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Continued use of Key drivers for the continued use RFID technology of RFID technology in the emergency room Charlie C. Chen
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Department of Computer Information Systems, Appalachian State University, North Carolina, USA
Jiinpo Wu and Yu Sheng Su Department of Information and Management, Tamkang University, Tamsui, Taiwan, Republic of China, and
Samuel C. Yang Department of Information Systems and Decision Sciences, California State University, Fullerton, California, USA Abstract Purpose – More hospitals and caregivers are realizing the importance of radiofrequency identification (RFID) technology in the face of increased healthcare costs, medical errors, and pressure of governmental mandates. The necessity for and awareness of RFID has yet to drive its widespread adoption in the healthcare industry. As such, this study aims to examine key factors that contribute to the intention to continue using RFID. Design/methodology/approach – The paper adopts the expectation-confirmation model (ECM) to study the intention of caregivers to continue using RFID as a vehicle to deliver emergency medical services. It is theorized that perceived usefulness of front-end interoperability and backend interoperability along with performance expectancy contribute to confirmation experience, which in turn leads to satisfaction and ultimately to intention to continue to use RFID. The study surveys caregivers and staffs in the emergency room department of five hospitals in Taiwan. Findings – Perceived usefulness of front-end interoperability and performance expectancy both have significant relationships with confirmation experience; confirmation experience has a significant relationship with satisfaction, which in turn relates to intention to continue using RFID. The relationship between perceived usefulness of back-end interoperability and confirmation experience is not significant. Research limitations/implications – This study explains RFID adoption behavior using the ECM. Limitations of the study and possible future research direction are discussed. Practical implications – The results of this study should help hospital management to build commitment to the RFID system and help equipment vendors to build loyalty to the technology. Originality/value – This study represents a novel attempt to explain RFID adoption behavior using the ECM. It is expected that the proposed framework and empirical findings can contribute to further understanding of how RFID is adopted and used in a hospital environment. Keywords Health services, Identification, Radiofrequencies, Customer satisfaction, Behaviour Paper type Research paper
Introduction After years of continuing growth, the market of radiofrequency identification (RFID) software and services began showing weakening signs. ABI Research forecasted that 2007 revenue in RFID software and services would decrease to $3.1 billion, which is about 15 per cent downward adjustment from 2006 (Wireless News, 2006). Many industry-level factors have contributed to the weaker RFID market, specifically in the areas of asset management and supply chain management. These factors include
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consolidating markets, growing availability of off-the-shelf RFID packages, and improving levels of skills in RFID project planning (Wireless News, 2006). At the same time in the healthcare industry, the demand for RFID technology has not been strong despite RFID’s many benefits, such as improved tracking of assets, drugs, and patients and reduced number of medical errors (BearingPoint, 2006). To accelerate the adoption of RFID technology in healthcare, hospital management and equipment vendors may now need to pay special attention to individual-level factors, such as training, positive perception of RFID by frontline caregivers, and user-friendly interfaces. Along with the growing scope of RFID applications and reduced system costs, an important question to examine is whether or not individual-level factors are important to the widespread adoption of RFID by caregivers. It has been asserted that improving users’ experience with an information technology can enhance their satisfaction with an intention to continue using the technology (i.e. continuance intention) (Bhattacherjee, 2001). From the perspective of the expectation-confirmation model (ECM) theory, users’ prior experience with a product or service can significantly influence their intention to repurchase it (Anderson and Sullivan, 1993). One primary objective of this study is to explore how one can improve the satisfaction of caregivers with and their intention to continue using RFID in the hospital environment, specifically in the emergency room (ER). The quality of front- and back-end interoperability can potentially affect caregiver’s perception of usefulness. In terms of the performance expectancy factor, we are particularly interested in examining caregiver’s perception of the relative advantages of RFID over barcode. We are also interested in the path dependency of creating a positive confirmation experience, a higher satisfaction level, and ultimately a higher intention of continuing to use RFID in the ER. As such, this study examines literature on the ECM and its applicability to the adoption of RFID technology in the ER. Five hypotheses are proposed to investigate the relationships between different constructs. Data are collected from caregivers in ERs of five hospitals to test the relationships, and statistical analysis of the data is performed to derive findings. Based on the results, this research concludes with a discussion of its limitations and implications. Benefits of RFID In a hospital setting, the appropriate application of RFID technologies can reduce many manual operations performed in patient care. When applied to existing workflows, RFID can reduce the number of manual steps involved in patient care. RFID systems can automate the admitting, screening and treating processes for patients, enhance communications between caregivers and support teams, and reduce medical errors (Wicks et al., 2006). In addition, some hospitals have initiated use of RFID tags on wristbands which store data and can be scanned with a reader to identify a patient and what surgical procedure is needed (Hancox, 2006; Cangialosi et al., 2007). When RFID is integrated into the hospital information system, a patient can be tracked from the time they enter the hospital to the time they leave. This process starts when a patient is admitted and issued an RFID wristband. Once tagged, the patient can be monitored as they enter and exit different areas. As care is provided to the patient, handheld readers and terminals with wireless capabilities may be used to input information about procedures performed. For example, during examination ER staff scans the patient wristband and all materials used in the care of the patient. This way, medicines and consumables would be associated with a patient and recorded automatically. The collected data enable other medical staff in the next shift to review
what was administered to treat the patient. By automating these systems, harmful drug interactions can be identified immediately and notification sent to the physicians (Cangialosi et al., 2007). Conceptual foundation Perceived usefulness of RFID Perceived usefulness is one of the salient predictors for information technology adoption (Davis, 1989). A higher perceived usefulness of RFID can lead to an increased customer demand for RFID implementation (Palmieri, 2006) and a positive confirmation experience (Bhattacherjee, 2001). This research thus posits that there is a positive relationship between perceived usefulness and confirmation experience. At the same time, this study separates perceived usefulness into two components – key drivers for perceived usefulness of RFID technology include its front- and back-end interoperability. The incompatibility between readers and tags is a front-end issue to users. RFID readers and tags vary in their read consistency at different granularity levels and for different types of objects. The difference in existing RFID standards has limited scalability and application scopes; as such, suppliers, manufacturers, and buyers in the supply chain often use dissimilar systems. On the other hand, the incompatibility between information provided by RFID readers and information stored in existing databases across supply chains is a back-end issue. Systems interoperability (e.g. data synchronization) among business partners is a significant and complex configuration process. Resolving the front- and back-end interoperability issues can help improve the perceived usefulness of users, and many in the industry are working to address these issues. For example, the primary purpose of the partnership between SAP and Intel is to address the interoperability issues resulting from the integration of RFID hardware, back-end systems, and business processes (Saran, 2006). Front-end interoperability. Front-end interoperability is the operational compatibility between RFID readers and tags. RFID tags can generally be classified into three types: passive, semi-passive, and active. An active tag is equipped with a battery and can use its own power to communicate with the reader. A passive tag draws power from the electromagnetic field or magnetic field created by the reader and uses it to power the tag’s circuits and for exchanging data. A semi-passive tag has the functions of both active and passive tags. The use of different tags varies with the scope of applications. Active RFID tags are reusable but more expensive; they are often used in a fixed geographical location. In contrast, passive RFID tags are cheaper and disposable, often adopted in a mobile scenario (Hoffmann, 2006). In addition, different types of tags can operate at different frequencies that range from 125 kHz to 960 MHz. For example, tags operating at frequencies of 125-134 kHz and 13.65 MHz can communicate over distances of up to 2 m, while tags operating at frequencies of 860-960 MHz can communicate over distances of up to 8 m. Typically, the higher the frequency used to communicate, the higher the data throughput. This capability characteristic is because the tag detection process (e.g. collision arbitration) is significantly more efficient in ultra-high frequency (UHF) systems than in highfrequency systems. A reader designed to transmit and receive at a specific range of frequency cannot transmit and receive signals at a different frequency range. The lack of industry-wide standards (e.g. e-pedigree standards) across different frequency ranges has slowed the wide adoption of RFID in the healthcare industry (Koroneos, 2006). Differences in frequencies, coupling modes, communication and power sources
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contribute to data incompatibility issues (Scharfeld, 2001), and these issues due to RFID’s front-end incompatibility raise the level of business challenges. Furthermore, object sizes and types (capsules, liquid, powder, tablet, medical equipment, and patients) vary greatly in the healthcare industry. The nature of objects to be read can pose a significant challenge to front-end compatibility, especially with older RFID technologies. Lack of front-end compatibility can cause radio interference and create difficulty in using the system. The latest generation of UHF tags is based on the global standard EPCglobal Gen2 that enables tags to operate under different conditions. Nevertheless, it is important to mitigate the issues of front-end interoperability and create a positive confirmation experience for users. H1.
Caregivers are more likely to have a positive confirmation experience if they perceive a greater usefulness of front-end interoperability of RFID technology.
Back-end interoperability. Back-end interoperability is the compatibility between data provided by RFID readers and applications and databases across the organization and the supply chain. RFID can generate at least ten times the amount of data generated by barcodes. It is crucial to build a secure and reliable network ecosystem to process the data collected by readers and move it across partner companies in an integrated supply chain (Chopra and Meindl, 2006). However, processing such a large amount of data on a real-time basis to support business decisions across organizational boundaries is a significant challenge. Yet, in today’s fast-changing business environment, nearinstantaneous processing and delivery of information are required. In addition, many early adopters have used the ‘‘slap-and-ship’’ approach to implement RFID by simply tagging objects, installing readers, antennas, and software without making the corresponding change in business processes. The mere installation of these RFID components by themselves cannot achieve long-lasting benefits (Ranch, 2006). Middleware has emerged as a type of application that not only makes the enterprisewide integration a possibility, but also is indispensable for the success of business process redesign and change. Well-designed RFID middleware include at least four basic functions: reader and device management, data management, application integration, and partner integration (Sweeney, 2005), and these functions can be organized into three layers of applications that contribute to greater back-end interoperability: collection layer, integration layer, and enterprise layer (see Figure 1). The collection layer gathers the raw data provided RFID readers and filters and cleanses the data before passing it to the applications. RFID tags emit different signals at different frequencies at various locations; these signals are read by RFID readers. Data collected by different RFID readers have different formats because data are encoded differently with respect to syntax and semantics. In addition, working environmental factors, such as noise, temperature, and distance, can distort or attenuate signals emitted by the tags. Numerous data-encoding techniques (e.g. nonreturn to zero, Manchester) need to be in place to encode the bits of data, and a wide variety of modulation approaches (i.e. amplitude, frequency, and phase shift keying) are available to represent data. Middleware in the collection layer not only administers the configuration management of this ensemble of readers but also cleanses the collected data and performs the first round of data reduction, local data aggregation, and preprocessing before passing data to downstream applications for further processing.
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Figure 1. RFID system architecture
The integration layer mediates the information flow between an organization’s applications and databases. It is likely that more than one application will receive and process data collected by RFID readers, and these applications will produce information in different formats. Information in different formats needs to be standardized and integrated before they can be fed into back-end databases and data warehouses. The task of the integration layer is to perform such a conversion before information is permanently archived. Companies like IBM, Hewlett-Packard, and Sun’s OATSystems Inc. are vendors that provide the integration solution. The enterprise layer mediates the information flow between different organizations. Companies across a supply chain adopt various systems at different managerial levels (e.g. decision support systems, expert systems, executive information systems, data warehouse systems, and group support systems) to process data in numerous ways to support their business operations. Data integration is a challenge when disparate information systems of business partners are incompatible with each other. This situation necessitates the inter-cooperation of business partners through a system integration life cycle, including adoption decision, acquisition, implementation, use and maintenance, evolution and retirement phases (Esteves and Pastor, 1999). It is often difficult to elicit such a high degree of cooperation from business partners. Other managerial factors, such as the degree of trust, shared common vision, the degree of convincing and compulsory power, and business practices in different countries can also contribute to the success of back-end integration of RFID. When partners desire to integrate their information systems across organizational boundaries, they rely on middleware operating in the enterprise layer that standardizes information exchanged among partners. Frontline caregivers may be concerned with back-end interoperability of an RFID system because they too require timely information captured by RFID readers, stored in back-end databases, and transmitted from outside organizations. Such up-to-date information, enabled by back-end interoperability and sharing of data among multiple
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systems, can help them provide better care for patients. Lack of back-end interoperability can result in islands of information and poor decision-making process. As a result, business process transformation through RFID cannot be achieved. It is important to mitigate the back-end interoperability issues and create positive confirmation experience. H2.
Caregivers are more likely to have a positive confirmation experience if they perceive a greater usefulness of back-end interoperability of RFID technology.
Performance expectancy: relative advantages of RFID over barcode Performance expectancy is the belief of users to accomplish job tasks (Venkatesh et al., 2003). The literature has shown that the higher the gap between the customer’s prior feelings about a product and actual usage experience of that product, the higher the satisfaction level users have (Oliver, 1981). On the other hand, confirmation is inversely related to expectation and directly related to perceived performance. Adopting RFID technology is a challenge to many caregivers because RFID is not a core and ‘‘mustuse’’ technology in the hospital. The existing barcode has performed most functions well to support the delivery of medical services. At the same time, caregivers and RFID solution providers are still concerned about the limitation of RFID as used in the healthcare industry. Hospitals have been known to experience many systemic problems, including overstretched staffs, insufficient coordination of limited resources, inefficiency of manually tracking location and care progression of patients, inefficiency of tracking location of medical equipment, disparities in response time, uncertain quality of care, lack of disaster readiness, and divided professional identity (Wicks et al., 2006). Exacerbated by these problems existing in hospitals, performance expectancy about the use of RFID technology in the hospital tends to be relatively low. H3.
Caregivers are more likely to have a positive confirmation experience if they have a low performance expectancy of using RFID technology.
Confirmation and satisfaction The customer behaviors literature shows that expectation-confirmation experience is an important predictor of customer satisfaction (Anderson and Sullivan, 1993) and repurchasing behaviors (Dabolkar et al., 2000; Swan and Trawick, 1981). Satisfaction is a psychological, positive emotion, or affective state resulting from the use of an information technology. Satisfaction is also a transient affective factor that intermediates the casual relationship between confirmation experience and customer loyalty (Anderson and Sullivan, 1993). The self-perception theory posits that users continually adjust their perceptions of the purchased products or services throughout their consumption behavior to achieve satisfactory status in varying occasions (Bem, 1972). From the perspective of adaptation level theory, subsequent actions (e.g. becoming loyal to the same products or different products with the same brands, or switching to a competitor’s products) take places after achieving a confirmed selfperception status (Helson, 1964). Caregiver’s confirmation with prior use of RFID technology can turn into positive or negative satisfactory experience. Caregivers with positive RFID confirmation experiences should have satisfactory usage experience. H4.
Caregivers are more likely to have a high satisfaction level if they have a positive confirmation experience of using RFID technology.
Satisfaction and intention Satisfaction is a salient independent variable for the intention of continued usage of various products and services, such as repurchase of automobile (Oliver, 1993), camcorder and photographic products (Dabolkar et al., 2000), restaurant service (Swan and Trawick, 1981), and business professional services (Patterson and Spreng, 1997). In the healthcare industry, two key drivers for RFID applications are the increased pressure to reduce rising healthcare costs and the mandate of the US Food and Drug Administration. However, the ultimate goals of RFID applications should go beyond cost savings and regulatory compliance by addressing operational effectiveness (e.g. minimizing medical errors) and patient satisfaction (Wicks et al., 2006). For instance, RFID technology has the potential of transforming the pharmaceutical supply chain into a ‘‘de facto electronic pedigree’’ or an open and a transparent value chain (Young, 2006). With an improved transparency in the pharmaceutical supply chain, counterfeit drugs can be eliminated to protect patients’ safety. The operational effectiveness can build up the trust of patients of the medical providers and result in higher satisfaction. Some hospitals are applying RFID technology to track patients and new-born babies for security and anti-abduction purposes. The technology is also used to track medical equipments, as well as to automate the medical administration process. Achieving operational effectiveness in these areas can improve the satisfaction of users, including physicians, nurses, staff, IS professionals, and pharmacists. Customer satisfaction is a precursor to customer loyalty (Chiou and Droge, 2006), which can be measured with the intention to continue using the products and services (continuance intention). Customer satisfaction differs from attitude in its transitory nature (Anderson and Sullivan, 1993). The formation of an affective attitude towards a product or service indicates a high level of customer loyalty. Caregivers’ loyalty to the use of RFID technology can be enhanced with its ability to improve their satisfaction. We posit that satisfaction can also lead to caregiver’s intention to continue using RFID. H5.
Caregivers are more likely to intend to continue using RFID if they have a high satisfaction level with using this technology.
The proposed theoretical framework is shown in Figure 2. We specify perceived usefulness and performance expectancy of RFID technology as precursors to caregiver’s confirmation experience. Moreover, a positive confirmation experience can enhance users’ satisfaction which can lead to a higher intention to continue using RFID. This study adopts the ECM to explore RFID in hospitals because the ultimate dependent variable (i.e. intention to continue using RFID) in the model is crucial to the increased adoption of RFID technology by healthcare workers. Methodology A survey was conducted with caregivers (physicians, nurses, and staff) and IS professionals who work in the ER and have experience using RFID in their work. The hospitals under study are located in Taiwan. An examination of secondary data showed that nine hospitals would implement RFID systems. An interview with the management of these hospitals allowed us to screen out four hospitals that did not deploy RFID systems as the secondary data claimed. The remaining five hospitals were actually implementing RFID systems, primarily in their ERs. The primary RFID applications used in ERs of the studied hospitals were: streamline the admission process for patients, mitigate potential errors in prescription process, match blood types and patient’s personal medical records, and locate patients and medical supplies.
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Figure 2. Conceptual model
Four of these five hospitals agreed to participate in this research project. We added another hospital that was planning to adopt RFID systems but was not included in the secondary data. The studied hospitals are labeled A, B, C, D, and E. A pilot test was conducted with healthcare industry experts to evaluate the appropriateness of semantics, wording and sentence of questionnaire in the context of RFID adoption. A full-scale survey was conducted after the questionnaire was modified based on the feedback on the pilot test. A total of 85 caregivers working in these five hospitals were randomly chosen and surveyed online or offline. Four samples were invalid and not included for further statistical analysis. Results Descriptive statistics Multivariate analysis method is adopted to assess the relationships between independent and dependent variables. Statistical software used to assist the analysis is SPSS for Windows 13.0. Twenty-nine subjects are males and 52 subjects are females. The sampled number of subjects are 3, 24, 15, 29, and 10 from Hospital A, B, C, D, and E, respectively. Fifty-five subjects are caregivers in the ERs, and 26 subjects are from the information system departments supporting the ERs. Seventy-three subjects are under age 40, and eight subjects are above age 40. Reliability and validity analysis Experts in the healthcare industry were invited to participate in the pilot test to assess the content quality of the questionnaire. The content validity of the questionnaire was further enhanced with Cronbach tests that assess the internal consistencies of the models used to measure the constructs of the proposed framework. Table I shows Cronbach values for the six theoretical constructs examined in this study. All Cronbach values except one exceeded the threshold value of 0.7 (Fornell and Larcker,
1981). This indicates that the adopted questionnaire has a relatively high internal reliability. Perceived usefulness in back-end compatibility has a Cronbach value of 0.525. This lower-than-expected value is addressed later in the Discussion section.
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Regression The linear regression analysis is adopted to determine the predictive power of independent variables for the respective dependent variables. Three statistical models are constructed for regression analysis. The first model is used to validate H1, H2, and H3. The second and third models are to validate H4 and H5, respectively.
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Confirmation experience of using RFID in ER ¼ Perceived usefulness in front-end compatibility þ Perceived usefulness in back-end compatibility þ Performance expectancy þ constant;
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Satisfaction with the actual use of RFID in ER ¼ Confirmation experience of using RFID in ER þ constant;
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Intention to continue to use RFID in ER ¼ Satisfaction with the actual use of RFID in ER þ constant.
Table II shows the direct effects of perceived usefulness and performance expectancy on the confirmation experience of using RFID in the ER to support the delivery of emergency medical services. These three independent variables together can explain 69.5 per cent (R2 value) of the variance in the confirmation experience of using RFID in the ER (F ¼ 58.411, p ¼ 0.00 < 0.01). Perceived usefulness in front-end compatibility ( ¼ 0.537, p ¼ 0.00 < 0.01) has a higher predictive power than performance expectancy ( ¼ 0.328, p ¼ 0.00 < 0.01) for the variance in the confirmation experience of caregivers. Perceived usefulness in back-end compatibility ( ¼ 0.083, p ¼ 0.191) does not have significant predictive power on the confirmation experience of caregivers in using RFID in the ER. We ran another regression analysis on the direct effect of confirmation experience on caregiver’s satisfaction with the actual use of RFID in the ER. The analysis result shows that the confirmation experience factor can explain 74.6 per cent of satisfaction with the actual use of RFID in the ER (F ¼ 231.774, p ¼ 0.00 < 0.01). The difference in caregiver’s satisfaction with the actual use of RFID in the ER is sensitive to the
Constructs Cronbach
Perceived usefulness: front-end
Perceived usefulness: back-end
0.718
0.525
Perceived usefulness: front-end Perceived usefulness: back-end Performance expectancy Notes: R2 ¼ 0.695; adjusted R2 ¼ 0.683
Performance expectancy 0.825
Confirmation 0.865
Satisfaction 0.845
Continuance intention 0.792
Beta
p-Value
0.537 0.083 0.328
0.000 0.191 0.004
Table I. Cronbach values of theoretical constructs
Table II. Regression analysis of dependent variable confirmation experience
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variations in confirmation experience ( ¼ 0.864). The relationship is positively correlated (p ¼ 0.00 < 0.01). It was also proposed that caregiver’s satisfaction with the actual use of RFID in the ER is positively associated with the intention to continue to use RFID. Another regression analysis confirms the existence of this relationship (p ¼ 0.00 < 0.01). The satisfaction factor can explain 46.7 per cent of the intention to continue using RFID in the ER. The difference in continuance intention is sensitive to the changes in satisfaction with the technology ( ¼ 0.684). Table III summarizes testing results of our proposed hypotheses. Four hypotheses (H1, H3, H4, and H5) are supported given the statistical evidence gathered. H2 is not supported. Academic and practical implications on these findings are discussed in the following section. Discussion This research project adopts ECM theory to investigate factors leading to the intention of caregivers to continue to use RFID in the ER. Given the slowed growth of the RFID market, it is imperative to know how to improve not only adoption by new users, but also continued use by past users. It is posited that caregiver’s perceived usefulness of the front- and back-end compatibility, as well as performance expectancy, can enhance the confirmation experience of users; a positive confirmation experience can result in the improvement of user satisfaction, and satisfactory experiences can augment the intention of caregivers to continue using RFID in the ER. Eighty-one caregivers and IS professionals participated in this research project via online and offline surveys. Empirical data collected in this study confirms the existence of four of five posited relationships. Perceived value of front-end interoperability has the highest predictive power ( ¼ 0.537) for the confirmation experience of caregivers and information systems (IS) professionals in using RFID technology in the ER. A good design of front-end interoperability (e.g. ease-of-use, clear and understandable interface, and flexible read procedure) is the most important precursor to caregiver’s confirmation experience. For example, work efficiency is greatly increased (e.g. in the supermarkets) when there is only one type of barcode tag that can be read by barcode readers. In a hospital, if the
Table III. Summary of hypotheses testing results
Hypotheses
Results
H1. Caregivers are more likely to have a positive confirmation experience if they perceive a greater usefulness of front-end interoperability of RFID technology H2. Caregivers are more likely to have a positive confirmation experience if they perceive a greater usefulness of back-end interoperability of RFID technology H3. Caregivers are more likely to have a positive confirmation experience if they have a low performance expectancy of using RFID technology H4. Caregivers are more likely to have a high satisfaction level if they have a positive confirmation experience of using RFID technology H5. Caregivers are more likely to have high intention to continue using RFID if they have high satisfaction level with using this technology
Supported Not supported Supported Supported Supported
RFID tag on a patient wristband is of a different type than the RFID tag on a drug bottle, two different types of readers are required. This heterogeneous set of readers may create confusion among frontline caregivers in the hospital. For this reason, the Massachusetts Institute of Technology AutoID Center, a primary FID standards body, is constantly improving its de facto standards of the application level events to ease the interfacing process of front-end interoperability (Borck, 2006). Vendors also recognize the importance of front-end interoperability. For instance, Zebra Technologies simplified the interoperability of multiple RFID smart labeling printers and encoders via XML connectivity (FinancialWire, 2006). The joint effort between SAP AG and Intel enables users to enter RFID data directly from desktops, notebooks, and RFID readers of different vendors (Hoffmann, 2006). The more such front-end attributes RFID systems have, the more likely caregivers will have a more positive confirmation experience. As the competition increases and the cost of RFID systems continues to decrease, users will increase their demand for front-end systems with high degrees of interoperability. Perceived value in the back-end interoperability is much less important than that in the front-end. Caregivers surveyed in this study did not treat back-end interoperability as a key driver of their confirmation experience. They did not treat time and efforts spent in configuring the RFID system to interoperate with back-end systems as an important issue to them. The results make sense because it is not the responsibility of frontline caregivers and staff to deal with back-end systems. Perceived usefulness of back-end interoperability is not a significant precursor to the confirmation experience of caregivers in the ER. It is also noted that back-end interoperability touches upon many business issues, such as business process reengineering, software integration, and database management. These issues are major concerns of technical and business executives and are beyond the sphere of control of caregivers and staff. To facilitate the decision-making process of top management to invest in RFID systems, many technical solution providers have been striving to adequately address the back-end interoperability issues. For instance, Symbol Inc., a manufacturer of RFID readers, rolled out RFID solutions based on the Windows CE operating system to support multi-platforms (Al Bawaba News, 2006). Some companies integrate RFID with wireless communication technologies to achieve cost savings, improve productivity and provide privacy-aware, highly dynamic and personalizing services (Sackmann et al., 2006). Performance expectancy is the second most important predictor ( Âź 0.328) of confirmation experience of caregivers in adopting RFID in the ER. Caregivers in this study have the view that RFID is more effective than barcode technology in many respects, such as tracking mobile medical equipment, in-patient and out-patient testing results, and patient drug-treatment compliance (Wicks et al., 2006). RFID systems continue to evolve to show their persistent relative advantages over barcode technology. Take the Intel case in point, this company introduced a clinical mobile assistant platform to streamline the clinical workflow and help reduce medication dispensing errors (FinancialWire, 2006). The stronger the belief in RFIDâ&#x20AC;&#x2122;s relative advantage over barcode, the more likely caregivers will have a positive confirmation experience. At the same time, it is important to note that while barcode systems have optical scanners that can be used in any hospital environment, the use of RFID systems in a hospital may be restricted depending on the proximity of other RF-sensitive equipment. This restriction in relation to the target work flow/process may affect the performance expectancy of RFID systems.
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The confirmation experience of actual use of RFID in the daily operation of ER can improve satisfaction of caregivers ( ¼ 0.864). Thus to improve the satisfaction of caregivers, it is important to create the positive confirmation experience. In addition, the data also show that satisfaction contributes to the intention to continue to use RFID ( ¼ 0.684). St. Elizabeth Medical Center first implemented an RFID system to prevent baby thefts in the maternity room. The hospital was very satisfied with the technology that it has since committed to upgrading and extending the use of RFID with patients with psychological or substance abuse problems in the ER (Gearon, 2005). This case and the data show that a higher satisfaction has a direct influence on the intention to continue using RFID. Establishing this relationship is imperative for customer retention in highly personal, service-oriented industries (e.g. hotels and restaurants). Our findings show that this relationship is equally important in the RFID adoption in the ER. Given the results of this study, to create a positive confirmation experience and ultimately to encourage caregivers to continue to use RFID, hospital administration and equipment vendors can target two factors: perceived value of front-end interoperability and performance expectancy of RFID’s advantages over barcode. In practice, front-end interoperability will largely depend on the actual system selected. Thus in an RFID implementation project, system selection is crucial. Given that RFID has not been widely adopted by hospitals (BearingPoint, 2006), it is likely that IS departments of hospitals do not have the requisite skillset to vet systems and make a knowledgeable choice consistent with their internal processes. In this case, hospitals may consider using system integrators and consultants who specialize in healthcare applications. Furthermore, in terms of performance expectancy of RFID’s advantages over barcode, management may consider giving training to caregivers and providing information on actual statistics of performance improvements in other hospitals after they implemented RFID. Such training and education efforts can help improve caregiver’s performance expectancy. Overall, to support the continued use of RFID, hospital management and equipment vendors should focus on improving both perceived usefulness of front-end interoperability and performance expectancy of RFID. These improvements should enhance the confirmation experience of caregivers, which leads to satisfaction and ultimately to intention to continue to use RFID. Limitations of the present research In terms of limitations, this study may not have considered other individual-level factors that can potentially moderate the hypothesized relationships. Two such factors are voluntariness of use and experience. Past literature shows that both factors can influence the intention of using an information technology and the actual behavior of using it (Venkatash et al., 2003). However, the effects of these two factors should be minimal in this study. Regarding voluntariness of use, caregivers and IS professionals complied with the mandatory requirements of their hospitals to deploy RFID technology in the ER, so there is little variance in voluntariness. Regarding experience of use, RFID is a novelty project to most participants; most users have little experience of using the technology, thus the effect of experience should not be salient. In addition, subjects participating in this study are homogeneous Taiwanese. Taiwan is a country endowed with masculinity and high uncertainty avoidance culture. From the anthropological and technological perspective, social norms, particularly in the society where masculinity and high uncertainty avoidance cultures are prevalent, are stronger determinant of behavioral intention of using new information technology than
experience (Srite and Karahanna, 2006). However, readers should be aware of these limitations when using the findings of this study. Another limitation of this study is the lower-than-expected Cronbach for perceived usefulness in back-end interoperability (0.525). Cronbach assesses the internal consistency of the model used to measure a construct. The adopted instrument measuring perceived usefulness in back-end interoperability is a validated instrument (Davis, 1989). The reason why the instrument produced a low may be because of the composition of the subject pool. The subjects consist of ER physicians, nurses, and staffs as well as IS professionals supporting systems in the ER. While IS professionals may understand the meaning of back-end systems, physicians, nurses, and staffs may not have fully understood the items used to assess perceived usefulness in back-end interoperability. The heterogeneity of the subjects may have caused the measurement consistency of this construct to be lower. It is important to recognize that this study is an investigation of the ER departments of participating hospitals. Thus the results of this study cannot be generalized to other departments of a hospital or other types of organizations. In addition, although this study did not demonstrate a relationship between back-end interoperability and confirmation experience, there may be other back-end technological issues (e.g. system costs) and technology-related factors that contribute to the dependent variables. Readers are advised of these limitations when interpreting the results of this study. Suggestions for future research Since it is difficult to obtain a large sample size of hospitals in this industry, future research may want to carry out a longitudinal study of a smaller number of hospitals. This approach would have the added advantage of investigating how the use of RFID can evolve and mature over time. An in-depth investigation using case studies is also an appropriate vehicle to achieve this purpose. The relative high internal validity is an advantage of this study because it confines the setting to just the ER department of the hospital. Future studies can extend the investigation to other departments in the hospital, such as surgery and pharmacy. Also, with a more controllable environment, researchers can manipulate those factors (e.g. experience and voluntariness of use) that were not examined by this study. In addition, the ECM theory originates from the marketing field. Other marketing studies theorize relationships between constructs of service value (Dodds and Monroe, 1985), service quality (DeLone and McLean, 1992), and sacrifice (Zeithaml, 1988), and the construct of behavioral intention. These studies confirm relationships between those constructs and behavioral intention and actual use of a product or service. Future research can further explore these other constructs in the context of RFID in hospitals. Moreover, this study examined RFIDâ&#x20AC;&#x2122;s relative advantage over barcode as part of the performance expectancy construct which positively contributes to confirmation. But there may be other factors that can negatively impact confirmation, such as radio interference with existing sensitive hospital equipment. Thus, a future modification of the conceptual framework can include both positive and negative factors in the performance expectancy construct. Conclusion An increased number of vendors, hospital administrators, and caregivers are advocating the relative advantages of RFID over barcode technology. However, the growth of RFID adoption seems to have slowed in the hospital environment. Many
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have attributed the slower growth to a culture of technology resistance, expensive system costs, and disparate standards. This research addresses the RFID adoption issues in the hospital from the expectation-confirmation perspective. As such, this study shows that ER caregivers who have a high perception of the usefulness in front-end interoperability and of performance expectancy affirm a positive confirmation experience with the use of RFID technology. However, perceived usefulness of back-end interoperability has little to do with a positive confirmation experience. Moreover, a positive confirmation experience leads to increased satisfaction with this technology. Consequently, the intention of caregivers to continue to use RFID in the ER can be improved. These results have both practical and research implications. For the practitioners, to encourage caregivers to continue to use RFID hospital administrators and equipment vendors can target those factors that have been shown to be significant. For example, they may attempt to increase the perceived frontend interoperability by using experienced consultants and integrators to implement systems that are proven to be interoperable at the front-end. They may also intervene via training and education to increase caregivers’ performance expectancy of RFID. For researchers, this research is confined to a single department in hospitals (i.e. ER). Future research can extend the investigation of the proposed model to other departments (e.g. surgery and pharmacy). It is expected that the results of this research can provide a foundation upon which subsequent work can be built. References Al Bawaba News (2006), ‘‘Symbol launches next generation RFID reader’’, Al Bawaba News, 31 July, p. 1. Anderson, E.W. and Sullivan, M.W. (1993), ‘‘The antecedents and consequences of customer satisfaction for firms’’, Marketing Science, Vol. 12 No. 5, pp. 125-43. BearingPoint (2006), RFID in Healthcare: Poised for Growth, BearingPoint, McLean, VA. Bem, D.J. (1972), Self-Perception Theory, Vol. 6, Academic Press, New York, NY. Bhattacherjee, A. (2001), ‘‘Understanding information systems continuance: an expectation confirmation model’’, MIS Quarterly, Vol. 25 No. 3, pp. 351-70. Borck, J.R. (2006), ‘‘Tuning in to RFID’’, InfoWorld, 17 April, pp. 31-5. Cangialosi, A., Monaly, J. and Yang, S.C. (2007), ‘‘Applying RFID to patient care: challenges and opportunities’’, Proceedings of the 2007 Information Resources Management Association (IRMA) International Conference, 19-23 May, Vancouver, British Columbia. Chiou, J. and Droge, C. (2006), ‘‘Service quality, trust, specific asset investment, and expertise: direct and indirect effects in a satisfaction-loyalty framework’’, Academy of Marketing Science Journal, Vol. 34 No. 4, pp. 613-27. Chopra, S. and Meindl, P. (2006), Supply Chain Management, Prentice Hall, Upper Saddle River, NJ. Dabolkar, P.A., Shepard, C.D. and Thorpe, D.I. (2000), ‘‘A comprehensive framework for service quality: an investigation of critical conceptual and measurement issues through a longitudinal study’’, Journal of Retailing, Vol. 76 No. 2, pp. 139-73. Davis, F.D. (1989), ‘‘Perceived usefulness, perceived ease of use, and user acceptance of information technology’’, MIS Quarterly, Vol. 13 No. 3, pp. 319-39. DeLone, W.H. and McLean, E.R. (1992), ‘‘Information system success: the quest for the dependent variable’’, Information System Research, Vol. 3 No. 1, pp. 60-95. Dodds, W.B. and Monroe, K.B. (1985), ‘‘The effect of brand and price information on product evaluations’’, in Hirschman, E.C. and Holbrook, M.B. (Eds), Advances in Consumer Research, XII, Vol. 12, Association for Consumer Research, Provo, UT, pp. 85-90.
Esteves, J. and Pastor, J. (1999), ‘‘An ERP lifecycle-based research agenda’’, paper presented at the International Workshop on Enterprise Management Resource and Planning Systems (EMRPS), Venice. FinancialWire (2006), ‘‘Intel designs mobile platform for hospitals’’, FinancialWire, 28 September. Fornell, C. and Larcker, D. (1981), ‘‘Structural equation models with unobservable variables and measurement error’’, Journal of Marketing Research, Vol. 18 No. 1, pp. 39-50. Gearon, C. (2005), ‘‘Behind the hype’’, Hospitals & Health Networks, available at: www. hhnmag.com/hhnmag_app/jsp/articledisplay.jsp?dcrpath=HHNMAG/PubsNewsArticle/ data/0506HHN_InBox_Technology&domain=HHNMAG (accessed 5 February 2008). Hancox, D. (2006), ‘‘Using RFID technology to enhance corporate effectiveness’’, IT Audit, 10 April. Helson, H. (1964), Adaptation Level Theory, Harper & Row, New York, NY. Hoffmann, W. (2006), ‘‘RFID becomes more active’’, Journal of Commerce, 27 March, available at: http://www.joc.com/news (accessed 5 February 2008). Koroneos, G. (2006), ‘‘RFID and the future of pharmaceutical supply chains’’, Pharmaceutical Technology, Vol. 30 No. 5, pp. 28-9. Oliver, R.L. (1981), ‘‘Measurement and evaluation of satisfaction processes in retail settings’’, Journal of Retailing, Vol. 57, pp. 25-48. Oliver, R.L. (1993), ‘‘Cognitive, affective and attribute bases of the satisfaction response’’, Journal of Consumer Research, Vol. 20 No. 3, pp. 418-30. Palmieri, M. (2006), ‘‘RFID-ready, or not?’’, Official Board Markets, Vol. 82, p. 14. Patterson, P.G. and Spreng, R.A. (1997), ‘‘Modelling the relationship between perceived value, satisfaction and repurchase intentions in a business-to-business, services context: an empirical examination’’, International Journal of Service Industry Management, Vol. 8 No. 5, pp. 414-34. Ranch, H. (2006), ‘‘Wells dairy milks quick ROI from RFID’’, Manufacturing Business Technology, Vol. 24 No. 4, p. 49. Sackmann, S., Stru¨ker, J. and Accorsi, R. (2006), ‘‘Personalization in privacy-aware highly dynamic systems’’, Communications of the ACM, Vol. 49 No. 9, p. 32. Saran, C. (2006), ‘‘RFID developments aim to boost flexibility and facilitate roll-outs’’, Computer Weekly, 21 March, p. 42. Scharfeld, T. (2001), ‘‘An analysis of the fundamental constraints on low-cost passive radiofrequency identification system design’’, Massachusetts Institute of Technology. Srite, M. and Karahanna, E. (2006), ‘‘The role of espoused national cultural values in technology acceptance’’, MIS Quarterly, Vol. 30 No. 3, p. 679. Swan, J.E. and Trawick, I.F. (1981), ‘‘Disconfirmation of expectations and satisfaction with a retail service’’, Journal of Retailing, Vol. 57, pp. 49-67. Sweeney, P.J., II (2005), RFID for Dummies, Wiley Publishing Inc., Indianapolis, IN. Venkatesh, V., Morris, M.G., Davis, G.B. and Davis, F.D. (2003), ‘‘User acceptance of information technology: toward a unified view’’, MIS Quarterly, Vol. 27 No. 3, pp. 425-78. Wicks, A.M., Visich, J.K. and Li, S. (2006), ‘‘Radio frequency identification applications in hospital environment’’, Hospital Topics, Vol. 84 No 3, pp. 3-8. Wireless News (2006), ‘‘ABI Research trims RFID software and services 2007 revenue forecasts’’, Wireless News, 11 August, p. 1. Young, D. (2006), ‘‘RFID implementation not moving fast enough, FDA says’’, American Journal of Health-System Pharmacy, Vol. 63 No. 6, pp. 500-2.
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Zeithaml, V.A. (1988), ‘‘Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence’’, Journal of Marketing, Vol. 52, pp. 2-22. Further reading Davis, F.D., Bagozzi, R.P. and Warshaw, P.R. (1989), ‘‘User acceptance of computer technology: a comparison of two theoretical models’’, Management Science, Vol. 35, pp. 982-1003.
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About the authors Charlie C. Chen is an Assistant Professor in the Department of Computer Information Systems at Appalachian State University. He is also a certified Project Management Professional (PMP). Dr Chen received his PhD in management of information systems from Claremont Graduate University in 2003. He has authored more than 30 referred articles and proceedings and presented at many professional conferences and venues. Dr Chen has published in journals such as Behaviour and Information Technology, Communications of the Association for Information Systems, and Information Technology, Learning, and Performance Journal. His current main research areas are online learning, mobile commerce, and supply chain technology. Jiinpo Wu is an Associate Professor in the Information Management Department at Tamkang University in Taiwan. He received his PhD in Business Computer Information Systems from North Texas University. His research areas are executive information systems, online learning, and social network analysis. Yu Sheng Su received his masters’ degree in Management Information Systems from Tamkang University in Taiwan. He specializes in the yield characterization analysis of wafer components and is currently working for Inotera Memories, a semiconductor firm. Mr Su’s research interests include technology acceptance models and wafer process flow analysis. Samuel C. Yang is an Associate Professor of Information Systems and Decision Sciences at California State University, Fullerton. He holds a PhD in management of information systems from Claremont Graduate University. He has an undergraduate degree from Cornell University and two graduate degrees from Stanford University, all in electrical engineering. Dr Yang has 14 years of managerial and professional experience in the telecommunications industry prior to entering academia. He is the author of two books in the area of wireless communications. His current interests are in telecommunications management, business data communications, enterprise wireless networks, and e-learning and m-learning. Samuel C. Yang is the corresponding author and can be contacted at: syang@fullerton.edu
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