Usability Of Health Information Systems Research Articles

The Assessment of the Usability of Health Information Systems in Referral Hospitals in Tanzania: A Case of Geita Regional Referral Hospital

This study assesses the usability of the health information system in referral hospitals in Tanzania. The study divided the research participants into two strata, including service providers and service recipients, to ensure balanced opinions. The participants were obtained using a simple random sampling technique. The mixed-research approach was applied to collecting both quantitative and qualitative data. A questionnaire and an unstructured interview guide were used in data collection. The findings revealed that the usability of the health information system at Geita regional referral hospital is adequate, despite a few insights that should be taken into consideration to maximize its usability, quality of service delivery, and increased level of acceptance. The usability factors that were perceived positively include visibility, navigation, and easy retrieval of data. On the other hand, although factors including task-technology match, report generation capability, stock level management notifications, and the ability to manage queues were positively perceived, it was found that a significant percentage of participants were not sure or disagreed. Additionally, despite the usability challenges, the use of the health information system at Geita Regional Referral Hospital has resulted in improved quality of healthcare provision in terms of reduced waiting time, easy and quick patient data retrieval, a proper payment system, and equitable service.

How do automated reasoning features impact the usability of a clinical task management system? Development and usability testing of a prototype

BackgroundElectronic clinical task management systems (ECTMSs) have been developed and adopted by care providers to improve care coordination. Some systems utilised automated reasoning (AR) to enable more intelligent task management functionalities, such as automated task allocation. Yet, the impact of such features on usability remains unclear. Poor usability of health information systems has been described to cause frustration and contribute to patient safety incidents. AimTo design AR features for an ECTMS and to evaluate their impact on usability. MethodsIn this mixed methods study, four ECTMS feature prototypes were co-designed with two clinicians. For each prototype, one AR variant and one non-AR variant with equivalent functionalities were developed. A moderated usability testing was conducted with seven clinicians to obtain ease-of-use ratings of prototypes and measure task durations. Parameters related to demographics and attitudes of participants were obtained via a questionnaire. A framework analysis was performed to summarise qualitative feedback. To determine statistical relationships of study variables, Spearmańs rank coefficients were calculated and presented as a correlation matrix. ResultsThree out of four prototypes received higher median ease-of-use ratings for AR variants and were associated with shorter average task durations. Multiple clinical use cases suitable for AR were identified. Preference for AR was found to moderately correlate with digital proficiency and prior experience with ECTMSs. Insufficient trust in automation, alert fatigue, and system customisation were identified as challenges in the adoption of AR features. ConclusionsThis study provides evidence for the potential of AR to enhance usability in ECTMSs. Consideration of psychological and organisational context of users in the feature design was found to be decisive for usability. Future research should explore implications for operational and clinical outcomes.

Developing a Native Model for Evaluating the Usability of Health Information Systems Through Heuristic Evaluation Technique

Introduction: A quality criterion for evaluating information systems (ISs) is their usability, which can be determined by examining the user interface. User interface issues may generate user errors, dissatisfaction, and inefficiency, making IS adoption difficult. Therefore, the International Standard Organization recommends usability testing to evaluate IS acceptability and deployment. So, this study aimed to develop a native model for the usability testing of hospital information systems (HISs) via heuristic evaluation (HE). Method: This multi -staged qualitative study was conducted in 2020; ScienceDirect, PubMed, Web of Science, Scopus, Civilica, and Magiran databases were searched. After meeting the inclusion criteria, the articles were scored. Then, the initial model was created in the following stage by extracting data from library sources and validated using the Delphi technique, and consequently, the final model was presented. Results: : The native model was developed using thirteen principles: 1) visibility of system status, 2) the match between the system and the real world, 3) users’ control and freedom, 4) consistency and standards, 5) error prevention, 6) recognition rather than recall, 7) flexibility and efficiency of use, 8) aesthetic and minimalist design, 9) helping users recognize, diagnose, and recover errors, 10) documentation and help, 11) skill , 12) pleasurable, respectful interaction with users, and 13) privacy protection. Conclusion: This study demonstrated that localizing the usability evaluation of HISs based on trustworthy sources and HE is a wise strategy, because not only it avoids repetitive processes, but also it uses the best up -to -date resources to enable the presentation of the highest evaluation quality.

An Efficient Slime Mould Algorithm Combined With K-Nearest Neighbor for Medical Classification Tasks

Growing science and medical technologies have produced a massive amount of knowledge on different scales of biological systems. By processing various amounts of medical data, these technologies will increase the quality of disease detection and enhance the usability of health information systems. The integration of machine learning in computer-based diagnostic systems facilitates the early detection of diseases, enabling more productive treatments and prolonged survival rates. The slime mould algorithm (SMA) may have drawbacks, such as being trapped in minimal local regions and having an unbalanced exploitation and exploration phase. To overcome these limitations, this paper proposes ISMA, an improved version of the slime mould algorithm (SMA) hybridized with the opposition-based learning (OBL) strategy based on the k-nearest neighbor (kNN) classifier for the classification approach. Opposition-based learning improves global exploratory ability while avoiding premature convergence. The experimental results revealed the superiority of the proposed ISMA–kNN in various classification evaluation metrics, including accuracy, sensitivity, specificity, precision, F-score, G-mean, computational time, and feature selection (FS) size compared with the tunicate swarm algorithm (TSA), the marine predators algorithm (MPA), the chimp optimization algorithm (ChOA), the moth–flame optimization (MFO) algorithm, the whale optimization algorithm (WOA), the sine cosine algorithm (SCA), and the original SMA algorithm. Performance tests were run on the same maximum number of function evaluations (FEs) on nine UCI benchmark disease data sets with different feature sizes.

Effects of User Participation in the Development of Health Information Systems on Their Evaluation Within Occupational Health Services.

Information management and the usability of health information systems (HIS) are important for the development of HIS in occupational health services. User participation in the HIS development process has been shown to contribute to the success of an HIS. The purpose of this study was to analyze how user participation in HIS development affected evaluation of the success of HIS. The success was assessed on the basis of the DeLone and McLean Information Systems (IS) Success Model. The study was conducted within occupational health services and the data (n=210) was analyzed with quantitative methods. The results showed that users participating in the HIS development process assessed the success of the HIS as better than those that had not taken part in the development. This difference could be seen in all seven dimensions of the DeLone and McLean IS success model but was statistically significant only for System Quality and Intention to Use. The results also showed that the users that had participated in the HIS development process also used the HIS more often and more extensively than those that had not participated in the development. The results indicate that user participation in the development process positively influences their assessment of the HIS and increases their active use of the IS. However, more research is needed to determine the long-term effects of using participatory design in HIS development.

Developing the National Usability-Focused Health Information System Scale for Physicians: Validation Study.

BackgroundProblems in the usability of health information systems (HISs) are well acknowledged, but research still lacks a validated questionnaire for measuring and monitoring different dimensions of usability of HISs. Such questionnaires are needed not only for research but also for developing usability of HISs from the viewpoint of end-user experiences.ObjectiveThis study aimed to develop and test the validity of the questionnaire measuring the National Usability-Focused HIS-Scale (NuHISS) among a nationally representative sample of Finnish physicians.MethodsWe utilized 2 cross-sectional data collected from a random sample of Finnish physicians in 2014 (N=3781; of which 2340 [61.9%] were women) and 2017 (N=4018; of which 2604 [64.8%] were women). Exploratory and confirmatory factor analyses (structural equation modeling [SEM]) were applied to test the structural validity of the NuHISS. As the concurrent validity measure, we used the self-reported overall quality of the electronic health record system (school grade) provided by the participants using marginal structural models.ResultsThe exploratory factor analyses with Varimax rotation suggested that the 7-factor solution did offer a good fit to the data in both samples (C2=2136.14 in 2014 and C2=2109.83 in 2017, both P<.001). Moreover, structural equation modelling analyses, using comparative fit index (CFI), Tucker-Lewis Index (TLI), Normed Fit Index (NFI), root mean squared error of approximation (RMSEA), and Standardized Root Mean square Residual (SRMR), showed that the 7-factor solution provided an acceptable fit in both samples (CFI=0.92/0.91, TLI=0.92/0.91, NFI=0.92/0.91, RMSEA=0.048/0.049, and SRMR=0.040/0.039). In addition, concurrent validity of this solution was shown to be acceptable. Ease of use, but also all other dimensions, was especially associated with overall quality reports independent of measured confounders. The 7-factor solution included dimensions of technical quality, information quality, feedback, ease of use, benefits, internal collaboration, and cross-organizational collaboration.ConclusionsNuHISS provides a useful tool for measuring usability of HISs among physicians and offers a valid measure for monitoring the long-term development of HISs on a large scale. The relative importance of items needs to be assessed against national electronic health policy goals and complemented with items that have remained outside the NuHISS from the questionnaire when appropriate.

Comparison of two heuristic evaluation methods for evaluating the usability of health information systems

ObjectivesIn addition to following the usual Heuristic Evaluation (HE) method, the usability of health information systems can also be evaluated using a checklist. The objective of this study is to compare the performance of these two methods in identifying usability problems of health information systems. MethodsEight evaluators independently evaluated different parts of a Medical Records Information System using two methods of HE (usual and with a checklist). The two methods were compared in terms of the number of problems identified, problem type, and the severity of identified problems. ResultsIn all, 192 usability problems were identified by two methods in the Medical Records Information System. This was significantly higher than the number of usability problems identified by the checklist and usual method (148 and 92, respectively) (p < 0.0001). After removing the duplicates, the difference between the number of unique usability problems identified by the checklist method (n = 100) and usual method (n = 44) was significant (p < 0.0001). Differences between the mean severity of the real usability problems (1.83) and those identified by only one of the methods (usual = 2.05, checklist = 1.74) were significant (p = 0.001). ConclusionsThis study revealed the potential of the two HE methods for identifying usability problems of health information systems. The results demonstrated that the checklist method had significantly better performance in terms of the number of identified usability problems; however, the performance of the usual method for identifying problems of higher severity was significantly better. Although the checklist method can be more efficient for less experienced evaluators, wherever usability is critical, the checklist should be used with caution in usability evaluations.

User Interface Problems of a Nationwide Inpatient Information System: A Heuristic Evaluation.

While studies have shown that usability evaluation could uncover many design problems of health information systems, the usability of health information systems in developing countries using their native language is poorly studied. The objective of this study was to evaluate the usability of a nationwide inpatient information system used in many academic hospitals in Iran. Three trained usability evaluators independently evaluated the system using Nielsen's 10 usability heuristics. The evaluators combined identified problems in a single list and independently rated the severity of the problems. We statistically compared the number and severity of problems identified by HIS experienced and non-experienced evaluators. A total of 158 usability problems were identified. After removing duplications 99 unique problems were left. The highest mismatch with usability principles was related to "Consistency and standards" heuristic (25%) and the lowest related to "Flexibility and efficiency of use" (4%). The average severity of problems ranged from 2.4 (Major problem) to 3.3 (Catastrophe problem). The experienced evaluator with HIS identified significantly more problems and gave higher severities to problems (p<0.02). Heuristic Evaluation identified a high number of usability problems in a widely used inpatient information system in many academic hospitals. These problems, if remain unsolved, may waste users' and patients' time, increase errors and finally threaten patient's safety. Many of them can be fixed with simple redesign solutions such as using clear labels and better layouts. This study suggests conducting further studies to confirm the findings concerning effect of evaluator experience on the results of Heuristic Evaluation.

Erratum: User Interface Problems of a Nationwide Inpatient Information System: A Heuristic Evaluation.

Introduction: While studies have shown that usability evaluation could uncover many design problems of health information systems, the usability of health information systems in developing countries using their native language is poorly studied. The objective of this study was to evaluate the usability of a nationwide inpatient information system used in many academic hospitals in Iran. Material and Methods: Three trained usability evaluators independently evaluated the system using Nielsen’s 10 usability heuristics. The evaluators combined identified problems in a single list and independently rated the severity of the problems. We statistically compared the number and severity of problems identified by HIS experienced and non-experienced evaluators. Results: A total of 158 usability problems were identified. After removing duplications 99 unique problems were left. The highest mismatch with usability principles was related to “Consistency and standards” heuristic (25%) and the lowest related to “Flexibility and efficiency of use” (4%). The average severity of problems ranged from 2.4 (Major problem) to 3.3 (Catastrophe problem). The experienced evaluator with HIS identified significantly more problems and gave higher severities to problems (p<0.02). Discussion: Heuristic Evaluation identified a high number of usability problems in a widely used inpatient information system in many academic hospitals. These problems, if remain unsolved, may waste users’ and patients’ time, increase errors and finally threaten patient’s safety. Many of them can be fixed with simple redesign solutions such as using clear labels and better layouts. This study suggests conducting further studies to confirm the findings concerning effect of evaluator experience on the results of Heuristic Evaluation.

Human Factors in the Large: Experiences from Denmark, Finland and Canada in Moving Towards Regional and National Evaluations of Health Information System Usability. Contribution of the IMIA Human Factors Working Group.

The objective of this paper is to explore approaches to understanding the usability of health information systems at regional and national levels. Several different methods are discussed in case studies from Denmark, Finland and Canada. They range from small scale qualitative studies involving usability testing of systems to larger scale national level questionnaire studies aimed at assessing the use and usability of health information systems by entire groups of health professionals. It was found that regional and national usability studies can complement smaller scale usability studies, and that they are needed in order to understand larger trends regarding system usability. Despite adoption of EHRs, many health professionals rate the usability of the systems as low. A range of usability issues have been noted when data is collected on a large scale through use of widely distributed questionnaires and websites designed to monitor user perceptions of usability. As health information systems are deployed on a widespread basis, studies that examine systems used regionally or nationally are required. In addition, collection of large scale data on the usability of specific IT products is needed in order to complement smaller scale studies of specific systems.

Exploring the relationship between usability and technology-induced error: unraveling a complex interaction.

The effective evaluation of the usability of health information systems is currently a major challenge. It is essential that the applications we develop are not only usable, but that they are also shown to be safe and do not inadvertently introduce errors. Furthermore, to provide appropriate feedback to designers of systems new methods for evaluation are needed as applications become more complex and distributed. To ensure system usability and safety a variety of methods have emerged from the area of usability engineering that have been adapted to healthcare. The authors have applied and adapted methods of usability engineering, working with hospitals and other healthcare organizations for designing and evaluating a range of health information systems over a number of years. We describe a methodological framework for considering some of these advances and show how a range of usability evaluations can be used to evaluate both the usability and safety of healthcare information systems both in artificial mocked up and real clinical settings using in-situ testing approaches. We conclude with a discussion of recent trends in the area of usability engineering in healthcare that have potential for improving the safety of healthcare information systems.