Bio
Brant Oliver is a healthcare improvement and implementation scientist, educator, and board-certified family and psychiatric nurse practitioner (FNP-BC, PMHNP-BC). Dr. Oliver's work focuses on applied healthcare improvement science research with a focus on "3C" (complex, costly, and chronic) conditions including MS, IBD, CF, RA and others, coproduction, learning health systems, and shared decision making (SDM). He has been in clinical practice since 2003, working primarily as a certified MS specialist (MSCN) and a MS neurobehavioral nurse practitioner.
Dr. Oliver holds faculty appointments at Dartmouth, VA Quality Scholars (VAQS), and the MGH Institute of Health Professions School of Nursing. He is a Lean Six Sigma Black Belt and experienced in Clinical Microsystems and IHI Model for Improvement approaches, including IHI Breakthrough Series (BTS) collaboratives. He teaches graduate students, residents and post-doctoral fellows in improvement science, methodology, measurement, and analytics.
Published Research
Oliver BJ, Batalden PB, DiMilia PR, Forcino RC, Foster TC, Nelson EC, Garre BA
BMJ Open|2020 Oct 5
Alexander C, Rovinski-Wagner C, Wagner S, Oliver BJ
J Nurs Care Qual|2020 Sep 14
Patient activation in adults with chronic conditions: A systematic review.
Newland P, Lorenz R, Oliver BJ
J Health Psychol|2020 Aug 23
Horstman MJ, Miltner RS, Wallhagen MI, Patrician PA, Oliver BJ, Roumie CL, Dolansky MA, Perez F, Naik AD, Godwin KM
Acad Med|2020 Aug 4
Initial User Testing of Decision Aids for Multiple Sclerosis Disease-Modifying Therapies.
Hakim H, Newland P, Oliver BJ
J Neurosci Nurs|2020 Aug
Courses Taught
PH 126:
Statistical Measurement and Analysis for Healthcare Quality Improvement (elective)
(1 unit)
This course explores the history, theory, and application of Statistical Process Control (SPC) in health care improvement. Topics include development of measures; data collection; graphical display of data; the selection and generation of SPC analyses for continuous measures, proportions, counts and rare events; for both longitudinal and cross-sectional analyses. Benchmarking, organizational approaches, and multicenter collaborative approaches to improvement measurement are discussed and research study designs for improvement and implementation science are explored. The course emphasizes application of theories and principles through the use of case studies based on ongoing work in the field, individual and small group exercises and interactive discussions with guest presenters. Individual lab exercises, a small group project and an in class final exam are required elements of the course.