ABSTRACT
Importance: Late predictions of hospitalized patient deterioration, resulting from early warning systems (EWS) with limited data sources and/or a care team's lack of shared situational awareness, contribute to delays in clinical interventions. The COmmunicating Narrative Concerns Entered by RNs (CONCERN) Early Warning System (EWS) uses real-time nursing surveillance documentation patterns in its machine learning algorithm to identify patients' deterioration risk up to 42 hours earlier than other EWSs. Objective: To test our a priori hypothesis that patients with care teams informed by the CONCERN EWS intervention have a lower mortality rate and shorter length of stay (LOS) than the patients with teams not informed by CONCERN EWS. Design: One-year multisite, pragmatic controlled clinical trial with cluster-randomization of acute and intensive care units to intervention or usual-care groups. Setting: Two large U.S. health systems. Participants: Adult patients admitted to acute and intensive care units, excluding those on hospice/palliative/comfort care, or with Do Not Resuscitate/Do Not Intubate orders. Intervention: The CONCERN EWS intervention calculates patient deterioration risk based on nurses' concern levels measured by surveillance documentation patterns, and it displays the categorical risk score (low, increased, high) in the electronic health record (EHR) for care team members. Main Outcomes and Measures: Primary outcomes: in-hospital mortality, LOS; survival analysis was used. Secondary outcomes: cardiopulmonary arrest, sepsis, unanticipated ICU transfers, 30-day hospital readmission. Results: A total of 60 893 hospital encounters (33 024 intervention and 27 869 usual-care) were included. Both groups had similar patient age, race, ethnicity, and illness severity distributions. Patients in the intervention group had a 35.6% decreased risk of death (adjusted hazard ratio [HR], 0.644; 95% confidence interval [CI], 0.532-0.778; P<.0001), 11.2% decreased LOS (adjusted incidence rate ratio, 0.914; 95% CI, 0.902-0.926; P<.0001), 7.5% decreased risk of sepsis (adjusted HR, 0.925; 95% CI, 0.861-0.993; P=.0317), and 24.9% increased risk of unanticipated ICU transfer (adjusted HR, 1.249; 95% CI, 1.093-1.426; P=.0011) compared with patients in the usual-care group. Conclusions and Relevance: A hospital-wide EWS based on nursing surveillance patterns decreased in-hospital mortality, sepsis, and LOS when integrated into the care team's EHR workflow. Trial Registration: ClinicalTrials.gov Identifier: NCT03911687 https://clinicaltrials.gov/ct2/show/NCT03911687. Key Points: Question: Do patients whose care team receive the CONCERN Early Warning System (EWS) intervention have a lower mortality rate and shorter length of stay than patients in the usual-care group?Findings: In this multisite, pragmatic cluster-randomized controlled clinical trial that included 60 893 hospital patient encounters, patients whose care team received the CONCERN EWS intervention had a 35.6% decreased risk of death and 11.2% shorter length of stay compared with those in the usual-care group.Meaning: A machine learning-based EWS modeled on nursing surveillance patterns significantly decreased the risk of inpatient deterioration events.
ABSTRACT
Background: The Risk Assessment and Prediction Tool (RAPT) and the Activity Measure for Post-Acute Care "6-Clicks" Mobility Score (AM-PAC) are validated discharge planning tools for patients undergoing total hip arthroplasty (THA) and total knee arthroplasty (TKA). Planning for discharge with these tools considers very different factors and it is important to determine if they relate. Purpose: We sought to determine whether the preoperative RAPT score would correlate with postoperative AM-PAC score for predicting discharge destination for THA and TKA populations. Secondarily, we sought to examine whether the AM-PAC and RAPT scores would remain statistically significant predictors of discharge destination despite covariates. Methods: A retrospective cohort study was performed for patients who underwent THA or TKA from January 2020 to December 2022 at a specialty orthopedic hospital. Primary variables included the RAPT score, the AM-PAC score, and discharge disposition. Correlation between AM-PAC and RAPT scores was tested using Pearson's correlation coefficient, and association between both scores and discharge destination was tested using chi-square tests and multivariable logistic regression. Results: Our comparison of AM-PAC scores and RAPT scores found a statistically significant, positive correlation in both THA and TKA patients. Regression analysis found that increased RAPT and AM-PAC scores resulted in higher odds of being discharged home for both populations, after adjusting for all other variables. In both cohorts, patients discharged to a facility were more likely to be female, be over the age of 70 years, have Medicare/Medicaid insurance, and have a higher number of preoperative social work visits or any incidence of an intraoperative or hospital complication. Conclusions: This retrospective study found that RAPT score correlated with AM-PAC score for predicting discharge destination for elective THA and TKA populations, suggesting that these scores may be predictors of home discharge destination even when accounting for covariates. Further study is recommended.
ABSTRACT
Background: Increasing numbers of patients are undergoing total joint arthroplasty as a treatment for osteoarthritis, which can be an anxiety-provoking experience. Setting expectations through a preoperative physical therapy (pre-op PT) session can alleviate some of these stressors, potentially decrease hospital length of stay (LOS), and promote home discharge. Purpose: We sought to determine whether attending a pre-op PT session is associated with decreased hospital LOS and home discharge in total hip arthroplasty (THA) and total knee arthroplasty (TKA) patients. Methods: A retrospective cohort study was performed of 20,822 patients who underwent THA or TKA between January 2020 and December 2023. Pre-op PT attendance and covariates, including patient demographics and clinical data, were collected and analyzed for association with LOS and discharge disposition. Results: Unadjusted univariate analysis revealed that THA and TKA patients who received pre-op PT had a significantly lower average LOS and were more likely to be discharged home. Our multivariate regression model showed that pre-op PT was not significantly associated with LOS in both groups but was significantly associated with home discharge among THA patients. Conclusions: Our retrospective study of the effect of pre-op PT education on LOS and discharge disposition for elective THA and TKA patients found different results in univariate and multivariate analysis. Further study is needed to confirm the association found on multivariate analysis between pre-op PT and home discharge in THA patients.
