Conceptual map

Running head: Data quality and integration Introduction The main concern is to explore and optimize the available data quality and data integration issues for use by Customer Relationship Management (CRM) system. Patient data/information is the master tool in this framework.
Sources of patient data in a healthcare organization can be either internal or external.
Internal sources include administrative departments, medical department and pharmacy department. External sources include demographic data, government data, syndicated data, web-based data and externally purchased business data.
Patient data is useful in healthcare organizations’ departments on different operating systems like healthcare business, system for reporting purposes, system for healthcare business intelligence for example data marts, data warehouses and online analytical processing (OLAP ) systems.
The framework ensures high quality data and integrated patient data. Ensuring high quality data involves cleansing, standardization, enhancement, consolidation and quality data collection.
Quality data collection enhances the quality of services offered as measured by a focus on patients’ needs, speed of response to enquiries and problems and accuracy of information. It also enhances quality of information as measured by timeliness, accuracy, accessibility, completeness, relatability, uniqueness and validity.
Approaches for incorporating data quality into CRMs data warehouse include defining data quality expectations and metrics, which can be done by the use of metadata or data quality metrics, indentifying poor data and its limitations, assessing data quality limitation and improving data quality through human experts or state-of-the-art tools.
Data integration is essential for unified view of the patients. It also allows combination o information on patients’ products and better understanding of patients’ needs and its findings are useful in planning, marketing and sales efforts. Data integration tools include statistical modeling, campaign management and data mining.
Conclusion
All these lead to improved data quality and subsequently lead to improved results, reduced cost and informed healthcare decisions. They also improve patients’ acquisition and retention, enhance customer services, increase patients’ loyalty and preference and maximize the lifetime value of each patient.

Reference
Alshawi, S. et al. (2003). Healthcare information management: the integration of patients’ data. Retrieved, February 26, 2009 from http://www. emeraldinsight. com/Insight/viewContentItem. do; jsessionid= 26B7258DE12ADE23B5D324BBA4724D84? contentType= Article&contentId= 852239