The Patient Classification section of the Physician Detail Page contains five tables with corresponding pie charts that reveal significant patient demographics for the physician listed on the page.
Data Calculation Highlights
- The counts and percentages in these tables are calculated on ALL Medicare claims for the physician listed on the page. The purpose is to give an overall assessment for the types of patients the physician treats.
- The Reporting period for the data in these tables is the standard 1 year period. (Please see Reporting Periods for more details.)
- The counts do not necessarily reflect unduplicated patient counts. A patient who moved from one ZIP code to another within the year who also had two separate claims would be counted once in each ZIP code to reflect the whole of a physician’s scope of practice.
Diagnostic Grouping Breakout
This table provides a breakdown of the 20 Trella Health Diagnostic Groupings by percentage of patient for each category listed. There is an entry titled, “Aggregated INS MDC’s” which represents the combined percentage for all diagnostic categories that are too small to be significant on their own. There is a button that is a link to a page that lists the complete content of the 25 Diagnostic Categories. If you see a diagnostic category that is presented in bold print, those are categories that your leadership team has specifically as categories requiring special attention.
Identifying the primary types of care provided by a specific physician will allow you to match higher patient populations that could coincide with areas of strength in your agency. Physicians who have larger patient populations that match your strengths are good potential sources for collaboration or partnership.
In order to examine the MDC's in greater detail, click the button in the Solution. or see, Trella Health Diagnostic Groupings.
County and ZIP Code Breakout Tables
- The counts that yield the percentages in these tables are based on the county or ZIP code of the patient residence at the time the claim was filed, not the location where treatment was provided.
- Any and all counties or ZIP codes where the percentage would represent a count of less than 11 patients will not be identified in the table but will be aggregated into the row titled, “Other.” For example, if a physician had 100 patients in the reporting period, any county or ZIP code with 10% of the total, or less, would represent less than eleven patients in that location and therefore, that location will not be identified, but would be combined with all other locations also not specified.
- County or ZIP code data might indicate a higher patient population of urban patients, or rural patients, which could suggest a need for higher levels of a specific type of care.
- County or ZIP code data could identify a location where no Home Care services exist, which could explain lower PAC utilization by the listed physician.
- If a physician has a large percentage of patients identified in the “other” category, this could represent a physician in a specialty where labs or tests are sent to the physician for consultation from patients located in a large geographical area.
Age Breakout Table
- This table gives a simple breakout of the patients for the listed physician by age.
- This table provides insight into the ages of patients that this physician treats.