Monitoring the Health Care Safety Net

Slide Presentation by John Billings, J.D. and Robin M. Weinick, Ph.D.


On September 23, 2003, John Billings, J.D. and Robin M. Weinick, Ph.D. made a presentation in the Web-Assisted Audioconference entitled Monitoring the Health Care Safety Net.

This is the text version of Mr. Billings and Dr. Weinick's slide presentation. Select to access the PowerPoint® slides (6.7 MB).


Monitoring the Health Care Safety Net

Agency for Healthcare Research and Quality
Health Resources and Services Administration

John Billings, J.D.
Robin M. Weinick, Ph.D.

Slide 1

Goals of Initiative

Slide 2

Areas Included in Data Book

The slide contains a map of the United States. It is color-coded to show, by county, rural counties included in the data book and urban counties included in the data book. States that do not have counties included in the data books include: Alaska, Montana, Idaho, Wyoming, North Dakota, South Dakota, Nebraska, New Mexico, Texas, Oklahoma, Louisiana, Mississippi, Alabama, Vermont, New Hampshire, Ohio, Indiana, West Virginia, Kentucky.

Slide 3

Monitoring the Safety Net: The Conceptual Model

Slide 4

Monitoring the Safety Net: More Complete Model

This slide shows a flow chart for monitoring the safety net. On the left is a column of components of optimal health. It includes genetics, environment, lifestyle/behavior, personal health maintenance, care availability, provider performance, and disease/condition management. Of those components, care availability and provider performance are included in the health care safety net. Arrows are drawn between this column to the middle column, which lists the mediating factors. The mediating factors are divided into two categories: personal factors and contextual factors. Personal factors include health knowledge, perceptions of system, personal characteristics, personal resources, and personal circumstances. Contextual factors include health delivery system, public health system, community environment, community infrastructure, neighborhood characteristics, civic environment/civil culture, and state/national policies. These mediating factors lead to optimal health, which is the sole term in the column on the right.

Slide 5

Monitoring the Safety Net: Types of Measures

Slide 6

This slides show Figure 3-1: Percent of Population Under 200 Percent of Poverty Uninsured Metropolitan Areas in 1999. The y axis is the percent uninsured, from 0 to 60 percent, and the x axis is divided into Northeast, South, Midwest, and West. The area on the graph with the highest percent uninsured (approximately 58 percent) is Augusta; and the area on the graph with the lowest percent uninsured (approximately 12 percent) is Springfield. In the Northeast, the low is Springfield, middle is Boston, and high is Jersey City. In the South, the low is Chattanooga, middle is Little Rock, and high is Augusta. In the Midwest, the low is St. Louis, middle is Minneapolis, and high is Chicago. In the West, the low is Tacoma, middle is San Diego, and high is San Francisco.

The bottom of the slide says "Each [diamond] represents a metropolitan area [not all areas are identified]."

Slide 7

This slide shows Figure 3-3: Percent of Population Below Poverty and Percent Uninsured Adults Ages 18-64 Metropolitan Areas in 2000. The y axis is the percent population uninsured, from 0 to 60 percent, and the x axis is percent population below federal poverty level, from 0 to 30 percent. R squared equals .074. The squares (each represents an MSA area) appear to be clustered between 5 and 15 percent on the x axis, and 10 to 50 percent on the y axis.

Slide 8

This slide shows Figure 4-3: Percent of Population Below 200 Percent of Poverty on Medicaid Metropolitan Areas. The y axis is the percent on Medicaid, from 0 to 80 percent, and the x axis is divided into Northeast, South, Midwest, and West. The area on the graph with the highest percent on Medicaid (approximately 74 percent) is Augusta; and the area on the graph with the lowest percent on Medicaid (approximately 14 percent) is Las Vegas. In the Northeast, the low is New Haven, middle is New York, and high is Springfield. In the South, the low is Melbourne, middle is Charlotte, and high is Knoxville. In the Midwest, the low is Wichita, middle is Kansas City, and high is Lansing. In the West, the low is Las Vegas, middle is San Diego, and high is Tacoma.

The bottom of the slide says "Each [diamond] represents a metropolitan area [not all areas are identified]."

Slide 9

This slide shows Table 4-4: Community Health Centers and County-Level Poverty. It shows the Percent of County Population Below Federal Poverty Level in 2000 (left column) and the Percent of Counties with Community Health Centers 1999 (right column). The left and right columns match up in the following way: less than 6 percent=15.9 percent; 6 percent to 9.9 percent=51.7 percent; 10 percent to 20 percent=77.8 percent; more than 20 percent=92.3 percent; all counties=56. 6. percent.

Slide 10

This slide shows Table 5-7: A Tale of Two Cities: Portland, Oregon and Newark, New Jersey, 1999. In the Portland, Oregon MSA, the HMO Market Penetration=47.5 percent; the physicians per 100,000 persons=70.4; the hospital beds per 1,000 persons=1.7; emergency department visits per 1,000 persons=253.1; and cost shifting index=5.7. In the Newark, New Jersey MSA, the HMO Market Penetration=24.9 percent; physicians per 100,000 persons=110.2; hospital beds per 1,000 persons=3.6; emergency department visits per 1,000 persons=390.2; and cost shifting index=21.0.

Slide 11

This slide shows Table 5-8: A Tale of Two Counties: Orange County and San Francisco, California, 1999. In Orange County, the percent of admissions in public hospitals=0.0; the percent of not-for-profit hospitals=61.5; the percent of investor-owned hospitals=38.5; the percent of admissions in major teaching hospitals=0.0; the percent of admissions in other teaching hospitals=25.2; and the percent of admissions in non-teaching hospitals=74.8. In San Francisco City and County, the percent of admissions in public hospitals=21.2; the percent of admissions in not-for-profit hospitals=78.8; the percent of admissions investor-owned hospitals=0.0; the percent of admissions in major teaching hospitals=51.4; the percent of admissions in other teaching hospitals=16.7; and the percent admissions in non-teaching hospitals=31.9.

Slide 12

Monitoring the Safety Net: Types of Measures

Community Context

Slide 13

Monitoring the Safety Net: Types of Measures

Outcomes/Safety Net Performance

Slide 14

This slide shows Figure 7-1: Preventable/Avoidable Hospitalizations Per 1,000 Children Ages 0-17 Metropolitan Areas in 1999. The y axis is the number of preventable hospitalizations per 1,000 children, from 0 to 30, and the x axis is divided into Northeast, South, Midwest, and West. The metropolitan area with the highest number of preventable hospitalizations (approximately 25) is Jersey City, and the metropolitan area with the lowest number of preventable hospitalizations (approximately 5) is Portland. In the Northeast, the low is Rochester, middle is Philadelphia, and high is Jersey City. In the South, the low is Atlanta, middle is Washington, D.C., and the high is Richmond. In the Midwest, the low is Grand Rapids, middle is Milwaukee, and high is Saginaw. In the West, the low is Portland, middle is Las Vega, and high is Riverside.

The bottom of the slide says "Each [diamond] represents a metropolitan area [not all areas are identified]."

Slide 15

This slide shows Figure 7-6: Preventable/Avoidable Hospitalizations (Children Ages 0-17) and Percent of the Population Below Poverty Cities, County Residuals, and Suburban Counties in 1999. The y axis is the preventable hospitalizations per 1,000 children, from 0 to 35, and the x axis is the percent of population below poverty, from 0 to 35 percent. R squared equals .341. The squares appear to be concentrated on the x axis between 2 and 15 percent, and on the y axis between 2 and 15.

The bottom of the slide says "Each [square] represents a city/county/county "residual" area."

Slide 16

This slide shows Figure 7-7: Preventable/Avoidable Hospitalizations (Adults Ages 40-64) and Percent of the Population Below Poverty Cities, County Residuals, and Suburban Counties in 1999. The y axis is the preventable hospitalizations per 1,000 adults, from 0 to 35, and the x axis is the percent of population below poverty, from 0 to 35 percent. R squared equals .531. The squares appear to be concentrated on the x axis between 2 and 15 percent, and on the y axis between 5 and 20.

The bottom of the slide says "Each [square] represents a city/county/county "residual" area."

Slide 17

Multivariate Results

Federal and state financing of the safety net helps

Public facilities matter

Slide 18

Multivariate Results

More providers is not always the answer

Levels of personal distress are a concern

Slide 19

Data Products

Two print volumes

Electronic files

http://www.ahrq.gov/data/safetynet

Slide 20

This slide shows a Web page with URL address. It serves as an example of the Safety Net Profile Tool. The Web site can be accessed at http://63.107.122.40/AllVersions/SafetyNet.006/SafetyNet.asp. The Web page says "With the Safety Net Profile Tool, you have easy access to all the data included in the Safety Net Monitoring Initiative. More than 120 measures are available for 30 states and the District of Columbia, including 355 counties and 172 cities in 90 metropolitan areas, as well as all 1,818 counties (both metropolitan and non-metropolitan) in those states. The Profile Tool will guide you step-by-step to obtain the statistics you need, and can be used to generate reports the compare multiple measures for one or more geographic areas.

The data in the Profile tool comes from the books, "Monitoring the Health Care Safety Net - Book 1: A Data Book for Metropolital Areas" and "Monitoring the Health Care Safety Net - Book 2: A Data Gook for States and Counties." In addition to this Profile Tool, these data are available in a variety of electronic formats."

Slide 21

This slide shows a Web page with URL address. It serves as an example of the Safety Net Profile Tool. The Web site can be accessed at http://63.107.122.40/AllVersions/SafetyNet.006/SafetyNet.asp. The Web page is titled "Choose Type of Geographic Area." It says "The Safety Net Monitoring Initiative includes data on metropolitan areas, counties, and states. Please choose one of the following for this data query: metropolitan areas (data from 90 metropolitan statistical areas (MSAs), including separate data on all the counties and a selection of the cities included in each area), counties (data from 1,818 counties including 355 counties in metropolitan areas and 1,463 counties in non-metropolitan areas, a number of independent cities are included in this category), and states (data from 30 states).

Slide 22

This slide shows a Web page with URL address. It serves as an example of the Safety Net Profile Tool. The Web site can be accessed at http://63.107.122.40/AllVersions/SafetyNet.006/SafetyNet.asp. The page is titled "Choose Measures," and provides an example of Minneapolis-St. Paul, MN as the Metropolitan Area; and Orange County, CA and Phoenix-Mesa, AZ as Comparison Areas. It says "Which data are you interested in: Demand for Safety Net Services (includes 10 measures of uninsurance, poverty, disability, and AIDS) or Financial Support for Safety Net Services (includes 6 measures related to Medicaid, Disproportionate Share Hospital payments, Community Health Centers, and Uncompensated Care Pooling)."

Slide 23

This slide shows a Web page with URL address. It serves as an example of the Safety Net Profile Tool. The Web site can be accessed at http://63.107.122.40/AllVersions/SafetyNet.006/SafetyNet.asp. This slide provides a table of "Demand for Safety Net Services" in Minneapolis-St Paul, Orange County, and Phoenix.

Current as of February 2004


Internet Citation:

Monitoring the Health Care Safety Net. Text Version of a Slide Presentation at a Web-assisted Audioconference. Agency for Healthcare Research and Quality, Rockville, MD. http://www.ahrq.gov/news/ulp/safetynetaud/sess1/weinicktxt.htm


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