Taxonomy for multi-perspective assessment of the value of health information systems

Fitterer, René; Mettler, Tobias; Rohner, Peter; Winter, Robert

doi:10.1504/ijhtm.2011.037220

Cited by 7 publications

(5 citation statements)

References 32 publications

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“…Studies have been conducted to evaluate HIT from partial dimensions of the HOT-fit framework [27,41]. Randell and Dowding [27] emphasized organizational influences on nurses’ uses of CDSSs.…”

Section: Methodsmentioning

confidence: 99%

“…They found that the key factors for the introduction of a CDSS are instigation from individual clinicians, initiatives at policy level, clinician engagement, the need for adequate resources, the characteristics of the system itself, and adequate training. Fitterer et al [41] proposed a taxonomy for a multi-perspective assessment of HIT values in accordance with human and organizational considerations. They found system use to be related to people who use it, their level of use, their training, and their attitudes toward the system.…”

Section: Methodsmentioning

confidence: 99%

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Factors of accepting pain management decision support systems by nurse anesthetists

Hsiao¹,

Wu²,

Chen³

2013

BMC Med Inform Decis Mak

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BackgroundPain management is a critical but complex issue for the relief of acute pain, particularly for postoperative pain and severe pain in cancer patients. It also plays important roles in promoting quality of care. The introduction of pain management decision support systems (PM-DSS) is considered a potential solution for addressing the complex problems encountered in pain management. This study aims to investigate factors affecting acceptance of PM-DSS from a nurse anesthetist perspective.MethodsA questionnaire survey was conducted to collect data from nurse anesthetists in a case hospital. A total of 113 questionnaires were distributed, and 101 complete copies were returned, indicating a valid response rate of 89.3%. Collected data were analyzed by structure equation modeling using the partial least square tool.ResultsThe results show that perceived information quality (γ=.451, p<.001), computer self-efficacy (γ=.315, p<.01), and organizational structure (γ=.210, p<.05), both significantly impact nurse anesthetists’ perceived usefulness of PM-DSS. Information quality (γ=.267, p<.05) significantly impacts nurse anesthetists’ perceptions of PM-DSS ease of use. Furthermore, both perceived ease of use (β=.436, p<.001, R2=.487) and perceived usefulness (β=.443, p<.001, R2=.646) significantly affected nurse anesthetists’ PM-DSS acceptance (R2=.640). Thus, the critical role of information quality in the development of clinical decision support system is demonstrated.ConclusionsThe findings of this study enable hospital managers to understand the important considerations for nurse anesthetists in accepting PM-DSS, particularly for the issues related to the improvement of information quality, perceived usefulness and perceived ease of use of the system. In addition, the results also provide useful suggestions for designers and implementers of PM-DSS in improving system development.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Factors of accepting pain management decision support systems by nurse anesthetists

Hsiao¹,

Wu²,

Chen³

2013

BMC Med Inform Decis Mak

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“…It is widely accepted that e-Health can address many of the problems currently faced by the healthcare systems, improving quality of care, increasing efficiency of healthcare work, assuring healthcare services more accessible and better effectiveness of medical interventions and patient care (Fitterer et al 2011). …”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…strategic, organizational, group, individual) for different types of systems. For instance at the individual level, where the main issue is the lack of awareness among medical and nursing personnel, Fitterer et al (2011) have recently proposed a taxonomy for multi-perspective assessment of the value of HIS based on the Unified Theory of Acceptance and Use of Technology (UTAUT). A more comprehensive framework for evaluating HIS has been introduced by Yusof et al (2008a) building on previous models of IS evaluation, which measure the fit among technological, human and organizational dimensions.…”

Section: Introductionmentioning

confidence: 99%

A fuzzy taxonomy for e-Health projects

D’Urso

Giovanni

Spagnoletti

2012

Int. J. Mach. Learn. & Cyber.

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Abstract. Evaluating the impact of Information Technology (IT) projects represents a problematic task for policy and decision makers aiming to define roadmaps based on previous experiences. Especially in the healthcare sector IT can support a wide range of processes and it is difficult to analyze in a comparative way the benefits and results of e-Health practices in order to define strategies and to assign priorities to potential investments. A first step towards the definition of an evaluation framework to compare e-Health initiatives consists in the definition of clusters of homogeneous projects that can be further analyzed through multiple case studies. However imprecision and subjectivity affect the classification of e-Health projects that are focused on multiple aspects of the complex healthcare system scenario. In this paper we apply a method, based on advanced cluster techniques and fuzzy theories, for validating a project taxonomy in the e-Health sector. An empirical test of the method has been performed over a set of European good practices in order to define a taxonomy for classifying e-Health projects.

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“…On that account, much research is currently being undertaken to develop instruments and methods to help health service providers quantify the benefits of their investments in e-health e.g., [7][8][9]. Still, there is a considerable lack of guidance and an inability to establish effective business models, as a recent study conducted by the eHealth Initiative shows [10].Our goal is, therefore, to introduce and develop a rationale for experimenting with e-health business model designs.…”

Section: Introductionmentioning

confidence: 99%