dataops the future of healthcare automation

The Future of Healthcare Automation, Health News, ET HealthWorld


DataOps: The Future of Healthcare AutomationBy Dr. Sina Bari

Traditionally, healthcare has been human-powered. Physicians and related staff have always driven manual processes, be it record keeping, diagnosis, or administrative tasks. However, unprecedented challenges – such as the COVID-19 pandemic and escalating cost – have put immense pressure on healthcare systems and conventional methods have fallen short.

The healthcare industry generates vast amounts of data through record keeping, imaging, laboratory analysis, and compliance. In high-pressure, resource-depleting situations, such as the pandemic, managing and analysing the large volume of data could be strenuous. Thus, the utilisation of data from electronic health records (EHRs) is increasing significantly and automation is playing a key role.

These recent dynamics in the healthcare ecosystem have led the industry to innovate and adopt newer tools such as digitisation and automation throughout business processes to increase overall efficiency.

As of 2020, 34% of large healthcare organisations had already implemented automation solutions, said a report by Statista. A pre-COVID survey by Deloitte similarly found that 75% of healthcare organisations with an annual revenue of $10 billion have already invested over $50 million in artificial intelligence (AI) projects and research. Moreover, 73% of all healthcare organisations plan to increase investment in AI development soon.

Data challenges in healthcare
As healthcare takes center stage across the globe, there is a need to address challenges and streamline the ecosystem to deliver fiscal impact and timely care. The pandemic uncovered the shortcomings of healthcare systems and underscored these data-related flaws:

● Difficulty in analysing real-time data in large amounts and deriving real-time insights for better decision making
● Challenges in extracting, integrating and standardising data generated in the ecosystem
● Complexities in using data to monitor and manage resources and integrations due to budgetary constraints and staffing issues

DataOps for addressing healthcare challenges

With increasing social and environmental complexities, traditional healthcare systems are bound to get overwhelmed. This is where technology, especially the adoption of DataOps solutions, will play a vital role.

DataOps links across technical disciplines to deliver faster insights, high-quality data, collaborations across people and processes, and defines measurement and transparency. This has the potential to assist the healthcare sector to use innovative data analytics and drive smart business practices to effectively reduce costs and increase profitability. Here’s how DataOps can play a significant role in healthcare.

● Optimising staff and systems: Clinical staff and operations are the most crucial elements of the healthcare ecosystem. They are also complex and costly. Intelligent, data-driven insights can enable organisations to predict the right clinician mix needed for a specific department. It can create a value-based ecosystem by automating clinical operations such as investments in physician recruiting, clinical staff scheduling and clinical systems change seamlessly.

● Insights into community health: A data management approach using automated data pipelines and governance can enable the creation of dashboards of community health data to deliver insights. These insights are important in dealing with community health crises as well as forecasting future health challenges. This is important as it helps organisations to prepare for and reduce negative impact.

● Patient-centric systems: DataOps can assist in creating patient-centric systems to deliver enhanced operating processes and better customer engagement. Such DataOps-led architecture can help assess tools and capabilities to identify and recommend patient-centric approaches to improve connectivity, engagement and collaboration with patients.

● Optimised revenue: Data-driven systems are capable of processing large volumes of data to deliver actionable insights. Managing revenue models manually is error-prone, time-consuming and may lead to delays and backlogs. With DataOps, these challenges can be managed daily and in real-time.

● Pharma innovation and investigative analysis: Advanced analytics can add immense value to pharmaceutical discovery and investigation. It automates data analysis and extracting insights to improve performance of lab experiments and molecular data, leading to accelerated results. It also enables analysis of patient data to match diseases and treatments in vulnerable populations for improved patient care.

Technology in healthcare is not just about medical robots. It is about employing modern technology to advance performance and delivery of solutions. DataOps in healthcare has the potential to provide benefit to not just the healthcare ecosystem but also society overall. It can build strong healthcare systems with the capability to manage local as well as global crises such as the COVID-19 pandemic efficiently.

Dr.Sina Bari, – Director of Medical AI at iMerit.

(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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