Nurses’ Perceptions of the Application of the Internet of Things in Healthcare Services in Indonesia: A Mixed Methods Study

Citation: Lindayani, L., Taryudi, & Darmawati, I. (2021). Nurses’ perceptions of the application of the internet of things in healthcare services in Indonesia: A mixed methods study. Online Journal of Nursing Informatics (OJNI), 25(2), https://www.himss.org/resources/online-journal-nursing-informatics

Abstract

The aim of this study was to explore nurse perceptions about Internet of Things (IoT) applications. This study was conducted using a mixed-methods sequential explanatory design at a secondary hospital, located in West Java, Indonesia. The sample was composed of nurses with minimum educational backgrounds of Diploma III who had worked for at least one year.

A cross-sectional study design was conducted with 120 participants, followed by qualitative content analysis. Most of the participants were female (77.5%); ages ranged from 27 to 53 years, and the majority held a diploma degree.

The vital sign measuring device interface system was the highest priority demand of IoT applications, with a score of 6.89 points on average, followed by the pressure ulcer monitoring and management system (6.79), and the fall prediction and alarm system (6.19).

The qualitative findings revealed the motivations and challenges, as perceived by nurses, for using IoT applications in clinical practice. This reinforces the potential IoT advances developed in various fields such as improving patient safety and reducing errors. Future research could assess IoT demand in multiple hospitals, incorporating feedback from clients and all healthcare personnel including doctors.

Introduction

The Internet of Things (IoT) connects objects to the Internet and collects data as a means for improving the user experience (Mieronkoski, et al., 2017). IoT is an innovative network of distinct "things" that link to service hosts to enable efficient services (Lampropoulos, et al., 2019). There are many technologies that have proven to be useful within the IoT paradigm. For example, radio frequency identification (RFID) and Bluetooth modules have been used and embedded in various objects, such as vehicles, air conditioning units and lighting systems, and share information within a network (Gubbi, et al., 2013). In 2016, Ray projected that 25 billion "things" would be connected to the internet by 2020. This connection would enhance the amount of collected data, and information extracted from these data would be used to handle and make appropriate decisions independently (Ray, 2016).

There is a continuous increase in IoT applications in healthcare, and numerous studies have taken place (Dimitrov, 2016; Kato, et al., 2020; Ramirez, et al., 2016; Risso, et al., 2016; Sun, et al., 2016; Yang, et al., 2014). The main feature of IoT technology is the recording, monitoring and fast responses of medical information in patients despite their place and time via real information assessment (Xu, et al., 2018). A rapid response and call for help is possible by raising an alarm and phone for the medical staff or guardian if an emergency situation arises (Yang, et al., 2014; Vincent, et al., 2018). In daily life, walking characteristics recorded with a wearable device could be used to estimate a risk of falls (Benson, et al., 2018; Forbes, et al., 2020). Patient positioning, movement and risk of ulcers can be monitored by sensors installed in a bed (Minteer, et al., 2020). However, in health care facilities, the problems of IoT applications are continuing to increase due to efficiency, quality of study in previous clinical trials, and healthcare cost issues. There is little research available addressing the perceptions of hospital users about the use of IoT in their routine services, especially among nurses in Indonesia. The aim of this study was to explore nurse perceptions about IoT applications by conducting a survey and focused group discussion to explore thoughts and perceptions about IoT applications.

Methods

Study design

This research used a mixed-methods sequential explanatory design that entailed gathering and analyzing quantitative and qualitative data in two stages with one sample. Secondarily, qualitative data were gathered and analyzed to further clarify or build on the quantitative analysis conducted in the first process. The rationale for this approach was that quantitative data and major findings could provide broad insight into the problem. By delving deeper into the viewpoints of the participants, the qualitative evidence and interpretation could strengthen and confirm the quantitative measurements (Ivankova, et al., 2006). A mixed methods approach is a research paradigm that encourages the combined use of qualitative and quantitative data to answer complex questions, and has recently gained tremendous popularity (Younas, et al., 2019). This is a two-phased, mixed-method study that used a cross-sectional design coupled with a qualitative phase that included focus group discussion data.

Sample

This study was conducted at a secondary hospital located in West Java, Indonesia with more than 1,300 beds. The purposive sample included nurses with a minimum educational background of Diploma III who have worked for at least one year. From 350 nurses, 120 of the nurses in three departments (medical surgical, paediatrics and maternity) agreed to participate in this study. Mixed-methods sampling was used to include a sequential model of identical samples since the same 120 people took part in both the qualitative and quantitative phases.

Instrument

Quantitative instrument

An online survey using an instrument developed by Kang et al., (2019) focused on hospital IoT service demand, was used in this study. This instrument was used to identify the demand for IoT applications from a nursing perspective. Fifteen health services items, including patient safety, work performance and hospital ecosystems, were selected from expert discussions. However, many other IoT devices have not been fully used in real-world hospitals or are undergoing research and development. Among the selected product items, only the real-time patient position monitoring system was applicable in a specific region; thus, we excluded it from the items in the instrument.

To confirm the need for each IoT applications item, respondents were asked to select and label their preferences using a seven-point Likert scale, with responses of "very unnecessary" for one point and "very important" for seven points. A "do not know" response was introduced to reduce the bias of the results, given the risk that respondents might misinterpret the assessment by randomly selecting an answer whenever there is a product item that is difficult to understand in the text. This instrument has been translated into Bahasa following procedure sequences, according to the translation and cultural adaptation process of using questionnaires from different countries (Wild, et al., 2005).

The Content Validity Index (CVI) was used to determine the translated questionnaire's content (Wood and Ross-Kerr, 2010). Five specialists, three individuals specializing in education, and two nurses were invited to validate the content. The reliability of the questionnaire was measured with Cronbach alpha (patient safety: 0.70, work efficiency: 0.78, and medical environment: 0.81).

Focus group interview guide

Topics for discussion with nurses were related to three main question areas: (1) the experiences of nurses with IoT-related use, (2) the feelings and responsibilities of nurses with IoT-related problems (including difficulties and problems), and (3) the further activities of nurses in their roles of IoT therapists. The researchers created the question guidelines with the help of supervisors who were knowledgeable about both qualitative research and information technology. The experience of nurses using IoT was the subject of the guidelines for questions regarding qualitative results. Key questions were as follows:

1. Have you used any certain IoT platforms, such as applications or autonomous devices?
2. Please give an example of the type of IoT you used?
3. What feelings or impacts do you have when you use IoT?
4. How do you implement or use IoT?
5. How do nurses use IoT to help patients?

Data Collection

The research was approved by the Institutional Review Board of the affiliated institution. The survey was carried out by distributing the online survey to the nursing department. To protect the privacy of survey respondents, a standardized framework was used to inform survey respondents about the study's privacy procedures. The online survey (via an applications platform) was sent to each facility administrator, who was required to submit it to the nursing staff.

Google forms were used to gather confidential information during the entire procedure by limiting access of people to see the responses. Information was stored on a drive that only the research team could access. Access to the data was provided if the research team requested, and the request was granted by the principal investigator.

The software automatically addressed the possibility of double participants by preventing two or more access permissions from the same e-mail address to the survey if the questionnaire had already been completed. The survey only took a few minutes to complete, and no incentive was given to the participants.

Data were collected between June and August 2020. The data collection method used in this study included two stages. First, the respondents filled out closed-ended questionnaires to explore perceptions of IoT implementation. A focus group discussion using a formal interview outline was then conducted with nurses to obtain a qualitative assessment of their opinions and experiences on the use of IoT in clinical practice.

The focus group discussion among nurses was divided into four groups, with each group comprised of 10 participants. Each group was attended by nurses with different educational backgrounds to explore more deeply their perceptions of IoT. The focus group session was carried out and recorded using a video conference application.

Data Analysis

The characteristics of the study respondents and nurse perception of IoT applications were analysed using descriptive statistics. Qualitative data analysis was carried out using the seven steps of Colaizzi's method (Venkatesh, et al., 2013), as follows: (1) read and reread each participant's answer to generate their feelings or perspective, (2) extract relevant statements for the purpose of collecting insights directly related to research in the field of phenomena, 3) construct an interpretation of each argument in the scientific language, 4) categorize the responses into a theme cluster and check with the original sentence, 5) integrate all results into a full description of the desired phenomenon, 6) ask the participants to re-assess the text, and 7) update based on feedback from the participants.

Several methods were used to ensure integrity and reliability. Credibility was achieved through in-depth interviews and group debriefing. Reliability was achieved through an independent transcription analysis by three co-authors using the seven steps of Colaizzi's data analysis method, and the team then compared the results and explored them before agreement was reached on the codes, categories, sub-themes and themes. Transferability was achieved by providing information on the context and setting of the study, sampling and sample size; demographic characteristics of study participants including inclusion and exclusion criteria; and the interview procedure and topics.

Results

Quantitative findings

Most of the participants were female (77.5%). In terms of ethnicity, the participants included Sundanese (80%), Javanese (12.5%) and other (7.5 %). The ages ranged from 27 to 53 years, and the majority held a diploma degree. About 34.2% of participants had work experience between 11 and 15 years, and many of them worked in a chronic ward (32.5%). Table 1 presents the socio-demographic characteristics of the participants.

Table 1: Socio-demographic characteristics of Nurses (n=120)

Table 2 shows the priority of demand of IoT applications from the nurses’ perspective. A vital sign measuring device interface system was the highest priority demand of IoT applications, with a score of 6.89 points on average, followed by a pressure ulcer monitoring and management system (6.79), and a fall prediction and alarm system (6.19). A medical staff location tracking system (5.01) showed a relatively lower demand.

Table 2:  Demand on IoT applications from the nurses’ perspective (n=120)

Qualitative findings

The qualitative results of the study were gained through focus group discussions conducted with the same nurses working at secondary hospitals in West Java, Indonesia. During these discussions, some participants tended to be more expressive and some participants were rather quiet. Consequently, the quotes used under each theme were extracted from the significant responses of a specific participant rather than by consensus (Pawi, et al., 2012). The qualitative findings revealed the motivations and challenges perceived by nurses related to using IoT applications in clinical practice.

Motivation

Participants indicated that their main motivation for using an IoT applications was for their own personal use and to take care of and monitor patient conditions. Applications such as blood pressure monitoring devices or other health information apps were used because they were easy to monitor their patients’ health status and give updated information. They also thought of using a smartwatch to monitor a patient's condition. For personal use, many of them also used a smartphone app to track their menstrual cycles. However, many of the nurses did not use electronic medical records and did not use any advanced technology in their practice. For example:

“I love to use BP check from a mobile phone because it is easy and interesting for monitoring patient conditions” (p.3)

“Hmmm...I downloaded because I would like to know updated information about my patients ...” (p.5)

“…For my personal use, I use fertility applications, so we can track our fertility periods because I am planning for pregnancy.” (p.15)

“…no... I don’t use, we use paper based-documentation.”

Challenges

Participants’ engagement and perception of IoT applications were influenced by their apparent capabilities. Participants believed they had limited competence, but they recognized that the chance to voice their opinions provided opportunities for personal development. Participants who were less capable of IoT device use revealed their lower level of understanding of IoT features in distinct ways, such as how to turn off their device notifications. As a result, they were more likely to be distracted and annoyed by common features and the amount of perceived trivial communication. This also increased the amount of time they spent on IoT devices to achieve what they wanted. In most cases, users with less capacity could not differentiate between platforms. For example:

“I just don’t know how to do, may be need to be trained first…” (p.34)

“Yes…hmm…. I think it’s good, but we need to upgrade our skill on operating all advanced device…” (p.12)

Participants who were competent were more likely to disclose a deeper understanding of IoT applications functionality through their simple navigation of content with minimal distractions. They also described their communication by using multiple features confidently, as indicated below:

            “I prefer to use the ‘iCareMonitoring’ application to monitor my patient’s condition remotely and get engaged with patients through this app” (p.10)

            “sometimes, patients call me by just pressing a button in the applications and I will know what their problem is quickly…” (p.9)

Another challenge in using IoT for nurses in Indonesia was that many of the apps were not available in Indonesia's native language of Bahasa Indonesia. Some participants were aware of their less proficient level in using IoT applications and discussed how their age had limited their use of IoT applications. As quoted below:

            “some technology or apps were in English, so we cannot use it…”
            “I am too old to learn about technology or IoT, it seems to need effort.”

Discussion

This mixed-method analysis provides information on the demand for development of IoT applications and the perception of nurses to make use of it. To our knowledge, this is the first research to clarify the views of nurses on the use of IoT in Indonesia and the scope for use in their health care practices. Current research reveals a high demand for IoT health care services such as heart rate monitoring systems, fall prediction and alarm systems, pressure ulcer monitoring and management systems.

Many nurses need to use IoT for monitoring purposes, including vital signs, pressure ulcers, and detecting the risk for falls. Essential nursing management issues are directly related to patient safety. Many studies are being conducted to address this issue. For example, pressure ulcer control methods have been designed in the context of a system to measure the intensity of consistent pressure on the overall body of the patient. This innovative design enables the patient to maintain enhanced safety by automatically adjusting the patient's position according to the current risk of a pressure ulcer. Another application such as iStoppFalls, an information and communication technology (ICT)-based fall prevention activity guide, has the benefit of treating patients right after they are discharged from the hospital. The prediction system, developed using IoT technology, would therefore play a key role in the prevention of pressure ulcer and fall risk.

The nurses tended to be motivated by a mix of individual motivation and complexity in the IoT implementation. There are some considerations that need to be included in the implementation of IoT in clinical practices, namely simple use, engagement, language and the nurse’s ability to use IoT devices. Respondents expressed a strong desire for a private app and used several devices. As IoT users gain proficiency, they may also become eligible to participate in support groups on the social media platforms they use. Various basic requirements for IoT deployment have been established, including appropriate skill sets and motives (Zarei, et al., 2016). These basic requirements were shown in varying degrees by all respondents in the current study. It seemed that combining their willingness to use the IoT applications to benefit their current experiences and their ability to use it influenced the perceptions and attitudes of the respondents towards IoT. Similarly, barriers such as an inability, lack of motivation, and a pessimistic attitude are more likely to prevent older nurses from using the applications (Uckelmann, et al., 2011).

The biggest limitation of this study is generalizability. The findings are not representative of the views of nurses all around the world as it focuses on one hospital in Indonesia. Moreover, since only nurses were interviewed and surveyed, the findings cannot be described as insights into the implementation of IoT for the entire healthcare system. Therefore, an IoT demand survey should be carried out in multiple hospitals, incorporating feedback from patients and all medical personnel including doctors.

In addition, this research did not assess which IoT applications were always in use or not in use in different contexts. However, the results of this study are significant in evaluating the need for IoT services in healthcare facilities, based on the highest level of perspective and expertise in emerging technologies.

Implication for nursing practice

During a hospital stay, monitoring vital signs is one of the most fundamental tasks performed by nurses routinely. This is largely the responsibility of nurses, who are expected to monitor vital signs every hour or more, depending on the patient's condition. Currently, most medical facilities record vital signs manually and errors may occur during this process such as data loss or input mistakes. Therefore, integration of IoT technology into vital sign measurement and monitoring can provide a stable service that reduces workload and improves efficiency by allowing quick responses to patient health changes. Another implication was in the treatment of pressure ulcers, during which nurses would constantly assist patients in moving and manually track pressure ulcers signs. This IoT technology may assist nurses by means of actuators to ensure improved patient safety automatically by using specific algorithms to correct patient posture if the risk of pressure ulcers is high.

Conclusion

This study explored the perception of nurses in clinical practice towards the Internet of Things, including demand, motivation and challenge. This supports potential IoT advances developed in various fields, such as improving patient safety and reducing errors. However, if IoT services are to be successfully implemented in a healthcare facility, the issues of big data processing and constant process data processing from advanced technologies should be explored. Data analytics combined with user research to better incorporate and refine different prediction models into healthcare workflows should be considered in future research.