Fida Hussain Chandio (Corresponding Author)
Understanding and Analyzing Critical Success Factors for Physician’s Continuance Usage Intention towards Evidence-Based Medicine: Extended Expectation Confirmation Model
Fida Hussain Chandio (Corresponding author)
Kuliyyah of Information & Communication technology
Internation Islmaic Uniververisty Malaysia
Email:
Fozia Anwar
COMSATS Institute of Information Technology
Islamabad Campus, Pakistan
Email:
Abdul Waheed Mahesar
Kulliyyah of Information & Communication Technology
International Islamic University Malaysia
Email:
Akram M Z Khedher
Kulliyyah of Information & Communication Technology
International Islamic University Malaysia
Email:
Abstract
This research proposes an extended expectation confirmation model (EECM) to investigate the continued IT usage behavior among health care professionals. The proposed model integrates key constructs from the health inofmatics and technology acceptance research streams into the theoretical frame of the expectation confirmation model. The model was tested on a sample of 352 physicians. Data analysis was performed using structural equation modeling tools and techniques. The results of this study showed considerable support for EECM. Altough the impact of both perceived usefulness and perceived ease of use was found significant in influencing user satisfaction and continued usage intention, perceived ease of use, however, had shown stronger impact than perceived usefulness. In addition, results suggested strong influence of perceived usefulness on continuous usage intention, this implies that the nature of the target technology can be an important boundary condition in understanding the continued IT usage behavior in evidence-based medicine (EBM) context. By underatanding continued EBM usage behavior from physicians point of view, this study will provide a deeper insight into how to increase acceptance and usage of healhe care information technologies by intended health care professionals.
Keywords: Continued IT usage; Evidence based medicine; Extended Expectation-confirmation model; Health technolgies acceptance; Structural equation modelling.
1. Introduction
With the rapid growth of information systems and web-based health care technologies, physicians are required to operate health care information systems and relavent applications for providing better health care facilities to the paptients. Due to the dramatic growth in new types of diseases, it is believed that patients visit clinic with prefrerences, unique concerns and expectations about the services offered in the clinic (Greenhalgh, Howick, & Maskrey, 2014). Evidence-based medicine (EBM) is the integration of clinical expertise, patient values, and the best research evidence into the decision making process for patient care. Where clinical expertise refers to the cumulated experience of medical and clinical education, and skills of the medical practitioners (Haynes, Wilczynski, McKibbon, Walker, & Sinclair, 1994). EBM is a type of new information systems that uses the innovative resources of the internet and health care technologies to enable physicians to provide better health care facilties to their patients . Therefore, it is important for physicians to apply current health care information systems into their clinical settings to effectively improve the quality of patients’ healthcare services.
There is consensus among the researchers around the globe (BHASKAR, 2011; Organization, 2009) that health care information systems are, and, will continue to have a considerable effect on the health care industry. Novel trends of medical practice (scuh as EBM) requires fairly complex understanding and mental capability to fully employ IS functionalities. Utilization of these new type of information systems may be hard to achieve due to potential users’ (such as physicians) limited exposure and access to it (Majid et al., 2011). Therefore, in order to better understand and exaplain the maximum usage of these systems, it merits a systematic mechanism to understand the factors that can facilitate physcisians acceptance and continued usage of health infromation systems. This issue is of particular importance for health care industry policy makers because by understanding crucial factors, they will be able to understand user perceptions and continued usage intentions towards evidence based medicine. As a result, increase acceptance and continued usage of such systems.
In literature many technology acceptance theories such as technology acceptance model (Davis, Bagozzi, & Warshaw, 1989), innovation diffusion theory (Rogers, 2003), and the theory of planned behavior (Ajzen, 1991), studied initial technology adoption and explored the variables that motivate individuals to accept new technology and information system (IS). Although initial acceptance is first step toward realizing IS success yet long-term successful sustainability of an IS depend on its continued use rather than initial use (Bhattacherjee & Lin, 2014). Continuous usage intention is very critical in IS implementation. Consequences of inappropriate and ineffective long-term use of IS results in corporate failures (Bhattacherjee & Lin, 2014; Cecez-Kecmanovic, Kautz, & Abrahall, 2014; Lyytinen & Hirschheim, 1988).
Understanding physicians’ continuance usage intention towards EBM by using e-information resources is the goal of this study. The concept of continuance is not an entirely alien concept in IS research. As "implementation" (Zmud, 1982), "incorporation" (Cooper, 1990), and "routinization" (Cooper, 1990) are the various ways available in the IS implementation literature, where post acceptance stage of IS usage excels conscious behavior and becomes part of normal routine activity. Many studies in literature, view continuance intention as an acceptance behaviors extension as they are employing the same set of pre-acceptance variables to explain both acceptance and continuance decisions, thus, indirectly it is assumed in these studies that continuance covaries with acceptance (Cecez-Kecmanovic et al., 2014; Davis et al., 1989; Karahanna, Straub, & Chervany, 1999). Therefore, this literature is unable to explain acceptance-discontinuance anomaly.
This paper is based on the proposed model of EECM-IT (Hong, Thong, & Tam, 2005). EECM-IT is based on expectation-confirmation theory (Oliver, 1980). This study empirically validates the EECM-IT using a field survey data of 352 physicians. We believe the lack of a theoretical foundation for this stream of research has limited the contributions of previous research and prevented health care organizations from understanding what makes a practical use of technology to practice evidence based medicineThe rest of the paper is organized as follows. The next section describes ECT and integrates it with prior IS usage research to postulate the hypothesis in EECM-IT. The third section describes the research methodology adopted to test the research model. The fourth section presents the results of data analysis and discusses the implications of the study. The final section summarizes the study's core findings and its contributions.
2. Theory and Hypothesis
2.1 Expectation Confirmation Model -IS
The Expectation Confirmation Model (ECM)-IS model give provision to evaluate the requirements of individual users in their own environment (may be at home or at their workplace) and the continuance intention of use of specific system in the absence of organizational supporting factors. However, the modifications on the original ECM-IS are necessary in the case of integrated and complex systems where a lot of strongly associated users are involved who depends on each other to have full utilization of the IS (Sharma & Yetton, 2007). In 2001, Bhattacherjee developed ECM rooted in expectancy-confirmation paradigm for continued information technology (IT) usage. This modified model is based on three antecedents constructs, which are user satisfaction, user confirmation and post-adoption expectations, which is represented by perceived usefulness (PU) in this modified model. Key determinants of satisfaction are perceived usefulness and user’s levels of confirmation (Bhattacherjee, 2001). As it is proved in the expectancy-confirmation paradigm that satisfaction is positively influenced by the perceived usefulness providing a baseline for reference against confirmation judgments. Helson’s adaptation level theory also provides a theoretical support to this relationship (Helson, 1964). Adaption level theory postulates that one perceives stimuli only in relation to an adapted level (Yi, 1990). A directly proportional relationship between user’s expectation and subsequent satisfaction achieved, is also found in prior user’s behavior research (Hussein, Moriarty, Stevens, Sharpe, & Manthorpe, 2014; Oliver & DeSarbo, 1988). Additionally, studies on IT adoption have reliably found that perceived usefulness is the most imperative factor in defining and explaining users’ adoption intentions (Davis et al., 1989; Venkatesh & Davis, 2000).
2.2 Extended Expectation Confirmation Model
Extended Expectation Confirmation Model (EECM-IT) added user’s support and maintenance of the IS as a salient feature in shaping the IS user behavior, which can further influence the user’s decision to either continue or discontinue with IS use (Bhattacherjee, 2001). In EECM-IT the post-adoption expectation is characterized by perceived ease of use and perceived usefulness. Furthermore, as hypothesized in technology acceptance model (TAM) that perceived ease of use may have both direct influence and indirect influence via perceived usefulness on sustained IT usage intention. With the same logic of reasoning applied to the relationship between confirmation and perceived usefulness in the ECM-IT, the level of confirmation is also hypothesized to positively affect perceived ease of use. As a user gains confirmation experience, the user’s perceived ease of use will become more concrete and updated (Hong et al., 2005).
In TAM, perceived usefulness has an immediate effect upon behavioral intention for IS, which is helpful towards the actual behavior (Bhattacherjee, 2001; Davis et al., 1989; Karahanna & Straub, 1999). Perceived Usefulness (PU) is proved as a significant influencing factor in determining the user acceptance, user intention, satisfaction and usage behavior. Literature review provided the evidence of the significant effect of PU on IS acceptance and usage (Davis et al., 1989; Sun, Wang, Guo, & Peng, 2013). Bhattacherjee verified that perceived usefulness is a significant determinant of satisfaction (Bhattacherjee, 2001). A positive correlation between PU and perceived ease of use (PEOU) is also established in prior literature (Hayashi, Chen, Ryan, & Wu, 2004; Rai, Lang, & Welker, 2002; Seddon, 1997). Devaraj et al. found that perceived ease of use and perceived usefulness both are antecedent of satisfaction (Devaraj, Fan, & Kohli, 2002). Correspondingly, in the usage of online information resources with the context of EBM, if physicians have an opinion that system is useful then they are more likely to accept it. Therefore, it is hypothesized that PU will have a significant positive effect on physician’s satisfaction and continued usage behavior towards online information resources to practice EBM. Accordingly, the hypotheses are as follows:
H1a. Perceived usefulness will have a significant positive effect on satisfaction
H1b. Perceived usefulness will have a significant positive effect on continued usage intention
Literature review proved that PEOU is also among the major factors of user acceptance, satisfaction and usageintention, which eventually have a significant positive effect on actual system usage behavior (Davis et al., 1989; Gefen & Straub, 2000; Igbaria, Zinatelli, Cragg, & Cavaye, 1997; Sun et al., 2013; Venkatesh & Davis, 2000). As physicians’ experience with online information resources (to get authenticated and valid evidences during their clinical practice) is different from a common person. Because of the technical nature of medical databases and their interactive characteristics, physicians require more cognitive effort as compared to other IT users. Specifically, physicians first need to get access to find the relavant resources and then make a quick evaluation of whether it is worthy to rely on the obtained information for clinical decision making process. Therefore, the easier they perceive using available online information resources, the more likely they are to engage them in their decision making process (Davis et al., 1989; Venkatesh & Davis, 2000).
Other researchers established the significant relation between PEOU and PU (Adams, Nelson, & Todd, 1992; Davis et al., 1989; Gefen & Straub, 2000; Igbaria et al., 1997). The literature suggested that ease of use may be an antecedent of usefulness, rather than a parallel, direct determinant of usage” (p. 334) (Davis et al., 1989). Therefore, the construct of satisfaction is introduced between ease of use and perceived usefulness, suggesting that perceived usefulness and perceived ease of use can be adjusted by confirmation experience. Similarly, if physicians find online medical information resources easy to use then they are more likely to accept and subsequently continue using the system.r. Therefore, it is hypothesized that PU and PEOU has an influence on user satisfaction and usage intention. The hypotheses related to PEOU are summarized as follow:
H2a. Perceived ease of use and perceived usefulness will have a significant positive effect on satisfaction
H2b. Perceived ease of use and perceived usefulness will have a significant positive effect on continued usage Intention
H2c. Perceived ease of use will have a significant positive effect on perceived usefulness.
Perceived usefulness is influenced by users ‘confirmation level in online banking services, business-to-consumer and e-commerce services (Bhattacherjee, 2001). This causal relationship have been confirmed in virtual learning environment as well and in the use of a web portal (Hayashi et al., 2004; Lin, Wu, & Tsai, 2005). According to ECT both disconfirmation and expectations is going to affect satisfaction where gap between expectations and perceived performance is indicated by disconfirmation. Swan et al. studied the concepts of disconfirmed expectations and satisfaction in retail businesses and results showed that a higher level of positive disconfirmation indicates higher satisfaction (Swan & Trawick, 1981). Spreng et al. proposed an updated model complementing the previous ECT model. This updated model indicated that disconfirmation has a significant influence upon satisfaction of product attributes and information, thereby influencing overall satisfaction (Spreng, MacKenzie, & Olshavsky, 1996). This suggests that users positive confirmation expections about the system will significantly increase the level of satisifaction with system. Furthermore, Bhattacherjee (2001) in their study concluded that confirmation had a positive influence on satisfaction and perceived usefulness. Thus, the hypotheses for confirmation are presented below:
H3a. Confirmation will have a positive significant relation with PU.
H3b. Confirmation will have a positive significant relation with PEOU.
H3c. Confirmation will have a positive significant relation with the satisfaction.
In the context of IS acceptance, satisfaction is a decisive factor affecting continuous usage intentions of the customers towards that IS; thus, there is a significant correlation between satisfaction and intention (Hussein et al., 2014; Swan & Trawick, 1981). According to Bhattacherjee, satisfaction of previous experience is the main factor, which affects the continuance usage intention . In an empirical study of 1000 customers of banking IS network, satisfaction was found to be a determinant of IS continuance usage intention (Bhattacherjee, 2001). Satisfaction has a positive effect upon repurchase intentions of trading partners in e-commerece domain (Devaraj et al., 2002). Behavioral intention is primarily predicted by satisfaction in the studies where satisfaction is viewed as an attitude. Several studies show that satisfaction is a strong indicator of continuance intention. Researchers found that there is a strong link between satisfaction and continued use (Liao, Chen, & Yen, 2007; Roca, Chiu, & Martínez, 2006). Therefore, the following hypothesis is proposed: