SEARCH · Search PubMed
Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Collaboration in Medicaid solves providers' data reporting troubles. If you're looking for effective ways to give plans the information they want on pregnant Medicaid members and you want good programs for your high-risk patients, see how plans and providers in Philadelphia collaborated to improve birth outcomes.
Publicly reported data can positively impact cost and quality of care--especially when hospitals use the data to improve their administrative procedures. After reading published data on the cost, mortality, and length of stay related to coronary artery bypass graft surgery at 44 Pennsylvania hospitals, 77% of hospital CEOs responding to a survey said they used the data to make institutional decisions.
Forty-six data reports which appeared in the Journal of Manipulative and Physiological Therapeutics from 1986 to 1988 were reviewed according to specific methodological criteria. There appears to be a need for improved study design in contemporary chiropractic research. Experimental and quasi-experimental studies were most commonly deficient in the areas of reliable methods of measurement, the use of blind assessors and blind, or at least naive, study subjects. Common flaws in surveys were: failure to test the survey instrument prior to the study, not stating the response rate, and omitting discussion of the question of confidentiality. The results confirmed findings obtained in a similar study of data reports of an Australian peer-reviewed chiropractic journal. The use of various types of checklists is recommended for authors and reviewers of chiropractic scientific material.
BACKGROUND: This study was undertaken to ascertain whether mortality data in the cardiac surgical literature mirror data reported in national databases. METHODS: This was a review of articles with 50 or more subjects reporting single-center mortality data for coronary artery bypass or aortic or mitral valve replacement published in the three major cardiothoracic surgical journals from 1997 through 2000. Mortality data and trends were examined. RESULTS: One hundred sixty-nine articles were found (coronary artery bypass, n = 119; aortic valve replacement, n = 34; mitral valve replacement, n = 16). Articles were predominantly case series (N = 95), with smaller numbers of comparative retrospective studies (n = 34), randomized trials (n = 29), and prospective noncomparative studies (n = 11). The median mortality figures for these studies were 1.5% (interquartile range, 0.3%-2.6%) for coronary artery bypass, 3.4% (interquartile range, 2.0%-5.3%) for aortic valve replacement, and 4.7% (interquartile range, 2.1%-6.9%) for mitral valve replacement. In contrast, the national registry mortality figures were 2.9%, 4.0%, and 6.0%, respectively, in the United States and 2.6%, 4.5% and 6.3%, respectively, in the United Kingdom. Coronary bypass studies with samples smaller than 100 patients reported lower mortality figures (median 0%) than did those with more than 100 patients (1.8%). Exploration with graphical plots suggested a bias toward reporting and publication of studies with below average mortality. CONCLUSIONS: Particularly for coronary artery bypass, published data tend to underrepresent the risk of death as seen in most centers. Outcomes and magnitudes of effects as reported in these research studies may not be replicable to the same degree in most centers. In particular, extreme caution should be taken in extrapolating results from studies with fewer than 100 patients to larger surgical populations.
This study was conducted to assess the reliability of self-reported hospitalization data, as well as the appropriateness of using self-reported data in evaluating the effectiveness of the Maine Ambulatory Diabetes Education and Follow-Up (ADEF) program. A Maine Blue Cross/Blue Shield (BC/BS) inpatient claims file was used as the reference source to verify self-reported hospitalization data. For a sample of 99 BC/BS subscribers who attended the ADEF program, 77% of the study participants accurately self-reported hospitalization patterns over a 12-mo time period before attending the education program, and 81% of the participants accurately self-reported hospitalization patterns during a posteducation follow-up time period. The reference BC/BS claims data documented a reduction in hospitalizations for the study participants similar to that reported using the ADEF self-reported hospitalization data. The Maine Diabetes Control Project used the self-reported hospitalization data in combination with selected reference claims data to secure third-party reimbursement for the Maine ADEF Program.
Pattern reliability, or the invariance of relationships among variables, was investigated in this study. The consistency of theoretical constructs reflected by measures taken at two separate occasions can be tested using confirmatory factor analysis. Self-report data were obtained from 323 narcotics addicts in two face-to-face interviews conducted in 1974/75 and 1985/86. The two interviews overlapped approximately 4 years between 1970 and 1974/75. Through the testing of the invariance of measurement and structural models, pattern reliability was confirmed in one of the models developed. Explication of pattern reliability offers an alternative means of assessing validity of self-report data.
Overweight is an important public health problem affecting around 50% of the population of Wales, resulting in increased risk of illness, premature disability and premature death. The aim of this study was to examine critically the accuracy of self-reported data in describing the prevalence of overweight in Wales. A sample of 1622 adults aged 18 to 64 years was taken from the Welsh Heart Health Survey 1985. In that survey weight and height data were collected on a self-completed questionnaire and by clinical measurement. Mean differences between self-reported and measured weight and height were used as indicators of bias, and the accuracy of BMI and the prevalence of overweight based on this data were analysed. Weight was reported without significant bias in men, but women under-reported their weight by an average of 1.1 kg. Height was over-reported by 1.4 cm in men, and 0.7 cm in women, on average. More than two-thirds of subjects reported to within 2.3 kg and 2.5 cm of their actual weight and height. Reporting was more biased in older and overweight groups. The calculation of body mass index resulted in amplification of bias and underestimation of the prevalence of overweight and obesity in the study sample of 4.5% in men and 6.7% in women. The results have important implications for the use of self-reported data for the scientific measurement of the prevalence of overweight, especially in longitudinal studies, and suggest that further research should be conducted into the stability of reporting bias over time.
This study examined age differences in the quality of self-report data in patients with chronic disease conditions (hypertension, diabetes, heart disease, depression). Data are from 2,304 patients in three health care systems in Los Angeles, Chicago, and Boston. Results support the idea that self-report health data can be gathered from older and younger patients without significant decrements in data quality. Specifically, results showed: (1) small decreases in the reliability of multi-item measures with age, primarily occurring in balanced scales; (2) little evidence of differences among age groups in response set or the tendency to respond "don't know" or "uncertain," although older patients had a greater tendency to respond in a socially desirable manner; (3) higher item nonresponse in older patients; (4) little variation in item nonresponse by type of question or question placement; (5) generally high panel retention in all age groups, supporting the value of repeated follow-up; and (6) similar known-groups validity across age groups.
Drug testing is widely used and employed in diverse contexts, including drug treatment clinics. Building on previous research, this paper aims to (i) compare self-report data and oral fluid (OMT) testing in detecting drug use amongst individuals beginning a new episode of drug treatment and (ii) identify factors that may predict drug users who have discordant self-report and OMT test results. Two hundred and seventy-one new drug treatment clients completed a structured questionnaire that included questions relating to drug use during the preceding 3 days and provided an oral fluid sample that was independently tested for opiates, benzodiazepines, methadone and cannabis. Data were analysed using kappa statistics (Cohen, 1960) and univariate and multivariate logistic regression. Findings indicated a high level of consistency between self-reported drug use and OMT testing. However, agreement varied by drug type and respondents commonly reported consumption that screening failed to identify. Inconsistencies appeared to relate to a number of factors and were not necessarily a function of deliberate distortion by the drug user. Overall, it is concluded that OMT testing is a good indicator of the validity and reliability of drug users' self-report data. Nonetheless, its accuracy might be greater for some drug categories than for others. Equally, further study comparing test results and self-reported drug use amongst different populations and in different contexts is required.
The quality of proxy reporting was assessed among 136 prenatal patients and their spouse/partners recruited from the obstetric services of a New Jersey hospital between 1985 and 1987. The concordance, sensitivity, and specificity of proxy reports about partners' occupation, smoking, and drinking were examined in relation to self-reports. Overall, private patients provided better proxy data than did clinic patients, and women provided better data than did men. No consistent effects on the quality of proxy reports were found in relation to age, level of education, marital status, or length of cohabitation. Partners' recent job titles appeared to be quite accurately reported, whereas partners' smoking and drinking patterns were less well-reported. For alcohol use in particular, there was evidence of considerable misclassification resulting from proxy reports even when kappa statistics and intraclass correlation coefficients suggested good agreement. Use of proxy respondents is unnecessary in reproductive studies and should be avoided when it may produce misleading results. Our data indicate that private prenatal patients and their partners can give reasonable proxy reports about job titles and smoking, but not about alcohol use. The high proportion of clinic patients who did not refer a partner (or whose partners could not be contacted) limits the generalizability of our results for this group and gives cause for concern about collecting proxy information from clinic populations.
This paper examines factors that influence the veracity of verbal self-report data in health services research, using a cognitive social-psychological model of the data-gathering process as an organizing framework. It begins by briefly summarizing the consequences that can result from measurement error. Next, a cognitive social-psychological model of the question-answering process is presented. Common assumptions regarding the utility of specific assessment methods are evaluated with particular emphasis on the strengths and weaknesses of alternative data sources. The framework is then applied specifically to understanding the factors that may affect self-report measures in health services research relating to alcohol and other substance use. Overall, self-report procedures can provide useful estimates of consumption in clinical settings when conditions are designed to maximize response accuracy.
We examined the correspondence between the structure of act-report data and 5-factor models emerging from trait-rating data. Twenty categories were selected as markers for the 5-factor model and retrospective act reports were constructed for the target categories. One hundred eighteen men and women comprising 59 dating couples completed self-based and observer-based act reports. Several factor analyses tested different assumptions. Retaining total act performance (TAP) produced a blend of the traditional 5 factors. Removing TAP closely reproduced the 5-factor model in both principal-components and procrustes analyses. Correlations between the derived act factors and trait ratings from 6 data sources support a reinterpretation of the traditional trait labels. Discussion focuses on the implications of different assumptions on the formulation of a basic model of personality structure.
This article compares self-report and automated data as measures of dose and duration of antidepressant use in order to assess the feasibility of using automated pharmacy data in a disease management context. We used self-report and computerized refill data to identify two treatment failures-premature discontinuation of the medication and sub-optimal dosages-at time points 1 and 4 months after initiation of antidepressant therapy. The sources showed modest agreement regarding identification of current users at 1 month (kappa = .33); agreement was high at 4 months (kappa = .72). Agreement regarding dosage adequacy was also higher later in treatment, with kappas of .52 and .65 at 1 and 4 months, respectively. The two sources showed high agreement on an overall measure of acute phase treatment adequacy (kappa = .80). Data completeness was another outcome, with data on current users and overall treatment adequacy generally available from computerized files, data on dose less so. Automated pharmacy data appear to be a feasible means of monitoring treatment adequacy and quality of care as part of a disease management approach to improving care for populations of patients.
In a study of occupational causes of spontaneous abortions, based upon self-reported data and data from the hospital registry, evidence of differential misclassification was noted. Among those exposed a larger proportion of the self-reported spontaneous abortions were identified in the hospital registry, compared with what was found in the control group. This could be due to recall bias of the questionnaire data masking an effect of exposure, or a lower threshold for hospitalization among those exposed vis-à-vis controls, which would exaggerate the effect of exposure, if any. The analysis tended to support the idea of a less accurate recall of spontaneous abortions among controls, especially for abortion that occurred more than 3 years before the questionnaires were sent out. A second questionnaire was sent out to a subset of the participants 3 1/2 years after the first questionnaire. 17% reported fewer spontaneous abortions in this second questionnaire compared with the situation in the first questionnaire, for the period 1973 to 1980.
The present study focuses on the evaluation of mental health outcome of 151 young people who received psychodynamic psychotherapy at the Brandon Centre, a community-based psychodynamic psychotherapy centre; for young people. This paper reports the results from a 1-year follow-up based on self-report data. Participants aged 12-18 years completed either the Youth Self Report form or, if they were aged over 18, the Young Adult Self Report form at intake, 3 months, 6 months, and 1 year. The domains evaluated included young people's externalizing problems, internalizing problems, and total problems. Outcome was measured in three different ways: the change in mean scores; the change in numbers from the clinical to the non-clinical range; and categorizing cases according to the presence of statistically reliable change in the level of adaptation. These approaches showed improvement among participants in all three domains. Although there was a high general tendency to improve, the rate of improvement dropped significantly over time. Several tentative predictors of improvement were identified. The paper discusses how the results from systematic monitoring of effectiveness at the Brandon Centre have formed an empirical basis that has led to changes in service delivery with the aim of optimizing provision for troubled young people.
Clinical case reports can be important sources of information for alerting health professionals to the existence of possible health hazards. Isolated case reports, however, are weak evidence of causal relationships between exposure and disease because they do not provide an indication of the frequency of a particular exposure leading to a disease event. A database of chemicals causing allergic contact dermatitis (ACD) was compiled to discern structure-activity relationships. Clinical reports represented a considerable fraction of the data. Multiple Computer Automated Structure Evaluation (MultiCASE) was used to create a structure-activity model to be used in predicting the ACD activity of untested chemicals. We examined how the predictive ability of the model was influenced by including the case report data in the model. In addition, the model was used to predict the activity of chemicals identified from clinical case reports. The following results were obtained: When chemicals which were identified as dermal sensitizers by only one or two case reports were included in the model, the specificity of the model was reduced. Less than one half of these chemicals were predicted to be active by the most highly evidenced model. These chemicals possessed substructures not previously encountered by any of the models. We conclude that chemicals classified as sensitizers based on isolated clinical case reports be excluded from our model of ACD. The approach described here for evaluating activity of chemicals based on sparse evidence should be considered for use with other endpoints of toxicity when data are correspondingly limited.
BACKGROUND: Self-report and review of medical records are the most common methods for the assessment of past exposures. However, information obtained from self-reports and medical records may not be consistent. This study compared information provided in a self-administered questionnaire with medical records data. METHODS: Self-report and medical records data came from a case-control study on prostate cancer. Cases were 181 patients with primary prostate cancer and controls were 297 men without the disease, enrolled in Group Health Cooperative (GHC) in Seattle. The consistencies between the two data sources were examined. RESULTS: In general, agreement between the two data sources was almost perfect for demographic and anthropometric variables, substantial for the history of inguinal hernia and kidney stones, and moderate for vasectomy, family history of prostate cancer, smoking and alcohol consumption. However, the two data sources generally were poorly concordant for prior genitourinary diseases that have less explicit diagnostic criteria such as benign prostatic hyperplasia and prostatitis. Analyses of discordant data showed that men were more likely to report an exposure or medical condition that could not be verified from medical records. No discernible patterns in the difference of agreement were found according to age, GHC membership length or case-control status. CONCLUSIONS: This study suggests that agreement between self-reported data and medical records data varies depending upon the study variables. While both data sources are subject to some problems, self-report may provide more complete and comparable information, at least for variables unrelated to diagnosis.
The Intensive Care Antimicrobial Resistance Epidemiology project has established laboratory-based surveillance for antimicrobial resistance and antimicrobial use at a subset of hospitals participating in the National Nosocomial Infections Surveillance system. These data illustrate that, for most antimicrobial resistant organisms studied, rates of resistance were highest in the intensive care unit areas and lowest in the outpatient areas. For most of the antimicrobial agents, the rate of use was highest in the intensive care unit areas in parallel to the pattern seen for resistance. These comparative data on antimicrobial use and resistance among similar areas (ie, intensive care unit or other inpatient areas) can be used as a benchmark by participating hospitals to focus their efforts at addressing antimicrobial resistance.