Clinical Decision Support for Hypertension Management in Chronic Kidney Disease: A Randomized Clinical Trial.

Importance: Chronic kidney disease (CKD) affects 37 million adults in the United States, and for patients with CKD, hypertension is a key risk factor for adverse outcomes, such as kidney failure, cardiovascular events, and death. Objective: To evaluate a computerized clinical decision support (CDS) system for the management of uncontrolled hypertension in patients with CKD. Design, Setting, and Participants: This multiclinic, randomized clinical trial randomized primary care practitioners (PCPs) at a primary care network, including 15 hospital-based, ambulatory, and community health center-based clinics, through a stratified, matched-pair randomization approach February 2021 to February 2022. All adult patients with a visit to a PCP in the last 2 years were eligible and those with evidence of CKD and hypertension were included. Intervention: The intervention consisted of a CDS system based on behavioral economic principles and human-centered design methods that delivered tailored, evidence-based recommendations, including initiation or titration of renin-angiotensin-aldosterone system inhibitors. The patients in the control group received usual care from PCPs with the CDS system operating in silent mode. Main Outcomes and Measures: The primary outcome was the change in mean systolic blood pressure (SBP) between baseline and 180 days compared between groups. The primary analysis was a repeated measures linear mixed model, using SBP at baseline, 90 days, and 180 days in an intention-to-treat repeated measures model to account for missing data. Secondary outcomes included blood pressure (BP) control and outcomes such as percentage of patients who received an action that aligned with the CDS recommendations. Results: The study included 174 PCPs and 2026 patients (mean [SD] age, 75.3 [0.3] years; 1223 [60.4%] female; mean [SD] SBP at baseline, 154.0 [14.3] mm Hg), with 87 PCPs and 1029 patients randomized to the intervention and 87 PCPs and 997 patients randomized to usual care. Overall, 1714 patients (84.6%) were treated for hypertension at baseline. There were 1623 patients (80.1%) with an SBP measurement at 180 days. From the linear mixed model, there was a statistically significant difference in mean SBP change in the intervention group compared with the usual care group (change, -14.6 [95% CI, -13.1 to -16.0] mm Hg vs -11.7 [-10.2 to -13.1] mm Hg; P = .005). There was no difference in the percentage of patients who achieved BP control in the intervention group compared with the control group (50.4% [95% CI, 46.5% to 54.3%] vs 47.1% [95% CI, 43.3% to 51.0%]). More patients received an action aligned with the CDS recommendations in the intervention group than in the usual care group (49.9% [95% CI, 45.1% to 54.8%] vs 34.6% [95% CI, 29.8% to 39.4%]; P < .001). Conclusions and Relevance: These findings suggest that implementing this computerized CDS system could lead to improved management of uncontrolled hypertension and potentially improved clinical outcomes at the population level for patients with CKD. Trial Registration: ClinicalTrials.gov Identifier: NCT03679247.

A Multiyear Survey Evaluating Clinician Electronic Health Record Satisfaction.

OBJECTIVES: We assessed how clinician satisfaction with a vendor electronic health record (EHR) changed over time in the 4 years following the transition from a homegrown EHR system to identify areas for improvement. METHODS: We conducted a multiyear survey of clinicians across a large health care system after transitioning to a vendor EHR. Eligible clinicians from the first institution to transition received a survey invitation by email in fall 2016 and then eligible clinicians systemwide received surveys in spring 2018 and spring 2019. The survey included items assessing ease/difficulty of completing tasks and items assessing perceptions of the EHR's value, usability, and impact. One item assessing overall satisfaction and one open-ended question were included. Frequencies and means were calculated, and comparison of means was performed between 2018 and 2019 on all clinicians. A multivariable generalized linear model was performed to predict the outcome of overall satisfaction. RESULTS: Response rates for the surveys ranged from 14 to 19%. The mean response from 3 years of surveys for one institution, Brigham and Women's Hospital, increased for overall satisfaction between 2016 (2.85), 2018 (3.01), and 2019 (3.21, p < 0.001). We found no significant differences in mean response for overall satisfaction between all responders of the 2018 survey (3.14) and those of the 2019 survey (3.19). Systemwide, tasks rated the most difficult included "Monitoring patient medication adherence," "Identifying when a referral has not been completed," and "Making a list of patients based on clinical information (e.g., problem, medication)." Clinicians disagreed the most with "The EHR helps me focus on patient care rather than the computer" and "The EHR allows me to complete tasks efficiently." CONCLUSION: Survey results indicate room for improvement in clinician satisfaction with the EHR. Usability of EHRs should continue to be an area of focus to ease clinician burden and improve clinician experience.

Management of Fall Risk Among Older Adults in Diverse Primary Care Settings.

OBJECTIVES: Falls are persistent among community-dwelling older adults despite existing prevention guidelines. We described how urban and rural primary care staff and older adults manage fall risk and factors important to integration of computerized clinical decision support (CCDS). METHODS: Interviews, contextual inquiries, and workflow observations were analyzed using content analysis and synthesized into a journey map. Sociotechnical and PRISM domains were applied to identify workflow factors important to sustainable CCDS integration. RESULTS: Participants valued fall prevention and described similar approaches. Available resources differed between rural and urban locations. Participants wanted evidence-based guidance integrated into workflows to bridge skills gaps. DISCUSSION: Sites described similar clinical approaches with differences in resource availability. This implies that a single intervention would need to be flexible to environments with differing resources. Electronic Health Record's inherent ability to provide tailored CCDS is limited. However, CCDS middleware could integrate into different settings and increase evidence use.

Correction: Performance of a Web-Based Reference Database With Natural Language Searching Capabilities: Usability Evaluation of DynaMed and Micromedex With Watson.

[This corrects the article DOI: 10.2196/43960.].

Performance of a Web-Based Reference Database With Natural Language Searching Capabilities: Usability Evaluation of DynaMed and Micromedex With Watson.

BACKGROUND: Evidence-based point-of-care information (POCI) tools can facilitate patient safety and care by helping clinicians to answer disease state and drug information questions in less time and with less effort. However, these tools may also be visually challenging to navigate or lack the comprehensiveness needed to sufficiently address a medical issue. OBJECTIVE: This study aimed to collect clinicians' feedback and directly observe their use of the combined POCI tool DynaMed and Micromedex with Watson, now known as DynaMedex. EBSCO partnered with IBM Watson Health, now known as Merative, to develop the combined tool as a resource for clinicians. We aimed to identify areas for refinement based on participant feedback and examine participant perceptions to inform further development. METHODS: Participants (N=43) within varying clinical roles and specialties were recruited from Brigham and Women's Hospital and Massachusetts General Hospital in Boston, Massachusetts, United States, between August 10, 2021, and December 16, 2021, to take part in usability sessions aimed at evaluating the efficiency and effectiveness of, as well as satisfaction with, the DynaMed and Micromedex with Watson tool. Usability testing methods, including think aloud and observations of user behavior, were used to identify challenges regarding the combined tool. Data collection included measurements of time on task; task ease; satisfaction with the answer; posttest feedback on likes, dislikes, and perceived reliability of the tool; and interest in recommending the tool to a colleague. RESULTS: On a 7-point Likert scale, pharmacists rated ease (mean 5.98, SD 1.38) and satisfaction (mean 6.31, SD 1.34) with the combined POCI tool higher than the physicians, nurse practitioner, and physician's assistants (ease: mean 5.57, SD 1.64, and satisfaction: mean 5.82, SD 1.60). Pharmacists spent longer (mean 2 minutes, 26 seconds, SD 1 minute, 41 seconds) on average finding an answer to their question than the physicians, nurse practitioner, and physician's assistants (mean 1 minute, 40 seconds, SD 1 minute, 23 seconds). CONCLUSIONS: Overall, the tool performed well, but this usability evaluation identified multiple opportunities for improvement that would help inexperienced users.

Usability Testing of an Interoperable Computerized Clinical Decision Support Tool for Fall Risk Management in Primary Care.

BACKGROUND: Falls are a widespread and persistent problem for community-dwelling older adults. Use of fall prevention guidelines in the primary care setting has been suboptimal. Interoperable computerized clinical decision support systems have the potential to increase engagement with fall risk management at scale. To support fall risk management across organizations, our team developed the ASPIRE tool for use in differing primary care clinics using interoperable standards. OBJECTIVES: Usability testing of ASPIRE was conducted to measure ease of access, overall usability, learnability, and acceptability prior to pilot . METHODS: Participants were recruited using purposive sampling from two sites with different electronic health records and different clinical organizations. Formative testing rooted in user-centered design was followed by summative testing using a simulation approach. During summative testing participants used ASPIRE across two clinical scenarios and were randomized to determine which scenario they saw first. Single Ease Question and System Usability Scale were used in addition to analysis of recorded sessions in NVivo. RESULTS: All 14 participants rated the usability of ASPIRE as above average based on usability benchmarks for the System Usability Scale metric. Time on task decreased significantly between the first and second scenarios indicating good learnability. However, acceptability data were more mixed with some recommendations being consistently accepted while others were adopted less frequently. CONCLUSION: This study described the usability testing of the ASPIRE system within two different organizations using different electronic health records. Overall, the system was rated well, and further pilot testing should be done to validate that these positive results translate into clinical practice. Due to its interoperable design, ASPIRE could be integrated into diverse organizations allowing a tailored implementation without the need to build a new system for each organization. This distinction makes ASPIRE well positioned to impact the challenge of falls at scale.

Dynamic reaction picklist for improving allergy reaction documentation: A usability study.

OBJECTIVE: To assess novel dynamic reaction picklists for improving allergy reaction documentation compared to a static reaction picklist. MATERIALS AND METHODS: We developed three web-based user interfaces (UIs) mimicking the Mass General Brigham's EHR allergy module: the first and second UIs (i.e., UI-1D, UI-2D) implemented two dynamic reaction picklists with different ranking algorithms and the third UI (UI-3S) implemented a static reaction picklist like the one used in the current EHR. We recruited 18 clinicians to perform allergy entry for 10 test cases each via UI-1D and UI-3S, and another 18 clinicians via UI-2D and UI-3S. Primary measures were the number of free-text entries and time to complete the allergy entry. Clinicians were also interviewed using 30 questions before and after the data entry. RESULTS AND DISCUSSIONS: Among 36 clinicians, less than half were satisfied with the current EHR reaction picklists, due to their incomprehensiveness, inefficiency, and lack of intuitiveness. The clinicians used significantly fewer free-text entries when using UI-1D or UI-2D compared to UI-3S (p < 0.05). The clinicians used on average 51 s (15 %) less time via UI-1D and 50 s (16 %) less time via UI-2D in completing the allergy entries versus UI-3S, and there was not a statistically significant difference in documentation time for either group between the dynamic and static UIs. Overall, 15-17 (83-94 %) clinicians rated UI-1D and 13-15 (72-83 %) clinicians rated UI-2D as efficient, easy to use, and useful, while less than half rated the same for UI-3S. Most clinicians reported that the dynamic reaction picklists always or often suggested appropriate reactions (n = 30, 83 %) and would decrease the free-text entries (n = 26, 72 %); nearly all preferred the dynamic picklist over the static picklist (n = 32, 89 %). CONCLUSION: We found that dynamic reaction picklists significantly reduced the number of free-text entries and could reduce the time for allergy documentation by 15%. Clinicians preferred the dynamic reaction picklist over the static picklist.

Development and Usability Testing of an Exercise-Based Primary Care Fall Prevention Clinical Decision Support Tool.

For older patients, falls are the leading cause offatal and nonfatal injuries. Guidelines recommend that at-risk older adults are referred to appropriate fall-prevention exercise programs, but many do not receive support for fall-risk management in the primary care setting. Advances in health information technology may be able to address this gap. This article describes the development and usability testing of a clinical decision support (CDS) tool for fall prevention exercise. Using rapid qualitative analysis and human-centered design, our team developed and tested the usability of our CDS prototype with primary care team members. Across 31 Health-Information Technology Usability Evaluation Scale surveys, our CDS prototype received a median score of 5.0, mean (SD) of 4.5 (0.8), and a range of 4.1-4.9. This study highlights the features and usability offall prevention CDS for helping primary care providers deliver patient-centeredfall prevention care.

Human-centered design of clinical decision support for management of hypertension with chronic kidney disease.

BACKGROUND: Primary care providers face challenges in recognizing and controlling hypertension in patients with chronic kidney disease (CKD). Clinical decision support (CDS) has the potential to aid clinicians in identifying patients who could benefit from medication changes. This study designed an alert to control hypertension in CKD patients using an iterative human-centered design process. METHODS: In this study, we present a human-centered design process employing multiple methods for gathering user requirements and feedback on design and usability. Initially, we conducted contextual inquiry sessions to gather user requirements for the CDS. This was followed by group design sessions and one-on-one formative think-aloud sessions to validate requirements, obtain feedback on the design and layout, uncover usability issues, and validate changes. RESULTS: This study included 20 participants. The contextual inquiry produced 10 user requirements which influenced the initial alert design. The group design sessions revealed issues related to several themes, including recommendations and clinical content that did not match providers' expectations and extraneous information on the alerts that did not provide value. Findings from the individual think-aloud sessions revealed that participants disagreed with some recommended clinical actions, requested additional information, and had concerns about the placement in their workflow. Following each step, iterative changes were made to the alert content and design. DISCUSSION: This study showed that participation from users throughout the design process can lead to a better understanding of user requirements and optimal design, even within the constraints of an EHR alerting system. While raising awareness of design needs, it also revealed concerns related to workflow, understandability, and relevance. CONCLUSION: The human-centered design framework using multiple methods for CDS development informed the creation of an alert to assist in the treatment and recognition of hypertension in patients with CKD.

Clinical Decision Support for Fall Prevention: Defining End-User Needs.

BACKGROUND AND SIGNIFICANCE: Falls in community-dwelling older adults are common, and there is a lack of clinical decision support (CDS) to provide health care providers with effective, individualized fall prevention recommendations. OBJECTIVES: The goal of this research is to identify end-user (primary care staff and patients) needs through a human-centered design process for a tool that will generate CDS to protect older adults from falls and injuries. METHODS: Primary care staff (primary care providers, care coordinator nurses, licensed practical nurses, and medical assistants) and community-dwelling patients aged 60 years or older associated with Brigham & Women's Hospital-affiliated primary care clinics and the University of Florida Health Archer Family Health Care primary care clinic were eligible to participate in this study. Through semi-structured and exploratory interviews with participants, our team identified end-user needs through content analysis. RESULTS: User needs for primary care staff (n = 24) and patients (n = 18) were categorized under the following themes: workload burden; systematic communication; in-person assessment of patient condition; personal support networks; motivational tools; patient understanding of fall risk; individualized resources; and evidence-based safe exercises and expert guidance. While some of these themes are specific to either primary care staff or patients, several address needs expressed by both groups of end-users. CONCLUSION: Our findings suggest that there are many care gaps in fall prevention management in primary care and that personalized, actionable, and evidence-based CDS has the potential to address some of these gaps.

Usability of a perioperative medication-related clinical decision support software application: a randomized controlled trial.

OBJECTIVE: We developed a comprehensive, medication-related clinical decision support (CDS) software prototype for use in the operating room. The purpose of this study was to compare the usability of the CDS software to the current standard electronic health record (EHR) medication administration and documentation workflow. MATERIALS AND METHODS: The primary outcome was the time taken to complete all simulation tasks. Secondary outcomes were the total number of mouse clicks and the total distance traveled on the screen in pixels. Forty participants were randomized and assigned to complete 7 simulation tasks in 1 of 2 groups: (1) the CDS group (n = 20), who completed tasks using the CDS and (2) the Control group (n = 20), who completed tasks using the standard medication workflow with retrospective manual documentation in our anesthesia information management system. Blinding was not possible. We video- and audio-recorded the participants to capture quantitative data (time on task, mouse clicks, and pixels traveled on the screen) and qualitative data (think-aloud verbalization). RESULTS: The CDS group mean total task time (402.2 ± 85.9 s) was less than the Control group (509.8 ± 103.6 s), with a mean difference of 107.6 s (95% confidence interval [CI], 60.5-179.5 s, P < .001). The CDS group used fewer mouse clicks (26.4 ± 4.5 clicks) than the Control group (56.0 ± 15.0 clicks) with a mean difference of 29.6 clicks (95% CI, 23.2-37.6, P < .001). The CDS group had fewer pixels traveled on the computer monitor (59.5 ± 20.0 thousand pixels) than the Control group (109.3 ± 40.8 thousand pixels) with a mean difference of 49.8 thousand pixels (95% CI, 33.0-73.7, P < .001). CONCLUSIONS: The perioperative medication-related CDS software prototype substantially outperformed standard EHR workflow by decreasing task time and improving efficiency and quality of care in a simulation setting.

Development of a Perioperative Medication-Related Clinical Decision Support Tool to Prevent Medication Errors: An Analysis of User Feedback.

OBJECTIVES: Medication use in the perioperative setting presents many patient safety challenges that may be improved with electronic clinical decision support (CDS). The objective of this paper is to describe the development and analysis of user feedback for a robust, real-time medication-related CDS application designed to provide patient-specific dosing information and alerts to warn of medication errors in the operating room (OR). METHODS: We designed a novel perioperative medication-related CDS application in four phases: (1) identification of need, (2) alert algorithm development, (3) system design, and (4) user interface design. We conducted group and individual design feedback sessions with front-line clinician leaders and subject matter experts to gather feedback about user requirements for alert content and system usability. Participants were clinicians who provide anesthesia (attending anesthesiologists, nurse anesthetists, and house staff), OR pharmacists, and nurses. RESULTS: We performed two group and eight individual design feedback sessions, with a total of 35 participants. We identified 20 feedback themes, corresponding to 19 system changes. Key requirements for user acceptance were: Use hard stops only when necessary; provide as much information as feasible about the rationale behind alerts and patient/clinical context; and allow users to edit fields such as units, time, and baseline values (e.g., baseline blood pressure). CONCLUSION: We incorporated user-centered design principles to build a perioperative medication-related CDS application that uses real-time patient data to provide patient-specific dosing information and alerts. Emphasis on early user involvement to elicit user requirements, workflow considerations, and preferences during application development can result in time and money efficiencies and a safer and more usable system.

Physician use of speech recognition versus typing in clinical documentation: A controlled observational study.

IMPORTANCE: Speech recognition (SR) is increasingly used directly by clinicians for electronic health record (EHR) documentation. Its usability and effect on quality and efficiency versus other documentation methods remain unclear. OBJECTIVE: To study usability and quality of documentation with SR versus typing. DESIGN: In this controlled observational study, each subject participated in two of five simulated outpatient scenarios. Sessions were recorded with Morae® usability software. Two notes were documented into the EHR per encounter (one dictated, one typed) in randomized order. Participants were interviewed about each method's perceived advantages and disadvantages. Demographics and documentation habits were collected via survey. Data collection occurred between January 8 and February 8, 2019, and data analysis was conducted from February through September of 2019. SETTING: Brigham and Women's Hospital, Boston, Massachusetts, USA. PARTICIPANTS: Ten physicians who had used SR for at least six months. MAIN OUTCOMES AND MEASURES: Documentation time, word count, vocabulary size, number of errors, number of corrections and quality (clarity, completeness, concision, information sufficiency and prioritization). RESULTS: Dictated notes were longer than typed notes (320.6 vs. 180.8 words; p = 0.004) with more unique words (170.9 vs. 120.4; p = 0.01). Documentation time was similar between methods, with dictated notes taking slightly less time to complete than typed notes. Typed notes had more uncorrected errors per note than dictated notes (2.9 vs. 1.5), although most were minor misspellings. Dictated notes had a higher mean quality score (7.7 vs. 6.6; p = 0.04), were more complete and included more sufficient information. CONCLUSIONS AND RELEVANCE: Participants felt that SR saves them time, increases their efficiency and allows them to quickly document more relevant details. Quality analysis supports the perception that SR allows for more detailed notes, but whether dictation is objectively faster than typing remains unclear, and participants described some scenarios where typing is still preferred. Dictation can be effective for creating comprehensive documentation, especially when physicians like and feel comfortable using SR. Research is needed to further improve integration of SR with EHR systems and assess its impact on clinical practice, workflows, provider and patient experience, and costs.

Assessing the cognitive and work load of an inpatient safety dashboard in the context of opioid management.

For health information technology to realize its potential to improve flow, care, and patient safety, applications should be intuitive to use and burden neutral for frontline clinicians. We assessed the impact of a patient safety dashboard on clinician cognitive and work load within a simulated information-seeking task for safe inpatient opioid medication management. Compared to use of an electronic health record for the same task, the dashboard was associated with significantly reduced time on task, mouse clicks, and mouse movement (each p < 0.001), with no significant increases in cognitive load nor task inaccuracy. Cognitive burden was higher for users with less experience, possibly partly attributable to usability issues identified during this study. Findings underscore the importance of assessing the usability, cognitive, and work load analysis during the design and implementation of health information technology applications.

Comparison of a Prototype for Indications-Based Prescribing With 2 Commercial Prescribing Systems.

Importance: The indication (reason for use) for a medication is rarely included on prescriptions despite repeated recommendations to do so. One barrier has been the way existing electronic prescribing systems have been designed. Objective: To evaluate, in comparison with the prescribing modules of 2 leading electronic health record prescribing systems, the efficiency, error rate, and satisfaction with a new computerized provider order entry prototype for the outpatient setting that allows clinicians to initiate prescribing using the indication. Design, Setting, and Participants: This quality improvement study used usability tests requiring internal medicine physicians, residents, and physician assistants to enter prescriptions electronically, including indication, for 8 clinical scenarios. The tool order assignments were randomized and prescribers were asked to use the prototype for 4 of the scenarios and their usual system for the other 4. Time on task, number of clicks, and order details were captured. User satisfaction was measured using posttask ratings and a validated system usability scale. The study participants practiced in 2 health systems' outpatient practices. Usability tests were conducted between April and October of 2017. Main Outcomes and Measures: Usability (efficiency, error rate, and satisfaction) of indications-based computerized provider order entry prototype vs the electronic prescribing interface of 2 electronic health record vendors. Results: Thirty-two participants (17 attending physicians, 13 residents, and 2 physician assistants) used the prototype to complete 256 usability test scenarios. The mean (SD) time on task was 1.78 (1.17) minutes. For the 20 participants who used vendor 1's system, it took a mean (SD) of 3.37 (1.90) minutes to complete a prescription, and for the 12 participants using vendor 2's system, it took a mean (SD) of 2.93 (1.52) minutes. Across all scenarios, when comparing number of clicks, for those participants using the prototype and vendor 1, there was a statistically significant difference from the mean (SD) number of clicks needed (18.39 [12.62] vs 46.50 [27.29]; difference, 28.11; 95% CI, 21.47-34.75; P < .001). For those using the prototype and vendor 2, there was also a statistically significant difference in number of clicks (20.10 [11.52] vs 38.25 [19.77]; difference, 18.14; 95% CI, 11.59-24.70; P < .001). A blinded review of the order details revealed medication errors (eg, drug-allergy interactions) in 38 of 128 prescribing sessions using a vendor system vs 7 of 128 with the prototype. Conclusions and Relevance: Reengineering prescribing to start with the drug indication allowed indications to be captured in an easy and useful way, which may be associated with saved time and effort, reduced medication errors, and increased clinician satisfaction.