Pouyan Esmaeilzadeh1, Tala Mirzaei2. 1. Department of Information Systems and Business Analytics, College of Business, Florida International University, Miami, FL, 33199, United States. Electronic address: pesmaeil@fiu.edu. 2. Department of Information Systems and Business Analytics, College of Business, Florida International University, Miami, FL, 33199, United States.
Abstract
OBJECTIVE: Consumers' willingness to allow the distribution of their health data is a prerequisite for the success of any health information exchange (HIE) initiative. Several mechanisms are being used by healthcare organizations to exchange health information electronically. Our goal is to investigate how patients' preferences regarding information exchange (i.e., privacy concern, opt-in intention, and perceived health information sensitivity) are affected by different HIE models and exchange architectures. METHODS: We designed a series of scenarios for controlled online experiments. Totally, 1416 respondents participated in seven experiments. Each experiment includes a separate scenario and 27 questions to measure outcome variables and demographics. Data were collected from a wide range of adult population in the U.S. and all the experiments were performed in English. RESULTS: The findings demonstrate that there are significant differences in patients' perceptions of different HIE mechanisms in terms of privacy concern and opt-in intention. Consumers believe that the patient-controlled HIE at the regional level is the most preferred model to protect health information privacy and they are willing to opt-in to this model. However, there is no solid evidence to show that different HIE mechanisms would affect the consumers' perceived health information sensitivity. CONCLUSIONS: This study supports the importance of patient-controlled HIE models that potentially enable patients to access, manage, integrate, and share their medical information with multiple healthcare organizations. The results show in-depth consumer adoption patterns across multiple HIE models and architectures which are required to identify optimal approaches for HIE implementation using different exchange mechanisms.
OBJECTIVE: Consumers' willingness to allow the distribution of their health data is a prerequisite for the success of any health information exchange (HIE) initiative. Several mechanisms are being used by healthcare organizations to exchange health information electronically. Our goal is to investigate how patients' preferences regarding information exchange (i.e., privacy concern, opt-in intention, and perceived health information sensitivity) are affected by different HIE models and exchange architectures. METHODS: We designed a series of scenarios for controlled online experiments. Totally, 1416 respondents participated in seven experiments. Each experiment includes a separate scenario and 27 questions to measure outcome variables and demographics. Data were collected from a wide range of adult population in the U.S. and all the experiments were performed in English. RESULTS: The findings demonstrate that there are significant differences in patients' perceptions of different HIE mechanisms in terms of privacy concern and opt-in intention. Consumers believe that the patient-controlled HIE at the regional level is the most preferred model to protect health information privacy and they are willing to opt-in to this model. However, there is no solid evidence to show that different HIE mechanisms would affect the consumers' perceived health information sensitivity. CONCLUSIONS: This study supports the importance of patient-controlled HIE models that potentially enable patients to access, manage, integrate, and share their medical information with multiple healthcare organizations. The results show in-depth consumer adoption patterns across multiple HIE models and architectures which are required to identify optimal approaches for HIE implementation using different exchange mechanisms.
Authors: M J Sabatino; C V Gans; A J Zynda; J S Chung; S M Miller; P L Wilson; C H Jo; H B Ellis Journal: J Child Orthop Date: 2019-08-01 Impact factor: 1.548