NURS 8210 Controlled Terminology and Standards
NURS 8210 Controlled Terminology and Standards
The availability of data across systems has undoubtably transitioned healthcare in the 20th century. Ease in availability, communication, patient access to records and uniformity are just a few benefit advances that informatics provides. Sharing data across systems can present challenges. While working in inpatient psychiatry I have personally witnessed patient concern for “this information in my chart.” As health care professionals, we are not immune to mental health and physical challenges. While treating members in our health care system for mental health related issues the fear of judgment and embarrassment is often identified. The concern of maintaining HIPPA with the ease and accessibility can contribute to patients feeling uneasy and potentially guarded in information recall.
Additional experiences I have encountered as a challenge specifically to interoperability communication is resistance to change. Resistance to change is not uncommon to encounter initially however with exposure and time the initial fears can be resolved. The uniformization of hand offs in care with intraoperative communication can be intimidating to individuals with a lower comfort level in computerized records and charting. Comfort levels in computer technology and programing can present a significant obstacle to interoperability in our health care system worldwide.
A strategical approach to accommodating the protentional fear during hand off reposts can be alleviated by the utilization of primary interoperative care. According to Dexter, et al., (2019) intraoperative care provides multiple opportunities for a different provider to assume responsibility for the patients between cases, thus avoiding an official face to face handoff altogether. Providing learning opportunities in skill labs, hands on training and resources readily available can also assist in identifying and managing challenges associated with intraoperative communication and advances throughout healthcare.
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Dexter F, Osman BM, & Epstein RH. (2019). Improving intraoperative handoffs for ambulatory anesthesia: challenges and solutions for the anesthesiologist. Local and Regional Anesthesia, volume 12, 37–46.
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I do agree with you that the integration of informatics and big data in the healthcare practice is crucial to achieving quality care and increased patient satisfaction. EHRs are intended to make it easier to identify individual patients in clinical workflows (Mitchell & Kan, 2019). Patient identifiers include the patient’s full name, date of birth, contact information such as address and phone numbers, the next of kin’s name and contact information, emergency contact information, and other personal data deemed relevant for healthcare delivery operations (e.g., employer information, insurance information) (Yen et al., 2017). EHRs provide a unique patient ID (i.e., medical record number) for internal operations, which is used to identify a specific patient within the care setting. EHRs typically include patient demographic data such as age, gender, and ethnicity/race. These data are required for clinical operations and are mandated by Meaningful Use goals. Because of the various mandates to collect accurate age and gender data, the quality of data is often acceptable. However, other factors such as mode of measurement, user errors, and data conversion issues may have an impact on the quality of demographics data. EHRs frequently have a moderate to high missing data rate for non-essential demographic information such as income, marital status, education, employment status, and nationality (Ehrenstein et al., 2019).
Ehrenstein, V., Kharrazi, H., Lehmann, H., & Taylor, C. O. (2019). Obtaining Data From Electronic Health Records. In www.ncbi.nlm.nih.gov. Agency for Healthcare Research and Quality (US). https://www.ncbi.nlm.nih.gov/books/NBK551878/
Mitchell, M., & Kan, L. (2019). Digital Technology and the Future of Health Systems. Health Systems and Reform, 5(2), 113–120. https://doi.org/10.1080/23288604.2019.1583040
Yen, P.-Y., McAlearney, A. S., Sieck, C. J., Hefner, J. L., & Huerta, T. R. (2017). Health Information Technology (HIT) Adaptation: Refocusing on the Journey to Successful HIT Implementation. JMIR Medical Informatics, 5(3), e28. https://doi.org/10.2196/medinform.7476