A critical analysis of Discovery Health’s claims-based risk adjustment of mortality rates in South African private sector hospitals

In 2019, Discovery Health published a risk adjustment model to determine standardised mortality rates across South African private hospital systems, with the aim of contributing towards quality improvement in the private healthcare sector. However, the model suffers from limitations due to its design and its reliance on administrative data. The publication’s aim of facilitating transparency is unfortunately undermined by shortcomings in reporting. When designing a risk prediction model, patient-proximate variables with a sound theoretical or proven association with the outcome of interest should be used. The addition of key condition-specific clinical data points at the time of hospital admission will dramatically improve model performance. Performance could be further improved by using summary risk prediction scores such as the EUROSCORE II for coronary artery bypass graft surgery or the GRACE risk score for acute coronary syndrome. In general, model reporting should conform to published reporting standards, and attempts should be made to test model validity by using sensitivity analyses. In particular, the limitations of machine learning prediction models should be understood, and these models should be appropriately developed, evaluated and reported.http://www.samj.org.zaam2023Gordon Institute of Business Science (GIBS

Machine learning models for the early real-time prediction of deterioration in intensive care units: a novel approach to the early identification of high-risk patients

BACKGROUND: Predictive machine learning models have made use of a variety of scoring systems to identify clinical deterioration in ICU patients. However, most of these scores include variables that are dependent on medical staff examining the patient. We present the development of a real-time prediction model using clinical variables that are digital and automatically generated for the early detection of patients at risk of deterioration. METHODS: Routine monitoring data were used in this analysis. ICU patients with at least 24 h of vital sign recordings were included. Deterioration was defined as qSOFA ≥ 2. Model development and validation were performed internally by splitting the cohort into training and test datasets and validating the results on the test dataset. Five different models were trained, tested, and compared against each other. The models were an artificial neural network (ANN), a random forest (RF), a support vector machine (SVM), a linear discriminant analysis (LDA), and a logistic regression (LR). RESULTS: In total, 7156 ICU patients were screened for inclusion in the study, which resulted in models trained from a total of 28,348 longitudinal measurements. The artificial neural network showed a superior predictive performance for deterioration, with an area under the curve of 0.81 over 0.78 (RF), 0.78 (SVM), 0.77 (LDA), and 0.76 (LR), by using only four vital parameters. The sensitivity was higher than the specificity for the artificial neural network. CONCLUSIONS: The artificial neural network, only using four automatically recorded vital signs, was best able to predict deterioration, 10 h before documentation in clinical records. This real-time prediction model has the potential to flag at-risk patients to the healthcare providers treating them, for closer monitoring and further investigation

Systematic Review of the Roost-Site Characteristics of North American Forest Bats: Implications for Conservation

Continued declines in North American bat populations can be largely attributed to habitat loss, disease, and wind turbines. These declines can be partially mitigated through actions that boost reproductive success; therefore, management aimed at promoting availability of high-quality roosting habitat is an important conservation goal. Following the principles of the umbrella species concept, if co-occurring species share similar roost-tree preferences, then management practices targeting one species may confer conservation benefits to another. We conducted a systematic review of roost-site characteristics of thirteen species inhabiting eastern temperate forests to: (1) synthesize existing knowledge across species; (2) assess niche overlap among co-occurring species; and (3) evaluate the potential for currently protected species to serve as conservation umbrellas. We performed multivariate ordination techniques to group species based on the seven most-reported roost-site characteristics, including tree species, diameter at breast height, tree health, roost type, tree height, canopy closure, and roost height. Species sorted into three roosting guilds: (1) southern wetland inhabitants; (2) foliage specialists; and (3) dead tree generalists. Myotis septentrionalis and Perimyotis subflavus had significant roost-niche overlap with five and four other species respectively, and their existing protections make them suitable umbrellas for other bats in the North American eastern temperate forests

Systematic Review of the Roost-Site Characteristics of North American Forest Bats: Implications for Conservation

Continued declines in North American bat populations can be largely attributed to habitat loss, disease, and wind turbines. These declines can be partially mitigated through actions that boost reproductive success; therefore, management aimed at promoting availability of high-quality roosting habitat is an important conservation goal. Following the principles of the umbrella species concept, if co-occurring species share similar roost-tree preferences, then management practices targeting one species may confer conservation benefits to another. We conducted a systematic review of roost-site characteristics of thirteen species inhabiting eastern temperate forests to: (1) synthesize existing knowledge across species; (2) assess niche overlap among co-occurring species; and (3) evaluate the potential for currently protected species to serve as conservation umbrellas. We performed multivariate ordination techniques to group species based on the seven most-reported roost-site characteristics, including tree species, diameter at breast height, tree health, roost type, tree height, canopy closure, and roost height. Species sorted into three roosting guilds: (1) southern wetland inhabitants; (2) foliage specialists; and (3) dead tree generalists. Myotis septentrionalis and Perimyotis subflavus had significant roost-niche overlap with five and four other species respectively, and their existing protections make them suitable umbrellas for other bats in the North American eastern temperate forests.</jats:p

Episodic Gregariousness Leads to Level‐Dependent Core Habitats: A Case Study in Eastern Copperheads (Agkistrodon contortrix)

ABSTRACT Characterizing the complex relationships between animals and their habitats is essential for effective wildlife conservation and management. Wildlife–habitat selection is influenced by multiple life‐history requirements, which act over varying spatial and temporal scales, and result in dispersion patterns that can differ across ecological levels. For example, sites that attract intense communal use (e.g., hibernacula and communal basking sites) are often a subset of the habitats required by individuals for survival. Despite the conservation importance of both individually and communally significant habitats, snake habitat models rarely incorporate information about both individual and population‐level activity. We used 4 years of radiotelemetry data from eastern copperheads (Agkistrodon contortrix) to evaluate the presence of multilevel spatial habitat responses and whether they revealed conservation‐relevant information. We related individual and population space use intensity to underlying habitat covariates to determine whether predictors of copperhead spatial activity were level‐dependent, and whether individual core habitats differed by sex and reproductive state. Copperheads' episodic gregariousness resulted in spatial and environmental separation between individual and communal core habitats. Population‐level use was greatest in rocky, forested habitats associated with winter brumation and spring basking, whereas individual‐level use was greatest in open habitats with woody debris associated with foraging and reproductive behaviors. Male core habitats were open and thickly vegetated while those of females were moderately forested, with gravid female core habitats containing ample woody debris. Our findings demonstrate that multilevel spatial patterns carry conservation‐relevant information about snake habitat relationships. We suspect that behaviors leading to multilevel spatial patterns exist in many wildlife species whose individual spatial activities overlap around shared resources

FIDSSA 2017 Congress Abstracts Oral Presentations

No abstract available.</jats:p

Selecting umbrella species for conservation: A test of habitat models and niche overlap for beach-nesting birds

Umbrella species are rarely selected systematically from a range of candidate species. On sandy beaches, birds that nest on the upper beach or in dunes are threatened globally and hence are prime candidates for conservation intervention and putative umbrella species status. Here we use a maximum-likelihood, multi-species distribution modeling approach to select an appropriate conservation umbrella from a group of candidate species occupying similar habitats. We identify overlap in spatial extent and niche characteristics among four beach-nesting bird species of conservation concern, American oystercatchers (Haematopus palliatus), black skimmers (Rynchops niger), least terns (Sterna antillarum) and piping plovers (Charadrius melodus), across their entire breeding range in New Jersey, USA. We quantify the benefit and efficiency of using each species as a candidate umbrella on the remaining group. Piping plover nesting habitat encompassed 86% of the least tern habitat but only 15% and 13% of the black skimmer and American oystercatcher habitat, respectively. However, plovers co-occur with all three species across 66% of their total nesting habitat extent (~&nbsp;649&nbsp;ha), suggesting their value as an umbrella at the local scale. American oystercatcher nesting habitat covers 100%, 99% and 47% of piping plover, least tern and black skimmer habitat, making this species more appropriate conservation umbrellas at a regional scale. Our results demonstrate that the choice of umbrella species requires explicit consideration of spatial scale and an understanding of the habitat attributes that an umbrella species represents and to which extent it encompasses other species of conservation interest. Notwithstanding the attractiveness of the umbrella species concept, local conservation interventions especially for breeding individuals in small populations may still be needed