Читать книгу The Internet of Medical Things (IoMT) - Группа авторов - Страница 33

All data comes from someone, but regrettably, it is not always from someone with flawless data management habits for many healthcare providers. Collecting clean, comprehensive, precise, and correctly structured data for numerous systems is a constant battle for businesses, many of whom are not on the gaining side of the conflict.

In a recent investigation at an ophthalmology clinic, EHR data were only 23.5% matched by patient-reporting data. When patients reported three or more eye problems, their EHR data were absolutely not in agreement.

Poor usability of EHRs, sophisticated processes, and an incomplete understanding why big data is crucial to properly collect all can contribute to quality problems that afflict data during its life cycle.

Providers can begin to improve the data capture routines by prioritizing valuable data types for their specific projects, by enlisting the data management and integrity expertise of professional health information managers, and by developing clinical documentation improvement programs to train clinicians on how to ensure data are useful for downstream analysis.