Category Archives: Big Data

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Predictive Analytics May Save Healthcare Budgets 15%, Survey Finds

Ninety-three percent of healthcare provider and payer executives agree predictive analytics are important to the future of their business, according to a Society of Actuaries report.

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It’s Time for Prescribing Leadership in Healthcare

The healthcare industry has been charged with making significant changes in the last few years. From value-based care, to population health and now precision medicine. Unfortunately, many hospital systems will not be successful due to the need for better leadership.

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Putting the Precision into Precision Medicine

I was invited to speak at Oxford Global’s inaugural Precision Medicine Congress, April 25 and 26 in London, England. My topic, “Big Data Analytics for Precision Medicine”, stood out from the other presentations, as intended, since I was one of few non-clinicians or genomics scientists invited to speak at the Congress but believe that as I professor and data scientist I was able to hold my own. As an added bonus, I had to pleasure to meet a ‘Sir’ and a ‘Dame’, which are knighthood titles bestowed on extraordinary subjects, in recognition of their great achievement or outstanding service to the United Kingdom. Both worked in the healthcare industry either in the public or private sectors.

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BIG DATA & HEALTHCARE ANALYTICS: A HIMSS EVENT

Please join me at my leadership presentation for this conference.

SAN FRANCISCO, CA

MAY 15-16, 2017


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5 Must-Haves for Effective Analytics in Clinical Decision-Making

In healthcare, data is king. Clinicians rely on data to make informed decisions at the point-of-care and ultimately propel patients’ health forward. However, the wealth of unstructured data captured by IT systems in hospitals may prove fruitless if physicians can’t use it to inform care decisions in real time. Analytics must be straightforward, easily digestible and accessible to help physicians personalize and improve patient care planning.

Read More at Becker’s Health IT & CIO Review

 


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2016 State of Population Health Analytics Report

Executive Summary

Since 2014, the Healthcare Center of Excellence (HCOE) has been tracking the healthcare industry’s progress towards population health analytics using their proprietary Healthcare Transformation Change Model. This model was developed in 2013 to help healthcare organizations understand the requirements to become an analytics focused healthcare organization. The concepts were based on a customer relationship marketing (CRM) implementation model, previously co-developed by Professor Bennett. The CRM model was considered by Gartner to be one of the top three CRM implementation visions at the time and has become the basis for most successful CRM implementations today.

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2016 State of Population Health Analytics – Webinar Reminder

There is only one day before the webinar on the 2016 State of Population Health Analytics study on Wednesday, December 7th. Spaces are filling up. Please register using one of the links below.

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The State of Population Health Analytics – 2016 Study Results & Webinar

Since 2014, the Healthcare Center of Excellence (HCOE) has been tracking the healthcare industry’s progress towards population health analytics using their proprietary Healthcare Transformation Change Model. This model was developed in 2013 to help healthcare organizations understand the requirements to become a data-enabled healthcare organization. The concepts were based on a Gartner recognized CRM implementation model Professor Bennett previously co-developed. This model was considered one of the top three CRM implementation visions at the time and has become the basis for most successful CRM implementations today . Based on the model, the HCOE determined that in 2014, the industry was just past the “EHR Implementation” stage. In 2015, the dial moved a bit further as many organizations began achieving success with integrating data sources.

How is the healthcare industry progressing towards the implementation of population health analytics?

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Need a Data Scientist? Try Building a ‘DataScienceStein’

Category : Big Data

Organizations are finding that hiring qualified Data Scientist is a real challenge. Experienced Data Scientists are expensive and are usually employed elsewhere. This high demand, low supply economics is leading to a situation of the ‘haves’ versus the ‘have-nots’, where the larger, financially rich organizations in the ‘sexy’ industries are most capable of attracting and hiring data scientists, while the lesser companies will have to make do without one.

Organizations are looking at new approaches to finding data scientists. Some are able to attract them with more than money like autonomy and development opportunities. Others are training current staff to become more data literate through professional development programs. Once trained, these individuals typically must work 12 to 24 months at the organization or have to pay back the amount spent on their training.

There is another approach that should be considered.

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Predictive Analytics World Chicago 2016 Recap

I attended Predictive Analytics World in Chicago the week of June 20 to June 23. I met a lot of new people and was reacquainted with several other colleagues. As I listened to 2 days of workshops and the pre- and post-conference workshops, some common themes emerged. Most of these themes confirmed what I have been touching on in the presentations I’ve made at conferences over the last few years and discussed in my book, Competing On Healthcare Analytics, but it was reassuring to hear the same concepts presented by others.

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Upcoming Speaking Events

 

Becker’s Hospital Review 9th Annual Meeting
The Personalized Leadership Journey
Chicago, IL
April 14, 2018

Becker’s Healthcare 16th Annual Spine, Orthopedic and Pain Management-Driven ASC Conference + The Future of Spine
How Leadership is Like Golf
Chicago, IL
June 16, 2018

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