An exploratory case study to understand primary care users and their data quality tradeoffs

Abstract:

Primary care data is an important part of the evolving healthcare ecosystem. Generally, users in primary care are expected to provide excellent patient care and record high-quality data. In practice, users must balance sets of priorities regarding care and data. The goal of this study was to understand data quality tradeoffs between timeliness, validity, completeness, and use among primary care users. As a case study, data quality measures and metrics are developed through a focus group session with managers. After calculating and extracting measurements of data quality from six years of historic data, each measure was modeled with logit binomial regression to show correlations, characterize tradeoffs, and investigate data quality interactions. Measures and correlations for completeness, use, and timeliness were calculated for 196,967 patient encounters. Based on the analysis, there was a positive relationship between validity and completeness, and a negative relationship between timeliness and use. Use of data and reductions in entry delay were positively associated with completeness and validity. Our results suggest that if users are not provided with sufficient time to record data as part of their regular workflow, they will prioritize spending available time with patients. As a measurement of a primary care system's effectiveness, the negative correlation between use and timeliness points to a self-reinforcing relationship that provides users with little external value. In the future, additional data can be generated from comparable organizations to test several new hypotheses about primary care users.

Año de publicación:

2017

Keywords:

• Data Mining
• PRIMARY CARE
• tradeoffs
• Statistical Analysis
• Case study

Fuente:

scopus