Representativeness of breast cancer cases in an integrated health care delivery system View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2015-12

AUTHORS

Scarlett Lin Gomez, Salma Shariff-Marco, Julie Von Behren, Marilyn L. Kwan, Candyce H. Kroenke, Theresa H. M. Keegan, Peggy Reynolds, Lawrence H. Kushi

ABSTRACT

BACKGROUND: Integrated health care delivery systems, with their comprehensive and integrated electronic medical records (EMR), are well-poised to conduct research that leverages the detailed clinical data within the EMRs. However, information regarding the representativeness of these clinical populations is limited, and thus the generalizability of research findings is uncertain. METHODS: Using data from the population-based California Cancer Registry, we compared age-adjusted distributions of patient and neighborhood characteristics for three groups of breast cancer patients: 1) those diagnosed within Kaiser Permanente Northern California (KPNC), 2) non-KPNC patients from NCI-designated cancer centers, and 3) those from all other hospitals. RESULTS: KPNC patients represented 32 % (N = 36,109); cancer center patients represented 7 % (N = 7805); and all other hospitals represented 61 % (N = 68,330) of the total breast cancer patients from this geographic area during 1996-2009. Compared with cases from all other hospitals, KPNC had slightly fewer non-Hispanic Whites (70.6 % versus 74.4 %) but more Blacks (8.1 % versus 5.0 %), slightly more patients in the 50-69 age range and fewer in the younger and older age groups, a slightly lower proportion of in situ but higher proportion of stage I disease (41.6 % versus 38.9 %), were slightly less likely to reside in the lowest (4.2 % versus 6.5 %) and highest (36.2 % versus 39.0 %) socioeconomic status neighborhoods, and more likely to live in suburban metropolitan areas and neighborhoods with more racial/ethnic minorities. Cancer center patients differed substantially from patients from KPNC and all other hospitals on all characteristics assessed. All differences were statistically significant (p < .001). CONCLUSIONS: Although much of clinical research discoveries are based in academic medical centers, patients from large, integrated medical centers are likely more representative of the underlying population, providing support for the generalizability of cancer research based on electronic data from these centers. More... »

PAGES

688

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s12885-015-1696-9

DOI

http://dx.doi.org/10.1186/s12885-015-1696-9

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https://app.dimensions.ai/details/publication/pub.1046254358

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/26467773


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38 schema:description BACKGROUND: Integrated health care delivery systems, with their comprehensive and integrated electronic medical records (EMR), are well-poised to conduct research that leverages the detailed clinical data within the EMRs. However, information regarding the representativeness of these clinical populations is limited, and thus the generalizability of research findings is uncertain. METHODS: Using data from the population-based California Cancer Registry, we compared age-adjusted distributions of patient and neighborhood characteristics for three groups of breast cancer patients: 1) those diagnosed within Kaiser Permanente Northern California (KPNC), 2) non-KPNC patients from NCI-designated cancer centers, and 3) those from all other hospitals. RESULTS: KPNC patients represented 32 % (N = 36,109); cancer center patients represented 7 % (N = 7805); and all other hospitals represented 61 % (N = 68,330) of the total breast cancer patients from this geographic area during 1996-2009. Compared with cases from all other hospitals, KPNC had slightly fewer non-Hispanic Whites (70.6 % versus 74.4 %) but more Blacks (8.1 % versus 5.0 %), slightly more patients in the 50-69 age range and fewer in the younger and older age groups, a slightly lower proportion of in situ but higher proportion of stage I disease (41.6 % versus 38.9 %), were slightly less likely to reside in the lowest (4.2 % versus 6.5 %) and highest (36.2 % versus 39.0 %) socioeconomic status neighborhoods, and more likely to live in suburban metropolitan areas and neighborhoods with more racial/ethnic minorities. Cancer center patients differed substantially from patients from KPNC and all other hospitals on all characteristics assessed. All differences were statistically significant (p < .001). CONCLUSIONS: Although much of clinical research discoveries are based in academic medical centers, patients from large, integrated medical centers are likely more representative of the underlying population, providing support for the generalizability of cancer research based on electronic data from these centers.
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