I want to share an example of a failed system (according to me) but still is operating. It’s a system called “X”; the system connects to other systems that overlapped each other. It’s like EMR, collected data and transactions are recorded. The “X” is to record all “ongoing” activities taken throughout the insurance claim cycle, which involved by two departments, the claim and the medical. When a claim is finalized, all data and transactions must be transferred to the “Z” system, which has other back-office departments involved. The transfer is a 95% manual with duplicated data entering, and unformatted datasets. Often, stakeholders end up with using a spreadsheet with another data entering manually out of the “X” and the “Z” instead of extracting out of it. The system is well-designed with advanced data options, but the problem is that the data is not interoperable among systems and does not meet the workflow’s needs in operational and decision-making requirements. The multiple data entry on systems leads to workload and non-valued add steps. The failure, for me, is mainly because of data quality and design if data exchange.
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This reply was modified 3 years, 7 months ago by
Ameen.