Patients' Perspectives on Plans Generated During Primary Care Visits and Self-Reported Adherence at 3 Months: Data From a Randomized Trial.

BACKGROUND: Effective primary care necessitates follow-up actions by the patient beyond the visit. Prior research suggests room for improvement in patient adherence. OBJECTIVE: This study sought to understand patients' views on their primary care visits, the plans generated therein, and their self-reported adherence after 3 months. METHODS: As part of a large multisite cluster randomized pragmatic trial in 3 health care organizations, patients completed 2 surveys-the first within 7 days after the index primary care visit and another 3 months later. For this analysis of secondary outcomes, we combined the results across all study participants to understand patient adherence to care plans. We recorded patient characteristics and survey responses. Cross-tabulation and chi-square statistics were used to examine bivariate associations, adjusting for multiple comparisons when appropriate. We used multivariable logistic regression to assess how patients' intention to follow, agreement, and understanding of their plans impacted their plan adherence, allowing for differences in individual characteristics. Qualitative content analysis was conducted to characterize the patient's self-reported plans and reasons for adhering (or not) to the plan 3 months later. RESULTS: Of 2555 patients, most selected the top box option (9=definitely agree) that they felt they had a clear plan (n=2011, 78%), agreed with the plan (n=2049, 80%), and intended to follow the plan (n=2108, 83%) discussed with their provider at the primary care visit. The most common elements of the plans reported included reference to exercise (n=359, 14.1%), testing (laboratory, imaging, etc; n=328, 12.8%), diet (n=296, 11.6%), and initiation or adjustment of medications; (n=284, 11.1%). Patients who strongly agreed that they had a clear plan, agreed with the plan, and intended to follow the plan were all more likely to report plan completion 3 months later (P<.001) than those providing less positive ratings. Patients who reported plans related to following up with the primary care provider (P=.008) to initiate or adjust medications (P≤.001) and to have a specialist visit were more likely to report that they had completely followed the plan (P=.003). Adjusting for demographic variables, patients who indicated intent to follow their plan were more likely to follow-through 3 months later (P<.001). Patients' reasons for completely following the plan were mainly that the plan was clear (n=1114, 69.5%), consistent with what mattered (n=1060, 66.1%), and they were determined to carry through with the plan (n=887, 53.3%). The most common reasons for not following the plan were lack of time (n=217, 22.8%), having decided to try a different approach (n=105, 11%), and the COVID-19 pandemic impacted the plan (n=105, 11%). CONCLUSIONS: Patients' initial assessment of their plan as clear, their agreement with the plan, and their initial willingness to follow the plan were all strongly related to their self-reported completion of the plan 3 months later. Patients whose plans involved lifestyle changes were less likely to report that they had "completely" followed their plan. TRIAL REGISTRATION: ClinicalTrials.gov NCT03385512; https://clinicaltrials.gov/study/NCT03385512. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/30431.

Targeting patients for early COVID-19 therapy; Pre-infection metabolic dysfunction, polycystic ovary syndrome and risk of severe disease in patients under 65: A Massachusetts community-based observational study.

INTRODUCTION: The demographics of those developing severe coronavirus disease (COVID-19) outcomes are shifting to younger patients. In an observational study utilizing electronic health records from a Massachusetts group medical practice, we identified 5025 patients with confirmed COVID-19 from March 1 to December 18, 2020. Of these, 3870 were under 65 years of age. We investigated the hypothesis that pre-infection metabolic or immunologic dysregulation including polycystic ovary syndrome (PCOS) increased risk of serious COVID-19 outcomes in patients under 65 years of age. MATERIALS AND METHODS: We compared those with COVID-19 related hospitalization or mortality to all other COVID-19 patients, using a case control approach. Using logistic regression and propensity score modeling, we evaluated risk of developing severe COVID-19 outcomes (hospitalization or death) in those with pre-infection comorbidities, metabolic risk factors, or PCOS. RESULTS: Overall, propensity score matched analyses demonstrated pre-infection elevated liver enzymes alanine aminotransferase (ALT) >40, aspartate aminotransferase (AST) >40 and blood glucose ≥215 mg/dL were associated with more severe COVID-19 outcomes, OR = 1.74 (95% CI 1.31, 2.31); OR = 1.98 (95% CI 1.52, 2.57), and OR = 1.55 (95% CI 1.08, 2.23) respectively. Elevated hemoglobin A1C or blood glucose levels were even stronger risk factors for severe COVID-19 outcomes among those aged < 65, OR = 2.31 (95% CI 1.14, 4.66) and OR = 2.42 (95% CI 1.29, 4.56), respectively. In logistic regression models, women aged < 65 with PCOS demonstrated more than a four-fold increased risk of severe COVID-19, OR 4.64 (95% CI 1.98, 10.88). CONCLUSION: Increased risk of severe COVID-19 outcomes in those < age 65 with pre-infection indicators of metabolic dysfunction heightens the importance of monitoring pre-infection indicators in younger patients for prevention and early treatment. The PCOS finding deserves further investigation. Meanwhile women who suffer from PCOS should be carefully evaluated and prioritized for earlier COVID-19 treatment and vaccination.

Trends in breast and prostate cancer screening and diagnostic procedures during the COVID-19 pandemic in central Massachusetts.

PURPOSE: We calculated rates of breast and prostate cancer screening and diagnostic procedures performed during the COVID-19 pandemic through December 2021 compared to the same months in 2019 in a large healthcare provider group in central Massachusetts. METHODS: We included active patients of the provider group between January 2019 and December 2021 aged 30-85 years. Monthly rates of screening mammography and digital breast tomosynthesis, breast MRI, total prostate specific antigen (PSA), and breast or prostate biopsy per 1,000 people were compared by year overall, by age, and race/ethnicity. Completed procedures were identified by relevant codes in electronic health record data. RESULTS: Rates of screening mammography, tomosynthesis, and PSA testing reached the lowest levels in April-May 2020. Breast cancer screening rates decreased 43% in March and 99% in April and May 2020, compared to 2019. Breast cancer screening rates increased gradually beginning in June 2020 through 2021, although more slowly in Black and Hispanic women and in women aged 75-85. PSA testing rates decreased 34% in March, 78% in April, and 53% in May 2020, but rebounded to pre-pandemic levels by June 2020; trends were similar across groups defined by age and race/ethnicity. CONCLUSION: The observed decline in two common screening procedures during the COVID-19 pandemic reflects the impact of the pandemic on cancer early detection and signals potential downstream effects on the prognosis of delayed cancer diagnoses. The slower rate of return for breast cancer screening procedures in certain subgroups should be investigated to ensure all women return for routine screenings.

Using passive extraction of real-world data from eConsent, electronic patient reported outcomes (ePRO) and electronic health record (EHR) data loaded to an electronic data capture (EDC) system for a multi-center, prospective, observational study in diabetic patients.

As clinical trial complexity has increased over the past decade, using electronic methods to simplify recruitment and data management have been investigated. In this study, the Optum Digital Research Network (DRN) has demonstrated the use of electronic source (eSource) data to ease subject identification, recruitment burden, and used data extracted from electronic health records (EHR) to load to an electronic data capture (EDC) system. This study utilized electronic Informed Consent, electronic patient reported outcomes (SF-12) and included three sites using 3 different EHR systems. Patients with type 2 diabetes with an HbA1c ≥ 7.0% treated with metformin monotherapy were recruited. Endpoints consisted of changes in HbA1c, medications, and quality of life measures over 12-weeks of study participation using data from the subjects' eSources listed above. The study began in June of 2020 and the last patient last visit occurred in January of 2021. Forty-eight participants were consented and enrolled. HbA1c was repeated for 33 and ePRO was obtained from all subjects at baseline and 28 at 12-week follow-up. Using eSource data eliminated transcription errors. Medication changes, healthcare encounters and lab results were identified when they occurred in standard clinical practice from the EHR systems. Minimal data transformation and normalization was required. Data for this observational trial where clinical outcomes are available using lab results, diagnoses, and encounters may be achieved via direct access to eSources. This methodology was successful and could be expanded for larger trials and will significantly reduce staff effort and exemplified clinical research as a care option.

Effect of Technology-Assisted Brief Abstinence Game on Long-term Smoking Cessation in Individuals Not Yet Ready to Quit: A Randomized Clinical Trial.

IMPORTANCE: Most trials of behavioral or pharmaceutical interventions for people who smoke are limited to individuals reporting they are ready to quit smoking. Engaging individuals who initially report they are not yet ready to quit in brief, precessation, skills-building interventions (eg, practice quit attempts or nicotine replacement therapy [NRT] sampling) is challenging. OBJECTIVE: To test an integrated behavioral plus NRT-sampling intervention using a gamification approach supported by mobile health. DESIGN, SETTING, AND PARTICIPANTS: A multisite randomized clinical trial with site-level 1-to-1 allocation into 2 conditions was conducted in 4 US health care systems. A total of 433 individuals who were currently smoking and reported at enrollment that they were not ready to quit smoking were enrolled. The study was conducted from November 7, 2016, to July 31, 2020. INTERVENTIONS: Take a Break (TAB) was a 3-week game experience and included 5 behavioral components (motivational messaging, challenge quizzes, brief abstinence goal setting, mobile health apps for cravings management, and reward points for participation) integrated with NRT sampling. TAB draws on social cognitive theory and game mechanics concepts to engage participants in health behavior change. The comparison included NRT sampling only. MAIN OUTCOMES AND MEASURES: Time to first quit attempt (duration from TAB experience to primary outcome) and carbon monoxide level-verified smoking cessation at 6-month follow-up. All analyses used an intention-to-treat approach. RESULTS: Of the 433 individuals included in the trial, 223 were women (52%); mean (SD) age was 54 (13) years. More than half (53% [112 of 213]) of the TAB participants completed 100% of the daily challenge quizzes in the first week, 73% (145 of 199) of participants who completed the goal-setting call set a brief abstinence goal (most frequently 1-2 days of abstinence from cigarettes), and 75% (159 of 213) of participants used the mobile health apps to manage nicotine cravings. Time to the first quit attempt was lower for the TAB vs comparison group (hazard ratio, 1.68; 95% CI, 1.09-2.60; P = .02). At the 6-month follow-up, 18% (28 of 160) of TAB participants and 10% (17 of 171) of the comparison (χ2 test, P = .045) participants obtained carbon monoxide level-verified smoking cessation (accounting for clustering of outcomes by site; odds ratio, 1.92; 95% CI, 1.01-3.68; P = .048). CONCLUSIONS AND RELEVANCE: The findings of this randomized clinical trial demonstrate that individuals not yet ready to quit smoking could be engaged in a brief abstinence game. Six months later, the TAB group had nearly double the rate of smoking cessation vs the NRT sampling comparison group. Integrating a skills-building game experience with brief NRT sampling can enhance long-term cessation among those not yet ready to quit smoking. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02973425.

Implementation of Patient Engagement Tools in Electronic Health Records to Enhance Patient-Centered Communication: Protocol for Feasibility Evaluation and Preliminary Results.

BACKGROUND: Patient-physician communication during clinical encounters is essential to ensure quality of care. Many studies have attempted to improve patient-physician communication. Incorporating patient priorities into agenda setting and medical decision-making are fundamental to patient-centered communication. Efficient and scalable approaches are needed to empower patients to speak up and prepare physicians to respond. Leveraging electronic health records (EHRs) in engaging patients and health care teams has the potential to enhance the integration of patient priorities in clinical encounters. A systematic approach to eliciting and documenting patient priorities before encounters could facilitate effective communication in such encounters. OBJECTIVE: In this paper, we report the design and implementation of a set of EHR tools built into clinical workflows for facilitating patient-physician joint agenda setting and the documentation of patient concerns in the EHRs for ambulatory encounters. METHODS: We engaged health information technology leaders and users in three health care systems for developing and implementing a set of EHR tools. The goal of these tools is to standardize the elicitation of patient priorities by using a previsit "patient important issue" questionnaire distributed through the patient portal to the EHR. We built additional EHR documentation tools to facilitate patient-staff communication when the staff records the vital signs and the reason for the visit in the EHR while in the examination room, with a simple transmission method for physicians to incorporate patient concerns in EHR notes. RESULTS: The study is ongoing. The anticipated completion date for survey data collection is November 2021. A total of 34,037 primary care patients from three health systems (n=26,441; n=5136; and n=2460 separately recruited from each system) used the previsit patient important issue questionnaire in 2020. The adoption of the digital previsit questionnaire during the COVID-19 pandemic was much higher in one health care system because it expanded the use of the questionnaire from physicians participating in trials to all primary care providers midway through the year. It also required the use of this previsit questionnaire for eCheck-ins, which are required for telehealth encounters. Physicians and staff suggested anecdotally that this questionnaire helped patient-clinician communication, particularly during the COVID-19 pandemic. CONCLUSIONS: EHR tools have the potential to facilitate the integration of patient priorities into agenda setting and documentation in real-world primary care practices. Early results suggest the feasibility and acceptability of such digital tools in three health systems. EHR tools can support patient engagement and clinicians' work during in-person and telehealth visits. They could potentially exert a sustained influence on patient and clinician communication behaviors in contrast to prior ad hoc educational efforts targeting patients or clinicians. TRIAL REGISTRATION: ClinicalTrials.gov NCT03385512; https://clinicaltrials.gov/ct2/show/NCT03385512. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/30431.

Effect of a Multifaceted Clinical Pharmacist Intervention on Medication Safety After Hospitalization in Persons Prescribed High-risk Medications: A Randomized Clinical Trial.

Importance: The National Action Plan for Adverse Drug Event (ADE) Prevention identified 3 high-priority, high-risk drug classes as targets for reducing the risk of drug-related injuries: anticoagulants, diabetes agents, and opioids. Objective: To determine whether a multifaceted clinical pharmacist intervention improves medication safety for patients who are discharged from the hospital and prescribed medications within 1 or more of these high-risk drug classes. Design, Setting, and Participants: This randomized clinical trial was conducted at a large multidisciplinary group practice in Massachusetts and included patients 50 years or older who were discharged from the hospital and prescribed at least 1 high-risk medication. Participants were enrolled into the trial from June 2016 through September 2018. Interventions: The pharmacist-directed intervention included an in-home assessment by a clinical pharmacist, evidence-based educational resources, communication with the primary care team, and telephone follow-up. Participants in the control group were provided educational materials via mail. Main Outcomes and Measures: The study assessed 2 outcomes over a 45-day posthospital discharge period: (1) adverse drug-related incidents and (2) a subset defined as clinically important medication errors, which included preventable or ameliorable ADEs and potential ADEs (ie, medication-related errors that may not yet have caused injury to a patient, but have the potential to cause future harm if not addressed). Clinically important medication errors were the primary study outcome. Results: There were 361 participants (mean [SD] age, 68.7 [9.3] years; 177 women [49.0%]; 319 White [88.4%] and 8 Black individuals [2.2%]). Of these, 180 (49.9%) were randomly assigned to the intervention group and 181 (50.1%) to the control group. Among all participants, 100 (27.7%) experienced 1 or more adverse drug-related incidents, and 65 (18%) experienced 1 or more clinically important medication errors. There were 81 adverse drug-related incidents identified in the intervention group and 72 in the control group. There were 44 clinically important medication errors in the intervention group and 45 in the control group. The intervention did not significantly alter the per-patient rate of adverse drug-related incidents (unadjusted incidence rate ratio, 1.13; 95% CI, 0.83-1.56) or clinically important medication errors (unadjusted incidence rate ratio, 0.99; 95% CI, 0.65-1.49). Conclusions and Relevance: In this randomized clinical trial, there was not an observed lower rate of adverse drug-related incidents or clinically important medication errors during the posthospitalization period that was associated with a clinical pharmacist intervention. However, there were study recruitment challenges and lower than expected numbers of events among the study population. Trial Registration: ClinicalTrials.gov Identifier: NCT02781662.

Hypertension, medications, and risk of severe COVID-19: A Massachusetts community-based observational study.

It remains uncertain whether the hypertension (HT) medications angiotensin-converting enzyme inhibitors (ACEi) and angiotensin receptor blockers (ARB) mitigate or exacerbate SARS-CoV-2 infection. We evaluated the association of ACEi and ARB with severe coronavirus disease 19 (COVID-19) as defined by hospitalization or mortality among individuals diagnosed with COVID-19. We investigated whether these associations were modified by age, the simultaneous use of the diuretic thiazide, and the health conditions associated with medication use. In an observational study utilizing data from a Massachusetts group medical practice, we identified 1449 patients with a COVID-19 diagnosis. In our study, pre-infection comorbidities including HT, cardiovascular disease, and diabetes were associated with increased risk of severe COVID-19. Risk was further elevated in patients under age 65 with these comorbidities or cancer. Twenty percent of those with severe COVID-19 compared to 9% with less severe COVID-19 used ACEi, 8% and 4%, respectively, used ARB. In propensity score-matched analyses, use of neither ACEi (OR = 1.30, 95% CI 0.93 to 1.81) nor ARB (OR = 0.94, 95% CI 0.57 to 1.55) was associated with increased risk of severe COVID-19. Thiazide use did not modify this relationship. Beta blockers, calcium channel blockers, and anticoagulant medications were not associated with COVID-19 severity. In conclusion, cardiovascular-related comorbidities were associated with severe COVID-19 outcomes, especially among patients under age 65. We found no substantial increased risk of severe COVID-19 among patients taking antihypertensive medications. Our findings support recommendations against discontinuing use of renin-angiotensin system (RAS) inhibitors to prevent severe COVID-19.

Electronic Health Record Portal Messages and Interactive Voice Response Calls to Improve Rates of Early Season Influenza Vaccination: Randomized Controlled Trial.

BACKGROUND: Patient reminders for influenza vaccination, delivered via an electronic health record patient portal and interactive voice response calls, offer an innovative approach to engaging patients and improving patient care. OBJECTIVE: The goal of this study was to test the effectiveness of portal and interactive voice response outreach in improving rates of influenza vaccination by targeting patients in early September, shortly after vaccinations became available. METHODS: Using electronic health record portal messages and interactive voice response calls promoting influenza vaccination, outreach was conducted in September 2015. Participants included adult patients within a large multispecialty group practice in central Massachusetts. Our main outcome was electronic health record-documented early influenza vaccination during the 2015-2016 influenza season, measured in November 2015. We randomly assigned all active portal users to 1 of 2 groups: (1) receiving a portal message promoting influenza vaccinations, listing upcoming clinics, and offering online scheduling of vaccination appointments (n=19,506) or (2) receiving usual care (n=19,505). We randomly assigned all portal nonusers to 1 of 2 groups: (1) receiving interactive voice response call (n=15,000) or (2) receiving usual care (n=43,596). The intervention also solicited patient self-reports on influenza vaccinations completed outside the clinic. Self-reported influenza vaccination data were uploaded into the electronic health records to increase the accuracy of existing provider-directed electronic health record clinical decision support (vaccination alerts) but were excluded from main analyses. RESULTS: Among portal users, 28.4% (5549/19,506) of those randomized to receive messages and 27.1% (5294/19,505) of the usual care group had influenza vaccinations documented by November 2015 (P=.004). In multivariate analysis of portal users, message recipients were slightly more likely to have documented vaccinations when compared to the usual care group (OR 1.07, 95% CI 1.02-1.12). Among portal nonusers, 8.4% (1262/15,000) of those randomized to receive calls and 8.2% (3586/43,596) of usual care had documented vaccinations (P=.47), and multivariate analysis showed nonsignificant differences. Over half of portal messages sent were opened (10,112/19,479; 51.9%), and over half of interactive voice response calls placed (7599/14,984; 50.7%) reached their intended target, thus we attained similar levels of exposure to the messaging for both interventions. Among portal message recipients, 25.4% of message openers (2570/10,112) responded to a subsequent question on receipt of influenza vaccination; among interactive voice response recipients, 72.5% of those reached (5513/7599) responded to a similar question. CONCLUSIONS: Portal message outreach to a general primary care population achieved a small but statistically significant improvement in rates of influenza vaccination (OR 1.07, 95% CI 1.02-1.12). Interactive voice response calls did not significantly improve vaccination rates among portal nonusers (OR 1.03, 95% CI 0.96-1.10). Rates of patient engagement with both modalities were favorable. TRIAL REGISTRATION: ClinicalTrials.gov NCT02266277; https://clinicaltrials.gov/ct2/show/NCT02266277.

Recruitment Challenges for Low-Risk Health System Intervention Trials in Older Adults: A Case Study.

OBJECTIVE: To assess factors associated with trial participation in the context of a low-risk intervention intended to reduce adverse drug events in recently hospitalized older adults. DESIGN: Mixed methods: analysis of data collected during enrollment efforts and focus groups. SETTING: A large, multispecialty group practice. PARTICIPANTS: Individuals 50 years and older, recently discharged from the hospital and prescribed at least one high-risk medication, were eligible for the trial. Enrollees, decliners, and their caregivers were eligible to participate in focus groups. MEASUREMENTS: Reasons for declining to participate during the initial invitation as well as reasons for not providing consent were recorded. Focus groups were conducted with eligible individuals to explore reasons for enrolling or declining. We conducted multivariable logistic regression to compare characteristics (including sex, age, healthcare proxy, number and type of medications, visiting nurse services, reason for admission, and length of hospital stay) of those who enrolled with those who did not enroll. RESULTS: Of 3,606 individuals determined eligible, 3,147 (87%) declined, 98 (3%) verbally consented to participate but did not complete written consent, and 361 (10%) provided written consent and were considered enrolled. Individuals 80 year and older (odds ratio (OR) = 0.44; 95% confidence interval (CI) = 0.30-0.65) and those with visiting nurse services (OR = 0.64; 95% CI = 0.48-0.85) were least likely to enroll. Among those who provided a reason for declining (2,473), the most common was the belief they did not need additional medication assistance (18%). Another 332 (11%) declined because they were receiving visiting nurse services. CONCLUSION: Recruiting older adults recently discharged from the hospital to participate in trials of low-risk, system-level interventions is challenging and may underenroll the oldest individuals and those potentially at the highest risk for adverse events, limiting generalizability of study findings. Alternative study designs may be more effective than individually randomized trials in assessing low-risk, system-level interventions.

The 'Take a Break' game: Randomized trial protocol for a technology-assisted brief abstinence experience designed to engage lower-motivated smokers.

BACKGROUND: While smoking continues to be the most preventable cause of mortality in the United States, most current smokers remain not ready to quit at any given time. Engaging these 'motivation phase' smokers with brief experiences to build confidence and practice skills related to cessation could lead to sooner and more successful quit attempts. Increasingly available mobile technology and gamification can be used to provide smokers with accessible and engaging support. METHODS: We describe our protocol for conducting a randomized controlled trial evaluating Take a Break, an mHealth-based smoking pre-cessation challenge designed for smokers not ready to quit. Participants in the intervention receive 1) Motivational Messages, 2) text message Challenge Quizzes, 3) Goal-setting with tobacco treatment specialist, 4) Coping Mini-Games apps, and 5) Recognition and Rewards for participation during a 3-week challenge. Access to coping mini-games and motivational messaging continues for 6-months. Both intervention and comparison group participants receive brief Nicotine Replacement Therapy (NRT) sampling and daily smoking assessment text messages for three weeks. Primary outcomes include number of days abstinent during the challenge, change in patient-reported self-efficacy after the challenge, time to first quit attempt following the challenge, and 7-day point prevalent smoking cessation at six months. CONCLUSION: Take a Break is an innovative approach to engage those not prepared for a quit attempt. Take a Break provides motivation phase smokers with tools and a brief experience to prepare them for a quit attempt, filling a gap in tobacco cessation support and current research.

Use of Electronic Health Record Access and Audit Logs to Identify Physician Actions Following Noninterruptive Alert Opening: Descriptive Study.

BACKGROUND: Electronic health record (EHR) access and audit logs record behaviors of providers as they navigate the EHR. These data can be used to better understand provider responses to EHR-based clinical decision support (CDS), shedding light on whether and why CDS is effective. OBJECTIVE: This study aimed to determine the feasibility of using EHR access and audit logs to track primary care physicians' (PCPs') opening of and response to noninterruptive alerts delivered to EHR InBaskets. METHODS: We conducted a descriptive study to assess the use of EHR log data to track provider behavior. We analyzed data recorded following opening of 799 noninterruptive alerts sent to 75 PCPs' InBaskets through a prior randomized controlled trial. Three types of alerts highlighted new medication concerns for older patients' posthospital discharge: information only (n=593), medication recommendations (n=37), and test recommendations (n=169). We sought log data to identify the person opening the alert and the timing and type of PCPs' follow-up EHR actions (immediate vs by the end of the following day). We performed multivariate analyses examining associations between alert type, patient characteristics, provider characteristics, and contextual factors and likelihood of immediate or subsequent PCP action (general, medication-specific, or laboratory-specific actions). We describe challenges and strategies for log data use. RESULTS: We successfully identified the required data in EHR access and audit logs. More than three-quarters of alerts (78.5%, 627/799) were opened by the PCP to whom they were directed, allowing us to assess immediate PCP action; of these, 208 alerts were followed by immediate action. Expanding on our analyses to include alerts opened by staff or covering physicians, we found that an additional 330 of the 799 alerts demonstrated PCP action by the end of the following day. The remaining 261 alerts showed no PCP action. Compared to information-only alerts, the odds ratio (OR) of immediate action was 4.03 (95% CI 1.67-9.72) for medication-recommendation and 2.14 (95% CI 1.38-3.32) for test-recommendation alerts. Compared to information-only alerts, ORs of medication-specific action by end of the following day were significantly greater for medication recommendations (5.59; 95% CI 2.42-12.94) and test recommendations (1.71; 95% CI 1.09-2.68). We found a similar pattern for OR of laboratory-specific action. We encountered 2 main challenges: (1) Capturing a historical snapshot of EHR status (number of InBasket messages at time of alert delivery) required incorporation of data generated many months prior with longitudinal follow-up. (2) Accurately interpreting data elements required iterative work by a physician/data manager team taking action within the EHR and then examining audit logs to identify corresponding documentation. CONCLUSIONS: EHR log data could inform future efforts and provide valuable information during development and refinement of CDS interventions. To address challenges, use of these data should be planned before implementing an EHR-based study.

Consensus Statement: Feature and Function Recommendations to Optimize Clinician Usability of Direct Interoperability to Enhance Patient Care.

BACKGROUND: Secure clinical messaging and document exchange utilizing the Direct Protocol (Direct interoperability) has been widely implemented in health information technology (HIT) applications including electronic health records (EHRs) and by health care providers and organizations in the United States. While Direct interoperability has allowed clinicians and institutions to satisfy regulatory requirements and has facilitated communication and electronic data exchange as patients transition across care environments, feature and function enhancements to HIT implementations of the Direct Protocol are required to optimize the use of this technology. OBJECTIVE: To describe and address this gap, we developed a prioritized list of recommended features and functions desired by clinicians to utilize Direct interoperability for improved quality, safety, and efficiency of patient care. This consensus statement is intended to inform policy makers and HIT vendors to encourage further development and implementation of system capabilities to improve clinical care. METHODS: An ad hoc group of interested clinicians came together under the auspices of DirectTrust to address challenges of usability and create a consensus recommendation. This group drafted a list of desired features and functions that was published online. Comments were solicited from interested parties including clinicians, EHR and other HIT vendors, and trade organizations. Resultant comments were collected, reviewed by the authors, and incorporated into the final recommendations. RESULTS: This consensus statement contains a list of 57 clinically desirable features and functions categorized and prioritized for support by policy makers, development by HIT vendors, and implementation and use by clinicians. CONCLUSION: Fully featured, standardized implementation of Direct interoperability will allow clinicians to utilize Direct messaging more effectively as a component of HIT and EHR interoperability to improve care transitions and coordination.

Improving Rates of Outpatient Influenza Vaccination Through EHR Portal Messages and Interactive Automated Calls: A Randomized Controlled Trial.

BACKGROUND: Patient reminders for influenza vaccination, delivered via electronic health record (EHR) patient portal messages and interactive voice response (IVR) calls, offer an innovative approach to improving patient care. OBJECTIVE: To test the effectiveness of portal and IVR outreach in improving rates of influenza vaccination. DESIGN: Randomized controlled trial of EHR portal messages and IVR calls promoting influenza vaccination. PARTICIPANTS: Adults with no documented influenza vaccination 2 months after the start of influenza season (2014-2015). INTERVENTION: Using a factorial design, we assigned 20,000 patients who were active portal users to one of four study arms: (a) receipt of a portal message promoting influenza vaccines, (b) receipt of IVR call with similar content, (c) both a and b, or (d) neither (usual care). We randomized 10,000 non-portal users to receipt of IVR call or usual care. In all intervention arms, information on pneumococcal vaccination was included if the targeted patient was overdue for pneumococcal vaccine. MAIN MEASURES: EHR-documented influenza vaccination during the 2014-2015 influenza season, measured April 2015. KEY RESULTS: Among portal users, 14.0% (702) of those receiving both portal messages and calls, 13.4% (669) of message recipients, 12.8% (642) of call recipients, and 11.6% (582) of those with usual care received vaccines. On multivariable analysis of portal users, those receiving portal messages alone (OR 1.20, 95% CI 1.06-1.35) or IVR calls alone (OR 1.15 95% CI 1.02-1.30) were more likely than usual care recipients to be vaccinated. Those receiving both messages and calls were also more likely than the usual care group to be vaccinated (ad hoc analysis, using a Bonferroni correction: OR 1.29, 97.5% CI 1.13, 1.48). Among non-portal users, 8.5% of call recipients and 8.6% of usual care recipients received influenza vaccines (p = NS). Pneumococcal vaccination rates showed no significant improvement. CONCLUSIONS: Our outreach achieved a small but significant improvement in influenza vaccination rates. Registration: ClinicalTrials.gov Identifier NCT02266277 ( https://clinicaltrials.gov/ct2/show/NCT02266277 ).

Strategies to Reduce Injuries and Develop Confidence in Elders (STRIDE): A Cluster-Randomized Pragmatic Trial of a Multifactorial Fall Injury Prevention Strategy: Design and Methods.

Background: Fall injuries are a major cause of morbidity and mortality among older adults. We describe the design of a pragmatic trial to compare the effectiveness of an evidence-based, patient-centered multifactorial fall injury prevention strategy to an enhanced usual care. Methods: Strategies to Reduce Injuries and Develop Confidence in Elders (STRIDE) is a 40-month cluster-randomized, parallel-group, superiority, pragmatic trial being conducted at 86 primary care practices in 10 health care systems across United States. The 86 practices were randomized to intervention or control group using covariate-based constrained randomization, stratified by health care system. Participants are community-living persons, ≥70 years, at increased risk for serious fall injuries. The intervention is a comanagement model in which a nurse Falls Care Manager performs multifactorial risk assessments, develops individualized care plans, which include surveillance, follow-up evaluation, and intervention strategies. Control group receives enhanced usual care, with clinicians and patients receiving evidence-based information on falls prevention. Primary outcome is serious fall injuries, operationalized as those leading to medical attention (nonvertebral fractures, joint dislocation, head injury, lacerations, and other major sequelae). Secondary outcomes include all fall injuries, all falls, and well-being (concern for falling; anxiety and depressive symptoms; physical function and disability). Target sample size was 5,322 participants to provide 90% power to detect 20% reduction in primary outcome rate relative to control. Results: Trial enrolled 5,451 subjects in 20 months. Intervention and follow-up are ongoing. Conclusions: The findings of the STRIDE study will have important clinical and policy implications for the prevention of fall injuries in older adults.

Primary Care Providers' Opening of Time-Sensitive Alerts Sent to Commercial Electronic Health Record InBaskets.

BACKGROUND: Time-sensitive alerts are among the many types of clinical notifications delivered to physicians' secure InBaskets within commercial electronic health records (EHRs). A delayed alert review can impact patient safety and compromise care. OBJECTIVE: To characterize factors associated with opening of non-interruptive time-sensitive alerts delivered into primary care provider (PCP) InBaskets. DESIGN AND PARTICIPANTS: We analyzed data for 799 automated alerts. Alerts highlighted actionable medication concerns for older patients post-hospital discharge (2010-2011). These were study-generated alerts sent 3 days post-discharge to InBaskets for 75 PCPs across a multisite healthcare system, and represent a subset of all urgent InBasket notifications. MAIN MEASURES: Using EHR access and audit logs to track alert opening, we performed bivariate and multivariate analyses calculating associations between patient characteristics, provider characteristics, contextual factors at the time of alert delivery (number of InBasket notifications, weekday), and alert opening within 24 h. KEY RESULTS: At the time of alert delivery, the PCPs had a median of 69 InBasket notifications and had received a median of 379.8 notifications (IQR 295.0, 492.0) over the prior 7 days. Of the 799 alerts, 47.1% were opened within 24 h. Patients with longer hospital stays (>4 days) were marginally more likely to have alerts opened (OR 1.48 [95% CI 1.00-2.19]). Alerts delivered to PCPs whose InBaskets had a higher number of notifications at the time of alert delivery were significantly less likely to be opened within 24 h (top quartile >157 notifications: OR 0.34 [95% CI 0.18-0.61]; reference bottom quartile ≤42). Alerts delivered on Saturdays were also less likely to be opened within 24 h (OR 0.18 [CI 0.08-0.39]). CONCLUSIONS: The number of total InBasket notifications and weekend delivery may impact the opening of time-sensitive EHR alerts. Further study is needed to support safe and effective approaches to care team management of InBasket notifications.

Improving Rates of Influenza Vaccination Through Electronic Health Record Portal Messages, Interactive Voice Recognition Calls and Patient-Enabled Electronic Health Record Updates: Protocol for a Randomized Controlled Trial.

BACKGROUND: Clinical decision support (CDS), including computerized reminders for providers and patients, can improve health outcomes. CDS promoting influenza vaccination, delivered directly to patients via an electronic health record (EHR) patient portal and interactive voice recognition (IVR) calls, offers an innovative approach to improving patient care. OBJECTIVE: To test the effectiveness of an EHR patient portal and IVR outreach to improve rates of influenza vaccination in a large multispecialty group practice in central Massachusetts. METHODS: We describe a nonblinded, randomized controlled trial of EHR patient portal messages and IVR calls designed to promote influenza vaccination. In our preparatory phase, we conducted qualitative interviews with patients, providers, and staff to inform development of EHR portal messages with embedded questionnaires and IVR call scripts. We also provided practice-wide education on influenza vaccines to all physicians and staff members, including information on existing vaccine-specific EHR CDS. Outreach will target adult patients who remain unvaccinated for more than 2 months after the start of the influenza season. Using computer-generated randomization and a factorial design, we will assign 20,000 patients who are active users of electronic patient portals to one of the 4 study arms: (1) receipt of a portal message promoting influenza vaccines and offering online appointment scheduling; (2) receipt of an IVR call with similar content but without appointment facilitation; (3) both (1) and (2); or (4) neither (1) nor (2) (usual care). We will randomize patients without electronic portals (10,000 patients) to (1) receipt of IVR call or (2) usual care. Both portal messages and IVR calls promote influenza vaccine completion. Our primary outcome is percentage of eligible patients with influenza vaccines administered at our group practice during the 2014-15 influenza season. Both outreach methods also solicit patient self-report on influenza vaccinations completed outside the clinic or on barriers to influenza vaccination. Self-reported data from both outreach modes will be uploaded into the EHR to increase accuracy of existing provider-directed EHR CDS (vaccine alerts). RESULTS: With our proposed sample size and using a factorial design, power calculations using baseline vaccination rate estimates indicated that 4286 participants per arm would give 80% power to detect a 3% improvement in influenza vaccination rates between groups (α=.05; 2-sided). Intention-to-treat unadjusted chi-square analyses will be performed to assess the impact of portal messages, either alone or in combination with the IVR call, on influenza vaccination rates. The project was funded in January 2014. Patient enrollment for the project described here completed in December 2014. Data analysis is currently under way and first results are expected to be submitted for publication in 2016. CONCLUSIONS: If successful, this study's intervention may be adapted by other large health care organizations to increase vaccination rates among their eligible patients. CLINICALTRIAL: ClinicalTrials.gov NCT02266277; https://clinicaltrials.gov/ct2/show/NCT02266277 (Archived by WebCite at http://www.webcitation.org/6fbLviHLH).

A Pilot Health Information Technology-Based Effort to Increase the Quality of Transitions From Skilled Nursing Facility to Home: Compelling Evidence of High Rate of Adverse Outcomes.

OBJECTIVES: Older adults are often transferred from hospitals to skilled nursing facilities (SNFs) for post-acute care. Patients may be at risk for adverse outcomes after SNF discharges, but little research has focused on this period. DESIGN: Assessment of the feasibility of a transitional care intervention based on a combination of manual information transmission and health information technology to provide automated alert messages to primary care physicians and staff; pre-post analysis to assess potential impact. SETTING: A multispecialty group practice. PARTICIPANTS: Adults aged 65 and older, discharged from SNFs to home; comparison group drawn from SNF discharges during the previous 1.5 years, matched on facility, patient age, and sex. MEASUREMENTS: For the pre-post analysis, we tracked rehospitalization within 30 days after discharge and adverse drug events within 45 days. RESULTS: The intervention was developed and implemented with manual transmission of information between 8 SNFs and the group practice followed by entry into the electronic health record. The process required a 5-day delay during which a large portion of the adverse events occurred. Over a 1-year period, automated alert messages were delivered to physicians and staff for the 313 eligible patients discharged from the 8 SNFs to home. We compared outcomes to those of individually matched discharges from the previous 1.5 years and found similar percentages with 30-day rehospitalizations (31% vs 30%, adjusted HR 1.06, 95% CI 0.80-1.4). Within the adverse drug event (ADE) study, 30% of the discharges during the intervention period and 30% of matched discharges had ADEs within 45 days. CONCLUSION: Older adults discharged from SNFs are at high risk of adverse outcomes immediately following discharge. Simply providing alerts to outpatient physicians, especially if delivered multiple days after discharge, is unlikely to have any impact on reducing these rates.

Patient Portals: An Underused Resource for Improving Patient Engagement.

The potential of patient portals to improve patient engagement and health outcomes has been discussed for more than a decade. The slow growth in patient portal adoption rates among patients and providers in the United States, despite external incentives, indicates that this is a complex issue. We examined evidence of patient portal use and effects with a focus on the pulmonary domain. We found a paucity of studies of patient portal use in pulmonary practice, and highlight gaps for future research. We also report on the experience of a pulmonary department using a patient portal to highlight the potential of these systems.