eBook - Data Analytics in Healthcare

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Gain insights from data analytics and take action! Learn why everyone is making a big deal about big data in healthcare and how data analytics creates action.

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eBook - Data Analytics in Healthcare

  1. 1. Gain insights 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.
  2. 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 | Email us at Results@NextGen.com | Call us at 855-510-6398 Ambulatory Practice Management AnalyticsPopulation Health InteroperabilityInSight Reporting
  3. 3. The right stuff Data 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.
  4. 4. 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 preventative care 63% 62% 60% CHAPTER ONE
  5. 5. $450 billionLast year, McKinsey Company reported that big data could help save American taxpayers $450 billion in annual healthcare costs. That’s big.
  6. 6. 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. Right from the top
  7. 7. “The underpinnings of EHRs need to be reconfigured to support the purposes of big data. ” Dr. Karen DeSalvo National Coordinator for HIT
  8. 8. 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 value- based care, health data analytics is at the heart of accountable, collaborative care. The right to panicif you’re not prepared.
  9. 9. The right analysisData Analytics 101: What you need to know. CHAPTER TWO
  10. 10. Ambulatory and Inpatient EHRs 1 Physical therapy4 pharmacies3 labs/radiology/ ancillary testing 2 extended care facilities 5 nursing homes6 medical examiner 8 Data for healthcare analytics comes from diverse sources including but not limited to: 7disease registr ies
  11. 11. hospice care facilites 12 behavioral health11 community health centers 13 patient -generated data14 homecare organizations 15 16specialty and sub-specialty practices 10 public health agencies correctional9
  12. 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. 13. 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? Brontobyte This will be our digital universe tomorrow... 1027 1024 Yottabyte This is our digital universe today 1018 Exabyte 1EB of data is created on the Internet each day - 250 million DVDs 1015 Petabyte The CERN Large Hadron Collider generates 1PB per second 1012 Terabyte 500TB of new data per day are ingested in Facebook databases 109 Gigabyte 106 Megabyte 1021 Zetabyte 1.3 ZB network traffic by 2016
  14. 14. 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
  15. 15. 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
  16. 16. 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. What’s so great about predicitive analytics? BIGDATA ANALYTICS
  17. 17. 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
  18. 18. 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
  19. 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. 20. 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.
  21. 21. 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’ 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 CHAPTER FIVE
  22. 22. 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 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. 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. 24. 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 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. 25. When data resides in multiple disparate silos, payers and providers cannot cost-effectively aggregate, analyze, and assess risk.
  26. 26. 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?
  27. 27. 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 Pop Quiz! Go ahead. Surprise yourself with how much you now know about data analytics!
  28. 28. Copyright © 2014 NextGen Healthcare Information Systems, 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. Patent pending. NextGen® Ambulatory EHR version 5.8 is ONC-HIT 2014 Edition certified as a complete EHR. 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, 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. *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.

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