I Already Have a Data Warehouse. Can I Use Health Catalyst Applications With It?

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By Health Catalyst I Already Have a Data Warehouse. Can I Use Health Catalyst Applications With It?

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Comparing Data Warehouse Options You’ve already made an investment in an early-binding data warehouse. Can you still take advantage of Health Catalyst applications and technology? Let’s see some options.

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Comparing Data Warehouse Options Custom Apps How it works: Information from the existing data warehouse is fed into new, third-party applications allowing health system to gain functionality and insight from the data already collected in a data warehouse. When needed, data from existing schema is adapted to work on new schema. Disruptions associated with initial implementation of this solution are minimal as the existing early-binding data warehouse continues to perform its job as usual and new apps are merely layered on top. Long term costs may be higher. Build applications with additional functionality on top of existing data warehouse Short-term resource impact Long-term resource impact Time to Value Pros: Retains existing early-binding data warehouse while increasing functionality through the addition of advanced analytics apps Cons: Custom solutions tend to be difficult and costly to maintain and may not perform as desired when advanced applications run on a platform they weren’t designed for or if the data required isn’t available; developing new applications on an older platform may increase time-to-delivery for applications that require newer data sources

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Comparing Data Warehouse Options Feeder Data Warehouse How it works: To obtain broad-spectrum, advanced analytics functionality, a Late-Binding™ data warehouse platform is added, but remains dependent upon data fed to it from the existing early-binding data warehouse. If desired, existing data warehouse may continue to perform certain key, custom functions without the migration of data to new platform. However, full advantage of new platform can’t be realized if existing data warehouse or data heritage is outdated. Use existing early-binding data warehouse as source system for new data warehouse platform Short-term resource impact Long-term resource impact Time to Value Pros: Adds enhanced analytics functionality to existing data warehouse, which may be beneficial when custom functions or custom-developed EMRs are a consideration Cons: New tech advantages and platform not fully realized due to dependency upon existing early-binding data warehouse, which may also result in conflicts/incompatibility in data heritage, governance and lineage; employable only in environments with one existing data warehouse

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Comparing Data Warehouse Options Parallel Platform How it works: Existing data warehouse(s) remains online performing its current functions while new platform is added to perform required and desired advanced analytics. Information for new Late-Binding™ platform is pulled directly from source systems, thereby eliminating any rules or other limitations of existing data warehouse. With two systems, users are required to remember which system performs which function. Users may also resist adopting the new system if an alternative exists. Add new fully functional Late-Binding™ platform parallel to existing early-binding data warehouse Short-term resource impact Long-term resource impact Time to Value Pros: Allows immediate build-out of applications required to perform new, needed functions while existing applications remain intact; new apps take full advantage of Late-Binding™ platform Cons: Costs and staffing can increase as a result of maintenance of two systems and potential dual input and duplicate data integration; retaining two data warehouses reduces the value of a data warehouse as the single source of truth and may result in user confusion 2x Current Impact May vary

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Comparing Data Warehouse Options Cloud Data Warehouse How it works: As an alternative to a second on-premise data warehouse, a cloud-based solution can act as an additional data warehouse. Featuring a rapid deployment cycle, cloud-based/hosted solutions include hardware, software, maintenance, network bandwidth, backups, and warehouse management in customized packages. Hosting organization drives acquisition and rollout efforts and ongoing maintenance. Healthcare organizations will carefully want to review the efforts and options available. Adopt a cloud-based, hosted data warehouse to run parallel to existing data warehouse Short-term resource impact Long-term resource impact Time to Value Pros: Very fast deployment option without need to acquire capital equipment; both deployment and continued operation/maintenance are outsourced freeing up existing IT resources to work on other projects Cons: Initial cost may be higher but longer term costs are reduced over time; security of data can be a perceived concern for organizations, although vendors offering this option should take precautions to ensure data is secure 2x Current Impact

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Comparing Data Warehouse Options All-New Platform How it works: While this option does not retain the existing early-binding data warehouse, it provides users with the full advantages associated with the new Late-Binding™ data warehouse platform and associated advanced applications. New platform can also be developed to replicate key functionality of existing data warehouse, if desired. Offers increased adaptability and growth potential while eliminating limitations and/or shortcomings associated with existing data warehouse(s). Migrate data to new Late-Binding™ platform while phasing out former early-binding data warehouse(s) Short-term resource impact Long-term resource impact Time to Value Pros: Scalable and agile solution bringing full advantage of advanced apps and flexibility that drives the new Late-Binding™ platform’s technology; involves minimal risk while delivering value in a short amount of time. Cons: Migration over time results in full phase-out of existing data warehouse, which may be met with resistance from key stakeholders; higher short-term cost; adoption phase can seem disruptive when not phased in over time May vary

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Success w/Advanced Analytics Applications These options represent just a few available for organizations wanting to add advanced analytics functionality to an existing data warehouse. Determining the one that’s appropriate for a healthcare organization involves assessing its needs and goals relative to its current data warehouse solution. Your assessment should include: Investment to date Cost Time Apps

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Success w/Advanced Analytics Applications While preserving the existing investment is an important consideration, it should NOT be the driving force behind a decision. It’s more important to review long-term value. The total cost of ownership from the previous investment plus an investment in an additional or replacement data warehouse may be a better value than continued investment in a system that has outlived its capabilities and that carries with it a high investment cost per advanced analytics application. Investment to Date

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Success w/Advanced Analytics Applications Review both up-front costs and projected long-term costs for each option. What appears to be the best value at implementation may come at a high price over time, both financially and through maintenance resources. Cost

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Success w/Advanced Analytics Applications Consider the longevity of the various option relative to a healthcare system’s specific needs and goals. Flexibility to grow and change is vital to success. Time

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Success w/Advanced Analytics Applications The number of apps readily available to make use of the data in the data warehouse should be a key component of the decision. Review the options – including the potential and limitations of the existing early-binding data warehouse – in terms of cost per year as follows: Cost/app/year Apps

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Success w/Advanced Analytics Applications While adopting a new solution is rarely an easy decision, selecting the right one will help make data more accessible for everyone in the organization – from clinical staff to analysts, financial teams and more. If you are interested in a more in-depth assessment, please contact Health Catalyst to better evaluate the solutions optimized for your organization. In conclusion

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More about this topic Build vs. Buy a Data Warehouse: Which is Best for You?  Mike Doyle, Vice President What Is the Best Healthcare Data Warehouse Model? Comparing Enterprise Data Models, Independent Data Marts, and Late-Binding Solutions  Steve Barlow, Senior Vice President and Co-Founder Star Schema vs. Late-Binding: Best Approach for a Healthcare Data Warehouse  Steve Barlow, Senior Vice President and Co-Founder 6 Reasons Why Healthcare Data Warehouses Fail  Steve Barlow, Senior Vice President and Co-Founder EDW Cloud Hosting: Is It Right for Your Health System?  Nate Arnold, Director, Infrastructure Systems

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Other Clinical Quality Improvement Resources Click to read additional information at www.healthcatalyst.com Health Catalyst is a mission-driven data warehousing and analytics company that helps healthcare organizations of all sizes perform the clinical, financial, and operational reporting and analysis needed for population health and accountable care. Our proven enterprise data warehouse (EDW) and analytics platform helps improve quality, add efficiency and lower costs in support of more than 30 million patients for organizations ranging from the largest US health system to forward-thinking physician practices. Faster and more agile than data warehouses from other industries, the Health Catalyst Late-Binding™ EDW has been heralded by KLAS as a “newer and more effective way to approach EDW.” For more information, visit www.healthcatalyst.com, and follow us on Twitter, LinkedIn and Facebook.