Impact of a hospital service for adults with chronic childhood-onset disease: A propensity weighted analysis.

BACKGROUND: Young adults with chronic childhood-onset diseases (CCOD) transitioning care from pediatrics to adult care are at high risk for readmission after hospital discharge. At our institution, we have implemented an inpatient service, the Med-Peds (MP) line, to improve transitions to adult care and reduce hospital utilization by young adults with CCOD. OBJECTIVE: This study aimed to assess the effect of the MP line on length of stay (LOS) and 30-day readmission rates compared to other inpatient services. METHODS: This was an observational, retrospective cohort analysis of patients admitted to the MP line compared to other hospital service lines over a 2-year period. To avoid potential confounding by indication for admission to the MP line, propensity score weighting methods were used. RESULTS: The MP line cared for 302 patients with CCOD from June 2019 to July 2021. Compared to other service lines, there was a 33% reduction in relative risk of 30-day readmission (26.9% compared to 40.3%, risk ratio = 0.67, 95% confidence interval [CI] 0.55-0.81). LOS was 10% longer for the MP line (event time ratio (ETR): 1.10 95% CI 1.0-1.21) with median LOS 4.8 versus 4.5 days. Patients with sickle cell disease had less of a reduction in 30-day readmissions and longer LOS. CONCLUSION: Hospitalization for young adults with CCOD on a MP service line was associated with lower 30-day readmission rates and longer LOS than hospitalization on other services. Further research is needed to assess which components of the line most contribute to decreased utilization.

The Use of Templates for Documenting Advance Care Planning Conversations: A Descriptive Analysis.

CONTEXT: While professional societies and expert panels have recommended quality indicators related to advance care planning (ACP) documentation, including using structured documentation templates, it is unclear how clinicians document these conversations. OBJECTIVE: To explore how clinicians document ACP, specifically, which components of these conversations are documented. METHODS: A codebook was developed based on existing frameworks for ACP conversations and documentation. ACP documentation from a hospital medicine quality improvement project conducted from November 2019 to April 2021 were included and assessed. Documentation was examined for the presence or absence of each component within the coding schema. Clinician documented ACP using three different note types: template (only template prompts were used), template plus (authors added additional text to the template), and free text only. ACP note components were analyzed by note type and author department. RESULTS: A total of 182 ACP notes were identified and reviewed. The most common note type was template plus (58%), followed by free text (28%) and template (14%). The most frequent components across all note types were: important relationships to patient (92%), and discussion of life-sustaining treatment preferences (87%). There was considerable heterogeneity in the components across note types. The presence of components focused on treatment decisions and legal paperwork differed significantly between note types (P < 0.05). Components on preference for medical information, emotional state, or spiritual support were rarely included across all note types. CONCLUSION: This study provides a preliminary exploration of ACP documentation and found that templates may influence what information is documented after an ACP conversation.

A Customized Electronic Health Record-Based Tool Highlights and Addresses Gaps in Patient Safety.

The authors present a tool to improve gaps in patient safety using the electronic health record. The tool integrates gap identification, passive alerts, and actions into a single interface embedded within clinicians' workflow. The tool was developed to address venous thromboembolism prophylaxis, prevention of hypo- and hyperglycemia, code status documentation, bowel movement frequency, and skilled nursing facility transitions. Alerts and actions during silent and live periods were retrospectively analyzed. The most prevalent safety gaps were lack of venous thromboembolism prophylaxis (40.4% of alerts), constipation (19.3%), and lack of code status (18.4%). Disparities in safety gaps were present by patient race, sex, and socioeconomic status. Usability testing showed positive feedback without significant alert burden. Thus, a safety gap tool was successfully built to study and address patient safety issues. The tool's strengths are its integration within the electronic health record, ease of use, customizability, and scalability.

Implementation of a comprehensive hospitalist-led initiative to improve care for patients with opioid use disorder.

BACKGROUND: As opioid-related hospitalizations rise, hospitals must be prepared to evaluate and treat patients with opioid use disorder (OUD). We implemented a hospitalist-led program, Project Caring for patients with Opioid Misuse through Evidence-based Treatment (COMET) to address gaps in care for hospitalized patients with OUD. OBJECTIVE: Implement evidence-based treatment for inpatients with OUD and refer to postdischarge care. DESIGN, SETTING, AND PARTICIPANTS: Project COMET launched in July 2019 at Duke University Hospital (DUH), an academic medical center in Durham, NC. INTERVENTION, MAIN OUTCOMES, AND MEASURES: We engaged key stakeholders, performed a needs assessment, and secured health system funding. We developed protocols to standardize OUD treatment and employed a social worker to facilitate postdischarge care. Electronic health records were utilized for data analysis. RESULTS: COMET evaluated 512 patients for OUD during their index hospitalization from July 1, 2019 through June 30, 2021. Seventy-one percent of patients received medication for OUD (MOUD) during admission. Of those who received buprenorphine during admission, 64% received a discharge prescription. Of those who received methadone during admission, 83% of eligible patients were connected to a methadone clinic. Among all patients at DUH with OUD, MOUD use during hospitalization and at discharge increased in the post-COMET period compared to the pre-COMET period (p < .001 for both). CONCLUSION: Our program is one of the first to demonstrate successful implementation of a hospitalist-led, comprehensive approach to caring for hospitalized patients with OUD and can serve as an example to other institutions seeking to implement life-saving, evidence-based treatment in this population.

Prospective and External Evaluation of a Machine Learning Model to Predict In-Hospital Mortality of Adults at Time of Admission.

Importance: The ability to accurately predict in-hospital mortality for patients at the time of admission could improve clinical and operational decision-making and outcomes. Few of the machine learning models that have been developed to predict in-hospital death are both broadly applicable to all adult patients across a health system and readily implementable. Similarly, few have been implemented, and none have been evaluated prospectively and externally validated. Objectives: To prospectively and externally validate a machine learning model that predicts in-hospital mortality for all adult patients at the time of hospital admission and to design the model using commonly available electronic health record data and accessible computational methods. Design, Setting, and Participants: In this prognostic study, electronic health record data from a total of 43 180 hospitalizations representing 31 003 unique adult patients admitted to a quaternary academic hospital (hospital A) from October 1, 2014, to December 31, 2015, formed a training and validation cohort. The model was further validated in additional cohorts spanning from March 1, 2018, to August 31, 2018, using 16 122 hospitalizations representing 13 094 unique adult patients admitted to hospital A, 6586 hospitalizations representing 5613 unique adult patients admitted to hospital B, and 4086 hospitalizations representing 3428 unique adult patients admitted to hospital C. The model was integrated into the production electronic health record system and prospectively validated on a cohort of 5273 hospitalizations representing 4525 unique adult patients admitted to hospital A between February 14, 2019, and April 15, 2019. Main Outcomes and Measures: The main outcome was in-hospital mortality. Model performance was quantified using the area under the receiver operating characteristic curve and area under the precision recall curve. Results: A total of 75 247 hospital admissions (median [interquartile range] patient age, 59.5 [29.0] years; 45.9% involving male patients) were included in the study. The in-hospital mortality rates for the training validation; retrospective validations at hospitals A, B, and C; and prospective validation cohorts were 3.0%, 2.7%, 1.8%, 2.1%, and 1.6%, respectively. The area under the receiver operating characteristic curves were 0.87 (95% CI, 0.83-0.89), 0.85 (95% CI, 0.83-0.87), 0.89 (95% CI, 0.86-0.92), 0.84 (95% CI, 0.80-0.89), and 0.86 (95% CI, 0.83-0.90), respectively. The area under the precision recall curves were 0.29 (95% CI, 0.25-0.37), 0.17 (95% CI, 0.13-0.22), 0.22 (95% CI, 0.14-0.31), 0.13 (95% CI, 0.08-0.21), and 0.14 (95% CI, 0.09-0.21), respectively. Conclusions and Relevance: Prospective and multisite retrospective evaluations of a machine learning model demonstrated good discrimination of in-hospital mortality for adult patients at the time of admission. The data elements, methods, and patient selection make the model implementable at a system level.

Assessing the Impact of an Order Panel Utilizing Weight-Based Insulin and Standardized Monitoring of Blood Glucose for Patients With Hyperkalemia.

Intravenous insulin with glucose is used in urgent treatment for hyperkalemia but has a significant risk of hypoglycemia. The authors developed an order panel within the electronic health record system that utilizes weight-based insulin dosing and standardized blood glucose monitoring to reduce hypoglycemia. As initial evaluation of this protocol, the authors retrospectively compared potassium and blood glucose lowering in patients treated with the weight-based (0.1 units/kg) insulin order panel (n = 195) with those given insulin based on provider judgment (n = 69). Serum potassium lowering did not differ between groups and there was no relationship between dose of insulin and amount of potassium lowering. There was a difference in hypoglycemia rates between groups ( P = .049), with fewer severe hypoglycemic events in the panel (2.56%) than in the non-panel group (10.14%). These data suggest weight-based insulin dosing is equally effective for lowering serum potassium and may lower risk of severe hypoglycemia.

The highest utilizers of care: individualized care plans to coordinate care, improve healthcare service utilization, and reduce costs at an academic tertiary care center.

BACKGROUND: High utilizers are medically and psychosocially complex, have high rates of emergency department (ED) visits and hospital admissions, and contribute to rising healthcare costs. OBJECTIVE: Develop individualized care plans to reduce unnecessary healthcare service utilization and hospital costs for complex, high utilizers of inpatient and ED care. DESIGN: Quality-improvement intervention with a retrospective pre/post intervention analysis. SETTING: Nine hundred twenty-four-bed tertiary academic medical center. PATIENTS: Twenty-four medically and psychosocially complex patients with the highest rates of inpatient admissions and ED visits from August 1, 2012 to August 31, 2013. INTERVENTION: A multidisciplinary team developed individualized care plans integrated into our electronic medical record (EMR) that summarize patient histories, utilization patterns, and management strategies. MEASUREMENTS: Primary outcomes included inpatient admissions, ED visits, and corresponding variable direct costs 6 and 12 months after care-plan implementation. Secondary outcomes include inpatient length of stay (LOS) and 30-day readmissions. RESULTS: Hospital admissions decreased by 56% (P < 0.001) and 50.5% (P = 0.003), 6 and 12 months after care-plan implementation. Thirty-day readmissions decreased by 66% (P < 0.001) and 51.5% (P = 0.002), 6 and 12 months after care-plan implementation. ED visits, ED costs, and inpatient LOS did not significantly change. Inpatient variable direct costs were reduced by 47.7% (P = 0.001) and 35.8% (P = 0.052), 6 and 12 months after care-plan implementation. CONCLUSIONS: Individualized care plans developed by a multidisciplinary team and integrated with the existing healthcare workforce and EMR reduce hospital admissions, 30-day readmissions, and hospital costs for complex, high-utilizing patients.