Biomedical subjects

Michael A Posner

Publications and source records attributed to Michael A Posner.

8 recordsLinked to original sources

PubMed2007

Improving follow-up to abnormal breast cancer screening in an urban population. A patient navigation intervention.

Delays in follow-up after cancer screening contribute to racial/ethnic disparities in cancer outcomes. We evaluated a patient navigator intervention among inner-city women with breast abnormalities. A full-time patient navigator supported patients using the care management model. Female patients 18 years and above, referred to an urban, hospital-based, diagnostic breast health practice from January to June 2000 (preintervention) and November 2001 to February 2003 (intervention), were studied. Timely follow-up was defined as arrival to diagnostic evaluation within 120 days from the date the original appointment was scheduled. Data were collected via computerized registration, medical records, and patient interview. Bivariate and multivariate logistic regression analyses were conducted, comparing preintervention and intervention groups, with propensity score analysis and time trend analysis to address the limitations of the pre-post design. 314 patients were scheduled preintervention; 1018, during the intervention. Overall, mean age was 44 years; 40% black, 36% non-Hispanic white, 14% Hispanic, 4% Asian, 5% other; 15% required an interpreter; 68% had no or only public insurance. Forty-four percent of referrals originated from a community health center, 34% from a hospital-based practice. During the intervention, 78% had timely follow-up versus 64% preintervention (P < .0001). In adjusted analyses, women in the intervention group had 39% greater odds of having timely follow-up (95% CI, 1.01-1.9). Timely follow-up in the adjusted model was associated with older age (P = .0003), having private insurance (P = .006), having an abnormal mammogram (P = .0001), and being referred from a hospital-based practice, as compared to a community health center (P = .003). Our data suggest a benefit of patient navigators in reducing delay in breast cancer care for poor and minority populations. Cancer 2007. (c) 2006 American Cancer Society.

Adolescent↗

PubMed2006

Evaluation of the Centers for Disease Control and Prevention's recommendations regarding routine testing for human immunodeficiency virus by an inpatient service: who are we missing?

OBJECTIVE: To assess the proportion of hospitalized patients who tested positive for human immunodeficiency virus (HIV) by a routine inpatient testing service, as recommended by the Centers for Disease Control and Prevention, who might not have been identified had routine testing not been offered. PATIENTS AND METHODS: In this retrospective cohort study, the medical records of patients who tested HIV positive by the inpatient testing service between 1999 and 2003 were compared with the medical records of inpatients who tested HIV negative by the inpatient testing service and the medical records of patients who tested HIV positive in ambulatory settings. We compared HIV risk factors, discharge diagnoses, CD4 cell counts, and HIV RNA concentrations. RESULTS: A total of 243 patients participated in this study: 81 patients who tested HIV positive and 81 who tested HIV negative by the inpatient testing service, and 81 patients who tested HIV positive in ambulatory settings. Both HIV-positive inpatients and HIV-positive outpatients had similar frequencies of HIV risk factors (46% vs 43%; P=.75). Both groups differed significantly from HIV-negative inpatients (4%; P<.001). Comparing HIV-positive inpatients with HIV-positive outpatients, CD4 cell counts were lower (196 vs 371 cells/mm3; P<.001), and HIV RNA levels were higher (4.61 vs 4.09 Iog, HIV RNA; P=.001). At diagnosis, 64 HIV-positive inpatients (79%) met criteria for acquired immunodeficiency syndrome compared with 21 HIV-positive outpatients (26%) (P<.001). CONCLUSION: Patients who tested HIV positive through inpatient testing have more advanced disease than those identified as outpatients. Half of these patients would not have been identified had testing not been routinely offered. Routine inpatient HIV testing offers an important opportunity to identify patients with HIV infection.

Adult↗

PubMed2005

Do variations in disease prevalence limit the usefulness of population-based hospitalization rates for studying variations in hospital admissions?

BACKGROUND: Studies of geographic variation in hospitalizations commonly examine age- and gender-adjusted population-based hospitalization rates (ie, the numbers of persons hospitalized relative to what is expected given the age/gender distributions in the area population). OBJECTIVE: To determine whether areas identified as extreme using population-based hospitalization rates remain extreme when ranked by disease-based hospitalization rates (the numbers of persons hospitalized relative to what is expected given the amount of disease in the area). DESIGN: The authors examined 1997 Medicare data on both inpatient admissions and outpatient visits of patients 65 years and older in each of 71 small areas in Massachusetts for 15 medical conditions. For each area, the number of people having each condition was calculated as the sum of those hospitalized plus those treated as outpatients only. The authors used hierarchical Bayesian modeling to estimate area-specific population-based hospitalization rates, disease-based hospitalization rates (DHRs), and disease prevalence. MAIN OUTCOME MEASURE: The extent to which the same areas were identified as extreme based on population-based hospitalization rates versus DHRs. RESULTS: Area-specific population-based hospitalization rates, DHRs, and disease prevalence varied substantially. Areas identified as extreme using population-based hospitalization rates often were not extreme when ranked by DHRs. For 11 of the 15 conditions, 5 or more of the 14 areas ranked in top and bottom deciles by population-based hospitalization rates were more likely than not (ie, with probability > or = 0.50) to be at least 2 deciles less extreme when ranked by DHRs. CONCLUSION: Differences in disease prevalence can limit the usefulness of population-based hospitalization rates for studying variations in hospital admissions.

Aged↗

PubMed2005

Mammography use.

OBJECTIVES: The goal of this study was to compare mammography use in Haitian women versus that of other racial/ethnic groups in the same neighborhoods and to identify factors associated with mammography use in subpopulations that are seldom studied. METHODS: A community-based, cross-sectional survey sampled a multiethnic group of inner-city women from eastern Massachusetts. Bivariate analyses and logistic regression models were used to predict lifetime and recent (within two years) mammography screening. RESULTS: Self-reported lifetime mammography use was similar for Haitian (82%), African-American (78%), Caribbean (81%) and Latina women (86%) but higher for white women (94%, p = 0.008). Mammography use in the past two years was also similar in all groups (66-82%, p = 0.41). In multivariate models, African-American (adjusted odds ratio [AOR]; 0.3; 95% CI 0.1-0.9) and Haitian women (AOR 0.3; 95% CI 0.1-0.9) had lower odds of lifetime mammography compared to white women. Factors independently related to lifetime and recent mammography included having a regular healthcare provider, greater knowledge of breast cancer screening; higher education, and private health insurance. CONCLUSIONS: Haitian women with a regular provider and knowledge of breast cancer screening reported recent mammography use similar to women from other racial/ethnic groups. The racial/ethnic patterns of mammography use in our study do not explain racial/ethnic differences in breast cancer stage or mortality.

Adult↗

PubMed2003

Comparing the importance of disease rate versus practice style variations in explaining differences in small area hospitalization rates for two respiratory conditions.

Many studies have reported large variations in age- and sex-adjusted rates of hospitalizations across small geographic areas. These variations have often been attributed to differences in medical practice style which are not reflected in differences in health care outcomes. There is, however, another potentially important source of variation that has not been examined much in the literature: geographic differences in the age-sex adjusted size of the pool of patients who present with the disease and are candidates for hospitalization. Previous studies of small area variations in hospitalization rates have only used data on hospitalizations. Thus, it has not been possible to distinguish the extent to which differences in hospitalization rates are due to (i). differences in the chance that patients diagnosed with a disease are admitted to a hospital, which we refer to as the 'practice style effect,' versus (ii). geographic differences in the total amount of diagnosed disease, which we refer to as the 'disease effect.' Elementary methods for estimating the relative strength of the two effects directly from the data can be misleading, since equal amounts of variability in each effect result in unequal impacts on hospitalization rates. In this paper we describe a model-based approach for estimating the relative importance of the practice style effect and the disease effect in explaining variations in hospitalization rates. The key to our approach is the use of data on both inpatient and outpatient visits. We use 1997 Medicare data for two respiratory medical conditions across 71 small areas in Massachusetts: chronic bronchitis and emphysema, and bacterial pneumonia. Based on a Poisson model for the process generating hospitalizations and outpatient visits, we use a Bayesian framework and Gibbs sampling to compute and compare the correlation between the number of people hospitalized and each of these two sources of variation. Our results show that for the two conditions, disease rate variation explains at least as much of the variation in hospitalization rates as does practice style variation.

Aged↗

PubMed2003

Using claims data to examine mortality trends following hospitalization for heart attack in Medicare.

OBJECTIVE: To see if changes in the demographics and illness burden of Medicare patients hospitalized for acute myocardial infarction (AMI) from 1995 through 1999 can explain an observed rise (from 32 percent to 34 percent) in one-year mortality over that period. DATA SOURCES: Utilization data from the Centers for Medicare and Medicaid Services (CMS) fee-for-service claims (MedPAR, Outpatient, and Carrier Standard Analytic Files); patient demographics and date of death from CMS Denominator and Vital Status files. For over 1.5 million AMI discharges in 1995-1999 we retain diagnoses from one year prior, and during, the case-defining admission. STUDY DESIGN: We fit logistic regression models to predict one-year mortality for the 1995 cases and apply them to 1996-1999 files. The CORE model uses age, sex, and original reason for Medicare entitlement to predict mortality. Three other models use the CORE variables plus morbidity indicators from well-known morbidity classification methods (Charlson, DCG, and AHRQ's CCS). Regressions were used as is--without pruning to eliminate clinical or statistical anomalies. Each model references the same diagnoses--those recorded during the pre- and index admission periods. We compare each model's ability to predict mortality and use each to calculate risk-adjusted mortality in 1996-1999. PRINCIPAL FINDINGS: The comprehensive morbidity classifications (DCG and CCS) led to more accurate predictions than the Charlson, which dominated the CORE model (validated C-statistics: 0.81, 0.82, 0.74, and 0.66, respectively). Using the CORE model for risk adjustment reduced, but did not eliminate, the mortality increase. In contrast, adjustment using any of the morbidity models produced essentially flat graphs. CONCLUSIONS: Prediction models based on claims-derived demographics and morbidity profiles can be extremely accurate. While one-year post-AMI mortality in Medicare may not be worsening, outcomes appear not to have continued to improve as they had in the prior decade. Rich morbidity information is available in claims data, especially when longitudinally tracked across multiple settings of care, and is important in setting performance targets and evaluating trends.

Adolescent↗

PubMed2002

Do "we just know"? Masked assessors' ability to accurately identify children with prenatal cocaine exposure.

This study evaluated perceptions of masked assessors to determine whether there are subtle differences in cocaine-exposed and unexposed children who might be identified by those interacting with children. As part of a longitudinal study, developmental assessors were masked to 163 4-year-old children's actual in utero cocaine exposure status and developmental history. After each battery, assessors documented their guesses of the child's cocaine exposure. Thirty-seven percent of the children who were exposed were misclassified as unexposed, whereas 74% of those unexposed were incorrectly classified as exposed. Although the sample did not differ on assessment scores when results were analyzed by actual cocaine exposure status ( >.3), children who did less well on assessments were more likely to be labeled by assessors as cocaine-exposed ( <.001). Results highlight the potential of stereotyping and negative attributions that might distort observations, both in unmasked studies of prenatal cocaine exposure and in clinical settings.

Adult↗

PubMedDate not supplied

Pap smear rates among Haitian immigrant women in eastern Massachusetts.

OBJECTIVE: Given limited prior evidence of high rates of cervical cancer in Haitian immigrant women in the U.S., this study was designed to examine self-reported Pap smear screening rates for Haitian immigrant women and compare them to rates for women of other ethnicities. METHODS: Multi-ethnic women at least 40 years of age living in neighborhoods with large Haitian immigrant populations in eastern Massachusetts were surveyed in 2000-2002. Multivariate logistic regression analyses were used to examine the effect of demographic and health care characteristics on Pap smear rates. RESULTS: Overall, 81% (95% confidence interval 79%, 84%) of women in the study sample reported having had a Pap smear within three years. In unadjusted analyses, Pap smear rates differed by ethnicity (p=0.003), with women identified as Haitian having a lower crude Pap smear rate (78%) than women identified as African American (87%), English-speaking Caribbean (88%), or Latina (92%). Women identified as Haitian had a higher rate than women identified as non-Hispanic white (74%). Adjustment for differences in demographic factors known to predict Pap smear acquisition (age, marital status, education level, and household income) only partially accounted for the observed difference in Pap smear rates. However, adjustment for these variables as well as those related to health care access (single site for primary care, health insurance status, and physician gender) eliminated the ethnic difference in Pap smear rates. CONCLUSIONS: The lower crude Pap smear rate for Haitian immigrants relative to other women of color was in part due to differences in (1) utilization of a single source for primary care, (2) health insurance, and (3) care provided by female physicians. Public health programs, such as the cancer prevention programs currently utilized in eastern Massachusetts, may influence these factors. Thus, the relatively high Pap rate among women in this study may reflect the success of these programs. Public health and elected officials will need to consider closely how implementing or withdrawing these programs may impact immigrant and minority communities.

Adult↗