Dataset Information

Mortality and Length of Stay Trends Following Implementation of a Rapid Response System and Real-Time Automated Clinical Deterioration Alerts.

ABSTRACT: A study was performed to determine the potential influence of a rapid response system (RRS) employing real-time clinical deterioration alerts (RTCDAs) on patient outcomes involving 8 general medicine units. Introduction of the RRS occurred in 2006 with staged addition of the RTCDAs in 2009. Statistically significant year-to-year decreases in mortality were observed through 2014 ( r = -.794; P = .002). Similarly, year-to-year decreases in the number of cardiopulmonary arrests (CPAs; r = -.792; P = .006) and median lengths of stay ( r = -.841; P = .001) were observed. There was a statistically significant year-to-year increase in the number of RRS activations for these units ( r = .939; P < .001) that was inversely correlated with the occurrence of CPAs ( r = -.784; P = .007). In this single-institution retrospective study, introduction of a RRS employing RTCDAs was associated with lower hospital mortality, CPAs, and hospital length of stay.

SUBMITTER: Kollef MH

PROVIDER: S-EPMC5783295 | biostudies-literature | 2017 Jan/Feb

REPOSITORIES: biostudies-literature

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Mortality and Length of Stay Trends Following Implementation of a Rapid Response System and Real-Time Automated Clinical Deterioration Alerts.

Kollef Marin H MH Heard Kevin K Chen Yixin Y Lu Chenyang C Martin Nelda N Bailey Thomas T

American journal of medical quality : the official journal of the American College of Medical Quality 20160709 1

A study was performed to determine the potential influence of a rapid response system (RRS) employing real-time clinical deterioration alerts (RTCDAs) on patient outcomes involving 8 general medicine units. Introduction of the RRS occurred in 2006 with staged addition of the RTCDAs in 2009. Statistically significant year-to-year decreases in mortality were observed through 2014 ( r = -.794; P = .002). Similarly, year-to-year decreases in the number of cardiopulmonary arrests (CPAs; r = -.792; P ...[more]

PMID: 26566998

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Project description:STUDY DESIGN: Retrospective cohort study. BACKGROUND: Several studies focus on the long-term results of anterior cervical discectomy and fusion (ACDF) surgeries, but little information exists regarding how various patient-related, procedure-related, and payer-related variables may affect postoperative hospital length of stay (LOS). OBJECTIVE: To determine what factors, if any, contribute to increased hospital LOS in patients who have had an ACDF. METHODS: Retrospective cohort study of 108 consecutive patients who underwent elective ACDF at a Midwest academic medical center. Extensive preoperative, intraoperative, and postoperative data were abstracted and analyzed to identify prognostic factors for an increased LOS. Multivariate analysis was performed to analyze the effects of patient and hospital characteristics on hospital LOS. RESULTS: 103 patients met inclusion and exclusion criteria. The mean LOS for patients undergoing ACDF was 1.98 (±1.6) days. Only 29% of patients had one level fused. The mean blood loss during surgery was 87.4 ± 99.6 mL. One subject lost 700 mL of blood. Complications, though rare, included uncontrolled postoperative pain (13%), cardiac (6%), pulmonary (4%), and urinary (3%). Covariates included in the final model were age, sex, cardiac complication, urinary complication, and pulmonary complication. Factors that contributed to increased LOS and their associated adjusted mean days were: ≥50 years of age (2.5 ± 1.2 days), female gender (2.3 ± 1.2 days), and three particular types of complications. The complications that had the largest effect on increased LOS from least to most severe were cardiac (3.5 ± 1.3 days), urinary (4.7 ± 1.3 days), and pulmonary (5.3 ± 1.3 days). CONCLUSIONS: The information presented in this study may be useful for patients, clinicians, and insurance companies, including precertification and case-management services. Our results can be instrumental in designing future prospective studies using more detailed analyses with more patients, more surgeons, and multiple institutions. [Table: see text].

Project description:PurposeKnowledge-based planning (KBP) offers the ability to predict dose-volume metrics based on information extracted from previous plans, reducing plan variability and improving plan quality. As clinical integration of KBP is increasing there is a growing need for quantitative evaluation of KBP models. A .NET-based application, RapidCompare, was created for automated plan creation and analysis of Varian RapidPlan models.MethodsRapidCompare was designed to read calculation parameters and a list of reference plans. The tool copies the reference plan field geometry and structure set, applies the RapidPlan model, optimizes the KBP plan, and generates data for quantitative evaluation of dose-volume metrics. A cohort of 85 patients, divided into training (50), testing (10), and validation (25) groups, was used to demonstrate the utility of RapidCompare. After training and tuning, the KBP model was paired with three different optimization templates to compare various planning strategies in the validation cohort. All templates used the same set of constraints for the planning target volume (PTV). For organs-at-risk, the optimization template provided constraints using the whole dose-volume histogram (DVH), fixed-dose/volume points, or generalized equivalent uniform dose (gEUD). The resulting plans from each optimization approach were compared using DVH metrics.ResultsRapidCompare allowed for the automated generation of 75 total plans for comparison with limited manual intervention. In comparing optimization techniques, the Dose/Volume and Lines optimization templates generated plans with similar DVH metrics, with a slight preference for the Lines technique with reductions in heart V30Gy and spinal cord max dose. The gEUD model produced high target heterogeneity.ConclusionAutomated evaluation allowed for the exploration of multiple optimization templates in a larger validation cohort than would have been feasible using a manual approach. A final KBP model using line optimization objectives produced the highest quality plans without human intervention.

Dataset Information

Mortality and Length of Stay Trends Following Implementation of a Rapid Response System and Real-Time Automated Clinical Deterioration Alerts.

Publications

Mortality and Length of Stay Trends Following Implementation of a Rapid Response System and Real-Time Automated Clinical Deterioration Alerts.

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