Ineffective communication between nursing staff and residents leads to numerous educational and patient-care interruptions, increasing resident stress and overall workload. We developed an innovative and simple, secure electronic health record (EHR) base text paging system to communicate with internal medicine residents. The goal is to avoid unnecessary interruption during patient care or educational activities and reduce stress. Traditional paging system can send a phone number to call back. We developed and implemented a HIPPA-compliant, EHR-integrated text paging at a busy 591-bed urban hospital. Access was granted to unit clerks, nursing staff, case managers, and physicians. Senders could either send a traditional telephone number page or a text page through our EHR. The recipient could then either acknowledge receipt of the page or take appropriate actions. Afterward, Internal medicine residents were polled on overall satisfaction difference between basic phone based numeric paging and the enhanced EHR text paging system. Educational interruptions (averaging over 7 pages) decreased from 64% to 16%. Patient care interruptions fell from 68% to 12%. 88% of residents felt that 50% or less of the pages were non-emergent and did not require an immediate action. 92% of 25 surveyed internal medicine residents preferred text paging over numeric paging and responded through the EHR 60% of the time by placing direct orders. Time savings using the new system over a 3-month span amounted to 72.5 h in transmission time alone. Text paging among medical caregivers and internal medicine residents through EHR-associated communication reduced patient care and educational interruptions. It saved time spent sending pages, answering unnecessary pages and it improved resident's subjective stress and satisfaction levels.
Introduction:
Existing models predicting right ventricular failure (RVF) after durable left ventricular assist device (LVAD) support are limited due to lack of multicenter validation, absence of intraoperative characteristics, and marginal predictive power. We sought to derive and validate a risk model to predict post-LVAD RVF.
Methods:
Advanced heart failure (HF) patients (N=798) requiring continuous-flow LVAD were enrolled at the Utah Transplant Affiliated Hospitals (n=477), Inova Heart & Vascular Institute (n=183), and Henry Ford Medical Center (n=138). Baseline clinical and intraoperative characteristics were recorded. The primary outcome was RVF incidence, defined as the need for right VAD (RVAD) or intravenous inotropes for >14 days. Bootstrap imputation and lasso variable selection were used to derive a predictive model which was then validated. A risk calculator was developed classifying patients into risk groups, and survival was compared.
Results:
Patients were predominantly white (72%), males (84%), aged 56±13 years. Patients in the RVF and non-RVF groups were comparable in terms of sex, age, and LVAD indication, while RVF patients more commonly had a history of systemic hypertension, non-ischemic cardiomyopathy, lower INTERMACS profiles, and more commonly required inotropic or temporary circulatory support pre-LVAD. Overall, 193 (24.2%) patients developed RVF with 109 (56.5%) requiring inotropes and 84 (43.5%) an RVAD. Multivariable predictors for RVF are shown in the
Figure
and achieved a c-statistic of 0.74 (95% CI: 0.70-0.78). Inclusion of intraoperative characteristics did not improve model performance. Cumulative survival was higher in the minimal risk group compared to low, moderate, and high.
Conclusions:
The STOP-RVF calculator effectively stratifies the risk for RVF after LVAD support by implementing routinely collected clinical data. It could impact patient selection and peri-operative management of advanced HF patients.
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