Decision Support Systems In Information-Technology Field - Assignment Example

Section - I Synopsis The information technology application in the field of medicine started even in 1906's. These kinds of applications have become inevitable in most of the disciplines of science and technology. Just how IT revolutionized other fields, the medical informatics emerged as a new Informatics application domain in medical sciences. The need for automation and IT enabled process are found to ever increase recently. Decision Support Systems represents a computerized system that facilitates the decision-making process. Previously these systems were referred as artificial intelligence or expert systems. DSS is usually designed as an interactive tool which receives input from the user end to compile, assist and guide in the decision making process. The reliability and accuracy of the DSS have been proved in various occasions (Shortliffe, 1987). This present research work deals with various applications of DSS in medical informatics. Various applications of DSS in medical informatics includes a. Prescription of drugs b. Physicians order entry c. Treatment process and clinical practice Few of the positive outcomes of the DSS applications in health care are listed below. DSS application in medical informatics can 1. Improve the decision making process 2. Reduce the medical errors and cost effective. Section - II Information technology in health care There is a growing interest in adopting decision support systems in health care. The application of information technology can improve the process quality by automation and minimizing errors drastically. It can rectify the problems associated with the existing technologies. Prescription process A study was conducted to evaluate the impact of CDSS on the prescription costs (S.Troy McMullin et al 2004). The CDSS provides clinicians with adequate recommendations for the prescription process. The promotional activities of pharmaceutical companies influence the physicians in the drug prescription. They culminate in prescription of inappropriate drugs with high cost. These kinds of consequences can be overcome by the utilization of the automated systems since they provide guidelines based on preset facts and literature providing a cost effective solution. The CDSS WELLINX is one such example for this. The developed system guides the clinicians to choose a specific diagnosis and displays prescription relating to the condition. It works effectively in the decision making process cost effectively. DSS have been widely used and has also shown significant results in the patient outcomes. Studies carried out by shows CDSS improves quality of healthcare by providing accurate and timely diagnostic information. Once a system is derived taking into consideration all the requirements including the knowledge base it will prove good in the decision making process. Minimizing errors It was reported in a survey the prescribers had an error rate of 1.5%, a quarter of which may lead to serious effects (Dean B, 2002). Computerized systems for medicine or decision support system evolved as a result of repeated encountered errors; the UK and US government reformed the medical policy by depending on the information technological support and applications to minimize these errors. DSS improving decision quality In a study conducted (Vitali Sintchenko et al, 2004) on the impact of computerized decision support systems (CBSS) on antibiotic prescribing decisions, it was found CBSS improved the decision quality significantly. They graded the clinical impact score based on adoption rate and decision effectiveness and it was revealed from their work that DSS along with the microbiology report showed a high clinical impact score than the electronic guideline and electronic medical reports. Treatment guidelines Madhukar H. Trived et al, 2004 in his work describes the outlines the present use of computerized systems for implementing treatment guidelines and early use of a computerized decision support system for treating depression. It was found that the physicians' adherence to guidelines when guidelines are provided in a computerized format. The authors have designed a computerized decision support system for the treatment of major depressive disorder by using evidence-based guidelines. This computerized decision support system (CompTMAP) provides support in diagnosis, treatment, follow-up, and preventive care and can be incorporated into the clinical setting. CompTMAP has gone through extensive testing to ensure accuracy and reliability. Survey conducted among Physicians has shown a positive response. CompTMAP (computerized treatment algorithm for the treatment of depression) was developed at the University of Texas Southwestern Medical Center is designed for psychiatrists and primary care physicians for treating depression. The DSS for treatment of depression is limited. It was found form the study the patients who were treated for major depressive disorder in the TMAP had better outcomes than those who received normal treatment (Trivedi MH et al., 2004). In this present system the physician arrives at a clinical decision based on the guidelines provided by the CompTMAP, which in turn is based on the information entered by the physician about the patient's clinical condition at every sequential visit. This is integrated with the inbuilt preset factors of the system. MINT (Medical Informatics Network Tool) is software designed to support the management of care for chronic illness. It was developed with an objective to improve the treatment of schizophrenia (Alexander s. Young et al., 2004). The system facilitates clinicians to collect, manage, and utilize patient-specific and scientific information. The system is designed to enable communication between members of the clinical team. It also supports research evaluation by maintaining on all the adequate patients information linked to the treatment protocols. It has a simple interface for entry and organization of data and preparation of real-time reports. In a typical patient record it has various fields like assessment information, a messaging interface, and access to treatment guidelines. The usage of the systems reveals that it has been used with more than 165 patients and 29 psychiatrists and has shown improvements in the quality of care. It has modules for sequential entry of the patient's progress at various treatment levels and this will in managing the patient's treatment process. Though this is designed exclusively for schizophrenia, protocols can be developed for similar diseases. In terms of the DSS, it is not possible to derive a uniform system for the different diseases since the diagnostic process varies systematically. But the systems can be customized to few diseases. Computerized physician order entry Computerized Physician order entry (POE) systems are generally used to automate the prescription process, which contains a prescribing decision support module to validate the final prescription. This system makes the clinicians to spend more time in direct patient care. Computerized physician order entry (CPOE) with clinical decision support (CDS) is an application that physicians use to enter patient prescriptions directly into a computer and receive immediate feedback about clinically important information that may improve their prescribing decision. The author (Paula A. Rochon etal., 2006 )describes a situation how a prescribing decision can lead to unexpected results. The case mentioned in his example work shows how a series of subsequent events lead to development of adverse drug reaction. DSS employed in these kind of situation will prevent adverse effects by influences the decision making process by proving the proper guidelines. The working mode of the DSS is mostly based on how comprehensive it is in including a wide range of parameters. Cost effectiveness Studies relating to the impact of CDSS on the efficiency of health care delivery have focused on reductions in costs due to fewer medication errors and adverse drug events, increased efficiency in the execution of patient care, particularly in relation to tests and drug orders; and increased use of generic drug brands. Several estimates of the money saved as a result of computerized physician order entry systems have been made. The prevention of adverse drug event will result in massive cost reduction to the patients since one adverse drug event in US is estimated to add an average of $2000 - $6000 to a patient admission and as a whole will lead to an overall cost above $2 billion every year for US hospitals alone. Conclusion Various methods have been proposed recently for employing Information Technology in designing a specific DSS. Rather than developing these systems at the technological front it has to be based on the problems encountered at the utilization of these systems. The DSS have been developed at advanced levels without determining the actual clinical need. The DSS has produced promising results in improving quality of health care, ensuring patients safely and efficient process operation. The CDSS has to be customized according to the specific medical application. It is critical to devise an appropriate DSS pertaining to the medical applications. Numerous systems have been developed recently and they all may not suit a specific application, hence it is mandatory to develop decision support system based on the requirement or solution based or customized based on the user requirement rather than technology driven. It was found from the above justifications they have provided significant results in improving health care. There will be much more systems derived in the near future which will revolutionize the medical applications. Decision support systems have produced remarkable results in proving cost effective solutions, reducing errors and as well as by improving the quality of health care. Though the automated process cannot replace a human as a whole, it has produced significant results. Pertaining to the health care a human touch will make more difference than an automated system. 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Network-based system to improve care for schizophrenia: the medical informatics network tool (mint) j am med inform assoc. 2004; 11: 358-367. Paula A. Rochon, Terry S. Field, David W. Bates, Monica Lee, Linda Gavendo,Janet Erramuspe-Mainard, James Judge, Jerry H. GurwitzClinical application of a computerized system for physician order entry with clinical decision support to prevent adverse drug events in long-term care CMAJ January 3, 2006 174(1) Read More