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4 MAIN FINDINGS
AND RECOMMENDATIONS
From the point of view of this work intrinsic data
quality, data quality context, data quality
representation and data quality accessibility were
identified as major data quality characteristics. Data
availability, data format, data accuracy and data
accessibility arise as major problems identified,
relating to high-quality data collection on EHRs.
There are solutions to solve such problems like early
recognition of development of those problems and
direct physician entry or physician entry control.
Also, structured encounter forms and well structured
and designed EHRs that include anticipatory
prompts and that allow data linkage and aggregation
to data consumers are part of the solutions available.
A broad use of such systems for the most daily tasks
possible without compromising the goal of
compliant documentation and standard coding use
are also to consider. Other relevant issues are
periodic accuracy monitoring and feedback, better
research methods explanation, evidence-based
guidelines, automated data capture from patient
information systems and others. If attended they can
help reducing data quality problems in order to
improve EHRs suitability for general everyday use.
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