A Personalized and Interactive Web-Based Advance Care Planning Intervention for Older Adults (Koda Health): Pilot Feasibility Study.

Background: Advance care planning (ACP) is a process that involves patients expressing their personal goals, values, and future medical care preferences. Digital applications may help facilitate this process, though their use in older adults has not been adequately studied. Objective: This pilot study aimed to evaluate the reach, adoption, and usability of Koda Health, a web-based patient-facing ACP platform, among older adults. Methods: Older adults (aged 50 years and older) who had an active Epic MyChart account at an academic health care system in North Carolina were recruited to participate. A total of 2850 electronic invitations were sent through MyChart accounts with an embedded hyperlink to the Koda platform. Participants who agreed to participate were asked to complete pre- and posttest surveys before and after navigating through the Koda Health platform. Primary outcomes were reach, adoption, and System Usability Scale (SUS) scores. Exploratory outcomes included ACP knowledge and readiness. Results: A total of 161 participants enrolled in the study and created an account on the platform (age: mean 63, SD 9.3 years), with 80% (129/161) of these participants going on to complete all steps of the intervention, thereby generating an advance directive. Participants reported minimal difficulty in using the Koda platform, with an overall SUS score of 76.2. Additionally, knowledge of ACP (eg, mean increase from 3.2 to 4.2 on 5-point scale; P<.001) and readiness (eg, mean increase from 2.6 to 3.2 on readiness to discuss ACP with health care provider; P<.001) significantly increased from before to after the intervention. Conclusions: This study demonstrated that the Koda Health platform is feasible, had above-average usability, and improved ACP documentation of preferences in older adults. Our findings indicate that web-based health tools like Koda may help older individuals learn about and feel more comfortable with ACP while potentially facilitating greater engagement in care planning.

Assessment of EHR Efficiency Tools and Resources Associated with Physician Time Spent on the Inbox.

BACKGROUND: Physicians are experiencing an increasing burden of messaging within the electronic health record (EHR) inbox. Studies have called for the implementation of tools and resources to mitigate this burden, but few studies have evaluated how these interventions impact time spent on inbox activities. OBJECTIVE: Explore the association between existing EHR efficiency tools and clinical resources on primary care physician (PCP) inbox time. DESIGN: Retrospective, cross-sectional study of inbox time among PCPs in network clinics affiliated with an academic health system. PARTICIPANTS: One hundred fifteen community-based PCPs. MAIN MEASURES: Inbox time, in hours, normalized to eight physician scheduled hours (IB-Time8). KEY RESULTS: Following adjustment for physician sex as well as panel size, age, and morbidity, we observed no significant differences in inbox time for physicians with and without message triage, custom inbox QuickActions, encounter specialists, and message pools. Moreover, IB-Time8 increased by 0.01 inbox hours per eight scheduled hours for each additional staff member resource in a physician's practice (p = 0.03). CONCLUSIONS: Physician inbox time was not associated with existing EHR efficiency tools evaluated in this study. Yet, there may be a slight increase in inbox time among physicians in practices with larger teams.

Monitoring the Implementation of Tobacco Cessation Support Tools: Using Novel Electronic Health Record Activity Metrics.

BACKGROUND: Clinical decision support (CDS) tools in electronic health records (EHRs) are often used as core strategies to support quality improvement programs in the clinical setting. Monitoring the impact (intended and unintended) of these tools is crucial for program evaluation and adaptation. Existing approaches for monitoring typically rely on health care providers' self-reports or direct observation of clinical workflows, which require substantial data collection efforts and are prone to reporting bias. OBJECTIVE: This study aims to develop a novel monitoring method leveraging EHR activity data and demonstrate its use in monitoring the CDS tools implemented by a tobacco cessation program sponsored by the National Cancer Institute's Cancer Center Cessation Initiative (C3I). METHODS: We developed EHR-based metrics to monitor the implementation of two CDS tools: (1) a screening alert reminding clinic staff to complete the smoking assessment and (2) a support alert prompting health care providers to discuss support and treatment options, including referral to a cessation clinic. Using EHR activity data, we measured the completion (encounter-level alert completion rate) and burden (the number of times an alert was fired before completion and time spent handling the alert) of the CDS tools. We report metrics tracked for 12 months post implementation, comparing 7 cancer clinics (2 clinics implemented the screening alert and 5 implemented both alerts) within a C3I center, and identify areas to improve alert design and adoption. RESULTS: The screening alert fired in 5121 encounters during the 12 months post implementation. The encounter-level alert completion rate (clinic staff acknowledged completion of screening in EHR: 0.55; clinic staff completed EHR documentation of screening results: 0.32) remained stable over time but varied considerably across clinics. The support alert fired in 1074 encounters during the 12 months. Providers acted upon (ie, not postponed) the support alert in 87.3% (n=938) of encounters, identified a patient ready to quit in 12% (n=129) of encounters, and ordered a referral to the cessation clinic in 2% (n=22) of encounters. With respect to alert burden, on average, both alerts fired over 2 times (screening alert: 2.7; support alert: 2.1) before completion; time spent postponing the screening alert was similar to completing (52 vs 53 seconds) the alert, and time spent postponing the support alert was more than completing (67 vs 50 seconds) the alert per encounter. These findings inform four areas where the alert design and use can be improved: (1) improving alert adoption and completion through local adaptation, (2) improving support alert efficacy by additional strategies including training in provider-patient communication, (3) improving the accuracy of tracking for alert completion, and (4) balancing alert efficacy with the burden. CONCLUSIONS: EHR activity metrics were able to monitor the success and burden of tobacco cessation alerts, allowing for a more nuanced understanding of potential trade-offs associated with alert implementation. These metrics can be used to guide implementation adaptation and are scalable across diverse settings.

Development of an Advance Care Planning Portal-Based Tool for Community-Dwelling Persons Living With Cognitive Impairment: The ACPVoice Tool.

Background: Patient portals can be an innovative and efficient way to engage patients in advance care planning (ACP). However, comprehension and judgment in older adults with cognitive impairment presents several barriers and challenges to engaging in new technology. Our objective was to develop an ACP portal-based tool (ACPVoice) for community-dwelling persons living with cognitive impairment (PLCI) by engaging end-users in the design process. Methods: Two rounds of cognitive interviews were conducted to identify and resolve cognitive issues related to comprehension, judgment, response, and to assess content validity. Purposive sampling was used with the goal of enrolling 15 different participants (five with mild cognitive impairment and five dyads (those with mild dementia and their care partner) in each round to assess respondents' understanding of questions related to advance care planning to be administered via the patient portal. Results: Twenty PLCI (mean age 78.4, 10 females [50%]) and ten care partners (mean age 60.9, 9 females [90%]) completed cognitive interviews between May 2021 and October 2021. The mean Mini-Mental State Examination score for PLCI was 25.6 (SD 2.6). Unclear wording and undefined vague and/or unfamiliar terms were the major issues identified. Revisions to item wording, response options, and instructions were made to improve question comprehension and response as well as navigational ease. Conclusion: Minor changes to the wording, format, and response options substantially improved respondents' ability to interpret the item content of the ACPVoice tool. Dissemination and implementation of the ACPVoice tool could help to engage community-dwelling PLCI in ACP discussions.

Using an Electronic Health Record and Deficit Accumulation to Pragmatically Identify Candidates for Optimal Prescribing in Patients With Type 2 Diabetes.

Objective: Despite guidelines recommending less stringent glycemic goals for older adults with type 2 diabetes, overtreatment is prevalent. Pragmatic approaches for prioritizing patients for optimal prescribing are lacking. We describe glycemic control and medication patterns for older adults with type 2 diabetes in a contemporary cohort, exploring variability by frailty status. Research Design and Methods: This was a cross-sectional observational study based on electronic health record (EHR) data, within an accountable care organization (ACO) affiliated with an academic medical center/health system. Participants were ACO-enrolled adults with type 2 diabetes who were ≥65 years of age as of 1 November 2020. Frailty status was determined by an automated EHR-based frailty index (eFI). Diabetes management was described by the most recent A1C in the past 2 years and use of higher-risk medications (insulin and/or sulfonylurea). Results: Among 16,973 older adults with type 2 diabetes (mean age 75.2 years, 9,154 women [53.9%], 77.8% White), 9,134 (53.8%) and 6,218 (36.6%) were classified as pre-frail (0.10 < eFI ≤0.21) or frail (eFI >0.21), respectively. The median A1C level was 6.7% (50 mmol/mol) with an interquartile range of 6.2-7.5%, and 74.1 and 38.3% of patients had an A1C <7.5% (58 mmol/mol) and <6.5% (48 mmol/mol), respectively. Frailty status was not associated with level of glycemic control (P = 0.08). A majority of frail patients had an A1C <7.5% (58 mmol/mol) (n = 4,544, 73.1%), and among these patients, 1,755 (38.6%) were taking insulin and/or a sulfonylurea. Conclusion: Treatment with insulin and/or a sulfonylurea to an A1C levels <7.5% is common in frail older adults. Tools such as the eFI may offer a scalable approach to targeting optimal prescribing interventions.

Feasibility of computerized clinical decision support for pediatric to adult care transitions for patients with special healthcare needs.

The objective of this study was to determine the feasibility of a computerized clinical decision support (cCDS) tool to facilitate referral to adult healthcare services for children with special healthcare needs. A transition-specific cCDS was implemented as part of standard care in a general pediatrics clinic at a tertiary care academic medical center. The cCDS alerts providers to patients 17-26 years old with 1 or more of 15 diagnoses that may be candidates for referral to an internal medicine adult transition clinic (ATC). Provider responses to the cCDS and referral outcomes (e.g. scheduled and completed visits) were retrospectively analyzed using descriptive statistics. One hundred and fifty-two patients were seen during the 20-month observation period. Providers referred 87 patients to the ATC using cCDS and 77% of patients ≥18 years old scheduled a visit in the ATC. Transition-specific cCDS tools are feasible options to facilitate adult care transitions for children with special healthcare needs.

Alert burden in pediatric hospitals: a cross-sectional analysis of six academic pediatric health systems using novel metrics.

BACKGROUND: Excessive electronic health record (EHR) alerts reduce the salience of actionable alerts. Little is known about the frequency of interruptive alerts across health systems and how the choice of metric affects which users appear to have the highest alert burden. OBJECTIVE: (1) Analyze alert burden by alert type, care setting, provider type, and individual provider across 6 pediatric health systems. (2) Compare alert burden using different metrics. MATERIALS AND METHODS: We analyzed interruptive alert firings logged in EHR databases at 6 pediatric health systems from 2016-2019 using 4 metrics: (1) alerts per patient encounter, (2) alerts per inpatient-day, (3) alerts per 100 orders, and (4) alerts per unique clinician days (calendar days with at least 1 EHR log in the system). We assessed intra- and interinstitutional variation and how alert burden rankings differed based on the chosen metric. RESULTS: Alert burden varied widely across institutions, ranging from 0.06 to 0.76 firings per encounter, 0.22 to 1.06 firings per inpatient-day, 0.98 to 17.42 per 100 orders, and 0.08 to 3.34 firings per clinician day logged in the EHR. Custom alerts accounted for the greatest burden at all 6 sites. The rank order of institutions by alert burden was similar regardless of which alert burden metric was chosen. Within institutions, the alert burden metric choice substantially affected which provider types and care settings appeared to experience the highest alert burden. CONCLUSION: Estimates of the clinical areas with highest alert burden varied substantially by institution and based on the metric used.

Automated Frailty Screening At-Scale for Pre-Operative Risk Stratification Using the Electronic Frailty Index.

BACKGROUND: Frailty is associated with numerous post-operative adverse outcomes in older adults. Current pre-operative frailty screening tools require additional data collection or objective assessments, adding expense and limiting large-scale implementation. OBJECTIVE: To evaluate the association of an automated measure of frailty integrated within the Electronic Health Record (EHR) with post-operative outcomes for nonemergency surgeries. DESIGN: Retrospective cohort study. SETTING: Academic Medical Center. PARTICIPANTS: Patients 65 years or older that underwent nonemergency surgery with an inpatient stay 24 hours or more between October 8th, 2017 and June 1st, 2019. EXPOSURES: Frailty as measured by a 54-item electronic frailty index (eFI). OUTCOMES AND MEASUREMENTS: Inpatient length of stay, requirements for post-acute care, 30-day readmission, and 6-month all-cause mortality. RESULTS: Of 4,831 unique patients (2,281 females (47.3%); mean (SD) age, 73.2 (5.9) years), 4,143 (85.7%) had sufficient EHR data to calculate the eFI, with 15.1% categorized as frail (eFI > 0.21) and 50.9% pre-frail (0.10 < eFI ≤ 0.21). For all outcomes, there was a generally a gradation of risk with higher eFI scores. For example, adjusting for age, sex, race/ethnicity, and American Society of Anesthesiologists class, and accounting for variability by service line, patients identified as frail based on the eFI, compared to fit patients, had greater needs for post-acute care (odds ratio (OR) = 1.68; 95% confidence interval (CI) = 1.36-2.08), higher rates of 30-day readmission (hazard ratio (HR) = 2.46; 95%CI = 1.72-3.52) and higher all-cause mortality (HR = 2.86; 95%CI = 1.84-4.44) over 6 months' follow-up. CONCLUSIONS: The eFI, an automated digital marker for frailty integrated within the EHR, can facilitate pre-operative frailty screening at scale.

Effectiveness of a Nurse-Led Multidisciplinary Intervention vs Usual Care on Advance Care Planning for Vulnerable Older Adults in an Accountable Care Organization: A Randomized Clinical Trial.

Importance: Advance care planning (ACP), especially among vulnerable older adults, remains underused in primary care. Additionally, many ACP initiatives fail to integrate directly into the electronic health record (EHR), resulting in infrequent and disorganized documentation. Objective: To determine whether a nurse navigator-led ACP pathway combined with a health care professional-facing EHR interface improves the occurrence of ACP discussions and their documentation within the EHR. Design, Setting, and Participants: This was a randomized effectiveness trial using the Zelen design, in which patients are randomized prior to informed consent, with only those randomized to the intervention subsequently approached to provide informed consent. Randomization began November 1, 2018, and follow-up concluded November 1, 2019. The study population included patients 65 years or older with multimorbidity combined with either cognitive or physical impairments, and/or frailty, assessed from 8 primary care practices in North Carolina. Interventions: Participants were randomized to either a nurse navigator-led ACP pathway (n = 379) or usual care (n = 380). Main Outcomes and Measures: The primary outcome was documentation of a new ACP discussion within the EHR. Secondary outcomes included the usage of ACP billing codes, designation of a surrogate decision maker, and ACP legal form documentation. Exploratory outcomes included incident health care use. Results: Among 759 randomized patients (mean age 77.7 years, 455 women [59.9%]), the nurse navigator-led ACP pathway resulted in a higher rate of ACP documentation (42.2% vs 3.7%, P < .001) as compared with usual care. The ACP billing codes were used more frequently for patients randomized to the nurse navigator-led ACP pathway (25.3% vs 1.3%, P < .001). Patients randomized to the nurse navigator-led ACP pathway more frequently designated a surrogate decision maker (64% vs 35%, P < .001) and completed ACP legal forms (24.3% vs 10.0%, P < .001). During follow-up, the incidence of emergency department visits and inpatient hospitalizations was similar between the randomized groups (hazard ratio, 1.17; 95% CI, 0.92-1.50). Conclusions and Relevance: A nurse navigator-led ACP pathway integrated with a health care professional-facing EHR interface increased the frequency of ACP discussions and their documentation. Additional research will be required to evaluate whether increased EHR documentation leads to improvements in goal-concordant care. Trial Registration: ClinicalTrials.gov Identifier: NCT03609658.

Feasibility of Mobile Technology to Identify and Address Patients' Unmet Social Needs in a Primary Care Clinic.

Mobile health tools may overcome barriers to social needs screening; however, there are limited data on the feasibility of using these tools in clinical settings. The objective was to determine the feasibility of using a mobile health system to screen for patients' social needs. In one large primary care clinic, the authors tested a tablet-based system that screens patients for social needs, transmits results to the electronic health record, and alerts providers. All adult patients presenting for a nonurgent visit were eligible. The authors evaluated the feasibility of the system and conducted follow-up surveys to determine acceptability and if patients accessed resources through the process. All providers were surveyed. Of the 252 patients approached, 219 (86.9%) completed the screen. Forty-three (19.6%) required assistance with the tablet, and 150 (68.5%) screened positive for at least 1 unmet need (food, housing, or transportation). Of the 150, 103 (68.7%) completed a follow-up survey. The majority agreed that people would learn to use the tablet quickly. Forty-eight patients (46.6%) reported contacting at least 1 community organization through the process. Of the 27 providers, 23 (85.2%) completed a survey and >70% agreed the system would result in patients having better access to resources. It was feasible to use a tablet-based system to screen for social needs. Clinics considering using mobile tools will need to determine how to screen patients who may need assistance with the tool and how to connect patients to resources through the system based on the burden of unmet needs.

The Generalizability of a Medication Administration Discrepancy Detection System: Quantitative Comparative Analysis.

BACKGROUND: As a result of the overwhelming proportion of medication errors occurring each year, there has been an increased focus on developing medication error prevention strategies. Recent advances in electronic health record (EHR) technologies allow institutions the opportunity to identify medication administration error events in real time through computerized algorithms. MED.Safe, a software package comprising medication discrepancy detection algorithms, was developed to meet this need by performing an automated comparison of medication orders to medication administration records (MARs). In order to demonstrate generalizability in other care settings, software such as this must be tested and validated in settings distinct from the development site. OBJECTIVE: The purpose of this study is to determine the portability and generalizability of the MED.Safe software at a second site by assessing the performance and fit of the algorithms through comparison of discrepancy rates and other metrics across institutions. METHODS: The MED.Safe software package was executed on medication use data from the implementation site to generate prescribing ratios and discrepancy rates. A retrospective analysis of medication prescribing and documentation patterns was then performed on the results and compared to those from the development site to determine the algorithmic performance and fit. Variance in performance from the development site was further explored and characterized. RESULTS: Compared to the development site, the implementation site had lower audit/order ratios and higher MAR/(order + audit) ratios. The discrepancy rates on the implementation site were consistently higher than those from the development site. Three drivers for the higher discrepancy rates were alternative clinical workflow using orders with dosing ranges; a data extract, transfer, and load issue causing modified order data to overwrite original order values in the EHRs; and delayed EHR documentation of verbal orders. Opportunities for improvement were identified and applied using a software update, which decreased false-positive discrepancies and improved overall fit. CONCLUSIONS: The execution of MED.Safe at a second site was feasible and effective in the detection of medication administration discrepancies. A comparison of medication ordering, administration, and discrepancy rates identified areas where MED.Safe could be improved through customization. One modification of MED.Safe through deployment of a software update improved the overall algorithmic fit at the implementation site. More flexible customizations to accommodate different clinical practice patterns could improve MED.Safe's fit at new sites.

Considerations for Integrating Advance Care Planning Into the Electronic Health Record: A Primer for Clinicians.

Opportunities for expanding advance care planning (ACP) throughout the health-care system make it critical that primary care (PC) providers have a basic understanding of how the electronic health record (EHR) can aid promoting ACP discussions and documentation. This article will offer PC providers 5 useful tips for implementing ACP in outpatient settings utilizing the EHR.

Advance care planning for vulnerable older adults within an Accountable Care Organization: study protocol for the IMPACT randomised controlled trial.

INTRODUCTION: Patients with multimorbidity plus additional impairments (eg, mobility limitations, disability, cognitive impairments or frailty) are at the highest risk for poor healthcare outcomes. Advanced care planning (ACP) provides patients and their surrogates the opportunity to discuss their goals, values and priorities for healthcare-particularly in the context of end-of-life care. ACP discussions promote more person-centred care; however, it is currently underused. There is a tremendous need for systematic, scalable approaches to individualised ACP that promotes patient and family engagement. Here we describe the study protocol for a randomised effectiveness trial of a nurse navigator and informatics intervention designed to improve the documentation and quality of ACP discussions. METHODS AND ANALYSIS: This is a randomised, pragmatic, effectiveness trial; patients aged 65 years and older who have multimorbidity plus impairments in either physical function (eg, mobility limitations or disability) or cognition, and/or frailty within an affiliated Accountable Care Organization were eligible. The electronic health record was used to develop an automatic prescreening system for eligible patients (n=765) and participants were randomised in a 1:1 ratio to either the nurse navigator-led ACP pathway or usual care. Our primary outcomes are documentation of ACP discussions within the EHR along with the quality of ACP discussions. Secondary outcomes include a broad range of ACP actions (eg, usage of ACP billing codes, choosing a surrogate decision-maker and advance directive documentation). Outcomes will be measured over 12 months of follow-up. ETHICS AND DISSEMINATION: This study has been approved by the appropriate Institutional Review Boards and is guided by input from patient and clinical advisory boards. The results of this study will inform a scalable solution to ACP discussions throughout our healthcare system and statewide. TRIALS REGISTRATION NUMBER: NCT03609658.