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A National Study of Chronic Disease Prevalence and Access to Care in Uninsured U.S. Adults

Andrew P. Wilper, MD, MPH; Steffie Woolhandler, MD, MPH; Karen E. Lasser, MD, MPH; Danny McCormick, MD, MPH; David H. Bor, MD; and David U. Himmelstein, MD
[+] Article and Author Information

From Cambridge Health Alliance/Harvard Medical School, Cambridge, Massachusetts.


Acknowledgment: The authors thank John Z. Ayanian, MD, and Sarah Hollopeter, MD, for their comments on an earlier draft of the manuscript, and Amy Cohen, Manager of Instructional Computing, Harvard School of Public Health, for her help with statistical software.

Grant Support: By Health Resources and Service Administration National Research Service Award 5T32 HP110011 (Dr. Wilper).

Potential Financial Conflicts of Interest: None disclosed.

Reproducible Research Statement:Study protocol: The NHANES methodology is available from the Centers for Disease Control and Prevention (http://www.cdc.gov/nchs/about/major/nhanes/datalink.htm.) Statistical code and data set: Available from Dr. Wilper (e-mail, awilper@hsph.harvard.edu).

Requests for Single Reprints: Andrew P. Wilper, MD, Cambridge Health Alliance/Harvard Medical School, 1493 Cambridge Street, Cambridge, MA 02139; e-mail, awilper@hsph.harvard.edu.

Current Author Addresses: Drs. Wilper, Woolhandler, Lasser, McCormick, Bor, and Himmelstein: Cambridge Health Alliance/Harvard Medical School, 1493 Cambridge Street, Cambridge, MA 02144.

Author Contributions: Conception and design: A.P. Wilper, S. Woolhandler, K.E. Lasser, D. McCormick, D.H. Bor, D.U. Himmelstein.

Analysis and interpretation of the data: A.P. Wilper, S. Woolhandler, K.E. Lasser, D. McCormick, D.U. Himmelstein.

Drafting of the article: A.P. Wilper, S. Woolhandler.

Critical revision of the article for important intellectual content: A.P. Wilper, S. Woolhandler, K.E. Lasser, D. McCormick, D.H. Bor, D.U. Himmelstein.

Final approval of the article: A.P. Wilper, S. Woolhandler, K.E. Lasser, D. McCormick, D.H. Bor, D.U. Himmelstein.

Statistical expertise: A.P. Wilper, S. Woolhandler, D.U. Himmelstein.

Obtaining of funding: D.H. Bor.

Administrative, technical, or logistic support: A.P. Wilper.

Collection and assembly of data: A.P. Wilper.


Ann Intern Med. 2008;149(3):170-176. doi:10.7326/0003-4819-149-3-200808050-00006
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Chronic illness is common among persons without insurance. We identified individuals without insurance who had a previous diagnosis of cardiovascular disease (1.3 million), hypertension (5.9 million), diabetes (1.4 million), hypercholesterolemia (4.0 million), active asthma or chronic obstructive pulmonary disease (3.5 million), and previous cancer (1.1 million). We estimate that nearly one third of nonelderly U.S. adults without insurance (that is, 11.4 million individuals) had at least 1 chronic condition. These findings counter notions that persons without insurance are a largely healthy population with little need for ongoing medical care.

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Figure.
Study flow diagram.

NHANES = National Health and Nutrition Examination Survey.

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Re: A National Study of Chronic Disease Prevalence and Access to Care in Uninsured U.S. Adults
Posted on September 9, 2008
Tim J. Stocker
University of California Davis Medical Center
Conflict of Interest: None Declared

We were pleased to see Wilper and colleagues[1] characterize the prevalence of chronic disease among the uninsured, and Dr. Chin's editorial advocating for more quality improvement efforts among vulnerable populations[2]. At the University of California Davis Medical Center, our HRSA-funded Transforming Education and Community Health (TEACH) program includes an inpatient service for uninsured patients run by a dedicated team of internal medicine residents who then assume longitudinal care for these patients in a Sacramento County safety net clinic. Recognizing the paucity of quality improvement efforts for the uninsured, we completed an American Board of Internal Medicine (ABIM) Diabetes Practice Improvement Module[3] which demonstrated that the TEACH clinic performs better than commercial managed care for many intermediate outcomes. Some of the lessons learned from this project may be useful to other community health centers seeking to improve their quality of care[4]:

1. Focus on processes of care and intermediate outcomes. Because of significant migration among uninsured populations (in our study few patients received continuous care over a two year period), hard clinical outcomes may not appreciably change after a given intervention. In contrast, chronic disease processes of care (e.g laboratory testing, dilated eye exams) and intermediate outcomes (e.g. hemoglobin A1c, blood pressure) can quickly improve if patients have access to care and adequate followup.

2. Imperfect data are better than no data. Data collection may be difficult due to ongoing use of paper rather than electronic medical records. Given limited resources, we decided to collect only the most clinically relevant data. Although we left many questions unanswered, we successfully identified several areas for improvement. For example, we found that the TEACH clinic performs worse than commercial managed care for dyslipidemia outcomes because providers do not escalate lipid-lowering therapy aggressively[4]. While academic rigor is important, we suggest first gathering data that is likely to guide future local interventions.

3. Utilize existing quality improvement resources. Quality improvement projects require significant "˜activation energy,' but there are resources available to jumpstart the process. We used the ABIM's Diabetes Practice Improvement Module, which streamlines both study design and data collection. After entering our data into the internet-based software, we received a report summarizing our clinic's processes of care and intermediate outcomes. Although the software has some limitations (it does not export data to conventional statistics applications), overall it greatly facilitated our project.

4. Choose a meaningful comparator. We elected to compare the TEACH clinic's performance to Medicaid and commercial managed care outcomes from the Healthcare Effectiveness Data and Information Set[5]. Medicaid best approximates our patients' socioeconomic status, while commercial managed care reflects usual care for the privately insured. These data sets are limited by lack of patient demographic information, but confounders can be minimized by matching the comparator's inclusion and exclusion criteria. We believe these data sets provide useful quality benchmarks for safety net clinics.

1. Wilper, A.P., et al., A national study of chronic disease prevalence and access to care in uninsured U.S. adults. Ann Intern Med, 2008. 149(3): p. 170-6.

2. Chin, M.H., Improving Care and Outcomes of the Uninsured with Chronic Disease . . . Now. Ann Intern Med, 2008. 149(3): p. 206-8.

3. Diabetes Practice Improvement Module. Available from: http://www.abim.org/pims/.

4. Stocker, T.J., Fancher, T.L. Comprehensive Diabetes Care for the Uninsured: Assessing How Internal Medicine Residents Perform. Presented at the Society of General Internal Medicine national meeting. 2008. Pittsburgh.

5. State of Health Care Quality. 2007, National Committee for Quality Assurance: Washington, D.C.

This study was supported by a Health Resources and Services Administration Title VII Grant for Training in Primary Care Medicine and Dentistry (Residency Training in Primary Care Internal Medicine) (D58HP05139-01-00) and the American Board of Internal Medicine F. Daniel Duffy Small Grants program.

Conflict of Interest:

None declared

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