Impact of depression on the intensity of patient navigation for women with abnormal cancer screenings.

Patient navigation is increasingly being used to support vulnerable patients to receive timely and quality medical care. We sought to understand whether patients with depression utilize additional patient navigation services after abnormal cancer screening. We compared depressed and non-depressed women using three different measures of intensity of patient navigation: number of patient-navigator encounters, encounter time, and number of unique barriers to care. The study population consisted of 1,455 women who received navigation after abnormal screening for breast or cervical cancer at one of six community health centers in Boston. Navigators spent a median of 60-75 minutes over one or two encounters per participant, with 49% of participants having one or more documented barrier to care. Depressed women did not differ in total numbers of encounters, encounter time, or unique barriers compared with non-depressed women. Our findings suggest that pre-existing depression does not predict which women will utilize additional navigation services.

Analysis of combined data from heterogeneous study designs: an applied example from the patient navigation research program.

BACKGROUND: The Patient Navigation Research Program (PNRP) is a cooperative effort of nine research projects, with similar clinical criteria but with different study designs. To evaluate projects such as PNRP, it is desirable to perform a pooled analysis to increase power relative to the individual projects. There is no agreed-upon prospective methodology, however, for analyzing combined data arising from different study designs. Expert opinions were thus solicited from the members of the PNRP Design and Analysis Committee. PURPOSE: To review possible methodologies for analyzing combined data arising from heterogeneous study designs. METHODS: The Design and Analysis Committee critically reviewed the pros and cons of five potential methods for analyzing combined PNRP project data. The conclusions were based on simple consensus. The five approaches reviewed included the following: (1) analyzing and reporting each project separately, (2) combining data from all projects and performing an individual-level analysis, (3) pooling data from projects having similar study designs, (4) analyzing pooled data using a prospective meta-analytic technique, and (5) analyzing pooled data utilizing a novel simulated group-randomized design. RESULTS: Methodologies varied in their ability to incorporate data from all PNRP projects, to appropriately account for differing study designs, and to accommodate differing project sample sizes. LIMITATIONS: The conclusions reached were based on expert opinion and not derived from actual analyses performed. CONCLUSIONS: The ability to analyze pooled data arising from differing study designs may provide pertinent information to inform programmatic, budgetary, and policy perspectives. Multisite community-based research may not lend itself well to the more stringent explanatory and pragmatic standards of a randomized controlled trial design. Given our growing interest in community-based population research, the challenges inherent in the analysis of heterogeneous study design are likely to become more salient. Discussion of the analytic issues faced by the PNRP and the methodological approaches we considered may be of value to other prospective community-based research programs.

Factors associated with disclosure of medical errors by housestaff.

PURPOSE: Attributes of the organisational culture of residency training programmes may impact patient safety. Training environments are complex, composed of clinical teams, residency programmes, and clinical units. We examined the relationship between residents' perceptions of their training environment and disclosure of or apology for their worst error. METHOD: Anonymous, self-administered surveys were distributed to Medicine and Surgery residents at Boston Medical Center in 2005. Surveys asked residents to describe their worst medical error, and to answer selected questions from validated surveys measuring elements of working environments that promote learning from error. Subscales measured the microenvironments of the clinical team, residency programme, and clinical unit. Univariate and bivariate statistical analyses examined relationships between trainee characteristics, their perceived learning environment(s), and their responses to the error. RESULTS: Out of 109 surveys distributed to residents, 99 surveys were returned (91% overall response rate), two incomplete surveys were excluded, leaving 97: 61% internal medicine, 39% surgery, 59% male residents. While 31% reported apologising for the situation associated with the error, only 17% reported disclosing the error to patients and/or family. More male residents disclosed the error than female residents (p=0.04). Surgery residents scored higher on the subscales of safety culture pertaining to the residency programme (p=0.02) and managerial commitment to safety (p=0.05). Our Medical Culture Summary score was positively associated with disclosure (p=0.04) and apology (p=0.05). CONCLUSION: Factors in the learning environments of residents are associated with responses to medical errors. Organisational safety culture can be measured, and used to evaluate environmental attributes of clinical training that are associated with disclosure of, and apology for, medical error.

Depression and anxiety diagnoses are not associated with delayed resolution of abnormal mammograms and pap tests among vulnerable women.

BACKGROUND: Delays in care after abnormal cancer screening contribute to disparities in cancer outcomes. Women with psychiatric disorders are less likely to receive cancer screening and may also have delays in diagnostic resolution after an abnormal screening test. OBJECTIVE: To determine if depression and anxiety are associated with delays in resolution after abnormal mammograms and Pap tests in a vulnerable population of urban women. DESIGN: We conducted retrospective chart reviews of electronic medical records to identify women who had a diagnosis of depression or anxiety in the year prior to the abnormal mammogram or Pap test. We used time-to-event analysis to analyze the outcome of time to resolution after abnormal cancer screening, and Cox proportional hazards regression modeling to control for confounding. PARTICIPANTS: Women receiving care in six Boston-area community health centers 2004-2005: 523 with abnormal mammograms, 474 with abnormal Pap tests. RESULTS: Of the women with abnormal mammogram and pap tests, 19% and 16%, respectively, had co-morbid depression. There was no difference in time to diagnostic resolution between depressed and not-depressed women for those with abnormal mammograms (aHR = 0.9, 95 CI 0.7,1.1) or Pap tests (aHR = 0.9, 95 CI 0.7,1.3). CONCLUSIONS: An active diagnosis of depression and/or anxiety in the year prior to an abnormal mammogram or Pap test was not associated with a prolonged time to diagnostic resolution. Our findings imply that documented mood disorders do not identify an additional barrier to resolution after abnormal cancer screening in a vulnerable population of women.

Nursing home residence confounds gender differences in Medicare utilization an example of Simpson's paradox.

BACKGROUND: Gender differences in health care utilization in older Americans may be confounded by nursing home residence. Medicare data contain several files that can be used to create a measure of nursing home residence, but prior work has not addressed which best account for potential confounding. Simpson's paradox occurs when aggregated data support a different conclusion from what the disaggregated data show. We describe such a paradox that appeared when we sharpened our definition of "nursing home residence" while examining gender differences in Medicare utilization at the end of life. METHODS: To understand gender-specific health care utilization at the end of life, we conducted a retrospective analysis of a national random sample of Medicare beneficiaries aged 66 or older who died in 2001 with Parts A and B data for 18 months before death. We sought to associate each of total hospital days and costs during the final 6 months of life with numbers of primary care physician visits in the 12 preceding months. In addition to demographics, comorbidities, and geography, "nursing home residence" was a potential confounder, which we imputed in two ways: 1) from skilled nursing facility bills in the Part A Medicare Provider Analysis and Review (MedPAR) file; and 2) from Berenson-Eggers-Type-of-Service codes indicating widely spaced doctor visits in nursing homes obtained from Medicare's carrier file. CONCLUSION: Gender differences in Medicare utilization are strongly confounded by nursing home resident status, which can be imputed well from Medicare's carrier file, but not MedPAR.

Racial and ethnic differences in end-of-life costs: why do minorities cost more than whites?

BACKGROUND: Racial and ethnic minorities generally receive fewer medical interventions than whites, but racial and ethnic patterns in Medicare expenditures and interventions may be quite different at life's end. METHODS: Based on a random, stratified sample of Medicare decedents (N = 158 780) in 2001, we used regression to relate differences in age, sex, cause of death, total morbidity burden, geography, life-sustaining interventions (eg, ventilators), and hospice to racial and ethnic differences in Medicare expenditures in the last 6 months of life. RESULTS: In the final 6 months of life, costs for whites average $20,166; blacks, $26,704 (32% more); and Hispanics, $31,702 (57% more). Similar differences exist within sexes, age groups, all causes of death, all sites of death, and within similar geographic areas. Differences in age, sex, cause of death, total morbidity burden, geography, socioeconomic status, and hospice use account for 53% and 63% of the higher costs for blacks and Hispanics, respectively. While whites use hospice most frequently (whites, 26%; blacks, 20%; and Hispanics, 23%), racial and ethnic differences in end-of-life expenditures are affected only minimally. However, fully 85% of the observed higher costs for nonwhites are accounted for after additionally modeling their greater end-of-life use of the intensive care unit and various intensive procedures (such as, gastrostomies, used by 10.5% of blacks, 9.1% of Hispanics, and 4.1% of whites). CONCLUSIONS: At life's end, black and Hispanic decedents have substantially higher costs than whites. More than half of these cost differences are related to geographic, sociodemographic, and morbidity differences. Strikingly greater use of life-sustaining interventions accounts for most of the rest.

Can primary care visits reduce hospital utilization among Medicare beneficiaries at the end of life?

BACKGROUND: Medical care at the end of life is often expensive and ineffective. OBJECTIVE: To explore associations between primary care and hospital utilization at the end of life. DESIGN: Retrospective analysis of Medicare data. We measured hospital utilization during the final 6 months of life and the number of primary care physician visits in the 12 preceding months. Multivariate cluster analysis adjusted for the effects of demographics, comorbidities, and geography in end-of-life healthcare utilization. SUBJECTS: National random sample of 78,356 Medicare beneficiaries aged 66+ who died in 2001. Non-whites were over-sampled. All subjects with complete Medicare data for 18 months prior to death were retained, except for those in the End Stage Renal Disease program. MEASUREMENTS: Hospital days, costs, in-hospital death, and presence of two types of preventable hospital admissions (Ambulatory Care Sensitive Conditions) during the final 6 months of life. RESULTS: Sample characteristics: 38% had 0 primary care visits; 22%, 1-2; 19%, 3-5; 10%, 6-8; and 11%, 9+ visits. More primary care visits in the preceding year were associated with fewer hospital days at end of life (15.3 days for those with no primary care visits vs. 13.4 for those with > or = 9 visits, P < 0.001), lower costs ($24,400 vs. $23,400, P < 0.05), less in-hospital death (44% vs. 40%, P < 0.01), and fewer preventable hospitalizations for those with congestive heart failure (adjusted odds ratio, aOR = 0.82, P < 0.001) and chronic obstructive pulmonary disease (aOR = 0.81, P = 0.02). CONCLUSIONS: Primary care visits in the preceding year are associated with less, and less costly, end-of-life hospital utilization. Increased primary care access for Medicare beneficiaries may decrease costs and improve quality at the end of life.