Electronic Health Records: Benefits and Challenges for Data Quality

Data quality (DQ) issues in Electronic Health Records (EHRs) are a noticeable trend to improve the introduction of an adaptive framework for interoperability and standards to large-scale health Database Management Systems (DBMS). In addition, EHR technology provides portfolio management systems that allow Health Care Organisations (HCOs) to deliver higher quality of care to their patients than possible with paper-based records. The EHRs are in high demand for HCOs to run their daily services as increasing numbers of huge datasets occur every day. An efficient EHRs system reduces data redundancy as well as system application failures and increases the possibility to draw all necessary reports. Improving DQ to achieve benefits through EHRs is neither low-cost nor easy. However, different HCOs have several standards and different major systems, which have emerged as critical issues and practical challenges. One of the main challenges in EHRs is the inherent difficulty to coherently manage incompatible and sometimes inconsistent data structures from diverse heterogeneous sources. As a result, the interventions to overcome these barriers and challenges, including the provision of EHRs as it pertains to DQ will combine features to search, extract, filter, clean and integrate data to ensure that users can coherently create new consistent data sets.