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Complimentary from the publishers of
Predictive Modeling News
July 1, 2013 |
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"Predictive modeling
certainly can be used to identify patients/members who would be likely
candidates for wellness and other disease management programs. This is
done through a two-step process of analyzing health risk assessments,
preferably completed by the patients themselves, in conjunction with
historical lab test results to see what the trend is, and other data
such as ICD9 diagnosis codes, and then this information is matched to
patient satisfaction surveys such as the SF12 and SF36. The only thing
holding this back is the lack of patient satisfaction data and health
risk assessment data, more than the EHR and claims-based clinical data....The problem in trying to use predictive modeling
to generate a ‘likely candidate list’ is getting data with which to
indicate ‘willingness.’ If patient-generated health risk assessment and
satisfaction data aren’t present, finding correlations between variables
that would serve as surrogates for a patient’s willingness to change his
or her behavior is going to be difficult.” Lawrence S. Borok, President,
Vantage Point Healthcare Information Systems
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For the sixth year in a row, a majority of
respondents, 51.4%, ranked identification of high-risk patients for care
management as the highest priority for how an organization could spend
its funds on predictive modeling initiatives.
Excerpted from:
Predictive Modeling
News, Volume 6, Number 7, Prioritizing Predictive Modeling
Activities: High-Risk ID on Top
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Pushing for More Predictive Analytics, More Data Talent
Health Data Management, June 28, 2013 |
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Healthcare Analytics Market Showing Double-Digit
Growth
PR Newswire, June 28, 2013 |
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Predictive Analytics, Cloud Computing, and Healthcare
Logicworks/Gathering Clouds Blog, June 25, 2013 |
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Predictive Analytics
Executive Insight, June 17, 2013 |
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Healthcare Predictive Analytics Gains Spotlight through Foundation Initiative
Marketwatch, June 10, 2013 |
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-
Prioritizing Predictive Modeling Activities:
High-Risk ID on Top
-
Journal Review
- The
Complexities of National Healthcare Workforce
Planning: A Review of Current Data and Methodologies
and Recommendations for Future
Studies
- Thought Leader’s Corner: “Can
-- and should -- predictive models be developed to
identify patients/members most or least likely to
respond to, and modify behavior as a result of,
wellness incentives, value-based benefit designs and
related programs?”
- Industry News with briefs
regarding MedeAnalytics; BCBS Vermont; MZI Healthcare
and HP; GNS Healthcare; and Skila Mederi and Qforma
- Catching Up With…William
H. Rice MD
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Click here to view page one of this issue
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Click here to subscribe to
Predictive Modeling News, or find out more
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