Medicare Utilization data is one of many useful datasets available to analyze markets in your VisionLTC platform. VisionLTC presents the information in the form of both geographic and facility level data. With this unique dataset, you can see actual incidence rates for a select number of chronic conditions and the number of MB (Medicare Beneficiaries) that have been diagnosed with a chronic condition in the past year.
Geographic Data
The data available as part of the market-level Medicare Beneficiary dataset can be viewed either as a metric in reports or as a Dynamic Metric Layer. The list of the metrics and their definitions is as follows:
MB with Alzheimer’s Disease in past year: the number of Medicare beneficiaries in the market who have been diagnosed with Alzheimer’s in the past year.
MB with Alzheimer’s or Dementia in past year: the number of Medicare beneficiaries in the market who have been diagnosed with Alzheimer’s or Dementia in the past year.
MB with Chronic Kidney Disease in past year: the number of Medicare beneficiaries in the market who have been diagnosed with Chronic Kidney Disease in the past year.
MB with COPD in past year: the number of Medicare beneficiaries in the market who have been diagnosed with COPD in the past year.
MB with Congestive Heart Failure in past year: the number of Medicare beneficiaries in the market who have been diagnosed with Congestive Heart Failure in the past year.
MB with Diabetes in past year: the number of Medicare beneficiaries in the market who have been diagnosed with Diabetes in the past year.
MB with Hip Fracture in past year: the number of Medicare beneficiaries in the market who have been diagnosed with a hip fracture in the past year.
MB with Osteoporosis in past year: the number of Medicare beneficiaries in the market who have been diagnosed with Osteoporosis in the past year.
MB with Rheumatoid Arthritis or Osteoarthritis in past year: the number of Medicare beneficiaries in the market who have been diagnosed with either Rheumatoid Arthritis or Osteoarthritis in the past year.
MB with Stroke or Transient Ischemic Attack in past year: the number of Medicare beneficiaries in the market who have been diagnosed with either a stroke or a Transient Ischemic Attack in the past year.
MB with Hypertension in past year: the number of Medicare beneficiaries in the market who have been diagnosed with hypertension in the past year.
Total MB with Alzheimer’s: the total number of living Medicare Beneficiaries in the market who have diagnosed with Alzheimer’s.
Total MB with Alzheimer’s or Dementia: the total number of living Medicare Beneficiaries in the market who have been diagnosed with Alzheimer’s or Dementia.
Total MB with Chronic Kidney Disease: the total number of living Medicare Beneficiaries in the market who have been diagnosed with Chronic Kidney Disease.
Total MB with COPD: the total number of living Medicare Beneficiaries in the market who have been diagnosed with COPD.
Total MB with Congestive Heart Failure: the total number of living Medicare Beneficiaries in the market who have been diagnosed with Congestive Heart Failure.
Total MB with Diabetes: the total number of living Medicare Beneficiaries in the market who have been diagnosed with Diabetes.
Total MB with Hip Fracture: the total number of living Medicare Beneficiaries in the market who have been diagnosed with a hip fracture.
Total MB with Osteoporosis: the total number of living Medicare Beneficiaries in the market who have been diagnosed with Osteoporosis.
Total MB with Rheumatoid Arthritis or Osteoarthritis: the total number of living Medicare Beneficiaries in the market who have been diagnosed with Rheumatoid Arthritis or Osteoarthritis.
Total MB with Stroke or Transient Ischemic Attack: the total number of living Medicare Beneficiaries in the market who have been diagnosed with a stroke or Transient Ischemic Attack.
Total MB with Hypertension: the total number of Medicare Beneficiaries in the market who have been diagnosed with hypertension.
Historically, most demand models have relied on an assumed nationwide incidence rate. With this data, however, you are now able to find concentrations of Medicare Beneficiaries with an ailment in the market area – logically very similar to finding pockets of age-and-income qualified households.
Facility Data
In addition to the market-level Medicare data now available in VisionLTC, you can also view Medicare expenditure data at the building-level nationwide. While the market-level data is useful for determining need in the market, our building-level data can be leveraged to help foster resident referral relationships between your operators and their local health system.
The data points available in this dataset are as follows:
Total Medicare Spend Per Beneficiary: the average dollar amount spent by Medicare on each beneficiary at this building.
Average Beneficiary HCC Score: the average Hierarchical Condition Category (HCC) score of each beneficiary this building – a higher value for this number indicates more severe conditions that would require a greater level of care and represents a greater level of risk to the healthcare provider.
Medicare Spend / HCC Point: Total Medicare Spend Per Beneficiary divided by the Average Beneficiary HCC Score.
30 Day Readmission Rate: the percentage of patients who experience unplanned readmissions to a hospital after a previous hospital stay in the last 30 days – a lower value in this category indicates a higher level of clinical performance.
90 Day Readmission Rate: the percentage of patients who experience unplanned readmissions to a hospital after a previous hospital stay in the last 90 days – a lower value in this category indicates a higher level of clinical performance.
% Attributed to ACO: the portion of beneficiaries who are attributed to the facility and also a Medicare Shared Savings Program ACO for 2017, 2018, 2019.
For more information on how to effectively leverage this data to promote better health outcomes, please see our Article on Using Medicare Data to Partner with an ACO.