Implementation of the Modified Brain Injury Guidelines Might Be Feasible and Cost-Effective Even in a Nontrauma Hospital.

INTRODUCTION: The modified Brain Injury Guidelines (mBIG) provide a framework to stratify traumatic brain injury (TBI) patients based on clinical and radiographic factors in level 1 and 2 trauma centers. Approximately 75% of all U.S. hospitals do not carry any trauma designation yet could also benefit from these guidelines. To the best of our knowledge, this is the first report of applying the mBIG protocol in a community hospital without any trauma designation. METHODS: All adult patients with a TBI in a single center from 2020 to 2022 were retrospectively classified into mBIG categories. The primary outcomes included neurological deterioration, progression on computed tomography of the head, and surgical intervention. Additional outcomes included the hospital costs incurred by the mBIG 1 and mBIG 2 groups. RESULTS: Of the 116 included patients, 35 (30%) would have stratified into mBIG 1, 23 (20%) into mBIG 2, and 58 (50%) into mBIG 3. No patient in mBIG 1 had a decline in neurological examination findings or progression on computed tomography of the head or required neurosurgical intervention. Three patients in mBIG 2 had radiographic progression and one required surgical decompression. Two patients in mBIG 3 demonstrated a neurological decline and six had radiographic progression. Of the 21 patients who received surgical intervention, 20 were stratified into mBIG 3. Implementation of the mBIG protocol could have reduced costs by >$250,000 during the 2-year period. CONCLUSIONS: The mBIG protocol can safely stratify patients in a nontrauma hospital. Because nontrauma centers tend to see more patients with minor TBIs, implementation could result in significant cost savings, reduce unnecessary hospital and intensive care unit resources, and reduce transfers to a tertiary institution.

Focusing hospitalist roles on either admitting or rounding facilitates unit-based assignment and is associated with improved discharge efficiency.

BACKGROUND: Unit-based teams may improve care delivery for hospitalized patients but can be challenging to implement broadly across all acute care units in a hospital. OBJECTIVE: To determine the effect of a Lean-guided transition to hospital-wide unit-based assignment on care delivery outcomes. DESIGN, SETTING, AND PARTICIPANTS: The study was a retrospective time-series with primary outcomes of discharge efficiency, 30-day readmissions, and length of stay, performed at a 336-bed tertiary academic referral hospital in the Pacific Northwest with approximately 17,000 admissions annually. INTERVENTION: Implementation of a Lean-guided quality improvement intervention included division of hospitalist duties into 'admitters' and 'rounders,' with simulated patient flow exercises to determine the optimal staffing model. MAIN OUTCOMES AND MEASURES: Discharge efficiency (number of patients discharged by hospitalists divided by the number of hospitalist patient encounter days per month) and 30-day readmissions were compared using the t-test or chi-square, and length of stay was analyzed in a multivariate time-series regression model. RESULTS: The intervention was associated with a significant improvement in discharge efficiency, by 0.014 (from 0.168 to 0.181) discharges/encounter (95% CI = 0.024, 0.004), p = 0.009. Mean length of stay decreased by 0.98 days (95% CI 0.50, 1.47) after adjustment for patient age, patient type (medical versus surgical), critical care admissions, and discharge disposition, without a corresponding change in 30-day readmission rate (12.2% (1948/15,902) pre-intervention to 11.7% (397/3379) post-intervention (p = 0.42)). CONCLUSIONS: Dividing hospitalist roles into admitters and rounders enabled implementation of unit-based teams across the hospital, with corresponding improvements in discharge efficiency and length of stay.

Reduction of early inpatient transfers and rapid response team calls after implementation of an emergency department intake huddle process.

Patients admitted to the hospital and requiring a subsequent transfer to a higher level of care have increased morbidity, mortality and length of stay compared with patients who do not require a transfer during their hospital stay. We identified that a high number of patients admitted to our intermediate care (IMC) unit required a rapid response team (RRT) call and an early (<24 hours) transfer to the intensive care unit (ICU). A quality improvement project was initiated with the goal to reduce subsequent early transfers to the ICU and RRT calls. We started by focusing on IMC patients, implementing acuity-based nursing assignments and standardised daily nursing rounds in the IMC aiming to reduce early patient transfers to the ICU. Then, we expanded to all patients admitted to a hospital medical unit from the emergency department (ED), targeting patients with gastrointestinal (GI) bleed and sepsis who were at a higher risk for early transfer to the ICU. We then created an ED intake huddle process that over time was refined to target patients with SIRS criteria with an elevated serum lactic acid level greater than 2.0 mmol/L or a GI bleed with a haematocrit value less than 24%. These interventions resulted in an 10.8 percentage points (31.7% (225/710) to 20.9% (369/1764)) decrease in the early transfers to the ICU for all hospital medicine patients admitted to the hospital from the ED. Mean RRT calls/day decreased by 17%, from 3.0 mean calls/day preintervention to 2.5 mean calls/day postintervention. These quality improvement initiatives have sustained successful outcomes for over 6 years due to integrating enhanced team communication as organisational cultural norm that has become the standard.

Restructuring hospitalist work schedules to improve care timeliness and efficiency.

Background In 2014, we recognised that the pace of admissions frequently exceeded our ability to assign a hospitalist. Long patient wait times occurred at admission, especially for patients arriving in the late afternoon when hospitalist day shifts were ending. Our purpose was to redesign hospitalist schedules, duties and method of distributing admissions to match demand. Design We used administrative data to tabulate Hospital Medicine admission requests by time of day and identified mismatch between volume and capacity with the current staffing model. We determined that we needed to accommodate 29 admits per day with peak admission volume in the late afternoon and early evening. The current staffing model failed after 22 admits. To realign staffing around patient admissions, we organised a series of Lean quality improvements, starting with a 2-day event in July 2014, and followed by a series of Plan-Do-Study-Act (PDSA) cycles. The improvement team included hospitalists, residents and administrators, and each PDSA cycle involved collection of feedback from all affected providers. Strategy At baseline, our hospitalist group had six daytime and two nighttime services, including teaching services and attending-only services. Four of eight services were available for admissions, while four were rounding-only. Admitting capacity (patients per day) was 22. Through three PDSA cycles, we successively adapted our staffing and admitting model until the final staffing model aligned with patient admissions. The final model included different shift start times, use of all 10 shifts for admissions and addition of an Advanced Registered Nurse Practitioner (ARNP) service. Results Admitting capacity increased to 30. We confirmed success with follow-up data on patient wait times. Emergency department mean patient wait times for admission decreased 36% from 66 to 43 min (p<0.001). Conclusion Quantifying admission demand by time of day, then designing work schedules and duties around meeting this demand was an effective approach to reduce patient wait times.