Data is the most important source of information that can guide the consolidation to success. Without data, there is no experimentation and there is no predictability of the business.
Data Integration is the process that can measure operational efficiency even in the absence of the System Integration at both Business and Clinical Levels.

In organizations that have Standardized Clinical Systems, it is easier to establish medical operations level metrics due to normalization of the source code and established GL structure.

In the organizations where the clinical systems are not standardized,data integration is the most important puzzle that needs to be solved early in the game.

A thorough mapping process of current systems should be conducted to produce the full list of both Business and Clinical Systems. Then, the Metrics at the level of the Executive Balanced Scorecard should be determined and Dashboards created for each Department responsible for Growth Levers and Margin Expansion Tactics.

Once the Dashboards are created, possible KPIs should be investigated using existing Data Points. Future systems should be assessed for potential additional Data Points, since there might be additional data available in the near future. Several experiments should be run with the data sets before submitting them to the Organizational Scorecard.


Without overarching Business and Clinical Data Integration, the organization is flying blind. Sufficient Data Analytical and Software Integration competencies should be established at the organizational level in the early stages of Maturity. There is no ability to report progress to your investors or make future investment plans.


  • Prospect Hospitals Pipeline
  • M&A Process
  • Culture/People Integration
  • HR Process/Onboarding
  • Knowledge Accumulation
  • Core Processes Implementation
  • Strategic Filter
  • Prioritization (WSJF)
  • Talent acquisition
  • Pre- and Post-Acquisition Assessments
  • Training
  • Quarterly Goals/Rock Planning
  • Recruiting at the Hospital Level
  • Implementation of VCP Processes
  • Capacity Reservation Process
  • Change Management
  • Data-Driven Change Management
  • Data-Driven VCP Initiative Process
  • Horizon 2 Experiments
  • ML Data Model
  • Horizon 3 Experiments


Visualization of the data and results to goal settings is one of the Lean Thinking principles. Lack of transparency in metrics and how the organization arrived at the results is the most common reason to trigger: Lack of control, Value Conflict, Insufficient reward, Work Overload, Unfairness, Breakdown of the community.


Thorough Data Integration by design is a luxury which both de-novo and franchise have from the very early levels of maturity. The data integration process should be leveraged as soon as the core processes are established and the KPI curation begins.