Medicaid Expansion Update: What is its Impact on Uninsured Rates?

In the early days of this blog, I wrote extensively on how states were rolling out Medicaid expansion under the Affordable Care Act (aka Obamacare or ACA).  The 2012 Supreme Court decision that upheld the ACA made Medicaid expansion optional for the states.  This expansion allows states to raise the income eligibility level from 100% of the federal poverty level to 133%.

The above map shows that 12 states still refuse to expand Medicaid 11 years after the ACA was passed while 31 states have expanded and 8 states have used different methods to expand.  The map below shows where each state stood on expansion in 2012.  

The census bureau has 2018 as the most recent year where estimates of the uninsured are available.  Thus, to assess the impact of Medicaid expansion, I will compare uninsured rates at the state level between 2010 (the year the ACA was passed) and 2018.  The states will be grouped by whether they refused to expand it in 2018 (19 states), implemented expansion by 2018 (26 states), or implemented it with other methods (6 states).

	Expanded by 2018	2010		2018		Change in %
	N	M	SD	M	SD
none	19	18.6%	4.2%	12.5%	3.0%	6.1%
yes	26	14.6%	4.5%	7.6%	2.5%	7.0%
modified	6	16.0%	3.3%	8.7%	2.4%	7.4%

The table above shows the mean uninsured rates for each group of states with respect to Medicaid expansion.  There was a significant decrease in the uninsured in all three groups due to the implementation of other parts of the ACA.  The states that did not expand Medicaid had higher baseline mean or average uninsured rates at 18.6% compared to 14.6% for those that expanded traditionally and 16.0% for those who expanded using modified methods by 2018.  The uninsured rates for 2018 showed a wider gap in uninsured rates between states that did not expand (12.5%) and the other two groups (7.6% and 8.7% respectively). The standard deviation or SD's show less variability in uninsured rates in all three groups by 2018.

These numbers show that the ACA is having an impact on uninsured rates throughout the U.S.  Medicaid expansion increases this effect in states that have implemented it.  There is still a group of uninsured even in states that have implemented expansion.  A much harder number to measure is the number of uninsured individuals in then U.S.  Further steps will be needed to reach universal coverage.

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PBS Program on Data and Pandemics

PBS has a good series on how medicine has learned to fight pandemics.  This particular episode focuses on how data is used to understand and limit pandemics.  It starts with how William Farr used data to track a cholera outbreak.  I've embedded this episode here for your enjoyment and information.

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Why do African Americans live to be 64.8 years in Cambria County? Not drug overdoses.

Some Clues for Racial Disparities for Cambria County

Last week I posted on the racial disparities in health outcomes in Cambria County.  These disparities are primarily what is driving the low rankings for the county in the County Health Rankings.

County Health Rankings provides a wealth of statistics called health factors which provide clues to these disparities.  Here is a list:

• 9% of the live births in the county from 2013-2019 are low birthweight which is 1% higher then the state rate. 16% of African American births are low birthweight compared to 12% of Hispanic and 6% of Caucasian births. in the county
• The teen birth rate is 20 per 1,000 live births from 2013-2019 compared to 17/1,000 for PA.  For African Americans it is 54/1,000, 19/1,000 for Hispanics, and 18/1,000 in the county.
  
• The drug overdose death rate from 2017-2019 was 52 per 100,000 for the county.  For Pennsylvania it is 37/100,000.  For African-Americans the rate was 112/100,000  and for Caucasians it was 50/100,000.  According to the website Overdose free PA, there were 18 overdose deaths among African Americans (orange bar in the above graph) in the county from 2017-2019 out of 204 total overdose deaths or 8% of the total.

• The rate of preventable hospital stays per 100,000 Medicare enrollees for 2018 is 5,762 in the county compared 4464 for PA.  The African American Rate is 6,154 while it is 5,779 for Caucasians in the county.
  
• The rate of mammography screening is 42% for the county for Medicare enrollees for 2018 while it is 45% for the county.  For African Americans it is 31% compared to 38% for Asians, 50% for Hispanics, and 42% of Caucasians in the county.
• The rate of flu vaccinations is 41% overall for the county for Medicare enrollees in 2018 compared to 53% for PA.  For African Americans the rate was 36% in the county while it was 45% for Asians and Hispanics and 41% for Caucasians.
• The overall rate of child poverty was 23% for the county for 2019 while it was 17% for PA.  For African Americans it was 67% in the county while it was 19% for Asians, 42% for Hispanics, and 20% for Caucasians.
• Median income in the county was $48,800 for 2019 while it was $63,500 in PA.  For African Americans it was 18,900 in the county while for Asians it was $90,000, for Hispanics it was $35,100, and for Caucasians it was $48,100.
• The injury death rate was 128 per 100,000 for the county from 2015-2019 while it was 89/100,000 for PA.  For African-Americans it was 221/100,000 and 126/100,000 for Caucasians in the county.
• The homicide death rate was 6/100,000 for the county from 2013-2019 while it was 5/100,000 from 2013-2019.  For African Americans it was 50/100,000 while it was 4/100,000 for Caucasians in the county.
• For firearm fatalities the rate was 16/100,000 from 2015-2019 while it was 12/100,000 for PA.  For African Americans it was 41/100,000 and 15/100,000 for Caucasians in the county.
• For reading scores, the average grade level was 3.1 for 3rd graders in both the County and PA in 2018.  For African Americans it was at a 2.2 grade level and 3.2 for Caucasians in the county.
• For math scores, the average grade level for 3rd graders was 3.1 for both the county and PA in 2018.  For African Americans it was at a 2.0 grade level and 3.2 for Caucasians in the county
• Finally the % of residents who drive alone to work for the county was 82% from 2015-2019 while it was 76% for PA.  For African Americans, 62% drives alone to work in the county while it was 65% for Hispanics and 84% for Caucasians.  This could be due to African Americans and Hispanics being more likely to rely on public transportation to get to work.

These 14 statistics provide some clues to the nature of the racial/ethnic disparities in Cambria County.  They suggest violence and poverty as the main explanatory factors.  One must be careful not to assume that they tell the whole story.  They do provide some clues to where public health resources need to be allocated.  It remains to be seen how the Coronavirus pandemic will interact with these health issues.

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Testing and New Cases Declined in Cambria County While The Positive Test Rate Remains High

The graph above shows how the rise in cases appears to be levelling off in Cambria County since Donald Trump came here on October 13. The 7 day average for new cases reached a high of 214.29 on Dec 11 and has steadily decreased to 96.57 on Dec 25 (a 54.7% decrease) as can be seen in the solid black line in the graph below.

Also in the graph above we see that the 7 day average number of test results presented per day in the county (dotted red line in the graph) also decreased from 335 per day on Dec 11 and also decreased to 182 per day on Dec 25, a decrease of 45.7% over the same period.  This is a 9% smaller rate of decrease than that of cases in the county.

This graph above shows how the cumulative positive testing rates for the county (dotted blue line), Pennsylvania (red line), and the U.S. (yellow line).  The 7 day average for positive tests peaked at 68.29% on Dec 8 to 53.14% on Dec 25.  This is only a 22.2% decrease which is smaller than the decrease in cases and testing.  

On December 13 I posted on how the % of test results (46.8% today) for Greater Johnstown (zip codes 15901 thru 15909) was higher than the % of positive cases there (41.1% today).  This suggests that the cumulative testing rate for Johnstown is 31.48% while it is 35.74% for the rest of the county, a 13.53% increase outside of Johnstown.  The cumulative positive testing rate is 16.71% for Greater Johnstown while for the rest of the county it is 21.15%, a 26.54% increase.

While it is encouraging to watch the number of new positive cases decrease in Cambria County, the smaller decrease in the positive cases suggests that there may be more cases that are being missed, especially outside of Greater Johnstown.  The 7 day average for deaths in the county peaked at 8.14 per day on December 17 and decreased to 5 per day this Christmas day.  The peak in deaths came 6 days after the peak in cases in the county.  Lets hope the trend continues.  The Governor's order against dine in restaurant eating and gym us appears to be curtailing the rise in cases.  I wish I had better news this Christmas night.

**Update**

Dave Sutor of the Tribune Democrat has tweeted that Conemaugh Memorial hospital has rented refrigerator trailers to handle possible over crowding at the morgue.

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Season's Shootings

A Wave of Deaths in Blair County

I have written extensively about the surge in corona virus cases in Cambria County.  Recently there has been a surge in cases and deaths in in Blair County as can be seen in the image above (22 since July 21).  Centre County has seen a larger surge in cases since the Penn State students have come back but has had only four deaths since July 21.  

Looking at the numbers for Blair County more in depth, there are 887 total cases (31 probable +856 confirmed) and 18,865 total negative results.  This gives a total of 19,752 total tests and a positive rate of 4.49%.  The case rate of 728.07 per 100,000 ranks 39th in the state out of 67 counties.

The county's case mortality rate of 2.59% ranks 38th in the state.  The mortality rate of 18.88 deaths per 100,000 ranks 36th in the state.  

One hundred fifty three of the 887 cases are in a nursing home (17.2% of the total) in 13 facilities.  One hundred and ten of these nursing home cases are residents and 43 are staff members.  Thirteen of the 23 deaths or 56.5% of the total are in nursing homes.  By comparison, 10.49% of Cambria County's cases are in a nursing home and no deaths have been reported there.

The PA Department of Health reports that 8 cases are hospitalized and 4 are on ventilators.  The hospitalization rate is 6.57 per 100,00 ranking 16th in the state.  The ventilator rate is 3.28 per 100,000 and ranks third in the state.

The high rate of hospitalization, nursing home cases and deaths, and ventilator use relative to the number of cases in Blair County suggests a greater severity of these cases.  Without access to contact tracing data, it's hard to say why this is the case.

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Testing Rates Have Decreased in Cambria County as Cases Keep Rising

One week ago, Cambria County surpassed 400 cases of COVID-19.  This can be seen in the graph above.  Since then the number of new cases has tapered off.

On August 11 the 7 day average for new cases in the county was 11.14 cases per day.  As of today, it is 7.29 cases per day.  The graph above shows that the positive testing rate has increased in the county while it has decreased or remained the same for the US and Pennsylvania.  

The graph above shows the trend in the cumulative cases (red line), the number of tests per day (blue bars), and the 7 day average of tests per day.  The decrease in the testing average occurred after August 5 when the number of cases passed 300 (with a brief spike on August 10).  That day there was an increase of 30 cases.  The increase was primarily at the federal prison in Loretto. 

I don't have a very good explanation for the decrease in testing after the outbreak at the prison.  Carnegie Mellon's COVID Cast website has indicators to predict future cases such as doctor visits, and survey's of symptoms on Facebook.  The graph at the left shows that the composite of indicators has remained relatively steady.  I hope that the decrease is just an aberration.

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A Look at Positive COVID-19 Testing Rates in Cambria, PA, and the US

There have been recent media reports about positive testing rates increasing in Pennsylvania.  I thought I would take a closer look at positive test rates since they were reported by the state on April 17. The positive testing rate is simply the number of positive tests divided by the total number of tests.  The graph above shows the cumulative positive test rates for the US (orange line), PA (red line), and Cambria County (blue dotted line).  The black line shows the daily positive testing rate for Cambria County.  

The positive rate for the state has been consistently higher than the US and county rates.  Both rates have been decreasing as testing has become more readily available.  Cambria's positivity rate has been consistently lower than the state and US rates.  The daily testing rate for the county on April 13 was high because on that day there were three positive tests out of 16 total tests (18.25%).  

Since June 24, the cumulative positive test rate increased from 1.02% to 1.28% as of today.  This rise may not sound like much but the solid black line shows positive rates that were consistently at or above the cumulative rates for this period with one day being higher than 5% on July 11.  

The graph above is from the Johns-Hopkins Univeristy site tracking the Corona Virus Pandemic.  It shows the trend in testing for the US during the pandemic.  The blue line shows the seven day average of positive test % with a steady decrease from early April (21.9%) until the middle of June (4.4%) with an increase to 8.7% today.

This graph shows the trend in testing for the state of Pennsylvania for the same period.  Here, we see that there was a corresponding peak in mid April in the positive rate at 27.8% to 3.4% around June 21.  This decrease was followed by an increase to 5.5% as of today.  We can see that testing has risen at a slower rate in the state than in the US as a whole.

The black line in the graph at the top was replaced with the 7 day moving average in testing which does show a rise in positive tests after June 24.  I did not have the same access to 

testing data that Johns-Hopkins had.  I used publicly available data that the PA health department provided beginning on April 17.  

The graph below shows the comparison of the positive testing rate (in the red line) to the testing rate as a percentage of the population for six Johnstown zip codes, the overall rates for Greater Johnstown, Cambria County, Pennsylvania, and the US. These rates are cumulative.  The numbers at the top of each bar are the cumulative testing rates as a percentage of the population.  It's interesting that the state has a higher cumulative positive rate (10.08%) than its testing rate (7.57%).  Johns-Hopkins testing tracker has the state ranked 47th in the testing rates over the last two weeks (1.1 per 1,000) while it ranks 37th in the two week average positive testing rate (5.5%).  At the bottom is a summary of testing data for Pennsylvania.  How one frames the statistics makes all the difference.

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Update on Johnstown Zip Code Testing

Last week I reported that my most viewed post on COVID-19 was on zip code testing in Johnstown zip codes compared to the county, state and the U.S.  I reported that the testing rates for the zip code for downtown Johnstown (15901) was nearly identical to the U.S. rates while the rates for the other zip codes and the county lagged behind the state and the U.S. rates.  I reposted the chart from that post above. 

 

As I was tracking the testing rates I noticed that the pattern was changing in the testing rates.  You can see that pattern in the bar chart above from the Google Sheets I put together for the county.  The rate for 15901 is still the highest in the city but it is falling behind the U.S. rate. The 15902 zip code has been inching upwards while the 15909 zip code lags behind the others and the county.  

I updated the line chart at the top of the post with the trend in testing up to the current date.  I got rid of the data table to make it more readable. In the chart we see that the testing rate for 15901 started to fall behind the U.S. rate on May 29. The post for the chart at the top was on May 17.  

The 15902 zip code (red dotted line) testing rate has nudged ahead of the state rate (solid black line.  Finally we see that the 15909 zip code has fallen further behind the other zip codes and the state and county overall in the testing rates on May 26.  

The number of COVID-19 cases in the county on May 17 was 54.  Today (27 days later) it is 61.  The 15902 zip code (Hornerstown and Moxham) now has a cluster of five confirmed cases and between 1 and 4 probable cases (the exact number is not released for privacy concerns) while 15901 has between 1 and 4 confirmed cases according to the PA Department of Health.  

Does the lag in testing account for the decrease in the number of new cases for the county?  I suppose only God knows for sure.  The COVID cast website shows a decrease in the indicators that they use to forecast the future cases from may 17 to May 31.  These indicators include doctor visits with COVID-19 symptoms, google search data, and Facebook search data.  After May 31 the indicators has leveled off which suggests that a surge in cases is not imminent.  Dr. Fauci has warned that a surge could happen as the states have been reopening.  So far it has yet to materialize in Cambria County.  Time will tell.

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A Comparison of State Mortality Rates: Pennsylvania is 6th Highest, Michigan is Highest

In my last post I spoke of how Pennsylvania's case mortality rate (7.16%) was greater than the U.S. rate (5.91%).  At the time I was unsure how the state compared to the other states in the case mortality rate.  To do this I looked at the cases reported on Johns-Hopkins Coronavirus Dashboard.  The numbers that they report for Pennsylvania (74,045 cases, 5,373 deaths) are different than reported by the state department of health (70,042 cases, 5,373 deaths).  This is due to Johns-Hopkins relying on media reports of cases as well as government reports.  Deaths from the disease are easier to track than cases.

The case mortality rate is the number of deaths divided by the number of reported cases.  The numbers for each state as of yesterday are displayed at the table below.  Johns-Hopkins reports cases and deaths on the U.S. flagged Grand Princess and Diamond Princess cruise ships are included in the total.  Michigan has the highest case mortality rate at 9.59% followed by Connecticut at 9.21%, the U.S. Virgin Islands at 8.70%, New York at 8.08%, New Jersey at 7.24%, and Pennsylvania at 7.16%.  The high rate for Michigan is troubling given all of the protests against the coronavirus lockdown there.

Looking at the population adjusted mortality rate as deaths per 100,000 population, not surprisingly, New York has the highest rate at 151.56/100,000 followed by New Jersey at 127.66/100,000, Connecticut at 106.67/100,000, Massachusetts at 93.91/100,000, and the District of Columbia at 63.05/100,000.  Pennsylvania is 9th on this measure (41.13/100,000) and is right behind Michigan which is at 53.41/100,000.

New York is also first in coronavirus cases at 1,876.08/100,000 followed by New Jersey at 1763.39/100,000, Massachusetts at 1359.35/100,000, Rhode Island at 1354.87/100,000, and the District of Columbia at 1191.08/100,000.  Pennsylvania is 13th on this measure at 574.57/100,000 which is just ahead of Michigan which is at 556.84/100,000.  The U.S rate on this measure is 514.95/100,000.  

The graph above shows the state case mortality rate by population (the two cruise ships are excluded).  There is no linear association between the state's population and their case mortality rate.  The line crossing the graph just below 6% is the U.S. case mortality rate.  

The population rates indicate the prevalence in the population of coronavirus cases and deaths.  The case mortality rates are an indication of the strain that the disease has placed on the health care systems in that state.  Michigan Pennsylvania, and the Virgin Islands with low population adjusted mortality rates but high case mortality rates suggest additional strain.

State	cases	deaths	Case Mortality	case mortality rank	Population	Deaths per 100,000	Cases per 100,000
Michigan	55611	5334	9.59%	1	9,986,857	53.41	556.84
Connecticut	41288	3803	9.21%	2	3,565,287	106.67	1158.06
Virgin Islands	69	6	8.70%	3	104,901	5.72	65.78
New York	364965	29484	8.08%	4	19,453,561	151.56	1876.08
New Jersey	156628	11339	7.24%	5	8,882,190	127.66	1763.39
Pennsylvania	73557	5265	7.16%	6	12,801,989	41.13	574.57
Louisiana	38497	2723	7.07%	7	4,648,794	58.57	828.11
Massachusetts	93693	6473	6.91%	8	6,892,503	93.91	1359.35
Indiana	32437	2030	6.26%	9	6,732,219	30.15	481.82
Ohio	33439	2044	6.11%	10	11,689,100	17.49	286.07
Colorado	24754	1392	5.62%	11	5,758,736	24.17	429.85
Vermont	971	54	5.56%	12	623,989	8.65	155.61
Missouri	12798	688	5.38%	13	6,137,428	11.21	208.52
Washington	20181	1078	5.34%	14	7,614,893	14.16	265.02
DC	8406	445	5.29%	15	705,749	63.05	1191.08
Oklahoma	6229	322	5.17%	16	3,956,971	8.14	157.42
New Hampshire	4231	214	5.06%	17	1,359,711	15.74	311.17
Maryland	48423	2392	4.94%	18	6,045,680	39.57	800.95
Nevada	8113	396	4.88%	19	3,080,156	12.86	263.40
Arizona	17277	834	4.83%	20	7,278,717	11.46	237.36
Mississippi	14044	670	4.77%	21	2,976,149	22.51	471.88
Rhode Island	14353	655	4.56%	22	1,059,361	61.83	1354.87
New Mexico	7252	329	4.54%	23	2,096,829	15.69	345.86
Illinois	114306	5083	4.45%	24	12,671,821	40.11	902.05
Kentucky	9077	400	4.41%	25	4,467,673	8.95	203.17
Florida	52634	2319	4.41%	26	21,477,737	10.80	245.06
South Carolina	10623	466	4.39%	27	5,148,714	9.05	206.32
Georgia	44445	1908	4.29%	28	10,617,423	17.97	418.60
Minnesota	22464	942	4.19%	29	5,639,632	16.70	398.32
West Virginia	1899	74	3.90%	30	1,792,147	4.13	105.96
California	101032	3895	3.86%	31	39,512,223	9.86	255.70
Puerto Rico	3397	129	3.80%	32	3,193,694	4.04	106.37
Maine	2137	81	3.79%	33	1,344,212	6.03	158.98
Delaware	9096	344	3.78%	34	973,764	35.33	934.11
Alabama	15843	583	3.68%	35	4,903,185	11.89	323.12
Oregon	4038	148	3.67%	36	4,217,737	3.51	95.74
Montana	481	17	3.53%	37	1,068,778	1.59	45.00
North Carolina	24896	838	3.37%	38	10,488,084	7.99	237.37
Wisconsin	16462	539	3.27%	39	5,822,434	9.26	282.73
Virginia	40249	1281	3.18%	40	8,535,519	15.01	471.55
Idaho	2699	81	3.00%	41	1,787,065	4.53	151.03
Guam	170	5	2.94%	42	165,768	3.02	102.55
Grand Princess	103	3	2.91%	43
Texas	58537	1581	2.70%	44	28,995,881	5.45	201.88
Iowa	18360	493	2.69%	45	3,155,070	15.63	581.92
Hawaii	644	17	2.64%	46	1,415,872	1.20	45.48
Alaska	411	10	2.43%	47	731,545	1.37	56.18
North Dakota	2439	56	2.30%	48	762,062	7.35	320.05
Kansas	9270	212	2.29%	49	2,913,314	7.28	318.19
Arkansas	6277	120	1.91%	50	3,017,804	3.98	208.00
Tennessee	21288	353	1.66%	51	6,829,174	5.17	311.72
Wyoming	860	14	1.63%	52	578,759	2.42	148.59
Nebraska	12619	153	1.21%	53	1,934,408	7.91	652.34
Utah	8706	105	1.21%	54	3,205,958	3.28	271.56
South Dakota	4710	54	1.15%	55	884,659	6.10	532.41
Diamond Princess	49	0	0.00%	57
N Mariana	22	0	0.00%	57	56,882	0.00	38.68
Total	1697459	100274	5.91%		329,637,350	30.42	514.95

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