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Older patients from at-risk neighborhoods more likely to return to the hospital
MADISON, Wis. — If hospitals want to better predict which older adult patients are likely to be readmitted, they need only check the patients’ zip codes.
A new University of Wisconsin study shows that the risk of living in a disadvantaged neighborhood is similar to that of having a chronic lung disease, like emphysema, and worse than that of health conditions such as diabetes when it comes to putting people back in the hospital. The study also suggests that patients from disadvantaged neighborhoods are at greater risk for rehospitalization regardless of their treating hospital.
“We’ve long known that health is impacted by more than biological factors,” says lead author Dr. Amy Kind, assistant professor of medicine at the UW School of Medicine and Public Health. “The social context of where you live is incredibly important to keeping you healthy. Some neighborhoods can support people who are ill better than others.”
The study, published today in the Annals of Internal Medicine, looked at more than 250,000 Medicare patients hospitalized between 2004 and 2009 for diagnoses of pneumonia, heart attack or congestive heart failure.
It found that Medicare patients living in the most disadvantaged 15 percent of neighborhoods are readmitted to the hospital within 30 days at a rate of 22 to 27 percent, compared to a 21 percent readmission rate for the other 85 percent of neighborhoods. The more disadvantaged the neighborhood – as rated by the Area Deprivation Index or ADI – the more likely the patients will return to the hospital.
While those differences may seem small, they’re likely to catch the attention of hospitals, which are now being fined by Medicare if they have too many patients readmitted.
Kind says the results aren’t surprising. As people age, they often rely more on a network of community and family members to support their living at home, especially soon after a hospitalization. If family and neighbors are also under stress due to poverty, poor housing, unemployment and other struggles, they are less able to help the person stay healthy at home.
The neighborhood approach could be a more efficient way to quickly help inform who will need more support. The UW Health Innovation program will have an online calculator at www.HIPxChange.org that health providers can check to see which patients are being discharged to higher risk neighborhoods. It combines the neighborhood’s ADI and its zip+4 code, which breaks most zip codes into neighborhoods of about 1,500 people.
A map created by the research shows that many disadvantaged neighborhoods are spread through inner city neighborhoods and rural America, with concentrations in Appalachia, the Mississippi Delta, the Great Plains and Native American reservations. Some regions of the US have much larger older adult populations living in disadvantaged neighborhoods than others. The Dallas, Kansas City, Atlanta and Philadelphia regions have the most seniors living in neighborhoods that are disadvantaged, while the Seattle, Boston and San Francisco regions have the least.
Some European countries already use a similar geographic model to help decide where to target health resources.
“This could be used to inform policy and create innovative programs to target certain at-risk neighborhoods,” says Kind. For example, Kind helped create a program for the Veterans’ Administration system that has nurses call patients at home to provide intensive support to them when they leave the hospital.
This study also adds to the debate regarding the concerns of hospitals that contend they are being unfairly penalized by Medicare because they serve populations from disadvantaged neighborhoods
Kind’s UW collaborators include Dr. Menggang Yu, of biostatistics; Dr. Christie Bartels of medicine, Dr. William Ehlenbach, of medicine; Dr. Caprice Greenberg, of surgery and Dr. Maureen Smith of population health sciences. Former assistant surgeon general Dr. Steve Jencks and Dr. Jane Brock also contributed.
A link to the paper and supplementary material is available here: http://annals.org/article.
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This research was partly supported by a National Institute on Aging Beeson Career Development Award (K23AG034551), the Madison VA Geriatrics Research, Education and Clinical Center (GRECC-Manuscript #2013-13) and the Wisconsin Partnership Program.