Healthcare analytics for operational efficiency and better patient care.


Healthcare analytics for operational efficiency and better patient care.

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  • The healthcare industry has a large number of sensors and digital devices to investigate and monitor patients’ health. There are also laboratory reports, tests, payer information, emails, notes of health professionals etc. with a wealth of data.
  • BryteFlow can ingest structured and unstructured data for analytics and Machine Learning from a variety of sources on a single platform that can be used to identify operational inefficiencies, actionable insights and waste. Real-time predictive data analytics can be used in research, to provide better bedside care, reduce risk and improve safety.
Better medical interventions and patient care

Instead of manually monitoring a patient’s vital signs, healthcare professionals can respond to situations proactively by having wireless sensors record and transmit patient data which can be collected and prepared by BryteFlow. The data collected can alert healthcare caregivers to take pre-emptive action if they sense a worsening of the situation. Over time the accumulated data can be used for healthcare predictive analytics to form algorithms that can predict and avert a medical crisis.

Preventing fraud and financial crimes

BryteFlow ingests very large datasets and prepares them for predictive modeling so healthcare providers can hone in on fraud and criminal practices. Over-use of hospital facilities in short time frames, treatments from different hospitals simultaneously, prescriptions for the same patient presented in multiple locations are red flags that come up when patient billing and records get under the data analytics scanner.

RFID to track caregivers, drugs and equipment

RFID tags, sensors and scans of devices can help record date of manufacture, shipping information, order number and location of devices and items. This radio frquency identification data helps hospitals to keep a track of essential items. They can plan inventory, restocking or even locate some needed item. Data from various sources and devices can be integrated and prepared by BryteFlow so medical facilities can use it for predictive healthcare analytics.

Data analytics and Machine Learning for healthcare research

Cutting edge medical research typically features very huge datasets. For e.g. medical trials involve using all kinds of data right from demographic data, patient data, trial controls and protocols, drug interactions and patient responses. BryteFlow has the capability to ingest and prepare this multi-source data for healthcare analytics and Machine Learning so researchers and doctors can form an informed and precise view of the trial’s outcomes.

Getting to know patients and providing a better customer care experience

The personal and medical data of every patient is logged into the medical facilities system – prescription, treatment details, attending doctors, payments, hospitalization records and more. The data is probably locked into legacy databases which BryteFlow can ingest and prepare to provide a unified view of the patient. Whenever a patient has a query or needs an appointment or needs to make a payment, he can be assured of getting a quick response rather than being subjected to the usual time-consuming barrage of questions. The hospital can send greetings on patients’ birthdays and anniversaries, inform them of hospital offers and promotions and generally build a long-term relationship with the patient.

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james w
James Weakley
Enterprise Architect,
NIB Health Funds

Better customer experience and improvement of lapse propensity.

“BryteFlow acts like a bridge between our legacy systems and digital technologies like Kinesis events stream to enable our digital initiatives. At nib Health funds we needed to publish a real-time data feed to AWS Kinesis from a third-party application and considering the massive volumes of data, needed an industrial strength data management solution that would achieve this.

The Bryte team did an outstanding job of configuring theirBryteFlow product to track and publish changes on the underlying SQL Server database. It has been over a year now and our BryteFlow solution is working like a dream. It acts like a bridge between our legacy systems and digital technologies like Kinesis events stream to enable our digital initiatives.The solution is resilient, cost-effective and very low maintenance. The team at Bryte worked hard with us to accommodate our requirements, modifying the application where necessary.”

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Enabling an omni-channel customer experience.

nib is one of Australia’s fastest growing health insurers providing medical and health insurance to over one million Australian and New Zealand residents. nib Health funds operates in an industry with very high “lapse propensity”. It was already collecting online clickstreams and was looking for a way to match the online visitor if he/she contacts the call centre enabling an omni-channel experience. The call centre operates a Genesys telephony system, which is underpinned by a SQL Server database.

BryteFlow helped nib improve its lapse propensity score.

Using BryteFlow’s point-and-click interface, nib Health Funds was able to sync SQL Server to AWS Kinesis stream. A third party tagging software was able to match the telephony stream to clickstreams, creating a unified persona across these different channels. With the solution fully operational, whenever a visitor fills out an online quote and quits before completion and when he/she contacts the call centre, the operator will have relevant contextual information to facilitate the caller in a meaningful way, thereby improving the customer experience.


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