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Health Information System Recommendations Report

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Updated: Jun 6th, 2021


There are multiple barriers to care quality in healthcare services, and designing strategies to identify and address them as soon as possible is an essential responsibility of health informatics specialists and the senior management. This report discusses detrimental factors related to internal workflow processes in the X Hospital. This information is then used to formulate recommendations regarding the selection of a new healthcare information system.

Environment, Issues, and Provider Objectives

The healthcare institution being analyzed is a U.S.-based rural hospital with a long history. Nowadays, it serves hundreds of local citizens and provides inpatient and outpatient care, as well as emergency services. The recent increases in the local population have contributed to changes in the patient flow, thus altering the work environment. The members of the nursing and healthcare teams have to serve more clients than before, which increases the risks of confusion and care mistakes. Therefore, new technological solutions helping to manage patient flow and optimize workforce utilization may be required to avoid problems linked to decreases in care quality and various types of nursing errors. Since inadequate health information systems impact the success of clinical decision-making in hospitals, provider objectives include analyzing and optimizing the use of IT to ensure patient safety.

Information Systems Configuration

Despite negative stereotypes about the state of healthcare IT in non-urban areas, the utilization of information systems in the discussed hospital is evident. Nowadays, healthcare providers in the organization use outdated EHR systems and old desktop computers to store and manage patient data. The EHR system being utilized is a basic one without clinician notes, which means that it only supports general information on patients’ health problems and medical history (Balgrosky, 2015). In particular, the functions that are limited include data from nursing assessments, advance healthcare directives, and nursing orders with in-depth descriptions of patient preferences and educational needs (Krousel-Wood et al., 2017). Utilizing the local basic EHR solution, the team is deprived of an opportunity to use multiple functions, including clinical guidelines or documents that standardize care and clinical reminders or alerts (Krousel-Wood et al., 2017). Furthermore, the currently used EHR system does not allow using drug-lab interactions data and decision support for drug dosing (Krousel-Wood et al., 2017). Considering changes in the number of patients, the absence of such functions may further increase the risks of errors, thus compromising the hospital’s positive reputation.


IT-related challenges impacting workflow and patient safety in the X hospital become evident when particular nurse-reported issues are analyzed. The situation indicating the need for advanced EHR solutions involves the members of the ICU nursing team and A. D., an adult patient in room 2 of the ICU. The problem of average severity was indicated four days ago, and it was manifested in excessive testing and diagnostic difficulties resulting from the lack of drug-lab interaction alerts. From the health informatics perspective, the situation points to the presence of information management problems at the systems level.


Continuing on the illustrative case, A. D. was admitted to the hospital with the signs of mild food poisoning on the first of October. As for the medications, in his conversation with the members of the care team, the patient reported the use of aspirin (300 mg) for the self-treatment of headaches that he associated with work-related stress and fatigue. The medications prescribed as a result of in-hospital assessments included antidiarrheal (loperamide) and anti-vomiting (bismuth subsalicylate) drugs. No allergies were indicated, and the utilization of IV fluids involved sodium chloride infusions in dealing with dehydration. The most recent vital signs were normal (BP 119/78; RR 19 bpm; HR 69 bpm), except for the body temperature reaching 99.5°F.

Speaking about the labs, both the first (1 October, 12 AM) and the second (3 October, 2 PM) stool culture tests were negative for pathogenic bacteria. Since the patient mentioned the possibility of mushroom poisoning, liver function tests were conducted on the first of October at 1 PM. As a result, the presence of slightly elevated ALT and AST levels was indicated, but there were no physical signs of liver damage, such as changes in skin or urine color and swelling. Concerning the code status, the patient does not reject the use of cardiopulmonary resuscitation in case of emergency.


The hospital’s EHR and its technical properties are linked to the problem pertinent to the described case. Information on the use of aspirin before hospitalization was entered into the patient’s EHR file in a proper manner. As a result of a computer mistake, that medical fact was displayed incorrectly for some time. Due to that problem and specialists’ lack of time to check everything twice, aspirin use was not considered when interpreting the results of a hepatic panel. Importantly, this drug can temporarily affect the results of liver function tests, in particular, AST and ALT levels (Doganer et al., 2015). The fact that some information had been missed was revealed sometime later, and the situation did not result in adverse outcomes for the client.

Given the increasing workload and its effects on healthcare specialists’ attention levels, similar cases will contribute to the threat of diagnostic delays. These decision-making problems can be eliminated by implementing one of the comprehensive EHR options. Such programs allow using a number of clinical decision support functions, including data on drug-lab interactions (Henry, Pylypchuk, Searcy, & Patel, 2016). Thus, the existing workflow and software challenges can be reduced to the urgent need for technical upgrades.


When it comes to the internal workflow, the limited effectiveness of the currently used patient data management tools may reduce the speed of clinical decision-making in different units. To prevent problems of the same nature, the hospital management team is recommended to focus on minimizing the necessity to retrieve information from different sources and waste time to exclude data presentation mistakes. Since eliminating such issues is the key goal behind modern EHRs, the decision to select and implement new technological solutions would be beneficial to the workflow speed. Another problem that has to deal with the workflow-related concerns is the use of ineffective hardware resources. Specifically, old computer equipment is often too slow to support the correct work of EMR and EHR systems (Or, Tong, Tan, & Chan, 2018). With that in mind, it would be beneficial to improve the hospital development plan to consider the need for faster computer equipment.

Concerning communications, the hospital’s employees may need to get education related to the state of communication technology. Apart from exchanging information through the use of the EHR, specialists can improve decision-making and teamwork with the help of web conferencing services that are cloud-based (Balgrosky, 2015). In the absence of video equipment, it is also possible to rely on instant messaging applications that make communication secure against data breaches (Balgrosky, 2015). Using them, specialists will be able to inform each other about software errors or any other problems. Regarding protocols, the available information is incomplete, and this is why it can be difficult to offer particular recommendations. However, overall, the new or improved system is to be constructed using widely recognized models, such as Transmission Control Protocol/Internet Protocol (Balgrosky, 2015). Additionally, subsequent evaluations are recommended to provide more specific findings.

Finally, to improve the use of information technology and prevent patient complaints, the management team is to consider purchasing a new software. The identified problems are linked to clinical decision-making and the potential influence of the human factor on patient outcomes. Therefore, it is logical to pay focused attention to vendors that offer new decision-support opportunities designed to eliminate diagnostic and medication management mistakes. IBM Micromedex is a good example of solutions that increase patient safety. It can be integrated into EHR platforms and uses alerts to make sure that providers make informed decisions concerning treatment (IBM Watson Health, 2018). Its implementation will help to achieve more favorable patient outcomes and prevent workflow issues in the future.


In summary, due to the characteristics of its current health information system, the X Hospital needs to implement changes to avoid threats to patient safety. To begin with, data presentation mistakes indicate the need to acquire new computer equipment and implement more comprehensive EHR options. Moreover, the use of applications for instant communication and purchasing clinical decision support software compatible with EHR is expected to be helpful.


Balgrosky, J. A. (2015). Essentials of health information systems and technology. Burlington, MA: Jones & Bartlett Publishers.

Doganer, Y. C., Rohrer, J. E., Aydogan, U., Agerter, D. C., Cayci, T., & Barcin, C. (2015). Atherosclerosis and liver function tests in coronary angiography patients. The West Indian Medical Journal, 64(4), 333-337.

Henry, J., Pylypchuk, Y., Searcy, T., & Patel, V. (2016). Adoption of electronic health record systems among US non-federal acute care hospitals: 2008-2015. ONC Data Brief, 35, 1-9.

IBM Watson Health. (2018). IBM Micromedex: EHR integration. Web.

Krousel-Wood, M., McCoy, A. B., Ahia, C., Holt, E. W., Trapani, D. N., Luo, Q.,… Milani, R. V. (2017). Implementing electronic health records (EHRs): Health care provider perceptions before and after transition from a local basic EHR to a commercial comprehensive EHR. Journal of the American Medical Informatics Association, 25(6), 618-626.

Or, C., Tong, E., Tan, J., & Chan, S. (2018). Exploring factors affecting voluntary adoption of electronic medical records among physicians and clinical assistants of small or solo private general practice clinics. Journal of Medical Systems, 42(7), 1-12.

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IvyPanda. "Health Information System Recommendations." June 6, 2021. https://ivypanda.com/essays/health-information-system-recommendations/.


IvyPanda. 2021. "Health Information System Recommendations." June 6, 2021. https://ivypanda.com/essays/health-information-system-recommendations/.


IvyPanda. (2021) 'Health Information System Recommendations'. 6 June.

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