Why Health Care Is Not Like Google Or Amazon: The Challenges Of Fitting Ideal Data Models Into The Real World

Transcription

1 Why Health Care Is Not Like Google Or Amazon: The Challenges Of Fitting Ideal Data Models Into The Real World The 2016 OPEN MINDS California Management Best Practices Institute August 24, :00am 11:15am Sponsored By York Street, Gettysburg, Pennsylvania Phone: info@openminds.com All Rights Reserved. 1

2 Our Mission We are not Amazon. We don t sell and deliver goods. We treat sick people, helping them recover and rebuild their lives, teaching them to thrive despite huge challenges. That s what we do. Everything else is in service to those simple yet exquisitely elusive goals. Could we focus more on our patients, clients, members and less on the structures we build to serve them? We might then develop the most powerful outcome measure of all: healthy, thriving people. Jana Spalding, M.D., Program Coordinator at The Peer Career Academy of the Center for Applied Behavioral Health Policy at Arizona State University, in response to an OPEN MINDS article on consumer sovereignty All Rights Reserved.

3 Data Model A data model organizes data elements and standardizes how the data elements relate to one another. Since data elements document real life people, places and things and the events between them, the data model represents reality, for example a house has many windows or a cat has two eyes. Computers are used for the accounting of these real life things and events and therefore the data model is a necessary standard to ensure exact communication between human beings All Rights Reserved.

4 Health Care Data Complexity Much of the data are in multiple places Data are structured and unstructured Lack of universal definitions The data is complex, not linear Regulatory differences and changes All Rights Reserved.

5 Getting From Here To There Governed Proactive Reactive Undisciplined All Rights Reserved.

6 Data Modeling The complexity of health care data is immense The risk is higher What is the risk of suggesting the wrong genre book to me? Variability is a GOOD thing We do not have reliable predictors We don t understand how to use information to inform decision making and we have to be facile with our problem solving All Rights Reserved.

7 Data Management Is The First Step Over time, the ability for data systems to support business processes in the pursuit of business goals degrades because data quality degrades. This results in more cost but less benefit. Attempting to fix these problems at the operational level will not work. Adding more data and data systems in an effort to fix these problems only makes them worse What will fix these problems is not more technology, more systems or more data but data governance. Data Governance advances the goal of reusable data data that is timelier, more accurate, more complete, more accessible, more useful and less costly. Phases of Data Modeling Dimensional Enterprise Adaptive All Rights Reserved.

8 Adaptive Modeling What We Aspire To This type of modeling is structured but customizable Think of a data mart that contains the data from the source systems You create a process for extraction, transformation, and loading (ETL) to create data stores Stores are specialty environments in which the ETL is designed to answer a specific set of questions. The primary mart contains everything and the store contains what you need to answer the specific questions When new questions arise, or new regulations, requirements, or services are in place, you can create a new store to answer the new questions while not changing the logic in the other existing stores. With the adaptive model, you have access to all of the data you need, and you don t have restrictions associated with a pre-defined list. You have the flexibility to include new data points or make other changes whenever the need arises. Example: The Service Event Mart, versus the Service Incurred Mart All Rights Reserved.

9 The First Step Is To Create Structure All Rights Reserved.

10 Executive Sponsorship This is critical to your program Leadership must make this a system-wide priority Lead by example Assure adequate time and resources Tie in program to mission of organization All Rights Reserved.

11 Data Governance Is Your Goal One of the most common errors we make is allowing operations to sit out these kinds of initiatives The process must be driven by the business Goal is to form a bridge between business operations and technology infrastructure Data governance and stewardship represent a collaborative relationship There are many different types of information technology experts. Do you have the right ones? All Rights Reserved.

12 Data Stewardship Identifying potential enterprise information and data management initiatives Guiding implementation of approved enterprise information and data management initiatives Drafting policies and standards for approval by the data governance board Managing creation of an approved enterprise business glossary Identifying master data domains and approving their attributes Resolving business definitions of data terms and when not possible, bringing conflicts to the attention of the data governance executive board Serving as a forum for discussion and resolution of information and data management challenges All Rights Reserved.

13 Data-Driven Decision Making Data-driven decision management (DDDM) is an approach to business governance that values decisions that can be backed up with data that can be verified. The data-driven approach is gaining popularity within the enterprise as the amount of available data increases in tandem with market pressures All Rights Reserved.

14 Data-Driven Decisions 1. What was the source of your data? 2. How well do the sample data represent the population? 3. Does your data distribution include outliers? How did they affect the results? 4. What assumptions are behind your analysis? Might certain conditions render your assumptions and your model invalid? 5. Why did you decide on that particular analytical approach? What alternatives did you consider? 6. How likely is it that the independent variables are actually causing the changes in the dependent variable? Might other analyses establish causality more clearly? All Rights Reserved.

15 Building A Data Culture 1. Data-oriented mindsets and infrastructure support metrics 2. Data is centralized and organized 3. Policies govern data access 4. Data access is layered 5. Analytics are integrated into tools All Rights Reserved.

16 Earl Lipphardt, MA Chief Residential Officer Integrity House

17 Why Health Care Is Not Like Google Or Amazon: The Challenges Of Fitting Ideal Data Models Into The Real World Earl Lipphardt, MA, Chief Residential Officer, Integrity, Inc. August 24, Open Minds California Management Best Practices Institute

18 Session Description Amazon and Google these organizations have led the way when it comes to leveraging data to gain the competitive market advantage. While we can learn from the data innovations at these organizations, the health care market has its own challenges. In this essential executive session, we will explore the importance of data to a successful organizational strategy, the practical challenges of utilizing data in behavioral health, and examples of practical, real world data management solutions for behavioral health provider organizations. 18

19 Dissecting the Session Description What is data? Is BH talking about the same thing as Google and Amazon? Competitive Market Advantage- How does this apply to a non-profit? The BH Limitations: Practical Challenges for Utilization of Data Real World Solutions for Data Utilization for BH Providers Lessons we can learn are noted throughout the presentation 19

20 What is Data? Most BH providers are not using Big Data, which usually includes data sets with sizes beyond the ability of commonly used software tools to capture, curate, manage, and process data within a tolerable elapsed time. 1 Martin Hilbert identified 5 dimensions of Big Data: Volume, Veracity, Variety, Velocity, and Variability. 2 20

21 How does Amazon and Google process Data, opposed to BH? Amazon, Microsoft, Google, Apple- they all have the Cloud for processing Big Data. 3 They built or contracted for their Clouds - Amazon Learning Machine 4, Azure Stream Analytics 5, Cloud Dataflow 6, McQueen 7. BH providers can utilize these systems, but many use in-house, desktop platforms such as Excel, Access, Filemaker Pro, as well as their own EHR for data processing. BH providers are typically not dealing with hundreds of thousands of records, and top of the line desktop computers have the power to manage their analytical needs. 21

22 Lessons to be learned: Invest in your physical infrastructure: a high speed network connection and a powerful desktop computer. Invest in your programs: Excel 97 and Access 97 was great in 1997, but it is now Recognize your scope: How much data are you truly managing? Millions of records, or under 10,000 clients per year? Never hesitate to call your EHR provider and ask for assistance and advice on how to best manage your data. They can advise on how to collect and extract needed data. 22

23 Who does the actual data management at Amazon, Google, and a BH organization? Corporations Corporations will hire teams of MBAs for processing their Big Data. MBAs can bring the technical expertise of an IT professional with the realworld business skills and knowledge that managers and C-Level executives need to operate their companies. 8 Behavioral Healthcare Providers BH providers know that Shirley from Accounting wants a challenge and is good with spreadsheets, so she gets promoted to System Administrator. Alternatively, the IT guy just takes over the entire project. Sometimes, a C-Level executive takes on the role of System Administrator as a side project and works with some really good student interns. Unfortunately, some BH providers just hire a consultant for 6 12 months. 23

24 Lesson to be learned: Whether or not BH providers are dealing with data or Big Data, the Cloud or Excel, they should look to hire the right people to manage the data. Training, managing, and clear performance goals are just as necessary for your data management staff as it is for any other staff. Initially, data management may not be a full time job, but as a BH provider gets better at it the need will increase. 24

25 Competitive Market Advantage in Corporations and Non-Profits Quick Definition: CMA is a cost or differentiation advantage that sets your BH provider apart from others. Every company must have at least one advantage to successfully compete in the market. 10 All BH organizations must have a CMA- and in today s world the CMA of we have been around a long time and people love us doesn t work anymore! BH providers are not competing for business- BH providers are competing to not go out of business. This does not mean that a BH provider s focus will remain static over time. Data driven expansion, merging, and exploration of new business opportunities will separate BH providers over the next 5 years. 25

26 What are corporations doing with Big Data to improve their CMA? 9 1. Improving Sports Performance 2. Improving Science and Research 3. Optimizing Machine and Device Performance 4. Improving Security and Law Enforcement 5. Financial Trading 6. Improving and Optimizing Cities and Countries 7. Understanding and Targeting Customers 8. Understanding and Optimizing Business Processes 9. Personal Quantification and Performance Optimization 10. Improving Healthcare and Public Health 26

27 How do we use to gain a Competitive Market Advantage? Understanding and Targeting Customers In corporations, predictive data models are used for ad and product placement. For Behavioral Health: 1) Identify where clients are from and locate your service in their neighborhood- great for Outpatient services 2) Track how many have diagnoses you do not treat to understand where to expand services- COD, adult education, MAT 3) Identify your worst performing customers- is this a client base you should be servicing? 4) Identify your worst performing service category- is this a business you should get out of? 27

28 How do we use to gain a Competitive Market Advantage? Understanding and Optimizing Business Processes Corporations utilize stock rotation, employee management, and logistic analysis. For Behavioral Health: 1) Digitizing forms and eliminating copies is a massive source of immediate savings when BH providers begin using EHRs. 2) Time equals money- collecting data on service provision versus time to document versus time to bill can reduce your payment wait time, improve collections, and reduce denials. 3) Adjust staffing patterns to meet your true staffing needs. Do you need a full contingent of intake staff on Friday? Are you paying overtime on Mondays? 4) Once you are collecting data, can you use it to build bridges with your vendors to reduce paper use and staff time? eprescribe, lab testing, and monthly reporting can become quick electronic functions driven by accurate data. 28

29 How do we use to gain a Competitive Market Advantage? Personal Quantification and Performance Optimization Corporations are just beginning to use Big Data in these areas. For once, Behavioral Health is more ahead of the curve: 1) Medication compliance software allows for remote monitoring and tracking of medication usage, as well as internal compliance and prescription management in a residential setting. 2) Substance monitoring technology, from patches to electronic bracelets, allows for tracking not just use of substances but also success rates and a means to identify triggers when someone relapses. 3) Amazing BH robotic technology is being developed for treatment of Autism Spectrum Disorder. 4) Remote diagnostic software used by multiple providers and operated by a single physician as a shared resource allows for more patients to receive care at a lower cost. 29

30 How do we use to gain a Competitive Market Advantage? Improving Healthcare and Public Health Major healthcare and government institutions use Big Data for DNA analysis, epidemic prediction, and research. In BH: 1) Popular wearables (such as an iwatch or Gear Fit) can transmit real-time health data to your EHR/EMR for monitoring purposes. 2) Smartphones and wearables can be GPS configured to set up no fly zones for relapse prevention purposes. 3) Smart devices can remind consumers of meetings, alert clinical staff when sessions are missed, and send appointment alerts. 4) Lessons learned from Big Data will drive BH provider services going forward, such as through more MAT, pain management strategies, or homeless management solutions. Keeping up-to-date on innovations is essential. 30

31 How do we use to gain a Competitive Market Advantage? Improving and Optimizing Cities and Countries Accountable Care Organizations are using Big Data to improve cities and states. Reduction in Emergency Room visits, reduced reincarceration rates, reduction in homeless populations, and reduction in various illness prevalence are examples of data tracked through them by a network of providers. If a BH provider belongs to an ACO, a CMA exists because of the volume of data collected and the information processed (often by a third party). California has a large number of Medicare and Commercial ACOs. 11 (New Jersey has ) If you do not have an EHR, joining an ACO is difficult. 31

32 Behavioral Healthcare Provider Limitations- Practical Challenges for Maximizing Data Utilization Common limitations that are brought up for use of data: No Dedicated Funding Insufficient Staffing Time Consuming and Labor Intensive Lack of Institutional Knowledge Lack of Support from C-Level and Board 32

33 Behavioral Healthcare Provider Limitations- A Practical Solution for Maximizing Data Utilization Establish a Data Management Strategy Starts at the C-Level Incorporate your Data Management Strategic Plan into your existing Strategic Plan What equipment do you need? Can it be donated? What skills do you need to hire? Do staff need to be reassigned? Who is responsible for execution? Do you have the right EHR? What is your expected outcome in terms of client services, outcomes, and revenue management? Incorporating your Data Management Strategic Plan into the existing Strategic Plan will help balance the time commitment factor. 33

34 Bibliography 1. Snijders, C.; Matzat, U.; Reips, U.-D. (2012). "'Big Data': Big gaps of knowledge in the field of Internet". International Journal of Internet Science. 7: Hilbert, Martin. "Big Data for Development: A Review of Promises and Challenges. Development Policy Review.". martinhilbert.net. Retrieved DT&SC 7-3: What is Big Data?. 12 August 2015 via YouTube million/

35 Questions & Discussion 35

36 Chronic Care Management Disability Supports & Long-Term Care Mental Health Services Addiction Treatment Social Services Intellectual & Developmental Disability Supports Child & Family Services Juvenile Justice Corrections Health Care York Street, Gettysburg, Pennsylvania Phone: info@openminds.com