Gain insights and take action

Transcription

1 Data Analytics in Healthcare Gain insights and take action The right stuff. The right data The right analysis The right modeling The right conclusions The right actions

2 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. IDENTIFY high-risk patients for improved population health management and outcomes ENSURE a more successful transition from volume-based to value-based care and payment IMPROVE productivity, increase reimbursements, and accelerate cash flow Watch an online demo Request a personal demo us at Results@NextGen.com Call us at Ambulatory Practice Management Population Health Analytics InSight Reporting Interoperability

3 What s the big deal about big data in healthcare? Find out in this new ebook. The right stuff Data analytics done right is kind of like the Five Rights of Medication Administration but with a data analytics twist Chapter Chapter Chapter Chapter Chapter 1 The right data 2 The right analysis 3 The right modeling 4 The right conclusions 5 The right actions and the right to ask, Are we done yet?

4 CHAPTER ONE he right data and the right to get excited! 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. 63% How will Big Data Help? say Big Data will help track and manage population health more efficiently 62% 60% say Big Data will significantly improve patient care within the military health and VA systems say Big Data will enhance the ability to deliver preventative care

5 $450 billion Last year, McKinsey & Company reported that big data could help save American taxpayers $450 billion in annual healthcare costs. That s big.

6 Right from the top When Dr. Karen DeSalvo took over as head of the Office of the National Coordinator (ONC) she said the ONC s agenda will 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.

7 The underpinnings of EHRs need to be reconfigured to support the purposes of big data. Dr. Karen DeSalvo National Coordinator for HIT

8 he right to panic if you re not prepared. 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 like 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 valuebased care, health data analytics is at the heart of accountable, collaborative care.

9 CHAPTER TWO The right analysis Data Analytics 101: What you need to know.

10 Data for healthcar e analytics comes from diverse sources including but not limited to: 5 extended car e facilities 1 Ambulatory and Inpatient EHRs 6 nursing homes 2 labs/radiology/ ancillary testing disease r egistr ies pharmacies Physical therapy 8 medical examiner

11 9 cor r ectional 13 community health centers patient -generated data public health 15 homecar e organizations agencies 11 behavioral health specialty and hospice car e facilites sub-specialty practices

12 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.

13 Analytics 101: How big is big? 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 [10 24 ]; 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: hp_discover_autonomy_vertica_big_data/ Yottabyte This is our digital universe today Brontobyte This will be our digital universe tomorrow Exabyte 1EB of data is created on the Internet each day million DVDs Terabyte 500TB of new data per day are ingested in Facebook databases 10 6 Megabyte Petabyte The CERN Large Hadron Collider generates 1PB per second 10 9 Gigabyte Zetabyte 1.3 ZB network traffic by 2016

14 ata analytics drives 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

15 CHAPTER THREE he right modeling What 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 (realtime/hours/day not months); emphasis on the relevance of resulting insights; and an emphasis on ease of use.

16 ANALYTICS BIG DATA What s so great about predicitive analytics? 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 s using 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.

17 The analytics triad for healthcare. 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. Descriptive analytics Prescriptive analytics Predictive analytics Data analytics functionality creates models used to predict scenarios and probable trends.

18 CHAPTER FOUR he right conclusions What 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.

19 The patient registry seamlessly aggregates multiple disparate data sources, payer data, preventative, and clinical quality scores to improve clinical and financial outcomes across the practice.

20 Payers just love, Love, LOVE data analytics. 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.

21 CHAPTER FIVE he right actions How 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 performances, 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

22 o more with less Analytics 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 get your toughest questions answered. 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.

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

24 re 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 6 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!)

25 When data resides in multiple disparate silos, payers and providers cannot cost-effectively aggregate, analyze, and assess risk.

26 Yes! or No! for data analytics? 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.

27 Pop Quiz! Go ahead. Surprise yourself with how much you now know about data analytics! 1 Gain insights 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

28 NextGen Healthcare Solutions. We provide HIT solutions, including an award-winning, integrated EHR and 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. To learn more about our proven solutions, including data analytics and system interoperability, contact us at Results@nextgen.com or call Horsham Road, Horsham, PA p: f: nextgen.com Copyright 2014 NextGen Healthcare Information Systems, LLC. All rights reserved. *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. 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. Patent pending. NextGen Ambulatory EHR version 5.8 is ONC-HIT 2014 Edition certified as a complete EHR.