Expanding the skills of specialist staff for the effective use of wearables in everyday hospital life
Knowledge database Human Personnel recruitment & retention Training & digital expertise B.2: Hospital in Motion - Preventing complications through activity monitoring in hospitalIn hospitals, patients' lack of exercise often leads to complications and slows down the recovery process. As there is no dedicated specialist responsible for physical activity, fitness and exercise are often neglected, even though inactivity can have serious consequences. Studies show that healthcare wearables (HWDs) can provide valuable data on physical activity and health. This requires new competences and interprofessional collaboration in order to motivate patients to be active and provide them with targeted care.
Problem description, research question and relevance
Lack of exercise among patients in hospitals is a common problem that often causes complications and impairs recovery. As physical fitness and activity are not the responsibility of a specific professional, these aspects are often not systematically recorded and patients are not encouraged to be active. Inactivity, in the absence of medical restrictions during hospitalisation, has drastic effects in the form of balance deficits, increased blood pressure and pulse rate and increased risk of infection (Mudge et al., 2016; Pedersen et al., 2013; Convertino et al., 1997).
Various studies show that so-called healthcare wearables devices (HWDs) offer the possibility of recording movement and behaviour analyses as well as psychological and physiological parameters (Fudickar et al., 2014; Hellmers et al., 2018; Friedrich et al., 2019; Iqbal et al., 2021). Digitalisation and the use of wearables are creating more and more complex data and challenges, particularly with regard to healthcare management (Näher et al., 2023). The digital transformation in the healthcare sector goes beyond the mere digitalisation of existing processes and leads to far-reaching, sometimes disruptive changes in the entire care structure. This implies change at various levels, from which different fields of action can be derived. As a result, the people responsible should have the necessary expertise in these areas. Sustainable management of healthcare data generally requires close interprofessional collaboration (Auermann & Hoffmann, 2024).
Accordingly, the following section focuses in particular on recording activity data using wearables in the clinical setting. This raises the question of which additional competences are required and which specialist personnel need to be involved in the integration of activity sensors. It is essential to identify these and to train selected healthcare professionals in order to ensure that the activity sensors and activity data are handled correctly.
One triggering factor that can lead to HAD is a lack of exercise. Lack of exercise among hospitalised patients is a common problem that often causes complications and impairs recovery. As general fitness and activity are not the responsibility of a specific professional, physical fitness and activity are not systematically recorded and patients are usually not encouraged to undertake the necessary activity. The prevalence of inactivity and its negative impact on the recovery process emphasises the urgency of promoting and monitoring physical activity during hospitalisation. The preliminary findings from the observation of the movement behaviour of patients in the USB, in which an average of 88.4% of the time was spent lying down or sitting, confirm the need for such an approach.
Methods and procedures in the project
We provide the basis for this in sub-project B.2 "Hospital in Motion". Following successful validation of the sensors for detecting various movements such as lying down, sitting/standing, walking and climbing stairs, the aim of the follow-up study is to define the processes that need to be adopted by the medical service, physiotherapy and nursing when using the wearables in order to map the additional effort involved in process integration. To this end, the patients' activity data is recorded over a maximum of four days using an activity sensor (Movesense). Based on this data, an interdisciplinary meeting is held with the medical service, physiotherapy and nursing to clarify how the activity data can be integrated into everyday care, therapy planning and the daily routine of the medical service. In addition, daily feedback is obtained from the responsible HCPs - using a questionnaire on the additional time required due to the use of the activity sensors. The patient's HCP also has the task of checking the battery status and ongoing activity tracking via a special system (device hub). In addition, the responsible carer must check the position of the sensors on the patients in the morning.
Based on this, it can be said that the following tasks are required in addition to the normal care routine: such as handling the device hub of the sensors, categorising and using the activity data and handling the sensors. Furthermore, close collaboration with IT is essential to ensure trouble-free activity tracking.
Results and findings
To summarise, it makes sense for selected healthcare professionals to acquire additional skills to ensure the integration of activity sensors into everyday hospital life. These competences can be categorised as follows:
- Technological competence: It is important to develop a sound understanding of how wearables work in order to be able to use them effectively in everyday clinical practice. This includes the safe handling of the system (device hub), which is used to manage and check the collected activity data. It is also essential to regularly check the battery status of the sensors, continuously monitor activity tracking and ensure that the data can be smoothly integrated into the clinical workflow.
- Digital health literacy: An important skill is to integrate the data obtained, such as the number of steps, number of stairs or time spent lying down, into everyday clinical practice. It is highly relevant to know and categorise this information, taking into account the patient's medical history and course of illness, and to incorporate this information into care planning.
- Counselling and training: A certain level of expertise in promoting physical activity is an advantage when it comes to explaining the benefits of wearables to patients and training them in their use in order to promote self-management.
Recommendations for practice
- Training of healthcare professionals: In order to make the integration of activity sensors as effective as possible, it makes sense to train selected healthcare professionals in this regard.
- Developing a routine: It makes sense to develop a clear routine for integrating activity sensors into the daily care of patients.
- Patient training: Patients should receive specific training on how to use the wearables so that they understand what the data means and how they can use the data to improve their health.
- Supplement with a tool for patients: In order to make wearing the sensors more attractive and clearer for patients, it makes sense to develop a tool that displays individual activity data and activity goals. A suitable tool for this would be, for example, a user-friendly app that visualises the patient's individual activity data and progress towards their defined activity goals and presents them in an easily understandable way.
Literature and other sources
Aufermann, D., Hoffmann, F. (2024). New roles and job profiles in hospitals - from Chief Information Officer to Health Data Officer. In: Henke, V., Hülsken, G., Schneider, H., Varghese, J. (eds) Health Data Management. Springer Gabler, Wiesbaden. https://doi.org/10.1007/978-3-658-43236-2_17
Convertino, V. A., Bloomfield, S. A. & Greenleaf, J. E. An overview of the issues: physiological effects of bed rest and restricted physical activity. Med. Sci. Sports Exerc. 29, 187-190 (1997).
Friedrich, B., et al. (2019). Transportation mode classification from smartphone sensors via a long-short-term-memory network. In Adjunct proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and proceedings of the 2019 ACM International Symposium on Wearable Computers. ACM. https://doi.org/10.1145/3341162.3344855
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Hellmers, S., et al. (2018). Stair climb power measurements via inertial m
Iqbal, S. M., et al. (2021). Advances in healthcare wearable devices. npj Flexible Electronics, 5, 9. doi.org/10.1038/s41528-021-00107-x
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Mudge, A. M. et al. Poor mobility in hospitalised adults of all ages. J. Hosp. Med. 11, 289-291 (2016).
Näher, A. F., Vorisek, C. N., Klopfenstein, S. A., Lehne, M., Thun, S., Alsalamah, S., & Grabenhenrich, L. (2023). Secondary data for global health digitalisation. The Lancet Digital Health, 5(2), e93-e101.
Pedersen, M. M. et al. Twenty-Four-Hour Mobility During Acute Hospitalisation in Older Medical Patients. Journals Gerontol. Ser. A 68, 331-337 (2013).