Development of minimum data set and dashboard for monitoring adverse events in radiology departments.

Background: To reduce the risk of errors, patient safety monitoring in the medical imaging department is crucial. Interventions are required and these can be provided as a framework for documenting, reporting, evaluating, and recognizing events that pose a threat to patient safety. The aim of this study was to develop minimum data set and dashboard for monitoring adverse events in radiology departments. Material and methods: This developmental research was conducted in multiple phases, including content determination using the Delphi technique; database designing using SQL Server; user interface (UI) building using PHP; and dashboard evaluation in three aspects: the accuracy of calculating; UI requirements; and usability. Results: This study identified 26 patient safety (PS) performance metrics and 110 PS-related significant data components organized into 14 major groupings as the system contents. The UI was built with three tabs: pre-procedure, intra-procedure, and post-procedure. The evaluation results proved the technical feasibility of the dashboard. Finally, the dashboard's usability was highly rated (76.3 out of 100). Conclusion: The dashboard can be used to supplement datasets to obtain a more accurate picture of the PS condition and to draw attention to characteristics that professionals might otherwise overlook or undervalue.

Effects and characteristics of clinical decision support systems on the outcomes of patients with kidney disease: a systematic review.

OBJECTIVES: This systematic review was conducted to investigate the characteristics and effects of clinical decision support systems (CDSSs) on clinical and process-of-care outcomes of patients with kidney disease. METHODS: A comprehensive systematic search was conducted in electronic databases to identify relevant studies published until November 2020. Randomized clinical trials evaluating the effects of using electronic CDSS on at least one clinical or process-of-care outcome in patients with kidney disease were included in this study. The characteristics of the included studies, features of CDSSs, and effects of the interventions on the outcomes were extracted. Studies were appraised for quality using the Cochrane risk-of-bias assessment tool. RESULTS: Out of 8722 retrieved records, 11 eligible studies measured 32 outcomes, including 10 clinical outcomes and 22 process-of-care outcomes. The effects of CDSSs on 45.5% of the process-of-care outcomes were statistically significant, and all the clinical outcomes were not statistically significant. Medication-related process-of-care outcomes were the most frequently measured (54.5%), and CDSSs had the most effective and positive effect on medication appropriateness (18.2%). The characteristics of CDSSs investigated in the included studies comprised automatic data entry, real-time feedback, providing recommendations, and CDSS integration with the Computerized Provider Order Entry system. CONCLUSION: Although CDSS may potentially be able to improve processes of care for patients with kidney disease, particularly with regard to medication appropriateness, no evidence was found that CDSS affects clinical outcomes in these patients. Further research is thus required to determine the effects of CDSSs on clinical outcomes in patients with kidney diseases.

Development of Decision Support System to Predict Neurofeedback Response in ADHD: an Artificial Neural Network Approach.

INTRODUCTION: Clinical decision support system (CDSS) is an analytical tool that converts raw data into useful information to help clinicians make better decisions for patients. AIM: The purpose of this study was to investigate the efficacy of neurofeedback (NF), in Attention Deficit Hyperactivity Disorder (ADHD) by the development of CDSS based on artificial neural network (ANN). METHODS: This study analyzed 122 patients with ADHD who underwent NF in the Parand-Human Potential Empowerment Institute in Tehran. The patients were divided into two groups according to the effects of NF: effective and non-effective groups. The patients' record information was mined by data mining techniques to identify effective features. Based on unsaturated condition of data and imbalanced classes between the patient groups (patients with successful NF response and those without it), the SMOTE technique was applied on dataset. Using MATLAB 2014a, a modular program was designed to test both multiple architectures of neural networks and their performance. Selected architecture of the neural networks was then applied in the procedure. RESULTS: Eleven features from 28 features of the initial dataset were selected as effective features. Using the SMOTE technique, number of the samples rose to around 300 samples. Based on the multiple neural networks architecture testing, a network by 11-20-16-2 neurons was selected (specify>00.91%, sensivity=100%) and applied in the software. CONCLUSION: The ANN used in this study has led to good results in sensivity, specificity, and AUC. The ANN and other intelligent techniques can be used as supportive tools for decision making by healthcare providers.

Semantic Web Technologies for Sharing Clinical Information in Health Care Systems.

INTRODUCTION: Semantic Web (SW) technologies is capable of facilitating the management and sharing of knowledge and promote semantic interoperability among healthcare information systems. AIM: This article is designed to provide an overview of the SW technologies. METHODS: This article was performed based on a literature review and Internet search through scientific databases such as PubMed, Scopus, Web of Science and Google Scholar. RESULT: The literature on SW addresses the technical and content aspects of SW technologies including description of ontology, interoperability standards in SW, creating ontology, types of ontologies, ontology editors, ontologies in healthcare. DISCUSSION: The discussion on this forum aims to help understand the benefits of SW technologies in healthcare. CONCLUSION: SW promotes a shift from the "syntactic" level to the "semantic" level of services, applications, and people and finally to pragmatic level by sharing knowledge among clinicians, researchers and healthcare providers.

Quality of patient information in emergency department.

PURPOSE: Data comprise one of the key resources currently used in organizations. High-quality data are those that are appropriate for use by the customer. The quality of data is a key factor in determining the level of healthcare in hospitals, and its improvement leads to an improved quality of health and treatment and ultimately increases patient satisfaction. The purpose of this paper is to assess the quality of emergency patients' information in a hospital information system. DESIGN/METHODOLOGY/APPROACH: This cross-sectional study was conducted on 385 randomly selected records of patients admitted to the emergency department of Shahid Beheshti Hospital in Kashan, Iran, in 2016. Data on five dimensions of quality, including accuracy, accessibility, timeliness, completeness and definition, were collected using a researcher-made checklist and were then analyzed in SPSS. The results are presented using descriptive statistics, such as frequency distribution and percentage. FINDINGS: The overall quality of emergency patients' information in the hospital information system was 86 percent, and the dimensions of quality scored 87.7 percent for accuracy, 86.8 percent for completeness, 83.9 percent for timeliness, 79 percent for definition and 62.1 percent for accessibility. ORIGINALITY/VALUE: Increasing the quality of patient information at emergency departments can lead to improvements in the timely diagnosis and management of diseases and patient and personnel satisfaction, and reduce hospital costs.

Adoption of Hospital Information System Among Nurses: a Technology Acceptance Model Approach.

INTRODUCTION: The successful implementation of Hospital Information Systems (HIS) depends on user acceptance. Nurses are the largest group of HIS users in hospitals. This study aims to evaluate some factors may affect the utilization of the Hospital Information System. AIM: To explore factors that contribute to using of Hospital Information System. METHODS: In this cross-sectional study, 325 nurses from training Hospitals affiliated with Lorestan University of Medical Sciences (LUMS) were chosen. A valid and reliable structured questionnaire based on Technology Acceptance Model 1&2 and Unified Theory of Acceptance and Use of Technology was used as the data collection tool. Descriptive statistics, Correlations analysis, multiple regression analysis, path analysis technique, Structure Equation Model using AMOS software was used to examine factors that influenced the Adoption of Hospital Information System. RESULTS: The findings indicate a significant direct relationship between Management Support and Perceived Usefulness of HIS. Perceived Usefulness has a significant effect on attitudes. While there was no significant effect of perceived ease of use on attitude. Attitude has a significant effect on behavioral intention. CONCLUSION: This research provides a tool to realize what factors undertake the behavioral intention of healthcare professionals to use hospital information system and how this may affect future use.

Evaluation of Effective Dashboards: Key Concepts and Criteria.

OBJECTIVE: The aim of this study is to offer appropriate criteria to evaluate effective dashboards for healthcare organizations. METHOD: In a Delphi study, a team of information technology consultants were asked to determine a set of user interface requirements for evaluating, building or selecting the dashboard. In the first round, a list of main features or criteria to be used was determined based on the panel's rating,. RESULTS: In this study, it was revealed that a set of key criteria for evaluating the dashboards can be used for all types of dashboards. These criteria were classified into 7 main categories including user customization, knowledge discovery, security, information delivery, alerting, visual design, and integration and system connectivity. CONCLUSION: Choosing good criteria for selecting effective dashboards for healthcare organizations is very critical because these organizations follow a data-intensive and technology-driven environment. This study revealed the importance of key criteria which can guarantee development of an evaluation checklist.

Clinical Data Warehouse: An Effective Tool to Create Intelligence in Disease Management.

Clinical business intelligence tools such as clinical data warehouse enable health care organizations to objectively assess the disease management programs that affect the quality of patients' life and well-being in public. The purpose of these programs is to reduce disease occurrence, improve patient care, and decrease health care costs. Therefore, applying clinical data warehouse can be effective in generating useful information about aspects of patient care to facilitate budgeting, planning, research, process improvement, external reporting, benchmarking, and trend analysis, as well as to enable the decisions needed to prevent the progression or appearance of the illness aligning with maintaining the health of the population. The aim of this review article is to describe the benefits of clinical data warehouse applications in creating intelligence for disease management programs.

Enhancing Patient Safety Using Medical Imaging Informatics.

A set of performance indicators and metrics related to patient safety that classifies and measures mistakes can prevent errors in medical imaging. The potential of harm in this department is high since it is a complicated environ- ment in terms of diversity of services, patient mix, personnel, equipment, tech- nology, and information. In such an environment, it is necessary to define aframeworkto identify safety inci- dents, analyze them, provide solutions for preventing them, and give feedback on the results. Using medical imaging informatics can be effective in monitor- ing these indicators. Benefits such as reducing radiation expo- sure and reducing medication errors and adverse effects can be achieved. It can also promote knowledge through acces- sibility of resources and useful informa- tion in order to optimize decision making.

From Information Management to Information Visualization: Development of Radiology Dashboards.

OBJECTIVE: The development and implementation of a dashboard of medical imaging department (MID) performance indicators. METHOD: Several articles discussing performance measures of imaging departments were searched for this study. All the related measures were extracted. Then, a panel of imaging experts were asked to rate these measures with an open ended question to seek further potential indicators. A second round was performed to confirm the performance rating. The indicators and their ratings were then reviewed by an executive panel. Based on the final panel's rating, a list of indicators to be used was developed. A team of information technology consultants were asked to determine a set of user interface requirements for the building of the dashboard. In the first round, based on the panel's rating, a list of main features or requirements to be used was determined. Next, Qlikview was utilized to implement the dashboard to visualize a set of selected KPI metrics. Finally, an evaluation of the dashboard was performed. RESULTS: 92 MID indicators were identified. On top of this, 53 main user interface requirements to build of the prototype of dashboard were determined. Then, the project team successfully implemented a prototype of radiology management dashboards into study site. The visual display that was designed was rated highly by users. CONCLUSION: To develop a dashboard, management of information is essential. It is recommended that a quality map be designed for the MID. It can be used to specify the sequence of activities, their related indicators and required data for calculating these indicators. To achieve both an effective dashboard and a comprehensive view of operations, it is necessary to design a data warehouse for gathering data from a variety of systems. Utilizing interoperability standards for exchanging data among different systems can be also effective in this regard.

Auditing Knowledge toward Leveraging Organizational IQ in Healthcare Organizations.

OBJECTIVES: In this study, a knowledge audit was conducted based on organizational intelligence quotient (OIQ) principles of Iran's Ministry of Health and Medical Education (MOHME) to determine levers that can enhance OIQ in healthcare. METHODS: The mixed method study was conducted within the MOHME. The study population consisted of 15 senior managers and policymakers. A tool based on literature review and panel expert opinions was developed to perform a knowledge audit. RESULTS: The significant results of this auditing revealed the following: lack of defined standard processes for organizing knowledge management (KM), lack of a knowledge map, absence of a trustee to implement KM, absence of specialists to produce a knowledge map, individuals' unwillingness to share knowledge, implicitness of knowledge format, occasional nature of knowledge documentation for repeated use, lack of a mechanism to determine repetitive tasks, lack of a reward system for the formation of communities, groups and networks, non-updatedness of the available knowledge, and absence of commercial knowledge. CONCLUSIONS: The analysis of the audit findings revealed that three levers for enhancing OIQ, including structure and process, organizational culture, and information technology must be created or modified.

Clinical Decision Support Systems and Medical Imaging.

Clinical decision support systems (CDSS) can help clinicians make correct and timely decisions about patient care, reduce errors, comply with standard treatment and medication guidelines, reduce costs, and ultimately improve the quality of healthcare. An overview of various models is provided. This tool can apply to six areas of healthcare, all of which have a significant impact on improving care and provider performance: diagnosis, disease progress management, care and treatment, drug prescribing, evaluation, and prevention. Beginning in January 2017, referring physicians must use appropriateness criteria when ordering advanced imaging for Medicare patients. CDSS will be a critical part of this process. In the medical imaging chain, from ordered study to communicating results, such systems can help achieve best practices.

Value Innovation in Hospital: Increase Organizational IQ by Managing Intellectual Capitals.

Hospital is a complex organization rich in intellectual capitals. Effective management of these assets in line with innovating value to reach strategic goals and objectives can lead to increasing organizational IQ. In hospital with high organizational IQ, Increasing syntropy in intellectual capitals can convert it to an agile, learner, innovative, and smart organization.

Organizational Factors that Affect the Implementation of Information Technology: Perspectives of Middle Managers in Iran.

OBJECTIVE: to examine the organizational factors affecting the application of information technology in hospitals. Since the organizational factors are one of the most important determinants of successful projects, by understanding their impact and identifying them it can help planning a systematic IT implementation. METHODS: In this cross-sectional descriptive study 110 middle managers were chosen from teaching hospitals. Structured questionnaire was used for the data collection. RESULTS: There was a significant relationship between organization resource, organizational knowledge, process, management structure and values and goals with implementation of information technology. CONCLUSION: Findings showed that organizational factors had a considerable impact on implementation of information technology. Top managers must consider the important aspects of effective organizational factors.

A design protocol to develop radiology dashboards.

AIM: The main objective of this descriptive and development research was to introduce a design protocol to develop radiology dashboards. MATERIAL AND METHODS: The first step was to determine key performance indicators for radiology department. The second step was to determine required infrastructure for implementation of radiology dashboards. Infrastructure was extracted from both data and technology perspectives. The third step was to determine main features of the radiology dashboards. The fourth step was to determine the key criteria for evaluating the dashboards. In all these steps, non-probability sampling methods including convenience and purposive were employed and sample size determined based on a persuasion model. RESULTS: Results showed that there are 92 KPIs, 10 main features for designing dashboards and 53 key criteria for dashboards evaluation. As well as, a Prototype of radiology management dashboards in four aspects including services, clients, personnel and cost-income were implemented and evaluated. Applying such dashboards could help managers to enhance performance, productivity and quality of services in radiology department.

Effective radiology dashboards: key research findings.

Innovative organizations have access to information for business intelligence through the objectives displayed in dashboards. In healthcare organizations, where the goal is to improve quality of care along with reducing costs, the radiology department is important from both financial and clinical aspects. Therefore, how to manage this department has critical impact on the effectiveness and efficiency of the organization. Today, since the information in this department not only has different data structure but also is gathered from different data sources, a well defined, comprehensive dashboard can be an effective tool to enhance performance.

Enhance hospital performance from intellectual capital to business intelligence.

Business intelligence (BI) refers to technologies, tools, and practices for collecting, integrating, analyzing, and presenting large volumes of information to enable better decision making. The aim of this study is to provide a general overview of BI and its impacts on improving hospital performance. In this paper, literature is reviewed on the concept, classification, and structure of intellectual capital and BI. Research on the building of BI and its impact on the performance of hospitals are briefly summarized. Some areas in healthcare which can utilize BI benefits, including radiology, are also discussed. Used properly, BI is an effective communication tool that can enable hospitals to reach strategic goals and objectives and can also help eliminate information asymmetry.