Where healthcare meets data science.
ASHDS is the professional home for the clinicians, analysts, and informaticists who use data to improve care. We help members earn recognized credentials, publish and read leading research, and build the connections that move a career forward.
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Three ways ASHDS supports your career
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ASHDS26 Annual Symposium
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From the Journal
Thought leadership from the Journal of Health Data Science
Each month we open one feature article to everyone. The rest of the issue is available to members.
Predictive Drift After Deployment: A Two-Year Audit of 31 Clinical Risk Models Across a Multi-Site Health System
Dr. Aisha Diallo (Riverstone Children's Hospital), Dr. Kwame Asante (Meridian Health System), Yuki Tanaka, MPH (Brookline Medical Center), Dr. Olufemi Bankole (Trent Valley University)
Clinical risk models are often validated once and then trusted indefinitely, but their accuracy can quietly erode as patient populations and care patterns change. We tracked 31 deployed models across eight hospitals for two years and found that nearly half lost meaningful accuracy within 18 months, often without anyone noticing. We describe a practical monitoring approach that flagged most of these failures early and required no specialized tooling to run.
Inside this issue
Volume 5, Number 3 · June 2026
Special interest groups
Find your community
Peer groups where members trade methods, failures, and standards in the open.
Predictive Risk Modeling
Builds, validates, and maintains clinical risk models, with a standing emphasis on what happens after deployment. Members share validation practices, monitoring approaches, and hard-won failures in a quarterly case review.
1,140 members
Health Equity Analytics
Examines how data and algorithms can either narrow or widen health disparities, and develops practical methods for measuring fairness in real systems. It runs a working library of equity audit techniques that members apply in their own organizations.
890 members
LLMs and Generative AI in Care
Tracks the fast-moving use of large language models in clinical settings and works to separate genuine capability from vendor claims. Members co-author practical evaluation checklists and meet monthly to review new tools and evidence.
1,470 members
Clinical NLP
Advances the extraction of meaning from clinical text, from discharge summaries to nursing notes, and advocates for shared annotation standards. It maintains a list of open datasets and benchmarks to lower the barrier for newcomers.
760 members
Data Governance and Privacy
Addresses the policy, ownership, and privacy questions that determine whether data work is trustworthy. Members trade governance templates and discuss real cases where access, consent, and accountability collided.
640 members
MLOps for Health Systems
Covers the engineering discipline of running models in production, including monitoring, retraining, and the handoffs between data scientists and operations. It is the most hands-on of the groups, with shared code patterns and architecture reviews.
820 members
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