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Health care is one of the fastest growing portions in economic services (Andaleeb 2001). This growth arises from aging population, mounting aggressive pressures (Abramowitz, Coté, and Berry 1987), increasing consumerism, and emerging treatments and technologies (Ludwig-Beymer et al. 1993; O’Connor, Trinh, and Shewchuk 2000). Quality of health care is currently at the forefront of professional, political, and managerial attention, primarily because it is being seen as a means to achieve the increased patronage, competitive advantage, and long-term profitability (Brown and Swartz 1989; Headley and Miller 1993) and ultimately as an approach for achieving better health outcomes for consumers (Dagger and Sweeney 2006; Marshall, Hays, and Mazel 1996; O’Connor, Shewchuk, and Carney 1994). Against this background, service quality has become an important corporate strategy for health care organizations. The advancement of technology in the health sector has growth potential and development of healthy lifestyle. Although mobile health creates positive change in the world, there are significant concerns about the perceived quality of such services and overall impact on patient satisfaction and quality of life. However, little researches have been conducted on the evaluation of this type of service, which describes the analysis (Strom et al, 2010). The mobile health service provider companies are trying to develop patient-centered care and quality improvement measures to increase significantly and its impact on the development of the structures for these new services. The role of service quality in fostering the growth of m-Health services has gained much attention in the academic and practitioner communities. However, empirical research in this area is not sufficiently adequate and in particular, the lack of sufficient research on the factors affecting the service quality is clearly evident.
Although a considerable amount of researches have been published in the field of service quality perceptions, much of them has focused on the development of generic service quality models (e.g., Brady and Cronin 2001; Parasuraman, Zeithaml, and Berry 1985). Despite the importance of developing appropriate models to assess factors affecting the quality of the organizations active in the field of health, relatively few researches has been done on the development of such special treatments. Given that m-Health implementation is in its infancy, a review of the literature has revealed few studies that directly explore service quality in this field. However, few researchers have examined factors affecting the service quality of care in mobile health care. The purpose of this paper is to present a new framework for the influencing factors on new mobile services in the field of health in corresponding organizations.
Donabedian (1992)’s studies showed that in health care, customers play an important role in determining their quality and designing of service delivery systems. Oliver (1993) introduced the service quality as a powerful concept due to its strong correlation with customer satisfaction. In 1987, Zeithaml described perceived quality of service as consumers’ (or patients’) judgment about the overall excellence or superiority of a mobile health service. Gronroos (1982) has defined perceived service quality as measuring performance against expectations. Berry and Parasuraman (1988) introduced service quality as the gap between expected and perceived service.
According to the research of (Gronroos, 1984; Parasuraman et al. 1988) service quality has been defined based on the consumer’s perceptions, and the dimensions of service quality must be multi-dimensional and also according to Brady and Cronin in 2001, hierarchical concept and based on the findings of Dagger et al 2007,whose evaluations are likely to be context dependent. The European Union’s Research & Development in Advanced Communications Technologies in the Europe (RACE) programdefines service quality as ‘‘a set of user perceivable attributes of that which makes a service what it is (RACE, 1994). Then, Brady and Cronin (2001) introduced quality of service as a multi-dimensional concept that underscores the findings of Dabholkar et al (1996). Fassnacht and Koese (2006) and Just et al. (2007) stated that service quality is a hierarchical concept and Dabholkar et al (2000) in their studies showed that the factors affecting the service quality is likely specific to a particular area to that confirmed Caraman (1990) and Babakas and Gregory (1992).
Voss et al (2004) introduced service quality as an important factor and particularly relevant in almost all kinds of services and showed that it must be stated as a user-understandable language and manifests it as a number of parameters, all of which have either subjective or objective values’’. According to Nelson et al (2005)’ findings, concepts of quality are interrelated and should be based on consumer perceptions. Dagger and Sweeney (2006) introduced service quality as an important factor due to the relationship between service quality and quality of life.
Based on Sarkr et al (2009), service quality is defined as evaluation of Performance, which confirmed the findings of Babakas and Gregory (1992) and Cronin and Taylor (1992).
Akter et al (2013) argue that the service quality of m-Health is an interdisciplinary domain that must be explored through generic theories from marketing, information systems (IS) and healthcare literature. In this study based on a definition from Akter et al (2013), service quality is defined as consumers’ (or patients’) judgment about the overall excellence or superiority of a mobile health service. Although existing research developed service quality as a general model, in many cases, there is not a new successful attempt, except to repeat existing ideas in new settings (Brady and Cronin, 2001; Parasuraman et al, 1988). In health care, most service quality research has focused on either Gronroos’s two-dimensional model (i.e., functional quality and technical quality) or Parasuraman et al.’s five dimensional SERVQUAL model (i.e., reliability, responsiveness, assurance, empathy and tangibles). In addition, several studies have followed Donabedian’s model, which measures service quality under two dimensions: technical and interpersonal quality. According to this framework, technical quality refers to the application of medical science and technology to health care, whereas interpersonal quality refers to the interaction that occurs between the service provider and consumer. Aligned with these findings, Brook and Kathleen in 1975advanced a conceptualization in which technical care reflects how well diagnostic and therapeutic processes are applied and interactive care is concerned with the interactive behavior between the service provider and user. In a similar vein, other researchers have introduced service quality models in health care. More recently, Dagger et al (2007) have produced a context-specific, multi-dimensional and hierarchical model for measuring health service quality in general healthcare settings. The authors identify four primary dimensions (interpersonal, technical, environment, and administrative) and nine sub-dimensions (Interaction, relationship, information, expertise, atmosphere, tangibles, timeliness, operation, and support) for measuring service quality in a hierarchical manner. Varshney (2006) investigated the impact of the information systems (IS), technological, managerial and medical perspectives of wireless health care. Akter and D’Ambra (2010)proposed a conceptual model of service quality in m-Health based on platform quality, interaction quality, and outcome quality.
Regarding to the purpose of the research, Identify the affecting factors the M-health service quality, the conceptual framework used in thisstudy is conceptual model from the study by Ahkter et al (2013) that is shownin theFig. 1.
Figure 1: The research model from service quality model for m-health
In this paper, to identify factors affecting the m-health service quality that is required by health clients in small and medium-sized enterprises in Iran, qualitative approach has been used. The method of sample size determination is based on the Snowball sampling and interview until saturation. The adequacy logic of the data collected as the full extent of the data is represented. To achieve this, interviews were conducted with twelve it experts in health and treatment area and after carry out the eleventh interview, it is concluded that the information of the interviewees was repeated and reached to saturation level. So, it is not required to continue the interview. After that, using coding method, the pivotal factors affecting on the new services in organizations were obtained.