Nurse-in-the-loop smart home detection of health events associated with diagnosed chronic conditions: A case-event series.
| Autor: | Fritz R; College of Nursing, Washington State University, Vancouver, WA, United States of America., Wuestney K; College of Nursing, Washington State University, Spokane, WA, United States of America., Dermody G; School of Nursing, Midwifery and Paramedicine, University of the Sunshine Coast, Queensland, Australia., Cook DJ; School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA, United States of America. |
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| Jazyk: | angličtina |
| Zdroj: | International journal of nursing studies advances [Int J Nurs Stud Adv] 2022 Dec; Vol. 4, pp. 100081. Date of Electronic Publication: 2022 May 25. |
| DOI: | 10.1016/j.ijnsa.2022.100081 |
| Abstrakt: | Background: Telehealth and home-based care options significantly expanded during the SARS-CoV2 pandemic. Sophisticated, remote monitoring technologies now exist that support at-home care. Advances in the research of smart homes for health monitoring have shown these technologies are capable of recognizing and predicting health changes in near-real time. However, few nurses are familiar enough with this technology to use smart homes for optimizing patient care or expanding their reach into the home between healthcare touch points. Objective: The objective of this work is to explore a partnership between nurses and smart homes for automated remote monitoring and assessing of patient health. We present a series of health event cases to demonstrate how this partnership may be harnessed to effectively detect and report on clinically relevant health events that can be automatically detected by smart homes. Participants: 25 participants with multiple chronic health conditions. Methods: Ambient sensors were installed in the homes of 25 participants with multiple chronic health conditions. Motion, light, temperature, and door usage data were continuously collected from participants' homes. Descriptions of health events and participants' associated behaviors were captured via weekly nursing telehealth visits with study participants and used to analyze sensor data representing health events. Two cases of participants with congestive heart failure exacerbations, one case of urinary tract infection, two cases of bowel inflammation flares, and four cases of participants with sleep interruption were explored. Results: For each case, clinically relevant health events aligned with changes from baseline in behavior data patterns derived from sensors installed in the participant's home. In some cases, the detected event was precipitated by additional behavior patterns that could be used to predict the event. Conclusions: We found evidence in this case series that continuous sensor-based monitoring of patient behavior in home settings may be used to provide automated detection of health events. Nursing insights into smart home sensor data could be used to initiate preventive strategies and provide timely intervention. Tweetable Abstract: Nurses partnered with smart homes could detect exacerbations of health conditions at home leading to early intervention. Competing Interests: None (© 2022 Published by Elsevier Ltd.) |
| Databáze: | MEDLINE |
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