474 Innovative solutions to streamline data collection, exchange, and utilization in translational research
OBJECTIVES/GOALS: To determine the utility of any standard, one must first evaluate whether or not the standard meets the needs of the use case it is meant to support. We aim to quantify data availability of the HL7 FHIR standard to support data collection for three state-based registries in a rural...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Maryam Y. Garza [verfasserIn] Fred Prior [verfasserIn] Joseph A. Sanford [verfasserIn] Kevin W. Sexton [verfasserIn] Meredith N. Zozus [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2022 |
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| Übergeordnetes Werk: |
In: Journal of Clinical and Translational Science - Cambridge University Press, 2019, 6(2022), Seite 94-94 |
|---|---|
| Übergeordnetes Werk: |
volume:6 ; year:2022 ; pages:94-94 |
| Links: |
|---|
| DOI / URN: |
10.1017/cts.2022.277 |
|---|
| Katalog-ID: |
DOAJ088056740 |
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| 520 | |a OBJECTIVES/GOALS: To determine the utility of any standard, one must first evaluate whether or not the standard meets the needs of the use case it is meant to support. We aim to quantify data availability of the HL7 FHIR standard to support data collection for three state-based registries in a rural state and measure the potential effects on data quality and collection time. METHODS/STUDY POPULATION: FHIR mapping will be performed to assess the level of HL7 FHIR standard completeness (or data element coverage) in supporting data collection for the three registries. A systematic approach, previously developed and used by Garza and Zozus, will be used to map registry data elements to corresponding HL7 FHIR standard resources. FHIR coverage will be calculated as a percentage (total data elements “Available in FHIR” vs. total data elements overall) and will be observed across different domain areas (i.e., demographics vs. medications vs. vital signs, etc.) in order to identify the domains with the least and most coverage. RESULTS/ANTICIPATED RESULTS: Although there have been informatics solutions that relied on data exchange standards to improve data collection, none have actually evaluated the coverage of the standard for supporting the needs of clinical data registries. To address this gap, we aim to evaluate the availability of the HL7 FHIR standard to support data collection for three state-based registries. These results will provide insight into the generalizability of a FHIR-based solution to support data acquisition and processing across multiple registries and demonstrate the potential for seamless exchange of that data for secondary use in clinical and translational research. Quantifying the coverage will also be used to further advance its development in order to meet the data collection needs of state and national clinical data registries. DISCUSSION/SIGNIFICANCE: Registries often rely on manual abstraction of EHR data. These manual approaches have had a negative impact on data quality and cost, often due to the complexities associated with collection and mapping of the data to fit the registry model. HL7 FHIR has the potential to address these issues by automating part or all of the data collection process. | ||
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10.1017/cts.2022.277 doi (DE-627)DOAJ088056740 (DE-599)DOAJ8b0a49a4f5074032b05d66513514b45d DE-627 ger DE-627 rakwb eng Maryam Y. Garza verfasserin aut 474 Innovative solutions to streamline data collection, exchange, and utilization in translational research 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier OBJECTIVES/GOALS: To determine the utility of any standard, one must first evaluate whether or not the standard meets the needs of the use case it is meant to support. We aim to quantify data availability of the HL7 FHIR standard to support data collection for three state-based registries in a rural state and measure the potential effects on data quality and collection time. METHODS/STUDY POPULATION: FHIR mapping will be performed to assess the level of HL7 FHIR standard completeness (or data element coverage) in supporting data collection for the three registries. A systematic approach, previously developed and used by Garza and Zozus, will be used to map registry data elements to corresponding HL7 FHIR standard resources. FHIR coverage will be calculated as a percentage (total data elements “Available in FHIR” vs. total data elements overall) and will be observed across different domain areas (i.e., demographics vs. medications vs. vital signs, etc.) in order to identify the domains with the least and most coverage. RESULTS/ANTICIPATED RESULTS: Although there have been informatics solutions that relied on data exchange standards to improve data collection, none have actually evaluated the coverage of the standard for supporting the needs of clinical data registries. To address this gap, we aim to evaluate the availability of the HL7 FHIR standard to support data collection for three state-based registries. These results will provide insight into the generalizability of a FHIR-based solution to support data acquisition and processing across multiple registries and demonstrate the potential for seamless exchange of that data for secondary use in clinical and translational research. Quantifying the coverage will also be used to further advance its development in order to meet the data collection needs of state and national clinical data registries. DISCUSSION/SIGNIFICANCE: Registries often rely on manual abstraction of EHR data. These manual approaches have had a negative impact on data quality and cost, often due to the complexities associated with collection and mapping of the data to fit the registry model. HL7 FHIR has the potential to address these issues by automating part or all of the data collection process. Medicine R Fred Prior verfasserin aut Joseph A. Sanford verfasserin aut Kevin W. Sexton verfasserin aut Meredith N. Zozus verfasserin aut In Journal of Clinical and Translational Science Cambridge University Press, 2019 6(2022), Seite 94-94 (DE-627)891016082 (DE-600)2898186-8 20598661 nnns volume:6 year:2022 pages:94-94 https://doi.org/10.1017/cts.2022.277 kostenfrei https://doaj.org/article/8b0a49a4f5074032b05d66513514b45d kostenfrei https://www.cambridge.org/core/product/identifier/S2059866122002771/type/journal_article kostenfrei https://doaj.org/toc/2059-8661 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2110 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2022 94-94 |
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10.1017/cts.2022.277 doi (DE-627)DOAJ088056740 (DE-599)DOAJ8b0a49a4f5074032b05d66513514b45d DE-627 ger DE-627 rakwb eng Maryam Y. Garza verfasserin aut 474 Innovative solutions to streamline data collection, exchange, and utilization in translational research 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier OBJECTIVES/GOALS: To determine the utility of any standard, one must first evaluate whether or not the standard meets the needs of the use case it is meant to support. We aim to quantify data availability of the HL7 FHIR standard to support data collection for three state-based registries in a rural state and measure the potential effects on data quality and collection time. METHODS/STUDY POPULATION: FHIR mapping will be performed to assess the level of HL7 FHIR standard completeness (or data element coverage) in supporting data collection for the three registries. A systematic approach, previously developed and used by Garza and Zozus, will be used to map registry data elements to corresponding HL7 FHIR standard resources. FHIR coverage will be calculated as a percentage (total data elements “Available in FHIR” vs. total data elements overall) and will be observed across different domain areas (i.e., demographics vs. medications vs. vital signs, etc.) in order to identify the domains with the least and most coverage. RESULTS/ANTICIPATED RESULTS: Although there have been informatics solutions that relied on data exchange standards to improve data collection, none have actually evaluated the coverage of the standard for supporting the needs of clinical data registries. To address this gap, we aim to evaluate the availability of the HL7 FHIR standard to support data collection for three state-based registries. These results will provide insight into the generalizability of a FHIR-based solution to support data acquisition and processing across multiple registries and demonstrate the potential for seamless exchange of that data for secondary use in clinical and translational research. Quantifying the coverage will also be used to further advance its development in order to meet the data collection needs of state and national clinical data registries. DISCUSSION/SIGNIFICANCE: Registries often rely on manual abstraction of EHR data. These manual approaches have had a negative impact on data quality and cost, often due to the complexities associated with collection and mapping of the data to fit the registry model. HL7 FHIR has the potential to address these issues by automating part or all of the data collection process. Medicine R Fred Prior verfasserin aut Joseph A. Sanford verfasserin aut Kevin W. Sexton verfasserin aut Meredith N. Zozus verfasserin aut In Journal of Clinical and Translational Science Cambridge University Press, 2019 6(2022), Seite 94-94 (DE-627)891016082 (DE-600)2898186-8 20598661 nnns volume:6 year:2022 pages:94-94 https://doi.org/10.1017/cts.2022.277 kostenfrei https://doaj.org/article/8b0a49a4f5074032b05d66513514b45d kostenfrei https://www.cambridge.org/core/product/identifier/S2059866122002771/type/journal_article kostenfrei https://doaj.org/toc/2059-8661 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2110 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2022 94-94 |
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10.1017/cts.2022.277 doi (DE-627)DOAJ088056740 (DE-599)DOAJ8b0a49a4f5074032b05d66513514b45d DE-627 ger DE-627 rakwb eng Maryam Y. Garza verfasserin aut 474 Innovative solutions to streamline data collection, exchange, and utilization in translational research 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier OBJECTIVES/GOALS: To determine the utility of any standard, one must first evaluate whether or not the standard meets the needs of the use case it is meant to support. We aim to quantify data availability of the HL7 FHIR standard to support data collection for three state-based registries in a rural state and measure the potential effects on data quality and collection time. METHODS/STUDY POPULATION: FHIR mapping will be performed to assess the level of HL7 FHIR standard completeness (or data element coverage) in supporting data collection for the three registries. A systematic approach, previously developed and used by Garza and Zozus, will be used to map registry data elements to corresponding HL7 FHIR standard resources. FHIR coverage will be calculated as a percentage (total data elements “Available in FHIR” vs. total data elements overall) and will be observed across different domain areas (i.e., demographics vs. medications vs. vital signs, etc.) in order to identify the domains with the least and most coverage. RESULTS/ANTICIPATED RESULTS: Although there have been informatics solutions that relied on data exchange standards to improve data collection, none have actually evaluated the coverage of the standard for supporting the needs of clinical data registries. To address this gap, we aim to evaluate the availability of the HL7 FHIR standard to support data collection for three state-based registries. These results will provide insight into the generalizability of a FHIR-based solution to support data acquisition and processing across multiple registries and demonstrate the potential for seamless exchange of that data for secondary use in clinical and translational research. Quantifying the coverage will also be used to further advance its development in order to meet the data collection needs of state and national clinical data registries. DISCUSSION/SIGNIFICANCE: Registries often rely on manual abstraction of EHR data. These manual approaches have had a negative impact on data quality and cost, often due to the complexities associated with collection and mapping of the data to fit the registry model. HL7 FHIR has the potential to address these issues by automating part or all of the data collection process. Medicine R Fred Prior verfasserin aut Joseph A. Sanford verfasserin aut Kevin W. Sexton verfasserin aut Meredith N. Zozus verfasserin aut In Journal of Clinical and Translational Science Cambridge University Press, 2019 6(2022), Seite 94-94 (DE-627)891016082 (DE-600)2898186-8 20598661 nnns volume:6 year:2022 pages:94-94 https://doi.org/10.1017/cts.2022.277 kostenfrei https://doaj.org/article/8b0a49a4f5074032b05d66513514b45d kostenfrei https://www.cambridge.org/core/product/identifier/S2059866122002771/type/journal_article kostenfrei https://doaj.org/toc/2059-8661 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2110 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2022 94-94 |
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10.1017/cts.2022.277 doi (DE-627)DOAJ088056740 (DE-599)DOAJ8b0a49a4f5074032b05d66513514b45d DE-627 ger DE-627 rakwb eng Maryam Y. Garza verfasserin aut 474 Innovative solutions to streamline data collection, exchange, and utilization in translational research 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier OBJECTIVES/GOALS: To determine the utility of any standard, one must first evaluate whether or not the standard meets the needs of the use case it is meant to support. We aim to quantify data availability of the HL7 FHIR standard to support data collection for three state-based registries in a rural state and measure the potential effects on data quality and collection time. METHODS/STUDY POPULATION: FHIR mapping will be performed to assess the level of HL7 FHIR standard completeness (or data element coverage) in supporting data collection for the three registries. A systematic approach, previously developed and used by Garza and Zozus, will be used to map registry data elements to corresponding HL7 FHIR standard resources. FHIR coverage will be calculated as a percentage (total data elements “Available in FHIR” vs. total data elements overall) and will be observed across different domain areas (i.e., demographics vs. medications vs. vital signs, etc.) in order to identify the domains with the least and most coverage. RESULTS/ANTICIPATED RESULTS: Although there have been informatics solutions that relied on data exchange standards to improve data collection, none have actually evaluated the coverage of the standard for supporting the needs of clinical data registries. To address this gap, we aim to evaluate the availability of the HL7 FHIR standard to support data collection for three state-based registries. These results will provide insight into the generalizability of a FHIR-based solution to support data acquisition and processing across multiple registries and demonstrate the potential for seamless exchange of that data for secondary use in clinical and translational research. Quantifying the coverage will also be used to further advance its development in order to meet the data collection needs of state and national clinical data registries. DISCUSSION/SIGNIFICANCE: Registries often rely on manual abstraction of EHR data. These manual approaches have had a negative impact on data quality and cost, often due to the complexities associated with collection and mapping of the data to fit the registry model. HL7 FHIR has the potential to address these issues by automating part or all of the data collection process. Medicine R Fred Prior verfasserin aut Joseph A. Sanford verfasserin aut Kevin W. Sexton verfasserin aut Meredith N. Zozus verfasserin aut In Journal of Clinical and Translational Science Cambridge University Press, 2019 6(2022), Seite 94-94 (DE-627)891016082 (DE-600)2898186-8 20598661 nnns volume:6 year:2022 pages:94-94 https://doi.org/10.1017/cts.2022.277 kostenfrei https://doaj.org/article/8b0a49a4f5074032b05d66513514b45d kostenfrei https://www.cambridge.org/core/product/identifier/S2059866122002771/type/journal_article kostenfrei https://doaj.org/toc/2059-8661 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2110 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2022 94-94 |
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OBJECTIVES/GOALS: To determine the utility of any standard, one must first evaluate whether or not the standard meets the needs of the use case it is meant to support. We aim to quantify data availability of the HL7 FHIR standard to support data collection for three state-based registries in a rural state and measure the potential effects on data quality and collection time. METHODS/STUDY POPULATION: FHIR mapping will be performed to assess the level of HL7 FHIR standard completeness (or data element coverage) in supporting data collection for the three registries. A systematic approach, previously developed and used by Garza and Zozus, will be used to map registry data elements to corresponding HL7 FHIR standard resources. FHIR coverage will be calculated as a percentage (total data elements “Available in FHIR” vs. total data elements overall) and will be observed across different domain areas (i.e., demographics vs. medications vs. vital signs, etc.) in order to identify the domains with the least and most coverage. RESULTS/ANTICIPATED RESULTS: Although there have been informatics solutions that relied on data exchange standards to improve data collection, none have actually evaluated the coverage of the standard for supporting the needs of clinical data registries. To address this gap, we aim to evaluate the availability of the HL7 FHIR standard to support data collection for three state-based registries. These results will provide insight into the generalizability of a FHIR-based solution to support data acquisition and processing across multiple registries and demonstrate the potential for seamless exchange of that data for secondary use in clinical and translational research. Quantifying the coverage will also be used to further advance its development in order to meet the data collection needs of state and national clinical data registries. DISCUSSION/SIGNIFICANCE: Registries often rely on manual abstraction of EHR data. These manual approaches have had a negative impact on data quality and cost, often due to the complexities associated with collection and mapping of the data to fit the registry model. HL7 FHIR has the potential to address these issues by automating part or all of the data collection process. |
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OBJECTIVES/GOALS: To determine the utility of any standard, one must first evaluate whether or not the standard meets the needs of the use case it is meant to support. We aim to quantify data availability of the HL7 FHIR standard to support data collection for three state-based registries in a rural state and measure the potential effects on data quality and collection time. METHODS/STUDY POPULATION: FHIR mapping will be performed to assess the level of HL7 FHIR standard completeness (or data element coverage) in supporting data collection for the three registries. A systematic approach, previously developed and used by Garza and Zozus, will be used to map registry data elements to corresponding HL7 FHIR standard resources. FHIR coverage will be calculated as a percentage (total data elements “Available in FHIR” vs. total data elements overall) and will be observed across different domain areas (i.e., demographics vs. medications vs. vital signs, etc.) in order to identify the domains with the least and most coverage. RESULTS/ANTICIPATED RESULTS: Although there have been informatics solutions that relied on data exchange standards to improve data collection, none have actually evaluated the coverage of the standard for supporting the needs of clinical data registries. To address this gap, we aim to evaluate the availability of the HL7 FHIR standard to support data collection for three state-based registries. These results will provide insight into the generalizability of a FHIR-based solution to support data acquisition and processing across multiple registries and demonstrate the potential for seamless exchange of that data for secondary use in clinical and translational research. Quantifying the coverage will also be used to further advance its development in order to meet the data collection needs of state and national clinical data registries. DISCUSSION/SIGNIFICANCE: Registries often rely on manual abstraction of EHR data. These manual approaches have had a negative impact on data quality and cost, often due to the complexities associated with collection and mapping of the data to fit the registry model. HL7 FHIR has the potential to address these issues by automating part or all of the data collection process. |
| abstract_unstemmed |
OBJECTIVES/GOALS: To determine the utility of any standard, one must first evaluate whether or not the standard meets the needs of the use case it is meant to support. We aim to quantify data availability of the HL7 FHIR standard to support data collection for three state-based registries in a rural state and measure the potential effects on data quality and collection time. METHODS/STUDY POPULATION: FHIR mapping will be performed to assess the level of HL7 FHIR standard completeness (or data element coverage) in supporting data collection for the three registries. A systematic approach, previously developed and used by Garza and Zozus, will be used to map registry data elements to corresponding HL7 FHIR standard resources. FHIR coverage will be calculated as a percentage (total data elements “Available in FHIR” vs. total data elements overall) and will be observed across different domain areas (i.e., demographics vs. medications vs. vital signs, etc.) in order to identify the domains with the least and most coverage. RESULTS/ANTICIPATED RESULTS: Although there have been informatics solutions that relied on data exchange standards to improve data collection, none have actually evaluated the coverage of the standard for supporting the needs of clinical data registries. To address this gap, we aim to evaluate the availability of the HL7 FHIR standard to support data collection for three state-based registries. These results will provide insight into the generalizability of a FHIR-based solution to support data acquisition and processing across multiple registries and demonstrate the potential for seamless exchange of that data for secondary use in clinical and translational research. Quantifying the coverage will also be used to further advance its development in order to meet the data collection needs of state and national clinical data registries. DISCUSSION/SIGNIFICANCE: Registries often rely on manual abstraction of EHR data. These manual approaches have had a negative impact on data quality and cost, often due to the complexities associated with collection and mapping of the data to fit the registry model. HL7 FHIR has the potential to address these issues by automating part or all of the data collection process. |
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474 Innovative solutions to streamline data collection, exchange, and utilization in translational research |
| url |
https://doi.org/10.1017/cts.2022.277 https://doaj.org/article/8b0a49a4f5074032b05d66513514b45d https://www.cambridge.org/core/product/identifier/S2059866122002771/type/journal_article https://doaj.org/toc/2059-8661 |
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Fred Prior Joseph A. Sanford Kevin W. Sexton Meredith N. Zozus |
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