How Big Data Can Thwart Epidemic Diseases
Digital disrupting technology such as Big Data is globally revolutionizing healthcare. The new technology is bringing about digital transformation into every aspect of how a healthcare facility works. It is helping doctors share best practices and treat patients. According to a report by research firm Markets and Markets, global healthcare analytics market could reach $24.55 billion by 2021 from #7.39 billion in 2016, at a CAGR of 27.1%. Several Indian healthcare providers are experimenting with the technology.
Usually, disease outbreaks get detected retrospectively. They are detected either after they are resolved or around the time they begin to wane. Timely feedback of infection patterns as well as collection of relevant data is a perplexing task faced by hospitals. Timely response can reduce infection-related adverse outcomes and bring down the cost and length of stay, particularly when the infection is hospital acquired or it is has secondary complications. In all this, microbiology data plays a significant role in controlling the disease.
This includes early recognition of outbreaks as well as collaboration and notification within the various healthcare teams. The process is resource-intensive and takes time for the huge corpus of structured data—generated from laboratory reports—to be analyzed. By the time it is carried out it results in two things: slower patient recovery and complex care processes. This is where modern communication and digital technologies can prove to be immensely beneficial. They can ensure that the communication of infection surveillance on time leads to prompt analysis and action. For this, hospitals need to analytics in their digital Hospital Information System (HIS).
A multi-dimensional analytics engine processes Big Data coming out of clinical laboratory reports and then analyzes it. The analytics is then leveraged for clinical use. The model is integrated within the HIS. It provides clinical data for analysis as well as measures the spread of infection inside hospitals. Analytics also gives out trends and data summaries. Moreover, there are applications to combine live streaming, instant messaging and networking, resulting in marked improvement in patients’ quality-of-life.
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Big Data Applications can also give access to an interactive educational library which can have inbuilt features such as training courses, live streams, virtual reality (VR), and augmented reality (AR). Such features can help physicians go through research papers and genetic-sequencing data, conduct analysis, run through treatment records, as well as deliver insights into how to treat particular group of patients such as those with specific characteristics like blood group or DNA sequencing. Doctors will be able to benchmark patients against previous occurrences and can take informed decisions.
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“Earlier, analysis and communication of infection control data used to take weeks. This resulted in treatment delay and increased costs. Big Data implementation brings analysis near real time. The process that would otherwise take 3 weeks to be completed is reaching real time,” said Shashank Dixit, CEO, Deskera, a global cloud provider that also has a Big Data tool.
The results can be quickly made available for swift action and decisions if data is entered into the electronic medical record or the EMR. The tools can be used for several forms of care, not only restricted to hospitalization. This would ensure infection control is monitored clinically at all levels in the healthcare system. Such solutions can also provide analytics into multidimensional infection patterns as well as the development of resistance to antibiotics in patients in one integrated view in order to aid diagnostics and therapeutics.
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Leveraging Big Data Applications will also help healthcare providers reduced costs and relieve the stress of medical personnel and staff in a number of ways. Devising a standardized approach to quick notification in infection control cases increased the speed of diagnosis and aids better collaboration among clinical care staff, leading to decreased treatment costs and better outcomes.