The use of Big data by healthcare continues to mature; the more sophisticated marketing of other sectors is being followed often. This maturity is based on the recognition by the health leaders that the information needs to be broadened and strategic. Big data was primarily used by medical networks to improve the health of the people, which would be necessary for the overall health value chain. Collectively, the data collected from certain high-risk patients are used successfully to slow healthcare inflation costs, based on age, sex, or medical history-health networks. Healthcare now needs to move its data management game to a business level that covers the end-to-end value chain. To make this shift, the focus is needed beyond patient information.
Health data governance and patient identity management go together. It is essential that the correct data is accurately connected to the right patient and HIM professionals are too aware of the challenges of patient matching and record management. The lack of interoperability with Electronic health records (EHR) and national health information collection standards has left organizations flooded with duplicate or disconnected records. The problem continues because consolidation of healthcare continues to rush through, and the data exchanges between suppliers are exponentially increasing the danger and problem of patient identification errors.
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Duplicate patient records often cause multiple name changes, data entry errors, and lack of data standardization. The problem is only compounded by a type or absence of one digit on the day of birth address or telephone number. Multiple providers in their community are moving, marrying, divorcing, and visiting patients—new data are being created, and patient misidentifications are increasing.
A survey called “Perspectives in Health Information Management” published by the AHIMA Foundation examined 400,000 pairs of double-size records found to be the root causes to patient matching problems associated with social security differences, middle names, first and last names, date of birth, and gender. The results show that better data management is essential to positive patient identification and standardized data collection processes.
As the industry enters 2019, providers are required to synthesize increasingly accurate diagnosis, treatment plans, and financial strategies. They need to make sure that this data is presented meaningfully and intuitively to key stakeholders to ensure that the information is absorbed and applied in order to address pressing business and clinical issues.