Importance of High-Quality Data in Healthcare Facilities

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

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



Current and timely



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



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:

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.