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Background & Problem Summary

Healthcare analysts spend countless hours understanding contract terms, performance measures, and internal quality improvement efforts. However, this work often resides in siloed spreadsheets. This leads to duplicative work, recreation of overlapping efforts, and an inability to see what is being monitored, reported on and reimbursed for at a system level. To most effectively manage both the proliferating value-based payment contracts and the data in the EDW, a shared reference tool is needed.

Application Overview

Manage all your measure sets in one central shared location.

Benefits and Features

MBL provides a robust analytic front-end to organize, summarize, and provide actionable visualization of value-based contract terms.  Visualizations highlight areas of overlap and thus, opportunities for alignment in system initiatives. MBL also provides a library for measure definitions and valuesets.

  1. Store all contract terms in the same tool; creating visibility between financial imperatives and quality improvement initiatives.
  2. Identify alignment across your system across various dimensions including provider specialty, disease type, action required (i.e. immunizations), or site of care
  3. Measure Library allows for any type of external or internal measure to be added; track differences across versions, governing bodies and system initiatives.
  4. Value set management links to terminology server to provide content that can be reused in various Health Catalyst products including the Registry Suite.

Use Cases

  • The clinical improvement work team wanted to begin a project around reducing spine complications. Although clinically important, the improvement work on its own did not have a significant financial ROI. Finance was able to support the proposal when it was identified that it would have a significant impact on a pay-for-performance measure to a large payer contract the improvement work, with a quality payment ROI of $1.8 million.
  • Population health leaders were charged with focusing on all the varied targets associated with different payer contracts. In doing so, they also needed to ensure clarity and simplicity at the point of care; no one wanted providers to have to focus on certain metrics for some patients but not others, depending on their insurers. Leaders first looked across the measures in five payer contracts. They had LDL screening measures in several, including in some contracts that had LDL screening exclusively for the diabetes patient population. Because the system wanted to pursue improvement in actual patient outcomes (not just compliance with screening standards), they chose to prioritize, at a system level, a measure on LDL control. They used the measure details surfaced in MBL to standardize the scope and definition of their LDL measure, ultimately deciding on a denominator that captured all the patient types who were incented by external measures and establishing a single target number for ‘control’.
  • A physician group wants to begin an internal project focused on diabetic patients. Using MBL, a data architect can quickly identify the ways the organization has already been defining diabetes, present them to the group to identify that one of these is appropriate, and then access the location of the code in the EDW to create the analyst report in a much shorter period of time than it would have traditionally taken.