Robert Penfold, PhD, is a health services research and health policy expert whose work focuses on developing and testing strategies to optimize behavioral health care delivery and patient outcomes—particularly in children and adolescents. His research addresses practical issues, such as how to reduce unnecessary use of antipsychotic medications in youth. He also studies the effects of cost-control policies on how clinicians deliver care, how people use care, and how those changes can promote or worsen their health.
Dr. Penfold is a co-investigator in the Mental Health Research Network (MHRN), a resource for studies on mental health conditions ranging from autism to postnatal depression. He leads the MHRN’s child and adolescent scientific interest group. He is also investigating reasons why similar patients receive different mental health treatment, such as different medications, depending on where they live or receive care.
His other recent and ongoing projects include:
Dr. Penfold has extensive experience gathering and analyzing information from large health databases, including those of Medicare, Medicaid, and the Health Care Systems Research Network’s Virtual Data Warehouse. These data and analyses allow rapid information sharing among Kaiser Permanente Washington and participating sites, which improves patient safety and timely access to effective, cutting-edge therapies.
He has also conducted several novel pragmatic clinical trials using the Epic electronic health record system.
Before joining KPWHRI in 2010, Dr. Penfold held research and teaching positions at Nationwide Children's Hospital in Columbus, Ohio; the Winnipeg Regional Health Authority; the Manitoba Centre for Health Policy; and most recently, at Harvard Medical School in the Department of Population Medicine and Harvard Pilgrim Health Care Institute.
Children and adolescents; anti-psychotics and anti-depressants; bipolar disorder, and depression
Comparative effectiveness; consumer-directed health plans; patient outcomes; costs of chronic illnesses; Medicare and Medicaid
Space-time surveillance; interrupted time series analysis
Shortreed SM, Walker RL, Johnson E, Wellman R, Cruz M, Ziebell R, Coley RY, Yaseen ZS, Dharmarajan S, Penfold RB, Ahmedani BK, Rossom RC, Beck A, Boggs JM, Simon GE. Complex modeling with detailed temporal predictors does not improve health records-based suicide risk prediction. NPJ Digit Med. 2023;6(1):47. doi: 10.1038/s41746-023-00772-4. PubMed
Negriff S, Lynch FL, Cronkite DJ, Pardee RE, Penfold RB. Using natural language processing to identify child maltreatment in health systems. Child Abuse Negl. 2023 Apr;138:106090. doi: 10.1016/j.chiabu.2023.106090. Epub 2023 Feb 8. PubMed
Evers S, Hsu C, Gray MF, Chisolm DJ, Dolcé M, Autio K, Thompson EE, Ervin E, Quintana LM, Beck A, Hansell L, Penfold R. Decision-making among adolescents prescribed antipsychotic medications: Interviews to gain perspectives of youth without psychosis or mania. Clin Child Psychol Psychiatry. 2022 Jun 12;13591045221105197. doi: 10.1177/13591045221105197. Online ahead of print. PubMed
Goger P, Zerr AA, Weersing VR, Dickerson JF, Crawford PM, Sterling SA, Waitzfelder B, Daida YG, Ahmedani BK, Penfold RB, Lynch FL. Health service utilization among children and adolescents with posttraumatic stress disorder: a case-control study. J Dev Behav Pediatr. 2022 Jun-Jul 01;43(5):283-290. doi: 10.1097/DBP.0000000000001041. Epub 2021 Nov 23. PubMed
Penfold RB, Carrell DS, Cronkite DJ, Pabiniak C, Dodd T, Glass AM, Johnson E, Thompson E, Arrighi HM, Stang PE. Development of a machine learning model to predict mild cognitive impairment using natural language processing in the absence of screening. BMC Med Inform Decis Mak. 2022 May 12;22(1):129. doi: 10.1186/s12911-022-01864-z. PubMed
KPWHRI researchers are contributing to better mental health care for people nationwide.
Models that are easier to explain, use could have better uptake in health care settings.
The HCSRN conference is a venue for collaborative work to improve health and health care.
Using doctor's notes to learn about drug reactions, dementia, and cannabis use.