The world is facing a global crisis, where timely decisions leaders will make over the coming weeks will distinctively shape the environment for years to come. From a public health perspective, to combat a pandemic, decision-makers must take several actions: to build awareness, set guidelines for health professionals, target infection clusters, limit population movements, and allocate scarce resources in a very quick manner.
But the challenge is this: it is the ever-evolving, rapidly changing, healthcare data recorded from the number of confirmed cases by geography to hospital staffs and inventory.
Leveraging on data-driven insights in real-time is imperative for leaders to make critical decisions at the frontlines of this pandemic, but many healthcare organizations are struggling to keep up with this rapidly evolving stream of data and efficiently harness it to meet the demands placed on the healthcare industry.
So, how do we navigate through the recovery of a pandemic like Covid-19 with data?
To connect real-time data between the hospitals and policy-makers, we need a dynamic feedback loop and a massive data integration. Here’s how it works:
Real-time feedback is crucial to understanding the virus activity, assessing the efficacy of suppression measures, and forecasting a near-term demand for local health systems.
Digital transformation adoption has been slow for most hospital systems, but COVID-19 has ignited the increase in effort, at least, to move towards consolidating health records. Hospitals have started to use multiple Electronic Health Record (EHR) systems for the clinical and organizational benefits they offer.
However, due to their complex data storage and analytics architectures, the interaction between these EHRs makes it difficult to collect all the data to provide a complete profile of the patient and to show the communities most vulnerable to Covid-19 by geography.
How to solve this:
A data platform that can integrate data across different EHRs, allowing for real-time exchange and utilization of information. As data from EHRs flow more instantaneously, healthcare organizations can predict patient surges, Emergency Room (ER) overcrowding, beds and oxygen supplies, ventilator inventory, and other essential operational issues.
Besides, data engineers are working on specialized AI live-streaming apps that can retrieve EHR data and build predictive dashboards to show how many patients they were likely to receive ventilator capacity, and peak ventilator usage.
During an outbreak, resources are limited and can be consumed quickly (such as the availability of equipment) as demand comes from the entire nation, possessing a major problem, especially in largely populated countries.
Government agencies play important roles to help the healthcare system receive the necessary resources for proper functioning. Hence, data analytics technology is much needed at a national level to rapidly generate updated data sets and run predictive models.
Such access, helps them to optimally allocate resources. Since most of the data important to government response is being generated in hospitals, this data must be easily communicated between healthcare systems and governments for policy development.
Atlas is an example platform that allows the integration between multiple sources of data (like the EHRs) that can allow for real-time data exchange and utilization for government agencies. Atlas provides a complete data governance suite that helps to govern and secure critical data without compromising the ease of data accessibility, restricting the data to be available only to those who need it, preventing any loss of time and data redundancy. For more information on Atlas, click here.
The Case of Taiwan and Swedish Health Services
With the outbreak of covid19 in China, Taiwan swung into action initiating health checks from airline travelers from Wuhan, gathering data from immigration records with its centralized national health insurance database. This information allowed healthcare facilities to access patient’s travel histories and identify individuals for Covid testing and tracking. Despite Taiwan’s proximity to Wuhan, Taiwan is credited for the low number of cases and deaths because of its efficient use of big data. Source: WHO
Swedish Health Services, a USA-based healthcare organization, has developed a platform for healthcare workers to report real-time data on volumes of patients with COVID-19, personal protective equipment, staffing, ventilator usage, and other resource information. This information has been shared across its hospitals to track the status of facilities, allocate healthcare resources, and increase hospital bed capacity. Source: WHO
While hospitals and governments are responsible to control the spread of the virus, many pharmaceutical and diagnostics companies spend their energies and resources on developing diagnostic tests, treatments, and vaccines for Covid-19 through in-depth research and clinical testing. These organizations require access to both clinical and real-world observational health data for fast-tracking the development of new medicines and equipment needed for current and future medicinal needs. The access to already existing data and analyzed results of handling the early strains of the coronavirus is a powerful guide to encounter any new variant like the Lambda variant found in South America.
However, the big challenge they face is the right teams having access to the right data on time. Most companies with large data storage often face the problem of not being able to access or share a group’s findings with other teams across an organization, which leads to a heavy loss of time causes a hindrance in further research progress and advancements. Therefore, it is important to have a platform that would ideally allow multiple teams to have access and share their data across the organization.
At Envyi by InfinitiLab, we constantly advocate for harnessing the power of data for organizations across the spectrum, with our first milestone, meet Atlas. Atlas provides the Single Source of Truth (SSOT) platform, which provides a real-time data platform that allows for faster decision-making. The interface provides a simple yet faster way for you to search, and use data to its full potential.