Healthcare Analytics

Controlling healthcare costs while maintaining a high quality of care requires understanding the drivers behind costs and effectiveness. Whether you’re a hospital administrator, a general practice doctor or a public health official, analyzing your data can give you new insights.

Heat Map Explorer can help you:

  • Provide personalized healthcare by analyzing effectiveness at a deeper level.
  • Understand how your processes affect different populations.
  • Uncover fraud, waste and abuse.
  • Monitor patients and processes in real-time.
  • Analyze regional and national trends.

Use Heat Map Explorer Desktop to analyze data from Excel or SQL databases, or use Heat Map Explorer Enterprise Edition to integrate directly into your enterprise applications.

  • Gain deep visibility into claims by seeing medical services, supplies and procedures clustered by coding hierarchy.
  • Analyze claims data for patterns in diagnosis and treatments.
  • Identify micro-patterns in clusters of claims that can be used to improve the efficiency & effectiveness of healthcare solutions.

This heat map shows Medicare claims organized by the Healthcare Common Procedure Coding System (HCPCS) hierarchy. The size of each box shows the number of claims and the color indicates the average amount paid out versus the amount submitted. Procedures and services that received full payment are easily seen in red.

  • Find micro-patterns by diagnosis and service provider to improve outcomes.
  • Apply group benchmarks to see how providers compare to their peers for the same diagnosis.
  • Understand the utilization of services by diagnosis, provider and population.

This heat map shows discharges by diagnosis. Each box represents the data for a specific diagnosis at a specific hospital. Boxes are grouped by Major Diagnostic Category (MDC), then by Diagnoses Related Group (DRG). The size of each box indicates the number of patients discharged under that diagnosis at that hospital.

The color represents the group benchmark of the length of stay. A group benchmark compares the performance of each item within a group to the average performance of the entire group. In this case, red boxes indicate lengths of stays far greater than the average for that diagnoses group, while green boxes indicate lengths of stays far less than the average. 

In the bottom middle you can see a group of bright red boxes representing the Psychoses diagnosis. The big red boxes indicate that the hospitals handling the most cases have far greater lengths of stays than the average hospital treating this diagnosis.

  • Monitor patient status in real-time.
  • See full patient details instantly by highlighting a bed.
  • Analyze historical data to identify location-based patterns and trends.

This heat map shows patient status in rooms and beds on a hospital floor. Green indicates a good condition, yellow is fair and red is serious.

  • Analyze process flows to find bottlenecks and potential improvements.
  • Filter by patient type, diagnosis or day of week.
  • See full details by hovering over each stage.

This heat map shows the wait times for each stage in an emergency room process. Green represents short wait times, yellow medium wait times and red long wait times.

  • Analyze geographic healthcare trends at the state, country and global level.
  • Use color schemes designed to highlight insights and set custom color thresholds.
  • Apply filters to compare different slices of data.

This heat map shows the average percentage of female Medicare enrollees age 67-69 that had at least one mammogram over the previous two years. Green counties have a rate above 70% while red counties have a rate below 50%. Yellow counties are in between.