VItreosHealth
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This document provides an overview of VitreosHealth, an advanced analytics company for population health management. It describes VitreosHealth's predictive models for disease cohorts and risk factors that predict patient risks and costs with over 60% accuracy. It also outlines VitreosHealth's suite of care management tools including a State of Health Analysis and strategic process for population health management. VitreosHealth works with providers, payers, and IDNs to improve outcomes and reduce costs through predictive analytics.
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VItreosHealth
- 1. ALL MATERIAL PROPRIETARY AND CONFIDENTIAL. ALL MATERIAL PROPRIETARY AND CONFIDENTIAL. PRODUCT SOLUTION OVERVIEW
- 2. ALL MATERIAL PROPRIETARY AND CONFIDENTIAL. WHO WE ARE Advanced analytics for Population Health through the use of Predictive and Prescriptive Insights the bridge between Hindsight and Foresight – for actionable answers that impact outcomes. Globo Vitreo. Used by Providers – IDNs, ACOs, large medical practice groups, and health systems to manage “at-risk” populations and position for success in value-based care model to improve outcomes and maximize revenues Used by Payers – Self Insured, Medicare & Medicaid HMOs to reduce medical loss ratios (MLR) 2016 Winner of Frost & Sullivan’s New Product Innovation Award for Advanced Population Health Analytics Solutions - North America VitreosHealth Selected as 20 Most Promising Healthcare Analytics Solution Providers of 2016 by Healthcare Tech Outlook 2 0 1 5 : 4 0 0 % G R O W TH A N D D O U B L E D C L I E N T B A S E , 2 0 1 6 : S E C U R E D $ 5 M O F P E F I N AN C I N G
- 3. ALL MATERIAL PROPRIETARY AND CONFIDENTIAL. MARQUEE CUSTOMERS & PARTNERS WE’VE WORKED WITH
- 4. ALL MATERIAL PROPRIETARY AND CONFIDENTIAL. PREDICTIVE MODELS Prioritized lists by disease cohorts with 60% plus predictive accuracy 20+ Disease-specific predictive models – Diabetes, CHF, CHD, COPD, Mental Illness, Pediatric Asthma, etc. Non-Clinical models – Compliance, Access-to-Care, Socioeconomic, Wellbeing, Motivational Index Right Patients – Right Gaps – Right Interventions Predictive Cost Impact Predictive RAPS scores 4
- 5. ALL MATERIAL PROPRIETARY AND CONFIDENTIAL. MULTIDIMENSIONAL RISK MODELS NON-CLINICAL FACTORS UTILIZATION Prior hospitalization PCP/specialist Medications Labs COMPLIANCE Appointments Labs Medications ACCESS-TO- CARE PCP proximity Insurance coverage Wait times SOCIO- ECONOMIC Race Education Income Marital status WELL-BEING HRA’s Well-being index + PHYSICAL HEALTH Diabetes CAD CHF Asthma COPD Osteoporosis Hypertension Pre-diabetes CARDIOLOGY ONCOLOGY PEDIATRIC Asthma Diabetes Obesity STATE OF HEALTH CLINICAL RISK MENTAL HEALTH CLINICAL FACTORS Anxiety Depression Phobias PTSD SMI Addiction STATE OF HEALTH CLINICAL RISK ADULT & PEDIATRIC SED Autism Spectrum Disorder PREDICTIVEPOWER CLAIMS +HOUSEHOLD +EHR+HRA IMPACT
- 6. ALL MATERIAL PROPRIETARY AND CONFIDENTIAL. CARE MANAGEMENT INSIGHTS SUITE 6
- 7. ALL MATERIAL PROPRIETARY AND CONFIDENTIAL. ALL MATERIAL PROPRIETARY AND CONFIDENTIAL. STATE OF HEALTH ANALYSIS (SOHA) QUICK ASSESSMENT OF THE OPPORTUNITIES FOR YOUR POPULATION (3-4 WEEK STUDY)
- 8. ALL MATERIAL PROPRIETARY AND CONFIDENTIAL. THE OLD WAY: ONE-DIMENSIONAL STRATIFICATION (HEALTHCURE, NOT HEALTHCARE) 8 Critical High Utilizers Moderate risk Healthy 50% 25% 15% 10% $52M $26M $15.6M $10.4M $104M $850 10,507 2013 TOTAL 2014 TOTAL $157.2M $1,187 11,038
- 9. ALL MATERIAL PROPRIETARY AND CONFIDENTIAL. Page 9 THE NEW PARADIGM: PRAGMATIC COST/RISK STRATIFICATION
- 10. ALL MATERIAL PROPRIETARY AND CONFIDENTIAL. IDENTIFYING ‘MOVER’ COHORTS In one year ~14 % Population moved from left to right to create additional ~40% Cost.
- 11. ALL MATERIAL PROPRIETARY AND CONFIDENTIAL. Page 11 OUR POPULATION HEALTH MANAGEMENT PROCESS
- 12. ALL MATERIAL PROPRIETARY AND CONFIDENTIAL.ALL MATERIAL PROPRIETARY AND CONFIDENTIAL. THANK YOU 12 Shanthan Ramasahayam We appreciate your partnership President (India Operations) sramasahayam@vitreoshealth.com VitreosHealth.com
Notas del editor
- Hello everyone, my name is Shanthan. Thank you so much for taking this time for this presentation. I’ll start right off with an overview of VitreosHealth and move onto the demo. Let me know if you have any questions along the way.
- So here’s a sample of some of our customers and as you can see there are health plans, large systems, provider groups, ACOs and, hospitals. Even though different they are all on the hook for controlling costs and making savings at the end of the year. And we’ve helped them get there by improving outcomes and controlling costs. And later in my presentation I’ll show you a little bit of what we’ve done for them and what we can do for you. I’ll also touch on outcomes and how we get to those outcomes with these customers. And then we are really proud that Dell and E&Y have chosen us as their predictive population health partner across their customer base. STOP I’m sure you recognize some of these names and you can see there are health plans, large systems, provider groups, ACO ands, hospitals. We have many different types of customers (but one thing that they all have in common is they have all taken risk. Meaning they) that are all on the hook for controlling costs and making savings at the end of the year. And we’ve helped them get there by improving outcomes and controlling costs. Our customers range from healthcare systems like cone heath in north Carolina, to Christus Trinity Mother Francis in Texas. We have large medical groups like USMD, patient physician network and payers like global health and EasyChoice which is under WellCare health plans. And two of our key strategic partners are dell healthcare and earnst and young who have chosen us as their predictive population health partner across their customer base.
- So something I like to start out with is what makes us different- and that is how we approach the data sets. So many companies that you come across today who say they do predictive ananytics are commonly focused on claims and sometimes one other data set. Our models are built to include both clinical and non-clinical factors. And those clinical factors include both physical and mental health and then non-clinical like socio-economic status or access to care. So difference #1 we have the ability to take in all of these meaningful data sets and difference #2 we use your data to customize our models. Both of these make our accuracy rate much high than our competitors. We’ve seen that every customer and their data capabilities are different so we can start with whatever data you have and build from there. As we are able to add additional information our accuracy increases even more and this slide shows how much of an impact this can make. STOP The value in our service starts with ability to include meaningful data sets into our models. We use a strong mix of Clinical and Non-Clinical information to strengthen the predictive power of our Insights. Slides – This is who we are, What we do and how we do it…. One or two slides about state of health analysis…. If you have Claims data only we can provide much greater statistically relevant data vs. the competition because of our approach. Using historical data, regression testing and looping in the socioeconomic data our accuracy rate is second to none. As we are able to add additional information our accuracy increases and this slide shows how much of an impact this can make. As shared risk programs become more of the norm our clients are partnered with someone that has already built this infrastructure. You don’t have to use a vendor with limited capabilities when you have limited data sets. Plan for the future by using a solution built for the future.
- Instead of using the Pyramid we use a multi-dimensional model and plot the population on this 2x2 grid. We say the state of health of a member is not just based on historical cost but also based on clinical risk. Now looking at.. critical, we know who these patients are, they are the patients with a high risk and high cost. Bellow that is the high utilizers, those are the ones that historically have been high cost but have a low clinical risk. Many of these patients end up in the emergency room, or have a substance abuse problem. And the root cause of these costs may not even be clinical, it could be socioeconomic. But what are less known are the other two categories. So the hidden category- are the patients that are at a high clinical risk but they aren’t on your radar because they’ve had low cost. But it’s just a matter of time until these patients are gong to have a high cost event, move to the critical category and cost you a ton of money. And then the healthy/unknown category these patients may have huge gaps in care, they may have a high socio-economic risk, but you don’t know because you don’t have any information on them, and if you don’t have care managers actively reaching out to them and getting that information they may soon move to the critical or high utilizers category. So you need to know who they are before they make this move. STOP The problem with traditional charts is they are one-dimensional. So the starting point for our analysis is multi-dimensional where we put cost and risk together and stratify the population. If advanced audience can add this: {On the y-axis is a predicted risk score, that represents the probability that the patient is going to have a high cost intervention due to a complication with one or more current diseases. The x-axis is a historical looking measure of utilization.} And what this does is categorizes patients into the four buckets you see here. The top right are high cost high risk, we call those the critical patients. Bellow that is the high utilizers, those are the ones that historically have been high cost but have a low clinical risk. Many of these patients end up in the emergency room, or have a substance abuse problem. And the root cause of these costs may not even be clinical. It could be socioeconomic, maybe they can’t afford co-pays or afford a taxi to appointments. These are gonna be the patients you may have already identified because of their high spend and the ones that may already be in your care management programs. But what are less know are the other two categories, so the hidden category is the patients that are clinically at a high risk but historically have been low cost. What this means is these patients are high risk because one or more of their diseases is out of control. Maybe their A1C is high, maybe their BMI is high, they have multiple comorbidities, their cholesterol levels are high, they haven’t seen a doctor in over two years. All of this could contribute to why they are at a high risk, but you’ve just been lucky that they have not had a high cost event. So we call them the hidden opportunity, the ticking time bombs, rising risk population. This group is very important because if you don’t take care of them it’s only a matter of time before they hit the emergency room and then it will be too late because that CAD patient just had a stroke or that diabetic patient just had renal failure. And they are now going to move to the right and become critical. You have to then manage renal failure for the rest of the patient’s life and they will continue to be high cost. Similarly, the healthy and unknown category is interesting because a lot of patients there are healthy, they don’t have many chronic conditions and many of them are young. But some of them might end up moving to the right because of a non-clinical factor, like socioeconomic status or due to mental health issues and s become high cost, so you need to know who they are before they make this move. And this category also includes unknown, so patients that have just joined your plan or network and you have no history. No clinical history, no claims history so they are unknown. At most you may do a risk assessment on them and you may get a little bit of information. But we find that many of these patients are in fact not healthy and very quickly they end up moving, and that’s why it’s so important to know who those unknowns are and get whatever information you can on them so that they can be stratified and categorized appropriately.
- So we took that Medicare ACO population and used our 2x2 grid to stratify the patients for years 1 and 2. We then did a mover analysis to see where the patients were moving during those years... And what we found was 508 members moved from the healthy category to the high utilizers category and accounted for $18.7M in new spend and 754 members moved from the hidden category to the critical category and accounted for $28.5M in new spend. SO the original theory that the $53.2M in new spend was attributed to new members joining and costly members becomomg more costly was wrong. The majority of the spend was actually from current members moving to the left becoming more costly. So the question becomes what if this ACO focused all of their time and resources on the people on the left so that they didn’t move to the right? This is millions of dollars they could have saved by addressing the right patients that were already in their population. But they were spending all of their time on the critical population.
- We aren’t here to rip and replace investments you have already made. We want to help maximize what you are already doing with our closed loop analytics piece and then if you don’t have a care management application then we can provide that as well. We will tell you who the risky patients are, Why they are risky, What you can do about it and then tell you how your population and programs are doing. So we are really here to help you be successful and be that partner in your move to value based care. Any questions on that? So now I’m going to show you a brief overview of demo but keep in mind we are going to be doing this for you as a service. We don’t sell an application we sell insights into your population. STOP Because we are managing this population there are many different thing we can look at. We aren’t trying to displace any other solutions or programs that you currently have, but if we can add value we will definitely do that. So at the end of the day we are a closed loop analytics process and we can help you wherever you may be in the move to value based care. We aren’t here to rip and replace investments you have already made. We want to help maximize what you are already doing with our closed loop analytics piece and if you don’t have a care management application then we can provide that as well. We will tell you who the risky patients are, Why they are risky, What you can do about it and then on a monthly basis tell you how your population is doing. We can also work with your current solutions to deliver complete insights as a service. We can add to your work flow applications Our closed loop process has either 3-5 steps depending on what you are currently doing. We can do the entire 5 step loop including the analytics, soha, care management platform and performance results or we can just be your pure ananlytics engine and imbed ourselves in current workflow applications. As I go through the demo there are 5 steps I’m going to cover, and these are the 5 steps in what we call the Closed Loop Process for Population Health Management. o Step 1 is to analyze my population. So let’s stratify and segment these patients into groups. o Step 2 show me the risky patients. This is who we predict is going to move from a low to a high risk. o Step 3 show me why they are risky. Show me the risk factors, show me the gaps in care- show me anything I need to know about these patients. o Step 4 now with all of this information tell me what I need to do, do I need to bring these patients in, do I need to close gaps. And who's going to do it? Do I need to do everything or get the help of a social worker? In other words, help me put a program together. o Step 5 measure the outcomes and tell me if what we’re doing is working or not working. And don't wait till the end of the year, tell me every month, every quarter, so if something isn’t working I can fix it. And doing this we have a closed-loop process that will continually help us improve and ultimately bend the cost curve.