Dataset Information

Attitude of physiotherapists toward electronic health record in Croatia.

ABSTRACT: Background:Electronic health record can facilitate everyday clinical practice of physiotherapists. The aim of this study is to determine attitude of physiotherapists towards implementation of information technology in their work and the differences in attitude in relation to gender, age, level of education and type of health institutions. Methods:This study is a cross-sectional survey of Croatian physiotherapists. The questionnaire ?Attitude of physiotherapists towards implementation of electronic health record included 12 items scored on a Likert-type scale from 1 to 5 and presented the award values as "Disagree", "Neither agree nor disagree" and "Agree". Croatian physiotherapists were (n =?267) recruited from 13 health care institutions. For analysis chi square test, t-test, one-way analysis of variance and as a post-hoc Tukey test were used. Results:Explanatory factorial analysis confirmed two factors: Satisfaction in the work of physiotherapists using computers (SAT) and Necessity of computers in the work of physiotherapists (NEC). Most physiotherapists agree on (SAT) (47.9%) and on (NEC) (51.3%). Male physiotherapists were significantly more likely to disagree with statements related to SAT (p??0.05). Conclusion:The attitude of Croatian physiotherapists towards electronic health record differs according to the age, gender, level of education and type of health care institutions. This finding can facilitate implementation of electronic health record in physiotherapy. Trial registration:Not applicable.

SUBMITTER: Filipec M

PROVIDER: S-EPMC6805644 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Attitude of physiotherapists toward electronic health record in Croatia.

Filipec Manuela M Brumini Gordana G

Archives of physiotherapy 20191022

<h4>Background</h4>Electronic health record can facilitate everyday clinical practice of physiotherapists. The aim of this study is to determine attitude of physiotherapists towards implementation of information technology in their work and the differences in attitude in relation to gender, age, level of education and type of health institutions.<h4>Methods</h4>This study is a cross-sectional survey of Croatian physiotherapists. The questionnaire ″Attitude of physiotherapists towards implementat ...[more]

PMID: 31660205

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Project description:Introduction:Electronic health record (EHR)-driven phenotyping is a critical first step in generating biomedical knowledge from EHR data. Despite recent progress, current phenotyping approaches are manual, time-consuming, error-prone, and platform-specific. This results in duplication of effort and highly variable results across systems and institutions, and is not scalable or portable. In this work, we investigate how the nascent Clinical Quality Language (CQL) can address these issues and enable high-throughput, cross-platform phenotyping. Methods:We selected a clinically validated heart failure (HF) phenotype definition and translated it into CQL, then developed a CQL execution engine to integrate with the Observational Health Data Sciences and Informatics (OHDSI) platform. We executed the phenotype definition at two large academic medical centers, Northwestern Medicine and Weill Cornell Medicine, and conducted results verification (n = 100) to determine precision and recall. We additionally executed the same phenotype definition against two different data platforms, OHDSI and Fast Healthcare Interoperability Resources (FHIR), using the same underlying dataset and compared the results. Results:CQL is expressive enough to represent the HF phenotype definition, including Boolean and aggregate operators, and temporal relationships between data elements. The language design also enabled the implementation of a custom execution engine with relative ease, and results verification at both sites revealed that precision and recall were both 100%. Cross-platform execution resulted in identical patient cohorts generated by both data platforms. Conclusions:CQL supports the representation of arbitrarily complex phenotype definitions, and our execution engine implementation demonstrated cross-platform execution against two widely used clinical data platforms. The language thus has the potential to help address current limitations with portability in EHR-driven phenotyping and scale in learning health systems.

Project description:BackgroundThe rapid expansion in the use of electronic health records (EHR) has increased the number of medical errors originating in health information systems (HIS). The sociotechnical approach helps in understanding risks in the development, implementation, and use of EHR and health information technology (HIT) while accounting for complex interactions of technology within the health care system.ObjectiveThis study addresses two important questions: (1) "which of the common EHR error types are associated with perceived high- and extreme-risk severity ratings among EHR users?", and (2) "which variables are associated with high- and extreme-risk severity ratings?"MethodsThis study was a quantitative, non-experimental, descriptive study of EHR users. We conducted a cross-sectional web-based questionnaire study at the largest hospital district in Finland. Statistical tests included the reliability of the summative scales tested with Cronbach's alpha. Logistic regression served to assess the association of the independent variables to each of the eight risk factors examined.ResultsA total of 2864 eligible respondents provided the final data. Almost half of the respondents reported a high level of risk related to the error type "extended EHR unavailability". The lowest overall risk level was associated with "selecting incorrectly from a list of items". In multivariate analyses, profession and clinical unit proved to be the strongest predictors for high perceived risk. Physicians perceived risk levels to be the highest ( P<.001 in six of eight error types), while emergency departments, operating rooms, and procedure units were associated with higher perceived risk levels ( P<.001 in four of eight error types). Previous participation in eLearning courses on EHR-use was associated with lower risk for some of the risk factors.ConclusionsBased on a large number of Finnish EHR users in hospitals, this study indicates that HIT safety hazards should be taken very seriously, particularly in operating rooms, procedure units, emergency departments, and intensive care units/critical care units. Health care organizations should use proactive and systematic assessments of EHR risks before harmful events occur. An EHR training program should be compulsory for all EHR users in order to address EHR safety concerns resulting from the failure to use HIT appropriately.

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Project description:BackgroundElectronic health record (EHR) system users devise workarounds to cope with mismatches between workflows designed in the EHR and preferred workflows in practice. Although workarounds appear beneficial at first sight, they frequently jeopardize patient safety, the quality of care, and the efficiency of care.ObjectiveThis review aims to aid in identifying, analyzing, and resolving EHR workarounds; the Sociotechnical EHR Workaround Analysis (SEWA) framework was published in 2019. Although the framework was based on a large case study, the framework still required theoretical validation, refinement, and enrichment.MethodsA scoping literature review was performed on studies related to EHR workarounds published between 2010 and 2021 in the MEDLINE, Embase, CINAHL, Cochrane, or IEEE databases. A total of 737 studies were retrieved, of which 62 (8.4%) were included in the final analysis. Using an analytic framework, the included studies were investigated to uncover the rationales that EHR users have for workarounds, attributes characterizing workarounds, possible scopes, and types of perceived impacts of workarounds.ResultsThe SEWA framework was theoretically validated and extended based on the scoping review. Extensive support for the pre-existing rationales, attributes, possible scopes, and types of impact was found in the included studies. Moreover, 7 new rationales, 4 new attributes, and 3 new types of impact were incorporated. Similarly, the descriptions of multiple pre-existing rationales for workarounds were refined to describe each rationale more accurately.ConclusionsSEWA is now grounded in the existing body of peer-reviewed empirical evidence on EHR workarounds and, as such, provides a theoretically validated and more complete synthesis of EHR workaround rationales, attributes, possible scopes, and types of impact. The revised SEWA framework can aid researchers and practitioners in a wider range of health care settings to identify, analyze, and resolve workarounds. This will improve user-centered EHR design and redesign, ultimately leading to improved patient safety, quality of care, and efficiency of care.

Dataset Information

Attitude of physiotherapists toward electronic health record in Croatia.

Publications

Attitude of physiotherapists toward electronic health record in Croatia.

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