Effect of digital tools to promote hospital quality and safety on adverse events after discharge.

OBJECTIVES: Post-discharge adverse events (AEs) are common and heralded by new and worsening symptoms (NWS). We evaluated the effect of electronic health record (EHR)-integrated digital tools designed to promote quality and safety in hospitalized patients on NWS and AEs after discharge. MATERIALS AND METHODS: Adult general medicine patients at a community hospital were enrolled. We implemented a dashboard which clinicians used to assess safety risks during interdisciplinary rounds. Post-implementation patients were randomized to complete a discharge checklist whose responses were incorporated into the dashboard. Outcomes were assessed using EHR review and 30-day call data adjudicated by 2 clinicians and analyzed using Poisson regression. We conducted comparisons of each exposure on post-discharge outcomes and used selected variables and NWS as independent predictors to model post-discharge AEs using multivariable logistic regression. RESULTS: A total of 260 patients (122 pre, 71 post [dashboard], 67 post [dashboard plus discharge checklist]) enrolled. The adjusted incidence rate ratios (aIRR) for NWS and AEs were unchanged in the post- compared to pre-implementation period. For patient-reported NWS, aIRR was non-significantly higher for dashboard plus discharge checklist compared to dashboard participants (1.23 [0.97,1.56], P = .08). For post-implementation patients with an AE, aIRR for duration of injury (>1 week) was significantly lower for dashboard plus discharge checklist compared to dashboard participants (0 [0,0.53], P < .01). In multivariable models, certain patient-reported NWS were associated with AEs (3.76 [1.89,7.82], P < .01). DISCUSSION: While significant reductions in post-discharge AEs were not observed, checklist participants experiencing a post-discharge AE were more likely to report NWS and had a shorter duration of injury. CONCLUSION: Interventions designed to prompt patients to report NWS may facilitate earlier detection of AEs after discharge. CLINICALTRIALS.GOV: NCT05232656.

Efficacy and Feasibility of Remote Cognitive Remediation Therapy in Parkinson's Disease: A Randomized Controlled Trial.

Background: Non-motor symptoms of Parkinson's disease (PD) such as cognitive impairment are common and decrease patient quality of life and daily functioning. While no pharmacological treatments have effectively alleviated these symptoms to date, non-pharmacological approaches such as cognitive remediation therapy (CRT) and physical exercise have both been shown to improve cognitive function and quality of life in people with PD. Objective: This study aims to determine the feasibility and impact of remote CRT on cognitive function and quality of life in patients with PD participating in an organized group exercise program. Methods: Twenty-four subjects with PD recruited from Rock Steady Boxing (RSB), a non-contact group exercise program, were evaluated using standard neuropsychological and quality of life measures and randomized to the control or intervention group. The intervention group attended online CRT sessions for one hour, twice a week for 10 weeks, engaging in multi-domain cognitive exercises and group discussion. Results: Twenty-one subjects completed the study and were reevaluated. Comparing groups over time, the control group (n = 10) saw a decline in overall cognitive performance that trended towards significance (p = 0.05) and a statistically significant decrease in delayed memory (p = 0.010) and self-reported cognition (p = 0.011). Neither of these findings were seen in the intervention group (n = 11), which overwhelmingly enjoyed the CRT sessions and attested to subjective improvements in their daily lives. Conclusions: This randomized controlled pilot study suggests that remote CRT for PD patients is feasible, enjoyable, and may help slow the progression of cognitive decline. Further trials are warranted to determine the longitudinal effects of such a program.

Developing, pilot testing, and refining requirements for 3 EHR-integrated interventions to improve diagnostic safety in acute care: a user-centered approach.

Objective: To describe a user-centered approach to develop, pilot test, and refine requirements for 3 electronic health record (EHR)-integrated interventions that target key diagnostic process failures in hospitalized patients. Materials and Methods: Three interventions were prioritized for development: a Diagnostic Safety Column (DSC) within an EHR-integrated dashboard to identify at-risk patients; a Diagnostic Time-Out (DTO) for clinicians to reassess the working diagnosis; and a Patient Diagnosis Questionnaire (PDQ) to gather patient concerns about the diagnostic process. Initial requirements were refined from analysis of test cases with elevated risk predicted by DSC logic compared to risk perceived by a clinician working group; DTO testing sessions with clinicians; PDQ responses from patients; and focus groups with clinicians and patient advisors using storyboarding to model the integrated interventions. Mixed methods analysis of participant responses was used to identify final requirements and potential implementation barriers. Results: Final requirements from analysis of 10 test cases predicted by the DSC, 18 clinician DTO participants, and 39 PDQ responses included the following: DSC configurable parameters (variables, weights) to adjust baseline risk estimates in real-time based on new clinical data collected during hospitalization; more concise DTO wording and flexibility for clinicians to conduct the DTO with or without the patient present; and integration of PDQ responses into the DSC to ensure closed-looped communication with clinicians. Analysis of focus groups confirmed that tight integration of the interventions with the EHR would be necessary to prompt clinicians to reconsider the working diagnosis in cases with elevated diagnostic error (DE) risk or uncertainty. Potential implementation barriers included alert fatigue and distrust of the risk algorithm (DSC); time constraints, redundancies, and concerns about disclosing uncertainty to patients (DTO); and patient disagreement with the care team's diagnosis (PDQ). Discussion: A user-centered approach led to evolution of requirements for 3 interventions targeting key diagnostic process failures in hospitalized patients at risk for DE. Conclusions: We identify challenges and offer lessons from our user-centered design process.

Early Expected Discharge Date Accuracy During Hospitalization: A Multivariable Analysis.

INTRODUCTION: Accurate estimation of an expected discharge date (EDD) early during hospitalization impacts clinical operations and discharge planning. METHODS: We conducted a retrospective study of patients discharged from six general medicine units at an academic medical center in Boston, MA from January 2017 to June 2018. We retrieved all EDD entries and patient, encounter, unit, and provider data from the electronic health record (EHR), and public weather data. We excluded patients who expired, discharged against medical advice, or lacked an EDD within the first 24 h of hospitalization. We used generalized estimating equations in a multivariable logistic regression analysis to model early EDD accuracy (an accurate EDD entered within 24 h of admission), adjusting for all covariates and clustering by patient. We similarly constructed a secondary multivariable model using covariates present upon admission alone. RESULTS: Of 3917 eligible hospitalizations, 890 (22.7%) had at least one accurate early EDD entry. Factors significantly positively associated (OR > 1) with an accurate early EDD included clinician-entered EDD, admit day and discharge day during the work week, and teaching clinical units. Factors significantly negatively associated (OR < 1) with an accurate early EDD included Elixhauser Comorbidity Index ≥ 11 and length of stay of two or more days. C-statistics for the primary and secondary multivariable models were 0.75 and 0.60, respectively. CONCLUSIONS: EDDs entered within the first 24 h of admission were often inaccurate. While several variables from the EHR were associated with accurate early EDD entries, few would be useful for prospective prediction.

A structured approach to EHR surveillance of diagnostic error in acute care: an exploratory analysis of two institutionally-defined case cohorts.

OBJECTIVES: To test a structured electronic health record (EHR) case review process to identify diagnostic errors (DE) and diagnostic process failures (DPFs) in acute care. METHODS: We adapted validated tools (Safer Dx, Diagnostic Error Evaluation Research [DEER] Taxonomy) to assess the diagnostic process during the hospital encounter and categorized 13 postulated e-triggers. We created two test cohorts of all preventable cases (n=28) and an equal number of randomly sampled non-preventable cases (n=28) from 365 adult general medicine patients who expired and underwent our institution's mortality case review process. After excluding patients with a length of stay of more than one month, each case was reviewed by two blinded clinicians trained in our process and by an expert panel. Inter-rater reliability was assessed. We compared the frequency of DE contributing to death in both cohorts, as well as mean DPFs and e-triggers for DE positive and negative cases within each cohort. RESULTS: Twenty-seven (96.4%) preventable and 24 (85.7%) non-preventable cases underwent our review process. Inter-rater reliability was moderate between individual reviewers (Cohen's kappa 0.41) and substantial with the expert panel (Cohen's kappa 0.74). The frequency of DE contributing to death was significantly higher for the preventable compared to the non-preventable cohort (56% vs. 17%, OR 6.25 [1.68, 23.27], p<0.01). Mean DPFs and e-triggers were significantly and non-significantly higher for DE positive compared to DE negative cases in each cohort, respectively. CONCLUSIONS: We observed substantial agreement among final consensus and expert panel reviews using our structured EHR case review process. DEs contributing to death associated with DPFs were identified in institutionally designated preventable and non-preventable cases. While e-triggers may be useful for discriminating DE positive from DE negative cases, larger studies are required for validation. Our approach has potential to augment institutional mortality case review processes with respect to DE surveillance.

An updated analysis of shoulder and elbow questions on the Orthopedic In-Training Examination.

BACKGROUND: The Orthopedic In-Training Examination (OITE) is an annual examination for orthopedic surgery residents used to assess orthopedic knowledge across a national standard. Having an updated understanding of currently tested topics and resources is useful to help residents guide their education. PURPOSE: The purpose of this study is to analyze the shoulder and elbow domain of the OITE in an effort to provide current trends and commonly tested topics. METHODS: All OITE questions related to shoulder and elbow topics over the years 2009-2013 and 2017-2020 were analyzed. Subcategories, the number and types of references used, publication lag time, imaging modalities, taxonomic classification, and resident performance were recorded. RESULTS: Shoulder and elbow topics comprised 8.61% of all OITE questions from 2009-2013 and 2017-2020. The most commonly tested shoulder topics were rotator cuff arthropathy and reverse total shoulder arthroplasty (13.6%), followed by hemiarthroplasty and total shoulder arthroplasty (12.9%), rotator cuff-related pathology (12.9%), anterior shoulder instability and/or dislocation (10.2%), and general anatomy (10.2%). The most commonly tested elbow topics were trauma (21%), ulnar collateral ligament injuries (12.12%), general anatomy (10%), and arthroplasty (10%). Decisions regarding management or appropriate next steps (taxonomy T3) comprised 39% of all question types. The incorporation of imaging modalities continues to be an important component of the OITE questions. The Journal of Shoulder and Elbow Surgery (JSES), the Journal of the American Academy of Orthopedic Surgeons (JAAOS), the Journal of Bone and Joint Surgery (JBJS), and the American Journal of Sports Medicine (AJSM) comprised 65% of articles referenced in all questions over our analysis period. CONCLUSION: This study provides an updated analysis of trends within the shoulder and elbow domain of the OITE. Application of these data can aid residents in their preparation for the examination.

Analyzing diagnostic errors in the acute setting: a process-driven approach.

OBJECTIVES: We describe an approach for analyzing failures in diagnostic processes in a small, enriched cohort of general medicine patients who expired during hospitalization and experienced medical error. Our objective was to delineate a systematic strategy for identifying frequent and significant failures in the diagnostic process to inform strategies for preventing adverse events due to diagnostic error. METHODS: Two clinicians independently reviewed detailed records of purposively sampled cases identified from established institutional case review forums and assessed the likelihood of diagnostic error using the Safer Dx instrument. Each reviewer used the modified Diagnostic Error Evaluation and Research (DEER) taxonomy, revised for acute care (41 possible failure points across six process dimensions), to characterize the frequency of failure points (FPs) and significant FPs in the diagnostic process. RESULTS: Of 166 cases with medical error, 16 were sampled: 13 (81.3%) had one or more diagnostic error(s), and a total of 113 FPs and 30 significant FPs were identified. A majority of significant FPs (63.3%) occurred in "Diagnostic Information and Patient Follow-up" and "Patient and Provider Encounter and Initial Assessment" process dimensions. Fourteen (87.5%) cases had a significant FP in at least one of these dimensions. CONCLUSIONS: Failures in the diagnostic process occurred across multiple dimensions in our purposively sampled cohort. A systematic analytic approach incorporating the modified DEER taxonomy, revised for acute care, offered critical insights into key failures in the diagnostic process that could serve as potential targets for preventative interventions.

Evaluation of electronic health record-integrated digital health tools to engage hospitalized patients in discharge preparation.

OBJECTIVE: To evaluate the effect of electronic health record (EHR)-integrated digital health tools comprised of a checklist and video on transitions-of-care outcomes for patients preparing for discharge. MATERIALS AND METHODS: English-speaking, general medicine patients (>18 years) hospitalized at least 24 hours at an academic medical center in Boston, MA were enrolled before and after implementation. A structured checklist and video were administered on a mobile device via a patient portal or web-based survey at least 24 hours prior to anticipated discharge. Checklist responses were available for clinicians to review in real time via an EHR-integrated safety dashboard. The primary outcome was patient activation at discharge assessed by patient activation (PAM)-13. Secondary outcomes included postdischarge patient activation, hospital operational metrics, healthcare resource utilization assessed by 30-day follow-up calls and administrative data and change in patient activation from discharge to 30 days postdischarge. RESULTS: Of 673 patients approached, 484 (71.9%) enrolled. The proportion of activated patients (PAM level 3 or 4) at discharge was nonsignificantly higher for the 234 postimplementation compared with the 245 preimplementation participants (59.8% vs 56.7%, adjusted OR 1.23 [0.38, 3.96], P = .73). Postimplementation participants reported 3.75 (3.02) concerns via the checklist. Mean length of stay was significantly higher for postimplementation compared with preimplementation participants (10.13 vs 6.21, P < .01). While there was no effect on postdischarge outcomes, there was a nonsignificant decrease in change in patient activation within participants from pre- to postimplementation (adjusted difference-in-difference of -16.1% (9.6), P = .09). CONCLUSIONS: EHR-integrated digital health tools to prepare patients for discharge did not significantly increase patient activation and was associated with a longer length of stay. While issues uncovered by the checklist may have encouraged patients to inquire about their discharge preparedness, other factors associated with patient activation and length of stay may explain our observations. We offer insights for using PAM-13 in context of real-world health-IT implementations. TRIAL REGISTRATION: NIH US National Library of Medicine, NCT03116074, clinicaltrials.gov.

Transition and Sustainability of an Online Care Model for People With Parkinson's Disease in Response to the COVID-19 Pandemic.

INTRODUCTION: CoronaVirus Disease-2019 (COVID-19) led to social distancing and the need for alternative care models. Telehealth programs for people with Parkinson's (PWP) disease may ensure continuity of care. The goal of this observational survey study was to determine the practicability, satisfaction, and barriers to online programs, their relationship to perceived symptoms, mood, and quality of life, and program sustainability beyond the immediate pandemic. METHODS: In-person Parkinson's programs at New York Institute of Technology College of Osteopathic Medicine transitioned online at the start of the pandemic to include Rock Steady Boxing, Support Groups, and Rock Steady Buddies. A custom online survey sent to 150 participants investigated PD history, symptomatology, level of exercise before and during the pandemic, depression (PHQ-9), quality of life (PDQ-39), and practicability and perceived satisfaction related to these online programs. Descriptive statistics were reported. RESULTS: Of 69 respondents [mean age of 70.2y (SD 8.4 yrs)], >75% were satisfied with the transition to online programs. Consistent attendance and minimal barriers to programs indicated practicability, with increased adherence to exercise. Of 66 completed PHQ-9s, 22.7% had scores ≥9 (moderate to severe depression); of 61 completed PDQ-39s, scores averaged 21.4; better quality of life than national averages for PWP. Self-perceived physical and mental wellbeing were positively affected. CONCLUSIONS: Results suggest the transition to online programs met the needs of the Parkinson's community in a practicable and sustainable manner during the pandemic. With COVID-19 still prevalent, the current model of blending synchronous online and in-person classes provides a more flexible, sustainable format compared to in-person alone. Institutions may consider including online components to existing programs to promote continuity of care for aging populations as part of best practices.

Interactive Digital Health Tools to Engage Patients and Caregivers in Discharge Preparation: Implementation Study.

BACKGROUND: Poor discharge preparation during hospitalization may lead to adverse events after discharge. Checklists and videos that systematically engage patients in preparing for discharge have the potential to improve safety, especially when integrated into clinician workflow via the electronic health record (EHR). OBJECTIVE: This study aims to evaluate the implementation of a suite of digital health tools integrated with the EHR to engage hospitalized patients, caregivers, and their care team in preparing for discharge. METHODS: We used the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework to identify pertinent research questions related to implementation. We iteratively refined patient and clinician-facing intervention components using a participatory process involving end users and institutional stakeholders. The intervention was implemented at a large academic medical center from December 2017 to July 2018. Patients who agreed to participate were coached to watch a discharge video, complete a checklist assessing discharge readiness, and request postdischarge text messaging with a physician 24 to 48 hours before their expected discharge date, which was displayed via a patient portal and bedside display. Clinicians could view concerns reported by patients based on their checklist responses in real time via a safety dashboard integrated with the EHR and choose to open a secure messaging thread with the patient for up to 7 days after discharge. We used mixed methods to evaluate our implementation experience. RESULTS: Of 752 patient admissions, 510 (67.8%) patients or caregivers participated: 416 (55.3%) watched the video and completed the checklist, and 94 (12.5%) completed the checklist alone. On average, 4.24 concerns were reported per each of the 510 checklist submissions, most commonly about medications (664/2164, 30.7%) and follow-up (656/2164, 30.3%). Of the 510 completed checklists, a member of the care team accessed the safety dashboard to view 210 (41.2%) patient-reported concerns. For 422 patient admissions where postdischarge messaging was available, 141 (33.4%) patients requested this service; of these, a physician initiated secure messaging for 3 (2.1%) discharges. Most patient survey participants perceived that the intervention promoted self-management and communication with their care team. Patient interview participants endorsed gaps in communication with their care team and thought that the video and checklist would be useful closer toward discharge. Clinicians participating in focus groups perceived the value for patients but suggested that low awareness and variable workflow regarding the intervention, lack of technical optimization, and inconsistent clinician leadership limited the use of clinician-facing components. CONCLUSIONS: A suite of EHR-integrated digital health tools to engage patients, caregivers, and clinicians in discharge preparation during hospitalization was feasible, acceptable, and valuable; however, important challenges were identified during implementation. We offer strategies to address implementation barriers and promote adoption of these tools. TRIAL REGISTRATION: ClinicalTrials.gov NCT03116074; https://clinicaltrials.gov/ct2/show/NCT03116074.