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Digital Disruption and Big Data in Healthcare - Opportunities and Challenges
Background: As the amount of medical data in the electronic medical records system (EMR) is increasing tremendously, the required time to read it by health providers is growing by the exact proportionality. This means that physicians must increase the time spared for each patient again by the precis...
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Published in: | ClinicoEconomics and outcomes research 2022-01, Vol.14, p.563-574 |
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description | Background: As the amount of medical data in the electronic medical records system (EMR) is increasing tremendously, the required time to read it by health providers is growing by the exact proportionality. This means that physicians must increase the time spared for each patient again by the precise proportionality. This may lead to exposing the accuracy and quality of the course of action to be taken for the patients. Increasing the physician's required time for one patient means that the physician can see fewer patients. This will create an issue with the medical management authority as more physicians are needed, and higher expenses will be required. Purpose: The two questions that arise here are 1. Identify the potential opportunities and challenges for extensive data analysis in the healthcare sector. 2. Evaluate different ways in which big medical data can be analyzed? Methods: The authors identified the four concerned parties representing the four potential solutions dimensions to answer these two questions. These parties are 1. physicians, 2. health information systems management (HISM) departments, mainly the EMR system, and 3. Health management departments 4. Relevant Health Information Systems (HIS) parties. A literature review and 25 interviews were conducted. The interviews covered 1: Two global organizations: John Hopkins and Joint Commission International (JCI), 2: Three United Arab Emirates-based health organizations: Department of health in Abu Dhabi, SEHA in Abu Dhabi, Dubai health Authority (DHA) in Dubai, 3: 10 Physicians from different specialties, 4: Five EMR managers and 5: Five IT (Information Technology) professionals representing the HIS parties. Qualitative analysis is used as the approach for data analysis. Results: Identifying the managerial and the technical recommendations to be utilized mainly based on digital disruption technologies, tools, and processes. Conclusion: Healthcare has been slow in embracing digital disruption and transformation. In most areas, it is still in the initial stages. Recommendations are based on the UAE cases, highlighting the specific technologies and their features. Keywords: digital disruption, healthcare, big data, electronic medical records, EMR, health information systems, HIS |
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This means that physicians must increase the time spared for each patient again by the precise proportionality. This may lead to exposing the accuracy and quality of the course of action to be taken for the patients. Increasing the physician's required time for one patient means that the physician can see fewer patients. This will create an issue with the medical management authority as more physicians are needed, and higher expenses will be required. Purpose: The two questions that arise here are 1. Identify the potential opportunities and challenges for extensive data analysis in the healthcare sector. 2. Evaluate different ways in which big medical data can be analyzed? Methods: The authors identified the four concerned parties representing the four potential solutions dimensions to answer these two questions. These parties are 1. physicians, 2. health information systems management (HISM) departments, mainly the EMR system, and 3. Health management departments 4. Relevant Health Information Systems (HIS) parties. A literature review and 25 interviews were conducted. The interviews covered 1: Two global organizations: John Hopkins and Joint Commission International (JCI), 2: Three United Arab Emirates-based health organizations: Department of health in Abu Dhabi, SEHA in Abu Dhabi, Dubai health Authority (DHA) in Dubai, 3: 10 Physicians from different specialties, 4: Five EMR managers and 5: Five IT (Information Technology) professionals representing the HIS parties. Qualitative analysis is used as the approach for data analysis. Results: Identifying the managerial and the technical recommendations to be utilized mainly based on digital disruption technologies, tools, and processes. Conclusion: Healthcare has been slow in embracing digital disruption and transformation. In most areas, it is still in the initial stages. Recommendations are based on the UAE cases, highlighting the specific technologies and their features. Keywords: digital disruption, healthcare, big data, electronic medical records, EMR, health information systems, HIS</description><identifier>ISSN: 1178-6981</identifier><identifier>EISSN: 1178-6981</identifier><identifier>DOI: 10.2147/CEOR.S369553</identifier><identifier>PMID: 36052095</identifier><language>eng</language><publisher>Macclesfield: Dove Medical Press Limited</publisher><subject>Analysis ; Artificial intelligence ; Big Data ; Computer organization ; Control theory ; digital disruption ; electronic medical records (emr) ; Health care ; Health care industry ; Health facilities ; health information systems (his) ; healthcare ; Information management ; Information technology ; International agencies ; Internet of Things ; Literature reviews ; Medical informatics ; Medical records ; Neural networks ; Original Research ; Patients ; Physicians ; Qualitative analysis ; R&D ; Research & development ; Technology</subject><ispartof>ClinicoEconomics and outcomes research, 2022-01, Vol.14, p.563-574</ispartof><rights>COPYRIGHT 2022 Dove Medical Press Limited</rights><rights>2022. This work is licensed under https://creativecommons.org/licenses/by-nc/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2022 El Khatib et al. 2022 El Khatib et al.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c553t-ab9deb9970554922375750f839ae82cb45e09c377e1c28921bf0cd2c33eddd0b3</citedby><cites>FETCH-LOGICAL-c553t-ab9deb9970554922375750f839ae82cb45e09c377e1c28921bf0cd2c33eddd0b3</cites><orcidid>0000-0002-6766-3728</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2715017325/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2715017325?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,25732,27903,27904,36991,36992,38495,43874,44569,53769,53771,74158,74872</link.rule.ids></links><search><creatorcontrib>Khatib, Mounir El</creatorcontrib><creatorcontrib>Hamidi, Samer</creatorcontrib><creatorcontrib>Ameeri, Ishaq Al</creatorcontrib><creatorcontrib>Zaabi, Hamad Al</creatorcontrib><creatorcontrib>Marqab, Rehab Al</creatorcontrib><title>Digital Disruption and Big Data in Healthcare - Opportunities and Challenges</title><title>ClinicoEconomics and outcomes research</title><description>Background: As the amount of medical data in the electronic medical records system (EMR) is increasing tremendously, the required time to read it by health providers is growing by the exact proportionality. This means that physicians must increase the time spared for each patient again by the precise proportionality. This may lead to exposing the accuracy and quality of the course of action to be taken for the patients. Increasing the physician's required time for one patient means that the physician can see fewer patients. This will create an issue with the medical management authority as more physicians are needed, and higher expenses will be required. Purpose: The two questions that arise here are 1. Identify the potential opportunities and challenges for extensive data analysis in the healthcare sector. 2. Evaluate different ways in which big medical data can be analyzed? Methods: The authors identified the four concerned parties representing the four potential solutions dimensions to answer these two questions. These parties are 1. physicians, 2. health information systems management (HISM) departments, mainly the EMR system, and 3. Health management departments 4. Relevant Health Information Systems (HIS) parties. A literature review and 25 interviews were conducted. The interviews covered 1: Two global organizations: John Hopkins and Joint Commission International (JCI), 2: Three United Arab Emirates-based health organizations: Department of health in Abu Dhabi, SEHA in Abu Dhabi, Dubai health Authority (DHA) in Dubai, 3: 10 Physicians from different specialties, 4: Five EMR managers and 5: Five IT (Information Technology) professionals representing the HIS parties. Qualitative analysis is used as the approach for data analysis. Results: Identifying the managerial and the technical recommendations to be utilized mainly based on digital disruption technologies, tools, and processes. Conclusion: Healthcare has been slow in embracing digital disruption and transformation. In most areas, it is still in the initial stages. Recommendations are based on the UAE cases, highlighting the specific technologies and their features. Keywords: digital disruption, healthcare, big data, electronic medical records, EMR, health information systems, HIS</description><subject>Analysis</subject><subject>Artificial intelligence</subject><subject>Big Data</subject><subject>Computer organization</subject><subject>Control theory</subject><subject>digital disruption</subject><subject>electronic medical records (emr)</subject><subject>Health care</subject><subject>Health care industry</subject><subject>Health facilities</subject><subject>health information systems (his)</subject><subject>healthcare</subject><subject>Information management</subject><subject>Information technology</subject><subject>International agencies</subject><subject>Internet of Things</subject><subject>Literature reviews</subject><subject>Medical informatics</subject><subject>Medical records</subject><subject>Neural networks</subject><subject>Original Research</subject><subject>Patients</subject><subject>Physicians</subject><subject>Qualitative analysis</subject><subject>R&D</subject><subject>Research & development</subject><subject>Technology</subject><issn>1178-6981</issn><issn>1178-6981</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>COVID</sourceid><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNptkltr2zAUx83YWEvXt30Aw2DsYc50sSzrZdAm7VoIBHZ5FpIsOwqK5EnyYN9-chK6Zkx6kDj6nb_OrSjeQrBAsKaflnebr4tvuGGE4BfFJYS0rRrWwpfP7hfFdYw7kFfNMGrZ6-ICN4AgwMhlsV6ZwSRhy5WJYRqT8a4UritvzVCuRBKlceWDFjZtlQi6rMrNOPqQJmeS0fGALrfCWu0GHd8Ur3pho74-nVfFj_u778uHar358ri8WVcqh5kqIVmnJWMUEFIzhDAllIC-xUzoFilZEw2YwpRqqHK8CMoeqA4pjHXXdUDiq-LxqNt5seNjMHsRfnMvDD8YfBi4CMkoq7mQsG8hEAgxUdeSSgxbRFgvYbYjDLLW56PWOMm97pR2KQh7Jnr-4syWD_4XZzVq2qbOAh9OAsH_nHRMfG-i0tYKp_0UOaKAUUwajDP67h9056fgcqkyBQmAFCPylxpETsC43ud_1SzKbyjMyZCazFqL_1B5d3pvlHe6N9l-5vD-mcP20NPo7TS3PJ6DH4-gCj7GoPunYkDA56nj89Tx09ThP36IxDc</recordid><startdate>20220101</startdate><enddate>20220101</enddate><creator>Khatib, Mounir El</creator><creator>Hamidi, Samer</creator><creator>Ameeri, Ishaq Al</creator><creator>Zaabi, Hamad Al</creator><creator>Marqab, Rehab Al</creator><general>Dove Medical Press Limited</general><general>Taylor & Francis Ltd</general><general>Dove</general><general>Dove Medical Press</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7XB</scope><scope>8C1</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>COVID</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>M2O</scope><scope>MBDVC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-6766-3728</orcidid></search><sort><creationdate>20220101</creationdate><title>Digital Disruption and Big Data in Healthcare - Opportunities and Challenges</title><author>Khatib, Mounir El ; 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This means that physicians must increase the time spared for each patient again by the precise proportionality. This may lead to exposing the accuracy and quality of the course of action to be taken for the patients. Increasing the physician's required time for one patient means that the physician can see fewer patients. This will create an issue with the medical management authority as more physicians are needed, and higher expenses will be required. Purpose: The two questions that arise here are 1. Identify the potential opportunities and challenges for extensive data analysis in the healthcare sector. 2. Evaluate different ways in which big medical data can be analyzed? Methods: The authors identified the four concerned parties representing the four potential solutions dimensions to answer these two questions. These parties are 1. physicians, 2. health information systems management (HISM) departments, mainly the EMR system, and 3. Health management departments 4. Relevant Health Information Systems (HIS) parties. A literature review and 25 interviews were conducted. The interviews covered 1: Two global organizations: John Hopkins and Joint Commission International (JCI), 2: Three United Arab Emirates-based health organizations: Department of health in Abu Dhabi, SEHA in Abu Dhabi, Dubai health Authority (DHA) in Dubai, 3: 10 Physicians from different specialties, 4: Five EMR managers and 5: Five IT (Information Technology) professionals representing the HIS parties. Qualitative analysis is used as the approach for data analysis. Results: Identifying the managerial and the technical recommendations to be utilized mainly based on digital disruption technologies, tools, and processes. Conclusion: Healthcare has been slow in embracing digital disruption and transformation. In most areas, it is still in the initial stages. Recommendations are based on the UAE cases, highlighting the specific technologies and their features. Keywords: digital disruption, healthcare, big data, electronic medical records, EMR, health information systems, HIS</abstract><cop>Macclesfield</cop><pub>Dove Medical Press Limited</pub><pmid>36052095</pmid><doi>10.2147/CEOR.S369553</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-6766-3728</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Analysis Artificial intelligence Big Data Computer organization Control theory digital disruption electronic medical records (emr) Health care Health care industry Health facilities health information systems (his) healthcare Information management Information technology International agencies Internet of Things Literature reviews Medical informatics Medical records Neural networks Original Research Patients Physicians Qualitative analysis R&D Research & development Technology |
title | Digital Disruption and Big Data in Healthcare - Opportunities and Challenges |
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