Lessons learned in migrating from one commercial genetics clinical decision-making tool to another: Assessment of data integrity and utilization
Purpose: Rapid advancements in information technology have greatly influenced clinicians’ engagement with patient data for health maintenance. The electronic health record often contains multiple ways to record risk factors and to identify patients at an elevated genetic risk for cancer. However, th...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-01-01
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| Series: | Genetics in Medicine Open |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2949774424010598 |
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| author | Calvin Le Kevin Tatunay Wayne Liu Haibo Lu Nicole-Ann Rodis Thomas Nam Mercy Y. Laurino Marianne E. Dubard-Gault |
| author_facet | Calvin Le Kevin Tatunay Wayne Liu Haibo Lu Nicole-Ann Rodis Thomas Nam Mercy Y. Laurino Marianne E. Dubard-Gault |
| author_sort | Calvin Le |
| collection | DOAJ |
| description | Purpose: Rapid advancements in information technology have greatly influenced clinicians’ engagement with patient data for health maintenance. The electronic health record often contains multiple ways to record risk factors and to identify patients at an elevated genetic risk for cancer. However, these variables exist in multiple forms and disparate locations in each commercial electronic health record solution resulting in significant variations in how family history or genetic data is codified. Furthermore, there is pressure to migrate from one commercial solution to another at times, prompting the need for a process ensuring data integrity during such a transition. Methods: Between July and December 2023, the genetics team migrated a family history database from one commercial software solution to another. After the data migration of 13,000 patient records, we reviewed 500 randomly selected charts in both support tools to measure the rate of concordance of information transferred. Results: A total of 461 patient charts were reviewed. Of these, 425 (92.2%) were noted to be concordant. Of the 36 charts that were discordant, 9 had incorrect genetic testing results entered, 19 had missing information, 5 charts contained data recorded on paper before 2017 (legacy data), and 3 had additional information transferred. Conclusion: There was high data integrity after migration from one commercial software solution to another. Although these results can ease clinicians’ concerns after such support tool transitions, our effort also highlights areas for improvement in how family and patient genetic data are recorded and utilized for clinical care and research within an institution. |
| format | Article |
| id | doaj-art-0decca32992a4f3ebb41d071132bc2ca |
| institution | Kabale University |
| issn | 2949-7744 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Genetics in Medicine Open |
| spelling | doaj-art-0decca32992a4f3ebb41d071132bc2ca2025-02-12T05:33:13ZengElsevierGenetics in Medicine Open2949-77442025-01-013101913Lessons learned in migrating from one commercial genetics clinical decision-making tool to another: Assessment of data integrity and utilizationCalvin Le0Kevin Tatunay1Wayne Liu2Haibo Lu3Nicole-Ann Rodis4Thomas Nam5Mercy Y. Laurino6Marianne E. Dubard-Gault7University of Washington, Seattle, WAFred Hutchinson Cancer Center, Seattle, WAFred Hutchinson Cancer Center, Seattle, WACancerIQ, Chicago, ILFred Hutchinson Cancer Center, Seattle, WAAmbry Genetics, Laguna Beach, CAFred Hutchinson Cancer Center, Seattle, WAUniversity of Washington, Seattle, WA; Fred Hutchinson Cancer Center, Seattle, WA; Providence Swedish Cancer Institute, Seattle, WA; Correspondence and requests for materials should be addressed to Marianne E. Dubard-Gault, Providence Swedish Cancer Institute, 1221 Madison Street Suite 600, Seattle, WA 98104.Purpose: Rapid advancements in information technology have greatly influenced clinicians’ engagement with patient data for health maintenance. The electronic health record often contains multiple ways to record risk factors and to identify patients at an elevated genetic risk for cancer. However, these variables exist in multiple forms and disparate locations in each commercial electronic health record solution resulting in significant variations in how family history or genetic data is codified. Furthermore, there is pressure to migrate from one commercial solution to another at times, prompting the need for a process ensuring data integrity during such a transition. Methods: Between July and December 2023, the genetics team migrated a family history database from one commercial software solution to another. After the data migration of 13,000 patient records, we reviewed 500 randomly selected charts in both support tools to measure the rate of concordance of information transferred. Results: A total of 461 patient charts were reviewed. Of these, 425 (92.2%) were noted to be concordant. Of the 36 charts that were discordant, 9 had incorrect genetic testing results entered, 19 had missing information, 5 charts contained data recorded on paper before 2017 (legacy data), and 3 had additional information transferred. Conclusion: There was high data integrity after migration from one commercial software solution to another. Although these results can ease clinicians’ concerns after such support tool transitions, our effort also highlights areas for improvement in how family and patient genetic data are recorded and utilized for clinical care and research within an institution.http://www.sciencedirect.com/science/article/pii/S2949774424010598Data integrationData managementFamily historyGeneticsHealth services |
| spellingShingle | Calvin Le Kevin Tatunay Wayne Liu Haibo Lu Nicole-Ann Rodis Thomas Nam Mercy Y. Laurino Marianne E. Dubard-Gault Lessons learned in migrating from one commercial genetics clinical decision-making tool to another: Assessment of data integrity and utilization Genetics in Medicine Open Data integration Data management Family history Genetics Health services |
| title | Lessons learned in migrating from one commercial genetics clinical decision-making tool to another: Assessment of data integrity and utilization |
| title_full | Lessons learned in migrating from one commercial genetics clinical decision-making tool to another: Assessment of data integrity and utilization |
| title_fullStr | Lessons learned in migrating from one commercial genetics clinical decision-making tool to another: Assessment of data integrity and utilization |
| title_full_unstemmed | Lessons learned in migrating from one commercial genetics clinical decision-making tool to another: Assessment of data integrity and utilization |
| title_short | Lessons learned in migrating from one commercial genetics clinical decision-making tool to another: Assessment of data integrity and utilization |
| title_sort | lessons learned in migrating from one commercial genetics clinical decision making tool to another assessment of data integrity and utilization |
| topic | Data integration Data management Family history Genetics Health services |
| url | http://www.sciencedirect.com/science/article/pii/S2949774424010598 |
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