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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Implementation of a standardised accept note to improve communication during inter-hospital transfer: a prospective cohort study

IMPORTANCE

The transfer of patients between hospitals (interhospital transfer, IHT), exposes patients to communication errors and gaps in information exchange.

OBJECTIVE

To design and implement a standardised accept note to improve communication during medical service transfers, and evaluate its impact on patient outcomes.

DESIGN

Prospective interventional cohort study.

SETTING

A 792-bed tertiary care hospital.

PARTICIPANTS

All patient transfers from any acute care hospital to the general medicine, cardiology, oncology and intensive care unit (ICU) services between August 2020 and June 2022.

INTERVENTIONS

A standardised accept note template was developed over a 9-month period with key stakeholder input and embedded in the electronic health record, completed by nurses within the hospital's Access Centre.

MAIN OUTCOMES AND MEASURES

Primary outcome was clinician-reported medical errors collected via surveys of admitting clinicians within 72 hours after IHT patient admission. Secondary outcomes included clinician-reported failures in communication; presence and 'timeliness' of accept note documentation; patient length of stay (LOS) after transfer; rapid response or ICU transfer within 24 hours and in-hospital mortality. All outcomes were analysed postintervention versus preintervention, adjusting for patient demographics, diagnosis, comorbidity, illness severity, admitting service, time of year, hospital COVID census and census of admitting service and admitting team on date of admission.

RESULTS

Of the 1004 and 654 IHT patients during preintervention and postintervention periods, surveys were collected on 735 (73.2%) and 462 (70.6%), respectively. Baseline characteristics were similar among patients in each time period and between survey responders and non-responders. Adjusted analyses demonstrated a 27% reduction in clinician-reported medical error rates postimplementation versus preimplementation (11.5 vs 15.8, adjusted OR (aOR) 0.73, 95% CI 0.53 to 0.99). Secondary outcomes demonstrated lower adjusted odds of clinician-reported failures in communication (aOR 0.88; 0.78 to 0.98) and rapid response/ICU transfer (aOR 0.57; 0.34 to 0.97), and improved presence (aOR 2.30; 1.75 to 3.02) and timeliness (-21.4 hours vs -8.7 hours, p<0.001) of accept note documentation. There were no significant differences in LOS or mortality.

CONCLUSIONS AND RELEVANCE

Among 1658 medical patient transfers, implementing a standardised accept note was associated with improved presence and timeliness of accept note documentation, clinician-reported medical errors, failures in communication and clinical decline following transfer, suggesting that improving communication during IHT can improve patient outcomes.

Inpatient Understanding of Their Care Team and Receipt of Mixed Messages: a Two-Site Cross-Sectional Study

BACKGROUND

Patient understanding of their care, supported by physician involvement and consistent communication, is key to positive health outcomes. However, patient and care team characteristics can hinder this understanding.

OBJECTIVE

We aimed to assess inpatients' understanding of their care and their perceived receipt of mixed messages, as well as the associated patient, care team, and hospitalization characteristics.

DESIGN

We administered a 30-item survey to inpatients between February 2020 and November 2021 and incorporated other hospitalization data from patients' health records.

PARTICIPANTS

Randomly selected inpatients at two urban academic hospitals in the USA who were (1) admitted to general medicine services and (2) on or past the third day of their hospitalization.

MAIN MEASURES

Outcome measures include (1) knowledge of main doctor and (2) frequency of mixed messages. Potential predictors included mean notes per day, number of consultants involved in the patient's care, number of unit transfers, number of attending physicians, length of stay, age, sex, insurance type, and primary race.

KEY RESULTS

A total of 172 patients participated in our survey. Most patients were unaware of their main doctor, an issue related to more daily interactions with care team members. Twenty-three percent of patients reported receiving mixed messages at least sometimes, most often between doctors on the primary team and consulting doctors. However, the likelihood of receiving mixed messages decreased with more daily interactions with care team members.

CONCLUSIONS

Patients were often unaware of their main doctor, and almost a quarter perceived receiving mixed messages about their care. Future research should examine patients' understanding of different aspects of their care, and the nature of interactions that might improve clarity around who's in charge while simultaneously reducing the receipt of mixed messages.

A Peer Recovery Coach Intervention for Hospitalized Patients with Opioid Use Disorder: A Pilot Randomized Controlled Trial

OBJECTIVES

Patients with opioid use disorder (OUD) are increasingly being hospitalized for acute medical illnesses. Despite initiation of medications for OUD (MOUDs), many discontinue treatment after discharge. To evaluate whether a psychosocial intervention can improve MOUD retention after hospitalization, we conducted a pilot randomized controlled trial of a peer recovery coach intervention.

METHODS

An existing peer recovery coach intervention was adapted for this trial. Hospitalized adults with OUD receiving MOUD treatment were randomized to receive either a recovery coach intervention or treatment-as-usual. For those in the intervention arm, the coach guided the participant to complete a relapse prevention plan, maintained contact throughout the 6-month follow-up period, encouraged MOUD continuation, and helped to identify community resources. Those receiving treatment-as-usual were discharged with a referral to outpatient treatment. Primary outcome was retention in MOUD treatment at 6 months. Secondary outcomes were the proportion of participants readmitted to the hospital and the number of days until treatment discontinuation and to hospital readmission.

RESULTS

Twenty-five individuals who provided consent and randomized to the recovery coach intervention (n = 13) or treatment-as-usual (n = 12) were included in the analysis. No significant differences were found in the proportion of participants retained in MOUD treatment at 6 months (38.5% vs 41.7%, P = 0.87), proportion of participants readmitted at 6 months (46.2% vs 41.2%, P = 0.82), or the time to treatment discontinuation (log-rank P = 0.92) or readmission (log-rank P = 0.85).

CONCLUSIONS

This pilot trial failed to demonstrate that a recovery coach intervention improved MOUD treatment retention compared with treatment-as-usual among hospitalized individuals with OUD.

What works in medication reconciliation: an on-treatment and site analysis of the MARQUIS2 study

BACKGROUND

The second Multicenter Medication Reconciliation Quality Improvement Study demonstrated a marked reduction in medication discrepancies per patient. The aim of the current analysis was to determine the association of patient exposure to each system-level intervention and receipt of each patient-level intervention on these results.

METHODS

This study was conducted at 17 North American Hospitals, the study period was 18 months per site, and sites typically adopted interventions after 2-5 months of preintervention data collection. We conducted an on-treatment analysis (ie, an evaluation of outcomes based on patient exposure) of system-level interventions, both at the category level and at the individual component level, based on monthly surveys of implementation site leads at each site (response rate 65%). We then conducted a similar analysis of patient-level interventions, as determined by study pharmacist review of documented activities in the medical record. We analysed the association of each intervention on the adjusted number of medication discrepancies per patient in admission and discharge orders, based on a random sample of up to 22 patients per month per site, using mixed-effects Poisson regression with hospital site as a random effect. We then used a generalised linear mixed-effects model (GLMM) decision tree to determine which patient-level interventions explained the most variance in discrepancy rates.

RESULTS

Among 4947 patients, patient exposure to seven of the eight system-level component categories was associated with modest but significant reductions in discrepancy rates (adjusted rate ratios (ARR) 0.75-0.97), as were 15 of the 17 individual system-level intervention components, including hiring, reallocating and training personnel to take a best possible medication history (BPMH) and training personnel to perform discharge medication reconciliation and patient counselling. Receipt of five of seven patient-level interventions was independently associated with large reductions in discrepancy rates, including receipt of a BPMH in the emergency department (ED) by a trained clinician (ARR 0.40, 95% CI 0.37 to 0.43), admission medication reconciliation by a trained clinician (ARR 0.57, 95% CI 0.50 to 0.64) and discharge medication reconciliation by a trained clinician (ARR 0.64, 95% CI 0.57 to 0.73). In GLMM decision tree analyses, patients who received both a BPMH in the ED and discharge medication reconciliation by a trained clinician experienced the lowest discrepancy rates (0.08 per medication per patient).

CONCLUSION AND RELEVANCE

Patient-level interventions most associated with reductions in discrepancies were receipt of a BPMH of admitted patients in the ED and admission and discharge medication reconciliation by a trained clinician. System-level interventions were associated with modest reduction in discrepancies for the average patient but are likely important to support patient-level interventions and may reach more patients. These findings can be used to help hospitals and health systems prioritise interventions to improve medication safety during care transitions.

A Public Health Critical Race Praxis Informed Congestive Heart Failure Quality Improvement Initiative on Inpatient General Medicine

BACKGROUND

Prior evaluation at our hospital demonstrated that, compared to White patients, Black and Latinx patients with congestive heart failure (CHF) were less likely to be admitted to the cardiology service rather than the general medicine service (GMS). Patients admitted to GMS (compared to cardiology) had inferior rates of cardiology follow-up and 30-day readmission.

OBJECTIVE

To develop and test the feasibility and impacts of using quality improvement (QI) methods, in combination with the Public Health Critical Race Praxis (PHCRP) framework, to engage stakeholders in developing an intervention for ensuring guideline-concordant inpatient CHF care across all patient groups.

METHODS

We compared measures for all patients admitted with CHF to GMS between September 2019 and March 2020 (intervention group) to CHF patients admitted to GMS in the previous year (pre-intervention group) and those admitted to cardiology during the pre-intervention and intervention periods (cardiology group). Our primary measures were 30-day readmissions and 14- and 30-day post-discharge cardiology follow-up.

RESULTS

There were 79 patients admitted with CHF to GMS during the intervention period, all of whom received the intervention. There were similar rates of Black and Latinx patients across the three groups. Compared to pre-intervention, intervention patients had a significantly lower 30-day readmission rate (18.9% vs. 24.8%; p=0.024), though the cardiology group also had a decrease in 30-day readmissions from the pre-intervention to intervention period. Compared to pre-intervention, intervention patients had significantly higher 14-day and 30-day post-discharge follow-up visits scheduled with cardiology (36.7% vs. 24.8%, p=0.005; 55.7% vs. 42.3%, p=0.0029), but no improvement in appointment attendance.

CONCLUSION

This study provides a first test of applying the PHCRP framework within a stakeholder-engaged QI initiative for improving CHF care across races and ethnicities. Our study design cannot evaluate causation. However, the improvements in 30-day readmission, as well as in processes of care that may affect it, provide optimism that inclusion of a racism-conscious framework in QI initiatives is feasible and may enhance QI measures.

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.

Prevalence and Causes of Diagnostic Errors in Hospitalized Patients Under Investigation for COVID-19

BACKGROUND

The COVID-19 pandemic required clinicians to care for a disease with evolving characteristics while also adhering to care changes (e.g., physical distancing practices) that might lead to diagnostic errors (DEs).

OBJECTIVE

To determine the frequency of DEs and their causes among patients hospitalized under investigation (PUI) for COVID-19.

DESIGN

Retrospective cohort.

SETTING

Eight medical centers affiliated with the Hospital Medicine ReEngineering Network (HOMERuN).

TARGET POPULATION

Adults hospitalized under investigation (PUI) for COVID-19 infection between February and July 2020.

MEASUREMENTS

We randomly selected up to 8 cases per site per month for review, with each case reviewed by two clinicians to determine whether a DE (defined as a missed or delayed diagnosis) occurred, and whether any diagnostic process faults took place. We used bivariable statistics to compare patients with and without DE and multivariable models to determine which process faults or patient factors were associated with DEs.

RESULTS

Two hundred and fifty-seven patient charts underwent review, of which 36 (14%) had a diagnostic error. Patients with and without DE were statistically similar in terms of socioeconomic factors, comorbidities, risk factors for COVID-19, and COVID-19 test turnaround time and eventual positivity. Most common diagnostic process faults contributing to DE were problems with clinical assessment, testing choices, history taking, and physical examination (all p < 0.01). Diagnostic process faults associated with policies and procedures related to COVID-19 were not associated with DE risk. Fourteen patients (35.9% of patients with errors and 5.4% overall) suffered harm or death due to diagnostic error.

LIMITATIONS

Results are limited by available documentation and do not capture communication between providers and patients.

CONCLUSION

Among PUI patients, DEs were common and not associated with pandemic-related care changes, suggesting the importance of more general diagnostic process gaps in error propagation.

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.