Electronic health records (EHRs) are easier to read than the paper charts of the past, but many complain that healthcare providers are focusing too much on the computer screen instead of the patient
1. Electronic health records (EHRs) are easier to read than the paper charts of the past, but many complain that healthcare providers are focusing too much on the computer screen instead of the patient.
- Is this due to lack of skill or training, poor computer system design, or just the nature of computer charting?
- Is patient care suffering from the implementation of EHRs?
- Charting in an EHR consist of clicking boxes, do you feel this provides enough detail about the patient, condition, and events if there was a law suit
[ANSWERED] Electronic health records (EHRs) are easier to read than the paper charts of the past, but many complain that healthcare providers are focusing too much on the computer screen instead of the patient.
2. Hebda, Hunter and Czar (2019) identify three types of data that is currently being tracked by organizations (p. 46).
- Identify and explain another type of data, specific to your practice, that is being tracked by an organization.
- Why do you feel this data is important to track?
- Identify and discuss the organization that is tracking the data.
- Are there any ethical concerns with an outside organization tracking this data, explain and give examples?
3. In this week’s discussion post, you identified and explain the topic selected for the project.
- Provide a description of your selected topic based on input from the discussion forum. What is your project, why is it relevant to this class, and why is it important to you?
- Identify an informatics/healthcare theory from pages 29-30 of the textbook that aligns with the project and explain why.
Expert Answer and Explanation
Theory of Healthcare Informatics
Electronic health records
Like any other new concept in healthcare, healthcare informatics is associated with different problems that limit its use in patient care. An improvement in the overall presentation of data in electronic health records could guarantee better success in the healthcare outcomes (Cowie et al., 2017). Data management is a crucial idea that should be treated with utmost care, as the exposure of patient data to unauthorized individuals is not only unethical, but could cause significant harm on patients.
EHR Causing too much Focus on Machines Rather than on Patients
Cause of the Over-emphasis on Computer Screen by Health Experts
Some healthcare givers focus too much on the computer screen instead of patients when using electronic health records because most of them are yet to be fully acquainted with the computer system. Also, the nature of computer charting requires full concentration lest the healthcare givers would make large mistakes in feeding the patient information (Kruse et al.
, 2017). Unlike the traditional charting techniques where one fills patient information in their files without much calculations and involvements, computer charting requires one to be fully engaged in the process, and this makes it hard to give patients full concentration.
Suffering of Patient Care under EHR Implementation
Patient care is not suffering from EHR implementation as the benefits of EHR systems exceed the limitations. One of the main advantages of having electronic health records is the fact that they help in faster patient information processing as well as accuracy in data collection and management. The drawbacks can also be corrected using basic maintenance procedures.
The Insufficiency of Clicking on Boxes in the Charting Process
Clicking boxes in EHR charting process is one of the reasons why patient details are not captured in full. There should be more options for filling patient information such as using prose format to capture details of patient’s condition. This can also help in safeguarding the safety of the healthcare givers in the case of a lawsuit.
Types of Data Tracking by Hebda, Hunter, and Czar (2019)
Type of Data Specific to my Organization and the Importance of Tracking it
Managing patient care
The incidence rate of various disease outbreaks is one of the primary data that is being tracked by organizations outside the facility. Tracking this data helps to implement national and international policies on disease control, such as in the case of the coronavirus pandemic. It also helps in improving the preparedness of healthcare facilities in managing patient care in different situations such as pandemics.
Organization Tracking the Data
The Centers for Disease Control and Prevention (CDC) is one of the organizations that track the data. This organization serves as a major health protection agency where it identifies health, security and safety threats early enough to allow corrective action (Yang et al., 2020). It also helps to promote vaccination and health education campaigns that reduce the overall vulnerable communities (Yang et al.
Ethical Concerns of the Tracking
Major ethical concerns
The CDC always obtains consent from the parties responsible for the data, and hence there are no major ethical concerns in tracking data. Besides, most of the data collected does not display personal information of the patient populations, as it is only used for research purposes (Rahimi et al., 2018).
Nevertheless, there is need to put up more regulations to reduce the chances of misuse of patient data by external organizations.
Topic Selected for the Project
Description of Topic Selected and its Relevance
The topic selected for the project is ‘the influence of health informatics nurses on behavior change.’ This topic is relevant in that there are many ways in which nurses today have integrated health informatics into care, but it is not clear how they can achieve the right levels of behavior change (Wu et al.
, 2019). Specifically, there is need to identify areas in informatics that can serve as better channels of achieving positive behavior change among nurses.
The behavior change model can be applied in healthcare informatics by using its concepts to assess how a health informatics intervention influences the patients (Medlock & Wyatt, 2019). The theory shows how nurses can respond to patient needs in a timely fashion and tailor their behaviors and those of the patients to suit the informatics demands.
Applying this theory in the topic can help in gaining more insight about the project.
Health informatics is one of the most discussed topics in nursing, and has helped nursing experts to grow their ability to deliver healthcare solutions. Among the changes that should be made to improve the nature of electronic health records is increasing the platform for collecting further details about patients.
The CDC is an organization that tracks most of the data in my organization for the purpose of management of healthcare on a broader contexts such as regional and national levels. A research on healthcare informatics can be improved by using a suitable informatics theory such as the behavior change theory.
Cowie, M. R., Blomster, J. I., Curtis, L. H., Duclaux, S., Ford, I., Fritz, F., & Michel, A. (2017). Electronic Health Records to Facilitate Clinical Research. Clinical Research in Cardiology, 106(1), 1-9. DOI 10.1007/s00392-016-1025-6
Kruse, C. S., Smith, B., Vanderlinden, H., & Nealand, A. (2017). Security Techniques for the Electronic Health Records. Journal of medical systems, 41(8), 127. https://doi.org/10.1007/s10916-017-0778-4
Medlock, S., & Wyatt, J. C. (2019). Health Behavior Theory in Health Informatics: Support for Positive Change. Studies in health technology and informatics, 263, 146-158. DOI: 10.3233/SHTI190119
Rahimi, B., Nadri, H., Afshar, H. L., & Timpka, T. (2018). A Systematic Review of the Technology Acceptance Model in Health Informatics. Applied clinical informatics, 9(3), 604. Doi: 10.1055/s-0038-1668091
American medical informatics association visual analytics working group task force
Wu, D. T., Chen, A. T., Manning, J. D., Levy-Fix, G., Backonja, U., Borland, D., & Kandaswamy, S. (2019). Evaluating Visual Analytics for Health Informatics Applications: A Systematic Review from the American Medical Informatics Association Visual Analytics Working Group Task Force on Evaluation. Journal of the American Medical Informatics Association, 26(4), 314-323. https://doi.org/10.1093/jamia/ocy190
Yang, L., Weston, C., Cude, C., & Kincl, L. (2020). Evaluating Oregon’s Occupational Public Health Surveillance System Based On The CDC Updated Guidelines. American Journal of Industrial Medicine. https://doi.org/10.1002/ajim.23139