Business Intelligence – the Next Implementation Priority

As with many other business and market drivers inspiring changes in healthcare, the need for improved business intelligence (BI) tools and capabilities is multifaceted.

Policy Drivers: 

  • HITECH Legislation – Meaningful use requirements, and the revenue associated with early attestation, have inspired many physicians and hospitals to implement EHRs to meet Phase 1 requirements.
  • ACA Legislation – Many of CMMI’s new models for ACOs, bundled payments, etc., include specific quality measures.  However, some new models from CMMI propose that institutions develop their own quality and other performance measures.

Financial Performance:

  • Cost Reductions – Federal and state healthcare funding continues to be reduced in current and projected budget cycles.
  • Payor Agreements – New payor agreements include both cost reductions and financial and performance measure improvements.

Clinical Integration:

  • Incentive Alignment – Incorporating performance measures into compensation and funds flow models helps incentivize clinical integration across departments, service lines, and other organizational boundaries.
  • System-Wide Integration – Performance measures across a system, including partnerships and affiliations, reinforce and reward clinical integration.  These same measures support those that are negotiated in payor agreements such that reimbursement is aligned with system-wide integration goals.

Reporting Requirements:

  • External – Payors, regulatory institutions, external disease registries, and databases require increasing data and reporting requirements.
  • Internal – Reporting for managers, senior leaders, and physicians (to the extent that compensation is metric-driven) will drive increasing expectations and demands for internal reporting and analysis.

BI tools are the next implementation priority after EHRs.  Data sources often come from different systems, yet need to be integrated in order to create the understanding of performance across a wider variety of data types.  Real-time decision support becomes essential to improve clinical outcomes and operations improvements in the clinical environment.  Combining cost and reimbursement data with clinical and outcomes data in a relevant real-time manner that can influence decisions in the clinical care setting is the vision of what your IT and BI tools need to enable.

BI can be designed in a way to meet your institution’s needs.  A structure for a BI center might include the components shown below.

Action Items

Preparing to improve your BI operations should involve the following steps:

  1. Identify the Functional Needs That Your BI Solution Needs to Support – Start with the end in mind.  Key stakeholders may be a broader audience, or at least the scope of data might be broader, than past assessments.  Partners and affiliations, external reporting requirements, and internal decision support needs – all of these warrant consideration in your initial needs assessment.
  2. Conduct a Gap Analysis – Assess the capabilities that you currently have and compare them with what you identified in the first step.  There are timing and frequency considerations that must be included in this assessment, which can often indicate that a higher-performing BI operation is possible than what might currently be in place.
  3. Estimate Resource Requirements – Addressing gaps must be planned so that you can prioritize adding resources in a way that has the most impact.  Obtaining new resources and doing the planning work (e.g., data governance) to make them effective may take some time, which should help you prioritize resource acquisitions accordingly.

Develop an Implementation Plan – Create an implementation plan that reflects the prioritization noted in the step above, balanced with your organization’s ability to acquire any needed new resources.  The implementation plan should include major milestones, along with the functionality enabled by each milestone, and any key considerations that must be addressed as you move through building a more robust BI operation.

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