Christopher Hess
· The Jill F. And Richard W. Cope Professorship; Associate Professor Of Neurology; Movement Disorders Fellowship Director And Medical Director; Director, Neurotechnology Program For Movement Disorders And Neurorestoration; Norman Fixel InstituteVerifiedUniversity of Florida · Neurology
Active 1993–2026
About
Christopher W. Hess, MD, is an associate professor of neurology at the University of Florida College of Medicine. He serves as the director of the Veterans Administration Parkinson’s Disease Consortium Center at the North Florida/South Georgia VA Medical Center. Dr. Hess received his medical degree from the Albert Einstein College of Medicine and completed his neurology residency, serving as chief resident, at Columbia University Medical Center. He also completed subspecialty fellowship training in movement disorders at Columbia under Dr. Stanley Fahn, with additional training in neurophysiology and intraoperative mapping for deep brain stimulation. His research interests include the study of wearable devices in movement disorders and the cortical oscillations associated with voluntary movements in dystonia. Dr. Hess has published extensively on topics such as movement disorders, neurophysiology, tremor analysis, neuroimaging, brain stimulation techniques in Parkinson’s disease, and substance abuse in movement disorders. He is a member of the International Parkinson and Movement Disorders Society and the American Academy of Neurology, and is board-certified by the American Board of Neurology and Psychiatry.
Research topics
- Computer Science
- Neuroscience
- Psychology
- Medicine
- Physical medicine and rehabilitation
- Human–computer interaction
- Engineering
- Engineering ethics
Selected publications
Parkinsonism & Related Disorders · 2026-01-29 · 2 citations
articleSenior authorResearch Square · 2026-01-08 · 1 citations
preprintOpen accessSenior authorMovement Disorders Clinical Practice · 2026-02-16 · 1 citations
articleSenior authorCorrespondingBACKGROUND: Urinary tract infections (UTIs) are common complications among hospitalized patients with Parkinson's disease (PD) and are associated with delirium and prolonged hospitalization. OBJECTIVES: To determine the prevalence of UTI, identify modifiable risk factors, and evaluate associated outcomes among hospitalized patients with PD. METHODS: We conducted a retrospective cohort study using the PINC-AI Healthcare Database including PD-related hospitalizations from 2019 to 2023. UTIs diagnosed on admission or during hospitalization were identified, and multivariable analyses were performed. RESULTS: Among more than 321,000 PD hospitalizations, 18.9% were associated with UTI. Emergent admission, inter-facility transfer, dementia, and indwelling urinary catheter use were independently associated with UTI, whereas male sex was protective. UTI was associated with prolonged length of stay and delirium. CONCLUSIONS: UTIs are frequent among hospitalized patients with PD and are associated with several modifiable risk factors. These findings may inform PD-specific inpatient strategies for UTI prevention and risk stratification.
npj Parkinson s Disease · 2026-03-28
articleOpen accessSenior authorRisk stratification during hospitalization may support real-world discharge planning. We developed and validated machine learning models and an interpretable risk score to predict discharge destination among patients hospitalized with Parkinson's disease using a nationwide administrative claims database. Adults aged ≥50 years hospitalized between November 2017 and June 2023 were included, and the first hospitalization was defined as the index admission. Discharge destination was categorized as home, facility, or in-hospital death. The dataset was randomly divided into training (80%) and testing (20%) cohorts. Random forest models were constructed for all discharge outcomes, and an elastic net logistic regression model was developed for facility discharge. Among 281,664 index admissions, 48.0% were discharged home, 44.8% to a facility, and 7.2% died in hospital. The random forest models achieved AUCs of 0.775 for home discharge, 0.774 for facility discharge, and 0.832 for mortality. The elastic net model demonstrated an AUC of 0.752. A seven-item risk score identified a high-risk group with a 73.8% facility discharge rate compared with 40.6% in the low-risk group. These models provide clinically interpretable risk stratification to support multidisciplinary discharge planning.
Neurology · 2025-04-07
articleTo assess the impact of deep brain stimulation (DBS) target and Parkinson’s disease (PD) motor subtype on the total levodopa equivalent daily dose (LEDD) following surgery.
Movement Disorders Clinical Practice · 2025-03-10 · 5 citations
articleOpen accessBACKGROUND: Social workers (SW) are part of multidisciplinary teams for many surgical disciplines. Their role in deep brain stimulation (DBS) presurgical evaluations has not been defined. OBJECTIVES: The goal was to characterize the role of SWs in a multidisciplinary DBS presurgical evaluation team and to construct a screening tool to identify patients who could benefit from a preoperative SW consultation. METHODS: A retrospective chart review was conducted on 100 consecutive patients. RESULTS: Ninety-seven subjects met with the SW. The median age was 68 years; 52% were female. Eight roles for the DBS SW were identified. The SW recommended follow-up for two subjects, and four additional subjects contacted the SW subsequently. CONCLUSIONS: This study revealed how SWs could be integrated into DBS presurgical evaluations. Because most patients do not have specific SW needs, the mnemonic DBS-FACTS (finances, advance care planning, caregivers, transportation, and suicide risk) may identify patients who could benefit from SW consultation.
Energy Consumption of MRI Systems: An Evaluation of the Relative Contribution of Chillers
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition · 2025-09-16
articleMotivation: We sought to understand the relative contribution of cooling systems on the overall energy use of MRI systems. Goal(s): To identify the potential for energy savings. Approach: Power meters were installed on three MRI (0.55T, 1.5, 3T) and their supporting chillers to independently assess energy consumption of each component. Power draw and energy consumption were evaluated during periods where MRI were idle and actively scanning. Results: Overall, the chillers were found to consume at least a third of the overall energy being expended, including substantial energy consumption during non-productive periods. Impact: Energy consumption by MRI systems is an important contributor to the carbon footprint of health care. A clear understanding of the relative contribution that system cooling plays will help develop impactful ways to improve MRI energy efficiency.
SSRN Electronic Journal · 2025-01-01
preprintOpen accessSenior authorSSRN Electronic Journal · 2025-01-01
preprintOpen accessSenior authorMovement Disorders Clinical Practice · 2025-07-11
letterData sharing not applicable to this article as no datasets were generated or analysed during the current study.
Recent grants
Towards Baby Brain Connectome: a Study of Newborn Brain Networks
NIH · $3.0M · 2013–2019
Frequent coauthors
- 256 shared
Nelson M. Oyesiku
- 256 shared
Zachary Litvack
Neuroscience Institute
- 256 shared
Chirag G. Patil
Cedars-Sinai Medical Center
- 256 shared
Bob S. Carter
- 256 shared
Luis M. Tumialán
Barrow Neurological Institute
- 256 shared
Maria Fleseriu
Oregon Health & Science University
- 256 shared
Gabriel Zada
- 256 shared
James Y. Chen
Labs
Education
M.D.
Albert Einstein College of Medicine
Other, Neurology
Columbia University Medical Center
Other, Movement Disorders
Columbia University Medical Center
Awards & honors
- The Jill F. And Richard W. Cope Professorship
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