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Nursing informatics in the clinical setting 

Paper: Nursing Informatics in the Clinical Setting

After completing the lesson content from these first three weeks, we want you to write a  paper reflecting  upon  how the science of informatics affects patient care, quality standards, and communication within healthcare.  Include the following content areas:

  • Discuss the use of patient care technology (electronic health record, bar-code medication administration, clinical databases, practice guidelines, vital signs and patient care monitors,etc.) to manage data and information to deliver appropriate care to the patient

  • Discuss how changing trends in patient data (vital signs, lab values, cardiac rhythms, etc.) facilitate nurses to identify subtle changes in patient conditions

  • Discuss the need for data privacy, how it is managed when data is exchanged using computer systems, the ethics involved in maintaining privacy, and possible penalties when privacy is breached

  • Discuss how technology impacts and improves interprofessional communication

   

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Nursing informatics in the clinical setting

The expansive use of technological devices in healthcare leads to the generation of large volumes of patient information. Thus, exploring how to leverage such information to improve patient safety, quality, and other positive patient outcomes has been the focus of nursing informatics. The Electronic Health Record (EHR), for example, through the adoption of the meaningful use concept has played an essential role in improvements in healthcare by enhancing the effectiveness of clinical practice leading to high quality and safe patient care. With the increased use of health information, concerns on ethical and legal issues surrounding privacy and confidentiality of patient-identifiable health information also arise. Regardless, health technology provides limitless opportunities for clinicians to provide appropriate care because of accuracy in diagnosis, early identification of symptoms, reduction in errors, and use of patient data in analytics to produce clinical insights.

Patient Technology in Management of Data and Patient Information   

Several patient care technologies introduced in healthcare have enabled better management of data and information leading to efficient, effective, and appropriate patient care. First, the benefit of these technologies in improving practice has been the elimination/ minimization of preventable errors thereby contributing to patient safety. For example, EHR is a real-time patient-centric resource center that contains patient information including medications, vital signs, notes laboratory results, problem lists, past medical history, orders, and other reports that allow clinicians to make better treatment decisions about a patient (Slight, et al., 2015). These ensure efficiency and eliminates chances of making wrong choices that lead to errors. Moreover, it allows electronic prescribing of medication, which eradicates human error associated with medication administration. Similarly, the barcode medication administration allows verification of the ‘5 rights of medication administration’ eliminating errors associated with medication administration (Shah et al., 2016).

Secondly, the patient care technologies promote accuracy in diagnosis leading to improvement in practice. For example, the systems enhance the ability for quick access of patient information, coordination between providers, and patient history pertinent in supporting the accuracy of diagnosis. For example, the use of clinical decision support (CDS) system is associated with improvement in diagnostic accuracy. A study by Breitbart, et al. (2020) shows a 34% overall improvement in diagnosis accuracy with the implementation of the CDS system. Similarly, the management of data combined with data analytics provides predictions that assist clinicians in making an accurate diagnosis (Dash et al., 2019). The predictive analytics techniques can detect patterns and connections in patient’s medical information, assist clinicians in making an accurate diagnosis (Cohen et al., 2014). Accuracy of diagnosis is essential in providing effective treatment to enhance patient outcomes.

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Thirdly, patient care technologies encourage easy coordination between healthcare providers through interoperability and other systems. One of the meaningful use of the EHR is to promote communication among providers by allowing access to patient’s records and sharing patient’s health information in real-time. Thus, clinicians avoid test duplications and provide well-coordinated and personalized care. For example, in patients with comorbid chronic conditions, coordination among specialists involved in the management of the patient reduces delays in treatment and allows the practitioners to make better decisions for treatment, for instance, avoid medications that would cause drug interactions. According to a survey, 94% of providers agree that EHR systems allow readily available patient records while 74% indicate it supports better patient care (HealthIT.gov, 2019).

Fourthly, the use of patient care technologies ensures the early detection of diseases and conditions that would otherwise remain undetected until late by the clinicians. The monitoring systems such as vital signs, CDS systems, and other monitors deliver information in real-time and detect minute changes in patients that indicate possible complications or infections (Sutton et al., 2020). For example, in my practice facility, the hospital has implemented a CDS system to assist in detecting possible Sepsis in patients with congestive heart failure. This allows faster response and intervention before the infection leads to mortality since it digresses the patient’s condition very first. Moreover, patient information collected from various technological systems is useful in data mining techniques to reveal insights that enhance efficiency and other improvements in the clinical environment. For example, some of the benefits of predictive analytics in healthcare include operational efficiency, detection of conditions, personalized medicine leading treatment effectiveness, and enhancement of cohort treatments (Wang et al., 2017).

Changing Trends in Patient Data and Impact on Nursing Care

One of the advantages of patient technologies in healthcare is that they store health information. As such, clinicians can access the information to observe trends in vital signs, cardiac rhythms, and lab values among others. This information tends to from trends that can be used to detect changes in patient data and the information utilized to improve patient care. According to a study by (Churpek et al., 2016), the changing trends in patient’s vital signs are essential in improving care outcomes because they allow the identification of early warning scores. Similarly, Brekke (2019), shows that the application of vital signs trends increases the chances of identifying deterioration in a patient’s condition. This allows nurses to provide timely intervention and prevent adverse outcomes. The patient data trends systems use models that allow for the identification of minute changes. Such is not possible with the normal clinical procedure, which exposes patients to the risk of complications and preventable mortalities. Further, vital signs are key to understanding the physiological functioning of a patient, thus, the ability to identify the subtle changes enhances the accuracy of assessment leading to effective treatment approaches.  

Ethical and Legal Issues in Data

The availability and accessibility of patient health and personal information through health IT technologies create the risk of a breach in personally identifiable information. Thus, privacy and confidentiality of patient information are of critical concern with the increasing use of these technologies. The Health Information Technology for Economic and Clinical Health (HITECH) Act and Health Insurance Portability and Accountability Act (HIPAA) are the main regulations addressing issues revolving around privacy and confidentiality of information transferred through electronic devices. These regulations provide a guideline for clinicians on how to share and use patient health information without violating privacy and confidentiality requirements and exposing patients to a security breach (HHS.gov, 2020). HIPAA privacy rule sets conditions for use, sharing, and disclosure of patient information, as well as recommendations for protection that apply to healthcare practitioners, healthcare management, healthcare plans, and other entities with access to protected patient information (HHS.gov, 2020). For example, patient authorization is a requirement when seeking to share information with researchers.

Moreover, the rule allows patients the right to obtain and examine their health records. Violations of the privacy and security rules under the regulations attract jail term, loss of license, or/and heavy penalties. HIPAA violations are categorized and penalized according to tiers. For example, tier 1 attracts a fine of between $100 and $50,000, tier 2 $10,000 to $50,000, tier 3 $10,000 to 50,000 and finally tier 4 $50,000 for every violation (HIPAA, 2020). On the other hand, jail term includes up to 1 year in jail for tier 1, 5 years for tier 2, and up to 10 years for tier 3 (HIPAA, 2020). Apart from the legal obligations, practitioners have the ethical responsibility to protect the confidentiality and privacy of patient information. Under the ethical code of conduct and principles of ethical practice, practitioners have the mandate to protect patients from harm. One of the ways of causing harm is sharing a patient’s health information without their authorization.

Impact of Technology on Interprofessional Communication

Interprofessional collaboration is a proven approach to improvement in clinical practice leading to better patient care because of coordination and integration of care. The availability of technology is essential for efficient collaboration because of enhancement in communication among the interprofessional team (Barr et al., 2017). For example, technology facilitates improved communication in the management of chronic conditions. Physicians and other clinicians working on the case of a patient can easily access patient’s data through the EHR, which is utilized in making important decisions. Moreover, members of the interprofessional team update the patient’s EHR information such as deterioration in symptoms, which is available to the other members of a team to access in real-time and come together to provide a solution. The system that allows clinicians to share information is interoperability (Barr et al., 2017). The availability of various technological devices also contributes to improved communication among the interprofessional team. For example, mobile devices allow faster communication, the team can form a WhatsApp group where they discuss information about the patient/interprofessional meetings whenever a physical meeting is not possible.

The use of healthcare technology is increasing with vigor. Healthcare providers implement such technology because of their association with improved patient outcomes, efficiency, and cost-effectiveness. The HER system, for instance, comes with several advantages including accuracy in diagnosis, reduction in medication errors, and better coordination of care. Similarly, other devices such and CDS, monitoring devices, and so on enhance the diagnosis and treatment of patients. The emergent data mining and data analytics technology has also proven highly beneficial to the healthcare environment. For example, predictive analytics allows for the development of insights that give an accurate diagnosis, personalized medication, and support effective decision-making leading to efficiency.

 

References

Barr, N., Vania, D., Randall, G., & Mulvale, G. (2017). Impact of information and communication technology on interprofessional collaboration for chronic disease management: a systematic review. J Health Serv Res Policy, 22(4), 250-257. https://doi: 10.1177/1355819617714292. Epub 2017 Jun 6.

Breitbart, E. W., Choudhury, K., Andersen, A., Bunde, H., Breitbart, M., & Maria, A. (2020). Improved patient satisfaction and diagnostic accuracy in skin diseases with a Visual Clinical Decision Support System—A feasibility study with general practitioners. PlosOne, https://doi.org/10.1371/journal.pone.0235410.

Brekke, I. J., Puntervoll, L., & Pedersen, P. (2019). The value of vital sign trends in predicting and monitoring clinical deterioration: A systematic review. PLoS One, 14(1), e0210875. htps://doi: 10.1371/journal.pone.0210875.

Churpek, M. M., Adhikari, R., & Edelson, D. (2016). The value of vital sign trends for detecting clinical deterioration on the wards. Resuscitation, 102: 1–5. https://doi: 10.1016/j.resuscitation.2016.02.005.

Cohen, G., Amarasingham, R., Shah, A., Xie, B., & Lo, B. (2014). The legal and ethical concerns that arise from using complex predictive analytics in health care. Health Affairs, 33(7), 139–47. https://doi.org/10.1377/hlthaff.2014.0048.

Dash, S., Shakyawar, S., & Sharma, M. (2019). Big data in healthcare: management, analysis and future prospects. J Big Data, 6(54), https://doi.org/10.1186/s40537-019-0217-0.

HealthIT.gov. (2019, June 4). Improved Diagnostics & Patient Outcomes. Retrieved from HealthIT.gov: https://www.healthit.gov/topic/health-it-and-health-information-exchange-basics/improved-diagnostics-patient-outcomes

HHS.gov. (2020, December 10). The HIPAA Privacy Rule. Retrieved from Health Information Privacy: https://www.hhs.gov/hipaa/for-professionals/privacy/index.html

HIPAA. (2020). What are the Penalties for HIPAA Violations? HIPAA JOURNAL, https://www.hipaajournal.com/what-are-the-penalties-for-hipaa-violations-7096/.

Shah, K., Lo, C., Babich, M., Tsao, N., & Bansback, N. (2016). Bar Code Medication Administration Technology: A Systematic Review of Impact on Patient Safety When Used with Computerized Prescriber Order Entry and Automated Dispensing Devices. Can J Hosp Pharm, 69(5), 394–402. https://doi: 10.4212/cjhp.v69i5.1594.

Slight, S. P., Berner, E., Galanter, W., Huff, S., Lambert, B., & Lannon, C. (2015). Meaningful Use of Electronic Health Records: Experiences From the Field and Future Opportunities. JMIR Med Inform, 3(3), e30. https://doi: 10.2196/medinform.4457.

Sutton, R., Pincock, D., & Baumgart, D. (2020). An overview of clinical decision support systems: benefits, risks, and strategies for success. npj Digit. Med, 3, 17. https://doi.org/10.1038/s41746-020-0221-y.

Wang, Y., Kung, L., Cegielski, C., & Chung, W. (2017). Yichuan Wang et al., “An integrated big data analytics-enabled transformation model: Application to health care. Information & Management, 55(1), 64–79. https://doi.10.1016/j.im.2017.04.001.

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