7- DATA, DATA,& MORE DATA IN HEALTHCARE by PHARMAGEEK
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7- DATA, DATA,& MORE DATA IN HEALTHCARE by PHARMAGEEK
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AI, User Experience Top Healthcare’s Data Analytics Priorities in 2019 #hcsmeufr

AI, User Experience Top Healthcare’s Data Analytics Priorities in 2019 #hcsmeufr | 7- DATA, DATA,& MORE DATA IN HEALTHCARE by PHARMAGEEK | Scoop.it

Healthcare organizations that want to get ahead in 2019 will need to prioritize the use of artificial intelligence, virtualized care, and technologies that offer intuitive user experiences, according to Forrester’s predictions for the upcoming year.

The ability to aggregate, analyze, and utilize big data to identify business opportunities and engage users will become even more valuable as traditional healthcare entities battle for market supremacy against a new wave of technology powerhouses, the survey-based brief says.

“Major disruptors, like Amazon and Walmart, will make good on their promises, delivering the personalized experiences that customers have been yearning for from healthcare organizations (HCOs),” the report projects, leaving providers and payers with a strong imperative to leverage the data they have to offer similar benefits to users.

“HCOs need to develop raving fans to survive, as all sectors face the entrance of new disruptors looking to own more of the customer journey,” Forrester added. “They must build digital experiences, including virtual care, based on an understanding of the customer’s evolving needs. Great customer experiences will be crucial to drive loyalty and revenue.”

Advanced analytics capabilities, including the use of tools driven by artificial intelligence, will be required to fulfill these expectations.

Healthcare organizations will need to let go of outdated measurement processes and approach the development of user-friendly systems in the same manner as other industries, the report stresses.

Star ratings and CAHPS scores may become less important as providers and health IT developers adopt new measurements for engagement and satisfaction.


Via Dominique Godefroy
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Harnessing data to improve patient outcomes #esante #hcsmeufr

Harnessing data to improve patient outcomes #esante #hcsmeufr | 7- DATA, DATA,& MORE DATA IN HEALTHCARE by PHARMAGEEK | Scoop.it

As data and analytics are increasingly leveraged in various aspects of the healthcare system, some companies are  making use of such capabilities to help clinicians make the best decisions for patients.

 

One such company is naviHealth.  Based in Brentwood, Tennessee, naviHealth provides both payers and providers with post-acute care management expertise. Its nH Predict tool allows clinicians to better predict a patient’s outcomes in order to craft a personalized post-acute care plan.

 

Using NaviHealths nH Predict tool, clinicians are better able to predict a patient's outcomes and generate a personalized post-acute care plan.

 

The result of the tool is a simple outcome report that is generated at the beginning of the patient’s stay in a facility or hospital. The report breaks down the patient’s basic information as well as how they’re doing in a variety of categories.

 

For instance, nH Predict outlines the individual’s gender, date of birth and admission date. It also includes their primary diagnostic group (such as COPD) and their usual living setting (like at home alone or in an assisted living facility).

 

Finally, the outcome report provides a score for a few of the patient’s functions based on the data of similar patients. It gives a score on the patient’s basic mobility (such as wheelchair skills or ability to take the stairs); daily activity (like bathing and dressing); and applied cognition (including memory and communication).

 

Additionally, the report creates a total average score for the patient based on their mobility, activity and cognition scores.

 

read the complete story at https://medcitynews.com/2018/10/navihealth-data-patient-outcomes/

 


Via nrip
nrip's curator insight, October 4, 2018 1:32 AM

Nowadays, healthcare data is increasingly being analyzed and complex algorithms created to help various aspects of the healthcare ecosystem.

 

This technique where some companies are  making use of such capabilities to help clinicians make the best decisions for patients, is also not new, and there are startups and enthusiasts working on building self learning algorithms to modify clinical pathways to create better patient outcomes in India, Singapore, Scandanavia. If you are working on something similar, please drop me a note. 

 

Beyond the hype, it will be interesting to see if the hypothesized benefits actually translate into reality. 

 

Plus91's R&D has stayed away from improving/modifying/changing medical care plans but instead we built self learning models both for early detection of diseases, as well as for early prediction of epidemics, and while we have been very successful with demonstrating epidemic prediction, and actually preventing it in 2 cases already, the same success is unfortunately not achieved yet in disease detection.