• by Adam Mayer
  • The Covid-19 pandemic is the most graphic example of a rapidly evolving exponential threat in our lifetime. It has made everyone realize the need for more advanced infrastructure to be deployed, ready for any crisis. Considering the situation in an Indian context, it is time to rebuild or redesign hospital operations to meet future needs and radically improve their patient experience.

The healthcare industry produces a massive amount of data, which is crucial for deriving insights that lead to actionable outcomes. This data is the “lifeline” of healthcare organizations that underpin every element of hospital operations and patient care. Any future hospital design must take advantage of data, not just for optimizing facilities and outcomes, but also, to decide on new work processes as the environment changes.

The past year has witnessed an increase in use of remote medicine technology or tele-health in India. However, during the pandemic, when real-time data was critical in developing strategies to stop COVID-19 from spreading quickly, the healthcare sector could have started making better use of data, much earlier. In countries like the United Kingdom, many NHS Trusts had already put data at the heart of their operations, which in turn helped them improve patient care and optimize service deliveries. Drawing from these learnings, it is time to start using data available in hospitals in India to improve the current healthcare system.

Industry innovators lead with data
Data and analytics are already empowering healthcare organizations around the world to optimize their services and deliver better patient experiences. Indeed, as part of an IDC study commissioned by Qlik, three-quarters of healthcare organizations reported that investments in data management and analytics had improved employee productivity (72%) and operational efficiencies (73%). Many hospitals have used data-driven services to make more informed decisions.

For example, in the UK University Hospitals of Morecambe Bay Trust (UHMBT)’s Royal Lancaster Infirmary site uses real-time analytics to get information viewed on large, interactive screens on the number of ambulances on the way and availability of beds. This has helped them to assess their resources and streamline according to needs, increasing the number of patients triaged within 15 minutes by 30 percent (from 65% to 95%).

Similarly, another UK NHS Trust, Wrightington, Wigan and Leigh (WWL) Teaching Hospitals NHS Foundation Trust uses data in calculating the number of patients awaiting discharge. In doing so WWL have significantly reduced the typical waiting time for patients awaiting MRIs from ten days to just two.

Data analytics allows healthcare organizations to make smarter and more educated decisions directly enhancing the patient experience, even more so with access to real-time data. Considering the current situation in India, a lot more people are waiting for Covid-19 test results, information regarding their health conditions and regular check-up dates and results. With data analytics on top of data delivered in real-time, the number of patients, staffs and visitors can be analyzed based on what is happening now rather than what happened yesterday, aiding healthcare and frontline workers with more accurate information.

Improving access to data sharing across hospitals
There are great learnings that can be deduced from the examples mentioned of healthcare units successfully implementing data strategies, such as:

Cloud-based analytics – Medical experts are likely to be seated in front of a computer screen, accessing data that is crucial to their decision-making. All staff, no matter the type of unit, should be able to access the relevant data, when it is needed. Cloud-based analytics allows for better patient care if information can be shared in a secured manner with other health care organizations, such as social services and mental health teams among many others.

Advanced analytics and Machine Learning – Predictive analytics would be critical in assisting hospitals in forecasting resource and demand. If a hospital can predict a patient’s risk of re-admittance, for example, it will be better equipped to handle unplanned demand.

Shared-data model – Connecting data from various healthcare organizations to help the transition to a population-health model is critical to the health service’s long-term sustainability. However, there are two obstacles to overcome – the first is the conventional process of data integration that relies on one time batch uploads. This isn’t equipped to handle real-time data sharing across multiple systems and solutions. Data streaming systems would be critical in ensuring that information can be replicated and accessed at any time, by all organizations. The second problem is not being able to identify population health patterns. Companies require analytical solutions that can combine real-time analysis with hyper-contextual data to drive Active Intelligence, which can compel data informed action in the critical moment it is needed.

Data-driven hospitals are India’s future for better healthcare
The potential for improving overall patient care, collaboration, and analysis with the aid of cloud technology and data analytics is enormous. As India is preparing for digitalization to harness the power of data, migration to cloud systems and use of data-driven solutions give healthcare organizations the flexibility and storage they need to handle such vast amounts of data, allowing them to gain insights that improve patient care and hospital operations. Healthcare staff and executives will be in a better position to make the right decisions that enhance overall care when they have access to real-time data. This will empower practitioners to deliver the highest quality care in hospitals of tomorrow.

Adam Mayer is Senior Manager at Qlik

(DISCLAIMER: The views expressed are solely of the author and ETHealthworld.com does not necessarily subscribe to it. ETHealthworld.com shall not be responsible for any damage caused to any person/organisation directly or indirectly).

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