Merging Children's Oncology Group Data with an External Administrative Database Using Indirect Patient Identifiers: A Report from the Children's Oncology Group
Clinical trials data from National Cancer Institute (NCI)-funded cooperative oncology group trials could be enhanced by merging with external data sources. Merging without direct patient identifiers would provide additional patient privacy protections. We sought to develop and validate a matching al...
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| Veröffentlicht in: | PloS one 2015-11, Vol.10 (11), p.e0143480 |
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| creator | Li, Yimei Hall, Matt Fisher, Brian T Seif, Alix E Huang, Yuan-Shung Bagatell, Rochelle Getz, Kelly D Alonzo, Todd A Gerbing, Robert B Sung, Lillian Adamson, Peter C Gamis, Alan Aplenc, Richard |
| description | Clinical trials data from National Cancer Institute (NCI)-funded cooperative oncology group trials could be enhanced by merging with external data sources. Merging without direct patient identifiers would provide additional patient privacy protections. We sought to develop and validate a matching algorithm that uses only indirect patient identifiers.
We merged the data from two Phase III Children's Oncology Group (COG) trials for de novo acute myeloid leukemia (AML) with the Pediatric Health Information Systems (PHIS). We developed a stepwise matching algorithm that used indirect identifiers including treatment site, gender, birth year, birth month, enrollment year and enrollment month. Results from the stepwise algorithm were compared against the direct merge method that used date of birth, treatment site, and gender. The indirect merge algorithm was developed on AAML0531 and validated on AAML1031.
Of 415 patients enrolled on the AAML0531 trial at PHIS centers, we successfully matched 378 (91.1%) patients using the indirect stepwise algorithm. Comparison to the direct merge result suggested that 362 (95.7%) matches identified by the indirect merge algorithm were concordant with the direct merge result. When validating the indirect stepwise algorithm using the AAML1031 trial, we successfully matched 157 out of 165 patients (95.2%) and 150 (95.5%) of the indirectly merged matches were concordant with the directly merged matches.
These data demonstrate that patients enrolled on COG clinical trials can be successfully merged with PHIS administrative data using a stepwise algorithm based on indirect patient identifiers. The merged data sets can be used as a platform for comparative effectiveness and cost effectiveness studies. |
| doi_str_mv | 10.1371/journal.pone.0143480 |
| format | Article |
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We merged the data from two Phase III Children's Oncology Group (COG) trials for de novo acute myeloid leukemia (AML) with the Pediatric Health Information Systems (PHIS). We developed a stepwise matching algorithm that used indirect identifiers including treatment site, gender, birth year, birth month, enrollment year and enrollment month. Results from the stepwise algorithm were compared against the direct merge method that used date of birth, treatment site, and gender. The indirect merge algorithm was developed on AAML0531 and validated on AAML1031.
Of 415 patients enrolled on the AAML0531 trial at PHIS centers, we successfully matched 378 (91.1%) patients using the indirect stepwise algorithm. Comparison to the direct merge result suggested that 362 (95.7%) matches identified by the indirect merge algorithm were concordant with the direct merge result. When validating the indirect stepwise algorithm using the AAML1031 trial, we successfully matched 157 out of 165 patients (95.2%) and 150 (95.5%) of the indirectly merged matches were concordant with the directly merged matches.
These data demonstrate that patients enrolled on COG clinical trials can be successfully merged with PHIS administrative data using a stepwise algorithm based on indirect patient identifiers. The merged data sets can be used as a platform for comparative effectiveness and cost effectiveness studies.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0143480</identifier><identifier>PMID: 26606521</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Acute myeloid leukemia ; Algorithms ; Analysis ; Birth ; Bone marrow ; Cancer ; Chemotherapy ; Childbirth & labor ; Children ; Clinical trials ; Clinical Trials, Phase III as Topic ; Cost effectiveness ; Databases, Factual ; Enrollments ; Epidemiology ; Health aspects ; Hematology ; Hospitals ; Humans ; Identification methods ; Information Storage and Retrieval ; Information systems ; Leukemia ; Leukemia, Myeloid, Acute ; Matching ; Medical informatics ; Medical Oncology ; Medical records ; Medical research ; Medicare ; Mortality ; Myeloid leukemia ; Oncology ; Patients ; Patients' rights ; Pediatrics ; Preventive medicine ; Privacy ; Reproducibility of Results ; Transplants & implants ; Two phase</subject><ispartof>PloS one, 2015-11, Vol.10 (11), p.e0143480</ispartof><rights>COPYRIGHT 2015 Public Library of Science</rights><rights>2015 Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2015 Li et al 2015 Li et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-dfc4af316d53a6cfe3d7c1661f774340eb93118641cad5224bab9994747708363</citedby><cites>FETCH-LOGICAL-c692t-dfc4af316d53a6cfe3d7c1661f774340eb93118641cad5224bab9994747708363</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4659568/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4659568/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79342,79343</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26606521$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Li, Yimei</creatorcontrib><creatorcontrib>Hall, Matt</creatorcontrib><creatorcontrib>Fisher, Brian T</creatorcontrib><creatorcontrib>Seif, Alix E</creatorcontrib><creatorcontrib>Huang, Yuan-Shung</creatorcontrib><creatorcontrib>Bagatell, Rochelle</creatorcontrib><creatorcontrib>Getz, Kelly D</creatorcontrib><creatorcontrib>Alonzo, Todd A</creatorcontrib><creatorcontrib>Gerbing, Robert B</creatorcontrib><creatorcontrib>Sung, Lillian</creatorcontrib><creatorcontrib>Adamson, Peter C</creatorcontrib><creatorcontrib>Gamis, Alan</creatorcontrib><creatorcontrib>Aplenc, Richard</creatorcontrib><title>Merging Children's Oncology Group Data with an External Administrative Database Using Indirect Patient Identifiers: A Report from the Children's Oncology Group</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Clinical trials data from National Cancer Institute (NCI)-funded cooperative oncology group trials could be enhanced by merging with external data sources. Merging without direct patient identifiers would provide additional patient privacy protections. We sought to develop and validate a matching algorithm that uses only indirect patient identifiers.
We merged the data from two Phase III Children's Oncology Group (COG) trials for de novo acute myeloid leukemia (AML) with the Pediatric Health Information Systems (PHIS). We developed a stepwise matching algorithm that used indirect identifiers including treatment site, gender, birth year, birth month, enrollment year and enrollment month. Results from the stepwise algorithm were compared against the direct merge method that used date of birth, treatment site, and gender. The indirect merge algorithm was developed on AAML0531 and validated on AAML1031.
Of 415 patients enrolled on the AAML0531 trial at PHIS centers, we successfully matched 378 (91.1%) patients using the indirect stepwise algorithm. Comparison to the direct merge result suggested that 362 (95.7%) matches identified by the indirect merge algorithm were concordant with the direct merge result. When validating the indirect stepwise algorithm using the AAML1031 trial, we successfully matched 157 out of 165 patients (95.2%) and 150 (95.5%) of the indirectly merged matches were concordant with the directly merged matches.
These data demonstrate that patients enrolled on COG clinical trials can be successfully merged with PHIS administrative data using a stepwise algorithm based on indirect patient identifiers. The merged data sets can be used as a platform for comparative effectiveness and cost effectiveness studies.</description><subject>Acute myeloid leukemia</subject><subject>Algorithms</subject><subject>Analysis</subject><subject>Birth</subject><subject>Bone marrow</subject><subject>Cancer</subject><subject>Chemotherapy</subject><subject>Childbirth & labor</subject><subject>Children</subject><subject>Clinical trials</subject><subject>Clinical Trials, Phase III as Topic</subject><subject>Cost effectiveness</subject><subject>Databases, Factual</subject><subject>Enrollments</subject><subject>Epidemiology</subject><subject>Health aspects</subject><subject>Hematology</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Identification methods</subject><subject>Information Storage and Retrieval</subject><subject>Information systems</subject><subject>Leukemia</subject><subject>Leukemia, Myeloid, Acute</subject><subject>Matching</subject><subject>Medical informatics</subject><subject>Medical Oncology</subject><subject>Medical records</subject><subject>Medical research</subject><subject>Medicare</subject><subject>Mortality</subject><subject>Myeloid leukemia</subject><subject>Oncology</subject><subject>Patients</subject><subject>Patients' rights</subject><subject>Pediatrics</subject><subject>Preventive medicine</subject><subject>Privacy</subject><subject>Reproducibility of Results</subject><subject>Transplants & implants</subject><subject>Two 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Children's Oncology Group Data with an External Administrative Database Using Indirect Patient Identifiers: A Report from the Children's Oncology Group</title><author>Li, Yimei ; Hall, Matt ; Fisher, Brian T ; Seif, Alix E ; Huang, Yuan-Shung ; Bagatell, Rochelle ; Getz, Kelly D ; Alonzo, Todd A ; Gerbing, Robert B ; Sung, Lillian ; Adamson, Peter C ; Gamis, Alan ; Aplenc, Richard</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c692t-dfc4af316d53a6cfe3d7c1661f774340eb93118641cad5224bab9994747708363</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Acute myeloid leukemia</topic><topic>Algorithms</topic><topic>Analysis</topic><topic>Birth</topic><topic>Bone marrow</topic><topic>Cancer</topic><topic>Chemotherapy</topic><topic>Childbirth & labor</topic><topic>Children</topic><topic>Clinical trials</topic><topic>Clinical Trials, Phase III as Topic</topic><topic>Cost 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One</addtitle><date>2015-11-25</date><risdate>2015</risdate><volume>10</volume><issue>11</issue><spage>e0143480</spage><pages>e0143480-</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Clinical trials data from National Cancer Institute (NCI)-funded cooperative oncology group trials could be enhanced by merging with external data sources. Merging without direct patient identifiers would provide additional patient privacy protections. We sought to develop and validate a matching algorithm that uses only indirect patient identifiers.
We merged the data from two Phase III Children's Oncology Group (COG) trials for de novo acute myeloid leukemia (AML) with the Pediatric Health Information Systems (PHIS). We developed a stepwise matching algorithm that used indirect identifiers including treatment site, gender, birth year, birth month, enrollment year and enrollment month. Results from the stepwise algorithm were compared against the direct merge method that used date of birth, treatment site, and gender. The indirect merge algorithm was developed on AAML0531 and validated on AAML1031.
Of 415 patients enrolled on the AAML0531 trial at PHIS centers, we successfully matched 378 (91.1%) patients using the indirect stepwise algorithm. Comparison to the direct merge result suggested that 362 (95.7%) matches identified by the indirect merge algorithm were concordant with the direct merge result. When validating the indirect stepwise algorithm using the AAML1031 trial, we successfully matched 157 out of 165 patients (95.2%) and 150 (95.5%) of the indirectly merged matches were concordant with the directly merged matches.
These data demonstrate that patients enrolled on COG clinical trials can be successfully merged with PHIS administrative data using a stepwise algorithm based on indirect patient identifiers. The merged data sets can be used as a platform for comparative effectiveness and cost effectiveness studies.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>26606521</pmid><doi>10.1371/journal.pone.0143480</doi><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2015-11, Vol.10 (11), p.e0143480 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_1736408219 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; Free Full-Text Journals in Chemistry; Public Library of Science (PLoS) |
| subjects | Acute myeloid leukemia Algorithms Analysis Birth Bone marrow Cancer Chemotherapy Childbirth & labor Children Clinical trials Clinical Trials, Phase III as Topic Cost effectiveness Databases, Factual Enrollments Epidemiology Health aspects Hematology Hospitals Humans Identification methods Information Storage and Retrieval Information systems Leukemia Leukemia, Myeloid, Acute Matching Medical informatics Medical Oncology Medical records Medical research Medicare Mortality Myeloid leukemia Oncology Patients Patients' rights Pediatrics Preventive medicine Privacy Reproducibility of Results Transplants & implants Two phase |
| title | Merging Children's Oncology Group Data with an External Administrative Database Using Indirect Patient Identifiers: A Report from the Children's Oncology Group |
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