Supporting the detection of patient deterioration: Observation chart design affects the recognition of abnormal vital signs

Resuscitation ◽  
2012 ◽  
Vol 83 (9) ◽  
pp. 1111-1118 ◽  
Author(s):  
Megan H.W. Preece ◽  
Andrew Hill ◽  
Mark S. Horswill ◽  
Marcus O. Watson
Keyword(s):  
Vital Signs ◽  
Patient Deterioration ◽  
Chart Design

scholarly journals Physiological Observations and Nursing Interventions in the Pre-Arrest Patient: A Descriptive Study

2021 ◽  
Author(s):  
◽  
Tara Marie Ryton-Malden
Keyword(s):  
Cardiac Arrest ◽  
Medical Staff ◽  
Early Recognition ◽  
Vital Signs ◽  
Nursing Interventions ◽  
Nursing Documentation ◽  
Patient Deterioration ◽  
Tertiary Teaching ◽  
Improve Compliance ◽  
Tertiary Teaching Hospital

<p>Aim: To identify how nurses respond to abnormal physiological observations in the 12 hours prior to a patient having a cardiac arrest. Methods: A descriptive observational design was used to retrospectively review the observation charts and nursing notes of 28 patients who had an in-hospital cardiac arrest, during a 20 month period. This study was performed in a large, tertiary teaching hospital in New Zealand. Key Findings Only one patient met the hospitals minimum standard of four hourly observations and a full set of vital signs were performed on only three patients. The nursing responses were limited to increasing the frequency of observations or informing the doctor. There were few other interventions to treat the abnormality. Eight (32%) patients who had either no response or a partial response to their abnormal physiology did not survive. The nursing documentation demonstrated that abnormal neurological observations were tolerated for significant periods of time and were not acted upon in 62% of these patients. The nursing documentation revealed that the delivery of oxygen was often insufficient to meet the patient's requirements and the medical staff were aware of less than half the patients with abnormal physiology. Discussion removed statement re pt survival: This research identified major deficiencies with recording patient vital signs. If these are not recorded regularly, patient deterioration will be missed and treatment cannot be initiated. Nurses need to respond to abnormal physiology beyond repeating vital signs and informing the medical staff. They are accountable for initiating interventions to prevent further deterioration. Conclusion: The early recognition of patient deterioration and treatment are essential to prevent cardiac arrest. Education strategies are required to improve compliance with recording patient vital signs, communication between nursing and medical staff and how to respond to patient deterioration. The barriers to these must be addressed and solutions sought if patient mortality is to be improved.</p>

scholarly journals Cueing Attention to a Matrix of Values on a Head-Worn Display: Four Studies with a Multiple Patient Monitoring Task

2019 ◽  
Vol 63 (1) ◽  
pp. 1771-1771
Author(s):  
Isaac S. Salisbury ◽  
Tsz-Lok Tang ◽  
Caitlin Browning ◽  
Paul D. Schlosser ◽  
Ismail Mohamed ◽  
...  
Keyword(s):  
Patient Monitoring ◽  
Vital Signs ◽  
High Contrast ◽  
Design Features ◽  
Visual Cue ◽  
Monitoring Task ◽  
Patient Deterioration ◽  
Auditory Alerts ◽  
Multiple Patients

Head-worn displays (HWDs) can help clinicians monitor multiple patients by displaying multiple patients’ vital signs. We conducted four experiments exploring design features that affect how a HWD can quickly and reliably cue attention to patient deterioration. In a series of lab-based experiments, we found that a HWD could quickly and reliably cue participants’ attention with high-contrast visual highlights with two distinct levels, or with a short white flash. However, visual alerts on a HWD did not cue attention as quickly as similar alerts on a conventional screen or auditory alerts. We conclude that HWDs can quickly notify clinicians of patient deterioration when paired with a strong visual cue, but there are perceptual challenges unique to HWDs.

scholarly journals Reliability of wireless monitoring using a wearable patch sensor in high-risk surgical patients at a step-down unit in the Netherlands: a clinical validation study

BMJ Open ◽  
2018 ◽  
Vol 8 (2) ◽  
pp. e020162 ◽  
Author(s):  
Martine J M Breteler ◽  
Erik Huizinga ◽  
Kim van Loon ◽  
Luke P H Leenen ◽  
Daan A J Dohmen ◽  
...  
Keyword(s):  
Heart Rate ◽  
High Risk ◽  
Outcome Measures ◽  
Vital Signs ◽  
Wireless Sensor ◽  
Surgical Patients ◽  
Data Loss ◽  
Limits Of Agreement ◽  
Patient Deterioration ◽  
Step Down

Background and objectivesIntermittent vital signs measurements are the current standard on hospital wards, typically recorded once every 8 hours. Early signs of deterioration may therefore be missed. Recent innovations have resulted in ‘wearable’ sensors, which may capture patient deterioration at an earlier stage. The objective of this study was to determine whether a wireless ‘patch’ sensor is able to reliably measure respiratory and heart rate continuously in high-risk surgical patients. The secondary objective was to explore the potential of the wireless sensor to serve as a safety monitor.DesignIn an observational methods comparisons study, patients were measured with both the wireless sensor and bedside routine standard for at least 24 hours.SettingUniversity teaching hospital, single centre.ParticipantsTwenty-five postoperative surgical patients admitted to a step-down unit.Outcome measuresPrimary outcome measures were limits of agreement and bias of heart rate and respiratory rate. Secondary outcome measures were sensor reliability, defined as time until first occurrence of data loss.Results1568 hours of vital signs data were analysed. Bias and 95% limits of agreement for heart rate were −1.1 (−8.8 to 6.5) beats per minute. For respiration rate, bias was −2.3 breaths per minute with wide limits of agreement (−15.8 to 11.2 breaths per minute). Median filtering over a 15 min period improved limits of agreement of both respiration and heart rate. 63% of the measurements were performed without data loss greater than 2 min. Overall data loss was limited (6% of time).ConclusionsThe wireless sensor is capable of accurately measuring heart rate, but accuracy for respiratory rate was outside acceptable limits. Remote monitoring has the potential to contribute to early recognition of physiological decline in high-risk patients. Future studies should focus on the ability to detect patient deterioration on low care environments and at home after discharge.

How to detect the subtle changes of early deterioration

2020 ◽  
Vol 11 (7) ◽  
pp. 325-330
Author(s):  
Kathryn Latimer-Jones
Keyword(s):  
Systematic Approach ◽  
Vital Signs ◽  
Nursing Role ◽  
Patient Deterioration ◽  
Life Threatening

A crucial nursing role is the identification of patient deterioration. Identifying deterioration usually begins with the observation of vital signs. Nevertheless, this depends on how users interpret the results they find, as well as their ability to consult with their senior colleagues when needed. The aim of this article is to help nurses improve their knowledge of the skills required to promptly identify potentially life-threatening problems by employing a systematic approach, which can ultimately result in better care and better outcomes.

Observation chart design features affect the detection of patient deterioration: a systematic experimental evaluation

2015 ◽  
Vol 72 (1) ◽  
pp. 158-172 ◽  
Author(s):  
Melany J. Christofidis ◽  
Andrew Hill ◽  
Mark S. Horswill ◽  
Marcus O. Watson
Keyword(s):  
Experimental Evaluation ◽  
Design Features ◽  
Patient Deterioration ◽  
Chart Design

scholarly journals Eye-tracking reveals how observation chart design features affect the detection of patient deterioration: An experimental study

2019 ◽  
Vol 75 ◽  
pp. 230-242 ◽  
Author(s):  
Lillian Cornish ◽  
Andrew Hill ◽  
Mark S. Horswill ◽  
Stefanie I. Becker ◽  
Marcus O. Watson
Keyword(s):  
Experimental Study ◽  
Eye Tracking ◽  
Design Features ◽  
Patient Deterioration ◽  
Chart Design

Applying heuristic evaluation to observation chart design to improve the detection of patient deterioration

2013 ◽  
Vol 44 (4) ◽  
pp. 544-556 ◽  
Author(s):  
Megan H.W. Preece ◽  
Andrew Hill ◽  
Mark S. Horswill ◽  
Rozemary Karamatic ◽  
David G. Hewett ◽  
...  
Keyword(s):  
Heuristic Evaluation ◽  
Patient Deterioration ◽  
Chart Design

scholarly journals Vital Signs Monitoring with Wearable Sensors in High-risk Surgical Patients

2020 ◽  
Vol 132 (3) ◽  
pp. 424-439 ◽  
Author(s):  
Martine J. M. Breteler ◽  
Eline J. KleinJan ◽  
Daan A. J. Dohmen ◽  
Luke P. H. Leenen ◽  
Richard van Hillegersberg ◽  
...  
Keyword(s):  
High Risk ◽  
Wearable Sensors ◽  
Vital Signs ◽  
Surgical Patients ◽  
Major Surgery ◽  
Data Loss ◽  
Limits Of Agreement ◽  
Correct Treatment ◽  
Patient Deterioration ◽  
Vital Signs Monitoring

Abstract Background Vital signs are usually recorded once every 8 h in patients at the hospital ward. Early signs of deterioration may therefore be missed. Wireless sensors have been developed that may capture patient deterioration earlier. The objective of this study was to determine whether two wearable patch sensors (SensiumVitals [Sensium Healthcare Ltd., United Kingdom] and HealthPatch [VitalConnect, USA]), a bed-based system (EarlySense [EarlySense Ltd., Israel]), and a patient-worn monitor (Masimo Radius-7 [Masimo Corporation, USA]) can reliably measure heart rate (HR) and respiratory rate (RR) continuously in patients recovering from major surgery. Methods In an observational method comparison study, HR and RR of high-risk surgical patients admitted to a step-down unit were simultaneously recorded with the devices under test and compared with an intensive care unit–grade monitoring system (XPREZZON [Spacelabs Healthcare, USA]) until transition to the ward. Outcome measures were 95% limits of agreement and bias. Clarke Error Grid analysis was performed to assess the ability to assist with correct treatment decisions. In addition, data loss and duration of data gaps were analyzed. Results Twenty-five high-risk surgical patients were included. More than 700 h of data were available for analysis. For HR, bias and limits of agreement were 1.0 (–6.3, 8.4), 1.3 (–0.5, 3.3), –1.4 (–5.1, 2.3), and –0.4 (–4.0, 3.1) for SensiumVitals, HealthPatch, EarlySense, and Masimo, respectively. For RR, these values were –0.8 (–7.4, 5.6), 0.4 (–3.9, 4.7), and 0.2 (–4.7, 4.4) respectively. HealthPatch overestimated RR, with a bias of 4.4 (limits: –4.4 to 13.3) breaths/minute. Data loss from wireless transmission varied from 13% (83 of 633 h) to 34% (122 of 360 h) for RR and 6% (47 of 727 h) to 27% (182 of 664 h) for HR. Conclusions All sensors were highly accurate for HR. For RR, the EarlySense, SensiumVitals sensor, and Masimo Radius-7 were reasonably accurate for RR. The accuracy for RR of the HealthPatch sensor was outside acceptable limits. Trend monitoring with wearable sensors could be valuable to timely detect patient deterioration. Editor’s Perspective What We Already Know about This Topic What This Article Tells Us That Is New

Assessing beyond vital signs to detect early patient deterioration

2015 ◽  
Vol 19 (2) ◽  
pp. 53-53 ◽  
Author(s):  
Wei Ling Chua ◽  
Sok Ying Liaw
Keyword(s):  
Vital Signs ◽  
Patient Deterioration
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