scholarly journals A strengths-based data capture model: mining data-driven and person-centered health assets

JAMIA Open ◽  
2018 ◽  
Vol 1 (1) ◽  
pp. 11-14
Author(s):  
Grace Gao ◽  
Madeleine J Kerr ◽  
Ruth A Lindquist ◽  
Chih-Lin Chi ◽  
Michelle A Mathiason ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Health Care ◽  
Health Care Policy ◽  
Population Level ◽  
Data Capture ◽  
Data Driven ◽  
Individual Level ◽  
Centered Care ◽  
The Individual ◽  
Health Assets

Abstract With health care policy directives advancing value-based care, risk assessments and management have permeated health care discourse. The conventional problem-based infrastructure defines what data are employed to build this discourse and how it unfolds. Such a health care model tends to bias data for risk assessment and risk management toward problems and does not capture data about health assets or strengths. The purpose of this article is to explore and illustrate the incorporation of a strengths-based data capture model into risk assessment and management by harnessing data-driven and person-centered health assets using the Omaha System. This strengths-based data capture model encourages and enables use of whole-person data including strengths at the individual level and, in aggregate, at the population level. When aggregated, such data may be used for the development of strengths-based population health metrics that will promote evaluation of data-driven and person-centered care, outcomes, and value.

scholarly journals Financial and Labor Benefits of the Individual TB Risk Assessment Model for Annual TB Screening

2020 ◽  
Vol 41 (S1) ◽  
pp. s234-s234
Author(s):  
Kristin Sims ◽  
Roger Stienecker
Keyword(s):  
Risk Assessment ◽  
Health Care ◽  
Assessment Model ◽  
Health Care Personnel ◽  
Individual Risk ◽  
Tuberculosis Screening ◽  
Hospital System ◽  
National Tuberculosis ◽  
The Individual ◽  
The Cost

Background: Since 1991, US tuberculosis (TB) rates have declined, including among health care personnel (HCP). Non–US born persons accounted for approximately two-thirds of cases. Serial TB testing has limitations in populations at low risk; it is expensive and labor intensive. Method: We moved a large hospital system from facility-level risk stratification to an individual risk model to guide TB screening based on Tuberculosis Screening, Testing, and Treatment of US Health Care Personnel: Recommendations from the National Tuberculosis Controllers Association and CDC, 2019. This process included individual TB risk assessment, symptom evaluation, TB testing for M. tuberculosis infection (by either IGRA or TST) for HCP without documented evidence of prior LTBI or TB disease, with an additional workup for TB disease for HCP with positive test results or symptoms compatible with TB disease. In addition, employees with specific job codes deemed high risk were required to undergo TB screening. Result: In 2018, this hospital system of ~10,000 employees screened 7,556 HCP for TB at a cost of $348,625. In 2019, the cost of the T Spot test increased from $45 to $100 and the cost of screening 5,754 HCP through October 31, 2019, was $543,057. In 2020, it is anticipated that 755 HCP will be screened, saving the hospital an estimated minimum of $467,557. The labor burden associated with employee health personnel will fall from ~629.66 hours to 62.91 hours. The labor burden associated with pulling HCPs from the bedside to be screened will be reduced from 629.66 hours to 62.91 hours as well. Conclusion: Adoption of the individual risk assessment model for TB screening based on Tuberculosis Screening, Testing, and Treatment of US Health Care Personnel: Recommendations from the National Tuberculosis Controllers Association and CDC, 2019 will greatly reduce financial and labor burdens in healthcare settings when implemented.Funding: NoneDisclosures: None

scholarly journals Migration, acculturation, and the maintenance of between-group cultural variation

2017 ◽  
Author(s):  
Alex Mesoudi
Keyword(s):  
Social Learning ◽  
Cultural Values ◽  
Cultural Evolution ◽  
Population Level ◽  
Empirical Literature ◽  
Cultural Variation ◽  
Individual Level ◽  
And Migration ◽  
The Individual ◽  
Social Learning Processes

AbstractHow do migration and acculturation (i.e. psychological or behavioral change resulting from migration) affect within- and between-group cultural variation? Here I answer this question by drawing analogies between genetic and cultural evolution. Population genetic models show that migration rapidly breaks down between-group genetic structure. In cultural evolution, however, migrants or their descendants can acculturate to local behaviors via social learning processes such as conformity, potentially preventing migration from eliminating between-group cultural variation. An analysis of the empirical literature on migration suggests that acculturation is common, with second and subsequent migrant generations shifting, sometimes substantially, towards the cultural values of the adopted society. Yet there is little understanding of the individual-level dynamics that underlie these population-level shifts. To explore this formally, I present models quantifying the effect of migration and acculturation on between-group cultural variation, for both neutral and costly cooperative traits. In the models, between-group cultural variation, measured using F statistics, is eliminated by migration and maintained by conformist acculturation. The extent of acculturation is determined by the strength of conformist bias and the number of demonstrators from whom individuals learn. Acculturation is countered by assortation, the tendency for individuals to preferentially interact with culturally-similar others. Unlike neutral traits, cooperative traits can additionally be maintained by payoff-biased social learning, but only in the presence of strong sanctioning institutions. Overall, the models show that surprisingly little conformist acculturation is required to maintain realistic amounts of between-group cultural diversity. While these models provide insight into the potential dynamics of acculturation and migration in cultural evolution, they also highlight the need for more empirical research into the individual-level learning biases that underlie migrant acculturation.

scholarly journals General intelligence disentangled via a generality metric for natural and artificial intelligence

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
José Hernández-Orallo ◽  
Bao Sheng Loe ◽  
Lucy Cheke ◽  
Fernando Martínez-Plumed ◽  
Seán Ó hÉigeartaigh
Keyword(s):  
Task Difficulty ◽  
Population Level ◽  
Limited Resources ◽  
General Intelligence ◽  
Individual Level ◽  
Cognitive Efficiency ◽  
Comprehensive Performance ◽  
Individual Measure ◽  
Level Of Difficulty ◽  
The Individual

AbstractSuccess in all sorts of situations is the most classical interpretation of general intelligence. Under limited resources, however, the capability of an agent must necessarily be limited too, and generality needs to be understood as comprehensive performance up to a level of difficulty. The degree of generality then refers to the way an agent’s capability is distributed as a function of task difficulty. This dissects the notion of general intelligence into two non-populational measures, generality and capability, which we apply to individuals and groups of humans, other animals and AI systems, on several cognitive and perceptual tests. Our results indicate that generality and capability can decouple at the individual level: very specialised agents can show high capability and vice versa. The metrics also decouple at the population level, and we rarely see diminishing returns in generality for those groups of high capability. We relate the individual measure of generality to traditional notions of general intelligence and cognitive efficiency in humans, collectives, non-human animals and machines. The choice of the difficulty function now plays a prominent role in this new conception of generality, which brings a quantitative tool for shedding light on long-standing questions about the evolution of general intelligence and the evaluation of progress in Artificial General Intelligence.

scholarly journals Ecology and Prediction of Compensatory Growth: From Theory to Application in Forestry

2021 ◽  
Vol 12 ◽  
Author(s):  
Chao Li ◽  
Hugh Barclay ◽  
Bernard Roitberg ◽  
Robert Lalonde
Keyword(s):  
Compensatory Growth ◽  
Population Level ◽  
Human Society ◽  
Common Phenomenon ◽  
Partial Mortality ◽  
Individual Level ◽  
State Dependent ◽  
Dependent Model ◽  
Accelerated Growth ◽  
The Individual

Compensatory growth has been observed in forests, and it also appears as a common phenomenon in biology. Though it sometimes takes different names, the essential meanings are the same, describing the accelerated growth of organisms when recovering from a period of unfavorable conditions such as tissue damage at the individual level and partial mortality at the population level. Diverse patterns of compensatory growth have been reported in the literature, ranging from under-, to compensation-induced-equality, and to over-compensation. In this review and synthesis, we provide examples of analogous compensatory growth from different fields, clarify different meanings of it, summarize its current understanding and modeling efforts, and argue that it is possible to develop a state-dependent model under the conceptual framework of compensatory growth, aimed at explaining and predicting diverse observations according to different disturbances and environmental conditions. When properly applied, compensatory growth can benefit different industries and human society in various forms.

scholarly journals Opposite outcomes of coinfection at individual and population scales

2018 ◽  
Vol 115 (29) ◽  
pp. 7545-7550 ◽  
Author(s):  
Erin E. Gorsich ◽  
Rampal S. Etienne ◽  
Jan Medlock ◽  
Brianna R. Beechler ◽  
Johannie M. Spaan ◽  
...  
Keyword(s):  
Reproduction Number ◽  
Negative Impact ◽  
Scale Up ◽  
Population Level ◽  
Clear Understanding ◽  
African Buffalo ◽  
Global Public Health ◽  
Individual Level ◽  
Secondary Infections ◽  
The Individual

Coinfecting parasites and pathogens remain a leading challenge for global public health due to their consequences for individual-level infection risk and disease progression. However, a clear understanding of the population-level consequences of coinfection is lacking. Here, we constructed a model that includes three individual-level effects of coinfection: mortality, fecundity, and transmission. We used the model to investigate how these individual-level consequences of coinfection scale up to produce population-level infection patterns. To parameterize this model, we conducted a 4-y cohort study in African buffalo to estimate the individual-level effects of coinfection with two bacterial pathogens, bovine tuberculosis (bTB) and brucellosis, across a range of demographic and environmental contexts. At the individual level, our empirical results identified bTB as a risk factor for acquiring brucellosis, but we found no association between brucellosis and the risk of acquiring bTB. Both infections were associated with reductions in survival and neither infection was associated with reductions in fecundity. The model reproduced coinfection patterns in the data and predicted opposite impacts of coinfection at individual and population scales: Whereas bTB facilitated brucellosis infection at the individual level, our model predicted the presence of brucellosis to have a strong negative impact on bTB at the population level. In modeled populations where brucellosis was present, the endemic prevalence and basic reproduction number (R0) of bTB were lower than in populations without brucellosis. Therefore, these results provide a data-driven example of competition between coinfecting pathogens that occurs when one pathogen facilitates secondary infections at the individual level.

Health Economics: Select Concepts of the Health Production Function, Risk, and Insurance

2018 ◽  
Author(s):  
Bruce L Hall
Keyword(s):  
Health Care ◽  
Health Economics ◽  
Health Care Policy ◽  
Insurance Contract ◽  
Health Care Economics ◽  
Health Production ◽  
Health Production Function ◽  
Concept Of Health ◽  
The Individual ◽  
Entire Theory

The production of health as an output of various inputs is a key concept of health care economics and a key influence on health care policy. Similarly, the notion of risk—that an outcome might not turn out as expected or hoped—underpins the entire theory of insurance. Insurance, and the benefits it can provide, cannot be understood without understanding risk, or without understanding how the features of an insurance contract transform risk for the individual, the payer, or society. The health economist, policy maker, leader, expert operator, financier, insurer, clinician of any stripe, patient or family or advocate, or other interested stakeholder must always consider the structural, clinical, and economic anatomy of health care in the context of the underlying physiology of these economic concepts. This review contains 2 figures, 1 table, and 14 references. Key Words: health economics, health policy, health production, marginal return (diminishing), utility, inputs, QALY, risk (aversion or tolerance), insurance (contract features)

scholarly journals Smart Sanitation—Biosensors as a Public Health Tool in Sanitation Infrastructure

2020 ◽  
Vol 17 (14) ◽  
pp. 5146 ◽  
Author(s):  
Emma Rary ◽  
Sarah M. Anderson ◽  
Brandon D. Philbrick ◽  
Tanvi Suresh ◽  
Jasmine Burton
Keyword(s):  
Public Health ◽  
Health Monitoring ◽  
Disease Surveillance ◽  
Population Level ◽  
Cost Effective ◽  
Small Scale ◽  
Individual Level ◽  
Emergent Technologies ◽  
The Individual ◽  
Sanitation Infrastructure

The health of individuals and communities is more interconnected than ever, and emergent technologies have the potential to improve public health monitoring at both the community and individual level. A systematic literature review of peer-reviewed and gray literature from 2000-present was conducted on the use of biosensors in sanitation infrastructure (such as toilets, sewage pipes and septic tanks) to assess individual and population health. 21 relevant papers were identified using PubMed, Embase, Global Health, CDC Stacks and NexisUni databases and a reflexive thematic analysis was conducted. Biosensors are being developed for a range of uses including monitoring illicit drug usage in communities, screening for viruses and diagnosing conditions such as diabetes. Most studies were nonrandomized, small-scale pilot or lab studies. Of the sanitation-related biosensors found in the literature, 11 gathered population-level data, seven provided real-time continuous data and 14 were noted to be more cost-effective than traditional surveillance methods. The most commonly discussed strength of these technologies was their ability to conduct rapid, on-site analysis. The findings demonstrate the potential of this emerging technology and the concept of Smart Sanitation to enhance health monitoring at the individual level (for diagnostics) as well as at the community level (for disease surveillance).

scholarly journals Individual-Level and Population-Level Lateralization: Two Sides of the Same Coin

Symmetry ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 739 ◽  
Author(s):  
Elisa Frasnelli ◽  
Giorgio Vallortigara
Keyword(s):  
Evolutionarily Stable Strategy ◽  
Population Level ◽  
Point Of View ◽  
Theoretical Point ◽  
Evolutionarily Stable Strategies ◽  
Functional Roles ◽  
Individual Level ◽  
Social Species ◽  
The Individual ◽  
Evolutionarily Stable

Lateralization, i.e., the different functional roles played by the left and right sides of the brain, is expressed in two main ways: (1) in single individuals, regardless of a common direction (bias) in the population (aka individual-level lateralization); or (2) in single individuals and in the same direction in most of them, so that the population is biased (aka population-level lateralization). Indeed, lateralization often occurs at the population-level, with 60–90% of individuals showing the same direction (right or left) of bias, depending on species and tasks. It is usually maintained that lateralization can increase the brain’s efficiency. However, this may explain individual-level lateralization, but not population-level lateralization, for individual brain efficiency is unrelated to the direction of the asymmetry in other individuals. From a theoretical point of view, a possible explanation for population-level lateralization is that it may reflect an evolutionarily stable strategy (ESS) that can develop when individually asymmetrical organisms are under specific selective pressures to coordinate their behavior with that of other asymmetrical organisms. This prediction has been sometimes misunderstood as it is equated with the idea that population-level lateralization should only be present in social species. However, population-level asymmetries have been observed in aggressive and mating displays in so-called “solitary” insects, suggesting that engagement in specific inter-individual interactions rather than “sociality” per se may promote population-level lateralization. Here, we clarify that the nature of inter-individuals interaction can generate evolutionarily stable strategies of lateralization at the individual- or population-level, depending on ecological contexts, showing that individual-level and population-level lateralization should be considered as two aspects of the same continuum.

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