Rod Walker, MS, has developed a diverse research portfolio in his 10+ years working as a biostatistician at KPWHRI. His varied interests have led to collaborations in women's health, cancer, aging and geriatrics, pharmacoepidemiology, opioids research, and mental health. During his tenure he has served as an analyst for the Statistical Coordinating Center for the National Cancer Institute's Breast Cancer Surveillance Consortium, evaluated the impact of health system initiatives to reduce risk associated with chronic opioid therapy prescribing, and investigated potential associations between different medications classes and a wide range of outcomes such as pneumonia, fall-related injury, and dementia.
One of Mr. Walker’s longest-running collaborations is with the Adult Changes in Thought (ACT) study, an ongoing longitudinal cohort study seeking to bolster knowledge of risk factors related to dementia, Alzheimer's disease, and healthy aging. As this project and related studies have grown, he has contributed to analyses of associations between medication use and laboratory values and cognitive outcomes within this cohort of older adults, extended this research to associations with neuropathology measures among autopsied individuals, and helped process and analyze activity monitoring data generated from devices worn by ACT participants. Continued collaboration with ACT-related investigators is a highlight of his research at KPWHRI, as the ACT study provides many avenues for increasing public health knowledge of issues relevant for older adults.
A relatively new area of collaboration for Mr. Walker is with researchers from the Mental Health Research Network seeking to use information captured in electronic health records to predict risk of suicide attempt and suicide death. He has appreciated learning from other investigators and biostatisticians on this project, expanding his knowledge in machine learning and risk prediction, as well as in potential issues surrounding health informatics and implementation of tools into clinical workflows. He looks forward to continued opportunities within this research area to address important public health issues in mental and behavioral health.
Survival and longitudinal data analysis; epidemiology; machine learning; two-phase sampling
Biostatistics; cognitive health and dementia; neuropathologic correlates of dementia; factors associated with healthy aging
Biostatistics; suicide risk prediction; interventions for risk reduction; machine learning and health informatics
Biostatistics; pharmacoepidemiology; medication safety in older adults; opioids and chronic pain
Floyd JS, Walker RL, Kuntz JL, Shortreed SM, Fortmann SP, Bayliss EA, Harrington LB, Fuller S, Albertson-Junkans LH, Powers JD, Lee MH, Temposky LA, Dublin S. Association between diabetes severity and risks of COVID-19 infection and outcomes. J Gen Intern Med. 2023 Feb 16. doi: 10.1007/s11606-023-08076-9. [Epub ahead of print]. PubMed
Power MC, Parthasarathy V, Gianattasio KZ, Walker RL, Crane PK, Larson EB, Gibbons LE, Kumar RG, Dams O'Connor K. Investigation of the association of military employment and Parkinson's disease with a validated Parkinson's disease case-finding strategy. Brain Inj. 2022 Dec 16:1-5. doi: 10.1080/02699052.2022.2158234. [Epub ahead of print]. PubMed
Lee CS, Krakauer C, Su YR, Walker R, Blazes M, McCurry SM, Bowen JD, McCormick WC, Lee AY, Boyko E, O'Hare A, Larson EB, Crane PK. Diabetic retinopathy and dementia association, beyond diabetes severity. Am J Ophthalmol. 2022 Dec 10:S0002-9394(22)00486-X. doi: 10.1016/j.ajo.2022.12.003. [Epub ahead of print]. PubMed
Cruz M, Shortreed SM, Richards JE, Coley RY, Yarborough BJ, Walker RL, Johnson E, Ahmedani BK, Rossom R, Coleman KJ, Boggs JM, Beck AL, Simon GE. Machine learning prediction of suicide risk does not identify patients without traditional risk factors. J Clin Psychiatry. 2022 Aug 31;83(5):21m14178. doi: 10.4088/JCP.21m14178. PubMed
Shortreed SM, Gray R, Akosile MA, Walker RL, Fuller S, Temposky L, Fortmann SP, Albertson-Junkans L, Floyd JS, Bayliss EA, Harrington LB, Lee MH, Dublin S. Increased COVID-19 infection risk drives racial and ethnic disparities in severe COVID-19 outcomes. J Racial Ethn Health Disparities. 2022 Jan 24. doi: 10.1007/s40615-021-01205-2. [Epub ahead of print]. PubMed
Models that are easier to explain and use could have better uptake in health care settings.
New work by Susan Shortreed, PhD, finds infection risks drive worse outcomes for some racial and ethnic groups.
Dr. Sascha Dublin tells how studies of KP electronic health record data can improve COVID-19 treatment and prevention.