Population Health Management (PHM) programmes are data driven endeavours. This has caused many involved to conclude that the solution to the challenge is more Business Intelligence (BI). More data visualisations. Perhaps inevitably this has led to a data dashboards arms race; this in the mistaken belief that the delivery of ‘self-service’ Business Intelligence – frequently interpreted as dashboards – are the route to some sort of PHM nirvana.
Spoiler alert – they aren’t.
In this world the Population Health Management challenge is defined in terms of technology; an opportunity to flex a bit of front-end development muscle in a bid to showcase the latest and greatest in dashboarding software [insert usual suspects here]
A whole industry has built up around these dashboarding activities.
Good business if you can get it but caveat emptor. This way lies madness and here is why.
- The illusion of Clarity
Dashboards offer the promise of clarity and yet it is all too easy to confuse an aesthetically pleasing data visualisation with genuine comprehension.
- Analysis Paralysis
As dashboards become ever more intricate, complex and bountiful there is a real risk that data consumers become paralysed by the weight and complexity of analysis presented. This is deeply unfortunate because data analysis is worthless if it does need engender action on the part of the end user.
- Selective Perception
Dashboards, despite their proclaimed objectivity can inadvertently encourage selective perception. When we design or interact with dashboards, we make choices about which data to include and how to present it. These choices can be influenced by our biases, consciously or unconsciously. As such there is a risk that dashboard designers/creators unintentionally focus on data that conforms to preconceived notions of what is important and what is not.
- Metrics over Meaning
In the pursuit of quantifiable results, there is a risk that we prioritise metrics over the deeper meaning behind the numbers. Dashboards glory in the provisioning of quantitative data, but then often fall short in the capture of qualitative nuances that can shape a situation. This is particularly true in the case of Population Health Management where behind every piece of data ‘sits’ flesh and blood human beings.
- Neglecting the Human
The journey through dashboards can be a bewildering and isolating one. They can be soulless and antiseptic. They stare back at us with a metaphorical quizzical eye as though the answer is staring us in the face. It rarely is. They lack the human dimension.
Dashboards typically offer predefined views and visualisations and as such limit the users ability to look beyond the data presented. To illustrate; in my experience of working with the primary care workforce – the doers of Population Health Management as opposed to the talkers and strategists – that workforce will frequently have specific questions or hypothesis that they want to test and re-test. They desire to test these hypotheses with other humans whose skills, judgement and knowledge they trust. Dashboards rarely accommodate the needs of the genuinely inquisitive.
It is true that some dashboards offer interactive features, yet few offer the level of interaction that rigorous data investigation entails. These interactions are inevitably human interactions and not ‘point and click’ ones.
Dashboard advocates will claim that user friendliness is ‘baked in’. There is an underlying assumption that end users have similar levels of data literacy and analytical skills. This is rarely the case. People delivering Population Health Management – as opposed to talking about it – require clarity and insight. This requires skilled data interpretation. The dashboard and the data contained therein rarely speaks for itself.
Dashboards are frequently designed based on anticipated user questions and needs. Real world user questions are often unforeseen. Dashboards built on anticipated need rarely survive combat with reality. Dashboards by their very nature are the creation of months of careful planning (it’s an industry remember), but as Mike Tyson once said …”everyone has a plan, until they get punched in the face”.
Healthcare is complex and there is always the need to look beyond visualisations to examine nuances and complexities that are not always self-evident in a chart, graph or table of data.
And because healthcare is complex, most Population Health Management investigations require advanced statistical or machine learning (ML) techniques that go beyond what dashboards can offer.
Context is everything. Dashboards often present data in isolation without providing the broader context or narrative behind the numbers. This can lead to misinterpretation and misunderstanding. As such they can be genuinely dangerous particularly when this misinterpretation impacts on real people’s lives.
There is little doubt that data visualisation as an aid to Population Health Management storytelling has its place; but that place should be centred around investigations that are focused around specific and targeted areas of enquiry. The process of discovery is necessarily an iterative and human one.
I posit these views based on many years working at the coalface with Population Health Management practitioners working in primary care.
The reality of the situation ‘on the ground’ is really quite simple.
The M (Management) of Population Health Management is typically done in primary care with the Multi-Disciplinary Team (MDT) to the fore. If the Population Health Management intervention is focused on a non-medicalised model of service delivery – as it should – then that workforce will extend beyond the MDT.
It will surprise no-one to learn that these Teams are under intense pressure currently and the great majority of the primary and community care workforce have neither the time nor inclination to wade through oceans of dashboards, no matter how beautifully crafted.
Primary care gets Population Health Management it really does. The primary care workforce live and work in the communities they serve and instinctively they will have views on the population health priorities of those communities. They understand that evidence-based approaches to service re-design is the right way to go. A great many of the workforce have been trained and work in an evidence-based world.
Thinking about the populations they serve; they will instinctively have hypotheses they wish to test. They will certainly need access to high quality data and skilled data scientists – blessed with storytelling skills – to test these hypotheses. Just don’t expect them to ‘self-serve’ data insights in the manner in which dashboard developers frequently assume they will.
Communicating insights and recommendations to stakeholders requires more than just visualisations. Calls to action are dependent on context, narrative and storytelling.
Population Health Management tooling and data visualisation software are part of the trade, but that is all they are…tools. They are a means of telling a story. It is stories that capture hearts and minds. It is stories that trigger actions. Story telling is an art form, a skill that once mastered has the potential to change lives.
The skilled storyteller connects emotionally with their audience; here there exists a human dimension that can never exist in a smorgasbord of dashboards.
Storytelling matters.
So, whilst Population Health Management is certainly a data driven enterprise and one where specific and purpose-built analytics tooling have their role, beware dashboard suppliers bearing expensive gifts.
All that glitters is not gold.
NCS
