Implementation of technology

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Annotated Bibliography

Oluwaseun Banjo

Herzing University

NSG 421- Nursing Informatics

Jennifer Dremann

09/19/2021

Selected technology: Computerized Provider Ordering and Electronic Medical Records.

Aronson, B., Keister, L. A., & Moody, J. (2020). Provider bias in prescribing opioid analgesics: An analysis of emergency department electronic medical records.  https://doi.org/10.21203/rs.3.rs-20738/v1

As provided by the authors, the use of electronic records has become one of the issues that need to be analyzed and better strategies deployed to reduce ethical concerns related to the use of electronic records more so in emergency departments. According to the article, A few healthcare professionals/physicians fail to uphold ethical standards when it comes to the prescription of opioid analgesics for pain treatment. As argued by the author, in many times, it has been found that physicians tend to bias when prescribing pain-relieving drugs such as opioids (Aronson et al., 2020). Failure to prescribe pain treatment drugs equally to across all groups of patients that are in need of such treatment may raise a significant public health concern. Worth noting from the article is that the author has presented a few factors that upon conducting extensive rea upon conduct research using electronic medical record data obtained from an emergency department of large healthcare facilities in the US, it was evident that facility constraints, along with cultural stereotypes were among the key factors that accelerated increased bias and as influenced physicians' treatment of pain before quantitative evidence is mixed.

Gkoulalas-Divanis, A., & Loukides, G. (2019). Case study on electronic medical records data. SpringerBriefs in Electrical and Computer Engineering, 55-64.  https://doi.org/10.1007/978-1-4614-5668-1_5

The article presents critical issues associated with the use of electronic medical records. The case study's focused primarily on the analysis of the efficient use of electronic medical records as the center of nursing documentation that not only makes work much easy as opposed to long-gene traditional paperwork that had numerous errors and time-consuming processes. The major focus of the author's research was based on the anonymization of electronic medical records to facilitate clinical analysis and provision of quality care to the patient as required (Gkoulalas-Divanis & Loukides, 2019) . However, there are concerns of security and privacy concerns over the use of medical data collected and shared among healthcare professionals. Further, the article examines some of the methods that can be initiated and deployed to secure healthcare data along with patient privacy when it comes to using and sharing patient data across a wide range of healthcare departments as the health needs of the patients may demand. Besides that, the research also explored various challenges facing the privacy and security threats facing medical data by analyzing existing data protection and privacy policies. Regulations and practices after which it extensively looked into widely used computational preserving techniques to ascertain their reliability in protecting patient privacy.

Evans, R. S. (2016). Electronic health records: Then, now, and in the future. Yearbook of Medical Informatics, 25(S 01), S48-S61.  https://doi.org/10.15265/iys-2016-s006

This article explores the effectiveness realized so far on the use of electronic healthcare records since 1992 up to 2018, it further explored how much the technology on medical data recording has kept on evolving to include other relevant features such as security and data protection features to curb the increasing menace of data compromise and loss of privacy. Perhaps the author seeks to analyze the evolutionary history of electronic health records by describing its state as early as the 1990s, it's status as of today, and its states 25 years to come. Worth mentioning is that the main aim of the study was not only to explore some of the advancements so far realized in electronic health records but also to analyze some of the factors and events that had contributed to the successful advancement of EHRs along with factors that might have derailed the evolution and advancement of the said technology (Evans, 2016). As opposed to the 1990s when the status of EHRs indicated that such technology was only used in academic centers, today’s state of the art of the EHRs has increasingly evolved and it can be used in primary care exam rooms as it has been interfaced with personal health records.

MIT Critical Data. (2016). Erratum to: Secondary analysis of electronic health records. Secondary Analysis of Electronic Health Records, E1-E1.  https://doi.org/10.1007/978-3-319-43742-2_30

According to the author, the primary aim of conducting this research was to find better ways of promoting an inter-disciplinary along with ethical approach when it comes to the analysis of medical data. The author presents the most appropriate methods that need to be used by data analytics and next-generation scientists working in different medical fields to leverage the data collected during routine patient care. the article provides more insights about how data generated during patient care need to be handled to reduced increased issues concerned with ethical decision making along with privacy issues (MIT Critical Data, 2016). Perhaps it formulates a more complete approach composed of evidence-based recommendations and support that guides physicians to make ethical decisions when analyzing patient data captured in electronic health records. Among the factors that have led to increased ethical dilemmas within the healthcare system is the progressive advancement of diagnostic and therapeutic technologies which not only make decision-making a complex process but also fail to provide guidelines to clinicians on how best to make clinical decisions.

Fife, C. E., & Eckert, K. A. (2017). Harnessing electronic healthcare data for wound care research: Standards for reporting observational registry data obtained directly from electronic health records. Wound Repair and Regeneration, 25(2), 192-209.  https://doi.org/10.1111/wrr.12523

As argued by the author, the United States Food and drug administration is working hand in hand with the healthcare sector to facilitate the expansion of coverage indications for drugs and medical equipment as well, as devices based on real-world data. Before the introduction of electronic health records technologies, most of the medical data collected from patients and other research centers were manually stored, and due to manual entry of data, the process was associated with several errors that affected the quality of information store about patients and other relevant medical details. Systematic errors linked to manual data collection and data entry have necessitated the development of efficient and automated technologies that not facilitate data collected, but also minimize systematic errors and perhaps increase the reliability of data collected along with easy automation of data transmitted directly from medical records (Fife & Eckert, 2017). The article provides that the manual health data sharing approach is labor-intensive and this has often resulted in potential errors and bias arising from the sources of data. The major issues are that some of the data documentation and aggregation procedures have not been well defined, all this makes it hard and difficult to share data that is relevant in the medical field. This, therefore, calls for the deployment of a quality clinical data registry, defined data documentation, that is based on a point of care documentation process that make use of universal definitional data dictionaries to help minimize errors when it comes to data sharing.

References

Aronson, B., Keister, L. A., & Moody, J. (2020). Provider bias in prescribing opioid analgesics: An analysis of emergency department electronic medical records. https://doi.org/10.21203/rs.3.rs-20738/v1

Evans, R. S. (2016). Electronic health records: Then, now, and in the future. Yearbook of Medical Informatics, 25(S 01), S48-S61. https://doi.org/10.15265/iys-2016-s006

Fife, C. E., & Eckert, K. A. (2017). Harnessing electronic healthcare data for wound care research: Standards for reporting observational registry data obtained directly from electronic health records. Wound Repair and Regeneration, 25(2), 192-209. https://doi.org/10.1111/wrr.12523

Gkoulalas-Divanis, A., & Loukides, G. (2019). Case study on electronic medical records data. SpringerBriefs in Electrical and Computer Engineering, 55-64. https://doi.org/10.1007/978-1-4614-5668-1_5

MIT Critical Data. (2016). Erratum to: Secondary analysis of electronic health records. Secondary Analysis of Electronic Health Records, E1-E1. https://doi.org/10.1007/978-3-319-43742-2_30