Gain insight and take action

Data Analytics in Healthcare

1

2

3

4

5

The right data

The right analysis

The right modeling

The right conclusions

The right actions

The right stuff.

NextGen Healthcare puts business intelligence and analytics at your fingertips.

Harness, aggregate, analyze, and interpret patient data directly from our integrated NextGen® Ambulatory EHR and NextGen® Practice Management solutions.

IDENTIFYhigh-risk patients for improved

population health management

and outcomes

ENSUREa more successful transition from

volume-based to value-based

care and payment

IMPROVEproductivity, increase

reimbursements, and accelerate

cash flow

Watch an online demo | Request a personal demo | Email us at Results@NextGen.com | Call us at 855-510-6398

Ambulatory PracticeManagement

AnalyticsPopulationHealth

InteroperabilityInSight ReportingTM

The right stuffData analytics done right is kind of like the Five Rights of Medication Administration… but with a data analytics twist.

Chapter 1 The right data

Chapter 2 The right analysis

Chapter 3 The right modeling

Chapter 4 The right conclusions

Chapter 5 The right actions

…and the right to ask, “Are we done yet?”

What’s the big deal about big data in healthcare? Find out in this new eBook.

A new study commissioned by EMC

asked federal agencies how big data

can help them. Among the results

published recently:

The healthcare industry is chomping at

the bit for data analytics. Because the

innovative answers needed to improve

patient experiences and the health of

populations, while simultaneously

reducing costs, comes from insights,

trends, and clues hiding in big data.

The right dataand the right to get excited!

How will Big Data Help?

say Big Data will help track and manage population health more efficiently

say Big Data will significantly improve patient care within the military health and VA systems

say Big Data will enhance the ability to deliver preventive care

63%

62%

60%

CHAPTER

ONE

$450 billionLast year, McKinsey & Company reported that big data could help save

American taxpayers $450 billion in annual healthcare costs. That’s big.

When Dr. Karen DeSalvo took over as

head of the Office of the National

Coordinator (ONC) she said that on the

ONC’s agenda will be a plan to launch a

new discussion about interoperability, big

data use, and patient-generated data, plus

the security required to support all three.

High-functioning health information

technology (HIT) analytics can handle

different data formats originating

from scores of different sources. Which is why “big data” and interoperability are two health IT concepts you can’t ignore.

Right from the top

“The underpinnings of EHRs need to be reconfigured to support the purposes of big data.”Dr. Karen DeSalvoNational Coordinator for HIT

Please don’t. There’s no reason to. Except if

you’re not preparing properly for big data.

Regardless of your healthcare sector, your

income will be tied to your performance,

which will be evaluated with data analytics

and quality reporting.

The Meaningful Use EHR incentive

program, quality-based reimbursement

models such as Patient Centered Medical

Homes (PCMHs) and Accountable Care

Organizations (ACOs), and the Physician

Quality Reporting System (PQRS) all

rely on reporting and healthcare data

analytics output.

With the transformation to value-based care, health data analytics is at the heart of accountable, collaborative care.

The right to panicif you’re not prepared.

The right analysisData Analytics 101: What you need to know.

CHAPTER

TWO

Ambulatory and Inpatient EHRs1

Physical therapy4

pharmacies3

labs/radiology/ ancillary testing2

extended care facilities5

nursing homes6

medical examiner8

Data for healthcare analytics comes from diverse sources including but not limited to:

7disease registr ies

hospice care facilites12

behavioral health11

community health centers13

patient -generated data14homecare organizations15

16specialty and sub-specialty practices

10public health

agencies

correctional9

New big data sources beyond the EHR may include genomics,

social determinants of health, and combining data from multiple body systems, to name a few.

Care for a brontobyte?Ten to the power of 27 [1+27 zeroes] is

a brontobyte. It’s where big data is

headed. Today, big data is happening on

the planet at the yottabyte level [1024];

one yottabyte = 250 trillion DVDs.

Today’s data scientist uses Yottabytes to

describe how much government data the

NSA or FBI have on people altogether.

In the near future, Brontobyte will be

the measurement to describe the type of

sensor data that will be generated from

the IoT (Internet of Things).

Resource: http://www.theregister.co.uk/2012/12/04/hp_discover_autonomy_vertica_big_data/

Analytics 101: How big is big?

BrontobyteThis will be our digital universe tomorrow...

1027

1024

YottabyteThis is our digital universe today

1018

Exabyte1EB of data is created on the Internet each day - 250 million DVDs

1015

PetabyteThe CERN Large Hadron Collider generates 1PB per second

1012

Terabyte500TB of new data per day are ingested in Facebook databases 109

Gigabyte

106

Megabyte

1021

Zetabyte1.3 ZB network traffic by 2016

Data analyticsdrives population health.

Integrated HIT with data analytics functionality. That’s your goal.

You’ll need data analytics functionality in

your HIT system to implement population

health properly… and profitably. Same

with coordinated care. Ditto for new

reimbursement models. Ditto to:

• track and manage population health

more efficiently

• enhance preventive care

• reduce per capita cost of patient care

• enhance progress in diagnostics and

medical research

• understand retail healthcare trends

• negotiate properly with payers

The right modelingWhat is predictive analytics?

It’s when you extract information from existing data sets in order to determine patterns and predict potential future outcomes and trends. Predictive analytics will not tell you

what will happen in the future. It helps you

forecast what might happen and includes

what-if scenarios and risk assessments.

In Gartner’s IT Glossary, among the

characteristics of predictive analytics most

important to healthcare reform is rapid

analysis of massive quantities of data (real-

time/hours/day… not months); emphasis

on the relevance of resulting insights; and

an emphasis on ease of use.

CHAPTER

THREE

We just covered predictive analytics. How about descriptive and prescriptive analytics?

Descriptive analytics is the simplest

form of analytics. It’s the easiest to do

because it uses data to describe what

happened to patients in the past. It’s the

most common form of data analytics

being used in healthcare today.

Predictive analytics is in the middle of

this descriptive, predictive, and prescriptive

analytics triad. It has the potential to

improve healthcare delivery by analyzing

all aggregated current and historical

patient data to identify high-risk patients

and opportunities for intervention

and treatment.

Prescriptive analytics is the most

advanced of these three types of data

analytics. In healthcare, prescriptive

analytics is what’s growing clinical decision

support platforms. It goes beyond

descriptive and predictive analytics by

recommending one or more courses of

action – and including the likely outcome

of each decision or action.

What’s so great about predictive analytics?

BIG

DATA

AN

ALY

TICS

Predictive analytics can significantly increase the potential

to improve care and population health. By analyzing all

aggregated current and historical patient data, providers

can identify high-risk patients and opportunities for

intervention and treatment. Providers assess risk level based

on a particular set of health conditions and clinical decision

making to develop an effective care plan.

The goal of predictive modeling is to identify and actively

manage high-risk patients, intervene before they become

critical, and reduce or eliminate unnecessary ED visits and

hospital admissions. Each of these steps can drive down

healthcare costs, improve clinical outcomes for patients,

and promote a healthier patient panel.

Data analytics functionality creates models used to predict scenarios and probable trends.

The analytics triad for healthcare.

Descriptive analytics

Predictive analytics

Prescriptive analytics

The right conclusionsWhat’s the secret?

It’s not a secret. It’s the patient registry.

A patient registry (also called a central data

repository or master patient index “MPI”)

is a centralized database that aggregates

patient data from multiple healthcare

providers and organizations (disparate

data sets – see page 23.

Providers and authorized users can

identify and query patient groups through

myriad segmentations and relational

database functions. For example, treatment

queries can target patients by specific

diagnosis or conditions (e.g., a risk factor)

that predispose them for a health-related

event. These patient groups are called

patient cohorts.

CHAPTER

FOUR

The patient registry seamlessly aggregates multiple disparate data sources, payer data, preventive, and

clinical quality scores to improve clinical and financial outcomes

across the practice.

And why shouldn’t they? Public and private payers are using

their analytics expertise to mine data for the answers they need to

build new pay for performance provider reimbursement models.

Payers want to know everything. They monitor, track, measure,

manage, and report healthcare services, workflows, and outcomes

using state-of-the-art data analytics. And they know a healthier

population means lower costs for both payers and patients.

Payers just love, Love, LOVE data analytics.

The right actionsHow do answers from data analytics create action?Use results from thoughtful healthcare data analytics programs to help create innovative approaches that enable you to continually improve your performance, your other providers’ performance, or the performance of your practice or facility.

• Evaluate provider performance in managing disease(s)

• Adjust treatment plans in accordance with evidence-based guidelines

• Better understand and treat diseases that influence multiple body systems

• Identify a patient’s risk level through a hybrid data assessment – clinical, social, cultural

• Develop treatment programs that align with recommended clinical guidelines

• Engage patients in a meaningful care transition program to ensure continuity of care

• Create care coordination protocols driven by evidence-based medicine

and personalized care

• Cultivate better transition of care to help reduce readmissions and decrease costs

• Evaluate patient outcome trends to negotiate fair reimbursement for patient cohorts

• Rank yourself against your peers and national healthcare benchmarks; know where

you stand, be a savvy healthcare reform provider

CHAPTER

FIVE

Do more with lessAnalytics makes it happen

Like we said at the beginning of this eBook: You want answers. But you’re searching for them in a healthcare setting that demands doing more with less, every day.

Only sophisticated analytics can create

the insights and data patterns you need

to create new actions that’ll answer

your toughest questions. It’s the way to

intelligently leverage your data.

Payers can figure out which patients are

most likely to generate the highest costs.

Providers will discover which of their

patients aren’t taking their meds. Hospital

executives can better understand the

probabilities of relapse and readmission.

That’s why more and more healthcare

professionals are interested in using big

data and analytics to prevent problems

before they occur in healthy patients.

“Advanced analytics [in healthcare] allows you to be much more sophisticated in where you intervene and with what.”Dr. Bob NeaseChief Scientist, Express Scripts

Are we done yet?Almost. But we need to mention interoperability.Without interoperability, big data and data analytics are useless.

HIT systems must achieve high degrees of

interoperability and data sharing for big

data to impact real-time clinical decision

making across the nation. Disparate

systems need to work together. Seamlessly.

We’re not there yet, but like Dr. DeSalvo’s

quote on page 7 of this eBook, the use of

big data across interoperable HIT systems

is the essence of ONC’s new 10-year plan.

(Told you it was quick!)

When data resides in multiple disparate silos,

payers and providers cannot cost-effectively aggregate,

analyze, and assess risk.

Hint: It’s a trick question.

Here’s a not-so-secret secret: Lots of

providers vote “yes” for data analytics and

“no” for wanting to do it. They want the

value; the new insights and answers. But

they don’t want the deep data dive for fear

of not understanding what to do or how to

do it and for wasting a lot of time trying to

figure it out.

That’s where your HIT vendor can help.

Don’t try to figure this out on your own.

You’re a medical professional, not a

data scientist.

Work with a committed, long-term HIT

partner. They’ll have a better understanding

of how to integrate and leverage data

analytics into your daily EHR and practice

management workflows.

And remember: A data analytics initiative

without an interoperability strategy is

like writing a book that no one can read.

Ask your vendor to share their long-term

interoperability road map.

“Yes!” or “No!” for data analytics?

1 Gain insight and take __________________.

2 The healthcare industry is chomping at the bit for__________________ __________________.

3 Dr. Karen DeSalvo said the underpinnings of EHRs need to be reconfigured to support the purposes of __________ __________.

4 A brontobyte is ten to the power of __________________.

5 Our digital universe today is happening at the __________________ level. One of these = 250 trillion DVDs.

6 A central repository or master patient index is called a __________________ __________________.

7 Patient groups are called __________________.

8 Predictive analytics increases the potential to __________________ __________________.

9 HIT systems must achieve high degrees of __________________.

10 Data analytics without interoperability is like ____________________________________________________.

*Answer key next page

Pop Quiz!Go ahead. Surprise yourself with how much you now know about data analytics!

Copyright © 2016 QSI Management, LLC. All Rights Reserved. NextGen is a registered trademark of QSI Management, LLC, an affiliate of NextGen Healthcare Information Systems, LLC. All other names and marks are the property of their respective owners.

* NextGen Ambulatory EHR version 5.8.2 is 2014 Edition compliant and has been certified by ICSA Labs in accordance with applicable certification criteria adopted by the Secretary of Health and Human Services. This certification does not represent any endorsement by the U.S. Department of Health and Human Services. ONC CHPL Number: 140204R01. Read more about our certifications at https://nextgen.com/Certifications

795 Horsham Road, Horsham, PA 19044

p: 215.657.7010 | f: 215.657.7011 | nextgen.com

NextGen Healthcare Solutions.We provide HIT solutions, including an award-winning, ONC HIT Certified* Ambulatory EHR, integrated with a Practice Management system along with Revenue Cycle Management (RCM) expertise and interoperability solutions to approximately 85,000 physicians, specialists, and dentists spanning in excess of 4,400 group practices and more than 300 hospitals across the nation. Our providers have attested for more than a half billion dollars (and growing) in Meaningful Use incentive revenue.

*Answer Key: 1) action; 2) data analytics; 3) big data; 4) 27; 5) yottabyte;

6) patient registry; 7) cohorts; 8) improve care; 9) interoperability;

10) writing a book that no one can read.

To learn more about our proven solutions, including

data analytics and system interoperability, contact us at

Results@nextgen.com or call 855-510-6398.

EDU35 - 5/16