USL20 Health Care Forecasts

Recently, the PBS News Hour interviewed a Primary Care Physician (here) to discuss problems in the US Healthcare System.

The summary of problems (from Google AI, above) suggests the following solutions  (also Google AI) to get control of the system:

To help understand the problems and difficulties, I ran four forecasts with the USL20HC Model (presented in the graph above). Both the Business-As-Usual (BAU) model and the USL203 Model as input** are unstable. Stabilizing (controlling) the BAUC model produces more moderate growth until after 2100.

Controlling specific parts of the system (Prices and Hospital Investment) without affecting Quality of Service will not be easy. Attempts to control Prices have failed (see Pasdirtz, 2007) largely for political reasons. ChatGPT notes:

A reduction in demand for Healthcare when the Baby Boomer Generation has aged out of the system might help. Until then, I do not see the political will necessary to change the system. However, Healthcare costs are directly related to the US Affordability Crisis (Google AI):

If dealing with the US Affordability Crisis becomes one of the outputs of the US Political System, then Healthcare expenditure has to be considered. If the US Healthcare System becomes more fully integrated with the US Political System, the relationships between HC1 = (Growth - Hospitals) might become more closely related to Austerity, Hardship and Debt management--and be affected by Growth or Collapse in the US Political System.

Right now, problems in the US Healthcare System are more a function of what the US Political System thinks it is supposed to be doing for the American people. In the Trump II Administration, it is not entire clear what the US Political System thinks it is supposed to be doing for the American people.

Notes

• Healthcare in the United States  largely provided by private sector healthcare facilities, and paid for by a combination of public programs, county indigent health care programs, private insurance, and out-of-pocket payments. The U.S. is the only developed country without a system of universal healthcare, with around 92% of the population covered under some kind of health insurance for some, or all of the year.
  
  
• The Affordable Care Act  formally the Patient Protection and Affordable Care Act (PPACA) and informally known as Obamacare, is a landmark U.S. federal statute enacted by the 111th United States Congress and signed into law by President Barack Obama on March 23, 2010. Together with amendments made to it by the Health Care and Education Reconciliation Act of 2010, it represents the U.S. healthcare system's most significant regulatory overhaul and expansion of coverage since the enactment of Medicare and Medicaid in 1965. Most of the act remains in effect.
  
  
• Medicare Sustainable Growth Rate a method used by the Centers for Medicare and Medicaid Services (CMS) in the United States to control spending by Medicare on physician services.

** The idea behind using the USL203 Model as input is to keep growth of the US Healthcare system in line with growth of the US Economy (see Pasdirtz, 2007). See also, US Healthcare, Austerity and Debt.

Pasdirtz (2007) Controlling the US Healthcare System with Policy Wedges Springer Health.

For more of my posts about the US Healthcare system, see Blog Roll: Healthcare. For more information about how the State Space models were constructed and the data sources, see the Boiler Plate. You can run the USL20HC Model model yourself using the R-code on my Google Site.

USL20HC Measurement Model

The indicators above implement the basic Kaya Identity: N -> L -> Q -> K -> GDP.

Expanding the Kaya Identity to fit the US Healthcare system, we get the Directed Graph above.

Three components in the USL20HC State Space (computed using Principal Components Analysis, PCA) explain 99.80% of the variation in the indicators. HC1 is the Hospital-Growth Controller. HC2 is Output Controller and HC3 is the investment controller.

Using the Expanded Kaya Identity (above) chatGPT suggests controlling the US Healthcare system by direct interventional in the following indicators: Capping Prices, Controlling Investment and limiting Hospital Consolidation. Healthcare labor and insured population would depend on the growth limits imposed. Direct intervention would allow direct control of growth rates.

USL20HC BAU Model System Matrix

The USL20HC Model has two unstable components, HC1= (Hospital-Growth Controller) and HC3 = (Investment Controller).

USL20HC BAUC Model System Matrix

Notice that stabilizing the USL20HC Model model turns the HC1 = (Hospital-Growth Controller) into a Random Walk while HC3 = (Investment Controller) requires a reduced growth rate.