Tech-enhanced Academic Writing

Coronavirus has completely changed how we work across most professions including in academic research. While those impromptu conversations around the coffee machine at work, or over drinks at academic conferences seem both a distant memory and a far-flung future dream, there have been some wins for collaborative working as well. Lockdown has brought both technological improvements and culture-change around the use of video conferencing and collaboration tools. A colleague – Dr. Stuart Stewart based at the University of Manchester and I (based at the University of Bristol) have been “meeting” once a week to discuss the creation of a concept paper covering ideas that have been percolating for years after a fortuitous meeting at a conference in 2018. Both of us are tech-adept and we often discuss ways that we can use software (and other technology) to enhance our work.


Google Meet is now our default platform to meet over – I run a “G-Suite” account which allows me to have my own domain name but use all of Google’s software such as Mail, Calendar and Drive seamlessly; I can book a meeting directly into my online calendar and add a Meet link with a single click. Most work events use Zoom and Microsoft Teams but we’ve found that Google Meet tends to be faster and more reliable than Teams and doesn’t have the 40 minute restriction that (free) Zoom has.

When we’re talking, we still use WhatsApp to send each other links or screenshots – we’ve been chatting on WhatsApp since we met and the “WhatsApp Web” platform adds additional capability to quickly share written information from your laptop to someone else’s; it’s also preserved for posterity when we need the link again.


Our discussions not only cover what we want to learn and express but also how we try to organise our thoughts between these. It’s not fresh news to point out that our brains are both incredibly powerful at making fresh connections between source material and also terrible at compiling and remembering those sources in a systematic way. How do I effectively record all the ideas I’ve had when reading that paper ready for when I want to collate and express them later?

Stuart recommended the new platform ‘Roam‘ as a possible solution to this problem. Looking at their work and what they are trying to achieve gives me a feeling that they are genuinely creating something great that’s just on the periphery of my consciousness and it’s possibly more to do with my inability to relax and flow into this different way of working than anything to do with their solution. I tried it for a few days and still didn’t quite “get it” but that doesn’t mean I’m not excited to see where they go in the future and hope they survive these challenging economic times.

For the moment, I have taken some of the concepts around daily journaling and hyperlinking back to the software platform that I have been using for nearly 10 years now – Evernote. I found this tool during my medical degree and now have over 4000 “notes” stored there; I have everything from scans of my kids’ artwork to a hyperlinked digital portfolio/CV. I have all of my study notes that get updated and re-used regularly in my clinical work, and I keep my productivity high by using the “Getting Things Done (GTD)” method through it. It can be frustratingly buggy is some basic areas *cough*tables*cough* but its cross-platform apps and widgets and the reassurance that I have never lost a single note allows me to dump anything into it and know it’s safe.

Despite Stuart being a more avid user of Roam (maybe his brain is just bigger and fresher!), he is also a fan of Notion. This has a similar offering to Evernote and I tried it for a short while and felt that it was better looking and potentially more powerful but unfortunately, their import from Evernote is not yet fully working and their Android offering isn’t as comprehensive so I’m sticking with Evernote now; I’m not sure if I would switch in the future but we shall see.


Stuart and I’s remote paper-writing collaboration to create a paper started with Microsoft Word with us sending the document to each other to review. Word is universal and it has the advantage of a good plug-in for Mendeley – the best citation manager I’ve used. I’ve tried a lot of them but again, despite being a little rough around the edges, it does the best all round job of storing and searching within PDF copies of papers, allowing me to highlight and make notes on those papers, and then quickly cite them in a document.

We have now moved on from Word to far more real-time collaborative writing where we can work online on the same paper at exactly the same time. First, we tried Overleaf which I imagine could be the “go to” tool for collaborative writing if you’re working with LaTeX. I keep thinking I should learn this ‘language’ but haven’t found the initial steep learning curve has been worth it yet. Instead, we fairly quickly switched to Authorea which combines a solid online paper-writing collaboration tool with the interesting concept of being able to freely publish a paper on their platform getting that all important DOI number without the lengthy process found in more traditional peer-reviewed journals. Our plan is still to see if a more mainstream publication will take our paper but it provides a fascinating alternative to getting your ideas out into the world compared to the peer-reviewed journal route.


Finally, in this far more online academic world, it’s important to have more than just a journal paper to express your ideas and connect with people, you need an online presence. I use Dreamhost to host my many websites and during one of our meetings, I bought a couple of domain names on Stuart’s behalf. In the space of a few minutes, he was able to transfer the money back to me using “Settle Up” through my app-based account with Starling Bank which instantly showed the money had arrived with a simple notification. Transferring money instantly and securely this way was a new experience for both of us and as someone old enough to remember my first building society account book where my changing balance was typed onto the next line each time I deposited some pocket money, it really brought home how integral technology is to how we run our world, whether it is in academic research or anything else.

Technology for Connection and Conservation

I was part of the organising team for the recent National GP ACF Conference (2020) in Bristol. I took on the role of finding, purchasing, configuring, deploying, and supporting a software package to use at the conference. There are a lot of potential tools on the market, ranging in price from free to many £thousands. I settled in the end on a tool by a company called “Whova”.

Our core goal initially was to remove the need for a paper programme (in keeping with the overall aim to make the conference more environmentally sustainable). It quickly became apparent that there were many other potential benefits in using a digital tool at the conference including: live polls and announcements, uploading and storage of posters and talk slides, and opportunities for attendees to communicate with each other

The live polls (shown on the big screen) added a sense of drama to the debate in a way that trying to count hands wouldn’t have done. The rating tool was also used heavily by attendees to score the speaker presentations which allowed the committee to choose the prize-winning talks easily and hopefully with less bias. Announcements enabled us to immediately update attendees of room and time changes and got lost property back to its owners. I was also pleasantly surprised at how often the app was used by attendees to communicate with each other and how even the less technically aware were able to use it fairly easily.

After the event, I received a downloadable report which, among a lot of statistical facts, showed that 80% of people who were registered as attendees at the event downloaded the app. This number, while reassuringly high, also highlights a few issues; firstly, the tickets weren’t purchased through the app and the translation between the ticket software and the app, while fairly seamless, resulted in a few ‘ghost’ attendees and a few people being missed off. Secondly, while the app was fairly intuitive, there will still be a proportion of people who will be disadvantaged by their dislike, disdain or fear of “tech”. Our robust debate on AI in medicine also highlighted this:

When is the right time to embrace (tech) solutions that work well for the vast majority of people but exclude a small minority – especially when that minority might have the greatest need?

Health Data Science – the next key development in patient-centred research will be data-led

The breadth of conditions doctors are expected to manage continues to grow as people and society become ever more complex and it is in GP surgeries up and down the country where this is most starkly seen. The volume of work expected of GPs is taking its toll on individual doctors and the service as a whole.

My previous career designing and developing information technology (IT) systems gives me insight into the huge potential computers and machine learning have to help us in this increasingly challenging environment. Artificial Intelligence (AI) can enable us to provide the best evidence-based medicine to our patients while also freeing us from mundane administration to spend more time connecting with the human beings in front of us.

In the UK, Primary Care is already leading the way when it comes to the use of IT in our daily work. New business start-ups such as Babylon Health show how much further the boundaries can be pushed, with their attempts to employ AI technology in diagnosis and management. Matt Hancock, the current health secretary, is keen for technology to be used in the NHS to ease the pressures on an increasingly under-resourced system.

For technology to truly assist with, and perhaps even replace, some clinicians’ work on the frontline, we must understand what information the system is being given and how it is being processed. This is the role of health data science. Health data science combines maths, statistics and technology to help us to better understand diseases and conditions and can provide new ways of treating them or spotting them earlier.

As a GP Academic Clinical Fellow with one of the National Institute for Health Research (NIHR) themed posts related to health data science, I was invited to London to the launch of a new research collaboration between NIHR and Health Data Research UK (HDR UK). The aim of the day was to promote not only a relationship between the two research entities but between the clinicians, data scientists, and statisticians who have different skill sets to bring to the complex puzzle of managing patient data. Exciting research projects were discussed and speakers from across the country presented their work and their goals to an engaged audience.

Professor Colin McCowan, Professor of Health Data Science at St. Andrews University, discussed the HDR UK National Multimorbidity Platform, which is grappling with the issue of linking disparate datasets across multiple areas of health data. Not only is accessing and extracting the data complex, but overlapping datasets need to be harmonised and standardised. Governance of these datasets also needs to be thought through carefully given their scope and the sensitivity of the data.

Dr Rashmi Patel, an HDR UK fellow, showcased his work using Natural Language Processing (NLP) to ‘read’ complex and extensive clerking notes of psychiatric patients, teasing out the mesh of symptoms they describe and how these do (or in some cases perhaps do not) overlap with the patient’s formal diagnosis. His project demonstrated the complexity of extracting and analysing ‘fuzzy’ data from even more complex real people.

Professor Simon Ball, Executive Medical Director for University Hospitals Birmingham, discussed with me the Trust’s recent decision to trial an implementation of Babylon Health AI technology to run a pre-hospital triage service. The software has already proved controversial with doctors over concerns about how it seems to mis-diagnose life-threatening symptoms. However, Professor Ball wondered if perhaps bold and innovative choices such as these are the only option available when services are already stretched to their limits.

Health data science is an exciting area of research that can only work as a collaborative effort, as no individual has all the skills needed to deliver meaningful research on their own. There are also benefits and risks associated with private enterprise taking the lead. Researchers and frontline clinicians will have to find an appropriate balance between the commercial attitude towards innovation of ‘Move Fast, Break Things’ and the more traditional academic attitude of careful, sometimes years-long, thorough peer-review and publication process.

Whatever the future holds, it’s clear that this research area is only just getting started and is here to stay.

The Gender Data Gap

I have just finished reading an exceptional (and 2019 Royal Society Insight Investment Science Book Prize shortlisted) book called “Invisible Women” by Caroline Criado Perez.

It covers the gender data gap in all areas of life (and research) where men are assumed to be the ‘default human’ and women are considered to often be ‘atypical men’. It turns women into a less visible ‘minority’ and impacts all areas of life including city infrastructure planning, workplace and product design and, most relevantly healthcare. For example, she notes that there is far less research into, for example, painful periods which can affect 90% of women, than there is into male impotence. This is particularly ironic given one specific example where a small 2013 study found that sildenafil citrate gave participants four hours of pain relief from menstrual cramps without side effects but when the lead researcher applied for additional funding to do a larger clinical trial, his grants were rejected as they questioned whether painful periods were a “priority public health issue”.

As both a woman and a researcher (with an interest in using big data to look at health problems), this book had a bit impact on me both personally and professionally. At times, it made me angry and frustrated; it has definitely made me more passionate about trying to remove bias from datasets, especially if we ever hope to use them to deliver safe and effective patient care.