Healthcare and Big Data A Rising Up To The Challenge

Healthcare providers have big challenges, and big opportunities, when it comes to Big Data.

Disruptive competition and legislation is shifting risk from patients to providers, making it imperative to use data to reduce cost.  These concerns are exacerbated by the possibility that the US Supreme Court might rule that current federal subsidies are unconstitutional, making health insurance unaffordable for many Americans.  No matter the outcome, healthcare firms understand they must use data to improve efficiency.

A second factor is public expectation.  As consumers we are highly sensitive to quality of care.  In today’s environment it is increasingly unacceptable to have patient care suffer because the right data point didn’t reach a physician or nurse in time.

Finally, data still sits on many “platforms” that include paper with doctor’s handwriting.  Electronic Medical Records are a great step forward.  But those datasets, often bottled up in legacy software that is based on decades-old code, might not be easily accessed for analytics.

Despite all this, there is room for plenty of optimism.  Here are a few reasons that healthcare CIOs can look to the future with confidence.

1.  New mobile and home-based technologies can greatly improve care. Wearable health devices are popular because the premise makes sense: informed people make better lifestyle decisions.  And informed doctors provide better care, creating the right incentive to share vital data.  Startups like CipherHealth enable individuals to send sleep, diet and exercise metrics through wearables such as Fitbit to their doctor. Signs of risk prompt a reminder call to the patient, to ensure they visit the doctor when blood pressure spikes, their weight drops, etc. and solve problems before they get out control.
2. On the home front, I recently spoke with the COO of a telemedicine provider that is using machine learning algorithms to combine broad demographic and behavioral data with patient monitoring.  They use this algorithm to spot and better serve individuals who, based on their history, have a higher risk of not taking prescribed medication. 
3. Healthcare firms can leverage proven approaches from other industries to improve efficiency. Operations and logistics are great examples here.  Data scientists at one of our clients recently designed the “Emergency Room of the Future” by essentially treating an existing emergency room like a factory floor.  They analyzed data feeds from RFID (Radio-Frequency Identification) badges worn by doctors, nurses and staff as they journeyed through the physical and digital worlds of a real emergency room.  They tracked every key action, condition and outcome, including patient survey responses.  
4. Armed with this information, our client identified bottlenecks and ways to move people and equipment more efficiently.  The resulting data and recommendations will help their clients – namely, hospitals – build a better facility that provides doctors and nurses more time to help patients, reducing cost and improving patient experiences.
5. New software can integrate data across environments. Attunity software can aggregate data and files, including those using the HL7 messaging standard, across all major database, data warehouse, Hadoop and Cloud platforms, rapidly and without manual coding.  These tools lay the foundation for powerful analytics, based on automated workflows and business rules.  As one of many examples, we have a client that uses our software to feed data from their Epic database into their real-time Teradata warehouse.

I will be meeting many healthcare providers and experts on June 18th and 19th at the Big Data Healthcare Analytics Forum in New York, and will be speaking on a panel, “Keys to Creating a Data-Driven Organization.”  If you are at the show, be sure to stop by the Attunity booth to share your Big Data challenges, and learn more about how we can beat the odds.