Background and aimObstetrics and gynecology information system is a critical component of the HIS in social security organization health centers. The objective of this study was to evaluate the usability of this system using the cognitive walkthrough method. Also, the present study provided a detailed formal description of how the cognitive usability evaluation can be applied and reported for a health care information system.MethodsThis study was conducted at the Mashhad University of Medical Sciences’ usability lab from March 2016 to June 2017. A two-phase approach was used to conduct the cognitive walkthrough evaluation: preparatory and evaluation. The preparation was done in three stages: first, we investigated users’ capabilities and background knowledge through a semi-structured interview. Second, the evaluation scenario was developed based on the most common tasks in routine workflow of users. Finally, each task was broken down into sequences of actions. In the evaluation phase, three usability experts independently assessed each action using a four-item checklist. Problems were categorized thematically and were reported from three different perspectives: Question-based, Task-based, and Evaluator-based. The data were then analyzed to understand the contribution of each task, along with its mean severity score.ResultsEvaluators’ responses were compared and any conflict was resolved in an expert panel. A total of 116 usability problems were identified based on the consensus of the evaluators. Inadequate system feedback was found to be the main source of 43% of the problems, and resulted in users confusion.ConclusionSince the system was evaluated in its pilot implementation phase, there was an opportunity to prevent future potential usability problems. The use of a mixed quantitative and qualitative approach in this usability study provided a more comprehensive perspective of the system problems. This study provided a detailed description of conducting CW usability evaluation which can be used as a practical guide for future studies.
Introduction: Semantic Process Mining is the extension field of process mining that is based on getting knowledge of conceptual event logs (based on ontologies) for analyzing frequent and rare processes. In the healthcare studies, semantic process mining has been used in different hospitals in order to improve processes.Material and Methods: A review of the usages of semantic process mining in hospitals is done. This review contains 65 articles from PubMed, dblp and Google scholar. It is searched from 2000 to 2017. One of them was duplicated and finally, we received 64 articles. Data were extracted according to PRISMA guidelines.Results: Out of 64 articles, 6 of them were related with inclusion and exclusion criteria. Most of them detect business process mining. In 80% of studies, the semantic process mining was useful and effective to improve hospital processes and improve its management.Conclusion: This review can show an overview the application of process mining in hospitals. It can help researchers to compare semantic process mining with other methods for improving processes in hospitals and finally, it shows the use of semantic process mining to enhance hospitals processes.
Not considering the usability in designing clinical information systems causes problems in human–computer interaction and patient dissatisfaction. Therefore, in this study, the usability of the bed information management system (BIMS) was examined by think-aloud method. This cross-sectional study was conducted on the BIMS in 50 noneducational hospitals. Participants consisted of three groups including users, facilitators, and technical support. To carry out the study, a scenario consisting of four tasks was designed. Three researchers analyzed the recorded files to identify the usability problems and their severity. The mean time of the evaluation process was 20:33 ± 4:47 s. The total number of the problems identifies by users was 80 cases. Data entry and layout problems with 38 (48%) and 33 (41%) cases were the most frequently found problems, respectively. About 61% and 55% of the data entry and layout problems had a minor severity (Severity 2), respectively. Furthermore, 43 (54%) cases of the problems were resolved by the users and 32 (40%) cases by the facilitator assistance. This study showed that a large number of the problems were due to the system poor design. Furthermore, by increasing the users’ level of knowledge about the system, it is possible to enhance user-system interaction. It is recommended that before designing and implementing a system, the system should be evaluated for usability, and the users should be educated in clinical information systems.
BACKGROUND: There are various electronic health records (EHRs) evaluation frameworks with multiple dimensions and numerous sets of evaluation measures, while the coverage rate of evaluation measures in a common framework varies in different studies. AIM: This study provides a literature review of the current EHR evaluation frameworks and a model for measuring the coverage rate of evaluation measures in EHR frameworks. METHODS: The current study was a comprehensive literature review and a critical appraisal study. The study was conducted in three phases. In Phase 1, a literature review of EHR evaluation frameworks was conducted. In Phase 2, a three-level hierarchical structure was developed, which includes three aspects, 12 dimensions, and 110 evaluation measures. Subsequently, evaluation measures in the identified studies were categorized based on the hierarchical structure. In Phase 3, relative frequency (RF) of evaluation measures in different dimensions and aspects for each of the identified studies were determined and categorized as follows: Appropriate, moderate, and low coverage. RESULTS: Out of a total of 8276 retrieved articles, 62 studies were considered relevant. The RF range in the second and third level of the hierarchical structure was between 8.6%–91.94% and 0.2%–61%, respectively. “Ease of use” and “system quality” were the most frequent evaluation measure and dimension. Our results indicate that identified studies cover at least one and at most nine evaluation dimensions and current evaluation frameworks focus more on the technology aspect. Almost in all identified studies, evaluation measures related to the technology aspect were covered. However, evaluation measures related to human and organization aspects were covered in 68% and 84% of the identified studies, respectively. CONCLUSION: In this study, we systematically reviewed all literature presenting any type of EHR evaluation framework and analyzed and discussed their aspects and features. We believe that the findings of this study can help researchers to review and adopt the EHR evaluation frameworks for their own particular field of usage.
Introduction The quality of clinical decisions being made every day by on-call physicians are totally based on the quality of medical information they receive during telephone consultations with residents. Some basic factors such as the right selection of medical items, type and format, and also the volume of such information may highly affect the quality of remote consultations. Therefore, developing a trusted standard model for such clinical communication seems vital. In this research, we used Delphi technique to develop a set of information items in form of clinical decision archetypes to standardize teleconsultation in high-risk pregnancies. Methods A multi-stage cross-sectional study was conducted to exploit the diagnostic items for the most common high-risk pregnancies in three obstetrics and gynecology department of educational hospitals, Mashhad, Iran. Results Our study revealed eclampsia/preeclampsia, hemorrhage, PROM, pre-term and post-term delivery as the most common high-risk pregnancies in the hospitals being studied. 189 clinically-important items were extracted from scientific references and then hand-filtered to 128 items by the participating gynecology and obstetrics experts. The final items were categorized into five classes including general information, chief complaint / current problem, medical history, clinical examination, and paraclinic tests. Conclusion In this study, a set of clinical decision archetype was developed to improve the decisions being made in high risk pregnancies.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.