International Journal of Engineering and Technical Research (IJETR) ISSN: 2321-0869 (O) 2454-4698 (P), Volume-7, Issue-5, May 2017 83 www.erpublication.org Abstract— Implementations of MDSSs have been shown to reduce practice variability and improve outcomes. Over the last few years, the evolution in decision-making systems is proceeding with an extension of knowledge and the decisional processes underlying this knowledge. Best practice must be an organizational and process oriented concept to achieve adoption and consequently outcome improvements. The first step in how decision support systems can be re-examined and improved may be with incorporating new and unambiguous knowledge with a clear scientific reference. Evaluating these improved systems implies evaluating physicians’ adoption, compliance with guidelines, and impact on outcomes. A second important building block is to adopt clear medical concepts and classifications. Because the use of medical data for cooperative care is necessary to improve the quality of care, the patient-centered electronic health care documentation is needed. The study covered over 100 researches conducted in the field of Medical Decision Support system (MDSS). However, the research was not limited to simply MDSS. The field of MDSS has evolved out of Information technology and medical informatics. The key concepts relating to current MDSS systems were developed and presented in the literature prior 1976. But the most monumental research was conducted by Miller (1994) and his study acts as the foundational study for this research. Index Terms— Medical Decision Support system (MDSS), Historical evolution of MDSS, Computer Techniques in Medical Practice, Drug discovery. I. INTRODUCTION This study employs the historical research to collect necessary information relating to developments in MDSS. The purpose of this study is mainly descriptive, aiming to understand some specific development in a particular period of time in a particular culture relating to MDSS. A historical investigation is conducted with objectivity and the desire to minimize bias, distortion and prejudice. Thus, it is similar to descriptive method of research in this aspect. As discussed in the previous chapter, there are four steps to historical research and they were adopted in this study as well. The study was initiated by first identifying MDSS as the key problem of investigation. A through literature review was conducted to understand the concept and its related issues. Based on the primary and secondary sources, key developments in MDSS are identified and evaluated. Then, the information is used to provide a summary of the developments as well as to present with further research possibilities. Raghu Babu Korrapati, Department of Computer Science, Rayalaseema University, Kurnool, AP, India. II. DATA ANALYSIS The results of the study provide an insightful answer to the key research question. The research question of the study is: What are the factors that influence the adoption of medical Decision Support Systems (MDSS)? The study covered over 100 researches conducted in the field of Medical Decision Support system (MDSS). However, the research was not limited to simply MDSS. The field of MDSS has evolved out of Information technology and medical informatics. The key concepts relating to current MDSS systems were developed and presented in the literature prior 1976. But the most monumental research was conducted by Miller (1994) and his study acts as the foundational study for this research. Medical Decision Support Systems, also known as clinical decision support systems have come a long way since its first use in the early 1950s. They have been hailed for their potential to significantly reduce medical errors and increase healthcare quality and efficiency. Medical decision support systems (MDSS) play an increasingly important role in medical practice. By assisting physicians with making clinical decisions, MDSS are expected to improve the quality of medical care. With introduction of probabilistic multi-dimensional techniques in Computer Science, the development of decision support systems in medical informatics field is common now (Moole & Korrapati, 2003, 2004). Computerized Artificial Intelligence Techniques have been discovered to assist in MDSS (Korrapati, 2000; Korrapati, 2005; Tadavarthi & Korrapati, 2017, Kapu & Korrapati, 2017). Currently, most MDSS provide decision support for particular diagnostic or therapeutic tasks such as interpreting pulmonary function tests, analyzing electrocardiograms, or managing the use of anti-infective agents. MDSS can help physicians to organize, store, and apply the exploding amount of medical knowledge. They are expected to improve the quality of care by providing more accurate, effective, and reliable diagnoses and treatments, and by avoiding errors due to physicians' insufficient knowledge. Evaluation studies demonstrate that MDSS can have a positive effect on clinician performance and patient outcomes. In addition, MDSS can decrease healthcare costs by providing a more specific and faster diagnosis, by processing drug prescriptions more efficiently, and by reducing the need for specialist consultations. However, the performance of MDSS is subject to some important limitations and their inappropriate use or malfunctioning might adversely affect the well-being of the patient. Some MDSS fail to achieve the same level of diagnostic performance as human experts. This raises the ethical question: How can we design and use MDSS in a way A Historical Research Study of the Factors that Influence the adoption of Medical Decision Support Systems (MDSS) Raghu Babu Korrapati