The impact of data entry structures on perceptions of individuals with chronic mental disorders and physical diseases towards health information sharing

BACKGROUND AND OBJECTIVE Collecting, integrating, and sharing mental and physical health information can enhance the care process of patients and improve the completeness of patient databases in the health information exchange (HIE) networks. There is a need to encourage patients with physical and mental disorders to share their health information with providers. Data entry interfaces are suggested as an important factor affecting the quality of information. However, little is known about whether individuals with different diseases (mental and physical) care for the data entry structure in sharing personal health information (PHI). MATERIALS AND METHODS We conduct four experiments to examine the impact of different health problems (mental vs. physical) and types of data entry interfaces (structured vs. unstructured) on individuals' perceptions of information quality and their willingness to share their health information. RESULTS Findings demonstrate that the type of disease and degree of data entry structure significantly influence individuals' perceptions of usefulness, accessibility, concise presentation, understandability, psychological risk, privacy concern, stigma, and willingness to share health information. DISCUSSION People with mental disorders prefer structured data interfaces as they perceive that a high degree of data entry structure can protect their privacy and mitigate stigma and psychological risk more than unstructured interfaces. Individuals with physical illnesses favor structured interfaces for their format, which is brief, comprehensive, accessible, useful, and understandable. People suffering from physical diseases are more likely to share their information when a highly-structured data entry interface is used. Moreover, individuals with mental disorders are less likely to disclose their information when providers collect health records using an unstructured data entry interface. CONCLUSIONS This study suggests that the best level of structure for data entry interfaces could be designed at the point of care consistent with patients' health status and their type of diseases to improve the success of HIE networks.

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