Sandra L Decker

Agency for Healthcare Research and Quality, Роквилл, Maryland, United States

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Publications (31)169.34 Total impact

  • Brandy J Lipton · Sandra L Decker
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    ABSTRACT: Affordable Care Act provisions implemented in 2010 required insurance plans to offer dependent coverage to people ages 19-25 and to provide targeted preventive services with zero cost sharing. These provisions both increased the percentage of young adults with any source of health insurance coverage and improved the generosity of coverage. We examined how these provisions affected use of the human papillomavirus (HPV) vaccine, which is among the most expensive of recommended vaccines, among young adult women. Using 2008-12 data from the National Health Interview Survey, we estimated that the 2010 policy implementation increased the likelihood of HPV vaccine initiation and completion by 7.7 and 5.8 percentage points, respectively, for women ages 19-25 relative to a control group of women age 18 or 26. These estimates translate to approximately 1.1 million young women initiating and 854,000 young women completing the vaccine series. Project HOPE—The People-to-People Health Foundation, Inc.
    Health Affairs 05/2015; 34(5):757-64. DOI:10.1377/hlthaff.2014.1302 · 4.64 Impact Factor
  • Brandy J. Lipton · Sandra L. Decker
    Journal of Diabetes 05/2015; DOI:10.1111/1753-0407.12311 · 2.35 Impact Factor
  • Dhaval Dave · Sandra L. Decker · Robert Kaestner · Kosali I. Simon
    04/2015; 1(2):165-193. DOI:10.1162/AJHE_a_00011
  • Sandra L. Decker · Brandy J. Lipton
    MMWR. Morbidity and mortality weekly report 03/2015; 64(8):232-232.
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    Esther Hing · Sandra Decker · Eric Jamoom
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    ABSTRACT: In 2013, most office-based physicians (95.3%) were accepting new patients. The percentage of physicians accepting new Medicaid patients (68.9%) was lower than the percentage accepting new Medicare (83.7%) or new privately insured (84.7%) patients. The percentage of physicians accepting new Medicaid and Medicare patients was lower for physicians within metropolitan statistical areas (MSAs) compared with physicians outside of MSAs. The percentage of physicians who accepted new privately insured, Medicare, and Medicaid patients each varied by state. All material appearing in this report is in the public domain and may be reproduced or copied without permission; citation as to source, however, is appreciated.
    NCHS data brief 03/2015;
  • Pinka Chatterji · Sandra L. Decker · Sara Markowitz
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    ABSTRACT: As of 2014, 37 states have passed mandates requiring many private health insurance policies to cover diagnostic and treatment services for autism spectrum disorders (ASDs). We explore whether ASD mandates are associated with out-of-pocket costs, financial burden, and cost or insurance-related problems with access to treatment among privately insured children with special health care needs (CSHCNs). We use difference-in-difference and difference-in-difference-in-difference approaches, comparing pre–post mandate changes in outcomes among CSHCN who have ASD versus CSHCN other than ASD. Data come from the 2005 to 2006 and the 2009 to 2010 waves of the National Survey of CSHCN. Based on the model used, our findings show no statistically significant association between state ASD mandates and caregivers’ reports about financial burden, access to care, and unmet need for services. However, we do find some evidence that ASD mandates may have beneficial effects in states in which greater percentages of privately insured individuals are subject to the mandates. We caution that we do not study the characteristics of ASD mandates in detail, and most ASD mandates have gone into effect very recently during our study period.
    Journal of Policy Analysis and Management 03/2015; 34(2). DOI:10.1002/pam.21814 · 0.93 Impact Factor
  • Sandra L. Decker
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    ABSTRACT: Objective To estimate the relationship between physicians' acceptance of new Medicaid patients and access to health care.Data SourcesThe National Ambulatory Medical Care Survey (NAMCS) Electronic Health Records Survey and the National Health Interview Survey (NHIS) 2011/2012.Study DesignLinear probability models estimated the relationship between measures of experiences with physician availability among children on Medicaid or the Children's Health Insurance Program (CHIP) from the NHIS and state-level estimates of the percent of primary care physicians accepting new Medicaid patients from the NAMCS, controlling for other factors.Principal FindingsNearly 16 percent of children with a significant health condition or development delay had a doctor's office or clinic indicate that the child's health insurance was not accepted in states with less than 60 percent of physicians accepting new Medicaid patients, compared to less than 4 percent in states with at least 75 percent of physicians accepting new Medicaid patients. Adjusted estimates and estimates for other measures of access to care were similar.Conclusions Measures of experiences with physician availability for children on Medicaid/CHIP were generally good, though better in states where more primary care physicians accepted new Medicaid patients.
    Health Services Research 02/2015; DOI:10.1111/1475-6773.12288 · 2.49 Impact Factor
  • Sandra L Decker · Genevieve M Kenney · Sharon K Long
    JAMA Internal Medicine 04/2014; 174(6). DOI:10.1001/jamainternmed.2014.518 · 13.25 Impact Factor
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    ABSTRACT: The National Ambulatory Medical Care Survey collects data on office-based physician care from a nationally representative, multistage sampling scheme where the ultimate unit of analysis is a patient-doctor encounter. Patient race, a commonly analyzed demographic, has been subject to a steadily increasing item nonresponse rate. In 1999, race was missing for 17 percent of cases; by 2008, that figure had risen to 33 percent. Over this entire period, single imputation has been the compensation method employed. Recent research at the National Center for Health Statistics evaluated multiply imputing race to better represent the missing-data uncertainty. Given item nonresponse rates of 30 percent or greater, we were surprised to find many estimates’ ratios of multiple-imputation to single-imputation estimated standard errors close to 1. A likely explanation is that the design effects attributable to the complex sample design largely outweigh any increase in variance attributable to missing-data uncertainty.
    03/2014; 30(1). DOI:10.2478/jos-2014-0008
  • Sandra L Decker
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    ABSTRACT: As part of the Affordable Care Act, primary care physicians providing services to patients insured through Medicaid in some states will receive higher payments in 2013 and 2014 than in the past. Payments for some services will increase to match Medicare rates. This change may lead to wider acceptance of new Medicaid patients among primary care providers. Using data from the 2011-12 National Ambulatory Medical Care Survey Electronic Medical Records Supplement, I summarize baseline rates of acceptance of new Medicaid patients among office-based physicians by specialty and practice type. I also report state-level acceptance rates for both primary care and other physicians. About 33 percent of primary care physicians (those in general and family medicine, internal medicine, or pediatrics) did not accept new Medicaid patients in 2011-12, ranging from a low of 8.9 percent in Minnesota to a high of 54.0 percent in New Jersey. Primary care physicians in New Jersey, California, Alabama, and Missouri were less likely than the national average to accept new Medicaid patients in 2011-12. The data presented here provide a baseline for comparison of new Medicaid acceptance rates in 2013-14.
    Health Affairs 07/2013; 32(7):1183-7. DOI:10.1377/hlthaff.2013.0361 · 4.64 Impact Factor
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    ABSTRACT: IMPORTANCE Under the Affordable Care Act (ACA), states can extend Medicaid eligibility to nearly all adults with income no more than 138% of the federal poverty level. Uncertainty exists regarding the scope of medical services required for new enrollees. OBJECTIVE To document the health care needs and health risks of uninsured adults who could gain Medicaid coverage under the ACA. These data will help physicians, other clinicians, and state Medicaid programs prepare for the possible expansions. DESIGN, SETTING, AND PATIENTS Data from the National Health and Nutrition Examination Survey 2007-2010 were used to analyze health conditions among a nationally representative sample of 1042 uninsured adults aged 19 through 64 years with income no more than 138% of the federal poverty level, compared with 471 low-income adults currently enrolled in Medicaid. MAIN OUTCOMES AND MEASURES Prevalence and control of diabetes, hypertension, and hypercholesterolemia based on examinations and laboratory tests, measures of self-reported health status including medical conditions, and risk factors such as measured obesity status. RESULTS Compared with those already enrolled in Medicaid, uninsured adults were less likely to be obese and sedentary and less likely to report a physical, mental, or emotional limitation. They also were less likely to have several chronic conditions. For example, 30.1% (95% CI, 26.8%-33.4%) of uninsured adults had hypertension, hypercholesterolemia, or diabetes compared with 38.6% (95% CI, 32.0%-45.3%) of those enrolled in Medicaid (P = .02). However, if they had these conditions, uninsured adults were less likely to be aware of them and less likely to have them controlled. For example, 80.1% (95% CI, 75.2%-85.1%) of the uninsured adults with at least 1 of these 3 conditions had at least 1 uncontrolled condition, compared with 63.4% (95% CI, 53.7%-73.1%) of adults enrolled in Medicaid. CONCLUSION AND RELEVANCE Compared with adults currently enrolled in Medicaid, uninsured low-income adults potentially eligible to enroll in Medicaid under the ACA had a lower prevalence of many chronic conditions. A substantial proportion of currently uninsured adults with chronic conditions did not have good disease control; projections based on sample weighting suggest this may represent 3.5 million persons (95% CI, 2.9 million-4.2 million). These adults may need initial intensive medical care following Medicaid enrollment.
    JAMA The Journal of the American Medical Association 06/2013; 309(24):1-8. DOI:10.1001/jama.2013.7106 · 30.39 Impact Factor
  • Sandra L Decker · Jalpa A Doshi · Amy E Knaup · Daniel Polsky
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    ABSTRACT: Although it has been shown that gaining Medicare coverage at age 65 years increases health service use among the uninsured, difficulty in changing habits or differences in the characteristics of previously uninsured compared with insured individuals may mean that the previously uninsured continue to use the healthcare system differently from others. This study uses Medicare claims data linked to two different surveys--the National Health Interview Survey and the Health and Retirement Study--to describe the relationship between insurance status before age 65 years and the use of Medicare-covered services beginning at age 65 years. Although we do not find statistically significant differences in Medicare expenditures or in the number of hospitalizations by previous insurance status, we do find that individuals who were uninsured before age 65 years continue to use the healthcare system differently from those who were privately insured. Specifically, they have 16% fewer visits to office-based physicians but make 18% and 43% more visits to hospital emergency and outpatient departments, respectively. A key question for the future may be why the previously uninsured seem to continue to use the healthcare system differently from the previously insured. This question may be important to consider as health coverage expansions are implemented.
    Health Economics 10/2012; 21(10):1155-68. DOI:10.1002/hec.1780 · 2.14 Impact Factor
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    Sandra L Decker
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    ABSTRACT: When fully implemented, the Affordable Care Act will expand the number of people with health insurance. This raises questions about the capacity of the health care workforce to meet increased demand. I used data on office-based physicians from the 2011 National Ambulatory Medical Care Survey Electronic Medical Records Supplement to summarize the percentage of physicians currently accepting any new patients. Although 96 percent of physicians accepted new patients in 2011, rates varied by payment source: 31 percent of physicians were unwilling to accept any new Medicaid patients; 17 percent would not accept new Medicare patients; and 18 percent of physicians would not accept new privately insured patients. Physicians in smaller practices and those in metropolitan areas were less likely than others to accept new Medicaid patients. Higher state Medicaid-to-Medicare fee ratios were correlated with greater acceptance of new Medicaid patients. The findings serve as a useful baseline from which to measure the anticipated impact of Affordable Care Act provisions that could boost Medicaid payment rates to primary care physicians in some states while increasing the number of people with health care coverage.
    Health Affairs 08/2012; 31(8):1673-9. DOI:10.1377/hlthaff.2012.0294 · 4.64 Impact Factor
  • Sandra L Decker · Eric W Jamoom · Jane E Sisk
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    ABSTRACT: By 2011 more than half of all office-based physicians were using electronic health record systems, but only about one-third of those physicians had systems with basic features such as the abilities to record information on patient demographics, view laboratory and imaging results, maintain problem lists, compile clinical notes, or manage computerized prescription ordering. Basic features are considered important to realize the potential of these systems to improve health care. We found that although trends in adoption of electronic health record systems across geographic regions converged from 2002 through 2011, adoption continued to lag for non-primary care specialists, physicians age fifty-five and older, and physicians in small (1-2 providers) and physician-owned practices. Federal policies are specifically aimed at encouraging primary care providers and small practices to achieve widespread use of electronic health records. To achieve their nationwide adoption, federal policies may also have to focus on encouraging adoption among non-primary care specialists, as well as addressing persistent gaps in the use of electronic record systems by practice size, physician age, and ownership status.
    Health Affairs 04/2012; 31(5):1108-14. DOI:10.1377/hlthaff.2011.1121 · 4.64 Impact Factor
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    Chun-Ju Hsiao · Sandra L Decker · Esther Hing · Jane E Sisk
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    ABSTRACT: As more physicians adopt electronic health record systems in their practices, policy interest is focusing on whether physicians are ready to meet the federal "meaningful use" criteria--a vital threshold to qualify for financial incentives. In our analysis of a 2011 nationally representative survey of office-based physicians, we found that 91 percent of physicians were eligible for Medicare or Medicaid meaningful-use incentives. About half of all physicians intended to apply. However, only 11 percent both intended to apply for the incentives and had electronic health record systems with the capabilities to support even two-thirds of the stage 1 core objectives required for meaningful use. Although the federal Medicare incentives will be available through 2016, and Medicaid incentives through 2021, widespread gaps in readiness throughout the states illustrate the challenges physicians face in meeting the federal schedule for the incentive programs.
    Health Affairs 04/2012; 31(5):1100-7. DOI:10.1377/hlthaff.2011.1315 · 4.64 Impact Factor
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    ABSTRACT: This article aims to describe potential racial differences in dementia care among nursing home residents with dementia. Using data from the 2004 National Nursing Home Survey (NNHS) in regression models, the authors examine whether non-Whites are less likely than Whites to receive special dementia care--defined as receiving special dementia care services or being in a dementia special care unit (SCU)--and whether this difference derives from differences in resident or facility characteristics. The authors find that non-Whites are 4.3 percentage points less likely than Whites to receive special dementia care. The fact that non-Whites are more likely to rely on Medicaid and less likely to pay out of pocket for nursing home care explains part but not all of the difference. Most of the difference is due to the fact that non-Whites reside in facilities that are less likely to have special dementia care services or dementia care units, particularly for-profit facilities and those in the South.
    Journal of Aging and Health 03/2012; 24(4):711-31. DOI:10.1177/0898264311432311 · 1.56 Impact Factor
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    ABSTRACT: Racial and ethnic differences in emergency department (ED) waiting times have been observed previously. We explored how adjusting for ED attributes, particularly visit volume, affected racial/ethnic differences in waiting time. We constructed linear models using generalized estimating equations with 2007-2008 National Hospital Ambulatory Medical Care Survey data. We analyzed data from 54,819 visits to 431 US EDs. Our dependent variable was waiting time, measured from arrival to time seen by physician, and was log transformed because it was skewed. Primary independent variables were individual race/ethnicity (Hispanic and non-Hispanic white, black, other) and ED race/ethnicity composition (covariates for percentages of Hispanics, blacks, and others). Covariates included patient age, triage assessment, arrival by ambulance, payment source, volume, region, and teaching hospital. Geometric mean waiting times were 27.3, 37.7, and 32.7 minutes for visits by white, black, and Hispanic patients. Patients waited significantly longer at EDs serving higher percentages of black patients; per 25 point increase in percent black patients served, waiting times increased by 23% (unadjusted) and 13% (adjusted). Within EDs, black patients waited 9% (unadjusted) and 4% (adjusted) longer than whites. The ED attribute most strongly associated with waiting times was visit volume. Waiting times were about half as long at low-volume compared with high-volume EDs (P<0.001). For Hispanic patients, differences were smaller and less robust to model choice. Non-Hispanic black patients wait longer for ED care than whites primarily because of where they receive that care. ED volume may explain some across-ED differences.
    Medical care 01/2012; 50(4):335-41. DOI:10.1097/MLR.0b013e318245a53c · 2.94 Impact Factor
  • Nancy Sonnenfeld · Sandra L Decker · Susan M Schappert
    JAMA The Journal of the American Medical Association 09/2011; 306(11):1202-3; author reply 1203. DOI:10.1001/jama.2011.1326 · 30.39 Impact Factor
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    Melissa Park · Donald Cherry · Sandra L Decker
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    ABSTRACT: The expansion of health insurance coverage through health care reform, along with the aging of the population, are expected to strain the capacity for providing health care. Projections of the future physician workforce predict declines in the supply of physicians and decreasing physician work hours for primary care. An expansion of care delivered by nurse practitioners (NPs), certified nurse midwives (CNMs), and physician assistants (PAs) is often cited as a solution to the predicted surge in demand for health care services and calls for an examination of current reliance on these providers. Using a nationally based physician survey, we have described the employment of NPs, CNMs, and PAs among office-based physicians by selected physician and practice characteristics.
    NCHS data brief 08/2011; 69(69):1-8.
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    Sandra L Decker
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    ABSTRACT: Although Medicaid removes most financial barriers to receipt of dental care among children and adolescents, Medicaid recipients may not be able to access dental care if dentists decline to participate in Medicaid because of low payment levels or other reasons. To describe the association between state Medicaid dental fees in 2 years (2000 and 2008) and children's receipt of dental care. Data on Medicaid dental fees in 2000 and 2008 for 42 states plus the District of Columbia were merged with data from 33,657 children and adolescents (aged 2-17 years) in the National Health Interview Survey (NHIS) for the years 2000-2001 and 2008-2009. Logit models were used to estimate the probability that children and adolescents had seen a dentist in the past 6 months as a function of the Medicaid prophylaxis fee and control variables including age group, race, poverty status, and state and year effects. The effect of fees on children with Medicaid relative to a control group, privately insured counterparts, served to separate Medicaid's effect on access to care from any correlation between the Medicaid fee or changes in fees by state and other attributes of states. Whether a child or adolescent had seen a dentist in the past 6 months. On average, Medicaid dental payment levels did not change significantly in inflation-adjusted terms between 2000 and 2008, although a difference existed for some states, including in 5 states plus the District of Columbia, where payments increased at least 50%. In 2008-2009, more children and adolescents covered by Medicaid (55%, 95% confidence interval [CI], 53%-57%) had seen a dentist in the past 6 months than did uninsured children (27%, 95% CI, 24%-30%), but fewer than children covered by private insurance (68%, 95% CI, 67%-70%). Changes in state Medicaid dental payment fees between 2000 and 2008 were positively associated with use of dental care among children and adolescents covered by Medicaid. For example, a $10 increase in the Medicaid prophylaxis payment level (from $20 to $30) was associated with a 3.92 percentage point (95% CI, 0.54-7.50) increase in the chance that a child or adolescent covered by Medicaid had seen a dentist. Higher Medicaid payment levels to dentists were associated with higher rates of receipt of dental care among children and adolescents.
    JAMA The Journal of the American Medical Association 07/2011; 306(2):187-93. DOI:10.1001/jama.2011.956 · 30.39 Impact Factor

Publication Stats

307 Citations
169.34 Total Impact Points

Institutions

  • 2015
    • Agency for Healthcare Research and Quality
      Роквилл, Maryland, United States
  • 2008–2015
    • Centers for Disease Control and Prevention
      • • National Center for Health Statistics
      • • National Center for Chronic Disease Prevention and Health Promotion
      Атланта, Michigan, United States