Data rich, information poor (DRIP) syndrome: is there a treatment?
DRIP (data rich, information poor) syndrome is paralyzing the performance improvement efforts of many healthcare organizations. Symptoms of DRIP syndrome include the use of an abundance of indicators and the predominant use of a retrospective medical record review to collect data. Often, too many indicators are used because the organization is still subscribing to a traditional quality assurance methodology for performance improvement. In these cases, quality assurance programs monitor multiple areas of performance assuming that, except for occasional outliers, the results will be acceptable. Another cause of an unmanageable number of indicators may be a lack of understanding of JCAHO measurement requirements. The ¿prescription¿ includes changing to a continuous quality improvement culture, learning measurement requirements, inventorying current data collection to identify and eliminate useless data and aligning data collection with the goals and objectives of the organization. An organization should collect only data that is required to improve performance and meet accreditation and regulatory requirements. Data collection should be automated and built into work processes as much as possible. Ideally, a well-integrated computer system offers access to real-time information and permits timely or even proactive performance.
Goodwin
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D001803:Blood Transfusion / Q000592:standards; D003625:Data Collection / Q000592:standards; D005246:Feedback; D005568:Forms and Records Control; D006739:Hospital Administration / Q000592:standards*; D006751:Hospital Information Systems / Q000592:standards*; D007591:Joint Commission on Accreditation of Healthcare Organizations; D008485:Medical Audit; D008499:Medical Records / Q000592:standards; D011785:Quality Assurance, Health Care / Q000458:organization & administration / Q000592:standards*; D011872:Radiology Department, Hospital / Q000592:standards; D013597:Systems Analysis; D014481:United States