Possibilities are, if you are reading this blog, you have actually heard some taste of the “build vs. buy” concern in the context of data warehousing. For example, here are 2 conflicting means that I have actually personally heard this question presented:.
“Do we have to buy [a data warehouse], or can we build it?”.
“Exist any suppliers we can buy this from, or will we have to build this?”.
As you can think of, both strategies resonate in a different way with various people, cultures, and strategies, and the exact same basic concerns sound really various depending upon who is asking it.
Historically, Why Were Healthcare Data Warehouses Built, Not Bought?
To offer some context to this concern, it might help to draw a parallel with the development of the EMR. Early adopters of EMRs had to build their own, as there were few industrial vendor options. Then, the first generation of basic commercial EMRs went along. Business like Siemens, Cerner, and Impressive advanced early ideas into 2nd and third generation systems, prompted by the EMR adoption model from HIMSS that provided suppliers and customers a benchmark– a roadmap– for product development and acquisition.
Likewise, till just recently no single supplier offered a business data warehouse (EDW) solution for healthcare that might provide measurable results and return on investment. Innovative companies with the resources to support a substantial internal development effort really had only one potential path: build it themselves.
Health systems without the staff, budget, or experience to build a centralized EDW themselves were left with two main options:.
“Data analyst heroism”– where a small number of savvy analysts used whatever reporting or analysis tools they had at their disposal. Great people in these roles achieved excellent outcomes, but their potential value was often underutilized due to the fact that they had to spend too much time extracting data instead of examining it.
Implemented best-of-breed analytics solutions to assist attend to specific, reporting, and analytic requirements.
Buying or Building a Healthcare Data Warehouse
More and more, organizations that have historically planninged to internal IT resources to help them ascend the rungs of the Healthcare Analytics Adoption Model are looking for help from an experienced commercial partner:.
This healthcare analytics market is at the same point as the market was for EMRs about 10 years ago, when viable commercial EMRs emerged and organizations no longer had to build their own.
Healthcare suppliers now have several commercial alternatives for numerous kinds of healthcare analytics. For instance, a 2013 report from Chilmark Study profiles numerous of these vendors, including Health Catalyst which received the highest general rating.
Organizations that have been able to nurture one or more teams of efficient, internal software developers want to preserve this precious resource, and deploy them strategically for a competitive advantage. Where possible, they are looking to suppliers to accelerate their implementation of analytics, not completely outsource or possess that capability altogether.
These organizations recognize that they can get 80 to 100 percent of the analytic capability they need, quickly, and affordably. They are looking to deploy their internal developers to help them attain much more, much faster.
Here are some vital points to consider when thinking about the Buy AND Build option:
Pros of Buying AND Building an EDW
All the pros of each purchasing and building– for instance:.
- Rapid implementation time– the right supplier can help get a big piece of the data warehouse implemented rapidly, allowing your IT leads to demonstrate early successes and keep project momentum high.
- A tailored fit– your internal software developers know your systems inside and out. A savvy supplier understands this and will certainly include and equip your leading IT entertainers, guaranteeing a smooth implementation, and honing in on ways to meet immediate analytic needs.
- Lower overall project risk– by choosing to leverage facets of both the “buy” and the “build” strategies, you are positioning yourself for a successful project in the following ways:.
- You are engaging some of your most valuable IT employees early on.
- Your vendor is contractually obligated to deliver on the agreed-upon terms and statement(s) of work.
- Additional opportunity to innovate– a great EDW vendor will partner with you to empower your internal designers through access to integrated data and easily accessible metadata. With the “plumbing” taken care of by your vendor, your in-house engineers can focus on extracting much more value from your investment. Health Catalyst customers, for example, have begun developing their own predictive models, connecting to operational systems, and building bi-directional interfaces with other third party systems.
Many EMRs are now providing interfaces to consume relevant external data, such as patient-level risk scores, to drive best practice alerts at the point of care. With access to the data in an enterprise data warehouse, a talented internal software developer could deliver a prototype solution to a use case like that in days, instead of months or years.
Cons of Building and Purchasing an EDW
- Some of the same “cons” as both structure and purchasing, however they tend to cancel each other out. For example: you will still need to be comfortable with your selection of vendor partner, but that is balanced by the internal developers you bring to the project team.
- This approach is best suited to a data-driven culture that values analytics as a business differentiator. Organizations with a commitment to a higher degree of data literacy and data management skills are very successful with a data warehouse.
- Slightly higher total expense of ownership than the purely “buy” choice. Nevertheless, this again is offset by the higher return on investment (ROI) which can be accomplished with the optimal utilization of your EDW.
Selecting Your Healthcare Data Warehouse Approach: You Have Options
As you can see, you have options when it comes to selecting your approach to a healthcare data warehouse. If you choose to develop an enterprise data warehouse purely from scratch, you face many of the same hurdles companies overcame through the last decade of expensive, internal software development. There are now vendors who can leverage their experience to help you attain a comparable level of analytic maturation in a much shorter time and at a lower total cost. Thanks to the early leaders of our market, we now understand enough about the features of a high-value EDW to make informed decisions when choosing a vendor. This blog, “The best ways to Evaluate a Clinical Analytics Supplier” outlines the concerns to consider, and criteria for evaluation.
When choosing either of the “buy” options described above, it’s crucial to consider not only total cost, but also how you want to engage your internal resources. Think about not only how fast you want to realize value in the short term, but also how you envision developing your own analytic applications in the future.
The early adopters of EMRs mentioned above were also some of the very first to build their own EDWs. Several of those early leaders are now applying their experience with home-grown EDWs to the purchase and installation of hybrid solutions– commercial vendor EDWs that come pre-configured for rapid deployment and quick value, but that can also be evolved and maintained by local IT organizations if they choose to do so.
For many organizations, the “hybrid” option of buy AND build provides a way to achieve the most value, while also mitigating many of the risks associated with big in-house software development efforts. This hybrid strategy is the very best of both worlds. You get the flexibility and empowerment of building a system by yourself, but without the dangers, and you get the advantages of a commercially supportable solution. No one would think of developing their own EMR now. Likewise, we are at a point in the evolution of the EDW where developing your own simply doesn’t make good sense from the viewpoint of risk, time to value, and long-term advancement of organizations’ analytics strategies.
