Dr Jessica Butler

Dr Jessica Butler
PhD

Research Fellow

Overview
Dr Jessica Butler
Dr Jessica Butler

Contact Details

Telephone
work +44 (0)1224 437219
Email
Address
The University of Aberdeen Room 1:172 Polwarth Building
Centre for Health Data Science
University of Aberdeen
Aberdeen, AB25 2ZD
Web Links

Twitter
Google Scholar profile


Biography

I came to the University of Aberdeen in 2015 to join the team at the Centre for Health Data Science. Before that I got my PhD and was a postdoc at the University of Massachusetts in bioinformatics. I'm originally from beautiful rural Pennsylvania in the US.

At the Centre I'm part of a great team studying NHS and government records to understand how to improve population health. I'm the Analytic Lead for our collaboration with Health Foundation called the Networked Data Lab. With NHS Grampian, we're analysing the health records of patients who have been told to shield from COVID, so the NHS can adapt their care to protect them from infection.

I'm an advocate of rigorous study design and transparent methods, and for improving research culture so scientists can work to a higher standard. I'm also the Aberdeen lead for the UK Reproducibility Network and run the Open Research Working Group here. We're a big, interdisciplinary group working to improve research methods and culture. All students and staff are very welcome to join - just drop me an email.

Resources

Open Science

A manifesto for reproducible science

The Turing Way - guide to reproducible science

Preregistration templates

Registered Reports

FAIR Guiding Principles for scientific data management

Good enough practices in scientific computing

Blind analysis

Reporting guidelines (see also TOP guidelines summary table)

Requiring journals to publish replication studies

Persistent Identifiers: ORCID for researchers, DOI for data sets and manuscripts

MedrXiv - preprint server for manuscripts

Stats and Errors

Statistical tests, P values, confidence intervals, and power

Statistical Errors in the Medical Literature

Communicating results about significance

Smallest effect size of interest

Common statistical tests are linear models

STRATOS - guidance in the design and analysis of observational studies

Using R

Data Skills for Reproducible Science - Glasgow's phenomenal open data science courses

Stats545 - excellent course on data skills for reproducible science

R for Data Science

Further Reading

Course Syllabi for Open and Reproducible Methods

Reproducibility Bibliography

Peer Support

UK Reproducibility Network (also slides from national meeting)

ReproducibiliTea journal clubs around the world

Twitter has an active and supportive Open Science community - check out the networks around @OSFramework, @UKRN, @OpenSciUtrecht, @ReproducibiliT

Open science is really scary y'all

Research

Research Interests

public health, health inequalities, open science, data provenance, meta-research

Current Research

NHS Networked Data Lab

I am the Analytic Lead for our new collaboration with Health Foundation and four other NHS Centres. This project, called the Networked Data Lab, is a close collaboration of teams working on methods for analysis and presentation of NHS data. Our short-term focus is on developing tools to identify and help people most vulnerable to COVID.

Coronavirus

I'm leading a Chief Scientist's Office project to protect patients with serious existing medical conditions who have been asked by the government to self-isolate to protect their health. We are mapping these patients' pre-COVID care pathways and advising the NHS on how to protect them as they receive care during the pandemic.

I also work with the awesome Dimitra Blana on an NHS R&D project to create a local COVID model. We are working with Graham Osler at NHS Grampian to use real-time infection data to predict hospital occupancy in Grampian.

Robust & Reproducible use of High-Security Patient Data

At the end of 2020, I will start a Wellcome Trust Open Research project to design reproducible and transparent methods for research using patient data. The goal of the project is to automate the capture and reporting of complex data provenance without compromising patient data privacy.

Patient-Centred Care for Fibromyalgia

Pre-pandemic, I was studying the diagnosis and treatment of fibromyalgia as part of the PACFIND project. The goal of this work is to map the complicated health care journeys fibromyalgia patients have to find ways to improve treatment. We are linking 15 years of patients' clinic visits, hospital admissions, and prescribing data to detailed personal surveys. We are also trying to identify undiagnosed fibromyalgia patients from GP records.

Schooling and Health

We collected 20 years of hospital admissions for 5000 Aberdeen Children of the 1950s study members to see if selective schooling effected long-term health. You can see our regression discontinuity analysis paper here.

We did this work in a novel manner called a Registered Report. The paper was accepted for publication based solely on the significance of the question and the quality of the study design, before we saw the data. The paper was the first Registered Report published in BMC Medicine, you can read my article about the experience here.

Collaborations

I work in the Aberdeen Centre for Health Data Science, part of Health Data Research UK.

I have an honorary post with NHS Grampian as a data analyst. We work closely with NHS Grampian across our range of projects.

I'm collaborating with the Health Foundation as analytic lead of our Networked Data Lab.

My work in patient data provenance is a Wellcome Open Research project done with the NHS Grampian Safe Haven.

My research on chronic pain is done as part of the Patient-centred Care of Fibromyalgia (PACFiND) consortium.

My research on the Aberdeen Birth Cohorts is done through the Scottish Centre for Administrative Data Research.

Research Grants

Our Networked Data Lab is funded with a £400,000 grant from the Health Foundation.

My work on COVID-shielded people is funded by a £76,000 grant from the Chief Scientist's Office COVID-19 Rapid Research Programme.

My work with Dimitra Blana on COVID modelling is funded by a £91,000 grant from the NHS Grampian Endowment Fund, a charity funded by NHS Grampian patients & their families.

My work on open science with high-security data is funded by a £50,000 grant from the Wellcome Trust Open Research Fund.

Our research on chronic pain is funded by a £1,200,000 grant from Arthritis Research UK

Our research on the Aberdeen Birth Cohorts was part of a £7,500,000 grant from the ESRC devoted to the analysis of large administrative data sets.

Our public engagement work was supported by the Gordon and Ena Baxter Foundation.

Teaching

Teaching Responsibilities

I'm supervising Krzys Adamczyk's PhD on social mobility and long-term health.

I'm the open science champion at the Centre for Health Data Science and train staff at the university and the NHS in reproducible methods.

Further Info

External Responsibilities

I'm an honorary data analyst with NHS Grampian, currently supporting the COVID response.

I'm a member of the Grampian COVID Surveillance team, a collaboration of NHS Grampian and the three Local Authorities in Grampian. You can see my work analysing vulnerabilities here.

I'm on the editorial board at Scientific Data, an open-access journal that advances the sharing and reuse of scientific data. I'm also on the editorial board of Scientific Reports, supporting their launch of Registered Reports.

I'm the local lead for the UK Reproducibility Network at the University of Aberdeen.

Admin Responsibilities

I run the Aberdeen Open Research Working Group. All students and staff are very welcome to join - just drop me an email.

I'm the Open Science Champion at the Centre for Health Data Science, a partnership with NHS Grampian and NHS Research & Development North Node.

I'm on the University of Aberdeen's Research Culture committee and the Postdoctoral Researcher committee - both dedicated to improving the quaility of research by creating a more supportive culture for researchers.