The Differing Effect of Gender and Clinical Specialty on Physicians' Intention to Use Electronic Medical Record

Abstract

Background The use of electronic medical record (EMR) is anticipated to bring benefits for patients, physicians, and organizations. But limited physicians' acceptance of EMR presents a serious threat to its effective implementation. Objectives The current study incorporates technology acceptance model (TAM) with two antecedents, gender, and clinical specialty and one context-specific factor, financial incentives, to identify the factors that influence physicians' intention to use EMR in Taiwan. Methods The survey methodology was used to collect data from the physicians, working in the regional hospital that had implemented EMR system. A total of 119 out of 213 questionnaires returned in a response rate of 56%. But four responses were considered ineffective due to missing values. The structural equation modeling (SEM) technique was employed to analyze the research framework. Results The partial least squares (PLS) regression indicated that three factors perceived usefulness, financial incentives, and attitude toward using EMR significantly affect physicians' intention. But concerning perceived ease of use (PEOU), an insignificant path coefficient was reported. Additionally, regression analysis showed gender, and clinical specialty positively influenced physicians' intention to use EMR. Discussion and Conclusions The proposed research framework contributes to the conclusive explanation for interpreting physicians' intention to use EMR. Physicians generally have a higher level of computer literacy. Therefore, the factor of PEOU could not be critical regarding adopting new health information technology (HIT). This study also brings perspectives from the gender, and clinical differences have primarily been missing in the literature of the physicians' intention to use HIT. In doing so, it infers how gender, and clinical specialty, may complement (and in some instances, reinforce) the influence of technological and attitudinal factors of HIT use. Thus, health care providers must take these factors into consideration in the development and validation of the theories regarding the intention to use EMR.

Role of Infodemics on Social Media in the Development of People’s Readiness to Follow COVID-19 Preventive Measures

“…Three experts have received their Ph.D. degrees already, and another one will receive her Ph.D. degree shortly. The age distribution of the experts was between 40-52 years (3 of them belong to the 40-50 group and 1 belongs to [45][46][47][48][49][50]. A significant concern to ask those experts to serve as the panel members is their expertise areas that are much more related to information science.…”

“…A positive attitude refers to the individual's perception of a specific behavior. Previous studies validated that citizens observe guidelines, necessities, and strategies while having a positive attitude [13,48,49,58]. On the other hand, infodemics negatively influence citizens' attitude, influencing them to give away a specific behavior.…”

“…In their study on adopting healthcare technology, Sun et al [13] theorized that attitude plays an essential role in impacting an individual's behavioral intention. Hwang et al [49] explored physicians' attitude towards healthcare technology that influenced their intention to use electronic medical records (EMR). Venkatesh et al [50] reported that attitude towards information technology (IT) is the second most significant predictor regarding physicians' intention to use telemedicine services.…”

Physicians’ Perceptions as Predictors of the Future Use of the National Death Information System in Peru: Cross-sectional Study

“…When reviewing the predictor variables of behavioral intention to use, in the cases under study, considerable heterogeneity was observed. Some studies found only 1 primary variable from TAM, such as perceived usefulness or perceived ease of use, associated with intention to use [30,31], and other studies reported subjective norm or job relevance directly related to behavioral intention to use, without being intermediated by perceived usefulness [30][31][32]. There are also studies that describe predictors of perceived ease of use, such as job relevance, management support, and training or computational self-efficacy [33,34], and some others found that age, sex, or clinical specialty were predictors of both perceived usefulness and perceived ease of use [31].…”

“…Some studies found only 1 primary variable from TAM, such as perceived usefulness or perceived ease of use, associated with intention to use [30,31], and other studies reported subjective norm or job relevance directly related to behavioral intention to use, without being intermediated by perceived usefulness [30][31][32]. There are also studies that describe predictors of perceived ease of use, such as job relevance, management support, and training or computational self-efficacy [33,34], and some others found that age, sex, or clinical specialty were predictors of both perceived usefulness and perceived ease of use [31]. This variability supports the idea of contextualizing the results of each study not only referring to the type of technology used but also to the organizational culture in which the technology will work.…”