Interventional Nephrology · Data Development

Dr. Julio L. Chevarría

Clinical Lead Interventional Nephrologist at MRHT & TUH, Ireland — building clinical tools, dashboards, and AI-assisted systems where medicine meets data.

Based
Ireland
Experience
10+ years
Stack
Python · R · Shiny

About

Clinician.
Data developer.

I am a Consultant Interventional Nephrologist and Clinical Lead at MRHT and Tallaght University Hospital, Ireland — with a decade of complex renal practice.

My clinical work spans tunnelled catheters, Permcaths, Vascaths, native and transplant biopsies, and point-of-care ultrasound. Alongside it I build data pipelines, dashboards, and AI-assisted tools in Python, R, Shiny, and Streamlit — turning messy health records into decisions.

Originally from Cusco, Peru, I also develop educational technology for schools back home — connecting clinical rigour with community impact.

10+
Years in Ireland
MRHT · TUH
Clinical Lead
Py · R
Shiny · Streamlit

Work

Selected projects

Clinical Apps & Tools

01

ISBAR App

Clinical handover errors are a leading cause of adverse events. ISBAR structures critical communication between clinicians.

RoleDesigned a training module plus a conversational AI consult service for structured renal/acute handovers.

OutcomeStandardised handover language across the team; AI consult triage available on demand.

  • Oracle DB
  • Python
  • Conversational AI
Open
02

Renal Review App

Keeping a nephrology department current with the literature is time-consuming and inconsistent.

RoleBuilt a literature-review tool with an ANKI card generator and interactive polls for grand rounds.

OutcomeFaster journal-club prep; spaced-repetition decks generated automatically from reviewed papers.

  • Python
  • Streamlit
  • Supabase
Enquire

Data Science & Dashboards

03

Dialysis KPI Dashboard

Dialysis unit quality depends on tracking adequacy, access infections, and hospitalisation trends in real time.

RoleBuilt an interactive R/Shiny dashboard pulling unit data into live KPI views.

OutcomeSingle source of truth for unit performance; supports audit and MDT review.

  • R
  • Shiny
  • SQL
  • Plotly
Enquire
04

IgA GMN Database

IgA glomerulonephritis patients eligible for novel trials are hard to identify from unstructured records.

RoleDesigned a structured clinical database tracking disease course, treatment response, and trial eligibility.

OutcomeRapid identification of trial-eligible patients; longitudinal phenotyping for QI.

  • Python
  • Streamlit
  • Supabase
Enquire
05

Consult Service Database

Nephrology consults arrive ad hoc, making it hard to audit demand, response times, and outcomes.

RoleBuilt a consult-tracking system logging referrals, clinical questions, and resolution.

OutcomeQuantified consult workload and turnaround; data feeds service-improvement cases.

  • R
  • Shiny
  • Supabase
Enquire

Educational Technology · Perú

06

Colegio Pardo y Lavalle

Un colegio en Cusco gestionaba asistencia y pagos con hojas de cálculo dispersas y propensas a error.

RoleDesarrollé un sistema de control de asistencia y pagos con dashboards en tiempo real para directivos y apoderados.

OutcomeRegistro centralizado; reportes automáticos reemplazan el trabajo manual.

  • Python
  • Streamlit
  • Supabase
Consultar
07

Academia Pardo y Lavalle

La academia preuniversitaria necesitaba seguimiento confiable de notas y asistencia para estudiantes y apoderados.

RoleConstruí apps de seguimiento de notas y asistencia con reportes automáticos para docentes y familias.

OutcomeComunicación clara del progreso académico; menos carga administrativa para los docentes.

  • R
  • Shiny
  • Supabase
Consultar

Education

Courses & workshops

POCUS Course

Point-of-Care Ultrasound for clinical teams — renal, vascular access, and acute applications with hands-on probe technique.

Vascular Access Workshop

Simulation-based training in vascular access insertion and maintenance: tunnelled catheters, Permcaths, and AV fistula care.


Research & QI

Quality improvement

  1. 01

    QI in IgA Glomerulonephritis

    Identifying patients eligible for novel clinical trials via structured EHR phenotyping.

    Active
  2. 02

    AI-assisted EHR Data Quality (eMed)

    LLM-assisted structured extraction to improve documentation completeness and coding accuracy.

    Active
  3. 03

    Diabetes in Haemodialysis Care

    Optimising glycaemic protocols and HbA1c monitoring in dialysis-dependent patients (MRHT).

    MRHT
  4. 04

    Dialysis KPIs & Vascular Access Infections

    Longitudinal surveillance and benchmarking of unit performance indicators.

    Ongoing

Contact

Let's build something
precise.

Open to collaboration in clinical informatics, nephrology research, and educational technology.

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Or email directly jl.chevarria@gmail.com