Medical Healthcare Records Data Quality Order Instructions: Data Quality  For your selected organization, create three sample Medical Records with the mandatory fields (1 per page. Use these fields to capture pertinent data as if you were an actual patient. Using the guidelines from MRI and AHIMA indicate how the information would be captured (paper or electronically).

How would the quality of data you evaluate compare with your expectations?

Medical Healthcare Records Data Quality Module Overview

Healthcare systems are driven by data, which is translated into useful information that can be used by organizations, providers, researchers, and consumers. The information used must be reliable so decisions that are made are appropriate, using the data and information available. When there are errors in the data, patient care, research, and courses of action suffer. This module examines the impact of poor data quality and how to prevent it.

Data Quality

The management of health information is a major concern from both a quality of care as well as a medicolegal perspective. There is a need for quality of data to ensure safe and appropriate patient care. One of the biggest challenges in capturing reliable and valid data is the understanding of the importance of data and protecting it from all levels of the organization, which include support staff, providers, administrators, and executives.

The problem with poor data quality is that data is gathered at the user level. Clinical providers and support staff typically enter data. When there are mistakes in data entering, it translates into problems in patient care, reimbursement, and research. The problem of poor data crosses departments and organizations, filtering into decisions that are made based on the data.

As a result of the importance of data quality, two organizations were developed: American Health Information Management Association (AHIMA) and Medical Records Institute (MRI). Both organizations developed standards to facilitate the move from paper to an electronic health information system. AHIMA developed a data quality model and MRI used a consensus group to present some of the challenges of capturing data electronically, including recommendations.

Medical Healthcare Records Data Quality Required Reading

Lorence, D., & Chen, L. (2008). Disparities in Health Information Quality Across the Rural-Urban Continuum: Where is Coded Data More Reliable? Journal of Medical Systems, 32(1), 1-8. Retrieved from ProQuest Computing. (Document ID: 1897506551).

Mooney, S. E. (1998, October). Health information management experts outline steps to data quality. Clinical Data Management, 5(7), 10. Retrieved from ProQuest Nursing & Allied Health Source. (Document ID: 35023770).

American Health Information Management Association (1998). Practice Brief: Data Quality Management Model.

Waegemann, C. P., Tessier, C., Barbash, A., Blumenfeld, B. H., Borden, J., Brinson, R. M., Jr., Cooper, T. … Weber, J. (2002). Healthcare documentation: A report on information capture and report generation. Medical Records Institute.

Medical Healthcare Records Data Quality Sample Answer

How the mandatory fields would compare with my expectations.

In all the three samples, the mandatory fields include patient’s identifiers, the reason for a hospital visit, review of the systems, allergies, diagnosis and care plan. The last sample only captures on patient’s physical examinations, and therefore leaves out on diagnosis and treatment. The benefit of mandatory fields in the Electronic Medical record is that they act as reminders and enhances patient’s safety. This implies that the healthcare providers must be extra careful when filling the field in order to store capture vital information. The mandatory field must be updated regularly in order to prevent medical errors (Bowman, 2013).

Therefore, it is important for a healthcare provider to take time and decide the mandatory fields important in their practice, and ensure that the Electronic medical record is configured in a way that one cannot bypass or disable the fields.  My expectation of these mandatory fields is that they will help improve patient safety, efficiency and quality, as well as help, assess potential health disparities. This information will also help maintain patient information private and enhance coordinated care (Linder,  Schnipper,  & Middleton,  2012).

Medical Healthcare Records Data Quality References

Linder, J. A., Schnipper, J. L., & Middleton, B. (2012). Method of electronic health record documentation and quality of primary care. Journal of the American Medical Informatics Association : JAMIA, 19(6), 1019–1024. http://doi.org/10.1136/amiajnl-2011-000788

Bowman, S. (2013). Impact of Electronic Health Record Systems on Information Integrity: Quality and Safety Implications. Perspectives in Health Information Management, 10(Fall), 1c.
Systematic data collection form

On-call physician medical record

Medical record: Physical Examination