HCS499 Strategic Planning Discussion 1. Why is it important to complete a SWOT analysis before creating goals for a strategic plan?150-200 words. Please c
HCS499 Strategic Planning Discussion 1. Why is it important to complete a SWOT analysis before creating goals for a strategic plan?150-200 words.
Please cite all quotations, facts, and ideas that are not your own original work and please don’t paraphrasing
2. Please review this article and let me know your thoughts: 150-200 words. This article is attached
Please cite all quotations, facts, and ideas that are not your own original work and please don’t paraphrasing
Keckley, P. (2015). Strategic planning checkup. Trustee, 68(3), 23-24. Retrieved from https://search-proquest-com.contentproxy.phoenix.e…
3.Please review this article and let me know your thoughts: 150-200 words. This article is attached
Please cite all quotations, facts, and ideas that are not your own original work and please don’t paraphrasing
Sammer, J. (2014). HOW PLANS CAN LEVERAGE BIG DATA. Managed Healthcare Executive, 24(2), 46-47. Retrieved from https://search-proquest-com.contentproxy.phoenix.e… Strategic Planning Checkup
Keckley, Paul
Trustee; Mar 2015; 68, 3; ProQuest Central
pg. 23
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
Technology
Tr an s fo r m i n g car e Th r o u g h h ealTh iT
How plans can leverage big data
Choose your goals before crunching numbers
by Joan n e Sam m e r
he age of big data is
here and many health
plans have been
building and leveraging their
data analytics capabilities
for some time. Plans that
have not invested in the
technology infrastructure
and data building necessary
to maximize the benefts of
data analytics could soon fnd
themselves lagging behind.
Here are some ways health
plans can start diferentiating
themselves by using big data.
1/ Build a foundation
Data analytics is only as powerful
as the underlying data. Tat is why
many health plans are investing
heavily in upgrading their technology infrastructure and cleaning up
and standardizing their data.
“Some plans are relatively
sophisticated in using their data
and others are struggling,” says
Pamela Peele, chief analytics ofcer
for UPMC Insurance Services
Division in Pittsburgh. “Te
constraining factor is how much
investment health plans have in
their IT infrastructure and that
varies widely across health plans.”
UPMC Health Plan, which has
invested some $1.5 billion in its IT
infrastructure, has created a large
data source of what Peele calls
“a harmonized, groomed layer of
information holdings and data from
46
multiple disparate sources.”
UPMC Health Plan is using
data analytics in a number of
areas. For example, it focuses on
reducing hospital readmissions
before a member is even admitted
rather than waiting until the
patient is discharged. Te plan
has developed data models
that calculate the probability of
readmission among its entire
health plan membership.
“Every month, we are
predicting readmission probability
based on whether a plan member
who is admitted to the hospital
today would be readmitted to
the hospital within 30 days after
discharge,” says Peele. “When
someone is admitted to one of
our hospitals, that readmission
risk is displayed on the opening
screen.” At that point, the hospital
creates the authorization for
the admission and also begins
the work on reducing that
readmission risk as much as
possible.
2/ Set guidelines
Using data analytics to bolster
existing priorities may be tempting,
but doing so will not allow health
plans to maximize their return
on their investments. Ken Park,
vice president of payer and
provider solutions at WellPoint
in Indianapolis, ofers three
suggestions that can serve
Managed healthcare executive ❚ February, 2014
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as broad guidelines when using
data analytics:
■
Don’t bend the data in order to
prove an ongoing hypothesis.
Look at what the data is actually
showing you.
■
The focus should be on ways
to deliver the highest quality
healthcare at the most afordable
prices rather than ways to provide
the lowest cost healthcare
regardless of the quality.
■
The most efective data analytics
focus on a valid clinical question
that is not already answered by the
academic literature, are relevant
to the business and promise a
signifcant business impact, and
begin with a clear idea of how the
organization will use the resulting
information.
3/ Learn from
other industries
As health plans shift to more
consumer-oriented business
models, data analytics will become
more important.
“Health plans need to learn
to use data the same way that
American Express, Disney,
Harrah’s and others have,” says
Jack Newsom, vice president of
marketing analytics at Silverlink
Communications, Inc. “Tis
means understanding what
motivates individuals and
learning how to communicate
with them in order to build trust
and loyalty, and ultimately change
behavior.”
For example, UnitedHealthcare
has leveraged its data analytics
in an efort to increase colorectal
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Technology
cancer screening rates among
minority populations. Tis efort
included analyzing the screening
rates among 500,000 plan members
in diferent ethnic groups to
identify barriers to screening and
to determine the most efective
methods of encouraging specifc
groups to complete recommended
screenings. Based on the results,
UnitedHealthcare created
customized outreach programs
to increase screening rates. Te
analysis found that a phone call
from a plan representative to one
group of men increased cancer
screening nearly 11% compared
to another group who received a
recorded call.
4/ Leverage multiple
data sources
Te more strong data in the system,
the more powerful data analytics
will be. Core claims data, memberprovided information from health
risk assessments and general
marketing data can all support
data analytics. For example, plans
can use general marketing data to
get information on household size,
whether members use mail order
and other standard marketing
information. Plans can use this
data to get a clearer picture of each
member that can be important
when trying to coordinate and
improve access to care.
UPMC Health Plan relies on
health risk assessment data to get
a sense of the potential plan usage
among new enrollees in Medicare
Advantage plans during their frst
12 months with the plan.
“With no usage data among
newly eligible Medicare Advantage
enrollees, we would have to wait
and see who is going to require
care coordination,” says Peele. “We
identify those members using a
specifc combination of answers
on the health assessment survey
and assign a care coordinator to
that member before they have
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their frst doctor’s appointment.”
UPMC Health Plan also receives
daily data feeds from all of its
vendors, including the provider of
health risk assessments, labs and
pharmacy beneft managers so
that the plan does not have to wait
for claims data before acting on
that data.
Peele expects clinical outcomes
data to be the next frontier in data
gathering. Claims data can show
productivity measures, such as
how often members see a doctor
and the exams or tests done.
However, “we want to know the
outcome of that care,” she says. “If
a diabetic patient sees a physician
for a hemoglobin A1c test,
outcomes-based data will show
how efective that care has been in
terms of actual clinical outcomes.”
5/ Combine clinical
and claims data
Data analytics do not have to focus
solely on operations. WellPoint
uses both claims and clinical data
to evaluate medical policies and
its drug formulary to see whether
coverage for a certain drug is
appropriate and to evaluate the
efectiveness of diferent beneft
designs and programs.
Another use for data analytics
is to test and disseminate
information on clinical care. For
example, WellPoint’s analytics
can evaluate treatment patterns
for children with chronic
headaches to determine the
prevalence of CT scans. A key
concern is that use of CT scans in
treatment and diagnosis exposes
patients to unnecessary radiation
at a young age.
“We examined the data to see
if we needed to change policies
or programs to avoid scans,” says
Park. “Upwards of one-quarter
of children who identifed with
headaches had some type of
imaging scan, most commonly a
CT scan.”
When the analytics identifed
emergency rooms as the
setting where scans for this
population are most likely to
occur, WellPoint was able to
adjust its policies and disease
management interventions to
reduce that number. In addition
to using this information in its
own operations, WellPoint also
shares its fndings in conjunction
with groups like the American
Academy of Pediatrics as a way
to support more evidence-based
medicine.
Joanne Sammer is a Brielle, N.J.-based
freelance writer.
Advertiser index
The following is a list of the advertisers in this issue. Although every efort is made
to ensure accuracy, this publication assumes no liability for errors or omissions.
Eisai ………………………………………………………………………………………………………………………………CoverTip
Forest Laboratories Inc ………………………………………………………………………………………………………17-21
Fresenius Medical Care ……………………………………………………………………………………………………….. CV2
Gilead …………………………………………………………………………………………………………………………………..CV4
Glaxo Smithkline Inc ……………………………………………………………………………………………………………. 4-8
Janssen Pharmaceutical Inc ………………………………………………………………………………………………33-40
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