Applying Analytics and Supply Chain Tools to Healthcare

To say that understanding and managing a large, disaggregated system such as healthcare delivery with its multitude of individual parts, including patients with various medical conditions, physicians, clinics, hospitals, pharmacies, rehabilitation services, home nurses and many more is a daunting task would be an understatement.  Like other service or manufacturing systems, different stakeholders have different performance measures.

Patients want safe, effective care with low insurance premiums. 

Payers, usually not the patient, want low cost. 

Health care providers want efficiency.

The Institute of Medicine has identified six quality aims for the twenty-first century healthcare system:  safety, effectiveness, timeliness, patient-centeredness, efficiency, and equity.  Achieving these goals in a complex system will require an holistic understanding of the needs and performance measures of all stakeholders and simultaneously optimizing the tradeoffs among them.

This, in turn, cannot be achieved without leveraging the tools that have been developed in other industries.  These are summarized in the table below.

While the bulk of the work and benefits derived from the application of these tools will lie at the organization level, these tools are well-developed concepts that can be applied directly to healthcare systems, beginning at the environmental level and working back left down to the patient, where indicated by the check marks.

Industrial engineers and operations researchers use systems analysis tools to understand how complex systems operate, how well they perform, and how they can be improved.  For example, mathematical analyses of system operations include queuing theory which can be used to understand the flow of patients through a system, the average time patients spend in a system, or bottlenecks in the system.  Discrete event simulation is another tool that can aid in a more detailed examination of system characteristics and sensitivity to inputs and changes in the system.  Economic and econometric models, based on data-driven analysis, help identify causal relationships among system variables.  Supply chain management tools help forecast demand for services and relate that demand to available resources.  Longer term mismatches can be minimized through sales and operations planning, while short-term challenges are addressed with capacity planning and scheduling.  A few examples of specific challenges that can be addressed through systems analysis tools include the following:

  1. Staff scheduling
  2. Improving patient flow through rooms and other resources and elimination of wait time and waste in work flow
  3. Capacity management in hospitals
  4. Evaluation of blood supply networks
  5. Distributing and balancing consumable supplies
  6. Ensuring the availability of medical device kits
  7. Optimal allocation of funding

Systems analysis techniques have been developed over many years and are based on a large body of knowledge.  These types of analytical approaches while very powerful, require appropriate tools and expertise in order to apply them efficiently and effectively.  Many healthcare delivery organizations are beginning to build staff who have at least some familiarity with a few of these tools, particularly Lean thinking in process design and six-sigma in supply chain management.  There also instances where some of the tools under “Optimizing Results” are being applied.  But, it is clear that much more remains to be done and many healthcare providers will initially need to depend on resources external to their own organizations in order to leverage many of these tools.

Two notes of caution as we move forward:

  1. In our efforts to consider end-to-end processes and their inherent tradeoffs, we must ensure that we do not enforce a complex structure to the detriment of disruptive innovations that will lead to more efficient and effective health care as described by Christensen et. al. in The Innovator’s Prescription.
  2. We must also take care not to base our data analysis and decision models on faulty cost data or inadequate outcome data.  In most cases, neither reimbursements nor charges reflect costs and the measurement of outcomes is significantly underdeveloped.  Some of the tools outlined above will be helpful in addressing these challenges.

Thanks again for stopping by Supply Chain Action.  I leave you with a thought from Mother Teresa, “We can do no great things – only small things with great love.”

Have a wonderful weekend!


About Arnold Mark Wells
Industry, software, and consulting background. I help companies do the things about which I write. If you think it might make sense to explore one of these topics for your organization, I would be delighted to hear from you. I am currently employed by Incorta, but I am solely responsible for the content in Supply Chain Action.

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