Multiple perspectives on clinical decision support: a qualitative study of fifteen clinical and vendor organizations

Designing the User Interface of a Nitroglycerin Dose Titration Decision Support System: User-Centered Design Study

BACKGROUND

 Nurses adjust intravenous nitroglycerin infusions to provide acute relief for angina by manually increasing or decreasing the dosage. However, titration can pose challenges, as excessively high doses can lead to hypotension, and low doses may result in inadequate pain relief. Clinical decision support systems (CDSSs) that predict changes in blood pressure for nitroglycerin dose adjustments may assist nurses with titration.

OBJECTIVE

 This study aimed to design a user interface for a CDSS for nitroglycerin dose titration (Nitroglycerin Dose Titration Decision Support System [nitro DSS]).

METHODS

 A user-centered design (UCD) approach, consisting of an initial qualitative study with semistructured interviews to identify design specifications for prototype development, was used. This was followed by three iterative rounds of usability testing. Nurses with experience titrating nitroglycerin infusions in coronary care units participated.

RESULTS

 A total of 20 nurses participated, including 7 during the qualitative study and 15 during usability testing (2 nurses participated in both phases). Analysis of the qualitative data revealed four themes for the interface design to be (1) clear and consistent, (2) vigilant, (3) interoperable, and (4) reliable. The major elements of the final prototype included a feature for viewing the predicted and actual blood pressure over time to determine the reliability of the predictions, a drop-down option to report patient side effects, a feature to report reasons for not accepting the prediction, and a visual alert indicating any systolic blood pressure predictions below 90 mm Hg. Nurses' ratings on the questionnaires indicated excellent usability and acceptability of the final nitro DSS prototype.

CONCLUSION

 This study successfully applied a UCD approach to collaborate with nurses in developing a user interface for the nitro DSS that supports the clinical decision-making of nurses titrating nitroglycerin.

Development and Integration of Machine Learning Algorithm to Identify Peripheral Arterial Disease: Multistakeholder Qualitative Study

BACKGROUND

Machine learning (ML)-driven clinical decision support (CDS) continues to draw wide interest and investment as a means of improving care quality and value, despite mixed real-world implementation outcomes.

OBJECTIVE

This study aimed to explore the factors that influence the integration of a peripheral arterial disease (PAD) identification algorithm to implement timely guideline-based care.

METHODS

A total of 12 semistructured interviews were conducted with individuals from 3 stakeholder groups during the first 4 weeks of integration of an ML-driven CDS. The stakeholder groups included technical, administrative, and clinical members of the team interacting with the ML-driven CDS. The ML-driven CDS identified patients with a high probability of having PAD, and these patients were then reviewed by an interdisciplinary team that developed a recommended action plan and sent recommendations to the patient's primary care provider. Pseudonymized transcripts were coded, and thematic analysis was conducted by a multidisciplinary research team.

RESULTS

Three themes were identified: positive factors translating in silico performance to real-world efficacy, organizational factors and data structure factors affecting clinical impact, and potential challenges to advancing equity. Our study found that the factors that led to successful translation of in silico algorithm performance to real-world impact were largely nontechnical, given adequate efficacy in retrospective validation, including strong clinical leadership, trustworthy workflows, early consideration of end-user needs, and ensuring that the CDS addresses an actionable problem. Negative factors of integration included failure to incorporate the on-the-ground context, the lack of feedback loops, and data silos limiting the ML-driven CDS. The success criteria for each stakeholder group were also characterized to better understand how teams work together to integrate ML-driven CDS and to understand the varying needs across stakeholder groups.

CONCLUSIONS

Longitudinal and multidisciplinary stakeholder engagement in the development and integration of ML-driven CDS underpins its effective translation into real-world care. Although previous studies have focused on the technical elements of ML-driven CDS, our study demonstrates the importance of including administrative and operational leaders as well as an early consideration of clinicians' needs. Seeing how different stakeholder groups have this more holistic perspective also permits more effective detection of context-driven health care inequities, which are uncovered or exacerbated via ML-driven CDS integration through structural and organizational challenges. Many of the solutions to these inequities lie outside the scope of ML and require coordinated systematic solutions for mitigation to help reduce disparities in the care of patients with PAD.

Usability of the IDDEAS prototype in child and adolescent mental health services: A qualitative study for clinical decision support system development

Introduction

Child and adolescent mental health services (CAMHS) clinical decision support system (CDSS) provides clinicians with real-time support as they assess and treat patients. CDSS can integrate diverse clinical data for identifying child and adolescent mental health needs earlier and more comprehensively. Individualized Digital Decision Assist System (IDDEAS) has the potential to improve quality of care with enhanced efficiency and effectiveness.

Methods

We examined IDDEAS usability and functionality in a prototype for attention deficit hyperactivity disorder (ADHD), using a user-centered design process and qualitative methods with child and adolescent psychiatrists and clinical psychologists. Participants were recruited from Norwegian CAMHS and were randomly assigned patient case vignettes for clinical evaluation, with and without IDDEAS. Semi-structured interviews were conducted as one part of testing the usability of the prototype following a five-question interview guide. All interviews were recorded, transcribed, and analyzed following qualitative content analysis.

Results

Participants were the first 20 individuals from the larger IDDEAS prototype usability study. Seven participants explicitly stated a need for integration with the patient electronic health record system. Three participants commended the step-by-step guidance as potentially helpful for novice clinicians. One participant did not like the aesthetics of the IDDEAS at this stage. All participants were pleased about the display of the patient information along with guidelines and suggested that wider guideline coverage will make IDDEAS much more useful. Overall, participants emphasized the importance of maintaining the clinician as the decision-maker in the clinical process, and the overall potential utility of IDDEAS within Norwegian CAMHS.

Conclusion

Child and adolescent mental health services psychiatrists and psychologists expressed strong support for the IDDEAS clinical decision support system if better integrated in daily workflow. Further usability assessments and identification of additional IDDEAS requirements are necessary. A fully functioning, integrated version of IDDEAS has the potential to be an important support for clinicians in the early identification of risks for youth mental disorders and contribute to improved assessment and treatment of children and adolescents.

Stakeholder Perspectives of Clinical Artificial Intelligence Implementation: Systematic Review of Qualitative Evidence

BACKGROUND

The rhetoric surrounding clinical artificial intelligence (AI) often exaggerates its effect on real-world care. Limited understanding of the factors that influence its implementation can perpetuate this.

OBJECTIVE

In this qualitative systematic review, we aimed to identify key stakeholders, consolidate their perspectives on clinical AI implementation, and characterize the evidence gaps that future qualitative research should target.

METHODS

Ovid-MEDLINE, EBSCO-CINAHL, ACM Digital Library, Science Citation Index-Web of Science, and Scopus were searched for primary qualitative studies on individuals' perspectives on any application of clinical AI worldwide (January 2014-April 2021). The definition of clinical AI includes both rule-based and machine learning-enabled or non-rule-based decision support tools. The language of the reports was not an exclusion criterion. Two independent reviewers performed title, abstract, and full-text screening with a third arbiter of disagreement. Two reviewers assigned the Joanna Briggs Institute 10-point checklist for qualitative research scores for each study. A single reviewer extracted free-text data relevant to clinical AI implementation, noting the stakeholders contributing to each excerpt. The best-fit framework synthesis used the Nonadoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) framework. To validate the data and improve accessibility, coauthors representing each emergent stakeholder group codeveloped summaries of the factors most relevant to their respective groups.

RESULTS

The initial search yielded 4437 deduplicated articles, with 111 (2.5%) eligible for inclusion (median Joanna Briggs Institute 10-point checklist for qualitative research score, 8/10). Five distinct stakeholder groups emerged from the data: health care professionals (HCPs), patients, carers and other members of the public, developers, health care managers and leaders, and regulators or policy makers, contributing 1204 (70%), 196 (11.4%), 133 (7.7%), 129 (7.5%), and 59 (3.4%) of 1721 eligible excerpts, respectively. All stakeholder groups independently identified a breadth of implementation factors, with each producing data that were mapped between 17 and 24 of the 27 adapted Nonadoption, Abandonment, Scale-up, Spread, and Sustainability subdomains. Most of the factors that stakeholders found influential in the implementation of rule-based clinical AI also applied to non-rule-based clinical AI, with the exception of intellectual property, regulation, and sociocultural attitudes.

CONCLUSIONS

Clinical AI implementation is influenced by many interdependent factors, which are in turn influenced by at least 5 distinct stakeholder groups. This implies that effective research and practice of clinical AI implementation should consider multiple stakeholder perspectives. The current underrepresentation of perspectives from stakeholders other than HCPs in the literature may limit the anticipation and management of the factors that influence successful clinical AI implementation. Future research should not only widen the representation of tools and contexts in qualitative research but also specifically investigate the perspectives of all stakeholder HCPs and emerging aspects of non-rule-based clinical AI implementation.

TRIAL REGISTRATION

PROSPERO (International Prospective Register of Systematic Reviews) CRD42021256005; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=256005.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/33145.

Barriers and enablers to implementing and using clinical decision support systems for chronic diseases: a qualitative systematic review and meta-aggregation

BACKGROUND

Clinical decision support (CDS) is increasingly used to facilitate chronic disease care. Despite increased availability of electronic health records and the ongoing development of new CDS technologies, uptake of CDS into routine clinical settings is inconsistent. This qualitative systematic review seeks to synthesise healthcare provider experiences of CDS-exploring the barriers and enablers to implementing, using, evaluating, and sustaining chronic disease CDS systems.

METHODS

A search was conducted in Medline, CINAHL, APA PsychInfo, EconLit, and Web of Science from 2011 to 2021. Primary research studies incorporating qualitative findings were included if they targeted healthcare providers and studied a relevant chronic disease CDS intervention. Relevant CDS interventions were electronic health record-based and addressed one or more of the following chronic diseases: cardiovascular disease, diabetes, chronic kidney disease, hypertension, and hypercholesterolaemia. Qualitative findings were synthesised using a meta-aggregative approach.

RESULTS

Thirty-three primary research articles were included in this qualitative systematic review. Meta-aggregation of qualitative data revealed 177 findings and 29 categories, which were aggregated into 8 synthesised findings. The synthesised findings related to clinical context, user, external context, and technical factors affecting CDS uptake. Key barriers to uptake included CDS systems that were simplistic, had limited clinical applicability in multimorbidity, and integrated poorly into existing workflows. Enablers to successful CDS interventions included perceived usefulness in providing relevant clinical knowledge and structured chronic disease care; user confidence gained through training and post training follow-up; external contexts comprised of strong clinical champions, allocated personnel, and technical support; and CDS technical features that are both highly functional, and attractive.

CONCLUSION

This systematic review explored healthcare provider experiences, focussing on barriers and enablers to CDS use for chronic diseases. The results provide an evidence-base for designing, implementing, and sustaining future CDS systems. Based on the findings from this review, we highlight actionable steps for practice and future research.

TRIAL REGISTRATION

PROSPERO CRD42020203716.

The Homeless People in China During the COVID-19 Pandemic: Victims of the Strict Pandemic Control Measures of the Government

Background: By implementing aggressive control measures, China has rapidly and effectively controlled the Coronavirus disease 2019 (COVID-19) pandemic. However, the neglected homeless population may become victims of that perceived success. Due to political sensitivity, we know little about them. Aims: This study aimed to investigate how the pandemic and the pandemic control strategies of the government affected the lives of the homeless people in mainland China. Methods: A total of 103 eligible participants experiencing absolute homelessness were recruited from Guangzhou City during July and August 2020. Surveys measured demographic characteristics including health status, changes in daily living, and actions of the government toward the homeless during the pandemic. Sankey diagrams and ordered logit regression models were used to examine the impact on the homeless of inhumane government efforts to drive the homeless away. Qualitative materials were analyzed by using an inductive approach to provide more details. Results: First, the homeless people in Guangzhou tended to be male, aged 40 to 64 years, less well-educated, and they originated from outside Guangdong although they were living in the city center. Most had little connection with their families. After a long period of homelessness, almost half of the participants were in poor health with various conditions, which made them extremely vulnerable to COVID-19. Second, the pandemic caused a substantial decline in incomes of homeless people, had less of a negative impact on their food intake, and affected sleep time in different ways. Third, during the COVID-19 pandemic, humanitarian aid from local governments of China decreased, whereas inhumane efforts to drive the homeless away intensified. Fourth, quantitative models and qualitative materials demonstrate the devastating effect of the strict pandemic control strategy of the government on the lives of homeless people, which may further cause their health problems. Conclusion: This study for the first time illustrated the characteristic features of the street homeless population in mainland China and their living situation during the COVID-19 pandemic, and most importantly demonstrated the devastating effect of the strict pandemic control of the government, which has been considered a great success in previous studies, on lives of homeless people. Urgent measures should be taken to ensure the protection of the homeless population and prevent an impending humanitarian crisis.

A qualitative study of provider burnout: do medical scribes hinder or help?

Objective

Provider burnout is a crisis in healthcare and leads to medical errors, a decrease in patient satisfaction, and provider turnover. Many feel that the increased use of electronic health records contributes to the rate of burnout. To avoid provider burnout, many organizations are hiring medical scribes. The goal of this study was to identify relevant elements of the provider–scribe relationship (like decreasing documentation burden, extending providers’ careers, and preventing retirement) and describe how and to what extent they may influence provider burnout.

Materials and Methods

Qualitative methods were used to gain a broad view of the complex landscape surrounding scribes. Data were collected in 3 phases between late 2017 and early 2019. Data from 5 site visits, interviews with medical students who had experience as scribes, and discussions at an expert conference were analyzed utilizing an inductive approach.

Results

A total of 184 transcripts were analyzed to identify patterns and themes related to provider burnout. Provider burnout leads to increased provider frustration and exhaustion. Providers reported that medical scribes improve provider job satisfaction and reduce burnout because they reduce the documentation burden. Medical scribes extend providers’ careers and may prevent early retirement. Unfortunately, medical scribes themselves may experience similar forms of burnout.

Conclusion

Our data from providers and managers suggest that medical scribes help to reduce provider burnout. However, scribes are not the only solution for reducing documentation burden and there may be potentially better options for preventing burnout. Interestingly, medical scribes sometimes suffer from burnout themselves, despite their temporary roles.

The future of medical scribes documenting in the electronic health record: results of an expert consensus conference

BACKGROUND

With the use of electronic health records (EHRs) increasing and causing unintended negative consequences, the medical scribe profession has burgeoned, but it has yet to be regulated. The purpose of this study was to describe scribe workflow as well as identify the threats and opportunities for the future of the scribe industry.

METHODS

The first phase of the study used ethnographic methods consisting of interviews and observations by a multi-disciplinary team of researchers at five United States sites. In April 2019, a two-day conference of experts representing different stakeholder perspectives was held to discuss the results from site visits and to predict the future of medical scribing. An interpretive content analysis approach was used to discover threats and opportunities for the future of medical scribes.

RESULTS

Threats facing the medical scribe industry were related to changes in the documentation model, EHR usability, different payment structures, the need to acquire disparate data during clinical encounters, and workforce-related changes relevant to the scribing model. Simultaneously, opportunities for medical scribing in the future included extension of their role to include workflow analysis, acting as EHR-related subject-matter-experts, and becoming integrated more effectively into the clinical care delivery team. Experts thought that if EHR usability increases, the need for medical scribes might decrease. Additionally, the scribe role could be expanded to allow scribes to document more or take on more informatics-related tasks. The experts also anticipated an increased use of alternative models of scribing, like tele-scribing.

CONCLUSION

Threats and opportunities for medical scribing were identified. Many experts thought that if the scribe role could be expanded to allow scribes to document more or take on more informatics activities, it would be beneficial. With COVID-19 continuing to change workflows, it is critical that medical scribes receive standardized training as tele-scribing continues to grow in popularity and new roles for scribes as medical team members are identified.

How can we partner with electronic health record vendors on the complex journey to safer health care?

The Office of the National Coordinator for Health Information Technology released the Safety Assurance Factors for EHR Resilience (SAFER) guides in 2014. Our group developed these guides covering key facets of both electronic health record (EHR) infrastructure (eg, system configuration, contingency planning for downtime, and system-to-system interfaces) and clinical processes (eg, computer-based provider order entry with clinical decision support, test result reporting, patient identification, and clinician-to-clinician communication). The SAFER guides encourage healthy relationships between EHR vendors and users. We conducted a qualitative study over 12 months. We visited 9 health care organizations ranging in size from 1-doctor outpatient clinics to large, multisite, multihospital integrated delivery networks. We interviewed and observed clinicians, IT professionals, and administrators. From the interview transcripts and observation field notes, we identified overarching themes: technical functionality, usability, standards, testing, workflow processes, personnel to support implementation and use, infrastructure, and clinical content. In addition, we identified health care organization-EHR vendor working relationships: marine drill sergeant, mentor, development partner, seller, and parasite. We encourage health care organizations and EHR vendors to develop healthy working relationships to help address the tasks required to design, develop, implement, and maintain EHRs required to achieve safer and higher quality health care.

Digitizing Infectious Disease Clinical Guidelines for Improved Clinician Satisfaction

The purpose of this project was to implement an improved rapid-deployment clinical decision support strategy for the detection and treatment of emerging and reemerging infectious diseases within an electronic health record informed by end-user satisfaction. After a review of the evidence and comprehensive workflow assessments, interdisciplinary focus groups were assembled to determine current infectious disease needs within the electronic health record and what guidance should be provided to clinicians to assist in making the best decisions for both patient care and population health. Education and reeducation issues were handled throughout the implementation process. Using the Plan-Do-Study-Act quality improvement framework for rapid cycle deployment, the design was implemented and monitored. To evaluate efficacy and clinician satisfaction of the implementation, presurvey and postsurvey measurements were employed. The Clinical Information System Implementation Evaluation Scale was used, along with demographic and qualitative textual questions, to evaluate clinician satisfaction. Findings indicate the implementation was successful (P < .05).

A Sociotechnical Multiple Perspectives Approach to the Use of Medical Scribes: A Deeper Dive into the Scribe-Provider Interaction

Because of increased electronic health record use, many organizations are hiring medical scribes as a way to alleviate provider burnout and increase clinical efficiency. The providers and scribes have unique relationships and thus, this study's purpose was to examine the scribe-provider interaction/relationship through the perspectives of scribes, providers, and administrators utilizing qualitative research techniques. Participants included 81 clinicians (30 providers, 27 scribes, and 24 administrators) across five sites. Analysis of the scribe-provider interaction data generated six subthemes: characteristics of an ideal scribe, characteristics of a good provider, provider variability, quality of the scribe-provider relationship, negative side of the scribe-provider relationship, and evaluation and supervision of scribes. Future research should focus on additional facets of the scribe-provider relationship including optimal ergonomic considerations to allow for scribes and providers to work together harmoniously.

Clinical decision support alert malfunctions: analysis and empirically derived taxonomy

Objective

To develop an empirically derived taxonomy of clinical decision support (CDS) alert malfunctions.

Materials and Methods

We identified CDS alert malfunctions using a mix of qualitative and quantitative methods: (1) site visits with interviews of chief medical informatics officers, CDS developers, clinical leaders, and CDS end users; (2) surveys of chief medical informatics officers; (3) analysis of CDS firing rates; and (4) analysis of CDS overrides. We used a multi-round, manual, iterative card sort to develop a multi-axial, empirically derived taxonomy of CDS malfunctions.

Results

We analyzed 68 CDS alert malfunction cases from 14 sites across the United States with diverse electronic health record systems. Four primary axes emerged: the cause of the malfunction, its mode of discovery, when it began, and how it affected rule firing. Build errors, conceptualization errors, and the introduction of new concepts or terms were the most frequent causes. User reports were the predominant mode of discovery. Many malfunctions within our database caused rules to fire for patients for whom they should not have (false positives), but the reverse (false negatives) was also common.

Discussion

Across organizations and electronic health record systems, similar malfunction patterns recurred. Challenges included updates to code sets and values, software issues at the time of system upgrades, difficulties with migration of CDS content between computing environments, and the challenge of correctly conceptualizing and building CDS.

Conclusion

CDS alert malfunctions are frequent. The empirically derived taxonomy formalizes the common recurring issues that cause these malfunctions, helping CDS developers anticipate and prevent CDS malfunctions before they occur or detect and resolve them expediently.

Mind the Gap. A systematic review to identify usability and safety challenges and practices during electronic health record implementation

OBJECTIVE

Decisions made during electronic health record (EHR) implementations profoundly affect usability and safety. This study aims to identify gaps between the current literature and key stakeholders' perceptions of usability and safety practices and the challenges encountered during the implementation of EHRs.

MATERIALS AND METHODS

Two approaches were used: a literature review and interviews with key stakeholders. We performed a systematic review of the literature to identify usability and safety challenges and best practices during implementation. A total of 55 articles were reviewed through searches of PubMed, Web of Science and Scopus. We used a qualitative approach to identify key stakeholders' perceptions; semi-structured interviews were conducted with a diverse set of health IT stakeholders to understand their current practices and challenges related to usability during implementation. We used a grounded theory approach: data were coded, sorted, and emerging themes were identified. Conclusions from both sources of data were compared to identify areas of misalignment.

RESULTS

We identified six emerging themes from the literature and stakeholder interviews: cost and resources, risk assessment, governance and consensus building, customization, clinical workflow and usability testing, and training. Across these themes, there were misalignments between the literature and stakeholder perspectives, indicating major gaps.

DISCUSSION

Major gaps identified from each of six emerging themes are discussed as critical areas for future research, opportunities for new stakeholder initiatives, and opportunities to better disseminate resources to improve the implementation of EHRs.

CONCLUSION

Our analysis identified practices and challenges across six different emerging themes, illustrated important gaps, and results suggest critical areas for future research and dissemination to improve EHR implementation.

How to improve vital sign data quality for use in clinical decision support systems? A qualitative study in nine Swedish emergency departments

Background

Vital sign data are important for clinical decision making in emergency care. Clinical Decision Support Systems (CDSS) have been advocated to increase patient safety and quality of care. However, the efficiency of CDSS depends on the quality of the underlying vital sign data. Therefore, possible factors affecting vital sign data quality need to be understood.

This study aims to explore the factors affecting vital sign data quality in Swedish emergency departments and to determine in how far clinicians perceive vital sign data to be fit for use in clinical decision support systems. A further aim of the study is to provide recommendations on how to improve vital sign data quality in emergency departments.

Methods

Semi-structured interviews were conducted with sixteen physicians and nurses from nine hospitals and vital sign documentation templates were collected and analysed. Follow-up interviews and process observations were done at three of the hospitals to verify the results. Content analysis with constant comparison of the data was used to analyse and categorize the collected data.

Results

Factors related to care process and information technology were perceived to affect vital sign data quality. Despite electronic health records (EHRs) being available in all hospitals, these were not always used for vital sign documentation. Only four out of nine sites had a completely digitalized vital sign documentation flow and paper-based triage records were perceived to provide a better mobile workflow support than EHRs. Observed documentation practices resulted in low currency, completeness, and interoperability of the vital signs. To improve vital sign data quality, we propose to standardize the care process, improve the digital documentation support, provide workflow support, ensure interoperability and perform quality control.

Conclusions

Vital sign data quality in Swedish emergency departments is currently not fit for use by CDSS. To address both technical and organisational challenges, we propose five steps for vital sign data quality improvement to be implemented in emergency care settings.

Electronic supplementary material

The online version of this article (doi:10.1186/s12911-016-0305-4) contains supplementary material, which is available to authorized users.

Tailoring implementation strategies for evidence-based recommendations using computerised clinical decision support systems: protocol for the development of the GUIDES tools

BACKGROUND

A computerised clinical decision support system (CCDSS) is a technology that uses patient-specific data to provide relevant medical knowledge at the point of care. It is considered to be an important quality improvement intervention, and the implementation of CCDSS is growing substantially. However, the significant investments do not consistently result in value for money due to content, context, system and implementation issues. The Guideline Implementation with Decision Support (GUIDES) project aims to improve the impact of CCDSS through optimised implementation based on high-quality evidence-based recommendations. To achieve this, we will develop tools that address the factors that determine successful CCDSS implementation.

METHODS/DESIGN

We will develop the GUIDES tools in four steps, using the methods and results of the Tailored Implementation for Chronic Diseases (TICD) project as a starting point: (1) a review of research evidence and frameworks on the determinants of implementing recommendations using CCDSS; (2) a synthesis of a comprehensive framework for the identified determinants; (3) the development of tools for use of the framework and (4) pilot testing the utility of the tools through the development of a tailored CCDSS intervention in Norway, Belgium and Finland. We selected the conservative management of knee osteoarthritis as a prototype condition for the pilot. During the process, the authors will collaborate with an international expert group to provide input and feedback on the tools.

DISCUSSION

This project will provide guidance and tools on methods of identifying implementation determinants and selecting strategies to implement evidence-based recommendations through CCDSS. We will make the GUIDES tools available to CCDSS developers, implementers, researchers, funders, clinicians, managers, educators, and policymakers internationally. The tools and recommendations will be generic, which makes them scalable to a large spectrum of conditions. Ultimately, the better implementation of CCDSS may lead to better-informed decisions and improved care and patient outcomes for a wide range of conditions.

PROTOCOL REGISTRATION

PROSPERO, CRD42016033738.