OpenApp have developed a unique and insightful approach to analysing health and business data in collaboration with the Health Service Executive (HSE), The Royal College of Surgeons of Ireland (RCSI), The Royal College of Physicians of Ireland (RCPI), The National Office of Clinical Audit (NOCA) and other organisations.
The primary aim of OpenApp Analytics is to exploit the potential of available data (internal, external and public) to help improve patient care.
Designed by clinicians for clinicians, OpenApp Analytics is a set of innovative processes and software tools which delivers Key Performance Indicators (KPIs), Key Quality Indicators (KQIs), Comparative Metrics and Process Control Indicators and Alerts.
OpenApp Analytics is customised for each clinical programme analysing validated data and transforming it into trusted, easily-understood, transparent intelligence and performance patterns.
A proven solution for health intelligence
OpenApp Analytics has evolved over a number of years, primarily driven by a suite of projects under development for the Health Intelligence Unit of the Health Service Executive in Ireland. The suite of projects has evolved under the banner of the National Quality Assurance Intelligence System (NQAIS) and currently covers a number of clinical programmes, all under differing stages of development, release and implementation.
Each clinical programme or healthcare unit has its own data sources it needs to analyse, answer and report on as defined metrics. From the outset, requirements are initially specified by clinical programmes and further refined by clinicians or clinical managers. Tight collaboration between OpenApp and client is key to the success of each project.
Health Data Quality Assurance in Mind
The Quality Assurance measures we have in mind that underpin the software design include:
1. Signalling of good and bad process performance should be clear and unambiguous.
2. The people who most need the data are the people who actually complete a process – whether reporting, analysing or further validating.
3. Quality Assurance methodologies give us indications of process performance to give us confidence we are ‘managing’ the process and it is under control.
4. Quality indicators that are easily understood and ‘actionable’, so that the user has a good idea how to proceed with rectifying problematic or undesirable performance.
Health Intelligent Visuals – Introducing OpenApp’s ‘DiamondFlag’
Viewing data visually is imperative to understanding what is being reported. We have a number of objectives of our visuals:
They are based on commonly used visuals.
They give a clear indicator of good or bad and/or desirable or undesirable performance.
OpenApp has a Unique ‘DiamondFlag’ display.
Improving on the standard box-plot chart, OpenApp Analytics ‘Diamond Flag’ allows outlier, mean and comparative data to be viewed in a unique and meaningful way.
The charts that are produced can quickly capture KPI and KQI performance and alerts using several variables in one chart. This visual display optimises the data and immediately tells a story, showing data shape and spread against a goal. In order to create an easily viewed and interpreted visual, the boxplot is converted to a horizontal diamond. This allows the assignment of a colour to indicate performance.
The pattern of patterns for healthcare informatics
No metric or Key Quality Indicator (KQI) stands on it’s own. The intelligence is in the context of other similar metrics that tell us whether “we are doing well and so are others” or “we’re not doing well but other are”, suggesting the known process is capable of better, or “we’re doing well and others are not”, suggesting we have something to share with others.
OpenApp Analytics presents metrics in the context of others, subject to the users’ viewing rights.