A retrospective study of risk factors for repeated admissions for asthma in a rural/suburban university hospital. (65/1545)

In the study reported, the authors examined risk factors for repeated hospital admissions for asthma in a rural/suburban setting. Charts of patients who were hospitalized two or more times with the diagnosis of asthma between June 1991 and January 1998 were reviewed. A questionnaire was completed for each admission for 65 patients. The results demonstrated an equal male-to-female ratio, with a mean age of 27 years. Hispanics represented 12% of the patients although they accounted for only 2.5% of the general population in the area under study. The mean number of hospital admissions was 3.2. A history of depression existed in 25% of the patients. Noncompliance was admitted in 38%. Twenty-five percent were active tobacco smokers. Acknowledged triggers of asthma included viral infections (74%), exercise (50%), weather conditions (43%), dust (38%), cats (36%), sinusitis (32%), pollen (32%), gastroesophageal reflux disease (31%), dogs (30%), smoke (28%), and emotional stress (15%). Medications at time of admission included albuterol (98%), salmeterol xinafoate (26%), theophylline (38%), ipratropium bromide (55%), nedocromil sodium (20%), cromolyn sodium (35%), prednisone (49%), and inhaled corticosteroids (69%). Ninety-five percent had access to a primary care physician. Fifty-seven percent had a pulmonary and 11% had an allergy consult. These data suggest that patients in rural/suburban areas with repeated hospitalizations for asthma have a high probability of noncompliance, depression, and allergenic triggers. Gastroesophageal reflux was a common recognized trigger. Inhaled steroids were underused, whereas ipratropium and theophylline were overused. Bilingual education on asthma and triggers and social support are necessary even in rural healthcare settings without a large minority population.  (+info)

Allergy test results of a rural and small-city population compared with those of an urban population. (66/1545)

The frequency of sensitization to environmental antigens changes in different regions. As such, the pattern of sensitivity to common allergens was studied at multiple sites across central Pennsylvania, an area composed of small cities and rural communities, to determine uniqueness of allergies in populations from this area in contrast to allergies as determined by skin testing in large urban centers. The study reported was undertaken to determine allergen variation from an urban population compared with a rural population of a Northeastern state so that environmental avoidance and immunotherapy can be more precisely prescribed. Patient charts were retrospectively reviewed to determine sensitivity to house dust mites (Dermatophagoides pteronyssinus, Dermatophagoides farinae), cockroach, Penicillium, Aspergillus spp, dog, cat, timothy grass, ragweed, oak, and Alternaria tenuis at five sites in Pennsylvania. All of these sites were classified as "small city" or "rural" for the study. One hundred patient records were examined at each site for the results of allergy testing by the prick puncture, radioallergosorbent test (RAST), or intradermal methods. These small-city and rural data were pooled and compared with that of the National Cooperative Inner-City Asthma Study (NCI-CAS), which included 1286 patients from urban environments. The prevalence of allergy to both species of dust mites, dog, timothy grass, and ragweed was significantly greater in the pooled rural group than in the NCICAS inner-city patients (P < .05). In contrast, sensitivity to cockroach antigens and Alternaria was significantly greater in the NCICAS urban population than in the pooled rural group (P < .05). No statistically significant difference was found between the NCICAS and the pooled rural patients in reference to Penicillium, cat, and oak (P > .05).  (+info)

Blueprint for discovery in academic medicine: plans, process and outcomes. (67/1545)

By the end of the decade, we had fully implemented most of the recommendations of the Molinoff Report. Our programmatic analysis is summarized in Table 11. While the space needs identified in the Molinoff Report were met by BRB I, II, and III (289,000 nsf as compared [table: see text] to 276,000 nsf as planned), it was possible to provide additional, somewhat unanticipated, research space (111,000 nsf) prior to the end of the decade. The faculty has now developed a research plan for the next decade. It is also important to emphasize that the total faculty grew by 41% [table: see text] over the decade and most of that growth occurred with faculty spending a substantial part of their time in clinical practice. Hence, the dramatic improvement in research funding of over 200% was due largely to the enhanced productivity of our faculty. By taking an organized planning approach deeply seated in the faculty, consistent with Trustee directives and with measurable outcomes, we were successful in growing the research programs within the School of Medicine of the University of Pennsylvania. We believe this particular approach, taken with a focus on multidisciplinary research, [table: see text] was the right one for the 1990s. In the final analysis, it is abundantly clear that outstanding faculty, working in an exciting supportive environment, was the most important factor for success. We are not certain what the right approach will be for the future. Clearly, with the important advances in genomics and information technology, the importance of the team, even if a virtual one world-wide, cannot be overstated. While research is only one mission of the School of Medicine, clearly, our visible success in research played an important role in the overall improvement in the School of Medicine as measured by others. For example, the ranking of the School of Medicine by U.S. News & World Report, perhaps the most widely used ranking by the lay press, went from 10th to 3rd behind only Harvard and Johns Hopkins during the period of the 90s (Table 12).  (+info)

Validation of the ICD/AIS MAP for pediatric use. (68/1545)

OBJECTIVE: To determine the performance of the ICD/AIS MAP (EJ MacKenzie et al) as a method of classifying injury severity for children. METHODS: Data on all children less than 16 years of age admitted to all designated trauma centers in Pennsylvania from January 1994 through October 1996 were obtained from the state trauma registry. The ICD/AIS MAP was used to convert all injury related ICD-9-CM diagnosis codes into abbreviated injury scale (AIS) score and injury severity score (ISS). Agreement between trauma registry AIS and ISS scores and MAP generated scores was assessed using the weighted kappa (kappaw) coefficient for ordered data and the intraclass correlation coefficient for continuous data. RESULTS: Agreement in ISS scores was excellent, both overall (intraclass correlation coefficient = 0.86, 95% confidence interval (CI) 0.84 to 0.89)), and when grouped into three levels of severity (kappaw= 0.86, 95% CI 0.85 to 0.87). Agreement in AIS scores across all body regions and ages was also excellent, (kappaw= 0.86 (95% CI 0.83 to 0.87). Agreement increased with age (kappaw= 0.78 for children <2 years; kappaw= 0.86 for older children) and varied by body region, though was excellent across all regions. CONCLUSIONS: The performance of the ICD/AIS MAP in assessing severity of pediatric injuries was equal to or better than previous assessments of its performance on primarily adult patients. Its performance was excellent across the pediatric age range and across nearly all body regions of injury.  (+info)

Screening for hospitalization and nutritional risks among community-dwelling older persons. (69/1545)

BACKGROUND: The potential for the use of nutritional screening to identify older persons at risk of hospitalization has not been contrasted with the use of tools developed for predicting hospital admissions. OBJECTIVE: Our goal was to compare the associations of items from the Level II Nutrition Screen (LII) and the Probability of Repeated Admissions (P(ra)) questionnaire with the outcome of hospitalization. DESIGN: This was a cohort study of participants in a Medicare managed-risk health plan who completed both the LII and P(ra) (n = 386). All hospitalizations within 1 y of screening were recorded. Hierarchical multivariate logistic regression was used to model associations with hospitalization. RESULTS: P(ra) items that retained significant associations with hospitalization were self-reported health, hospitalization in the past year, and >6 doctor visits in the past year (positive predictive value: 20%; sensitivity: 53.1; specificity: 69.7). LII items that retained significant associations with hospitalization were eating problems and polypharmacy (positive predictive value: 17.9%; sensitivity: 58.0; specificity: 56.3). Those persons designated by the P(ra) score as being at high risk of hospitalization (P(ra) > or = 0.30, 75th percentile) were also more likely to report weight loss, polypharmacy, consumption of a special diet, and functional limitation on the LII. CONCLUSIONS: Retained items from the P(ra) and the LII were comparable in identifying participants at risk of hospitalization. These observations suggest that nutritional risk factors such as eating problems, weight loss, and consumption of special diets should be considered in the management of older persons at risk of hospitalization, irrespective of the screening approach selected.  (+info)

Postpregnant vasectomies.(70/1545)

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Complications of meningococcal disease in college students. (71/1545)

A retrospective study was conducted to provide a description of the risk, complications, fatality, and sequelae associated with invasive meningococcal disease in college students admitted in the Allegheny county (Pennsylvania) hospital system from January 1990 to May 1999.  (+info)

The development of a survey instrument for community health improvement. (72/1545)

OBJECTIVE: To develop a survey instrument that could be used both to guide and evaluate community health improvement efforts. DATA SOURCES/STUDY SETTING: A randomized telephone survey was administered to a sample of about 250 residents in two communities in Lehigh Valley, Pennsylvania in the fall of 1997. METHODS: The survey instrument was developed by health professionals representing diverse health care organizations. This group worked collaboratively over a period of two years to (1) select a conceptual model of health as a foundation for the survey; (2) review relevant literature to identify indicators that adequately measured the health constructs within the chosen model; (3) develop new indicators where important constructs lacked specific measures; and (4) pilot test the final survey to assess the reliability and validity of the instrument. PRINCIPAL FINDINGS: The Evans and Stoddart Field Model of the Determinants of Health and Well-Being was chosen as the conceptual model within which to develop the survey. The Field Model depicts nine domains important to the origins and production of health and provides a comprehensive framework from which to launch community health improvement efforts. From more than 500 potential indicators we identified 118 survey questions that reflected the multiple determinants of health as conceptualized by this model. Sources from which indicators were selected include the Behavior Risk Factor Surveillance Survey, the National Health Interview Survey, the Consumer Assessment of Health Plans Survey, and the SF-12 Summary Scales. The work group developed 27 new survey questions for constructs for which we could not locate adequate indicators. Twenty-five questions in the final instrument can be compared to nationally published norms or benchmarks. The final instrument was pilot tested in 1997 in two communities. Administration time averaged 22 minutes with a response rate of 66 percent. Reliability of new survey questions was adequate. Face validity was supported by previous findings from qualitative and quantitative studies. CONCLUSIONS: We developed, pilot tested, and validated a survey instrument designed to provide more comprehensive and timely data to communities for community health assessments. This instrument allows communities to identify and measure critical domains of health that have previously not been captured in a single instrument.  (+info)