Clean Air for Healthcare

A use case had been identified were Anaeko could provide informative dashboards in order to determine and understand the relationship between air quality and health conditions. 

There is a wealth of data within healthcare industries from patient, research or physician data and there is no doubt that harnessing this data will lead to new technologies, innovation and improved patient care.

55% of the population live in urban environments and these environments play an essential role in human health and wellbeing. Air pollution contains air particulate matter, PM2.5, that can stay in the air for long periods of time and be inhaled deep into the lungs. Pollution within urban areas can have an affect on asthma sufferers and "Around two thirds of people with asthma tell us poor air quality makes their asthma worse, putting them at risk of an asthma attack." (www.asthma.org.uk).

Data analytics within healthcare has the potential to transform patient care and the health sector in many ways. The analysis of data can help gain insights and support decision-making by collecting data from a variety of areas like medical costs, clinical data, patient behaviour and pharmaceuticals. Because healthcare data is so complex and can be difficult to process there are some barriers but here are 4 benefits and a look at some examples of how data analytics is being used. 

The healthcare industry produces and gathers a huge amount of data and this data has the potential to be used in predictive analytics modelling to help improve and forecast the demand on healthcare services. There are many ways in which predictive analytics could be used. Some companies are looking at forecasting hospital readmissions and others looking at predicting specific patient illnesses before they become serious. 

Inpatient Waiting Times

In Northern Ireland inpatient waiting times are increasing and becoming longer compared with other parts of the UK.

Providers in the healthcare industry must take every precaution to ensure the data they are handling is protected with levels of data security and privacy.

Healthcare systems generate huge amounts of data and this opens the opportunity for data discovery, artificial intelligence and machine learning to provide insight, synchronise data between silos, optimise innovation, enhance decision making and increase efficiency of research.

Artificial Intelligence In Healthcare

There are few (if any) industries that can be transformed by artificial intelligence to the degree that healthcare can. As initiatives around the world seek to digitise healthcare data, there are huge opportunities for game-changing tools and platforms. However, with potentially a yottabyte (1024 gigabytes) of healthcare data in the United States alone, we are no closer to this utopian, data-driven world of healthcare. Data in existence is not standardised, highly fragmented and is stored in incompatible legacy platforms. The technology exists, so why is healthcare so far behind other sectors in utilising existing technology and what needs to be done to catch up?

In the Digital Age, the Private sector is investing in some of the best analytic tools to gain deeper insights to make better decisions. When we fail to interpret the data, the consequences can be detrimental.