Determination of Minimum Data Set (Msd) in Echocardiography Reporting System to Exchange With Iran's Electronic Health Record (Ehr) System Publisher



Mahmoudvand Z¹ ; Kamkar M² ; Shahmoradi L¹ ; Nejad AF¹
Source: Acta Informatica Medica Published:2016

Abstract

Background: Determination of minimum data set (MDS) in echocardiography reports is necessary for documentation and putting information in a standard way, and leads to the enhancement of electrocardiographic studies through having access to precise and perfect reports and also to the development of a standard database for electrocardiographic reports. Aim: To determine the minimum data set of echocardiography reporting system to exchange with Iran's electronic health record (EHR) system. Methods: First, a list of minimum data set was prepared after reviewing texts and studying cardiac patients' records. Then, to determine the content validity of the prepared MDS, the expert views of 10 cardiologists and 10 health information management (HIM) specialists were obtained; to estimate the reliability of the set, test-retest method was employed. Finally, the data were analyzed using SPSS software. Results: The highest degree of consensus was found for the following MDSs: Patient's name and family name (5), accepting doctor's name and family name, familial death records due to cardiac disorders, the image identification code, mitral valve, aortic valve, tricuspid valve, pulmonary valve, left ventricle, hole, atrium valve, Doppler examination of ventricular and atrial movement models and diagnoses with an average of. Conclusions: To prepare a model of echocardiography reporting system to exchange with EHR system, creation a standard data set is the vital point. Therefore, based on the research findings, the minimum reporting system data to exchange with Iran's electronic health record system include information on entity, management, medical record, carried-out acts, and the main content of the echocardiography report, which the planners of reporting system should consider. © 2016 Zahra Mahmoudvand, Mehran Kamkar, Leila Shahmoradi, Ahmadreza Farzaneh Nejad.