Acting Upon Discrimination in Health Spending

Spending Designs Discriminate

Designs for spending send less to counties in most need of care that have populations with multiple dimensions of "left behind." This can be tracked by measuring distributions of Medicare dollars or by measuring workforce distributions. Counties with lower to lowest concentrations of workforce not only have fewer services, they have higher proportions of primary care and basic services. In other words they have less of the services and providers that generate the most revenue under US design. Thirty or more states, 2600 counties, and 40,000 zip codes geographically map discrimination. Discrimination can also be mapped by economics, race, ethnicity, age, income, education, and other measures.

Decades of inaction indicate continued Discrimination by Design.

American health spending, like workforce, is concentrated in 6 states, 250 counties, and 1100 zip codes. Spending design favors those doing well across a wide range of social determinant dimensions. Workforce and training are similarly concentrated - influencing distributions of workforce and health spending.

Training Designs Discriminate

Designs for workforce production send fewer graduates to states and to counties in need of care and fewer to family practice positions (for MD, DO, NP, and PA grads). Family practice positions filled represent the multiple times greater multiplier of care where needed because family practice positions are the only ones distributed equitably. All other types of positions concentrate where clinicians are concentrated.

Only graduate results maximal for distribution can resolve deficits of services where needed. Population based distribution is seen in family medicine with 36% of family physicians in 2600 counties where 40% of Americans reside along with even higher proportions of nearly every population in greater need. The declines in the other major primary care contributor, internists, places even greater importance upon family practice position outcomes. Declines in MD, DO, NP, and PA family practice position result is discrimination against care where needed by training design. Designs must be specific to permanent family practice outcomes - the optimal health access recovery result.

Innovative Payment Designs Discriminate

Designs for pay for performance, value based, and readmissions penalties punish the same providers in the same locations - and the same populations that reside there.

Innovative Highly Technical Care May Not Benefit Those in Need of Care

To obtain maximal benefit from cancer chemotherapy, major surgery, or conditions requiring long term recovery, substantial support is required from family, insurance, employers, or others. The evidence is gathering that highly technical care designs fail for those in most need of care.

Clearly higher spending upon technologies such as Health Information Technology, results in less that can be spent upon clinicians and team members to deliver the care. This is not the only problem. As practices and states must spend more upon primary care locums or recruitment/retention incentives for needed primary care, even less remains to pay the clinicians and team members that delivery care.

CMS and Insurance Payers Support Discrimination

CMS has had critique, but much of this critique has apparently been dismissed as critique by those against Obamacare. When they have responded to charges of discrimination by individuals, experts, and studies, they have stated that to modify their formulas would not be fair. They have basically justified the destructive declines in health care delivery and health care workforce where needed.

Insurance policies that require smaller providers to beg for prescription approval, goods, consultations, admissions, and other services substantially raise the cost of delivery. Denials and delays in payments hurt smaller providers most. Many never even raise a protest as they have far too much service responsibility to allow distraction - already overwhelmed due to too much demand and too little supply of workforce. When small or needed practices spend more on personnel that address administrative needs, this leaves less for the support of clinicians and team members that deliver care.

With regard to Medicare Advantage, the insurance companies were obviously allowed too much ability to design their reimbursement - and used the design to harvest 70 billion more in the past 6 or 7 years. After complaining about over coding by health providers, it is the insurance companies using their mastery of health information that has provided one of the best examples of over coding and overcharging government. 12 billion a year dedicated to specific family practice workforce production would have contributed to primary care recovery and recovery where needed. When more is spent for those doing well, most left behind fall further behind by design.

Failure of Designers

Designers (pride? arrogance? defensive? unaware?) given the opportunity to demonstrate their designs have been focused on their own designs. The decisions made when given a change to reform, was to compromise on real reforms such as universal insurance or single payer. The designers may have been more focused on their own innovations or upon innovation for the sake of innovation. They may have underestimated the magnitude of the problem of America's failed health design. Clearly they have failed for decades to be aware of the chaos that they have promoted - chaos due to rapid change.

Designers from a few states, zip codes, and counties 
may not be able to grasp the situations facing those outside of their perspectives.

The last few years have resulted in substantial attention paid to health care. It was a great opportunity to showcase the best designs and the best leaders doing well in this important component. High expectations were a contrast with the major failure that is US health care. Decades have been required to get to the current situation. It will take decades of payment change and training change to shape real improvements where care is needed.

The magnification of health care tended to exaggerate the failures of health leaders and designers. This was a key reason that political victory was handed to those who are committed to even less support of populations in need of support across Social Security, child well being, nutrition, and basic health services - essentially any spending that is distributed in a population based pattern.

Consequences to Expect

The logical and expected result will be even less workforce, even less spending, and even lower outcomes for 40% of the nation in 2600 counties and even more with limited access despite residing in counties with too much workforce.

The result where care is most needed will be declines in health spending, declines in workforce, and declines in other spending. This will shape the social determinants of health adversely as well as failing for cost savings, failing for access, and failing for quality.

Show Me the Studies

Lessons for the future when reading studies claiming successful interventions - Accept less, assume less, question more! Think about advantage vs disadvantage in patient, provider, setting, and other dimensions.

When you see studies or interventions that claim improvements in multiple key areas, close examination is required.

It is very difficult to improve quality by spending less where care is already limited by lack of spending,  lack of workforce, and more complex patients

It is very difficult to reorganize care with Primary Care Medical Homes or consultants when the problem is lack of sufficient revenue, insufficient workforce, high turnover of personnel, higher cost of delivery getting rapidly higher, and high complexity of patient population.

It is impossible for the practices most needed - to function well with the numerous dimensions involved in delivering care with rapid changes in each dimension.

When you see such studies and differences are seen in cost - look for studies with populations that had too much spending already. Look for lost access or cherry picking.

When you see improvements in quality, look for differences in the populations studied.

When you see no difference for an intervention, consider this the norm. In a study with good controls involving the same patients or populations, the results should be the same. The setting, situation, and relationships of the patient shapes outcomes with provider or type of provider limited in impact.

The 2600 counties lower to lowest in clinician concentrations are paid the least per capita, are growing the fastest in population, have higher proportions of populations that are growing most in demand for services, and have the most social determinant challenges in the most dimensions. Why would improvements be likely at all?

Like designs for economics and for education, 
health care design assures even less for more and more for less.

Numerous studies have been done for decades and even more can be done. The time for action is long overdue.

Of all the forms of inequality, injustice in health care is the most shocking and inhumane. 
Martin Luther King, Jr.

Inequality in Medical Education - A Tribute to Martin Luther King, Jr.

Recent Blogs

Understanding Common Errors in Quality Studies

Real Reasons for Rotten Outcomes

Too Many and Still the Wrong Clinicians

The Government Control Card Still Plays Well

Rotten Apples, Rotten Support, or Rotten Media?

Improving Health Care is Not Likely for 2600 Counties

Global Fails Local But Local Focus Succeeds Globally

Domino Decline By Design - as ERs Close, Those Nearby Face Challenges, as Small or Rural Hospitals Close or Practices Where Needed...

Declines in Health Care Delivery Despite Increases in Health Spending - If We Keep Accelerating Non-Delivery Costs, We Can Continue to Remain Behind Health Care Demand

Blogs indicate that primary care can be recovered and should be recovered.

Dr. Bowman is the North American Co-Editor of Rural and Remote Health. He was the founding chair of the Rural Medical Educators Group of the National Rural Health Association and the long term chair of the STFM Group on Rural Health.


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