OBJECTIVE: To evaluate the participants in the Mayo Clinic Biobank for their representativeness to the entire Employee and Community Health program (ECH) primary care population with regard to hospital utilization. PATIENTS AND METHODS: Participants enrolled in the Mayo Clinic Biobank from April 1, 2009, to December 31, 2010, were linked to the ECH population. These individuals were categorized into risk tiers (0-4) on the basis of the number of health conditions present as of December 31, 2010. Outcomes were ascertained through December 31, 2011. Hazard ratios (HRs) and 95% CIs for risk of hospitalization, emergency department (ED) visits, and for risk of hospitalization and emergency department (ED) visits were estimated. RESULTS: The 8927 Biobank participants were part of ECH (N=84,872). Compared with the entire ECH population, the Biobank-ECH participants were more likely to be female (64.3% vs 54.6%), older (median age, 58 years vs 47 years), and categorized to tier 0 (6.4% vs 24.0%). There were strong positive associations between tier (tier 4 vs combined tiers 0 and 1) and risk of hospitalization (HR, 5.8; 95% CI, 4.6-7.5) and ED visits (HR, 5.4; 95% CI, 4.2-6.8) among Biobank-ECH participants. Similar associations for risk of hospitalization (HR, 8.5; 95% CI, 7.8-9.3) and ED visits (HR, 6.9; 95% CI, 6.4-7.5) were observed for the entire ECH population. CONCLUSION: Although the Biobank-ECH participants were older and had more chronic conditions compared with the overall ECH population, the associations of risk tier with utilization outcomes were similar, supporting the use of the Biobank participants to assess biomarkers for health care outcomes in the primary care setting.
OBJECTIVE: To evaluate the participants in the Mayo Clinic Biobank for their representativeness to the entire Employee and Community Health program (ECH) primary care population with regard to hospital utilization. PATIENTS AND METHODS: Participants enrolled in the Mayo Clinic Biobank from April 1, 2009, to December 31, 2010, were linked to the ECH population. These individuals were categorized into risk tiers (0-4) on the basis of the number of health conditions present as of December 31, 2010. Outcomes were ascertained through December 31, 2011. Hazard ratios (HRs) and 95% CIs for risk of hospitalization, emergency department (ED) visits, and for risk of hospitalization and emergency department (ED) visits were estimated. RESULTS: The 8927 Biobank participants were part of ECH (N=84,872). Compared with the entire ECH population, the Biobank-ECHparticipants were more likely to be female (64.3% vs 54.6%), older (median age, 58 years vs 47 years), and categorized to tier 0 (6.4% vs 24.0%). There were strong positive associations between tier (tier 4 vs combined tiers 0 and 1) and risk of hospitalization (HR, 5.8; 95% CI, 4.6-7.5) and ED visits (HR, 5.4; 95% CI, 4.2-6.8) among Biobank-ECHparticipants. Similar associations for risk of hospitalization (HR, 8.5; 95% CI, 7.8-9.3) and ED visits (HR, 6.9; 95% CI, 6.4-7.5) were observed for the entire ECH population. CONCLUSION: Although the Biobank-ECHparticipants were older and had more chronic conditions compared with the overall ECH population, the associations of risk tier with utilization outcomes were similar, supporting the use of the Biobank participants to assess biomarkers for health care outcomes in the primary care setting.
Authors: Sarah J Crane; Ericka E Tung; Gregory J Hanson; Stephen Cha; Rajeev Chaudhry; Paul Y Takahashi Journal: BMC Health Serv Res Date: 2010-12-13 Impact factor: 2.655
Authors: Samuel D Searle; Arnold Mitnitski; Evelyne A Gahbauer; Thomas M Gill; Kenneth Rockwood Journal: BMC Geriatr Date: 2008-09-30 Impact factor: 3.921
Authors: Euijung Ryu; Gregory D Jenkins; Yanshan Wang; Mark Olfson; Ardesheer Talati; Lauren Lepow; Brandon J Coombes; Alexander W Charney; Benjamin S Glicksberg; J John Mann; Myrna M Weissman; Priya Wickramaratne; Jyotishman Pathak; Joanna M Biernacka Journal: Psychol Med Date: 2021-11-12 Impact factor: 10.592
Authors: Paul Y Takahashi; Euijung Ryu; Matthew A Hathcock; Janet E Olson; Suzette J Bielinski; James R Cerhan; Jennifer Rand-Weaver; Young J Juhn Journal: J Epidemiol Community Health Date: 2015-10-12 Impact factor: 3.710
Authors: Paul Y Takahashi; Euijung Ryu; Janet E Olson; Erin M Winkler; Matthew A Hathcock; Ruchi Gupta; Jeff A Sloan; Jyotishman Pathak; Suzette J Bielinski; James R Cerhan Journal: Int J Gen Med Date: 2015-08-11
Authors: Euijung Ryu; Paul Y Takahashi; Janet E Olson; Matthew A Hathcock; Paul J Novotny; Jyotishman Pathak; Suzette J Bielinski; James R Cerhan; Jeff A Sloan Journal: Health Qual Life Outcomes Date: 2015-07-03 Impact factor: 3.186
Authors: Janet E Olson; Euijung Ryu; Matthew A Hathcock; Ruchi Gupta; Joshua T Bublitz; Paul Y Takahashi; Suzette J Bielinski; Jennifer L St Sauver; Karen Meagher; Richard R Sharp; Stephen N Thibodeau; Mine Cicek; James R Cerhan Journal: BMJ Open Date: 2019-11-06 Impact factor: 2.692
Authors: Paul Y Takahashi; Euijung Ryu; Suzette J Bielinski; Matthew Hathcock; Gregory D Jenkins; James R Cerhan; Janet E Olson Journal: Pharmgenomics Pers Med Date: 2021-02-11
Authors: Euijung Ryu; Janet E Olson; Young J Juhn; Matthew A Hathcock; Chung-Il Wi; James R Cerhan; Kathleen J Yost; Paul Y Takahashi Journal: BMJ Open Date: 2018-05-14 Impact factor: 2.692
Authors: Shelley-Ann M Girwar; Robert Jabroer; Marta Fiocco; Stephen P Sutch; Mattijs E Numans; Marc A Bruijnzeels Journal: Health Sci Rep Date: 2021-07-23