Effect of wearable continuous vital signs measurements on general wards length of stay

2021 ◽  
Author(s):  
Jobbe Leenen ◽  
Gijsbert Patijn
Keyword(s):  
Length Of Stay ◽  
Vital Signs ◽  
General Wards

Abstract P83: Predictors of Length of Stay for HF Patients: Results from Get With the Guidelines

2011 ◽  
Vol 4 (suppl_1) ◽  
Author(s):  
David J Whellan ◽  
Xin Zhao ◽  
Adrian F Hernandez ◽  
Eric D Peterson ◽  
Deepak L Bhatt ◽  
...  
Keyword(s):  
Heart Failure ◽  
Heart Rate ◽  
Length Of Stay ◽  
Vital Signs ◽  
P Value ◽  
Chi Square ◽  
Unit Increase ◽  
History Of ◽  
Multivariable Regression ◽  
Get With The Guidelines

Background: Heart failure (HF) admissions are frequent and result in significant expenditures. Identifying predictors of increased length of stay (LOS), particularly above the median LOS, may help providers set expectations for patients and target resources effectively. Methods: We analyzed HF admissions (n= 70,094) from January 2005 through April 2007 from 246 hospitals in the AHA's Get With The Guidelines-HF program. In a subset with BNP (n=44,535), baseline characteristics, admission vital signs and selected labs (BNP, creatinine, BUN, hemoglobin, and sodium) were included in a multivariable regression analysis to determine factors associated with LOS ≥4 days. Results: Patients were median age of 72, 45% female, 53% had ischemic etiology, and median LVEF was 35%. Median LOS was 4 days (25 th ,75 th 2,6). The most significant predictors of LOS ≥ 4 days were a higher admission BUN, higher heart rate, and lower SBP (Table 1). Age, insurance, race, creatinine, and LVEF were not. Conclusion: Upon admission for HF, certain vital signs, comorbidites, and laboratory values are associated with an increased likelihood of a LOS ≥ 4 days. These observations may be of value in the implementation of interventions aimed at reducing LOS and improving quality of care in HF. Variables Associated With Hospital LOS >/= 4 Days Variable Chi-Square OR Lower (95% CI) Upper (95% CI) P-value Admissioun BUN (/1 unit increase) 221.8 1.01 1.01 1.01 <.001 Admission SBP (/ 10-unit increase) 129.6 0.96 0.95 0.96 <.001 Heart Rate (/ 10-unit increase) 122.4 1.07 1.06 1.09 <.001 History of COPD/Asthma 45.8 1.19 1.13 1.25 <.001 Admission BNP (per 100-unit increase) 37.6 1.01 1.00 1.01 <.001 Female vs. Male 29.7 1.12 1.08 1.17 <.001 History of renal insufficiency 27.4 1.17 1.10 1.24 <.001 History of heart failure 18.0 0.89 0.85 0.94 <.001 Region: (MW vs. NE)
 (S vs NE)
 (W vs. NE) 17.3 0.71
 0.91
 0.71 0.60
 .077
 0.56 0.85
 1.08
 0.88 <.001

Rapid response teams for the critically ill

2016 ◽  
Author(s):  
Ken Hillman ◽  
Jack Chen
Keyword(s):  
Intensive Care ◽  
Early Stage ◽  
Vital Signs ◽  
Rapid Response ◽  
Serious Adverse Events ◽  
Rapid Response Systems ◽  
Acute Hospitals ◽  
Response Systems ◽  
General Wards ◽  
Seriously Ill

There is a high incidence of potentially preventable deaths and serious adverse events in acute hospitals. Most of these events occur on the general wards of the hospital. The concept of rapid response systems was developed as a way of identifying seriously-ill and at-risk patients in acute hospitals at an early stage in order to improve outcomes. The system has two major components—criteria to define the deteriorating patient linked to a rapid response. The criteria are based on a combination of abnormal vital signs and observations, and the response is based on matching the patient with staff with the appropriate skills. Implementing and evaluating hospital-wide systems present new challenges that are different to our approach to a new drug or procedure. As well as agreeing to the appropriate criteria and response, the system needs leadership and support across the whole hospital, including education programmes and, monitoring with appropriate quality assurance activities. Increasingly, the specialty of intensive care is designed around the needs of the seriously ill, rather than being geographically confined within the four walls of an intensive care unit. The concept of rapid response systems is part of that process.

scholarly journals Impact of the coronavirus pandemic on the patterns of vital signs recording and staff compliance with expected monitoring schedules on general wards

Resuscitation ◽  
2021 ◽  
Vol 158 ◽  
pp. 30-38
Author(s):  
Ina Kostakis ◽  
Gary B Smith ◽  
David Prytherch ◽  
Paul Meredith ◽  
Connor Price ◽  
...  
Keyword(s):  
Vital Signs ◽  
General Wards

‘Normal’ Vital Signs Belie Occult Hypoperfusion in Geriatric Trauma Patients

2010 ◽  
Vol 76 (1) ◽  
pp. 65-69 ◽  
Author(s):  
Jeremiah T. Martin ◽  
Fuad Alkhoury ◽  
Judith A. O'Connor ◽  
Tassos C. Kyriakides ◽  
John A. Bonadies
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Length Of Stay ◽  
Unit Length ◽  
Vital Signs ◽  
Intensive Care Unit Length ◽  
Hospital Length Of Stay ◽  
Common Finding ◽  
Trauma Patients ◽  
Severity Scores

Base deficit (BD) and lactic acid (LA) are accepted markers of hypoperfusion and predictors of outcome in the trauma patient and we aim to assess the value of these markers in the triage of the elderly with “normal” vital signs. Patients older than age 65 who presented between 1997 and 2004 but who did not have isolated head injuries were included. Three patient groups were established: normal, occult hypoperfusion (OH), and shock. Outcome measures included mortality, hospital length of stay, intensive care unit length of stay, and discharge disposition. One hundred six patients were included in the analysis and had similar Injury Severity Scores. Mean systolic blood pressure was similar in the normal and OH groups. Forty-two per cent of patients had abnormal BD or LA in the emergency room indicating OH. These patients were more likely to have a longer intensive care unit length of stay (8.6 days vs 3 days; P = 0.01) and were also more likely to be discharged to a nursing facility ( P = 0.03). The trend was toward increased mortality in the OH group. OH is a common finding in elderly trauma patients. Outcomes in these patients are different and more like those presenting in shock.

scholarly journals Monitoring Vital Signs: Development of a Modified Early Warning Scoring (Mews) System for General Wards in a Developing Country

PLoS ONE ◽  
2014 ◽  
Vol 9 (1) ◽  
pp. e87073 ◽  
Author(s):  
Una Kyriacos ◽  
Jennifer Jelsma ◽  
Michael James ◽  
Sue Jordan
Keyword(s):  
Developing Country ◽  
Early Warning ◽  
Vital Signs ◽  
General Wards

scholarly journals Hurricane Sandy - Initial Evaluation of Patient Characteristics

2019 ◽  
Vol 34 (s1) ◽  
pp. s7-s7
Author(s):  
Marc Rosenthal ◽  
Robert Dunne
Keyword(s):  
Emergency Department ◽  
Length Of Stay ◽  
Vital Signs ◽  
Retrospective Chart Review ◽  
Hurricane Sandy ◽  
System Response ◽  
Medical Needs ◽  
Medical Response ◽  
Wide Range ◽  
National Disaster

Introduction:Disaster medical team response by governmental and non-governmental responders is highly variable and poorly characterized. Each response is unique in terms of caseload, patient demographics, and medical needs encountered. This variability increases the difficulty of determining team member composition as well as supply and equipment needs. In an effort to demonstrate this issue, we have reviewed the National Disaster Medical Response to Hurricane Sandy.Methods:This project was a retrospective chart review of Hurricane Sandy data abstracted from the National Disaster Medical System (NDMS) Health Information Repository (HIR) medical records from the NDMS system response, and were abstracted for data including vital signs, ages, sex, chief complaint, and final impressions. In addition, length of stay among other parameters was abstracted. The data was analyzed using Microsoft Excel and Access with descriptive statistics. In addition, the results were compared to similar indices in a community emergency department and prior NDMS responses.Results:The results indicate a wide range of patient ages, chief complaints, and final impressions. The vast majority of patients seen by Disaster Medical Assistance Teams (DMAT) were stable with relatively low acuity issues. The total number of charts reviewed were 7,905. Respiratory complaints were the most frequent at 845 patients followed by toxicology/injuries at 706 patients and mental health issues at 452 patients. In approximately 3,400 patients, no diagnosis was present in the chart. Length of stay averaged below 1 hour and peak patient ages were between 50-60 with a significant number of infants less than 2 years.Discussion:Characterization of NDMS responses by DMATs and comparison with prior events and community emergency department caseloads can provide an insight into the needs of DMATs and other response organizations in future responses.

scholarly journals The association between the transfer of emergency department admitted patients to inpatient hallways and outcomes of oncology patients

2015 ◽  
Vol 4 (2) ◽  
pp. 1 ◽  
Author(s):  
Charles Lim ◽  
Matthew C. Cheung ◽  
Maureen E. Trudeau ◽  
Kevin R. Imrie ◽  
Ben De Mendonca ◽  
...  
Keyword(s):  
Emergency Department ◽  
Length Of Stay ◽  
Patient Flow ◽  
Vital Signs ◽  
Medication Administration ◽  
Oncology Patients ◽  
Flow Quality ◽  
Ed Crowding ◽  
The Impact

Objective: A protocol was implemented to ease Emergency Department (ED) crowding by moving suitable admitted patients into inpatient hallway beds (HALL) or off-service beds (OFF) when beds on an admitting service’s designated ward (ON) were not available. This study assessed the impact of hallway and off-service oncology admissions on ED patient flow, quality of care and patient satisfaction.Methods: Retrospective and prospective data were collected on patients admitted to the medical oncology service from Jan 1 to Dec 31, 2011. Data on clinician assessments and time performance measures were collected. Satisfaction surveys were prospectively administered to all patients. Results: Two hundred and ninty-seven patients (117 HALL, 90 OFF, 90 ON) were included in this study. There were no significant differences between groups for frequency of physician assessments, physical exam maneuvers at initial physician visit, time to complete vital signs or time to medication administration. The median (IQR) time spent admitted in the ED prior to departure from the ED was significantly longer for HALL patients (5.53 hrs [1.59-13.03 hrs]) compared to OFF patients (2.00 hrs [0.37-3.69 hrs]) and ON patients (2.18 hrs [0.15-5.57 hrs]) (p < .01). Similarly, the median (IQR) total ED length of stay was significantly longer for HALL patients (13.82 hrs [7.43-20.72 hrs]) compared to OFF patients (7.18 hrs [5.72-11.42 hrs]) and ON patients (9.34 hrs [5.43-14.06 hrs]) (p < .01). HALL patients gave significantly lower overall satisfaction scores with mean (SD) satisfaction scores for HALL, OFF and ON patients being 3.58 (1.20), 4.23 (0.58) and 4.29 (0.69) respectively (p < .01). Among HALL patients, 58% were not comfortable being transferred into the hallway and 4% discharged themselves against medical advice. Conclusions: The protocol for transferring ED admitted patients to inpatient hallway beds did not reduce ED length of stay for oncology patients. The timeliness and frequency of clinical assessments were not compromised; however, patient satisfaction was decreased.

scholarly journals Can medical admission and length of stay be accurately predicted by emergency staff, patients or relatives?

2007 ◽  
Vol 31 (4) ◽  
pp. 633 ◽  
Author(s):  
Andrew W Dent ◽  
Tracey J Weiland ◽  
Lisa Vallender ◽  
Nicola E Oettel
Keyword(s):  
Length Of Stay ◽  
Vital Signs ◽  
Prediction Tool ◽  
Short Stay ◽  
Reasonable Accuracy ◽  
Appropriate Use ◽  
Medical Assessment ◽  
Convenience Sample ◽  
Emergency Admissions ◽  
Medical Symptoms

Objectives: To determine the accuracy of predictions of the need for hospital admission and, if admitted, length of stay (LOS) made early in an emergency attendance by emergency department (ED) doctors, nurses, patients and relatives, and the characteristics of ED presentations predictive of admission and short stays (~3 days). Methods: Prospective collection of predictions by medical and nursing staff, patients and relatives of ED departure status and LOS (1 day, 2-3 days, 4- 7 days or longer) of a convenience sample of adults presenting with medical symptoms. Predictions were made before full medical assessment and matched against actual departure status and LOS. Vital signs and demographics were recorded. Results: Seventy five percent (2159/2904; CI 73%?77%) of all admission predictions in 704 patients were correct with 85% (575/673; CI 81%- 88%) of doctors? predictions correct. Thirty-five percent (361/1024) of all LOS predictions for 331 patients were correct with 46% (122/268; CI 40%- 52%) of doctors? predictions correct. Risk factors for short-stay over longer admission included age less than 65, normal oxygen saturations and selfreferral. Conclusion: Emergency admissions can be predicted with reasonable accuracy but LOS is difficult to predict. Development of a prediction tool may facilitate streaming and appropriate use of short-stay units.

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