Facilitators and Barriers to Integrating Patient-Generated Blood Pressure Data into Primary Care EHR Workflows

Abstract

Background Evidence supports using patient-generated blood pressure data for better outcomes in hypertension management. However, obstacles like dealing with home-generated paper data sets and questions of validity slowed the meaningful incorporation of home blood pressure into clinical care. As clinicians value patient data more, reliance on digital health solutions for data collection and shared decision-making grows.

Objectives The purpose of this study is to evaluate the design and early implementation of an electronic health record (EHR)-based data visualization tool and explore the barriers or facilitators to integrating) patients' home blood pressure data into the electronic workflow in the clinical setting. Findings can inform potential next steps for implementation and provide recommendations for leveraging patient-generated health data (PGHD) in hypertension management.

Methods We qualitatively explored pre- and early-implementation factors for integrating PGHD into clinicians' EHR interfaces intended to support shared decision-making using the Consolidated Framework for Implementation Research (CFIR). We collected data in the form of notes and transcripts from clinician focus groups, administrative leadership feedback sessions, research team observations, and recurring team meetings. This study took place at a midwestern academic health center.

Results We identify implementation facilitating factors, adoption considerations, and next steps across CFIR domains focusing on large-scale implementation. Key recommendations include aligning internal and external priorities, empowering champions to facilitate uptake, using intuitive design, and anticipating and planning for unintended consequences.

Conclusion These findings can guide future efforts to include PGHD in workflows, thus enhancing shared decision-making and laying the groundwork for larger implementations. Understanding the implementation barriers and facilitators to connect PGHD to clinician apps in the EHR workspace can promote their adoption and maintenance.

Keywords

hypertension management - blood pressure control - implementation science - shared decision-making - patient-generated health data - mHealth - data visualization - primary care

Background and Significance

Supplementing clinical blood pressure data with patient-generated home blood pressure data (PGHD) is an essential evidence-based component for managing hypertension.[1] Using home blood pressure data can (1) illuminate possible white coat effects (i.e., elevated readings due to anxiety in a clinical setting); (2) reveal masked hypertension (i.e., normal readings in a clinical setting but elevated at home); (3) improve the accuracy of diagnoses or control judgments; and (4) increase safety.[2] [3] [4] [5] As clinicians ascribe more value to PGHD for managing hypertension, their reliance on digital health solutions continues to mount. By digital health solutions, we mean mobile health (mHealth) applications and other tools embedded in clinician-facing electronic health record (EHR) workflows. These tools can assist patients in proper data collection and support shared decision-making in care decisions.[4] [6] [7] [8] [9] [10] Thus, incorporating PGHD as part of hypertension management is a growing—and feasible—imperative.

Important barriers and questions remain for effectively using PGHD in clinical care given we expect increased communication of home blood pressure data during clinical encounters and through patient portal messages.[10] [11] When clinicians want a patient to begin home monitoring, they typically offer them resources for obtaining and using home blood pressure cuffs and request that they record the measurements on a paper log or digital cuff. Directions on how often to measure and convey these home readings to the care team vary greatly and depend on patient and care team factors.[12] Another challenge involves transferring the paper data to a digital format and or migrating the digital data from one device to another. Ultimately, there are questions, concerns, and logistical problems to overcome to ensure the activity is sustainable in the effort to improve quality care. These include (1) clinician and patient doubt surrounding the evidence for using home blood pressure data; (2) uncertainty about technique, schedule, and validity of the home measurement; (3) burden of patient data entry; (4) the electronic flow of blood pressure data information; (5) clinical care team assimilation of these data; (6) data representation for clinical decision-making; (7) feedback to patients about their data; (8) time for interpretation of data during and between clinical visits; (9) responsibility for managing home data; and (10) security of data transmission to make all of this activity sustainable in the effort to improve care quality.[13] [14] [15] [16] [17] [18] [19] Complicating the practice of home monitoring further, insurance-based payment and reimbursement mechanisms in the United States lag behind other countries with universal health care models.[20] [21] Some plans fully cover the cost, while others may require a copayment or deductible. Many health plans, including Medicare and Medicaid, require a prescription or recommendation from a health care provider.[12] [13] [14] [15] [16] [17] [18] [19]

In 2015, our team began work to incorporate patient-generated home blood pressure data into the EHR of a midwestern academic health system. By 2018, we had secured approval from the institutional clinical governance committee to securely collect patient home blood pressure data via the EHR-tethered patient portal and transmit these data to be viewable in the clinical EHR. By 2019, we had implemented a data visualization in the clinician's view of the EHR workflow representing home and clinical blood pressure data trends using interoperable HL7® SMART™ on FHIR® (Health Level 7 Substitutable Medical Applications, Reusable Technologies on Fast Healthcare Interoperability Resources).[18] [22]

Next, using an iterative, user-centered design process, we developed the SMART BP Visualization Application (SMART BP App, or App, hereafter), as shown in [Fig. 1]. During development, we asked for patient and care team input to inform design decisions.[17] [18] [19] The clinician-facing App is integrated into the EHR workflow view. It features a line graph with smoothing functions for longitudinal blood pressure data and color-coded goal ranges to aid understanding and clinical decision-making for both patients and clinicians in a clinical context. Focus groups informed its iterative design to meet the needs of both physicians and patients. Accurate and timely data were crucial for engagement and effective use. Both groups found the visualization clear, valued the inclusion of both home and clinic blood pressures, and appreciated the inclusion of goal ranges based on clinical guidelines. Annotations provided context, though physicians preferred automated options to reduce manual effort.[17] [18] During the design process, we conducted online perception studies with patients to evaluate how health literacy, numeracy, and graph literacy affect perceptions of hypertension control using data visualizations, finding that smoothed graphs led to more accurate judgments. These findings echo research that found that effective visualization design enhances understanding and reduces clinical uncertainty and inertia in hypertension management.[23] [24]

Fig. 1 The SMART BP App visualization includes customizable timeline display windows; separate symbols for blood pressures arising from home, clinic, and other (e.g., ER, hospital) environments; trend lines; shaded goal ranges; medication timeline; and a locally weighted scatter-plot smoother (LOWESS( smoothing algorithm to ease patient and clinician interpretation of control for variable blood pressure data. EHR, electronic health record.

Studying the tool's early implementation and clinical use, we learned that it was easier and more efficient than paper recordings for home blood pressure monitoring. However, using the App required proper EHR infrastructure and patient capability to enter blood pressure readings into the clinical record. Patients and clinicians alike noted concerns about workflows and data accuracy. Despite the concerns, the App enhanced patients' sense of importance in providing blood pressure data and helped physicians integrate these data into clinical decision-making, thus promoting better blood pressure control.[19] Although the challenges of using PGHD have been discussed in the literature, few studies have completed a robust evaluation of the process where numerous collaborators and end-users—such as the EHR vendor, health care system leaders, and care team members—contributed to the process of implementing a tool embedded in the clinical EHR utilizing directly entered PGHD)[42].

Objectives

Having described the tool development and evaluation, we now turn toward a discussion on implementation at our large academic health care system. In addition, we will cover how our study might inform future system-level implementations of home blood pressure data and other PGHD.[17] [18] [19] [25] Our objective is to describe early-implementation facilitating factors, identify problems yet to be solved, propose potential next steps for implementation and inquiry, and provide recommendations for leveraging PGHD in hypertension management with a focus on implementation, at scale, in large/academic health systems. To achieve these aims, we apply domains from the Consolidated Framework for Implementation Research (CFIR)—a flexible tool for understanding organizational change and innovation factors as predictors or critical factors of anticipated implementation outcomes—in our analysis and presentation of results.[26] [27] [28] Health science researchers commonly use CFIR domains—Innovation, Inner Setting, Outer Setting, Individuals, and Implementation Process—for implementation studies of chronic disease care management and EHR decision support.[27] [29] [30]

Methods

We qualitatively explore pre- and early-implementation factors for integrating PGHD into patients' and primary care clinicians' EHR interfaces and workflows using multiple data sources obtained over several years.[31] [32] [33] As part of the SMART BP App's iterative and participatory design process, our team recruited and enrolled family medicine and general internal medicine physicians caring for adult patients in rural and urban outpatient primary care settings, as well as institutional leaders (i.e., administrators and clinicians) affiliated with a midwestern academic health center. This study was approved by the University of Missouri Institutional Review Board (#2002623).

Data include notes from 63 team meetings (the meetings occurred twice a month), 9 quarterly meetings with the vendor-affiliated software engineers, 5 focus groups with primary care physicians (N = 24), and 1 feedback session with clinicians in leadership roles (N = 12). Throughout the 2-year design process, the Principal Investigator (R.J.K.) and Project Director (S.M.C.) invited physicians to participate in an audio-recorded focus group or a feedback session. After we obtained informed consent for people's participation in the study, we presented clinical scenarios alongside images of the App and asked participants to describe their perceptions of how the App would function in practice or ways in which it could be improved. Methods for data collected during focus groups and the feedback session are described extensively elsewhere.[17] [18] [19] We used the CFIR framework to develop the following questions and objectives for each CFIR domain to guide our analysis and synthesis of results.

1. Innovation source: How might integrating patient-generated home blood pressure data into the clinical workflow via the App improve care? How does the design facilitate adoption? Objective 1: Explore how measurement contributes to the concept of “true” blood pressure and discuss physician information needs about clinic and home blood pressure data. Objective 2: Discuss attitudes and potential decision-making behaviors in response to candidate displays of graphical blood pressure data.

2. Outer setting: How does this App meet and align with the needs and mission of patient and clinical care team end-users, policymakers, or organizational leaders? Objective: Review and discuss the current state of blood pressure diagnosis and control in the United States.

3. Inner setting: What are the key factors for integration given the current culture, capacity, and resources? Objective 1: Discuss the challenges of utilizing patient-supplied home blood pressure data while encouraging patient engagement in hypertension treatment plans. Objective 2: Compare the most utilized and reliable blood pressure measurement practices.

4. Individuals: Are there people at the organizational and clinical level who can support the implementation process, adoption, and maintenance? Objective: Who at the clinic or the broader organization are health information technology champions?

5. Implementation process: What are the primary barriers and facilitators to using home blood pressure data via the App in the early stages of adoption? Objective: Identify barriers and facilitators and develop recommendations for future work.

The researchers (S.M.C. and R.J.K.) have an extensive collaborative work history and are experienced qualitative researchers, bringing different perspectives and reflexivity to their work.[17] [19] [34] S.M.C. is a primary care researcher with social work and public health background who explores quality, accessible, and patient-centered interventions in her work. R.J.K. is a practicing clinician with content expertise and extensive work in user-centered design. S.M.C. and R.J.K. used Dedoose to deductively code data by applicable CFIR domain and inductively code excerpts related to barriers, facilitators, and next steps. Where there was disagreement about code application, researchers met to discuss and come to a consensus. Next, researchers organized the data by CFIR primary and subdomains and created summary statements to represent the key ideas and takeaways from the data. In addition to our qualitative evaluation, we present early measures of implementation adoption from the patient portal (number of home blood pressures entered by patients) and EHR back-end use data (patient home blood pressures entered by clinical personnel).

Researchers collaborated with vendor-affiliated software engineers at the University of Missouri to supply SMART BP App usage data. The software engineering team used the interoperable Olympus Knowledge Exchange system to extract the date and time the App, whether home blood pressure was manually input into the clinical EHR by a care team member or a patient via the portal, and the number of readings input. This analysis was conducted quarterly.

Results

We describe early implementation facilitating factors or barriers, organized by CFIR domains represented in the data—subdomains are denoted with italics. We offer recommendations for leveraging EHR-based tools to manage PGHD in hypertension management, focusing on large-scale implementation in academic health systems in [Table 1].

Table 1 Recommendations for large health system implementation of EHR-based decision support to manage PGHD in hypertension management, organized by CFIR domain

Domain	Recommendations
Innovation	• Incorporate implementation leads who can augment clinical team buy-in and trust, building on a history of interaction with the clinical teams and a proven track record • Build-in time for interaction of the implementation team and clinical team to emphasize alignment of mission and goals around the importance of using PGHD • Meaningfully incorporate institutional leadership in creating prioritization of PGHD and the design and process of implementation
Outer setting	• Leverage alignment between national and local priorities to improve health with an organizational mission to promote and prioritize the intervention • Identify ways policy can support practice change, including incentives and reimbursement, with the opportunity to see change in measurable aspects of care quality and health outcomes • Ensure the organization knows the costs associated with implementing the intervention and utilizing policy mechanisms for reimbursement • Highlight unexpected benefits of the intervention to promote future innovation
Inner setting	• Use data-driven and best practice recommendations to initiate timely and impactful diffusion of innovation as part of hypertension management practice change • Identify champions and consider using models such as train-the-trainer to promote education for using the innovation • Explore practicing at the top of the license for a maximized team-based care approach
Individuals	• Maximize connections and opportunities for multidisciplinary collaboration • Acknowledge and appropriately design for existing work infrastructure and capacity • Create buy-in by integrating end-user feedback into the implementation design
Implementation process	• Embrace, realize, and repeat a rigorous plan-do-study-act process • Expect and reflect on unintended consequences and contexts—they can be barriers or facilitators

Abbreviations: CFIR, Consolidated Framework for Implementation Research; EHR, electronic health record; PGHD, patient-generated health data.

Innovation Domain

Concerning the CFIR source domain, a reputable team of user-centered design researchers at an academic health system developed the Smart BP App. The process included an iterative design process that took place over 2 years, and efforts to encourage buy-in and motivation to use the App. During development, we worked to align study aims, innovation purpose, and organizational mission. Researchers took a multipronged approach (consulting expert opinions, literature reviews, surveys, and applied informatics) to App design to ensure to ensure the visualization features of the home blood pressure data were grounded in the evidence.[18] [22] [23] [24] [35] A coinvestigator served on a national hypertension guideline panel, lending further weight to the team being viewed by App end-users as a reputable source.

With the movement away from paper records in the digital age, patients recording and delivering home blood pressure data on paper to their clinician is becoming less congruent with an EHR-based workflow. Thus, the App offered a relative advantage. The App was adaptable, given the clinician's ability to adjust goal ranges, toggle the data views by various periods (i.e., week, month, or year), and display a corresponding medication timeline.[25] Overall, patients and clinicians noted the App design and packaging presented data meaningfully, met end-user needs, and felt intuitive. These features facilitated implementation and limited “training” to a brief orientation.

People in this study described cost in terms of resources, capacity (i.e., care team members' time and effort), and patient-centered care. Participants seemed positive about the App's potential for decreasing care team members' effort required for entering patient data into the EHR and appreciated the increased opportunity for shared decision-making. They also expressed worry about physicians experiencing increased message center communications without additional staffing resources which could increase workloads. The concern of increased workloads and unreimbursed time was expressed as particularly pronounced in a fee-for-service practice environment.[17] [19] Although programming hours were high, the EHR vendor saw work related to this study as leading-edge and a good investment due to scalability.

Outer Setting Domain

Local conditions favored implementation, as the academic health center has connections with local experts; organizational, clinical, and technology governance, and connections with the EHR vendor. In addition, research to innovate digital health solutions for use in hypertension management aligns with local conditions favoring the implementation. Cardiovascular-related disease diagnosis, treatment, and prevention are priorities (i.e., external pressures) at organizational, local, state, and national levels. The 2015 United States Preventative Services Task Force (USPSTF) recommends using home blood pressure data in hypertension management.[35] However, the lack of established national directives and payment mechanisms may have dampened people's enthusiasm for adopting the SMART BP App.[17] Participants had questions about liability and protocols to ensure a timely PGHD review. They noted the possibility of patients uploading batched historical data at any time or day. Conversely, this work would not have happened without federal research grant resources (an inner setting domain) supporting the design of a rigorously developed, evidence-based App—a signal that national funding mechanisms prioritize research to develop digital health solutions such as this App.

The coronavirus disease (COVID-19) pandemic was an additional external pressure with the unanticipated benefit of promoting the uptake of the App. Because the App was fully available to primary care physicians by the fall of 2019, they could remotely monitor home blood pressure data via the EHR. [Figure 2] shows a graph used by R.J.K. during a telehealth visit in April 2020, when in-person visits for routine chronic disease management were not allowed. It is possible the pandemic increased the uptake of the tool.

Fig. 2 This figure shows a shared screen snip from an April 16, 2020, telehealth visit between a patient and a physician. It shows the App in use during the period of exclusive remote care in the COVID-19 pandemic's initial phase. COVID-19, coronavirus disease 2019.

Inner Setting Domain

The academic health center where this research took place was an early EHR adopter and supported operational and governance units tasked with technological assistance related to care processes. Initially, there were limitations to the technological infrastructure for integrating home blood pressure data into the clinical EHR. This study provided resources enabling that to change. Typical primary care processes and work infrastructure aligned with the SMART BP App concept. However, people in this study questioned the technical aspects of integrating the use of PGHD into workflows and cited increasing messaging center burden and alert fatigue as sources of hesitation.[17] [19] People's feedback about the App being used in regular workflows also highlighted the importance of teaming (e.g., triaging activities to nurses, medical assistants, and care coordinators and taking a team-based approach to blood pressure management activities) and avoiding a physician-centric approach to its integration. The risk of not doing so could contribute to burnout.

In our evaluation, we identified communications and partnerships as crosscutting topics related to communications and partnerships. The organization of clinics under the structure of departments in the academic medical center created uniformity in clinic protocols and supported communication. The care team members shared values and a sense of mission, which promoted a collaborative culture. People expressed that the App supported their work values due to its potential to improve quality and patient-centered care.[17]

The tension for change around the problematic paper-delivered home blood pressure data coupled with the increasing use of electronic workflows powerfully drove the development of the App. In addition, changes in policy and practice guidelines, an organizational focus on the delivery and measurement of care quality, and the normalization of the use of home data in blood pressure management all contributed to embedding the App into the EHR workflow. The implementation of the App was a solution and a logical step given its compatibility with existing systems and structures.

Hypertension has been called the silent killer and is the most significant indicator of risk for a fatal cardiac event, thus emerging as a priority at local and national levels.[36] The development of the App supports the institutional mission and clinical care culture aiming to improve outcomes. Institutionally, structural characteristics prioritized the development of the EHR visualization over the development of the corresponding patient portal entry page, leaving the patient interface as an area for future development.

Individuals Domain

The findings for this domain reinforce the importance of leadership, champions, and diverse collaborations to be engaged in iterative design processes and pre-implementation work. A critical aspect of the App implementation was the diversity of influence and input across the roles of different individuals, such as study investigators' national engagement with the USPSTF; participant positions in clinical governance (i.e., a Chief Medical Information Officer); extensive clinical knowledge; and expertise in user-centered design, public health, social science, computer science, human factors engineering, and psychology.

Implementation Process Domain

The researchers provide ongoing formal and informal engagement and education about the App as a way to support primary care teams. Care team members promoted the use of the App via word of mouth, with patients during clinical encounters, and through spontaneous serendipitous discovery in the patient portal. The researchers did not engage in a formal marketing campaign, although the momentum and piqued interest resulted in a larger adoption effort of the App than anticipated. However, the COVID-19 pandemic interrupted these efforts. Given the limited needs assessment and small-step (i.e., clinician-by-clinician) rollout, the research team was highly cognizant of the intervention's lack of a patient-facing tool and alert system (e.g., continued tailoring), thus the App was not implemented beyond the clinical workflow view. As we entered 2020, further implementation processes, planning, and evaluation were paused to give clinical priority to the COVID-19 pandemic. Nevertheless, 1,340 unique patients entered 10,927 home blood pressures in the first 21 months of the intervention, [Fig. 3].

Fig. 3 The option for patients to enter blood pressure data via the portal became available in the first quarter of 2018. The bar graph and corresponding y-axis on the left indicate the number of unique patient home blood pressure readings manually input to the EHR by a nurse or those via the patient portal by year and quarter. The line graph and corresponding y-axis on the right indicate the total number of systolic/diastolic blood pressure pairs input by patients. EHR, electronic health record.

As part of the early adoption evaluation, our EHR vendor partner collected data on how home blood pressure documentation transitioned from clinic personnel entry to patient portal entry, as illustrated in [Fig. 3]. In the last 3 months of 2019, usage data showed that nurses, medical assistants, and physicians spent a total of 36 hours entering home blood pressure data. As the data entry burden shifted to individual patients and, eventually, to Bluetooth upload, this intervention shows potential for saving care team members' time. When assessing context, we found that while the COVID-19 pandemic was a barrier to further implementation planning, it also cast the intervention as a serendipitous solution to an unforeseen problem: How to efficiently assess and communicate hypertension control during a telehealth visit.

Discussion

We have identified important considerations and concerns for implementing a system that introduces home blood pressure into clinical management decisions. Effective and efficient solutions are attractive and require flexibility and sustainable processes. Our intervention found that to effectively innovate, design, plan, and implement a PGHD tool such as the SMART BP App, institutions must align priorities between the research team, organizational leaders, clinic care teams, and patients. In addition, they must consider the effect on workflows, payment, and other incentives to ensure successful adoption and long-term sustainability. A key facilitating factor was linking the innovation with nationally and institutionally prioritized goals and using an iterative design process to create an attractive solution, thus creating buy-in with collaborators and end-users. The project was timely, achievable, and had the potential to support clinical decision-making while improving health outcomes and care quality.

Before this study, the PGHD was primarily integrated into the EHR manually by care team members, using 24-hour ambulatory monitoring. Integrating PGHD for hypertension management into the EHR workflow is complex, and this study found it dependent on organizational structures, capacity, and resources. EHR vendors suggested that the return on investment could outweigh the programming costs, as innovations like the App enhance communication, support shared decision-making, and potentially improve care quality, making it an appealing tool for scaling to other settings or populations.[13] [37]

Literature and experience (e.g., poorly designed portals and inefficiencies/inconsistencies associated with using paper to convey PGHD) inform us that releasing a product that is considered subpar or rushed to production at the cost of usability will permanently damage user trust.[38] [39] [40] [41] Thus, to encourage sustainability and maintenance of the intervention, future inquiry should focus on answering questions about what economic, quality, and efficiency measures can drive uptake and the planning processes needed for implementation.[42] The findings from this study highlight the need for further work, such as investigating reimbursement policies for home monitoring devices and for clinical care teams' time spent managing blood pressure remotely. Currently, reimbursement for these activities is inconsistent in predominantly fee-for-service systems.[21] [43]

There are several other ways this study informs future research. For instance, interventions like the SMART BP App are needed to enhance patient self-management by providing patient-centered, informative alerts.[44] [45] The development and implementation of this App highlighted physicians' continued and increasing concerns about capacity, specifically: (1) the time required to review data; (2) the need for the integration of a payment mechanism; and (3) a tendency for physician-centric rather than team-based care.[46] [47] [48] Future work should include targeted training and focused attention to maximizing existing workflows and employing user-centered design to create interventions that complement, rather than burden, the process of care. Health systems have cited challenges related to data quality and the clinical usefulness of PGHD.[49] In the case of this study, the research team and user clinician perceptions of what the intervention lacks—particularly programmed patient feedback on blood pressure and payment for non-visit-based clinician management activities—has resulted in an implementation that informs care during patient visits but has limited use outside of the visit context. Future work to develop a patient-facing tool might be embraced by care teams and patients if thoughtfully designed to promote shared decision-making supported by care teams with the capacity to deliver it.

Limitations

There are limitations to this study. The data collected in focus groups and feedback sessions represent clinician/leadership perspectives only. In addition to continuing to design with patients and physicians in mind, future work implementing digital health solutions including PGHD should include a spectrum of care team members. We suggest an advisory panel of nurses, care coordinators, pharmacists, caregivers, and allied health professionals for more effective and far-reaching implementation. This study occurred in only one academic health system. This initial inquiry should lay the foundation for future study of the implications of incorporating decision-support tools such as the SMART BP App at a larger scale, requiring testing at multiple, diverse sites. Finally, the lessons learned from this study only evaluate early implementation. Further study of implementation frameworks is necessary to monitor adoption and sustainability. Not addressed in this study, and a fertile area for future inquiry, is an examination of the patient workflow, patterns, burden, and motivations in collecting these PGHD.[45]

Conclusion

Hypertension management in primary care may benefit from Fast Healthcare Interoperability Resources (FHIR)-based applications embedded in the EHR, including home blood pressure. These applications can improve care quality and decision-making. Addressing user concerns and organizational barriers is key for adoption and sustainability. Understanding user needs, workflows, culture, and external support is crucial for long-term use. Findings from this study can inform more extensive pragmatic trials with great potential to improve cardiovascular health.

Clinical Relevance Statement

Findings from this study can inform future research aiming to include PGHD in shared clinical decision-making processes. Experts encourage the use of home blood pressure data in efforts for hypertension prevention and control. Understanding the implementation barriers and facilitators of using applications connecting patient-facing health records to the clinical workspace can promote meaningful adoption and maintenance of these interventions.

Multiple-Choice Questions

1. Which of the following applies to implementation science?

   • It improves the likelihood of intervention adoption and sustainability.

   • It indicates the odds of an intervention improving outcomes of interest.

   • CFIR is used in health science research alone.

   • All of the above.

   Correct Answer: The correct answer is option a. Adoption and sustainability signal longer term uptake of an intervention. In implementation science, we strive for evidence-based interventions put into real-world use, not used in theory alone.

2. Which of the following is an example of a factor representing the CFIR Outer Setting domain as it relates to researching digital health solutions?

   • Policies

   • Critical incidents

   • Financing

   • All of the above.

   Correct Answer: The correct answer is option d. External bodies often set policies driving the delivery of health care, critical incidents such as a pandemic change how care is received, and practices are modified to continue care delivery; financing supports research and payment mechanisms for health care.

Conflict of Interest

None declared.

Protection of Human Subjects

All participants gave informed consent before participating, and this study was conducted in accordance with the World Medical Association Declaration of Helsinki. The University of Missouri Institutional Review Board approved this study (#2002623).

Note

The authors have not presented the findings included in this manuscript at a conference.

Disclosure

The content is solely the responsibility of the authors and does not necessarily represent the official views of the Agency for Healthcare Research and Quality.

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Publication History

Received: 01 April 2024

Accepted: 16 August 2024

Article published online:
13 November 2024