The healthcareindustry is becoming increasingly digital. An expansion into online care has ensured a connected patient experience. The industry itself is growing exponentially: The global digital health market is anticipated to grow 17.5 percent by 2027, reaching a total valuation of USD 456 Million. Though digital solutions have ushered in a new era of healthcare, demand for patient-centered care, ever-increasing costs, and operational inefficiencies are continually adding new layers of complexity.
Harnessing the full potential of digital transformation could profoundly impact the healthcare industry, rendering it more agile and efficient. Although the challenges are substantial, the solutions are equally formidable.
Business Process Automation: Why Does it Matter?
The success of digital transformation efforts in a healthcare organization depends on its ability to capitalize on process automation capabilities. Business process automation helps automate repetitive and routine activities that usually cause inefficiencies and drive up operational expenses.
Process automation solutions such as Robotic Process Automation (RPA) present extraordinary opportunities for the healthcare business to thrive by offering tools to manage data, optimize workflows, and deliver superior clinical care.
Fully Automated Data Processing
Collecting, processing, storing, and retrieving health information is one of the central activities in the healthcare industry. The inflow of data comes from multiple sources: Diagnostic devices, Electronic Health Record (EHR) systems in hospitals, medical machinery, direct from the patient, online services, etc. Data is a big part of the healthcare industry, generating one-third of the world’s data volume.
At the same time, nearly 50 percent of medication-related issues in the industry are driven by error, and executives attribute staffing shortages as the primary reason for the increasing medical errors. As healthcare professionals grind through data and create reports, manual data processing goes terribly wrong and puts patients at serious risk.
When the healthcare industry chooses to automate data processing and employ RPA, it skillfully handles data complexity by deploying unattended bots. These bots mimic human actions and follow a sequence of steps efficiently to automate highly manual and error-prone tasks and non-standard processes. It can streamline data entry and reconciliation processes.
Fully optimized data capture, integration, and analysis can help healthcare industries unlock deeply buried insights from healthcare data. For instance, an analytics-driven center of excellence model helped a pharmaceutical research firm achieve a global view of the healthcare market, scaling operations across geographies and portfolios. The analytics-driven model helped the firm meet the client demand for comprehensive coverage, quality analysis, and swift turnaround. Healthcare businesses can use such analytical solutions to strategize their growth and expansion roadmaps.
RPA empowers the staff to accurately document patient encounters, diagnoses, treatments, and outcomes. Organizations can also add one more layer on top of RPA: Machine Learning (ML). Whereas RPA typically can process structured data, the ML component enables pattern recognition. It can process unstructured data from scanned document images like echocardiography, PDF, and scanned handwritten information.
Streamlined Administrative Processes
RPA can not only process patient data but also automate everyday administrative tasks like scheduling, billing, and claims processing. Healthcare providers can dedicate more time to delivering care and less time to manually managing front-office operations. For instance, a US-based health insurer automated its end-to-end claim processing to reduce turnaround time and improve operational efficiency.
59 percent of healthcare executives implement digital transformation solutions in their workplaces to fast-track employee productivity. RPA can implement a well-crafted automation strategy to streamline facilities such as outpatient clinics, medical departments, insurance agencies, and nursing homes, thus enhancing patient engagement. For example, RPA can schedule doctor appointments and send automated patient reminders.
Though delivering efficient and quality healthcare presents enormous challenges, the advent of business process automation tools like RPA and ML can alleviate overburdened staff and support them in administrative tasks. The results are spectacular: Patients receive more precise care and practitioners can be more productive.
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