Time-Inconsistent Linear-Quadratic Social Optima for Large Population System

5.4 Exploring Gene Dosage Disorders in the Healthcare Setting

Derivation of Consensus Algorithm Dynamics from Mean Field Stochastic Control NCE Equations

Biological systems involving genetic reactions are large discrete event systems, and often contain certain species that occur in small quantities, and others that occur in large quantities, leading to a difficulty in modelling and simulation. Small populations inhibit the usefulness of utilizing differential equations to represent the system, while the large populations cause stochastic discrete event simulation to become computationally intensive. This paper presents an algorithmic approach for the dynamic partitioning and stochastic hybrid simulation of biological systems. The algorithm uses a Poisson approximation for discrete event generation and a Langevin approximation for continuous behaviour. The populations are dynamically partitioned so that some populations are simulated in a discrete stochastic fashion, while others are simulated by continuous differential equations, and this partition between discrete and continuous behaviour is updated at regular intervals. The hybrid model of a simple biological toggle switch yields promising results, and a more complex example is explored.

Preoperative Frailty and Surgical Outcomes Across Diverse Surgical Subspecialties in a Large Health Care System

Healthcare systems play a key role in hypertension control and health equity promotion in large populations. This study assessed the impact of a multifaceted hypertension control program in a large healthcare system serving Medicare and dual eligible (DE) Beneficiaries primarily of Hispanic origin in South Florida, an understudied population. Leon Medical Centers, a major integrated healthcare services provider to Medicare and DE patients in Miami-Dade, FL, implemented a hypertension control program in 2011. Electronic health records (2008-2018) from patients aged 65-89 years with hypertension were analyzed. Controlled BP definition was annual average systolic BP< 140 mmHg and diastolic BP< 90 mmHg. Age- and diabetes-standardized annual BP control rates were calculated. Random effects modeling compared BP control levels after vs. before program implementation. From 2008 (n=4,710) to 2018 (n=21,540), mean age±SD increased (73.4±5.3 to 77.1±6.1). Proportion of Hispanics remained constant (>98%). Overall age-adjusted odds of BP control were 5.8 (95% confidence interval [CI]: 5.6-6.1) times higher after program implementation. BP control rates increased similarly in both sexes. In women, standardized control rates increased from 68.9-73.3% (2008-2010) to 88.8-92.3% (2013-2018). Standardized control rates tended to be lower in DE than in Medicare patients at baseline – e.g., 2008: 67.2% (65.9-69.3%) vs. 72.2% (70.4-73.8%), but similar after program implementation – e.g., 2018: 89.9% (89.3-90.5%) vs. 90.2% (89.4-91.0%). Implementation of a primary care-based, multicomponent, culturally congruent hypertension control program was associated with meaningful increases in BP control levels in both men and women, and Medicare and DE patients in a large healthcare system in South Florida.

Distributed adaptive tracking-type games is investigated for large population stochastic multi-agent systems. The dynamics of each agent is described by ARMAX model with unknown structure parameters and unknown coupled terms. The performance index has an unknown population state average (PSA) term. In order to deal with the uncertainties, the extended least-squares algorithm is used to estimate the unknown parameters, and the Nash certainty equivalence principle is used to estimate the unknown PSA term. Based on the certainty equivalence principle in adaptive control theory, a distributed adaptive tracking control is designed, under which the closed-loop system is shown to have the following properties: (1) the closed-loop system is almost surely uniformly stable with respect to the population number N; (2) the estimation of PSA is strongly consistent; (3) the adaptive control is almost surely asymptotically optimal in the sense of Nash equilibrium. A numerical example is given to demonstrate the results.

The adoption of predictive modeling for clinical decision support is accelerating in healthcare, however, the need for large sample sizes puts smaller health systems at a disadvantage. Small health systems have insufficient positive cases to build models are left with three choices. First, they can obtain already trained models, which are often too generic. Second, they can participate in research networks, building a model through a network-wide data set. Since small hospitals can only contribute small amounts of data influencing the resulting shared model minimally, this approach yields only minimal specialization. The third option is transfer learning, where a model previously trained on a large population is refined to the specific population, which carries the danger of over-specializing to the idiosyncrasies of the small data set. In this paper, we present a novel paradigm, consensus modeling, that allows a small health system to collaborate with a larger system to build a model specific to the smaller system without sharing any data instances. The method is similar to transfer learning in that it refines models from the larger system to be specific to the small system, but through iterative refinement, the larger system alleviates the risk of over-specializing to the small system. We evaluated the approach on predicting postoperative complications at two health systems with 9,044 and 38,545 patients. The model obtained from the proposed consensus modeling paradigm achieved a predictive performance on the small system that is as good as the transfer learning approach (AUC 0.71 vs 0.71) but significantly outperformed the transfer learning approach on the large dataset (AUC 0.80 vs 0.65) suggesting significantly reduced over-specializing.

Recognizing that social work students traditionally intend to work with individual clients, the authors developed the macro assignment described in this article to encourage master’s-level social work students to stretch their thinking about social work interventions to larger and larger systems. The authors summarize six student presentations and analyze students’ evaluations of the assignment. They assert that if, in a cognitive exercise, students can conceptualize interventions on such scales, they may be able to design programs for agencies and larger populations in their future professional roles.

Improving care of people with diabetes has become a major goal for many institutions. This is particularly important in the Bronx because we deal with a large underserved population of ethnic/racial minorities that is susceptible to more diabetes and further complications. Montefiore Medical Center already has in place many resources, such as multidisciplinary diabetes workgroups committed to implementing quality improvement (QI) projects. To carry on such endeavors, a complex and well-designed administrative support system is required from the executive office. The QI committees rely on step-by-step methodologies to define a series of factors that occur systematically and result in improved care. The large population with diabetes is cared for mainly by primary care physicians (PCPs) that are part of a large sophisticated health care system. Because of both the complexity and diversity of the population, several programs are tailored to the needs of specific subgroups. The implementation of different interventions and their effectiveness and cost must be properly assessed. Thus, QI projects are necessary to provide meaningful information that can be used for improving these health care systems and the patient care they provide. In this article, we describe the population of the Bronx, the structure and programs that are dedicated to diabetes at Montefiore, and our information technology (IT) system and how it can be used for QI programs. We also provide an example of how the system is being used. Although the Bronx is only one borough in New York City, its population is larger than all but five U.S. cities. This is a vibrant and younger population of diverse racial/ethnic backgrounds. Data from the U.S. Census Bureau, year 2000, illustrate how the Bronx statistics compare to national statistics. Average population age in the Bronx is 33.27 years versus 36.22 years nationally (71% are < 44 years of …

We consider a model for interacting objects, where the evolution of each object is given by a finite state Markov chain, whose transition matrix depends on the present and the past of the distribution of states of all objects. This is a general model of wide applicability; we mention as examples: TCP connections, HTTP flows, robot swarms, reputation systems. We show that when the number of objects is large, the occupancy measure of the system converges to a deterministic dynamical system (the "mean field") with dimension the number of states of an individual object. We also prove a fast simulation result, which allows to simulate the evolution of a few particular objects imbedded in a large system. We illustrate how this can be used to model the determination of reputation in large populations, with various liar strategies.

We consider a model for interacting objects, where the evolution of each object is given by a finite state Markov chain, whose transition matrix depends on the present and the past of the distribution of states of all objects. This is a general model of wide applicability; we mention as examples: TCP connections, HTTP flows, robot swarms, reputation systems. We show that when the number of objects is large, the occupancy measure of the system converges to a deterministic dynamical system (the mean field) with dimension the number of states of an individual object. We also prove a fast simulation result, which allows to simulate the evolution of a few particular objects imbedded in a large system. We illustrate how this can be used to model the determination of reputation in large populations, with various liar strategies.

This paper studies linear-quadratic-Gaussian (LQG) games of stochastic large population system with jump-diffusion processes. The most distinguishing feature, compared with the well-studied mean-field LQG games, is that the game system follows linear SDEs driven by random jumps. The individual agents of large population system are coupled both in their state dynamics and in their individual cost functionals. Each agent in large population system has negligible impact on others, but their collective behaviors will impose some significant impact on all agents. The so-called NCE methodology is introduced to deal with the dimensionality difficulty. This methodology derives a set of decentralized strategies, which is an ϵ-Nash equilibrium for a finite N population system where . A numerical example is provided to illustrate the consistency of the mean field estimation and the impact of the population's collective behaviors. As applications, a pricing problem is studied and the decentralized suboptimal price strategy is obtained.

Autism, schizophrenia, and other clinically distinct neurodevelopmental psychiatric disorders (NPDs) have shared genetic etiologies, including single-gene and multigenic copy number variants (CNVs). Because rare variants are primarily investigated in clinical cohorts, population-based estimates of their prevalence and penetrance are lacking. The authors determined the prevalence, penetrance, and NPD risk of pathogenic single-gene variants in a large health care system population. The authors analyzed linked genomic and electronic health record (EHR) data in a subset of 90,595 participants from Geisinger's MyCode Community Health Initiative, known as the DiscovEHR cohort. Loss-of-function pathogenic variants in 94 high-confidence NPD genes were identified through exome sequencing, and NPD penetrance was calculated using preselected EHR diagnosis codes. NPD risk was estimated using a case-control comparison of DiscovEHR participants with and without NPD diagnoses. Results from single-gene variant analyses were also compared with those from 31 previously reported pathogenic NPD CNVs. Pathogenic variants were identified in 0.34% of the DiscovEHR cohort and demonstrated a 34.3% penetrance for NPDs. Similar to CNVs, sequence variants collectively conferred a substantial risk for several NPD diagnoses, including autism, schizophrenia, and bipolar disorder. Significant NPD risk remained after participants with intellectual disability were excluded from the analysis, confirming the association with major psychiatric disorders in individuals without severe cognitive deficits. Collectively, rare single-gene variants and CNVs were found in >1% of individuals in a large health care system population and play an important contributory role in mental health disorders. Diagnostic genetic testing for pathogenic variants among symptomatic individuals with NPDs could improve clinical outcomes through early intervention and anticipatory therapeutic support.

Critical questions about cancer prevention, care, and outcomes increasingly require research involving large patient populations and their care delivery organizations. The Cancer Research Network (CRN) includes 11 integrated health systems funded by the National Cancer Institute (NCI) to conduct collaborative cancer research. This article describes the challenges of constructing a productive consortium of large health systems, and explores the CRN's responses. The CRN was initially funded through an NCI cooperative agreement in 1999 and has since received a second 4-year grant. Leadership and policy development are provided through a steering committee, subcommittees, and an external advisory committee. The CRN includes integral and affiliated research projects supported by a Scientific and Data Resources Core. Three characteristics of the CRN intensified the general challenges of consortium research: 1) its members are large health systems with legitimate concerns about confidentiality of data about enrollees, providers, and the organization; 2) CRN research projects often generate highly sensitive data about quality of care; and therefore 3) each participating organization wants a strong voice in CRN direction. CRN experience to date confirms that a consortium of health systems with internal research capacity can address a range of important cancer research questions that would be difficult to study in other venues. The advantages and challenges of consortium research are explored, with suggestions for the development, execution, and management of multisystem population laboratories.

Evaluation of pharmacist-led management of type 2 diabetes using personal continuous glucose monitors across a large tertiary academic health system.