Data Quality in Health Facilities:
Describe the problems of having poor data quality and make
recommendations to create an environment that promotes data quality and a
plan for the organization to improve data quality.
Importance of High-Quality Data in Healthcare
Facilities
Enable healthcare providers to accurately and more efficiently diagnose patient thus
reduced medical error and safer health care.
Enables clinicians to make informed decisions through accurate and up-to-date patient
information at the point of care hence high-quality care.
High-quality data means better performance in health facilities.
Help clinicians to improve work productivity and easy meeting of their business goals.
Reduced overall cost of health care due to the improved coordination of health care
services and improved safety.
Easy to monitor health, evaluate and improve healthcare services delivery
Impact of Poor Data Quality in Health Facilities
Increased medical errors, misdiagnose and medical malpractice
Increased health cost due to poor quality care.
Reduced patient safety and care
Reduced performance by health providers
Increased time consume and time wastages as it become hard to access
accurate patient records
Causes of Poor Quality Data
Poor interface design
Typing errors
Calculation errors
Lack of system to correct the detected errors
Lack of control over adherence to guideline and data definitions.
Illegible handwriting from the data sources
Characteristics of High-quality Data
Accurate
Accessible
Current and timely
Consistent
Completeness
Recommendation for Improving Data quality in
Health Facilities
Data training
Recruiting a data governance group
Establish and implement clear guideline on definitions and data entry formats
Creating domain definitions
Giving inadequate time for data entry
Data profiling to uncover data defects
References
References
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).
Raghupathi, W., & Raghupathi, V. (2014). Big data analytics in healthcare: promise and potential. Health Information
Science and Systems, 2(1), 3.
Dudeck, M. A., Weiner, L. M., Allen-Bridson, K., Malpiedi, P. J., Peterson, K. D., Pollock, D. A., … & Edwards, J. R.
(2013). National Healthcare Safety Network (NHSN) report, data summary for 2012, Device-associated module. American
journal of infection control, 41(12), 1148.
Schneeweiss, S. (2014). Learning from big health care data. New England Journal of Medicine, 370(23), 2161-2163.