Biomedical subjects

David Nerenz

Publications and source records attributed to David Nerenz.

6 recordsLinked to original sources

PubMed2005

Comorbidity and survival disparities among black and white patients with breast cancer.

CONTEXT: Reasons for the shorter survival of black breast cancer patients compared with their white counterparts are not completely understood. OBJECTIVE: To evaluate the role of comorbidity in this racial disparity among breast cancer patients. DESIGN, SETTING, AND PATIENTS: Historical cohort from the Henry Ford Health System (a large comprehensive health system in Detroit, Mich) followed up for a median of 10 years. Patients (n = 906) included 264 black (29.1%) and 642 white (70.9%) women diagnosed as having breast cancer between 1985 and 1990. Detailed comorbidity data (268 comorbidities) and study data were abstracted from medical records and institutional, Surveillance, Epidemiology, and End Results, and Michigan State registries. Associations were analyzed with logistic and Cox regression. MAIN OUTCOME MEASURES: Breast cancer recurrence/progression and survival to death from all, breast cancer, and competing (non-breast cancer) causes. RESULTS: Of blacks, 64 (24.9%) died of breast cancer and 95 (37.0%) died of competing causes. Comparable data for whites were 115 (18.3%) and 202 (32.1%). Blacks had worse all-cause survival (hazard ratio [HR], 1.34; 95% confidence interval [CI], 1.11-1.62), breast cancer-specific survival (HR, 1.47; 95% CI, 1.08-2.00), and competing-causes survival (HR, 1.27; 95% CI, 1.00-1.63). A total of 77 adverse comorbidities were associated with reduced survival. Adverse comorbidity count was associated with all-cause (adjusted HR, 1.29; 95% CI, 1.19-1.40) and competing-causes survival but was not associated with recurrence/progression or breast cancer-specific survival. At least 1 adverse comorbidity was observed in 221 (86.0%) blacks and 407 (65.7%) whites (odds ratio, 3.20; 95% CI, 2.17-4.72). Comparisons of unadjusted and comorbidity-adjusted HRs indicated that adverse comorbidity explained 49.1% of all-cause and 76.7% of competing-causes survival disparity. Diabetes and hypertension were particularly important in explaining disparity. CONCLUSIONS: More black breast cancer patients die of competing causes than of breast cancer. Effective control of comorbidity in black breast cancer patients should help improve life expectancy and lead to a reduction in survival disparities.

Adult↗

PubMed2005

The impact of diabetes on employment and work productivity.

OBJECTIVE: The purpose of this study was to longitudinally examine the effect of diabetes on labor market outcomes. RESEARCH DESIGN AND METHODS: Using secondary data from the first two waves (1992 and 1994) of the Health and Retirement Study, we identified 7,055 employed respondents (51-61 years of age), 490 of whom reported having diabetes in wave 1. We estimated the effect of diabetes in wave 1 on the probability of working in wave 2 using probit regression. For those working in wave 2, we modeled the relationships between diabetic status in wave 1 and the change in hours worked and work-loss days using ordinary least-squares regressions and modeled the presence of health-related work limitations using probit regression. All models control for health status and job characteristics and are estimated separately by sex. RESULTS: Among individuals with diabetes, the absolute probability of working was 4.4 percentage points less for women and 7.1 percentage points less for men relative to that of their counterparts without diabetes. Change in weekly hours worked was not statistically significantly associated with diabetes. Women with diabetes had 2 more work-loss days per year compared with women without diabetes. Compared with individuals without diabetes, men and women with diabetes were 5.4 and 6 percentage points (absolute increase), respectively, more likely to have work limitations. CONCLUSIONS: This article provides evidence that diabetes affects patients, employers, and society not only by reducing employment but also by contributing to work loss and health-related work limitations for those who remain employed.

Diabetes Mellitus↗

PubMed2003

Learning to leverage existing information systems: Part 1. Principles.

BACKGROUND: The success of performance improvement efforts depends on effective measurement and feedback regarding clinical processes and outcomes. Yet most health care organizations have fragmented rather than integrated data systems. Methods and practical guidance are provided for leveraging available information sources to obtain and create valid performance improvement-related information for use by clinicians and administrators. CASE VIGNETTE: At Virginia Mason Health System (VMHS; Seattle), a vertically integrated hospital and multispecialty group practice, patient records are paper based and are supplemented with electronic reporting for laboratory and radiology services. Despite growth in the resources and interest devoted to organization-wide performance measurement, quality improvement, and evidence-based tools, VMHS's information systems consist of largely stand-alone, legacy systems organized around the ability to retrieve information on patients, one at a time. By 2002, without any investment in technology, VMHS had developed standardized, clinic-wide key indicators of performance updated and reported regularly at the patient, provider, site, and organizational levels. LEVERAGING EXISTING SYSTEMS: On the basis of VHMS's experience, principles can be suggested to guide other organizations to explore solutions using their own information systems: for example, start simply, but start; identify information needs; tap multiple data streams; and improve incrementally.

Data Collection↗

PubMed2003

Learning to leverage existing information systems: Part 2. Case studies.

BACKGROUND: The ability to use available administrative and clinical information to produce performance reports is a key element of quality improvement. Six health care systems were identified that have done a particularly effective or innovative job of creating and implementing performance measurement tools and systems by using data available in existing clinical and administrative information systems: Dean Health System (Madison, WI), Sharp HealthCare (San Diego), Henry Ford Health System (Detroit), Scripps Health (San Diego), Legacy Health System (Portland, OR), and Lovelace Health System (Albuquerque). SUMMARY THOUGHTS: Interest in comparative performance information for health care organizations remains strong. The perfect measure set has not yet been invented. Every measure has one or more flaws, as do the data systems available to support them. Managers may take comfort, however, in the knowledge that performance measures need not be perfect to be useful. Measures tend to improve when people use the data to inform decisions that matter. Even the most accurate data, though, are not useful if there is either too much or too little "organizational distance" between the unit of analysis for the data and the unit of control for making change. Some systems have adopted a layered approach to performance measurement, in which measures are aggregated for reporting and use at the level of major operating units or divisions and then disaggregated for reporting and use at smaller levels and eventually to the level of individual clinicians.

California↗

PubMed2002

Perceptions of chest pain differ by race.

BACKGROUND: African American patients are less likely to receive thrombolytic therapy and coronary revascularization than are white patients. Delay and clinical presentation may be keys to understanding differences in care. OBJECTIVE: To determine how symptom recognition and perception influence clinical presentation as a function of race, we characterized symptoms and care-seeking behavior in African American and white patients seen in the ED with chest pain. METHODS: The prospective study was conducted from April 1999 to September 1999 among patients who were seen in the ED and were admitted or observed in the ED Chest Pain Unit (n = 215). Interviews were conducted within 48 hours with a structured set of questions. RESULTS: Thirty-one percent of white patients and 8.9% of African American patients were admitted with a diagnosis of acute myocardial infarction (P =.001). African American patients were as likely as white patients to report "typical" objective symptoms but were more likely to attribute their symptoms to a gastrointestinal source rather than a cardiac source (P =.05). Of those patients with the final diagnosis of myocardial infarction (n = 45), 61% of African American patients attributed symptoms to a gastrointestinal source and 11% to a cardiac source, versus 26% and 33%, respectively, for white patients. The median prehospital delay for African American patients was 263 minutes (interquartile range, 120 to 756 minutes), similar to the 247 minutes for white patients (interquartile range, 101 to 825 minutes, P =.72), despite African American patients (80%) being more likely than white patients (66%) to perceive their symptoms as severe/life-threatening at onset (P =.05). CONCLUSION: Racial differences in symptom perception exist. Although the proportion of objectively defined typical symptoms were similar, self-attribution was more often noncardiac in African American patients than in white patients. Self-attribution, in addition to objective clinical findings, is likely to influence caregiver diagnostic approaches and therefore therapeutic approaches, and merits further study.

Black People↗

PubMed2002

Categorizing race and ethnicity in the HMO Cancer Research Network.

BACKGROUND: The Cancer Research Network (CRN) was formed in 1999 with funding from the National Cancer Institute. The CRN represents a collaboration of 10 health plans across the United States, with a combined total of approximately 9 million enrollees. The goal of the CRN is to promote collaborative research, which will ultimately increase the effectiveness of preventive, curative, and supportive interventions for major cancers. Special emphasis is placed upon diverse populations, and racial and ethnic differences in outcomes, costs, and cost effectiveness. PURPOSE: There is increasing awareness in the research literature of the relationship between race and ethnicity and health outcomes. However, the majority of the health maintenance organizations represented in the CRN, similar to other health plans and organizations, do not routinely collect race and ethnicity data on their members. In order to compare data and outcomes across the CRN sites, consensus is needed in the measurement of race and ethnicity. METHODS: This review discusses terminology used in the research literature to describe race and ethnicity and the manner in which these constructs have been measured in previous studies. CONCLUSIONS: This review concludes with suggestions for standardized measures of race and ethnicity. IMPLICATIONS: It is hoped that shared conceptualizations of race and ethnicity will lead to improved data quality and precision in measurement.

Cooperative Behavior↗