For the last two years the United Kingdom’s Economic and Social Research Council (ESRC) has held a writing competition to encourage and recognize the writing skills of ESRC-funded students. Winners for the 2016 round were honored March 21 at a ceremony in London. Social Science Space will publish the winning essays, runners-up and eight shortlisted pieces in the next few weeks; here we present the shortlisted essay, “Deep Data Means Better Patient Care,” from Alison Harper of the University of Exeter.
For more on the competition, click here.
Deep Data Means Better Patient Care
By Alison Harper
Is the NHS paying the price as managers are forced to firefight bureaucratic red tape, rising demand and ever-shifting policy? After ten years of micromanaging productivity, healthcare austerity, frozen salaries, redundancies, cutting services and privatising swathes of the NHS, hospitals have been left struggling to hit performance targets, alongside deflated staff and distressed, undervalued patients.
High impact services such as emergency care have had their edges tinkered, but what of those that plod along in the background, under the same pressure to perform against budgetary and delivery constraints? Gastrointestinal endoscopy, the case study for my research, is one such service: a largely diagnostic set of procedures that inspect the lining of the bowel or stomach for cancer or other conditions.
Headlines such as ‘More patients waiting longer than 6 weeks to have a tube inserted into their colon’ don’t have the colourful impact of ‘Lives at risk due to emergency department closures.’ But the truth is, if performed in time, this procedure saves lives. Bowel cancer is the third most common cancer in both men and women and demand for endoscopy is increasing year on year. How do we plan for future demand on this vital procedure?
Capacity planning tools that support organisational decision-making, such as computer simulation, can help to understand future capacity requirements due to expected changes in demand. Can we predict future demand? The answer lies in data. A methodology that uses both demand modelling and capacity planning allows patterns of future demand on the service to be explored, and assesses the consequences of this on service delivery. Data generated by hospitals and other sources opens up huge opportunities.
Many organisations are already using data analytics to benefit society, from disaster management, to education, to the management of natural resources. Healthcare has been slower to catch on. Using data to model future developments inverts the usual form of finding and testing a hypothesis to create a solution. Instead of building knowledge at an individual level, and basing decisions on small amounts of data, we can look at large and varied datasets to comprehend patterns on a more universal level. By pooling the experience of millions of doctors and patients, the most effective treatments and most unexpected side effects can be identified. Likewise, operational decision-making, inherently political and loaded, can be supported by data. This will never replace human agency: the key to the application of data-based technical skills will always be creativity, imagination and intellectual risk-taking, especially in healthcare, where people are both the subject and object of decision-making.
What of endoscopy, which turns out to be an exemplar case study in modelling future demand which is influenced by demographic change? As a service most used by older people – the cancers it investigates are primarily diseases of the elderly – it will be heavily impacted by the effects of our rapidly ageing population.
My research modelled demand for endoscopy using official population projections and historical hospital demand data in a retirement-hotspot, South Devon. It showed that in this region, isolating the effects of population growth and ageing predicts a significantly higher demand for endoscopy services over the next ten years than the population of the same region is projected to rise.
For capacity planning, this figure was adjusted by future known policy changes designed to improve population-level health – namely public awareness campaigns and a change to hospital performance metrics – to create an adjusted demand scenario predicting up to a 60% increase in demand over the next ten years.
A simulation model then used these future demand predictions within a computerised representation of the system, to assess the consequences of changing demand on the service. Capacity initiatives such as seven-day working or restructuring the service can be explored within the simulation model, to discover the best approaches to meet the expected changes in demand over the next decade.
This methodology isn’t a ‘black box’ technique, obviating public interests and reducing distressed and worried patients to little more than entities in a process. In capturing the effects of demographic change and policy on future demand for an essential service, the data and its applications support patient needs, and allows transparent planning and creativity: intrinsically human characteristics that cannot be reduced to crunching numbers alone. While relying on data, this methodology doesn’t forget those who stand behind the numbers: the patients who need to know one way or the other which direction this crossroad in their lives will take them.
“Once more, with feeling: life as bilingual” |Wilhelmiina Toivo, University of Glasgow
“Living and looking for lavatories” | Lauren White, University of Sheffield
“Marginal money, mainstream economy”| Max Gallien, London School of Economics and Political Science
“Biotechnology and the world of tomorrow” | Elo Luik, University of Oxford
“Better healthcare with deep data” | Alison Harper, University of Exeter
“Child labour: making childhood work” |Sophie Hedges, London School of Hygiene and Tropical Medicine
“What future while living in uncertainty?” | Vanessa Hughes, Goldsmiths, University of London
“Ensuring a sweeter future” | Siobhan Maderson, Aberystwyth University
“Understanding the forgotten decade” | David Pollard, University of Birmingham
“Schools, funding and donor power” | Ruth Puttick, Newcastle University
“Fostering inclusion in the face of division” | Caoimhe Ryan, University of St Andrews
“Listen to the local” | Ruben Schneider, University of Aberdeen