Modern Technology-Based Information Systems

Table of Contents


Modern technology-based information systems can significantly improve the quality of health care provided to patients (Lu, Hsiao, & Chen, 2012). Such systems may include electronic health record (EHR) systems, computerized physician order entry services, or other examples of applying technology to procedures normally performed in health care facilities. EHR systems will be specifically addressed; their purpose is to increase the efficiency, speed, and convenience of keeping patient records in terms of collecting, storing, retrieving, and exchanging patient data. Successfully introduced, adopted, and employed by nursing care providers, EHR systems can make nurses’ work easier, save more time for the delivery of care (as opposed to formal data-related procedures), and ensure that better treatment is provided to patients (since the information based on which treatment decisions are made becomes more manageable). In this context, the example of EHR systems will be discussed, and personal experience on the issue will be shared.


Examples of the use of information systems (EHR systems specifically) in health care were discussed by Nguyen, Bellucci, and Nguyen (2014). The main purpose of the adoption of such systems was to automate and computerize procedures associated with the management of patient information. As a result of the adoption of EHR systems, such information becomes more processable and more accessible for health care providers who base their decision-making on patient data. Normally, data that should be inputted in an EHR system includes history of medical conditions and treatments, previous hospital admissions and the date and circumstances of the current admission (the latter applies to inpatients), general practitioner visits, allergies, medications taken currently or recently, complaints, and causes for visiting the health care facility. There is a wide range of software packages available in the market today, and some may include additional information, such as patients’ preferences in terms of the delivery of care and previous experiences of receiving health care.

Concerning the evaluation of EHR systems, Nguyen et al. (2014) claim that, in most cases, health care providers reported information quality as the main criterion. A lot of information is collected from patients and inputted into EHR systems, and all the collected information may be relevant to treatment, but since the volume of data is rather large, it may be challenging for nurses and physicians to find specific patient information needed for making a particular treatment-related decision; something important can be overlooked, too, if the records are large and unstructured. Therefore, to be perceived as high-quality products, EHR systems should enable proper structure of records to make it easier for providers to access and retrieve specific data. According to Ajami and Bagheri-Tadi (2013), it is also important that health care providers use all the available functions of EHR systems so that maximum benefits are gained. The authors support the example of using information systems in health care by exploring possible barriers, and major ones revealed in their study include the complexity of EHR systems and the lack of health care providers’ willingness to adopt them.

Personal Experience

My personal experience of working with information systems in health care was learning how to use a new EHR system adopted by a facility in order to decrease the number of mistakes and delays caused by inadequate management of patient information. A positive aspect of the experience was that I improved my understanding of the classification of patient data that needs to be collected and properly inputted into an EHR system so that all the nurses and physicians involved in the delivery of care to a certain patient could access relevant information quickly and conveniently. Also, I saw that, upon the adoption of the EHR system, nurses had more time they could spend with patients instead of managing paperwork like before the adoption.

However, there was a negative aspect of the experience, too. First of all, I learned that the system offered many functions that were irrelevant to the operation of the facility, and this revealed that the administrators who selected the specific software had not properly analyzed its compliance with the actual working processes and procedures practiced by nurses. Also, I should mention that, during the training period, a lot of nurses’ time in the workplace was spent on learning how to use the EHR system, and nurses might have paid more attention to mastering the patient record system instead of paying this attention to patients themselves. I believe the two aspects could have been improved if the facility administrators had had better selection criteria and had planned the training process so that nurses would not have been distracted from their work while learning how to use the new EHR system.


EHR systems present an example of using information systems in health care. Scholarly literature and my personal experience confirm that EHR systems can be beneficial in terms of increasing the efficiency of nurses’ work. At the same time, there are barriers to the successful adoption of such systems, and facility administrators should properly select software and plan the adoption to avoid negative effects on the delivery of care. In my practice, I will try to use EHR systems as extensively as possible because, as I have learned, ignoring the full range of available functions prevents achieving all the potential benefits.


Ajami, S., & Bagheri-Tadi, T. (2013). Barriers for adopting electronic health records (EHRs) by physicians. Acta Informatica Medica, 21(2), 129-134.

Lu, C. H., Hsiao, J. L., & Chen, R. F. (2012). Factors determining nurse acceptance of hospital information systems. Computers, Informatics, Nursing, 30(5), 257-264.

Nguyen, L., Bellucci, E., & Nguyen, L. T. (2014). Electronic health records implementation: an evaluation of information system impact and contingency factors. International Journal of Medical Informatics, 83(11), 779-796.

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