The effects of a multidisciplinary pathway for perioperative management of patients with hip fracture.

OBJECTIVES: To determine if a multidisciplinary pathway focused on non-opioid pain management, delirium assessment, and resource utilization improved outcomes in geriatric hip fracture patients. The goal was to reduce opioid usage, consultation not congruent with guidelines, and increase use of regional anesthesia to reduce delirium and improve outcomes. METHODS: An observational study was performed on hip fracture patients before and after the intervention. Hospitalists were educated on indications for preoperative cardiac consultation and specialized preoperative cardiac testing according to evidence-based guidelines with the inpatient cardiology service. Additional education on multimodal analgesia, limiting opioids, and peripheral nerve blocks was provided by the acute pain service. Pre-intervention outcomes from 1 July 20171 July 2017 to 31 May 201831 May 2018 (N = 92) were compared to post-intervention outcomes from 1 July 20181 July 2018 to 31 May 201931 May 2019 (N = 98) and included delirium, length of stay, 30-day readmission rate, time from arrival to procedure start time, time to first physical therapy session, and completion of cardiology consult time. We examined adherence, use of nerve blocks, and pre- and post-operative pain scores and opioid use. RESULTS: Delirium was reduced from 50.0% (N = 46/92) to 28.6% (N = 28/98); p = 0.002. Postoperative opioid use (IV morphine milligram equivalents) decreased from an average of 57.2 mg (±67.7) to 42.6 mg (±58.2),P < .0001. There was a significant decrease in mean pre-operative (5.4 ± 4.14 to 5.05 ± 2.8, P < .0001) and post-operative pain scores (4.3 ± 5.2 to 3.2 ± 2.2, P < .0001). There was a significant reduction in time to cardiology consultation from 18 h] to 12 h ; p < .001). CONCLUSIONS: A multidisciplinary collaboration between hospitalists, anesthesiologists, and cardiologists for hip fracture patients was associated with a reduction in pain and delirium and time to cardiologist evaluation. Prospective studies focusing on additional patient-centered outcomes are warranted.

Improving the Discharge Experience of Hospital Patients Through Standard Tools and Methods of Education.

ABSTRACT: Discharge education is essential to patient health and care coordination. Patient satisfaction with discharge education reveals a hospital's ability to provide reliable, quality experiences that engage and prepare patients for recovery in the community. The purpose of this study was to examine and improve patient satisfaction with discharge preparation by providing timely, standardized methods of educating patients about their medical condition, discharge needs, and follow-up care. This project provided nursing and the care team with training in effective techniques such as the teach-back method as well as new tools like a discharge folder to be successful. Provider workflows were redesigned, and the discharge education document was changed to ensure appropriate information was provided to patients. Patient perspective and satisfaction with their degree of preparedness for discharge were measured using the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey. After intervention, an improvement in the HCAHPS survey top box percent score for the domains of Care Transitions, 52.41%-54.49% (p < .0001) and Discharge Information, 87.38-90.12% (p < .0001), was noted. Increasing scores for HCAHPS questions pertinent to discharge suggest the intervention improved patient satisfaction with discharge information and preparation for recovery outside the hospital.

Video engagement to improve handwashing duration: A longitudinal study assessing creative and messaging fatigue.

BACKGROUND: Poor hand hygiene can contribute to increased rates of health care and community-acquired infections. Effective hand hygiene involves both a washer's technique and the duration of their wash. METHODS: The purpose of this longitudinal study was 2-fold: to improve the ability of hand-washers to meet the recommended handwashing duration of ≥20 seconds and to assess the effect of washer fatigue with the intervention. An innovative system of smart connected soap and towel dispensers synchronized to engaging video content was implemented to meet this objective. RESULTS: The intervention increased mean handwashing duration by 7.5 seconds (95% CI: 6.6, 8.4) and improved handwashing duration ≥20 seconds by 39.3% (P < .001). Using a similar cohort of hand-washers over 26 months, the video content had peak effect in month 1, and declined to a new steady state at month 11. DISCUSSION: Handwashing for the recommended time can be difficult to achieve. Most hand hygiene studies examine the rate of completion without measuring duration. CONCLUSIONS: Video engagement can improve and sustain handwashing duration. To mitigate creative and messaging fatigue, video content refresh for this intervention should be considered at 3 months for optimal effect or at 11 months prior to full decline to new steady state.

Development and Validation of a Web-Based Severe COVID-19 Risk Prediction Model.

BACKGROUND: Coronavirus disease 2019 (COVID-19) carries high morbidity and mortality globally. Identification of patients at risk for clinical deterioration upon presentation would aid in triaging, prognostication, and allocation of resources and experimental treatments. RESEARCH QUESTION: Can we develop and validate a web-based risk prediction model for identification of patients who may develop severe COVID-19, defined as intensive care unit (ICU) admission, mechanical ventilation, and/or death? METHODS: This retrospective cohort study reviewed 415 patients admitted to a large urban academic medical center and community hospitals. Covariates included demographic, clinical, and laboratory data. The independent association of predictors with severe COVID-19 was determined using multivariable logistic regression. A derivation cohort (n=311, 75%) was used to develop the prediction models. The models were tested by a validation cohort (n=104, 25%). RESULTS: The median age was 66 years (Interquartile range [IQR] 54-77) and the majority were male (55%) and non-White (65.8%). The 14-day severe COVID-19 rate was 39.3%; 31.7% required ICU, 24.6% mechanical ventilation, and 21.2% died. Machine learning algorithms and clinical judgment were used to improve model performance and clinical utility, resulting in the selection of eight predictors: age, sex, dyspnea, diabetes mellitus, troponin, C-reactive protein, D-dimer, and aspartate aminotransferase. The discriminative ability was excellent for both the severe COVID-19 (training area under the curve [AUC]=0.82, validation AUC=0.82) and mortality (training AUC= 0.85, validation AUC=0.81) models. These models were incorporated into a mobile-friendly website. CONCLUSIONS: This web-based risk prediction model can be used at the bedside for prediction of severe COVID-19 using data mostly available at the time of presentation.

Update on medical management of acute hip fracture.

Morbidity and mortality rates associated with acute hip fracture remain high. Over the past decade, the management of hip fracture has shifted to emphasize prompt surgical treatment, multimodal analgesia to reduce opioid use, and incorporation of enhanced recovery pathways. Preoperative evaluation focuses on acutely correctable problems, with the understanding that delaying surgery may worsen the outcome. Prophylaxis of venous thromboembolism, treatment of preoperative anemia and acute kidney injury, and cardiac stabilization are important measures to reduce morbidity. Multimodal analgesia incorporating regional anesthesia techniques may help prevent delirium and facilitate early participation in physical therapy to reduce complications.

Development and Validation of a Prediction Model for Stroke, Cardiac, and Mortality Risk After Non-Cardiac Surgery.

Background Commonly used cardiovascular risk calculators do not provide risk estimation of stroke, a major postoperative complication with high morbidity and mortality. We developed and validated an accurate cardiovascular risk prediction tool for stroke, major cardiac complications (myocardial infarction or cardiac arrest), and mortality after non-cardiac surgery. Methods and Results This retrospective cohort study included 1 165 750 surgical patients over a 4-year period (2007-2010) from the American College of Surgeons National Surgical Quality Improvement Program Database. A predictive model was developed with the following preoperative conditions: age, history of coronary artery disease, history of stroke, emergency surgery, preoperative serum sodium (≤130 mEq/L, >146 mEq/L), creatinine >1.8 mg/dL, hematocrit ≤27%, American Society of Anesthesiologists physical status class, and type of surgery. The model was trained using American College of Surgeons National Surgical Quality Improvement Program data from 2007 to 2009 (n=809 880) and tested using data from 2010 (n=355 870). Risk models were developed using multivariate logistic regression. The outcomes were postoperative 30-day stroke, major cardiovascular events (myocardial infarction, cardiac arrest, or stroke), and 30-day mortality. Major cardiac complications occurred in 0.66% (n=5332) of patients (myocardial infarction, 0.28%; cardiac arrest, 0.41%), postoperative stroke in 0.25% (n=2005); 30-day mortality was 1.66% (n=13 484). The risk prediction model had high predictive accuracy with area under the receiver operating characteristic curve for stroke (training cohort=0.869, validation cohort=0.876), major cardiovascular events (training cohort=0.871, validation cohort=0.868), and 30-day mortality (training cohort=0.922, validation cohort=0.925). Surgery types, history of stroke, and coronary artery disease are significant risk factors for stroke and major cardiac complications. Conclusions Postoperative stroke, major cardiac complications, and 30-day mortality can be predicted with high accuracy using this web-based predictive model.

Development and Validation of a Web-Based Prediction Model for AKI after Surgery.

Background: AKI after surgery is associated with high mortality and morbidity. The purpose of this study is to develop and validate a risk prediction tool for the occurrence of postoperative AKI requiring RRT (AKI-dialysis). Methods: This retrospective cohort study had 2,299,502 surgical patients over 2015-2017 from the American College of Surgeons National Surgical Quality Improvement Program Database (ACS NSQIP). Eleven predictors were selected for the predictive model: age, history of congestive heart failure, diabetes, ascites, emergency surgery, hypertension requiring medication, preoperative serum creatinine, hematocrit, sodium, preoperative sepsis, and surgery type. The predictive model was trained using 2015-2016 data (n=1,487,724) and further tested using 2017 data (n=811,778). A risk model was developed using multivariable logistic regression. Results: AKI-dialysis occurred in 0.3% (n=6853) of patients. The unadjusted 30-day postoperative mortality rate associated with AKI-dialysis was 37.5%. The AKI risk prediction model had high area under the receiver operating characteristic curve (AUC; training cohort: 0.89, test cohort: 0.90) for postoperative AKI-dialysis. Conclusions: This model provides a clinically useful bedside predictive tool for postoperative AKI requiring dialysis.

Making Room at the Bedside: Improving Communication Alongside Medical Education Through Interdisciplinary Rounds.

Interdisciplinary rounding has been shown to improve patient safety and provider engagement. Many models for interdisciplinary rounding have been proposed but few focus on preserving bedside medical education. The authors changed the interdisciplinary bedside rounding model to accommodate more time for medical education. The objective was to assess perceptions of communication, care coordination, and teamwork surrounding this change. Resident and attending physicians and unit-based nursing staff completed an anonymous online survey prior to and following the rounding intervention. Length of stay on medical units also was monitored prior to and following the rounding intervention. Following the intervention, there were perceived improvements in interdisciplinary communication, care coordination, and teamwork, and there were no significant changes in length of stay.

Improved Supervision and Safety of Discharges Through Formal Discharge Education.

The goal of this study is to evaluate change in residents' assessment of supervision and safety of the discharge process after formal discharge instruction education. An educational lecture and workshop addressing high-risk medications, medication reconciliation, follow-up, and handoffs were provided to internal medicine residents. Residents were given a longitudinal survey before and after the discharge education session. Significant improvement in perception was demonstrated in review of discharge instructions ( P < .001), review of new medications/side effects with patients ( P < .001), and review of discharge instructions with and receiving feedback from attending physicians ( P < .001). On review of 40 discharge instructions pre and post intervention, there was an improvement in completion of instructions for high-risk medications ( P < .05 [14 insulin, 26 anticoagulation]). This intervention was viewed positively by residents; more than two thirds of all residents favored a process of formal training over the current model of "training by doing."