analysis was used to determine preferences in eight hypothetical treatment scenarios, combining different levels of each attribute and ranking them from most to least preferred. Results: Sixty-five hospital pharmacists completed the study (mean age: 43.5 ± 7.8 years, 63.1% female, mean years of professional experience: 16.1 ± 7.4 years). Participants placed the greatest preference on delaying disease progression (35.7%) and preserving HRQoL (21.6%) and cognition (21.6%). Importance was consistent in all groups of pharmacists stratified according to demographic characteristics, experience, research background, and volume of patients seen per year. Conclusions: Understanding which treatment characteristics are meaningful to hospital pharmacists may help to enhance their synergistic role in the multidisciplinary management of patients with MS.

Identifying clinicians' priorities for the implementation of best practices in cognitive rehabilitation post-acquired brain injury

PURPOSE

To identify clinicians' perceptions of current levels of implementation of cognitive rehabilitation best practices, as well as individual and consensual group priorities for implementing cognitive rehabilitation interventions as part of a multi-site integrated knowledge translation initiative.

METHOD

A two-step consensus-building methodology was used, that is the Technique for Research of Information by Animation of a Group of Experts (TRIAGE), including a cross-sectional electronic survey followed by consensual in-person group discussions to identify implementation priorities from a list of evidence-based practices for cognitive rehabilitation following traumatic brain injury and stroke. Thirty-eight professionals from three rehabilitation teams (n = 9, 13 and 16) participated, including neuropsychologists, occupational therapists, speech-language pathologists, educators, clinical coordinators and program managers. Descriptive statistics were used to document the perceived levels of implementation as well as individual and consensual group priorities.

RESULTS

Most of the best practices (81-100%) were perceived as at least partially implemented by a minimum of 50% of the participants but only 20-25% of the practices were considered fully implemented. Findings suggest that current practices are mostly consistent with general cognitive rehabilitation principles suggested in guidelines but that further efforts are needed to support the application of specific cognitive rehabilitation strategies and interventions. Executive function and self-awareness retraining, as well as interventions promoting the generalization of skills, were among the highest implementation priorities. Consensual in-person group discussions, included as part of the TRIAGE process, also helped to define and operationalize these best practices into more specific intervention components according to the teams' needs and priorities.

CONCLUSIONS

TRIAGE consensus-building methodology can be used to engage stakeholders and support clinicians' decision-making regarding the identification of implementation priorities in cognitive rehabilitation post-ABI in order to tailor the implementation process to local needs.IMPLICATIONS FOR REHABILITATIONThe Technique for Research of Information by Animation of a Group of Experts (TRIAGE) can be used to support clinicians' decision-making regarding the identification of implementation priorities in cognitive rehabilitation post-ABI.The combination of individual consultations followed by consensual in-person group discussions, as part of the TRIAGE process, may help clinicians in defining and operationalizing best practices into more specific intervention components to implement.Effective implementation strategies are needed to support the use of specific cognitive rehabilitation interventions in prioritized areas, such as executive function and self-awareness retraining, as well as generalization of skills.Some differences in clinicians' perceived priorities point up the importance of tailoring implementation to local needs and contexts from the early stages in the process.

Using Conjoint Analysis to Investigate Hospital Directors' Preference in Adoption of an Evidence-based Intervention

This study used conjoint analysis, a marketing research technique, to investigate hospital stakeholders' decision-making in adoption of evidence-based interventions (EBI). An efficacious hospital-based stigma-reduction intervention was used as a "product" to study adoption of EBI. Sixty hospital directors in Fujian, China evaluated the likelihood of adopting the EBI in their hospitals by rating across eight hypothetical scenarios with preferred and non-preferred levels of seven attributes, including 1) administrative support, 2) cost, 3) personnel involvement, 4) format, 5) duration, 6) technical support, and 7) priority alignment with the hospital. A hierarchical generalized linear model was fit to the likelihood of intervention adoption for the eight scenarios, with the seven attributes served as independent variables. Monetary cost of intervention implementation (impact score=2.12) had the greatest impact on the directors' reported likelihood of adopting the EBI, followed by duration of the intervention (impact score=0.88), availability of technical support (impact score=0.69), and flexibility of format (impact score=0.36). The impact scores of other attributes were not statistically significant. Conjoint analysis was feasible in modeling hospital directors' decision-making in adoption of EBI. The findings suggested the importance of considering cost, duration, technical support, and flexibility of format in development and dissemination of interventions in healthcare settings.

Modeling the Decision of Mental Health Providers to Implement Evidence-Based Children's Mental Health Services: A Discrete Choice Conjoint Experiment

Using an online, cross sectional discrete choice experiment, we modeled the influence of 14 implementation attributes on the intention of 563 providers to adopt hypothetical evidence-based children’s mental health practices (EBPs). Latent class analysis identified two segments. Segment 1 (12%) would complete 100% of initial training online, devote more time to training, make greater changes to their practices, and introduce only minor modifications to EBPs. Segment 2 (88%) preferred fewer changes, more modifications, less training, but more follow-up. Simulations suggest that enhanced supervisor support would increase the percentage of participants choosing the intensive training required to implement EBPs. The dissemination of EBPs needs to consider the views of segments of service providers with differing preferences regarding EBPs and implementation process design.

Enhancing the Impact of Implementation Strategies in Healthcare: A Research Agenda

The field of implementation science was developed to better understand the factors that facilitate or impede implementation and generate evidence for implementation strategies. In this article, we briefly review progress in implementation science, and suggest five priorities for enhancing the impact of implementation strategies. Specifically, we suggest the need to: (1) enhance methods for designing and tailoring implementation strategies; (2) specify and test mechanisms of change; (3) conduct more effectiveness research on discrete, multi-faceted, and tailored implementation strategies; (4) increase economic evaluations of implementation strategies; and (5) improve the tracking and reporting of implementation strategies. We believe that pursuing these priorities will advance implementation science by helping us to understand when, where, why, and how implementation strategies improve implementation effectiveness and subsequent health outcomes.

Methods to Improve the Selection and Tailoring of Implementation Strategies

Implementing behavioral health interventions is a complicated process. It has been suggested that implementation strategies should be selected and tailored to address the contextual needs of a given change effort; however, there is limited guidance as to how to do this. This article proposes four methods (concept mapping, group model building, conjoint analysis, and intervention mapping) that could be used to match implementation strategies to identified barriers and facilitators for a particular evidence-based practice or process change being implemented in a given setting. Each method is reviewed, examples of their use are provided, and their strengths and weaknesses are discussed. The discussion includes suggestions for future research pertaining to implementation strategies and highlights these methods' relevance to behavioral health services and research.

Innovation Implementation in the Context of Hospital QI: Lessons Learned and Strategies for Success

In 1999, the Institute of Medicine reported that 98,000 people die each year due to medical errors. In the following years, the focus on hospital quality was intensified nationally, with policymakers providing evidence-based practice guidelines for improving health care quality. However, these innovations (evidence-based guidelines) that were being produced at policy levels were not translating to clinical practice at the hospital organizational level easily, and stark variations continued to persist, in the quality of health care. Circa 2009, nearly a decade after the release of the IOM report, the health care organizational literature began referring to this challenge as "innovation implementation failure" in health care organizations (HCOs), ie, failure to implement an evidence-based practice that is new to a HCO. This stream of literature drew upon management research to explain why innovation implementation failure occurs in HCOs and what could be done to prevent it. This paper conducts an integrative review of the literature on "innovation implementation" in hospitals and health systems over the last decade, since the spotlight was cast on "innovation implementation failure" in HCOs. The review reveals that while some studies have retrospectively sought to identify the key drivers of innovation implementation, through surveys and interviews of practitioners (the "what"), other studies have prospectively sought to understand how innovation implementation occurs in hospitals and health systems (the "how"). Both make distinctive contributions to identifying strategies for success in innovation implementation. While retrospective studies have helped identify the key drivers of innovation implementation, prospective studies have shed light on how these drivers could be attained, thereby helping to develop context-sensitive management strategies for success. The literature has called for more prospective research on the implementation and sustainability of health care innovations. This paper summarizes the lessons learned from the literature, discusses the relevance of management research on innovation implementation in HCOs, and identifies future research avenues.

Application of discrete choice experiments to enhance stakeholder engagement as a strategy for advancing implementation: a systematic review

Background

One of the key strategies to successful implementation of effective health-related interventions is targeting improvements in stakeholder engagement. The discrete choice experiment (DCE) is a stated preference technique for eliciting individual preferences over hypothetical alternative scenarios that is increasingly being used in health-related applications. DCEs are a dynamic approach to systematically measure health preferences which can be applied in enhancing stakeholder engagement. However, a knowledge gap exists in characterizing the extent to which DCEs are used in implementation science.

Methods

We conducted a systematic literature search (up to December 2016) of the English literature to identify and describe the use of DCEs in engaging stakeholders as an implementation strategy. We searched the following electronic databases: MEDLINE, Econlit, PsychINFO, and the CINAHL using mesh terms. Studies were categorized according to application type, stakeholder(s), healthcare setting, and implementation outcome.

Results

Seventy-five publications were selected for analysis in this systematic review. Studies were categorized by application type: (1) characterizing demand for therapies and treatment technologies (n = 32), (2) comparing implementation strategies (n = 22), (3) incentivizing workforce participation (n = 11), and (4) prioritizing interventions (n = 10). Stakeholders included providers (n = 27), patients (n = 25), caregivers (n = 5), and administrators (n = 2). The remaining studies (n = 16) engaged multiple stakeholders (i.e., combination of patients, caregivers, providers, and/or administrators). The following implementation outcomes were discussed: acceptability (n = 75), appropriateness (n = 34), adoption (n = 19), feasibility (n = 16), and fidelity (n = 3).

Conclusions

The number of DCE studies engaging stakeholders as an implementation strategy has been increasing over the past decade. As DCEs are more widely used as a healthcare assessment tool, there is a wide range of applications for them in stakeholder engagement. The DCE approach could serve as a tool for engaging stakeholders in implementation science.

Electronic supplementary material

The online version of this article (10.1186/s13012-017-0675-8) contains supplementary material, which is available to authorized users.

Priorities for Closing the Evidence-Practice Gaps in Poststroke Aphasia Rehabilitation: A Scoping Review

OBJECTIVE

To identify implementation priorities for poststroke aphasia management relevant to the Australian health care context.

DATA SOURCES

Using systematized searches of databases (CINAHL and MEDLINE), guideline and stroke websites, and other sources, evidence was identified and extracted for 7 implementation criteria for 13 topic areas relevant to aphasia management. These 7 priority-setting criteria were identified in the implementation literature: strength of the evidence, current evidence-practice gap, clinician preference, patient preference, modifiability, measurability, and health effect.

STUDY SELECTION

Articles were included if they were in English, related to a specific recommendation requiring implementation, and contained information pertaining to any of the 7 prioritization criteria.

DATA EXTRACTION

The scoping review methodology was chosen to address the broad nature of the topic. Evidence was extracted and placed in an evidence matrix. After this, evidence was summarized and then aphasia rehabilitation topics were prioritized using an approach developed by the research team.

DATA SYNTHESIS

Evidence from 100 documents was extracted and summarized. Four topic areas were identified as implementation priorities for aphasia: timing, amount, and intensity of therapy; goal setting; information, education, and aphasia-friendly information; and constraint-induced language therapy.

CONCLUSIONS

Closing the evidence-practice gaps in the 4 priority areas identified may deliver the greatest gains in outcomes for Australian stroke survivors with aphasia. Our approach to developing implementation priorities may be useful for identifying priorities for implementation in other health care areas.

Methods to Improve the Selection and Tailoring of Implementation Strategies

Implementing behavioral health interventions is a complicated process. It has been suggested that implementation strategies should be selected and tailored to address the contextual needs of a given change effort; however, there is limited guidance as to how to do this. This article proposes four methods (concept mapping, group model building, conjoint analysis, and intervention mapping) that could be used to match implementation strategies to identified barriers and facilitators for a particular evidence-based practice or process change being implemented in a given setting. Each method is reviewed, examples of their use are provided, and their strengths and weaknesses are discussed. The discussion includes suggestions for future research pertaining to implementation strategies and highlights these methods' relevance to behavioral health services and research.

A systematic review of implementation frameworks of innovations in healthcare and resulting generic implementation framework

BACKGROUND

Implementation science and knowledge translation have developed across multiple disciplines with the common aim of bringing innovations to practice. Numerous implementation frameworks, models, and theories have been developed to target a diverse array of innovations. As such, it is plausible that not all frameworks include the full range of concepts now thought to be involved in implementation. Users face the decision of selecting a single or combining multiple implementation frameworks. To aid this decision, the aim of this review was to assess the comprehensiveness of existing frameworks.

METHODS

A systematic search was undertaken in PubMed to identify implementation frameworks of innovations in healthcare published from 2004 to May 2013. Additionally, titles and abstracts from Implementation Science journal and references from identified papers were reviewed. The orientation, type, and presence of stages and domains, along with the degree of inclusion and depth of analysis of factors, strategies, and evaluations of implementation of included frameworks were analysed.

RESULTS

Frameworks were assessed individually and grouped according to their targeted innovation. Frameworks for particular innovations had similar settings, end-users, and 'type' (descriptive, prescriptive, explanatory, or predictive). On the whole, frameworks were descriptive and explanatory more often than prescriptive and predictive. A small number of the reviewed frameworks covered an implementation concept(s) in detail, however, overall, there was limited degree and depth of analysis of implementation concepts. The core implementation concepts across the frameworks were collated to form a Generic Implementation Framework, which includes the process of implementation (often portrayed as a series of stages and/or steps), the innovation to be implemented, the context in which the implementation is to occur (divided into a range of domains), and influencing factors, strategies, and evaluations.

CONCLUSIONS

The selection of implementation framework(s) should be based not solely on the healthcare innovation to be implemented, but include other aspects of the framework's orientation, e.g., the setting and end-user, as well as the degree of inclusion and depth of analysis of the implementation concepts. The resulting generic structure provides researchers, policy-makers, health administrators, and practitioners a base that can be used as guidance for their implementation efforts.

The preferences of users of electronic medical records in hospitals: quantifying the relative importance of barriers and facilitators of an innovation

Background

Currently electronic medical records (EMRs) are implemented in hospitals, because of expected benefits for quality and safety of care. However the implementation processes are not unproblematic and are slower than needed. Many of the barriers and facilitators of the adoption of EMRs are identified, but the relative importance of these factors is still undetermined. This paper quantifies the relative importance of known barriers and facilitators of EMR, experienced by the users (i.e., nurses and physicians in hospitals).

Methods

A discrete choice experiment (DCE) was conducted among physicians and nurses. Participants answered ten choice sets containing two scenarios. Each scenario included attributes that were based on previously identified barriers in the literature: data entry hardware, technical support, attitude head of department, performance feedback, flexibility of interface, and decision support. Mixed Multinomial Logit analysis was used to determine the relative importance of the attributes.

Results

Data on 148 nurses and 150 physicians showed that high flexibility of the interface was the factor with highest relative importance in their preference to use an EMR. For nurses this attribute was followed by support from the head of department, presence of performance feedback from the EMR and presence of decisions support. While for physicians this ordering was different: presence of decision support was relatively more important than performance feedback and support from the head of department.

Conclusion

Considering the prominent wish of all the intended users for a flexible interface, currently used EMRs only partially comply with the needs of the users, indicating the need for closer incorporation of user needs during development stages of EMRs. The differences in priorities amongst nurses and physicians show that different users have different needs during the implementation of innovations. Hospital management may use this information to design implementation trajectories to fit the needs of various user groups.

Developing attributes and attribute-levels for a discrete choice experiment on micro health insurance in rural Malawi

Background

Discrete choice experiments (DCEs) are attribute-driven experimental techniques used to elicit stakeholders’ preferences to support the design and implementation of policy interventions. The validity of a DCE, therefore, depends on the appropriate specification of the attributes and their levels. There have been recent calls for greater rigor in implementing and reporting on the processes of developing attributes and attribute-levels for discrete choice experiments (DCEs). This paper responds to such calls by carefully reporting a systematic process of developing micro health insurance attributes and attribute-levels for the design of a DCE in rural Malawi.

Methods

Conceptual attributes and attribute-levels were initially derived from a literature review which informed the design of qualitative data collection tools to identify context specific attributes and attribute-levels. Qualitative data was collected in August-September 2012 from 12 focus group discussions with community residents and 8 in-depth interviews with health workers. All participants were selected according to stratified purposive sampling. The material was tape-recorded, fully transcribed, and coded by three researchers to identify context-specific attributes and attribute-levels. Expert opinion was used to scale down the attributes and levels. A pilot study confirmed the appropriateness of the selected attributes and levels for a DCE.

Results

First, a consensus, emerging from an individual level analysis of the qualitative transcripts, identified 10 candidate attributes. Levels were assigned to all attributes based on data from transcripts and knowledge of the Malawian context, derived from literature. Second, through further discussions with experts, four attributes were discarded based on multiple criteria. The 6 remaining attributes were: premium level, unit of enrollment, management structure, health service benefit package, transportation coverage and copayment levels. A final step of revision and piloting confirmed that the retained attributes satisfied the credibility criteria of DCE attributes.

Conclusion

This detailed description makes our attribute development process transparent, and provides the reader with a basis to assess the rigor of this stage of constructing the DCE. This paper contributes empirical evidence to the limited methodological literature on attributes and levels development for DCE, thereby providing further empirical guidance on the matter, specifically within rural communities of low- and middle-income countries.