The Inclusion of Health Data Standards in the Implementation of Pharmacogenomics Systems: A Scoping Review

Roosan, Don; Hwang, Angela; Law, Anandi V.; Chok, Jay; Roosan, Moom R.

doi:10.2217/pgs-2020-0066

Cited by 26 publications

(10 citation statements)

References 67 publications

(70 reference statements)

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“…Another consideration for the app design is incorporating health information exchange, genomics data integration, complex analysis of patient clinical charts, and other 360 data integration. [16,[35][36][37][38][39] Early diagnosis of ADRD can also benefit disadvantaged populations, such as those with lower socioeconomic and health literacy. [40] Digital inclusion of diverse racial/ethnic disparities is limited and not well represented in existing ADRD research.…”

Section: Artificial Intelligence Can Helpmentioning

confidence: 99%

Development of a dashboard analytics platform for dementia caregivers to understand diagnostic test results

Roosan,

Chok,

Nersesian

et al. 2023

Preprint

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Alzheimer's Disease and Related Dementias (ADRD) create unimaginable stress and financial burden in the lives of informal caregivers, including family and friends. However, the current healthcare system is not designed to incorporate caregivers in the healthcare team model for an early diagnostic process. The objectives of the focus group study are twofold: 1) to understand the digital information needs of caregivers to develop a user-friendly digital health app for the early diagnosis of ADRD patients, and 2) to assess the willingness of caregivers to be included in the early diagnosis process using a digital health app. We conducted a focus group study to understand caregivers' digital information needs and willingness to participate in the early diagnosis of ADRD. A total of 25 caregivers participated in the five focus group sessions. Data analysis revealed three main themes: 1) eagerness to be involved with the healthcare team for diagnosis, 2) facilitating digital communication for early diagnosis, and 3) chronicling the journey. Our unique finding demonstrates caregivers' willingness to participate in diagnostics by utilizing innovative digital health applications. The result of this study informs an intuitive digital interface based on user-centered design.

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Section: Artificial Intelligence Can Helpmentioning

confidence: 99%

Development of a dashboard analytics platform for dementia caregivers to understand diagnostic test results

Roosan,

Chok,

Nersesian

et al. 2023

Preprint

Self Cite

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“…It is believed that utilizing the CDSS under appropriate regulation greatly optimizes patient treatment. To date, the CDSS has been implemented in pharmacology, pharmacogenomics, laboratory medicine, and pathology [ 49 , 50 , 51 , 52 ]. Pregnancy status, renal and hepatic function, drug allergy, drug selection, and dosage for specific diagnostic conditions should be collected.…”

Section: Part 2: Big Data-based Genomic Information Management System...mentioning

confidence: 99%

“…Each parameter, such as drug interaction, chronic disease, and kidney and liver function, is being modeled and refined using patient-derived real-world data [ 53 , 54 , 55 , 56 ]. Recently, as the cost of genomic analysis has decreased and accuracy has improved, genotyping of the cytochrome P450 gene, which encodes a protein that metabolizes drugs with narrow therapeutic windows (e.g., tacrolimus and warfarin), has been included in CDSS [ 50 ]. Based on this, evidence-based drugs and doses will be determined for individual genotypes.…”

Section: Part 2: Big Data-based Genomic Information Management System...mentioning

confidence: 99%

A Genomic Information Management System for Maintaining Healthy Genomic States and Application of Genomic Big Data in Clinical Research

Gim

2022

IJMS

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Improvements in next-generation sequencing (NGS) technology and computer systems have enabled personalized therapies based on genomic information. Recently, health management strategies using genomics and big data have been developed for application in medicine and public health science. In this review, I first discuss the development of a genomic information management system (GIMS) to maintain a highly detailed health record and detect diseases by collecting the genomic information of one individual over time. Maintaining a health record and detecting abnormal genomic states are important; thus, the development of a GIMS is necessary. Based on the current research status, open public data, and databases, I discuss the possibility of a GIMS for clinical use. I also discuss how the analysis of genomic information as big data can be applied for clinical and research purposes. Tremendous volumes of genomic information are being generated, and the development of methods for the collection, cleansing, storing, indexing, and serving must progress under legal regulation. Genetic information is a type of personal information and is covered under privacy protection; here, I examine the regulations on the use of genetic information in different countries. This review provides useful insights for scientists and clinicians who wish to use genomic information for healthy aging and personalized medicine.

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“…38 As a result, the disjointed EHRs and their lack of usability in available CDSS have introduced new medical errors into the health care system. [39][40][41][42][43][44][45] EHR usability and CDSS design remain critical challenge in health care, with implications for medical errors, patient safety, and clinician burnout. 46,47 Current system designers assume that more information supports clinical reasoning and will thus lead to better decisions.…”

Section: Implications For Health It System Designmentioning

confidence: 99%

Power of Heuristics to Improve Health Information Technology System Design

et al. 2022

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Background Clinical decision-making can be prone to error if health system design does not match expert clinicians' higher cognitive skills. There is a gap in understanding the need for the importance of heuristics in clinical decision-making. The heuristic approach can provide cognitive support in designing intuitive health information systems for complex cases. Objective We explored complex decision-making by infectious diseases (ID) clinicians focusing on fast and frugal heuristics. We hypothesized that ID clinicians use simple heuristics to understand complex cases using their experience. Methods The study utilized cognitive task analysis and heuristics-based decision modeling. We conducted cognitive interviews and provided clinicians with a fast-and-frugal tree algorithm to convert complex information into simple decision algorithms. We conducted a critical decision method–based analysis to generate if–then logic sentences from the transcript. We conducted a thematic analysis of heuristics and calculated the average time to complete and the number of crucial information in the decision nodes. Results A total of 27 if–then logic heuristics sentences were generated from analyzing the data. The average time to construct the fast-and-frugal trees was 1.65 ± 0.37 minutes, and the average number of crucial pieces of information clinicians focused on was 5.4 ± 3.1. Conclusion Clinicians use shortcut mental models to reduce complex cases into simple mental model algorithms. The innovative use of artificial intelligence could allow clinical decision support systems to focus on creative and intuitive interface design matching the higher cognitive skills of expert clinicians.

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The Inclusion of Health Data Standards in the Implementation of Pharmacogenomics Systems: A Scoping Review

Cited by 26 publications

References 67 publications

Development of a dashboard analytics platform for dementia caregivers to understand diagnostic test results

Development of a dashboard analytics platform for dementia caregivers to understand diagnostic test results

A Genomic Information Management System for Maintaining Healthy Genomic States and Application of Genomic Big Data in Clinical Research

Power of Heuristics to Improve Health Information Technology System Design

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