Identification of Hospitalized Patients Who May Benefit from a Serious Illness Conversation Using the Readmission Risk Score Combined with the Surprise Question.

BACKGROUND: Determining which patients benefit from a serious illness conversation (SIC) is challenging. The authors sought to determine whether Epic's Risk of Readmission Score (RRS), could be combined with a simple, validated, one-question mortality prognostic screen (the surprise question: Would you be surprised if the patient died in the next 12 months?) to identify hospitalized patients with SIC needs. METHODS: In this retrospective study, the authors randomly selected encounters for patients ≥ 18 years of age to a general medicine service from January 2019 to October 2021 who had an RRS > 28%. Two adjudicators independently performed chart reviews for each encounter to answer the surprise question to create two distinct prognostic groups (yes vs. no). Fisher's exact test was used to assess for statistically significant differences in standardized documentation of SICs between groups. RESULTS: Out of 2,879 encounters, 202 patient encounters were randomly selected. Adjudicators answered "no" to the surprise question for 156 (77.2%) patients. Patients for whom adjudicators answered "no" were generally older with higher comorbidity and more often had standardized documentation of a SIC (14 [9.0%] vs. 0.[0.0%], p = 0.042) compared to patients for whom adjudicators answered "yes." CONCLUSION: Approximately three quarters of patients with a high RRS were predicted to have a lifespan of less than a year. Although these patients were significantly more likely to have a SIC, rates of SICs were extremely low. Combining available electronic health record (EHR) data with a simple one-question screening tool may help identify hospitalized patients who require a SIC in quality improvement initiatives.

Patient-Clinician Diagnostic Concordance upon Hospital Admission.

OBJECTIVES: This study aimed to pilot an application-based patient diagnostic questionnaire (PDQ) and assess the concordance of the admission diagnosis reported by the patient and entered by the clinician. METHODS: Eligible patients completed the PDQ assessing patients' understanding of and confidence in the diagnosis 24 hours into hospitalization either independently or with assistance. Demographic data, the hospital principal problem upon admission, and International Classification of Diseases 10th Revision (ICD-10) codes were retrieved from the electronic health record (EHR). Two physicians independently rated concordance between patient-reported diagnosis and clinician-entered principal problem as full, partial, or no. Discrepancies were resolved by consensus. Descriptive statistics were used to report demographics for concordant (full) and nonconcordant (partial or no) outcome groups. Multivariable logistic regressions of PDQ questions and a priori selected EHR data as independent variables were conducted to predict nonconcordance. RESULTS: A total of 157 (77.7%) questionnaires were completed by 202 participants; 77 (49.0%), 46 (29.3%), and 34 (21.7%) were rated fully concordant, partially concordant, and not concordant, respectively. Cohen's kappa for agreement on preconsensus ratings by independent reviewers was 0.81 (0.74, 0.88). In multivariable analyses, patient-reported lack of confidence and undifferentiated symptoms (ICD-10 "R-code") for the principal problem were significantly associated with nonconcordance (partial or no concordance ratings) after adjusting for other PDQ questions (3.43 [1.30, 10.39], p = 0.02) and in a model using selected variables (4.02 [1.80, 9.55], p < 0.01), respectively. CONCLUSION: About one-half of patient-reported diagnoses were concordant with the clinician-entered diagnosis on admission. An ICD-10 "R-code" entered as the principal problem and patient-reported lack of confidence may predict patient-clinician nonconcordance early during hospitalization via this approach.

Inpatients' understanding of the hospitalist role and common medical terminology.

Many patients are unable to identify members of their hospital care team and experience confusion regarding some medical terminology used during hospitalization, including descriptions of the structure of their inpatient care team. This cross-sectional study sought to (1) examine inpatients' understanding of the role of a hospitalist and (2) assess inpatients' familiarity with other medical terminology commonly used in the hospital. We surveyed 172 patients admitted to the hospital medicine service at two academic medical centers. We found that almost half (47%) of respondents were unfamiliar with the term and/or role of a hospitalist, while the remaining patients had varied understanding of the role. Several other medical terms were frequently misunderstood (such as "NPO," "PA," and "Attending"). Ongoing efforts are needed to improve communication to ensure that hospitalized patients understand the hospitalist's role and the medical terms shared with them.

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.

Analysis of Clinical Criteria for Discharge Among Patients Hospitalized for COVID-19: Development and Validation of a Risk Prediction Model.

BACKGROUND: Patients hospitalized with COVID-19 can clinically deteriorate after a period of initial stability, making optimal timing of discharge a clinical and operational challenge. OBJECTIVE: To determine risks for post-discharge readmission and death among patients hospitalized with COVID-19. DESIGN: Multicenter retrospective observational cohort study, 2020-2021, with 30-day follow-up. PARTICIPANTS: Adults admitted for care of COVID-19 respiratory disease between March 2, 2020, and February 11, 2021, to one of 180 US hospitals affiliated with the HCA Healthcare system. MAIN MEASURES: Readmission to or death at an HCA hospital within 30 days of discharge was assessed. The area under the receiver operating characteristic curve (AUC) was calculated using an internal validation set (33% of the HCA cohort), and external validation was performed using similar data from six academic centers associated with a hospital medicine research network (HOMERuN). KEY RESULTS: The final HCA cohort included 62,195 patients (mean age 61.9 years, 51.9% male), of whom 4704 (7.6%) were readmitted or died within 30 days of discharge. Independent risk factors for death or readmission included fever within 72 h of discharge; tachypnea, tachycardia, or lack of improvement in oxygen requirement in the last 24 h; lymphopenia or thrombocytopenia at the time of discharge; being ≤ 7 days since first positive test for SARS-CoV-2; HOSPITAL readmission risk score ≥ 5; and several comorbidities. Inpatient treatment with remdesivir or anticoagulation were associated with lower odds. The model's AUC for the internal validation set was 0.73 (95% CI 0.71-0.74) and 0.66 (95% CI 0.64 to 0.67) for the external validation set. CONCLUSIONS: This large retrospective study identified several factors associated with post-discharge readmission or death in models which performed with good discrimination. Patients 7 or fewer days since test positivity and who demonstrate potentially reversible risk factors may benefit from delaying discharge until those risk factors resolve.

Pharmacist, nurse, and physician perspectives on the implementation of the pharmacist discharge care (pharm-dc) intervention: A qualitative study.

BACKGROUND: The PHARMacist Discharge Care (PHARM-DC) intervention is a pharmacist-led Transitions of Care (TOC) program intended to reduce 30-day hospital readmissions and emergency department visits which has been implemented at two hospitals in the United States. The objectives of this study were to: 1) explore perspectives surrounding the PHARM-DC program from healthcare providers, leaders, and administrators at both institutions, and 2) identify factors which may contribute to intervention success and sustainability. METHODS: Focus groups and interviews were conducted with pharmacists, physicians, nurses, hospital leaders, and pharmacy administrators at two institutions in the Northeastern and Western United States. Interviews were audio recorded and transcribed, with transcriptions imported into NVivo for qualitative analysis. Thematic analysis was performed using an iterative process, with two study authors independently coding transcripts to identify themes. RESULTS: Overall, 37 individuals participated in ten focus groups and seven interviews. The themes identified included: 1) Organizational, Pharmacist, and Patient Factors Contributing to Transitions of Care, 2) Medication Challenges in Transitions of Care at Admission and Discharge, 3) Transitions of Care Communication and Discharge Follow-up, and 4) Opportunities for Improvement and Sustainability. The four themes were mapped to the constructs of the CFIR and RE-AIM frameworks. Some factors facilitating intervention success and sustainability were accurate medication histories collected on admission, addressing medication barriers before discharge, coordinating discharge using electronic health record discharge features, and having a structured process for intervention training and delivery. Barriers to intervention implementation and sustainability included gaps in communication with other care team members, and variable pharmacist skills for delivering the intervention. This study identified that using educational resources to standardize the TOC process addressed the issue of variations in pharmacists' skills for delivering TOC interventions. CONCLUSIONS: Nurses, physicians, pharmacists, pharmacist leaders, and hospital administrators were in agreement regarding the usefulness of the PHARM-DC intervention, while acknowledging challenges in its implementation and opportunities for improvement. Future research should focus on developing training materials to standardize and scale the intervention, eliminating barriers to medication access pre-discharge, coordinating discharge across care team members, and communicating medication changes to primary care providers post-discharge.

Perspectives on Referral Pathways for Timely Head and Neck Cancer Care.

Importance: Timely diagnosis and treatment are of paramount importance for patients with head and neck cancer (HNC) because delays are associated with reduced survival rates and increased recurrence risk. Prompt referral to HNC specialists is crucial for the timeliness of care, yet the factors that affect the referral and triage pathway remain relatively unexplored. Therefore, to identify barriers and facilitators of timely care, it is important to understand the complex journey that patients undertake from the onset of HNC symptoms to referral for diagnosis and treatment. Objective: To investigate the referral and triage process for patients with HNC and identify barriers to and facilitators of care from the perspectives of patients and health care workers. Design, Participants, and Setting: This was a qualitative study using semistructured interviews of patients with HNC and health care workers who care for them. Participants were recruited from June 2022 to July 2023 from HNC clinics at 2 tertiary care academic medical centers in Boston, Massachusetts. Data were analyzed from July 2022 to December 2023. Main Outcomes and Measures: Themes identified from the perspectives of both patients and health care workers on factors that hinder or facilitate the HNC referral and triage process. Results: In total, 72 participants were interviewed including 42 patients with HNC (median [range] age, 60.5 [19.0-81.0] years; 27 [64%] females) and 30 health care workers (median [range] age, 38.5 [20.0-68.0] years; 23 [77%] females). Using thematic analysis, 4 major themes were identified: the HNC referral and triage pathway is fragmented; primary and dental care are critical for timely referrals; efficient interclinician coordination expedites care; and consistent patient-practitioner engagement alleviates patient fear. Conclusions and Relevance: These findings describe the complex HNC referral and triage pathway, emphasizing the critical role of initial symptom recognition, primary and dental care, patient information flow, and interclinician and patient-practitioner communication, all of which facilitate prompt HNC referrals.

Investigating racial and ethnic disparities in interhospital transfer within an academic integrated healthcare system: A matched cohort study.

The presence of racial and ethnic disparities in interhospital transfer (IHT) within integrated healthcare systems has not been fully explored. We matched Black and Latinx patients admitted to community hospitals in our integrated healthcare system between June 2015 and December 2019 to White patients by origin hospital, age, time of year, and disease severity. We performed conditional logistic regression models to determine if race or ethnicity was associated with IHT in one of the tertiary academic medical centers in the system, adjusting for covariates. The sample contained 107,895 admissions (82.6% White, 7.8% Black, and 9.6% Latinx). Transfer rates were 2.2% versus 2.2% after the Black/White match and 1.8% versus 1.8% after the Latinx/White match. After adjusting for covariates, there was no association between race or ethnicity and IHT (Black vs. White odds ratio [OR]: 0.87, 95% confidence interval [CI]: 0.72-1.07; Latinx vs. White OR: 1.05, 95% CI: 0.79-1.40). This may be due to reduced barriers to transfer with an integrated healthcare system.

Racial and Ethnic Disparities in Opioid Prescribing on Hospital Discharge Among Older Adults: A National Retrospective Cohort Study.

BACKGROUND: Disparities in opioid prescribing among racial and ethnic groups have been observed in outpatient and emergency department settings, but it is unknown whether similar disparities exist at discharge among hospitalized older adults. OBJECTIVE: To determine filled opioid prescription rates on hospital discharge by race/ethnicity among Medicare beneficiaries. DESIGN: Retrospective cohort study. PARTICIPANTS: Medicare beneficiaries 65 years or older discharged from hospital in 2016, without opioid fills in the 90 days prior to hospitalization (opioid-naïve). MAIN MEASURES: Race/ethnicity was categorized by the Research Triangle Institute (RTI), grouped as Asian/Pacific Islander, Black, Hispanic, other (American Indian/Alaska Native/unknown/other), and White. The primary outcome was an opioid prescription claim within 2 days of hospital discharge. The secondary outcome was total morphine milligram equivalents (MMEs) among adults with a filled opioid prescription. KEY RESULTS: Among 316,039 previously opioid-naïve beneficiaries (mean age, 76.8 years; 56.2% female), 49,131 (15.5%) filled an opioid prescription within 2 days of hospital discharge. After adjustment, Black beneficiaries were 6% less likely (relative risk [RR] 0.94, 95% CI 0.91-0.97) and Asian/Pacific Islander beneficiaries were 9% more likely (RR 1.09, 95% CI 1.03-1.14) to have filled an opioid prescription when compared to White beneficiaries. Among beneficiaries with a filled opioid prescription, mean total MMEs were lower among Black (356.9; adjusted difference - 4%, 95% CI - 7 to - 1%), Hispanic (327.0; adjusted difference - 7%, 95% CI - 10 to - 4%), and Asian/Pacific Islander (328.2; adjusted difference - 8%, 95% CI - 12 to - 4%) beneficiaries when compared to White beneficiaries (409.7). CONCLUSIONS AND RELEVANCE: Black older adults were less likely to fill a new opioid prescription after hospital discharge when compared to White older adults and received lower total MMEs. The factors contributing to these differential prescribing patterns should be investigated further.

A Mixed Methods Analysis of Standardized Documentation of Serious Illness Conversations Within an Electronic Health Record Module During Hospitalization.

BACKGROUND: Analysis of documented Serious Illness Conversations (SICs) in the inpatient setting can help clinicians align management to address patient and caregiver needs. METHODS: We conducted a mixed methods analysis of the first instance of standardized documentation of a SIC within a structured module among hospitalized general medicine patients from 2018 to 2019. Percentage of documentations that included a description of patient or family understanding of the patient's medical condition and use of radio buttons to answer the "prognostic information shared," "hopes," and "worries" modules are reported. Using grounded theory approach, physicians analyzed free text entries to: "What is important to the patient/family?" and "Recommendations or next steps planned." RESULTS: Out of 5142 patients, 59 patients had a documented SIC. Patient or family understanding of the medical condition(s) was reported in 56 (95%). For "prognostic information shared," the most frequently selected radio buttons were: 49 (83%) incurable disease and 28 (48%) prognosis of weeks to months while those for "hopes" were: 52 (88%) be comfortable and 27 (46%) be at home and for "worries" were: 49 (83%) other physical suffering and 36 (61%) pain. Themes generated from entries to "What's important to patient/family?" included being with loved ones; comfort; mentally and physically present; and reliable care while those for "Recommendations" were coordinating support services; symptom management; and support and communication. CONCLUSIONS: SIC content indicated concern about pain and reliable care suggesting the complex, intensive nature of caring for seriously ill patients and the need to consider SICs earlier in the life course of patients.

Formative Perceptions of a Digital Pill System to Measure Adherence to Heart Failure Pharmacotherapy: Mixed Methods Study.

BACKGROUND: Heart failure (HF) affects 6.2 million Americans and is a leading cause of hospitalization. The mainstay of the management of HF is adherence to pharmacotherapy. Despite the effectiveness of HF pharmacotherapy, effectiveness is closely linked to adherence. Measuring adherence to HF pharmacotherapy is difficult; most clinical measures use indirect strategies such as calculating pharmacy refill data or using self-report. While helpful in guiding treatment adjustments, indirect measures of adherence may miss the detection of suboptimal adherence and co-occurring structural barriers associated with nonadherence. Digital pill systems (DPSs), which use an ingestible radiofrequency emitter to directly measure medication ingestions in real-time, represent a strategy for measuring and responding to nonadherence in the context of HF pharmacotherapy. Previous work has demonstrated the feasibility of using DPSs to measure adherence in other chronic diseases, but this strategy has yet to be leveraged for individuals with HF. OBJECTIVE: We aim to explore through qualitative interviews the facilitators and barriers to using DPS technology to monitor pharmacotherapy adherence among patients with HF. METHODS: We conducted individual, semistructured qualitative interviews and quantitative assessments between April and August 2022. A total of 20 patients with HF who were admitted to the general medical or cardiology service at an urban quaternary care hospital participated in this study. Participants completed a qualitative interview exploring the overall acceptability of and willingness to use DPS technology for adherence monitoring and perceived barriers to DPS use. Quantitative assessments evaluated HF history, existing medication adherence strategies, and attitudes toward technology. We analyzed qualitative data using applied thematic analysis and NVivo software (QSR International). RESULTS: Most participants (12/20, 60%) in qualitative interviews reported a willingness to use the DPS to measure HF medication adherence. Overall, the DPS was viewed as useful for increasing accountability and reinforcing adherence behaviors. Perceived barriers included technological issues, a lack of need, additional costs, and privacy concerns. Most were open to sharing adherence data with providers to bolster clinical care and decision-making. Reminder messages following detected nonadherence were perceived as a key feature, and customization was desired. Suggested improvements are primarily related to the design and usability of the Reader (a wearable device). CONCLUSIONS: Overall, individuals with HF perceived the DPS to be an acceptable and useful tool for measuring medication adherence. Accurate, real-time ingestion data can guide adherence counseling to optimize adherence management and inform tailored behavioral interventions to support adherence among patients with HF.

Diagnostic Errors in Hospitalized Adults Who Died or Were Transferred to Intensive Care.

Importance: Diagnostic errors contribute to patient harm, though few data exist to describe their prevalence or underlying causes among medical inpatients. Objective: To determine the prevalence, underlying cause, and harms of diagnostic errors among hospitalized adults transferred to an intensive care unit (ICU) or who died. Design, Setting, and Participants: Retrospective cohort study conducted at 29 academic medical centers in the US in a random sample of adults hospitalized with general medical conditions and who were transferred to an ICU, died, or both from January 1 to December 31, 2019. Each record was reviewed by 2 trained clinicians to determine whether a diagnostic error occurred (ie, missed or delayed diagnosis), identify diagnostic process faults, and classify harms. Multivariable models estimated association between process faults and diagnostic error. Opportunity for diagnostic error reduction associated with each fault was estimated using the adjusted proportion attributable fraction (aPAF). Data analysis was performed from April through September 2023. Main Outcomes and Measures: Whether or not a diagnostic error took place, the frequency of underlying causes of errors, and harms associated with those errors. Results: Of 2428 patient records at 29 hospitals that underwent review (mean [SD] patient age, 63.9 [17.0] years; 1107 [45.6%] female and 1321 male individuals [54.4%]), 550 patients (23.0%; 95% CI, 20.9%-25.3%) had experienced a diagnostic error. Errors were judged to have contributed to temporary harm, permanent harm, or death in 436 patients (17.8%; 95% CI, 15.9%-19.8%); among the 1863 patients who died, diagnostic error was judged to have contributed to death in 121 (6.6%; 95% CI, 5.3%-8.2%). In multivariable models examining process faults associated with any diagnostic error, patient assessment problems (aPAF, 21.4%; 95% CI, 16.4%-26.4%) and problems with test ordering and interpretation (aPAF, 19.9%; 95% CI, 14.7%-25.1%) had the highest opportunity to reduce diagnostic errors; similar ranking was seen in multivariable models examining harmful diagnostic errors. Conclusions and Relevance: In this cohort study, diagnostic errors in hospitalized adults who died or were transferred to the ICU were common and associated with patient harm. Problems with choosing and interpreting tests and the processes involved with clinician assessment are high-priority areas for improvement efforts.

National Survey of Patient Safety Experiences in Hospital Medicine During the COVID-19 Pandemic.

BACKGROUND: During the COVID-19 pandemic, hospitals were caring for increasing numbers of patients with a novel and highly contagious respiratory illness, forcing adaptations in care delivery. The objective of this study was to understand the impact of these adaptations on patient safety in hospital medicine. METHODS: The authors conducted a nationwide survey to understand patient safety challenges experienced by hospital medicine clinicians during the COVID-19 pandemic. The survey was distributed to members of the Society of Hospital Medicine via an e-mail listserv. It consisted of closed- and open-ended questions to elicit respondents' experience in five domains: error reporting and communication, staffing, equipment, personal protective equipment (PPE) and isolation practices, and infrastructure. Quantitative questions were reported as counts and percentages; qualitative responses were coded and analyzed for relevant themes. RESULTS: Of 196 total responses, 167 respondents (85.2%) were attending physicians and 85 (43.8%) practiced at teaching hospitals. Safety concerns commonly identified included nursing shortages (71.0%), limiting patient interactions to conserve PPE (61.9%), and feeling that one was practicing in a more hazardous environment (61.4%). In free-text responses, clinicians described poor outcomes and patient decompensation due to provider and equipment shortages, as well as communication lapses and diagnostic errors resulting from decreased patient contact and the need to follow isolation protocols. CONCLUSION: Efforts made to accommodate shortages in staff and equipment, adapt to limited PPE, and enforce isolation policies had unintended consequences that affected patient safety and created a more hazardous environment characterized by less efficient care, respiratory decompensations, diagnostic errors, and poor communication with patients.

The Association of Standardized Documentation of Serious Illness Conversations With Healthcare Utilization in Hospitalized Patients: A Propensity Score Matched Cohort Analysis.

Background: Serious Illness Conversations (SICs) conducted during hospitalization can lead to meaningful patient participation in the decision-making process affecting medical management. The aim of this study is to determine if standardized documentation of a SIC within an institutionally approved EHR module during hospitalization is associated with palliative care consultation, change in code status, hospice enrollment prior to discharge, and 90-day readmissions. Methods: We conducted retrospective analyses of hospital encounters of general medicine patients at a community teaching hospital affiliated with an academic medical center from October 2018 to August 2019. Encounters with standardized documentation of a SIC were identified and matched by propensity score to control encounters without a SIC in a ratio of 1:3. We used multivariable, paired logistic regression and Cox proportional-hazards modeling to assess key outcomes. Results: Of 6853 encounters (5143 patients), 59 (.86%) encounters (59 patients) had standardized documentation of a SIC, and 58 (.85%) were matched to 167 control encounters (167 patients). Encounters with standardized documentation of a SIC had greater odds of palliative care consultation (odds ratio [OR] 60.10, 95% confidence interval [CI] 12.45-290.08, P < .01), a documented code status change (OR 8.04, 95% CI 1.54-42.05, P = .01), and discharge with hospice services (OR 35.07, 95% CI 5.80-212.08, P < .01) compared to matched controls. There was no significant association with 90-day readmissions (adjusted hazard ratio [HR] .88, standard error [SE] .37, P = .73). Conclusions: Standardized documentation of a SIC during hospitalization is associated with palliative care consultation, change in code status, and hospice enrollment.

Post-Hospitalization Home Monitoring Programs During the COVID-19 Pandemic: Survey Results from the Hospital Medicine Re-engineering Network (HOMERuN).

BACKGROUND: During the coronavirus disease 2019 (COVID-19) pandemic, hospitals and healthcare systems launched innovative responses to emerging needs. The creation and use of programs to remotely follow patient clinical status and recovery after COVID-19 hospitalization has not been thoroughly described. OBJECTIVE: To characterize deployment of remote post-hospital discharge monitoring programs during the COVID-19 pandemic METHODS: Electronic surveys were administered to leaders of 83 US academic hospitals in the Hospital Medicine Re-engineering Network (HOMERuN). An initial survey was completed in March 2021 with follow-up survey completed in July 2022. RESULTS: There were 35 responses to the initial survey (42%) and 15 responses to the follow-up survey (43%). Twenty-two (63%) sites reported a post-discharge monitoring program, 16 of which were newly developed for COVID-19. Physiologic monitoring devices such as pulse oximeters were often provided. Communication with medical teams was often via telephone, with moderate use of apps or electronic medical record integration. Programs launched most commonly between January and June 2020. Only three programs were still active at the time of follow-up survey. CONCLUSIONS: Our findings demonstrate rapid, ad hoc development of post-hospital discharge monitoring programs during the COVID-19 pandemic but with little standardization or evaluation. Additional study could identify the benefits of these programs, instruct their potential application to other disease processes, and inform further development as part of emergency preparedness for upcoming crises.

Comprehensive Pharmacist-led Transitions-of-care Medication Management around Hospital Discharge Adds Modest Cost Relative to Usual Care: Time-and-Motion Cost Analysis.

Optimal medication management is important during hospitalization and at discharge because post-discharge adverse drug events (ADEs) are common, often preventable, and contribute to patient harms, healthcare utilization, and costs. Conduct a cost analysis of a comprehensive pharmacist-led transitions-of-care medication management intervention for older adults during and after hospital discharge. Twelve intervention components addressed medication reconciliation, medication review, and medication adherence. Trained, experienced pharmacists delivered the intervention to older adults with chronic comorbidities at 2 large U.S. academic centers. To quantify and categorize time spent on the intervention, we conducted a time-and-motion analysis of study pharmacists over 36 sequential workdays (14 519 min) involving 117 patients. For 40 patients' hospitalizations, we observed all intervention activities. We used the median minutes spent and pharmacist wages nationally to calculate cost per hospitalization (2020 U.S. dollars) from the hospital perspective, relative to usual care. Pharmacists spent a median of 66.9 min per hospitalization (interquartile range 46.1-90.1), equating to $101 ($86 to $116 in sensitivity analyses). In unadjusted analyses, study site was associated with time spent (medians 111 and 51.8 min) while patient primary language, discharge disposition, number of outpatient medications, and patient age were not. In this cost analysis, comprehensive medication management around discharge cost about $101 per hospitalization, with variation across sites. This cost is at least an order of magnitude less than published costs associated with ADEs, hospital readmissions, or other interventions designed to reduce readmissions. Work is ongoing to assess the current intervention's effectiveness.

Achieving diagnostic excellence through prevention and teamwork (ADEPT) study protocol: A multicenter, prospective quality and safety program to improve diagnostic processes in medical inpatients.

BACKGROUND: Few hospitals have built surveillance for diagnostic errors into usual care or used comparative quantitative and qualitative data to understand their diagnostic processes and implement interventions designed to reduce these errors. OBJECTIVES: To build surveillance for diagnostic errors into usual care, benchmark diagnostic performance across sites, pilot test interventions, and evaluate the program's impact on diagnostic error rates. METHODS AND ANALYSIS: Achieving diagnostic excellence through prevention and teamwork (ADEPT) is a multicenter, real-world quality and safety program utilizing interrupted time-series techniques to evaluate outcomes. Study subjects will be a randomly sampled population of medical patients hospitalized at 16 US hospitals who died, were transferred to intensive care, or had a rapid response during the hospitalization. Surveillance for diagnostic errors will occur on 10 events per month per site using a previously established two-person adjudication process. Concurrent reviews of patients who had a qualifying event in the previous week will allow for surveys of clinicians to better understand contributors to diagnostic error, or conversely, examples of diagnostic excellence, which cannot be gleaned from medical record review alone. With guidance from national experts in quality and safety, sites will report and benchmark diagnostic error rates, share lessons regarding underlying causes, and design, implement, and pilot test interventions using both Safety I and Safety II approaches aimed at patients, providers, and health systems. Safety II approaches will focus on cases where diagnostic error did not occur, applying theories of how people and systems are able to succeed under varying conditions. The primary outcome will be the number of diagnostic errors per patient, using segmented multivariable regression to evaluate change in y-intercept and change in slope after initiation of the program. ETHICS AND DISSEMINATION: The study has been approved by the University of California, San Francisco Institutional Review Board (IRB), which is serving as the single IRB. Intervention toolkits and study findings will be disseminated through partners including Vizient, The Joint Commission, and Press-Ganey, and through national meetings, scientific journals, and publications aimed at the general public.