This article throws light on current data related challenges in healthcare sector along with how organisations can benefit from various digital initiatives like getting a unified and 360 degree view of various entities for an efficient and effective data exchange and management. Building a predictive intelligence and data analytics platform aggregating data from all stakeholders with real time reporting capabilities can bring a transformative change in digital healthcare.

Traditional Healthcare is experiencing a tectonic shift and is clearly one of the hottest frontiers for digital disruption. The sector is ripe for digital transformation as it could give an opportunity to unlock data related intelligence and analytics to a largely underserved industry, touching millions of lives. Many countries are devising their national eHealth programs investing heavily on digital healthcare. With organizations increasingly investing in robust IT infrastructure for an effective and efficient data exchange and management, initiatives such as digitizing medical records have made the need for good and clean data at the center of this digital transformation.Incorrect and inconsistent information across organizations due to reasons like information duplication or IT systems not talking to each other often leads to higher operational costs, compliance penalties, sub-optimal resource utilization with consequent impact on key stakeholders.

Organizations need a powerful and unified platform for an end to end data management of various stakeholders with a 360° view of entities like practitioners, patients, suppliers, insurers and other players in the ecosystem. Let us face it – data is the new oil,and goes without saying, we need good data refineries to really make sense of all the available data to get the right insights. Mining the massive amount of data, which most of the healthcare providers have access to can help in building predictive healthcare intelligence.For a largely traditional industry like healthcare, where practitioners depend on independent evaluation and derive own clinical diagnosis and decision making, an ecosystem level collaboration and exchange will be beneficial for the entire industry.

Key Challenges in Data Management

• Data duplication : Refining and making sense of the deluge of data from different sources.

• A 360° view of relations and interdependencies between various entities like providers, patients, suppliers for decision makers to take a holistic view.

• Risk categorization of patients for an integrated and holistic medicare.

• Data security and privacy.

• Data capturing is not taken seriously especially in the context of eHealth monitoring for digital health services.

• Right clinical data to get the right insights for effective decision making.

• High administrative and operational costs.

• Fraud in payments and other customer touch points.

• Data transparency in patient care.

• Lack of a good feedback mechanism for healthcare input companies (Pharma, Insurance, Medical instruments, Technology vendors, digital health systems etc) for innovating new and cost effective R&D in medical treatments.

• Building an effective outcome and evidence based service approach.

Why is 360° view important?

Healthcare providers across the world are sitting on huge amounts of data, often in silos, which when used in the right way, can really help drive better outcomes. The multiple sources of disparate data captured from diverse stakeholders can add to the complexity. Under these circumstances, Data integration and aggregation with robust infrastructure and technology platforms with inherent deduplication capability (which can remove noise from the sound, so to speak) becomes crucial. A unified and 360° view can help in getting a single source of truth with all possible contributing parameters available. Deduplication is an important step as it gives a streamlined, unified, duplicates-free and 360° view of the available data – which can mean connecting the right dots where decisions are taken in totality and not in isolation. After all, the analytics you get is only as good as the contributing data which drives it. For example, if a practitioner has a full overview of a patients’ health (current and historical data) in real-time, the diagnosis and prescription could be holistic and data driven which can be very effective.

The Big “Datalytics” moment is here

Data analytics can play a catalytic role in overall healthcare management for better services and outcomes. Analytics has become a proven phenomenon which has transformed many industries from government to banking, retail to travel verticals and has the potential to transform medicare industry too. While cost savings and overall improvement in medical services are immediate benefits, taking a lead in the data centric initiatives can give competitive advantages to organizations in many ways apart from giving the industry a new thrust and direction which could have a lasting impact on lives of millions of people around the world. An outcome based approach leveraging operational, clinical, claims and other available data can help improve overall patient care, something which access to right data can enable.

Access to the right data can help providers deliver superior quality service with differentiated and personalized value added services. Every aspect of patient care could become a digital data point for a comprehensive outcome based diagnosis in the overall clinical process. Some of the other tangible benefits include creating actionable insights, improving clinical effectiveness and decision making, reduce data related medical errors, and improve patient wellness and overall satisfaction. On the administrative front, it can reduce costs and improve overall operational efficiency, drive revenue growth. While healthcare has been a fertile ground for payment related frauds, a good data engine can help reduce fraud and incorrect payments. Regulatory compliance is another major area where good data analytics can help mitigate the risk and help build robust pro-active and stringent compliance initiatives.

Big Data Mining for Predictive Intelligence & Real time reporting

A pertinent question is: How can all the stakeholders in the healthcare sector together with government collaborate to build a risk mitigating and predictive intelligence platform? Essentially, a platform that can give a combined and aggregated view of different sources of data to get insights streamlined into a single view simplifying complex data. Can the organizations re-use and mine the massive data points to connect the dots (in terms of conditions for a particular health trigger to happen, discovering relationship and patterns within these disparate sources of data) and predict if a given place is going to have a health epidemic (like Zika virus)? Can we get reliable intelligence in making sure that does not happen as well as contain its spread further? The individual contributing data pools from each stakeholder when combined and rinsed for data related insights can be a great information clinical repository. Such data mining can throw light on various patterns and help analyze the cause-effect relationships with real-time reporting capabilities.

Want to write for InnoHEALTH? send us your article at  magazine@innovatiocuris.com

Connect with InnovatioCuris on: 
Facebook: https://www.facebook.com/InnovatioCuris
Twitter: https://twitter.com/innovatiocuris
Linkedin: https://www.linkedin.com/groups/7043791
Stay update about IC by visiting: www.innovatiocuris.com

Connect with InnoHEALTH 2017 on: 
Facebook: https://www.facebook.com/innohealth2017
Twitter: https://twitter.com/innhealth2017
Linkedin: https://www.linkedin.com/groups/7043791
Stay update about the conference by visiting: www.innohealth.in