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The effects of data entry structure on patients' perceptions of information quality in Health Information Exchange
Pouyan Esmaeilzadeh1, Tala Mirzaei2, Mahed Maddah3
1Department of Information Systems and Business Analytics, College of Business, Florida International University (FIU), Modesto A. Maidique Campus, 11200 S.W. 8th St, RB 261B, Miami, FL 33199, United States.
Background And Objective:
To exchange patient health information using Health Information Exchange (HIE) projects, such information first should be collected thoroughly using an appropriate data entry interface that reinforces information quality (IQ). Assessment of the given data interface based on its structure level may give us a better understanding of patients' attitudes toward information-sharing efforts. The main objective of this study is to examine the effects of data structure on perceptions and attitudes of patients toward the quality of health information that may be shared through HIE networks.
Materials And Methods:
Eight experiments were conducted to examine the impact of different design of information collection interfaces (structured vs. unstructured) to record two types of health information (sensitive vs. non-sensitive) that can be used for two types of sharing purposes (health care vs. marketing).
Results:
Results show that the degree of data entry structure can significantly influence patients' perceptions of completeness, accuracy, psychological risk, accessibility of data, concise representation, and understandability of health information.
Discussion:
There is a connection between data entry interface design and patients' perceptions of the quality of health information used in HIE networks, which in turn, could lead to the development of best practices in interface design and data collection techniques. This may also improve interactions between patients and healthcare entities, enhance patients' attitudes toward data collection procedures and HIE, and help healthcare providers use complete and accurate databases.
Conclusions:
We propose that healthcare professionals can tailor data entry interfaces based on the sensitivity of medical data and the purpose of information exchange.
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