This is Part 2 in a five-part series which presents a creative solution for today's health care crisis. Additional articles in the series can be found here: Part 1, Part 3, Part 4, and Part 5.

Variation in Health Care Affordability
To many people's surprise, few studies have reviewed health care affordability. Most analyze cost of health care, not affordability of health care. The AHP HCAI™ is one approach to analyze health care affordability. Table 1 presents information from the 2008 AHP HCAI™.

Table 1
2008 AHP Health Care Affordability Index

The above indices are the combined index reflecting the average of the employer index, the employee index and the government index. Table 1 shows that overall affordability varies widely from state to state. Table 2 compares 2008 results with those in the 2004 version. The ratios shown in the far right column show significant change over this time period.

Sorting the ratios in affordability from smallest to largest we find 20 states with an improved affordability index and 30 with a worsened one. Of the 20 improved states they average a 5% improvement. The 30 worsened states averaged a 6.5% decline.

For illustrative purposes, we will highlight three particular states through this series — California, Minnesota and Washington. All three states have a long history of favorable health care affordability, strong managed care presence and health care policy and thought leadership. Table 2 shows:

• California: still more affordable than average, but significant worsening (.82 to .87)
• Minnesota: still more affordable than average with a slight improvement (.94 to .92)
• Washington: still more affordable than average, but significant worsening (.85 to .91)

Any area with an affordability index change over a period of years is significant. This shows meaningful change and it needs to be monitored. As has been discussed in prior affordability analyses, the major factors correlated with levels of individual state indices are:

• Local hospital utilization rates (i.e., days/1,000)
• Local provider supply (i.e., beds/1,000 and MDs/1,000)
• Employee affordability index (i.e., out-of-pocket cost)
• Government affordability index (i.e., government funded tax burden for health care)

High correlation factors continue for these factors in the 2008 AHP HCAI™. The high correlation with these factors is interesting. Local hospital utilization rates have a direct impact on the affordability of health care. Regions with higher than average inpatient utilization rates have demonstrated less affordable health care. The regions with more health care providers are correlated with less affordable health care. Regions where employees consistently have to pay more for their health care have less affordable health care. Regions where the government funds a greater proportion of its taxes towards health care have less affordable health care.

In response to this one might ask these questions:

• If these items are so strongly correlated is there anything we can do to impact the item and eventually improve affordability?
• What can be done to further reduce hospital utilization rates?
• What should be done to impact the supply of providers? What can be done to impact the supply of providers?
• Should we change the way we allocate the cost between employers and employees? Is there a way to introduce lower costing alternatives to reduce the financial burden to employees?
• What more can be done to reduce the cost of government programs? Do government programs drive the cost of other programs? Is there something that can be changed regarding this?

Authors
David Axene collaborated with Nicholas Yphantides in writing this series of articles. Dr. Nicholas Yphantides serves as the Consulting Chief Medical Officer for San Diego County and is the National Director for Health & Wellness with Axene Health Partners. He is a cancer survivor and is an advocate for those in his community who need it the most. For nine years, Dr. Nick served as Chief Medical Officer of one the largest network of Community Clinics in San Diego County.