A minimum data set and empirical model for population health status assessment

Evaluating the demographic and clinical minimum data sets of Iranian National Electronic Health Record

BACKGROUND

Designing a standard data set is necessary to overcome the dispersion of data among different health information systems. The objective of this study was to evaluate the current demographic and clinical minimum data sets (MDSs) of Iranian National Electronic Health Record (known as SEPAS) and to identify most necessary data elements.

METHODS

Data were collected using a list of current demographic and clinical data of SEPAS and a self-administered questionnaire. All faculty members of six health related fields and the hospital authorities, and IT and HIM administrators of 6 hospitals in Kerman University of Medical Sciences were invited to participate in this study. The content validity of the questionnaire was confirmed by six medical informatics and HIM experts and the reliability was determined by Cronbach's alpha (α =0.95). SPSS v18 was used to generate descriptive statistics.

RESULTS

Survey results indicated that 15 data elements should become mandatory elements of MDS for communicating data to SEPAS. These elements include patient's name, surname, father's name, nationality, cell number, job, residential address, residence place, passport number (for non-Iranian patients), diagnosis date, death time, death place and the unit of the hospital where the patient died. Moreover, participants suggested 33 additional demographic and clinical data elements to be communicated mandatorily to SEPAS.

CONCLUSION

The results of this study showed that the minimum data sets of Iranian national electronic health record needs to be revised. Using the proposed MDSs by this study can improve the quality and efficiency of information and reduce redundancy by adding necessary data and preventing communication of unnecessary data. The method employed in this study can be used for investigating, refining and completing the MDSs of other health information systems.

NC CATCH: Advancing Public Health Analytics

The North Carolina Comprehensive Assessment for Tracking Community Health (NC CATCH) is a Web-based analytical system deployed to local public health units and their community partners. The system has the following characteristics: flexible, powerful online analytic processing (OLAP) interface; multiple sources of multidimensional, event-level data fully conformed to common definitions in a data warehouse structure; enabled utilization of available decision support software tools; analytic capabilities distributed and optimized locally with centralized technical infrastructure; two levels of access differentiated by the user (anonymous versus registered) and by the analytical flexibility (Community Profile versus Design Phase); and, an emphasis on user training and feedback. The ability of local public health units to engage in outcomes-based performance measurement will be influenced by continuing access to event-level data, developments in evidence-based practice for improving population health, and the application of information technology-based analytic tools and methods.