A Framework for Leveraging Business Intelligence to Manage Transactional Data Flows between Private Healthcare Providers and Medical Aid Administrators

Abstract

Leaders at company AB within different functional areas needed to effectively facilitate the integration of BI initiatives into business operations. Semi-structured interviews were used to extract key concepts and attributes relevant to business functional areas, from business leaders and these were related to BI techniques. Thematic analysis on collected data was used to identify critical success factors (CSFs). A conceptual framework was developed which comprises business CSFs that are related to opportunities for value derivation from BI activities. This framework can be used as a guideline by Company AB for opportunity assessment and BI implementation, thereby enabling Company AB to leverage the value of BI. A decision tree predictive analytics model whose business rules potentially assist in proactive churn management for companies that have customer transaction volumes as a feature, was developed. This analytics model shows that claims that are not submitted to a client's historically most frequently used medical aids and variances in transactional claim volumes of more than 20%, are good indicators of a client churn. Companies that provide value to the private healthcare industry via the facilitation and management of transactional data flows between healthcare providers and medical aid administrators will benefit from the insights derived from this model.