It is impossible to run a Commissioning Group without accurate and timely data. This article reveals the incompetence of the Health Services. GPs have had accurate data since the 1990s.
9th Feb 2017: “Another NHS crisis looms – an inability to analyse data” in The Guardian. (Beth Simone Novek)
Public institutions such as the National Health Service increasingly want—and are expected—to base their actions on nationally agreed standards, rather than anecdote. The collection and analysis of data, when done responsibly and in a trusted manner, has the potential to improve treatment and improve the social and economic value of healthcare.
However, the goal of using data to improve the NHS and social care is hampered by a talent gap – a lack of personnel with data analytical skills – that stands in the way of uncovering the rich insights that reside in the NHS’ own data. The NHS is not unique among institutions that are struggling to identify, hire and retain people with data science skills and the ability to apply these.
Take two examples. The Healthcare Quality Improvement Partnership (HQIP) conducts forty annual audits comparing hospital and physician outcomes, and the implementation of National Institute of Clinical Excellence standards across England and Wales. But, as HQIP Director Dr. Danny Keenan admits, although they have the expertise to do the analysis, “we are woefully inadequate at translating such analysis into improvements. What’s the takeaway for the hospital or community provider Board or the medical director? They cannot understand what they have to do.”
Dr. Geraldine Strathdee chairs the National Mental Health Intelligence Network, based at Public Health England. Together with partners, this launched the Fingertips Mental Health data dashboard of common mental health conditions in every locality. Strathdee points out there is a tremendous need for such benchmarking data: to design services based on local need, build community assets, and improve NHS services.
Without it, NHS resourcing is just based on historical allocations, guesswork or the “loudest voice”. An example is psychosis: “you can spend sixty percent of your budget on poorly treated psychosis with people ending up in hospital beds, homeless or in prison, and less than ten per cent ever get employment,” says Strathdee. The data dictates investment in early intervention psychosis teams, which dramatically improves outcomes. Fifty per cent of patients get back to education, training or employment. However, there is a shortage of people able to draw these insights. “We have a major capability level problem everywhere,” says Strathdee.
Over the past twenty years, the NHS has amassed increasing amounts of data. There is an almost universal consensus that, when used ethically and responsibly, with respect for the confidentiality of all patients (especially of vulnerable populations such as immigrants), better use of data could bring about more high quality, accessible and effective services. But this requires more than just technology. The NHS needs data analytical talent, which comes from a variety of disciplines.
This includes the ability to ask the questions and identify patterns in both structured and unstructured records. For example, Leeds Teaching Hospitals analyse approximately one million unstructured case files per month. They have identified thirty distinct areas for improvement by using natural language processing to identify wasteful procedures such as unnecessary diagnostic tests and treatments.
Data analysis also requires people who know how to apply diverse statistical methods to determine future outcomes. EPSRC has funded five research centres around the UK that will apply mathematics and statistics to prediction models in order to help clinicians tackle health challenges such as cancer, heart disease and antimicrobial resistance.
Improving public institutions with data also requires strong communications, design and visualisation skills. Digital designers are needed who know how to turn raw data into dashboards and other feedback mechanisms, to support managers’ decisions. And none of this is possible without the legal and ethical training that allows for the development of policies, platforms and procedures that enable data to be shared and algorithms to be used responsibly and effectively.
So the NHS needs to be able to tap into a wide range of data analytic know-how, from computer scientists, statisticians, economists, ethicists and social scientists. It is impractical and expensive to meet all of these needs through more hiring. But there are other ways that the NHS can match its demand for data expertise to the supply of knowledgeable talent both within and outside the organization.
For example, to make better use of sensitive administrative data to measure what works, the NHS should expand efforts already underway to construct an NHS Data Lab, modelled on the Ministry of Justice’s Data Lab. The MoJ’s Data Lab is a secure facility that accepts requests from anyone wishing to test the effectiveness of a program by using the government’s administrative data. It has conducted over 173 analyses over the past three years.
The NHS should also create a variety of online knowledge networks for those inside and outside the NHS, especially in universities, who possess the skills and willingness to help with data analytical questions. For example, last week the Rockefeller Foundation launched the Zilient platform to connect resilience practitioners, and the GovLab and Justice Management Institute launched DataJustice. Both are designed to connect networks of professionals for mutual learning.
NHS Improvement and the Health Foundation created an online network for improvement practitioners called the Q Network. Now NHS England is taking steps to create a Population Health Analytics Network, bringing academics, commercial and charitable organizations together to accelerate learning. But it can do more and expand the agility and scale of such groups, using new technology.
Such networking platforms help to catalogue relevant skills and make them more searchable. For example, the World Bank’s SkillFinder tracks expertise across three dimensions: technical expertise, geography, and business processes. In New York City, the Mayor’s Office Volunteer Language Bank tracks only a single skill—translation—to match the supply of multilingual civil servants to the demand for translation services.
Whether the NHS wants to know how to spot the most high-risk patients or where to allocate beds during a particularly cold winter, it can use online networks to find the talent hiding in plain sight, inside and outside the health and social care system. Regardless of the platform the NHS adopts, it needs to convene the different bodies already undertaking data analytical work, to compare research agendas, share learning, and identify gaps in its needs for data science skills.
Beth Simone Noveck is the Florence Rogatz Visiting Clinical Professor of Law at the Yale Law School and the Jerry M. Hultin Global Network Professor of Engineering at New York University, where she directs the Governance Lab. With support from NHS England, the GovLab published a report this week on “Smarter Health: Boosting Analytical Capacity at NHS England” which is available here.