169 research outputs found
Simulation and Modeling for Improving Access to Care for Underserved Populations
Indiana University-Purdue University Indianapolis (IUPUI)This research, through partnership with seven Community Health Centers (CHCs)
in Indiana, constructed effective outpatient appointment scheduling systems by
determining care needs of CHC patients, designing an infrastructure for meaningful use of
patient health records and clinic operational data, and developing prediction and simulation
models for improving access to care for underserved populations. The aims of this study
are 1) redesigning appointment scheduling templates based on patient characteristics,
diagnoses, and clinic capacities in underserved populations; 2) utilizing predictive
modeling to improve understanding the complexity of appointment adherence in
underserved populations; and 3) developing simulation models with complex data to guide
operational decision-making in community health centers. This research addresses its aims
by applying a multi-method approach from different disciplines, such as statistics,
industrial engineering, computer science, health informatics, and social sciences. First, a
novel method was developed to use Electronic Health Record (EHR) data for better
understanding appointment needs of the target populations based on their characteristics
and reasons for seeking health, which helped simplify, improve, and redesign current
appointment type and duration models. Second, comprehensive and informative predictive
models were developed to better understand appointment non-adherence in community
health centers. Logistic Regression, NaĂŻve Bayes Classifier, and Artificial Neural Network
found factors contributing to patient no-show. Predictors of appointment non-adherence
might be used by outpatient clinics to design interventions reducing overall clinic no-show rates. Third, a simulation model was developed to assess and simulate scheduling systems
in CHCs, and necessary steps to extract information for simulation modeling of scheduling
systems in CHCs are described. Agent-Based Models were built in AnyLogic to test
different scenarios of scheduling methods, and to identify how these scenarios could impact
clinic access performance. This research potentially improves well-being of and care
quality and timeliness for uninsured, underinsured, and underserved patients, and it helps
clinics predict appointment no-shows and ensures scheduling systems are capable of
properly meeting the populations’ care needs.2021-12-2
Conflicts, integration, hybridization of subcultures: An ecological approach to the case of queercore
This paper investigates the case study of queercore, providing a socio-historical analysis of its subcultural
production, in the terms of what Michel Foucault has called archaeology of knowledge (1969). In
particular, we will focus on: the self-definition of the movement; the conflicts between the two merged
worlds of punk and queer culture; the \u201cinternal-subcultural\u201d conflicts between both queercore and
punk, and between queercore and gay\lesbian music culture; the political aspects of differentiation.
In the conclusion, we will offer an innovative theoretical proposal about the interpretation of subcultures
in ecological and semiotic terms, combining the contribution of the American sociologist Andrew Abbot
and of the Russian semiologist Jurij Michajlovi\u10d Lotma
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