Implementation of Health Information Systems to Improve Patient Identification

Wellbeing can be ensured in society through quality healthcare, a minimum of medical errors, and the improved performance of healthcare professionals. To this end, health information systems have been implemented in hospitals, with this implementation representing progress in medicine and information technologies. As a result, life expectancy has significantly increased, standards in healthcare have been raised, and public health has improved. This progress is influenced by the process of managing healthcare organizations and information systems. While hospitals tend to adapt health information systems to reduce errors related to patient misidentification, the rise in the occurrence and recording of medical errors in Lebanon resulting from failures to correctly identify patients reveals that such measures remain insufficient due to unknown factors. This research aimed to investigate the effect of health information systems (HISs) and other factors related to work-related conditions on reductions in patient misidentification and related consequences. The empirical data were collected from 109 employees in Neioumazloum Hospital in Lebanon. The results revealed a correlation between HISs and components and the effects of other factors on patient identification. These other factors included workload, nurse fatigue, a culture of patient safety, and lack of implementation of patient identification policies. This paper provides evidence from a Lebanese hospital and paves the way for further studies aiming to explore the role of information technologies in adopting HISs for work performance and patient satisfaction. Improved care for patients can help achieve health equality, enhance healthcare delivery performance and patient safety, and decrease the numbers of medical errors.

Investigation the success rate of hospital information system (HIS): Development of a questionnaire and case study

INTRODUCTION AND OBJECTIVES

The implantation of hospital information systems (HISs) has grown dramatically in recent years. Understanding the success rate of HIS is key in health organizations. In this study, a validated questionnaire for HISs evaluation based on the Information System Success Model (ISSM) has been provided. In addition, the HIS success rate was determined.

MATERIALS AND METHODS

The current study was conducted at one of the largest teaching hospitals in eastern Iran. The 44-items questionnaire was developed for data gathering. The questionnaire covered ISSM dimensions, which include analysis of quality system, quality of information, quality service, system use, usefulness, satisfaction, and net benefits. Content validity, constructs validity, and reliability of the ISSM questionnaire was measured. HIS success rate has been determined and categorized based on users' perspective as follows: appropriate (75%≤HIS success rate), moderate (50%≤HIS success rate<75%), low coverage (25%≤HIS success rate<50%), and poor (coverage rate<25%).

RESULTS

In total, 253 users participated in the study. The ISSM questionnaire was validated by an expert panel with CVI: 85.12% and CVR: 88.22%. The overall Cronbach's alpha value of the instrument was determined as 92.2%. Nine factors with eigenvalues greater than 1.00 were identified, jointly accounting for 66.91% of the total variance. The value of KMO was.866 showed that the sample size was adequate for factor analysis. The highly significant Bartlett's test (p<0.000) indicated that variables were correlated and the factor analysis was appropriate. Our results demonstrated that the total mean of HIS success was "moderate" base on the users' point of view.

CONCLUSIONS

The findings of the current study, provide valuable scientific evidence for key affecting factors on hospital EHR in Iran as a developing country.

Investigating Evaluation Frameworks for Electronic Health Record: A Literature Review

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.

Improving Sustainable Mobile Health Care Promotion: A Novel Hybrid MCDM Method

Identifying the key influencing factors that affected users’ adoption of sustainable mobile health care and improving alternative mobile health services continuously can help ordinary consumers (especially vulnerable populations) use extensive health resources cheaply and conveniently; which can increase the quality and equity of health services; so as to promote the sustainable development of medical resources. We integrated decision making trial and evaluation laboratory (DEMETEL)-based analytic network process (DANP) and a modified VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method to form a DDANPMV (DEMATEL+ DANP + Modified VIKOR) model to examine consumers’ adoption of mobile health care. This method was developed to not only help decision-makers evaluate alternative mobile health care and determine the best option, but also use to identify and improve the performance gap of alternative products with the goal of satisfying the aspirations of consumers. Four types of mobile health care products were analyzed. The results indicate that social norms; product image; and consumer trust are three key factors in consumer adoption. The results can guide policy design and implementation. The government and enterprises should improve mobile health care through these three aspects.

A Systematic Review on Existing Measures for the Subjective Assessment of Rehabilitation and Assistive Robot Devices

The objective of the current study is to identify and classify outcome measures currently used for the assessment of rehabilitation or assistive robot devices. We conducted a systematic review of the literature using PubMed, MEDLINE, CIRRIE, and Scopus databases for studies that assessed rehabilitation or assistive robot devices from 1980 through January 2016. In all, 31 articles met all inclusion criteria. Tailor-made questionnaires were the most commonly used tool at 66.7%, while the great majority (93.9%) of the studies used nonvalidated instruments. The study reveals the absence of a standard scale which makes it difficult to compare the results from different researchers. There is a great need, therefore, for a valid and reliable instrument to be available for use by the intended end users for the subjective assessment of robot devices. The study concludes by identifying two scales that have been validated in general assistive technology devices and could support the scope of subjective assessment in rehabilitation or assistive robots (however, with limited coverage) and a new one called PYTHEIA, recently published. The latter intends to close the gap and help researchers and developers to evaluate, assess, and produce products that satisfy the real needs of the end users.

From bed to bench: bridging from informatics practice to theory: an exploratory analysis

BACKGROUND

In 2009, Applied Clinical Informatics (ACI)--focused on applications in clinical informatics--was launched as a companion journal to Methods of Information in Medicine (MIM). Both journals are official journals of the International Medical Informatics Association.

OBJECTIVES

To explore which congruencies and interdependencies exist in publications from theory to practice and from practice to theory and to determine existing gaps. Major topics discussed in ACI and MIM were analyzed. We explored if the intention of publishing companion journals to provide an information bridge from informatics theory to informatics practice and vice versa could be supported by this model. In this manuscript we will report on congruencies and interdependences from practice to theory and on major topics in MIM.

METHODS

Retrospective, prolective observational study on recent publications of ACI and MIM. All publications of the years 2012 and 2013 were indexed and analyzed.

RESULTS

Hundred and ninety-six publications were analyzed (ACI 87, MIM 109). In MIM publications, modelling aspects as well as methodological and evaluation approaches for the analysis of data, information, and knowledge in biomedicine and health care were frequently raised - and often discussed from an interdisciplinary point of view. Important themes were ambient-assisted living, anatomic spatial relations, biomedical informatics as scientific discipline, boosting, coding, computerized physician order entry, data analysis, grid and cloud computing, health care systems and services, health-enabling technologies, health information search, health information systems, imaging, knowledge-based decision support, patient records, signal analysis, and web science. Congruencies between journals could be found in themes, but with a different focus on content. Interdependencies from practice to theory, found in these publications, were only limited.

CONCLUSIONS

Bridging from informatics theory to practice and vice versa remains a major component of successful research and practice as well as a major challenge.

The USE IT-adoption-model to predict and evaluate adoption of information and communication technology in healthcare

BACKGROUND AND OBJECTIVE

The USE IT-model integrates theories about adoption and diffusion of innovations and is suitable to predict and evaluate the success of an information system from a user's perspective. The USE IT-model consists of four determinants: relevance, requirements, resources and resistance, which are measured at the macro-level (organizational), and at the micro-level (individual). After applying the USE IT approach in several researches we evaluated and updated the USE IT-model.

METHODS

We used the USE IT-model in ten case studies in healthcare and compared the results of the studies with the determinants and dimensions of the USE IT-model.

RESULTS

The quality of the implementation process is part of the innovation process-dimension and therefore relocated as a dimension of macro-resistance. The improvements and value in the relevance determinant are made more concrete by quality, efficiency, effectiveness, and task support. The dimensions of micro-resistance are reduced, and the dimension negative consequences is added. Also the dimensions of macro- and micro-requirements are made more specific to express the importance of information quality, availability and accessibility.

DISCUSSION AND CONCLUSION

The research resulted in the updated USE IT-adoption-model to predict and evaluate the adoption of information systems in healthcare. The structure and determinants of the original USE IT-model with a distinction between the macro- and micro-level remained unchanged.