The Contribution of First-name Information to the Accuracy of Racial-and-Ethnic Imputations Varies by Sex and Race-and-Ethnicity Among Medicare Beneficiaries.

BACKGROUND: Data on race-and-ethnicity that are needed to measure health equity are often limited or missing. The importance of first name and sex in predicting race-and-ethnicity is not well understood. OBJECTIVE: The objective of this study was to compare the contribution of first-name information to the accuracy of basic and more complex racial-and-ethnic imputations that incorporate surname information. RESEARCH DESIGN: We imputed race-and-ethnicity in a sample of Medicare beneficiaries under 2 scenarios: (1) with only sparse predictors (name, address, sex) and (2) with a rich set (adding limited administrative race-and-ethnicity, demographics, and insurance). SUBJECTS: A total of 284,627 Medicare beneficiaries who completed the 2014 Medicare Consumer Assessment of Healthcare Providers and Systems survey and reported race-and-ethnicity were included. RESULTS: Hispanic, non-Hispanic Asian/Pacific Islander, and non-Hispanic White racial-and-ethnic imputations are more accurate for males than females under both sparse-predictor and rich-predictor scenarios; adding first-name information increases accuracy more for females than males. In contrast, imputations of non-Hispanic Black race-and-ethnicity are similarly accurate for females and males, and first names increase accuracy equally for each sex in both sparse-predictor and rich-predictor scenarios. For all 4 racial-and-ethnic groups, incorporating first-name information improves prediction accuracy more under the sparse-predictor scenario than under the rich-predictor scenario. CONCLUSION: First-name information contributes more to the accuracy of racial-and-ethnic imputations in a sparse-predictor scenario than in a rich-predictor scenario and generally narrows sex gaps in accuracy of imputations.

How Do Gender Differences in Quality of Care Vary Across Medicare Advantage Plans?

BACKGROUND: Healthcare Effectiveness Data and Information Set (HEDIS) quality measures have long been used to compare care across health plans and to study racial/ethnic and socioeconomic disparities among Medicare Advantage (MA) beneficiaries. However, possible gender differences in seniors' quality of care have received less attention. OBJECTIVE: To test for the presence and nature of any gender differences in quality of care across MA Plans, overall and by domain; to identify those most at risk of poor care. DESIGN: Cross-sectional analysis of individual-level HEDIS measure scores from 23.8 million records using binomial mixed-effect models to estimate the effect of gender on performance. For each measure, we assess variation in gender gaps and their correlation with plan performance. PARTICIPANTS: Beneficiaries from 456 MA plans in 2011-2012 HEDIS data. MAIN MEASURES: Performance on 32 of 34 HEDIS measures which were available in both measurement years. The two excluded measures had mean performance scores below 10%. KEY RESULTS: Women experienced better quality of care than men for 22/32 measures, with most pertaining to screening or treatment. Men experienced better quality on nine measures, including four related to cardiovascular disease and three to potentially harmful drug-disease interactions. Plans varied substantially in the magnitude of gender gaps for 21/32 measures; in general, the gender gap in quality of care was least favorable to men in low-performing plans. CONCLUSIONS: Women generally experienced better quality of care than men. However, women experienced poorer care for cardiovascular disease-related intermediate outcomes and potentially harmful drug-disease interactions. Quality improvement may be especially important for men in low-performing plans and for cardiovascular-related care and drug-disease interactions for women. Gender-stratified reporting could reveal gender gaps, identify plans for which care varies by gender, and motivate efforts to address faults and close the gaps in the delivery system.

Mapping the Gaps: Gender Differences in Preventive Cardiovascular Care among Managed Care Members in Four Metropolitan Areas.

BACKGROUND: Prior research documents gender gaps in cardiovascular risk management, with women receiving poorer quality routine care on average, even in managed care systems. Although population health management tools and quality improvement efforts have led to better overall care quality and narrowing of racial/ethnic gaps for a variety of measures, we sought to quantify persistent gender gaps in cardiovascular risk management and to assess the performance of routinely used commercial population health management tools in helping systems narrow gender gaps. METHODS: Using 2013 through 2014 claims and enrollment data from more than 1 million members of a large national health insurance plan, we assessed performance on seven evidence-based quality measures for the management of coronary artery disease and diabetes mellitus, a cardiac risk factor, across and within four metropolitan areas. We used logistic regression to adjust for region, demographics, and risk factors commonly tracked in population health management tools. FINDINGS: Low-density lipoprotein (LDL) cholesterol control (LDL < 100 mg/dL) rates were 5 and 15 percentage points lower for women than men with diabetes mellitus (p < .0001), and coronary artery disease (p < .0001), respectively. Adjusted analyses showed women were more likely to have gaps in LDL control, with an odds ratio of 1.31 (95% confidence interval, 1.27-1.38) in diabetes mellitus and 1.88 (95% confidence interval, 1.65-2.10) in coronary artery disease. CONCLUSIONS: Given our findings that gender gaps persist across both clinical and geographic variation, we identified additional steps health plans can take to reduce disparities. For measures where gaps have been consistently identified, we recommend that gender-stratified quality reporting and analysis be used to complement widely used algorithms to identify individuals with unmet needs for referral to population health and wellness behavior support programs.

Training a patient safety work force: the patient safety improvement corps.

OBJECTIVE: Evaluate short-term effects of the Patient Safety Improvement Corps (PSIC), an Agency for Healthcare Research and Quality­sponsored program to train state teams in patient safety skills/tools, to assess its contribution to building a national infrastructure supporting effective patient safety practices. DATA SOURCE: Self-reported information gathered from (1) group interviews at the end of each year; (2) individual telephone interviews 1 year later; (3) faxed information forms 2 years later. STUDY DESIGN: Program evaluation of immediate and short-term process and impact (use of skills/tools, information sharing, changes in practice). DATA COLLECTION: Semistructured interviews; faxed forms. PRINCIPAL FINDINGS: One year after training, approximately half of Year 1 and 2 state agency representatives reported they had initiated or modified legislation to strengthen safe practices, and modified adverse event oversight procedures. Approximately three-quarters of hospital representatives said training contributed to modifications to adverse event oversight procedures and promotion of patient safety culture. Two years posttraining, approximately three-quarters of Year 1 trainees said they continued to use many skills/tools. CONCLUSIONS: The PSIC contributed to building a national infrastructure supporting effective patient safety practices. Expanded training is needed to reach a larger fraction of the population for which this training is important.

Differences in HIV care between patients with and without severe mental illness.

OBJECTIVE: This study explored how HIV care differs for infected persons with and without severe mental illness. METHODS: Data were obtained through interviews with and chart review of 295 patients with severe mental illness and HIV from public mental health agencies in Los Angeles County and New York City. Data were compared with data from 1,294 HIV patients without severe mental illness from a separate national probability sample. Measures were difficulty obtaining care, whether patients recommend their HIV care provider, hospital problem score, functional health status, and disability days. RESULTS: In Los Angeles, HIV patients with severe mental illness were more likely than those without severe mental illness to have difficulty obtaining care (p<.001); to not recommend their provider (10% versus 5%, p=.007); and to have problematic hospital care (p=.001), poor health status (p=.001), and more disability days (p<.001). In New York City, HIV patients with severe mental illness were more likely than patients without severe mental illness to have difficulty obtaining care (p=.002) and not recommend their provider (p=.02). The relationship between severe mental illness and health status in Los Angeles and access in New York City became insignificant after adjustment for sociodemographic factors, drug use, and CD4 cell count. Further adjustment for higher case management rates among HIV patients with severe mental illness reduced disparities only in the West. CONCLUSIONS: Patients with severe mental illness experienced more problems with HIV care than patients without severe mental illness, although high case management rates for patients with severe mental illness may have offset some problems.

Does quality of care for cardiovascular disease and diabetes differ by gender for enrollees in managed care plans?

PURPOSE: To assess gender differences in the quality of care for cardiovascular disease and diabetes for enrollees in managed care plans. METHODS: We obtained data from 10 commercial and 9 Medicare plans and calculated performance on 6 Health Employer Data and Information Set (HEDIS) measures of quality of care (beta-blocker use after myocardial infarction [MI], low-density lipoprotein cholesterol [LDL-C] check after a cardiac event, and in diabetics, whether glycosylated hemoglobin [HgbA1c], LDL cholesterol, nephropathy, and eyes were checked) and a 7th HEDIS-like measure (angiotensin-converting enzyme [ACE] inhibitor use for congestive heart failure). A smaller number of plans provided HEDIS scores on 4 additional measures that require medical chart abstraction (control of LDL-C after cardiac event, blood pressure control in hypertensive patients, and HgbA1c and LDL-C control in diabetics). We used logistic regression models to adjust for age, race/ethnicity, socioeconomic status, and plan. MAIN FINDINGS: Adjusting for covariates, we found significant gender differences on 5 of 11 measures among Medicare enrollees, with 4 favoring men. Similarly, among commercial enrollees, we found significant gender differences for 8 of 11 measures, with 6 favoring men. The largest disparity was for control of LDL-C among diabetics, where women were 19% less likely to achieve control among Medicare enrollees (relative risk [RR] = 0.81; 95% confidence interval [CI] = 0.64-0.99) and 16% less likely among commercial enrollees (RR = 0.84; 95%CI = 0.73-0.95). CONCLUSION: Gender differences in the quality of cardiovascular and diabetic care were common and sometimes substantial among enrollees in Medicare and commercial health plans. Routine monitoring of such differences is both warranted and feasible.

Use of geocoding and surname analysis to estimate race and ethnicity.

OBJECTIVE: To review two indirect methods, geocoding and surname analysis, for estimating race/ethnicity as a means for health plans to assess disparities in care. STUDY DESIGN: Review of published articles and unpublished data on the use of geocoding and surname analyses. PRINCIPAL FINDINGS: Few published studies have evaluated use of geocoding to estimate racial and ethnic characteristics of a patient population or to assess disparities in health care. Three of four studies showed similar estimates of the proportion of blacks and one showed nearly identical estimates of racial disparities, regardless of whether indirect or more direct measures (e.g., death certificate or CMS data) were used. However, accuracy depended on racial segregation levels in the population and region assessed and geocoding was unreliable for identifying Hispanics and Asians/Pacific Islanders. Similarly, several studies suggest surname analyses produces reasonable estimates of whether an enrollee is Hispanic or Asian/Pacific Islander and can identify disparities in care. However, accuracy depends on the concentrations of Asians or Hispanics in areas assessed. It is less accurate for women and more acculturated and higher SES persons due intermarriage, name changes, and adoption. Surname analysis is not accurate for identifying African Americans. Recent unpublished analyses suggest plans can successfully use a combined geocoding/surname analyses approach to identify disparities in care in most regions. Refinements based on Bayesian methods may make geocoding/surname analyses appropriate for use in areas where the accuracy is currently poor, but validation of these preliminary results is needed. CONCLUSIONS: Geocoding and surname analysis show promise for estimating racial/ethnic health plan composition of enrollees when direct data on major racial and ethnic groups are lacking. These data can be used to assess disparities in care, pending availability of self-reported race/ethnicity data.

An HIV collaborative in the VHA: do advanced HIT and one-day sessions change the collaborative experience?

BACKGROUND: Many organizations participate in quality collaboratives, yet the return on investment of the associated time and costs is unclear. METHOD: Semistructured interviews, surveys, and direct observation were used to assess experiences, improvement activities, and costs associated with participation in a year-long modified Institute for Healthcare Improvement-style collaborative designed to improve HIV care within the Veterans Health Administration. All nine sites had access to automated patient registries and semi-automated clinical measure reports; five sites also received computerized clinical reminders. Three one-day learning sessions were conducted. RESULTS: Participants reported that burden was small and value high, although many suggested that more time for peer-to peer learning would have been helpful. Teams averaged five quality improvement activities per site and most reported improvements in HIV care processes. The average annual cost per site was dollars 28,000 but costs varied considerably by site. DISCUSSION: Shortened learning sessions and the incorporation of health information technology can reduce some of the costs and burdens associated with collaboratives, yet peer-to-peer interaction and local organizational factors remain important to ensuring perceived effectiveness of collaboratives.

Patterns of HIV care for patients with serious mental illness.

Individuals with serious mental illness are at higher risk for HIV than are members of the general population. Although studies have shown that individuals with serious mental illness experience less adequate care and worse physical health outcomes than comparable patients without serious mental illness, little is known about HIV care among individuals with serious mental illness who become infected with HIV. In the present study, we describe patterns of highly active antiretroviral treatment (HAART) use and physician monitoring received by 154 patients with serious mental illness infected with HIV. Participants were recruited from mental health agencies in Los Angeles, California. Data from 762 HIV-only patients from a separate Western U.S. probability sample were used for comparison. High proportions of serious mental illness patients with HIV in our sample appeared to be receiving adequate HIV care. Fifty-one percent of all serious mental illness patients with serious mental illness with HIV were taking HAART, and the majority received close monitoring of their CD4 counts (84%) and viral loads (82%) throughout a 1-year period. HAART use and patterns of CD4 count and viral load monitoring did not differ significantly between patients with both serious mental illness and HIV, and patients with HIV only (all p > 0.05). Specialized programs providing assistance to serious mental illness populations with HIV may be helping to narrow health care disparities as a result of having serious mental illness.

Use of geocoding in managed care settings to identify quality disparities.

Tracking quality-of-care measures is essential for improving care, particularly for vulnerable populations. Although managed care plans routinely track quality measures, few examine whether their performance differs by enrollee race/ethnicity or socioeconomic status (SES), in part because plans do not collect that information. We show that plans can begin examining and targeting potential disparities using indirect measures of enrollee race/ethnicity and SES based on geocoding. Using such measures, we demonstrate disparities within both Medicare+Choice and commercial plans on Health Plan Employer Data and Information Set (HEDIS) measures of diabetes and cardiovascular care, including instances in which race/ethnicity and SES have distinct effects.

The Health Insurance Portability and Accountability Act Privacy Rule: a practical guide for researchers.

BACKGROUND: The Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule, intended to address potential threats to patient privacy posed by the computerization and standardization of medical records, provides a new floor level of federal protection for health information in all 50 states. In most cases, compliance with the Privacy Rule was required as of April 2003. Yet considerable confusion and concern remain about the Privacy Rule and the specific changes it requires in the way healthcare providers, health plans, and others use, maintain, and disclose health information. Researchers worry that the Privacy Rule could hinder their access to health information needed to conduct their research. OBJECTIVES: In this article, we explain how the final version of the Privacy Rule governs disclosure of health information, assess implications of the Privacy Rule for research, and offer practical suggestions for researchers who require access to health information. CONCLUSION: The Privacy Rule is fundamentally changing the way that healthcare providers, health plans, and others use, maintain, and disclose health information and the steps that researchers must take to obtain health data. The Privacy Rule requires researchers who seek access to identifiable health information to obtain written authorization from subjects, or, alternatively, to demonstrate that their research protocols meet certain Privacy Rule requirements that permit access without written authorization. To ensure continued access to data, researchers will need to work more closely than before with healthcare providers, health plans, and other institutions that generate and maintain health information.

Symptom-based framework for assessing quality of HIV care.

OBJECTIVE: To evaluate HIV quality of care using a symptom-based, patient-centered framework. METHODS: An expert panel developed 13 quality indicators for three common symptoms: cough with fever and/or shortness of breath; severe or persistent diarrhea; and significant weight loss. A nationally representative probability sample of HIV-infected adults was interviewed between 1996 and 1997. PARTICIPANTS: were asked about the presence and severity of HIV symptoms during the preceding 6 months, and care received. Variation in adherence to the indicators was assessed by symptom type and patient characteristics. RESULTS: In all, 2864 (71%) patients completed interviews and 920 reported being at least moderately bothered with one of the three symptoms. Of these, 41, 74, and 65% of patients with a symptom of cough, weight loss, or diarrhea, respectively, reported receiving all indicated care. Performance was better for patients with more severe HIV, measured as a CD4 cell count <50 cells/microliter, compared with those with less severe HIV, measured as CD4 cell count >500 cells/microliter (43% versus 60%; P = 0.02). Uninsured patients had worse performance than Medicare patients (45% versus 62%; P = 0.04), but care did not differ by patient's age, gender, ethnicity, HIV risk factor, providers' HIV patient load, or region. Only CD4 count remained significantly associated with performance in the multivariate analyses. CONCLUSIONS: Symptom-based quality indicators may provide a useful supplement to conventional measures. Patients with HIV reported substantial underuse of services for common, burdensome symptoms. Although adherence to quality indicators was better for patients with more advanced HIV disease, many still received suboptimal care. Vulnerable patient groups generally did not receive worse quality of care, suggesting that symptom-based measures of quality may measure domains that are distinct from those captured by conventional indicators.

Patterns of care for open-angle glaucoma in managed care.

OBJECTIVES: To describe patterns of care for primary open-angle glaucoma (POAG) and assess conformance with the American Academy of Ophthalmology's Preferred Practice Pattern (PPP). METHODS: We obtained administrative, survey, and eye care records data on 395 working-age patients with POAG enrolled in 6 managed care plans between 1997 and 1999. We assessed processes of care at the initial and follow-up visits, control of intraocular pressure (IOP), intervals between visits and visual field tests, and adjustments in therapy. RESULTS: We found high rates of performance on most recommended processes during initial evaluations, although only 53% of patients received an optic nerve head photograph or drawing and only 1% had a target IOP level documented. Recommended processes were performed at 80% to 97% of follow-up visits. Using loose criteria for control, IOP was controlled in 66% of follow-up visits for patients with mild glaucoma and 52% of visits for patients with moderate to severe glaucoma. Intervals between visits and visual field tests were generally consistent with PPP recommendations. Adjustments in therapy were more likely with worse control of IOP, although adjustments occurred in only half of visits where the IOP was 30 mm Hg or higher. CONCLUSIONS: Our study suggests that, in many respects, patients with POAG are receiving care that is consistent with the PPP. However, care is falling short on several key aspects, and POAG may be undertreated relative to standards for IOP control established in recent clinical trials.