Studies in health technology and informatics
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Assessment of vital signs is an essential part of surveillance of critically ill patients to detect condition changes and clinical deterioration. While most modern electronic medical records allow for vitals to be recorded in a structured format, the frequency and quality of what is electronically stored may differ from how often these measures are actually recorded. We created a tool that extracts blood pressure, heart rate, temperature, respiratory rate, blood oxygen saturation, and pain level from nursing and other clinical notes recorded in the course of inpatient care to supplement structured vital sign data.
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Stud Health Technol Inform · Jan 2015
Development and Usability Evaluation of the Mobile Delirium Assessment App Based on Confusion Assessment Method for Intensive Care Unit (CAM-ICU).
Delirium is a common complication among patients in ICU settings. The accuracy of using the assessment tool CAM-ICU to detect delirium is relatively low during routine practice among bedside nurses. The aim of this study is to develop a mobile application (app) to detect delirium in early stage and to test its usability among ICU nurses. ⋯ A questionnaire was created based on the Technology Acceptance Model (TAM) measuring their response to the four domains of TAM: perceived usefulness (PU), perceived ease of use (PEOU), attitudes towards usage (ATU) and behavioral intention to use (BIU). One hundred and two ICU nurses completed the survey. The result indicated that the app we developed has easy to use interfaces and is easier to use compared to the regular CAM-ICU.
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Stud Health Technol Inform · Jan 2015
Implementation of Data Drive Heart Rate and Respiratory Rate parameters on a Pediatric Acute Care Unit.
The majority of hospital physiologic monitor alarms are not clinically actionable and contribute to alarm fatigue. In 2014, The Joint Commission declared alarm safety as a National Patient Safety Goal and urged prompt action by hospitals to mitigate the issue [1]. It has been demonstrated that vital signs in hospitalized children are quite different from currently accepted reference ranges [2]. Implementation of data-driven, age stratified vital sign parameters (Table 1) for alarms in this patient population could reduce alarm frequency.
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Stud Health Technol Inform · Jan 2015
Developing an Emergency Physician Productivity Index Using Descriptive Health Analytics.
Emergency department (ED) crowding became a major barrier to receiving timely emergency care. At King Faisal Specialist Hospital and Research Center, Saudi Arabia, we identified variables and factors affecting crowding and performance to develop indicators to help evaluation and improvement. ⋯ Three variables were identified for their influence on productivity and performance; Number of Treated Patients per Physician, Patient Acuity Level and Treatment Time. The study suggested a formula to calculate the productivity index of each physician through dividing the Number of Treated Patients by Patient Acuity Level squared and Treatment Time to identify physicians with low productivity index and investigate causes and factors.