Improving the Patient-Clinician Interface of Clinical Trials through Health Informatics Technologies

Carrion, Jake

doi:10.1007/s10916-018-0973-y

Cited by 6 publications

(6 citation statements)

References 43 publications

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“… Philipp Bruland 2016 [ 18 ] Germany To determine the most commonly used data elements in clinical trials and their availability in hospital EHR systems. Jake Carrion 2018 [ 19 ] USA To examine the observed benefits and drawbacks of using Electronic Health Record (EHRs) to enhance various patient-centered aspects of the clinical trial process, specifically its potential to improve patient recruitment, patient retention, and data collection GeorgesDe Moor 2015 [ 20 ] Belgium To describe the EHR4CR project which aims to demonstrate a scalable, widely acceptable and efficient approach to interoperability between Electronic Health Record (EHR) systems and clinical research systems. Peter J. Embi 2005 [ 21 ] Ohio To determine if the use of EHR-based Clinical Trial Alert (CTAs) could enhance physicians’ participation in subject recruitment and increase physician-generated recruitment rates for an ongoing clinical trial.…”

Section: Resultsmentioning

confidence: 99%

“… Common data elements relevant to clinical trials were identified and their availability within hospital information systems were assessed. Jake Carrion 2018 [ 19 ] Improvement of patient recruitment, patient retention, and data collection through using the EHR. Leveraging EHR tools can enhance the way clinical trials are planned and executed.…”

Section: Resultsmentioning

confidence: 99%

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Utilization of EHRs for clinical trials: a systematic review

Kalankesh,

Monaghesh

2024

BMC Med Res Methodol

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Background and objective Clinical trials are of high importance for medical progress. This study conducted a systematic review to identify the applications of EHRs in supporting and enhancing clinical trials. Materials and methods A systematic search of PubMed was conducted on 12/3/2023 to identify relevant studies on the use of EHRs in clinical trials. Studies were included if they (1) were full-text journal articles, (2) were written in English, (3) examined applications of EHR data to support clinical trial processes (e.g. recruitment, screening, data collection). A standardized form was used by two reviewers to extract data on: study design, EHR-enabled process(es), related outcomes, and limitations. Results Following full-text review, 19 studies met the predefined eligibility criteria and were included. Overall, included studies consistently demonstrated that EHR data integration improves clinical trial feasibility and efficiency in recruitment, screening, data collection, and trial design. Conclusions According to the results of the present study, the use of Electronic Health Records in conducting clinical trials is very helpful. Therefore, it is better for researchers to use EHR in their studies for easy access to more accurate and comprehensive data. EHRs collects all individual data, including demographic, clinical, diagnostic, and therapeutic data. Moreover, all data is available seamlessly in EHR. In future studies, it is better to consider the cost-effectiveness of using EHR in clinical trials.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Utilization of EHRs for clinical trials: a systematic review

Kalankesh,

Monaghesh

2024

BMC Med Res Methodol

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“…The low adoption rate of standardized procedures and protocols for electronic health records platforms may lead to difficulties in coordinating research activities. 97 Electronic health records analysis use for drug hypersensitivity warrants further investigation. 98 Computerized physician order entry and mHealth facilitate real‐time identification of potential study subjects for clinical research.…”

Section: Ehealth For Academic and Clinical Researchmentioning

confidence: 99%

“…In the field of health informatics, electronic health records are used in a wide range of clinical trials, including for improvements of the patient‐clinician interface and data analysis. The low adoption rate of standardized procedures and protocols for electronic health records platforms may lead to difficulties in coordinating research activities 97 . Electronic health records analysis use for drug hypersensitivity warrants further investigation 98 .…”

Section: Ehealth For Academic and Clinical Researchmentioning

confidence: 99%

The applications of eHealth technologies in the management of asthma and allergic diseases

Alvarez-Perea

Dimov

Popescu

et al. 2021

Clinical & Translational All

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Portable devices, such as smartphones and mobile Internet access have become ubiquitous in the last decades. The term ‘eHealth’ stands for electronic health. The tools included in the eHealth concept utilize phones, computers and the Internet and related applications to improve the health care industry. Implementation of eHealth technologies has been documented for the management of different chronic diseases, including asthma and allergic conditions. Clinicians and patients have gained opportunity to communicate in new ways, which could be used cost‐effectively to improve disease control and quality of life of those affected. Additionally, these innovations bring new opportunities to academic researchers. For example, eHealth has allowed researchers to compile data points that were previously unavailable or difficult to access, and analyse them using novel tools, collectively described as ‘big data’. The role of eHealth become more important since early 2020, due to the physical distancing rules and the restrictions on mobility that have been applied worldwide as a response to the coronavirus disease 2019 pandemic. In this review, we summarize the most recent developments in various eHealth platforms and their relevance to the speciality of allergy and immunology, from the point of view of three major stakeholders: clinicians, patients and researchers.

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“…The healthcare delivery often defined by the concept that a network of clinicians rather than an individual clinician who offers the care for the patients. The failure or the success of the modern healthcare system is determined by the ability of these clinicians [1]. As the complexity within the domain of healthcare increases the varying process and also the clinician gets more difficult to be managed and also aligned that has resulted in increased risk for the patients and improper use of the available resources [1].…”

Section: Introductionmentioning

confidence: 99%

Story Point Based Effort Estimation Model with Machine Learning Techniques in Healthcare

Verma

Popli

Kumar

et al. 2021

Communications in Computer and Information Science

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Healthcare diseases diagnoses projects often exceed schedules and budgets due to the complication and their large size. Project planning and estimation are exclusively challenging in large and globally distributed projects. Agile with machine learning techniques can overcome these challenges of healthcare projects largely. The purpose of this study is to estimate efforts in large-scale healthcare projects using user story point with machine learning technique. Will be using user stories to estimates the size of Healthcare projects. The templates of user stories: As a [user or destination], I [want to some goal] so that [the goal can be achieved]. According to Bill Wake a good user story must have INVEST acronym. To predict accuracy of machine learning algorithms such as Naïve Bayes, Decision Tree, Logistic Regression cancer patient dataset has used. Writing user stories for healthcare is an easy way to maintain the requirements for an agile project. Agile model in healthcare has used to maintain the effectiveness by adopting the frequently changing demand of the customers. This research paper work on cancer diseases and will provide accuracy, precision, recall using machine learning algorithms such as naïve Bayes, logistic regression, Decision Tree.

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Improving the Patient-Clinician Interface of Clinical Trials through Health Informatics Technologies

Cited by 6 publications

References 43 publications

Utilization of EHRs for clinical trials: a systematic review

Utilization of EHRs for clinical trials: a systematic review

The applications of eHealth technologies in the management of asthma and allergic diseases

Story Point Based Effort Estimation Model with Machine Learning Techniques in Healthcare

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