Data is a hot topic in healthcare. Data availability is high on the agenda of policy-makers and information managers, among others, but ultimately data availability is not the end goal. It is about what data availability can facilitate: data-driven care.
But what does it mean to provide data-driven care? What can it mean for healthcare?
What is data-driven care?
First, a definition. When working data-driven, collected patient data can be used to improve the quality of care and related processes.
Opportunities
If data is available, it can be turned into information.
This can then:
- Offer greater insight into connections;
- Offer greater insight into patient characteristics, lifestyle patterns, ailments and outcomes of care;
- Help with anticipation (a predictive effect);
- Strengthen interdisciplinary collaboration;
- Facilitate the use of AI;
- Provide more information for management to improve operations.
Some examples of practical applications:
- Analysis of patient inflow and outflow with temporary admissions to better anticipate bed occupancy and better manage capacity (see also ‘Data-driven optimisation of the admission process’).
- There is considerable reporting pressure in healthcare - this requires a lot of manual labour and therefore time. By building smart reports based on data flows, you can automate some of this work.
- Making (possibly pseudonymised) data available to regional or perhaps even national or international research groups, so they have more complete datasets to draw conclusions from.
Preconditions for data-driven care
This all sounds pretty sensible, of course, but what does it take to become increasingly data-driven? First of all, data must be actually available and multi-useable to get a grip on data flows. Standardisation of data storage can help with this.
Next, processes need to be set up to analyse and then visualise data after collecting it. Data needs to be translated into information so that meaningful conclusions can be drawn from it. Having data is not a goal in itself, it should lead to action.
Then there is the deployment of AI - another topic that is high on the agenda, but with AI the rule is: crap in, crap out. The AI algorithms need to be trained with high-quality, structured data so that it can actually provide the help we envision. Once again, standardisation of data comes into play here.
A data foundation
We see open data platforms as the foundation for data-driven care. When healthcare data is stored in a standardised way in an open platform, separate from the application, you can make this data available for multiple uses in, for example, connected applications and reports or dashboards.
Our open platform is called CareBase24. Feel free to contact us, we are happy to tell you more.