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Towards a comprehensive algorithmic decision-support system in public service delivery : The case of wearable continuous vital signs monitoring in hospitalized patients.

Siccha Lazaro, B.E. (2023) Towards a comprehensive algorithmic decision-support system in public service delivery : The case of wearable continuous vital signs monitoring in hospitalized patients.

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Abstract:In recent years, decision-support systems have become a useful instrument for boosting efficiency and productivity in the provision of public services. However, the low sensitivity to individual settings and the lack of representation of certain groups might enhance systemic biases in such decision-support systems. The present study seeks to evaluate the accuracy of data used in algorithmic decision-support systems and the degree to which general standards in such systems reflect individual characteristics. Specifically, the study focuses on an algorithmic decision-support system deployed in a healthcare setting and designed to detect early patient deterioration through continuous monitoring of vital signs. The study was conducted at Isala Hospital Zwolle in the Netherlands, utilizing the Healthdot Philips patch to monitor the vital signs of hospitalized patients. The results showed that contextual factors such as activity, patient positioning, and individual factors such as BMI and age, affect the quality of heart rate and respiratory rate data obtained by the device. Similarly, it was observed that individual factors exert an influence on vital sign values. Specifically, heart rate values exhibited a significant increase among younger age groups when compared to other age groups. The results of this study show the importance of critical analysis of the completeness of the dataset used in algorithms for decision-support systems. In addition, the results of this study emphasize the importance of avoiding general approaches to diverse demographic populations.
Item Type:Essay (Master)
Clients:
Isala Hospital, Zwolle, The Netherlands
Faculty:BMS: Behavioural, Management and Social Sciences
Subject:88 social and public administration
Programme:Public Administration MSc (60020)
Link to this item:https://purl.utwente.nl/essays/96836
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