scholarly journals Nurses’ Readiness in the Adoption of Hospital Electronic Information Management Systems in Ghana: The Application of the Structural Equation Modeling and the UTAUT Model

SAGE Open ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 215824402093181
Author(s):  
Zhou Lulin ◽  
Joseph Owusu-Marfo ◽  
Henry Asante Antwi ◽  
Maxwell Opuni Antwi ◽  
Xinglong Xu
Keyword(s):  
Health Care ◽  
Structural Equation Modeling ◽  
Information Management ◽  
Structural Equation ◽  
Health Care Facilities ◽  
Management Systems ◽  
Equation Modeling ◽  
Successful Implementation ◽  
Electronic Information ◽  
Information Management Systems

Electronic health record (EHR) systems have become a basic need in most health care facilities worldwide. However, little can be said about the developing nations’ use of it. Nevertheless, Ghana is one of the very few countries in Africa to start using EHRs. Nursing is a field that has been substantially influenced by the use of hospital electronic information management systems (HEIMS). More importantly, the successful implementation of any mHealth and EHRs critically depends on user acceptance. Therefore, as nurses in Ghana work at the frontline of the health care system in the country with access to vital records about the patients, it is important to assess what motivates them to use the system. This study applied a non-experimental survey design. An electronic platform questionnaire on smartphones was used to collect data on 660 nurses. Statistically, AMOS structural equation modeling (SEM) was employed to examine the research model. “Behavioral intention” (BI) to HEIMS use was significantly predicted by effort expectancy (EE) ( p <.001). Notably, EE had an effect on BI, which explains the 37% variance in the intention of nurses to use HEIMS. Likewise, use behavior (UB) of HEIMS was also significantly predicted by performance expectancy (PE) ( R2 = .25), EE ( R2 = .311), and BI ( R2 = .397), and all explained 46% of the variance in nurses’ acceptance of HEIMS. Nurses’ acceptance of HEIMS was significantly predicted by PE, EE, and BI. Based on these findings, hospital administrators should put measures in place that will boost the nurses’ confidence in using HEIMS as well as endeavor to adopt and implement a very user-friendly system.

The Effects of Implementing an Accreditation Process on Health Care Quality Using Structural Equation Modeling

2018 ◽  
Vol 37 (4) ◽  
pp. 317-324 ◽  
Author(s):  
Parisa Pourrabia ◽  
Mohammadkarim Bahadori ◽  
Seyed Mojtaba Hosseini ◽  
Ramin Ravangard
Keyword(s):  
Health Care ◽  
Structural Equation Modeling ◽  
Structural Equation ◽  
Health Care Quality ◽  
Accreditation Process ◽  
Care Quality ◽  
Equation Modeling

scholarly journals Barriers and Facilitators to Implementation of Medication Decision Support Systems in Electronic Medical Records: Mixed Methods Approach Based on Structural Equation Modeling and Qualitative Analysis (Preprint)

2020 ◽  
Author(s):  
Se Young Jung ◽  
Hee Hwang ◽  
Keehyuck Lee ◽  
Ho-Young Lee ◽  
Eunhye Kim ◽  
...  
Keyword(s):  
Structural Equation Modeling ◽  
Decision Support ◽  
Quantitative Analysis ◽  
Qualitative Analysis ◽  
Structural Equation ◽  
Adverse Drug Events ◽  
Ease Of Use ◽  
Barriers And Facilitators ◽  
Equation Modeling ◽  
Successful Implementation

BACKGROUND Adverse drug events (ADEs) resulting from medication error are some of the most common causes of iatrogenic injuries in hospitals. With the appropriate use of medication, ADEs can be prevented and ameliorated. Efforts to reduce medication errors and prevent ADEs have been made by implementing a medication decision support system (MDSS) in electronic health records (EHRs). However, physicians tend to override most MDSS alerts. OBJECTIVE In order to improve MDSS functionality, we must understand what factors users consider essential for the successful implementation of an MDSS into their clinical setting. This study followed the implementation process for an MDSS within a comprehensive EHR system and analyzed the relevant barriers and facilitators. METHODS A mixed research methodology was adopted. Data from a structured survey and 15 in-depth interviews were integrated. Structural equation modeling was conducted for quantitative analysis of factors related to user adoption of MDSS. Qualitative analysis based on semistructured interviews with physicians was conducted to collect various opinions on MDSS implementation. RESULTS Quantitative analysis revealed that physicians’ expectations regarding ease of use and performance improvement are crucial. Qualitative analysis identified four significant barriers to MDSS implementation: alert fatigue, lack of accuracy, poor user interface design, and lack of customizability. CONCLUSIONS This study revealed barriers and facilitators to the implementation of MDSS. The findings can be applied to upgrade MDSS in the future.

scholarly journals Testing Kissick’s Iron Triangle - Structural Equation Modeling Analysis of a Practical Theory

2021 ◽  
Author(s):  
Brad Beauvais ◽  
Clemens Scott Kruse ◽  
Lawrence Fulton ◽  
Matthew Brooks ◽  
Michael Mileski ◽  
...  
Keyword(s):  
Health Care ◽  
Structural Equation Modeling ◽  
Structural Equation ◽  
Health Care Policy ◽  
Health Care Cost ◽  
Equation Modeling ◽  
Cost Curve ◽  
Hospital Data ◽  
Policy And Practice ◽  
Medicare Data

The purpose of this research is to determine if the tradeoffs that Kissick proposed among cost containment, quality, and access remain as rigidly interconnected as originally conceived in the contemporary health care context. Although many have relied on the Kissick model to advocate for health policy decisions, to our knowledge, the model has never been empirically tested. Some have called for policy makers to come to terms with the premise of the Kissick model tradeoffs, others have questioned the model given the proliferation of quality enhancing initiatives, automation, and information technology in the health care industry. One wonders whether these evolutionary changes alter or disrupt the originality of the Kissick paradigms themselves. Methods: Structural Equation Modeling (SEM) was used to evaluate the Kissick hypothetical relationships among the unobserved constructs of cost, quality, and access in hospitals for the year 2018. Hospital data were obtained from Definitive Healthcare a subscription site which contains Medicare data as well as non-Medicare data for networks, hospitals, and clinics (final n= 2,766). Results: Reporting significant net effects as defined by our chosen study variables, we find that as quality increases costs increase, as access increases quality increases, and as access increases, costs increase. Policy and Practice Implications: Our findings lend continued relevance to a balanced approach to health care policy reform efforts. Simultaneously bending the health care cost curve, increasing access to care, and advancing quality of care is as challenging now as it was when the Kissick model was originally conceived.

scholarly journals “Assessment of the social influence and facilitating conditions that support nurses’ adoption of hospital electronic information management systems (HEIMS) in Ghana using the unified theory of acceptance and use of technology (UTAUT) model”

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Lu Lin Zhou ◽  
Joseph Owusu-Marfo ◽  
Henry Asante Antwi ◽  
Maxwell Opuni Antwi ◽  
Arielle Doris Tetgoum Kachie ◽  
...  
Keyword(s):  
Information Management ◽  
Behavioral Intention ◽  
Management Systems ◽  
Unified Theory ◽  
Electronic Information ◽  
Utaut Model ◽  
Use Of Technology ◽  
The Social ◽  
Information Management Systems ◽  
Facilitating Conditions

Abstract Background Hospital electronic information management systems (HEIMS) are widely used in Ghana, and hence its performance must be carefully assessed. Nurses as clinical health personnel are the largest cluster of hospital staff and are the pillar of healthcare delivery. Therefore, they play a crucial role in the adoption and assessment of HEIMSs in Ghana. This report sought to assess the “Social Influence” (SI) and “Facilitating Conditions” (FC) that support Nurses’ Acceptance of HEIMS in Ghana using the “Unified Theory of Acceptance and Use of Technology” (UTAUT) model. Methods This study applied a non-experimental survey design. An electronic platform questionnaire on smartphones was used to collect data on 660 nurses. Statistically, AMOS Structural Equation Modelling (SEM) version 22.0 was employed to examine the research model. Results “Behavioral Intention” (BI) to HEIMS use was significantly predicted by SI and FC (p < 0.001). Notably, both SI and FC had an influence on nurses’ use behavior (UB) with behavioral intention (BI) as the mediator, which explains a total of 42.1% variance in the intention of nurses to use HEIMS. Likewise, UB of HEIMS was also significantly predicted by SI (R2 = 43.2) and BI (R2 = 0.39.6) with both constructs explaining a total of 51.7% of the variance in nurses’ acceptance to use HEIMS. Conclusion Nurses’ adoption of HEIMS in terms of the UB was influenced by SI and BI, whiles SI and FC had the strongest influence on BI (serving as mediator) of UB to adopt and use HEIMS among the nurses in Ghanaian hospitals.

scholarly journals Factors Influencing the Willingness to Pay for Aquaponic Products in a Developed Food Market: A Structural Equation Modeling Approach

2020 ◽  
Vol 12 (8) ◽  
pp. 3475
Author(s):  
Theresa Eichhorn ◽  
Oliver Meixner
Keyword(s):  
Structural Equation Modeling ◽  
Willingness To Pay ◽  
Production System ◽  
Purchase Intention ◽  
Food Production ◽  
Structural Equation ◽  
Primary Data ◽  
Equation Modeling ◽  
Successful Implementation ◽  
Food Production System

Even in highly developed food markets, aquaponic products have not yet been successfully introduced. This is particularly surprising, as aquaponics is an excellent example of a sustainable circulation food production system. The purpose of this empirical study was to determine the factors that influence consumers’ willingness to pay for aquaponic products. The direct and indirect relationships were tested via Structural Equation Modeling (SEM). Primary data of 315 respondents from Austria were collected. The findings revealed that the willingness to pay for aquaponic products was significantly and directly driven by the purchase intention. As a result, the successful implementation of aquaponics in the market requires the provision of information for consumers. We suggest emphasizing the value of aquaponics as a sustainable food production system, since indirect factors that influence the willingness to pay are (besides the assessment of aquaponics) environmental awareness and green consumption.

scholarly journals Barriers and Facilitators to Implementation of Medication Decision Support Systems in Electronic Medical Records: Mixed Methods Approach Based on Structural Equation Modeling and Qualitative Analysis

10.2196/18758 ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. e18758
Author(s):  
Se Young Jung ◽  
Hee Hwang ◽  
Keehyuck Lee ◽  
Ho-Young Lee ◽  
Eunhye Kim ◽  
...  
Keyword(s):  
Structural Equation Modeling ◽  
Decision Support ◽  
Quantitative Analysis ◽  
Qualitative Analysis ◽  
Structural Equation ◽  
Adverse Drug Events ◽  
Ease Of Use ◽  
Barriers And Facilitators ◽  
Equation Modeling ◽  
Successful Implementation

Background Adverse drug events (ADEs) resulting from medication error are some of the most common causes of iatrogenic injuries in hospitals. With the appropriate use of medication, ADEs can be prevented and ameliorated. Efforts to reduce medication errors and prevent ADEs have been made by implementing a medication decision support system (MDSS) in electronic health records (EHRs). However, physicians tend to override most MDSS alerts. Objective In order to improve MDSS functionality, we must understand what factors users consider essential for the successful implementation of an MDSS into their clinical setting. This study followed the implementation process for an MDSS within a comprehensive EHR system and analyzed the relevant barriers and facilitators. Methods A mixed research methodology was adopted. Data from a structured survey and 15 in-depth interviews were integrated. Structural equation modeling was conducted for quantitative analysis of factors related to user adoption of MDSS. Qualitative analysis based on semistructured interviews with physicians was conducted to collect various opinions on MDSS implementation. Results Quantitative analysis revealed that physicians’ expectations regarding ease of use and performance improvement are crucial. Qualitative analysis identified four significant barriers to MDSS implementation: alert fatigue, lack of accuracy, poor user interface design, and lack of customizability. Conclusions This study revealed barriers and facilitators to the implementation of MDSS. The findings can be applied to upgrade MDSS in the future.

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