Big data analytics has had a transformative effect on health in recent years. Nurses are using analytics solutions to gather more information on their patients' health backgrounds, and physicians are adopting advanced technologies that help them predict future outcomes and develop effective prognoses.
It's important that as the health sector ramps up its attention to data-oriented solutions, it works to maintain data quality. There are grave risks inherent in working with health data - if just one piece of a patient's medical history is inaccurate, it can lead doctors to make erroneous diagnoses and proceed in misguided ways with treatment.
According to Nursing Times, the health industry is now beginning to feel a sense of urgency to recognize the importance of high-quality data. Anne Cooper, clinical informatics adviser for nursing at NHS England, believes that higher standards for data quality are essential.
"Data quality can be defined as data that is timely, complete, accurate, consistent and meaningful," Cooper stated. "We need to ensure the quality of our data when we record information about what we do. We should be recording consistently, accurately and avoiding duplication."
Cooper clarified that health organizations can adopt several effective strategies for ensuring data quality. One is placing a higher level of emphasis on clear, accurate record keeping. If health providers avoid making errors when recording information in the first place, they won't face the burden of having to correct their data clusters later.
Further, healthcare firms need to understand the systems they use for gathering and analyzing information. All employees need to be well versed in how to use the hardware and software tools at their disposal without any risk of malfunction or human error.
Data analysis can have a transformative - perhaps even life-saving - effect on patients everywhere. Quality data is therefore absolutely essential.
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