Information systems with emphasis on business rules for demographics: A kaizen strategy for data quality in public health informatics.

摘要

Good demographic data quality is important for person-centric surveillance and care to succeed in Public Health Informatics. This study proposes and demonstrates a kaizen strategy for data quality. Kaizen principles are change for the better and continuity in the process; principles supported in this research by a business rules approach. Rules facilitate representation of knowledge, control data and support information systems.; A business rule theory for data quality was developed using Toulmin's model and tested on the demographic parameters of an actual public health information system. The theory's claim is that business rules for demographic data cause better data quality in public health information systems. Frameworks of data quality and business rule guidelines were developed to facilitate theory testing. The CDC National Electronic Disease Surveillance System (NEDSS) was the testing platform focusing on the NEDSS Logical Data Model (NLDM).; The study identified nineteen variables of importance in the public health demographic domain. Research demonstrated that NLDM demographics map well to the business rule guidelines, resulting in good data quality and validating the developed theory. NLDM is more comprehensive than the rule guidelines in certain demographics - an expanded domain for name use, martial status and education codes; greater details in location and contact data; ability to represent non-traditional occupations.; Demographic gap areas in NLDM identified by the study - non-representation of vital demographics like religion, living arrangement and disability status; restricted domain for a sex variable; lack of clear definitions and code specifications for some attributes. NLDM needs to accommodate gender and genotype data due to their importance in the future. The research presents a set of recommendations for NEDSS: address critical data quality issues; broader conceptualization, dissemination and management of business rules; mandated enforcement of business rules (standards).; This dissertation presents a best practices paradigm in the organizational context of public health demographic data quality imposed by the architectural structure of business rules. Findings from this work will help conceptualize clinical, community and consumer health information systems as part of a National Health Information Network and support integrative research in Public Health Informatics.