Factors influencing the adoption of computerized medical diagnosing system for tuberculosis
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ORIGINAL RESEARCH
Factors influencing the adoption of computerized medical diagnosing system for tuberculosis Rani Oomman Panicker1,2 • M. K. Sabu2
Received: 2 March 2019 / Accepted: 7 November 2019 Bharati Vidyapeeth’s Institute of Computer Applications and Management 2019
Abstract The study of the factors that influence the use of automated diagnosing system for Tuberculosis (TB) can help in developing a strategy to enhance health professional’s acceptance of a given new system. This paper aims to examine the factors influencing the adoption of Computer-assisted Medical Diagnosing system for TB by clinicians and lab technicians in the context of developing countries health care. For that, we conducted a qualitative study by collecting data through in-depth interviews of the clinicians and lab technicians. A total of 18 interviews were conducted and the collected data was analysed, using content analysis. The results show that human characteristics (age and computer knowledge), technological characteristics (performance expectancy and effort expectancy), organizational characteristics (training and support), and technological impact could influence the adoption of CMD system for TB. The findings of this study would help researchers and medical professionals in providing them more knowledge about technological adoption and also helps to determine the uptake of the recent technology by healthcare professionals. Keywords Technology adoption Computer-assisted diagnosing system Tuberculosis
& Rani Oomman Panicker [email protected] 1
College of Engineering, Trikaripur, Kerala, India
2
Department of Computer Applications, Cochin University of Science and Technology, Kochi, India
1 Introduction Health Information Technology (HIT) is the applicability of IT aspects in health care area [35] and it plays an important role in providing better clinical care to patients in health care industry. It also helps to enhance the overall quality, efficiency and safety of health care system [1, 5]. It helps the medical professionals to handle the complex cases from preventing possible medical errors in clinical decision making [35, 42], and thus enhances their capability and accuracy in clinical judgement. All this requires an automated medical diagnosing system [computers or Personal Digital Assistance (PDA)] that can analyse patient’s images and symptoms, with almost the same efficiency as that of clinicians. Nowadays these devices are also used by patients and social workers or health workers [35]. Automated clinical diagnosing systems prevent, to some extent, the spreading of diseases by detecting them in their early stages. The two major factors that necessitate automated medical diagnosing systems are the increase in the volume and complexity of medical data and the increase in the decision rate taken by clinicians. Automated medical systems, for example, automatic detection of diabetic retinopathy [54], automatic detection of malaria from the blood sample images [9], automatic detection of tumours in brain [33
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