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Condition Categories (condition + category)
Selected AbstractsDo Hierarchical Condition Category Model Scores Predict Hospitalization Risk in Newly Enrolled Medicare Advantage Participants as Well as Probability of Repeated Admission Scores?JOURNAL OF AMERICAN GERIATRICS SOCIETY, Issue 12 2009David G. Mosley MHA OBJECTIVES: To compare how well hierarchical condition categories (HCC) and probability of repeated admission (PRA) scores predict hospitalization. DESIGN: Longitudinal cohort study with 12-month follow-up. SETTING: A Medicare Advantage (MA) plan. PARTICIPANTS: Four thousand five hundred six newly enrolled beneficiaries. MEASUREMENT: HCC scores were identified from enrollment files. The PRA tool was administered by mail and telephone. Inpatient admissions were based on notifications. The Mann-Whitney test was used to compare HCC scores of PRA responders and nonresponders. The receiver operating characteristic curve provided the area under the curve (AUC) for each score. Admission risk in the top 5% of scores was evaluated using logistic regression. RESULTS: Within 60 days of enrollment, 45.1% of the 3,954 beneficiaries with HCC scores completed the PRA tool. HCC scores were lower for the 1,783 PRA respondents than the 2,171 nonrespondents (0.71 vs 0.81, P<.001). AUCs predicting hospitalization with regard to HCC and PRA were similar (0.638, 95% confidence interval (CI)=0.603,0.674; 0.654, 95% CI=0.618,0.690). Individuals identified in the top 5% of scores using both tools, using HCC alone, or using PRA alone had higher risk for hospitalization than those below the 95th percentile (odds ratio (OR)=8.5, 95% CI=3.7,19.4, OR=3.8, 95% CI=2.3,6.3, and OR=3.9, 95% CI=2.3,6.4, respectively). CONCLUSION: HCC scores provided to MA plans for risk adjustment of revenue can also be used to identify hospitalization risk. Additional studies are required to evaluate whether a hybrid approach incorporating administrative and self-reported models would further optimize risk stratification efforts. [source] Development of an Index of Biotic Integrity for a Southeastern Coastal Plain Watershed, USA,JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 2 2007Charles C. Morris Abstract:, This study evaluated biological integrity expectations of fish assemblages in wadeable streams for the Alabama portion of the Choctawhatchee River watershed using a multimetric approach. Thirty-four randomly selected stream sites were sampled in late spring 2001 to calibrate an index of biotic integrity (IBI). Validation data were collected during the spring 2001, and summer and fall of 2003 from disturbed and least-impacted targeted sites (n = 20). Thirty-five candidate metrics were evaluated for their responsiveness to environmental degradation. Twelve metrics were selected to evaluate wadeable streams and four replacement metrics were selected for headwater streams. Scores that ranged from 58 to 60 were considered to be representative of excellent biotic integrity (none found in this study), scores of 48-52 as good integrity (31% of the sites in this study), 40-44 as fair (43%), 28-34 as poor (21%), and 12-22 as very poor (5%). Of the four stream condition categories (urban, cattle, row crop, and least impacted), the IBI scores for urban and cattle sites differed significantly from least-impacted sites. Row crop sites, although not significantly different from least-impacted, tended to have greater variability than the other categories. Lower IBI scores at both urban and cattle sites suggest that the IBI accurately reflects stream impairment in the Choctawhatchee River drainage. [source] Habitat selection and sampling design for ecological assessment of heterogeneous ponds using macroinvertebratesAQUATIC CONSERVATION: MARINE AND FRESHWATER ECOSYSTEMS, Issue 7 2009Cristina Trigal-Domínguez Abstract 1.Habitat heterogeneity has many implications in ecological assessment studies. On one hand it provides varying niches for organisms, increasing diversity. On the other hand, the inherent spatial variability of structurally complex systems may overlap with ecological condition making it difficult to disentangle the effects of perturbation. This study investigated the combined and single effects of habitat and pond condition on the macroinvertebrate assemblages of 35 ponds located in north-west Spain and spanning a range of water quality and habitat characteristics. 2.Macroinvertebrate communities and several environmental variables were sampled in the summer of 2004 or 2003. Samples were collected from four dominant habitats (vegetated shores, shores without vegetation, submerged vegetation, bare sediments) following a time-limited sampling. Non-metric multidimensional scaling and two-way crossed ANOSIM were used to investigate the taxonomic and functional differences in macroinvertebrate assemblage structure among habitats (four types) and pond conditions (optimal, good, moderate, poor, very poor). To investigate the individual and combined effects of pond condition and habitat on several diversity measures GLM models were used. In addition, the accuracy of two sampling designs , stratified and multihabitat , was compared using the CVs of seven macroinvertebrate attributes. 3.Results showed that macroinvertebrate communities differed significantly, albeit weakly, among habitat types and pond condition categories. In particular, the abundance of several Chironomidae genera, rarefied richness and Shannon index decreased both in perturbed systems and bare sediments, whereas no marked differences occurred between shores and submerged vegetation. 4.We suggest that a multihabitat approach together with the use of community attributes not (or slightly) affected by habitat type will provide more comparable results across ponds than a stratified approach or observation of the whole community, especially in ponds where degradation leads to habitat loss.Copyright © 2009 John Wiley & Sons, Ltd. [source] Fund allocation within Australian dental care: an innovative approach to output based fundingAUSTRALIAN DENTAL JOURNAL, Issue 4 2005M. Tennant Abstract Background: Over the last 15 years in Australia the process of funding government health care has changed significantly. The development of dental funding models that transparently meet both the service delivery needs for data at the treatment level and policy makers' need for health condition data is critical to the continued integration of dentistry into the wider health system. Methods: This paper presents a model of fund allocation that provides a communication construct that addresses the needs of both policy makers and service providers. Results: In this model, dental treatments (dental item numbers) have been grouped into eight broad dental health conditions. Within each dental health condition, a weighted average price is determined using the Department of Veterans Affairs' (DVA) fee schedule as the benchmark, adjusted for the mix of care. The model also adjusts for the efficiency differences between sectors providing government funded dental care. In summary, the price to be applied to a dental health condition category is determined by the weighted average DVA price adjusted by the sector efficiency. Conclusions: This model allows governments and dental service providers to develop funding agreements that both quantify and justify the treatment to be provided. Such a process facilitates the continued integration of dental care into the wider health system. [source] | ||||||||||