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The Dangers of Data Shopping: The Mad Scramble for Information

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The phrase “data shopping” should conjure up images of crowded stores, out-of-stock items, long lines, and cranky sales clerks. This scenario is similar to that of your data users and analysts when they are trying to operate without a strict data management policy and without a unified data platform. Many healthcare institutions attempt to operate with data stored in multiple locations, accessible in different ways. Too much time is spent by users looking for the one source of truth and too much time is spent by analysts attempting to gather data to fulfill user requests. Not enough time is spent analyzing data and generating improvements. Data shopping is dangerous and organizations caught up in the spree need to consider a cleanup on aisle 9 (that’s analytic-speak for “consider an enterprise data warehouse”)

Publié dans : Santé
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The Dangers of Data Shopping: The Mad Scramble for Information

  1. 1. The Dangers of Data Shopping: The Mad Scramble for Information – Steve Barlow
  2. 2. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Data Shopping To understand why data shopping keeps many healthcare organizations from maximizing the value of their data through analytics, it helps to think about your shopping options in the real, offline world.
  3. 3. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Data Shopping One option is a strip mall with many independent stores. If I want to purchase a pair of jeans, some boots, a water storage system, and a backpack for a hike on Saturday, I will likely need to visit four separate stores. The selection may be limited, so I may have to accept what I can get.
  4. 4. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Data Shopping The second option is a large warehouse club where everything is under one roof, often with ample choices, allowing me to get exactly what I need in a single trip. Since all of the merchandise has been vetted by a single buying group, there is confidence in the quality of the warehouse club and the products it sells.
  5. 5. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Data Shopping Many organizations have their data stored like merchandise in the strip mall, in siloed, independent repositories throughout the ecosystem. Those repositories may contain clinical, financial, patient satisfaction, customer relationship management, and many other types of data.
  6. 6. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Data Shopping This lack of centralization often leads to a phenomenon known as “data shopping.” Essentially, data shopping is the practice of analysts and knowledge workers searching throughout the ecosystem to obtain the information they need to answer a pressing business question.
  7. 7. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Data Shopping Ideally, analysts would access a single source of truth, such as a Late-Binding™ Enterprise Data Warehouse (EDW), to mine the data their analytics require. Absent that, however, being the resourceful types they are, they will obtain it however they can. This piecemeal approach to data analysis can have challenging downstream consequences on the efficacy and consistency of the analytics.
  8. 8. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. The Dangers of Enabling Data Shopping There are dangers that result from a data shopping approach. One of the most significant is that scattered data results in no single source of the truth. The data quality may be high, low, or somewhere in between. Additionally, the definitions of the data from the different sources often do not agree and are inconsistent.
  9. 9. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. The Dangers of Enabling Data Shopping Just as important, the data required for a particular analysis may exist in both high and low quality in different repositories. As a result, the same analysis can produce different results based on where the data was sourced. If the data used isn’t clean and reliable, the organization risks making poorly-informed decisions.
  10. 10. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. The Dangers of Enabling Data Shopping Here’s a real-life example. Health Catalyst was working with a healthcare provider that was focused on reducing the rate of elective labor inductions before the baby achieved a gestational age of 39 weeks. Clinical evidence has established that the risks and complications related to induction of labor are reduced significantly after the 39- week mark.
  11. 11. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. The Dangers of Enabling Data Shopping A key to driving this clinical quality improvement was knowing when the 39 weeks had passed. That was difficult to determine because the data was captured in 14 different locations and 10 different formats. Before we could establish the baseline rate of elective labor induction before 39 weeks, we had to establish a single source of truth in the EDW regarding when the baby reached 39 weeks.
  12. 12. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. The Dangers of Enabling Data Shopping A second, related danger to having poor data quality is it becomes difficult to get clinicians onboard with clinical quality improvement programs. If they don’t trust the data, they won’t trust the conclusions.
  13. 13. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. The Dangers of Enabling Data Shopping This issue became evident when Health Catalyst worked with another provider on a population health management (PHM) program for diabetes care. This was the first experience with PHM for the physicians who managed this population, so they were wary about it.
  14. 14. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. The Dangers of Enabling Data Shopping It turned out they were right to be wary. When we showed them the analytics, they immediately pointed out flaws, such as a patient who was not a diabetic or a particular patient who had not been in for a year. We enlisted their help to clean up the data and the program moved forward.
  15. 15. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. The Dangers of Enabling Data Shopping When it came time to begin a similar program for patients with asthma, we didn’t bring data right away; we started by asking them questions. But they told us we needed to show them the data, because they now had a level of trust in it they hadn’t had before.
  16. 16. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. The Dangers of Enabling Data Shopping Knowledge workers, many with advanced degrees in statistical analysis, may spend the bulk of their time on activities they were not trained in, such as hunting for and gathering data, scrubbing it, and making it useful for analysis. In the process, they become producers of data rather than consumers of it. By the time they’re done, there’s little time left for meaningful analysis.
  17. 17. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Warning Signs of Data Shopping So, how do you know if your organization is in a data shopping mode? There are obvious warning signs: There are multiple data repositories where a knowledge worker can go to get answers to similar questions. This is an indicator that the same data elements are being captured, probably in different ways, within different areas.
  18. 18. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Warning Signs of Data Shopping So, how do you know if your organization is in a data shopping mode? There are obvious warning signs: There is a growing number of decentralized analysts or information consumers within the organization. While there will always be a need for analytics within specific departments to support operations, the organization should have a core group who perform most of the analytics across the enterprise.
  19. 19. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Warning Signs of Data Shopping So, how do you know if your organization is in a data shopping mode? There are obvious warning signs: The organization worked hard to hire brilliant analysts with tremendous training and experience, but those analysts are spending most of their time hunting and gathering data and making it consumable rather than working their magic.
  20. 20. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Warning Signs of Data Shopping According to attendees of the Healthcare Analytics Summit, 40% of data analysts spend 80% of their time gathering data, while 39% spend 60% of their time gathering data .
  21. 21. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Organic Growth of Analytics If data shopping causes so many problems, why does it occur? It results primarily from building new, disparate systems to capture data sets without having a data governance plan in place. Since information needs within a healthcare organization surfaces organically, analysts or knowledge workers may attempt to answer specific questions using whatever data they can find.
  22. 22. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Organic Growth of Analytics The problem is, in the quest to answer the immediate needs, little thought is given to the structure of the entire data ecosystem. Data isn’t often thought of and treated as a strategic asset that needs to be managed carefully, like human or financial capital. Soon there are little pockets of data everywhere, and those who want to use it must go shopping.
  23. 23. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Organic Growth of Analytics Compounding this process is the way many chief information officers view their jobs vis-a-vis data. Since the beginning of the computer age, the bulk of CIO budgets focused on capturing, storing, and securing data. A much smaller percentage is dedicated to how the data will actually be used.
  24. 24. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Organic Growth of Analytics EDW pioneer Ralph Kimball says enlightened CIOs should allocate as much of their budgets to getting data out of their systems as they are to getting it in. Getting there, however, will require healthcare organizations to move from siloed data systems in favor of a centralized approach that incorporates comprehensive data governance.
  25. 25. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Solving the Data Shopping Dilemma Some organizations are just getting into analytics and don’t yet have established patterns. Others may be well into their analytics efforts and now realize they have a data shopping issue. Either way, the advice to avoid/solve it is the same. It begins with having a plan that starts with the end in mind.
  26. 26. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Solving the Data Shopping Dilemma Two key points to consider: 1. Creating a single source of truth (such as an EDW) where everyone in the organization can go to obtain data that is clean, accurate and consistent. 2. Devoting as much time and as many resources into pulling out the data as is spent on storing and securing it.
  27. 27. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Solving the Data Shopping Dilemma This is all part of treating data as a strategic asset rather than simply capturing it and locking it away. Establishing a single source of truth is the first priority. It will not only save analysts time in finding and making the data consumable; it will also ensure that all knowledge workers are starting from the same point and using the same data.
  28. 28. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Solving the Data Shopping Dilemma Once the plan is in place and a single source of truth has been established, the next step is to deploy a data governance structure that focuses on the three pillars of data governance: 1. Data Quality 2. Data utilization and access 3. Data literacy
  29. 29. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Solving the Data Shopping Dilemma For organizations that are already in data shopping mode, it’s time to invoke the first law of holes: when you find yourself in one, stop digging! Acknowledge the situation and start moving toward establishing a single source of truth and a data governance structure, even if that means stopping or reducing work on analytics for a little while.
  30. 30. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Don’t Head to the Mall Data shopping occurs when there are no better alternatives. Rather than forcing knowledge workers to search for data throughout the enterprise like holiday shoppers going from strip mall to strip mall in search of the perfect gift, bring it all together.
  31. 31. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Don’t Head to the Mall Build a centralized, single source of truth, and create a centralized core set of data consumers. Make sure analysts are spending the bulk of their time consuming data and developing insights. Make getting data out of the systems is as easy as getting data into those systems. Establish a data-driven culture with a data governance program focusing on the three pillars.
  32. 32. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. More about this topic Master Data Management in Healthcare: 3 Approaches Brian Eliason, Jason Burke and Pete Hess Problems With Relying on EHR Analytics For Your ACO: You Need a True Data Warehouse Dr. David Burton – Senior Vice President, future product strategy Clinical Data Management: 3 Improvement Strategies Jane Felmlee 7 Essential Practices for Data Governance in Healthcare Dale Sanders – Executive Vice President, Software The 3 Challenges of Translational and Clinical Research Data Management and a Strategy to Succeed – Eric Just and Sean Whitaker Link to original article for a more in-depth discussion. The Dangers of Data Shopping: The Mad Scramble for Information
  33. 33. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. For more information:
  34. 34. © 2014 Health Catalyst www.healthcatalyst.com Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Steve Barlow is a co-founder of Health Catalyst and Executive Vice President of Client Operations. He is a founding member and former chair of the Healthcare Data Warehousing Association. He began his career in healthcare over 25 years ago at Intermountain Healthcare where he was a member of the team who developed the analytical capabilities that helped make Intermountain a nationally recognized leader in outcomes improvements and cost optimization. Mr. Barlow earned a BS in Health Promotion and Education from the University of Utah. Other Clinical Quality Improvement Resources Click to read additional information at www.healthcatalyst.com

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