Certified Healthcare Technology Specialist (CHTS) Process Workflow & Information Management Redesign Practice Exam

What is a systematic cause of insufficient data quality?

1. Random causes of error

2. User error in data entry

3. Greater predictability

4. Technical malfunctions

The correct answer is: Greater predictability

Insufficient data quality can often be attributed to systematic causes, which are consistent and repeatable factors that lead to errors or inaccuracies in data. Greater predictability, while generally a positive aspect in many contexts, does not directly cause issues with data quality. Instead, it suggests a stable and consistent environment where data can be reliably understood and analyzed. On the other hand, user error in data entry reflects a systematic cause of insufficient data quality because it often occurs consistently due to a lack of training, improper interface design, or misunderstanding of data requirements. Technical malfunctions, too, can lead to ongoing data quality issues stemming from predictable software or hardware failures. Random causes of error point to unpredictable anomalies that occur sporadically and do not contribute to systematic problems. Therefore, while greater predictability may be a desired characteristic, it does not systematically lead to a degradation of data quality, which stands in contrast to the true sources of data quality issues.