Many small to mid-sized organizations historically have felt the need to compromise or go without when it comes to data and analytics, especially in margin conscious organizations like community hospitals.Thankfully, with innovations in analytics and the SaaS model, you don’t need to be a large university health system with an expensive data warehouse to have a strong analytics strategy. In fact, new approaches to enterprise data management are shifting the focus away from data repositories, which can be a boon to community hospitals looking for cost-effective solutions to their analytics challenges. Today, you can develop a data strategy and governance that streamlines your analytics process and get self-service users the analysis-ready data they need faster than ever without exorbitant budgets.
This is a welcome change from the historical approach, where analytics projects in healthcare were “start from scratch.” These projects almost always were time consuming and expensive, relying on a data warehouse implementation. End users, especially at the operational level of smaller healthcare organization such as community hospitals, had to wait for the IT team to catch up with their analytics requirements.
Thankfully, today with third generation analytics tools delivered via SaaS, IT can be an enabler of analytics and provide users with self-serve analytics that leverages established IT infrastructure. This reduces the overhead and time usually devoted to creating and maintaining the data warehouse, and puts analytics ready insights into the hands of frontline workers much faster. This also enables community hospitals to strategically deploy analytics on their timeframe, scale and budget towards their most pressing issues, e.g. bed-to-patient ratios or staffing-plan-to-cost ratios. The flexibility of the SaaS model allows community hospitals to truly maximize the value of their data without impacting profitability or inhibiting business efficiencies.
There are certainly roadblocks, though. The more data there is to be standardized, the more departmental views there are to be resolved. And, healthcare data spans multiple systems across the continuum of care — clinical data, billing data, purchasing and payroll, just to name a few. Hospitals of all sizes, including community hospitals, are no different; they have similar complexities and multiple systems of record. It’s vital to have a clear picture of the issues you’re hoping analytics can help solve, build a strategy that can scale with your budget and deploy a technology like Qlik Sense that can bring multiple and disparate data sources together without the need of a data warehouse.
So, what holds community hospitals back from deploying SaaS analytics? One concern is that self-service tools and solutions do not always answer the data governance questions of IT, especially when it comes to sensitive patient data. Having an organization-wide data governance model that manages data assets throughout their lifecycle will ensure the organization’s quality and integrity standards are met regardless of the analytics tool in use. (We’ll dive more in depth into governance in a following post.)
A best practice community hospitals should aim for is to have solid enterprise-wide data governance policies and practices that facilitate achieving the Institute for Healthcare Improvement’s Triple Aim:
My advice?
Most of all, don’t get stuck; keep pushing forward until you’re leveraging a solution that scales to your operations and needs and yields valuable insights. You and your community hospital colleagues — and not to mention your IT department — will be more than happy to reap the benefits of having and deploying a robust data analytics strategy across the care continuum.