Mariel S. Lavieri

• University of Michigan

Supply chain disruptions and demand disruptions make it challenging for hospital pharmacy managers to determine how much inventory to have on-hand. Having insufficient inventory leads to drug shortages, while having excess inventory leads to drug waste. To mitigate drug shortages and waste, hospital pharmacy managers can implement inventory policie...

Long-term adherence to medication is a critical factor in preventing chronic diseases, such as cardiovascular disease. To address poor adherence, physicians may recommend adherence-improving interventions; however, such interventions are costly and limited in their availability. Knowing which patients will stop adhering helps distribute the availab...

Long-term adherence to medication is a critical factor in preventing chronic diseases, such as cardiovascular disease. To address poor adherence, physicians may recommend adherence-improving interventions; however, such interventions are costly and limited in their availability. Knowing which patients will stop adhering helps distribute the availab...

Background: A key component of return-to-play (RTP) from sport-related concussion is the symptom-free waiting period (SFWP), i.e., the period during which athletes must remain symptom-free before permitting RTP. Yet, the exact relationship between SFWP and post-RTP injury rates is unclear. Objective: We design computational simulations to estima...

Patient‐reported outcomes (PROs) play an increasingly important role in medical decision making. Yet, patients whose objectives differ from their physician's may strategically report symptoms to alter treatment decisions. For example, athletes may underreport symptoms to expedite return‐to‐play (RTP) from sports‐related concussion (SRC). Thus, clin...

Preventing chronic diseases is an essential aspect of medical care. To prevent chronic diseases, physicians focus on monitoring their risk factors and prescribing the necessary medication. The optimal monitoring policy depends on the patient's risk factors and demographics. Monitoring too frequently may be unnecessary and costly; on the other hand,...

Background and Objective Computer-based neurocognitive tests are widely used in sport-related concussion management, but the performance of these tests is not well understood in the participant population with attention-deficit/hyperactivity disorder (ADHD) and/or learning disorder (LD). This research estimates the sensitivity and specificity perfo...

Background: In the United States, the demand for organ transplants far outpaces available organs. The use of Organ Procurement and Transplantation Network -defined ineligible donors is an immediate method for increasing donations. However, the use of ineligible donors varies across organ procurement organizations (OPOs), and its association with r...

Continuous tracking of patient’s health data through electronic health records (EHRs) has created an opportunity to predict healthcare policies’ long-term impacts. Despite the advances in EHRs, data may be missing or sparsely collected. In this article, we use EHR data to develop a simulation model to test multiple treatment guidelines for cardiova...

In managing patients with chronic diseases, such as open angle glaucoma (OAG), the case treated in this paper, medical tests capture the disease phase (e.g. regression, stability, progression, etc.) the patient is currently in. When medical tests have low residual variability (e.g. empirical difference between the patient’s true and recorded value...

Purpose To assess whether the predictive accuracy of machine learning algorithms using Kalman filtering for forecasting future values of global indices on perimetry can be enhanced by adding global retinal nerve fiber layer (RNFL) data and whether model performance is influenced by the racial composition of the training and testing sets. Design Re...

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Objectives. There are several approaches such as presumed consent and compensation for deceased donor organs that could reduce the gap between supply and demand for kidneys. Our objective is to evaluate the magnitude of the economic impact of policies to increase deceased donor organ donation in the United States. Methods. We built a Markov model a...

Background: Optimizing organ yield (number of organs transplanted per donor) is a potentially modifiable way to increase the number of organs available for transplant. Models to predict the expected deceased donor organ yield have been developed based on ordinary least squares regression and logistic regression. However, alternative modeling metho...

Few studies have analyzed the Sport Concussion Assessment Tool's (SCAT) utility among athletes whose concussion assessment is challenging. Using a previously published algorithm, we identified Possible and Probable concussions at <6h (n=393 males, n=265 females) and 24-48h (n=323 males, n=236 females) post-injury within collegiate student-athletes...

Background To optimally care for concussed individuals, a multi-dimensional approach is critical and a key component of this assessment in the athletic environment is computer-based neurocognitive testing. However, there continues to be concerns about the reliability and validity of these testing tools. The purpose of this study was to determine th...

Atherosclerotic cardiovascular disease (ASCVD) is among the leading causes of death in the US. Although research has shown that ASCVD has genetic elements, the understanding of how genetic testing influences its prevention and treatment has been limited. To this end, we model the health trajectory of patients stochastically and determine treatment...

Importance Organ transplant is a life-saving procedure for patients with end-stage organ failure. In the US, organ procurement organizations (OPOs) are responsible for the evaluation and procurement of organs from donors who have died; however, there is controversy regarding what measures should be used to evaluate their performance. Objective To...

Objective: To compare forecasted changes in mean deviation (MD) on perimetry for patients with normal-tension glaucoma (NTG) and high-tension glaucoma (HTG) at different target intraocular pressures (IOPs) using a machine-learning technique called Kalman Filtering (KF). Design: Retrospective cohort study. Participants: 496 patients with HTG fr...

Background: After release of the Comprehensive Care for Joint Replacement bundle, there has been increased emphasis on reducing readmission rates for total knee arthroplasty (TKA). The potential for a separate, clinically-relevant metric, TKA revision rates within a year following surgery, has not been fully explored. Based on this, we compared ra...

Background: The Sport Concussion Assessment Tool (SCAT) could be improved by identifying critical subsets that maximize diagnostic accuracy and eliminate low information elements. Objective: To identify optimal SCAT subsets for acute concussion assessment. Methods: Using Concussion Assessment, Research, and Education (CARE) Consortium data, we...

Objectives To better understand the financial implications of readmission after radical cystectomy, an expensive surgery coupled with a high readmission rate. Currently, whether hospitals benefit financially from readmissions after radical cystectomy remains unclear, and potentially obscures incentives to invest in readmission reduction efforts. M...

The increasing availability of data has popularized risk estimation models in many industries, especially healthcare. However, properly utilizing these models for accurate diagnosis decisions remains challenging. Our research aims to determine when a risk estimation model provides sufficient evidence to make a positive or negative diagnosis, or if...

Objective: To determine if the addition of electronic health record data enables better risk stratification and readmission prediction after radical cystectomy. Despite efforts to reduce their frequency and severity, complications and readmissions following radical cystectomy remain common. Leveraging readily available, dynamic information such as...

Importance The Hospital Readmissions Reduction Program (HRRP) is a Centers for Medicare and Medicaid Services policy that levies hospital reimbursement penalties based on excess readmissions of patients with 4 medical conditions and 3 surgical procedures. A greater understanding of factors associated with the 3 surgical reimbursement penalties is n...

Importance Techniques that properly identify patients in whom ocular hypertension (OHTN) is likely to progress to open-angle glaucoma can assist clinicians with deciding on the frequency of monitoring and the potential benefit of early treatment. Objective To test whether Kalman filtering (KF), a machine learning technique, can accurately forecast...

Importance Presumed consent, or an opt-out organ transplant policy, has been adopted by many countries worldwide to increase organ donation. The implication of such a policy for transplants in the United States is uncertain, however. Objective To simulate the potential implications of a presumed consent policy in the United States. Design, Settin...

Objective To examine predictors of early readmissions after radical cystectomy (RC). Factors associated with preventable readmissions may be most evident in readmissions that occur within 3 days of discharge, commonly termed ‘bounce‐back’ readmissions, and identifying such factors may inform efforts to reduce surgical readmissions. Patients and Me...

Background: Genetic studies suggest that the relative risk reduction (RRR) of statins may increase over time, potentially resulting in much greater long-term benefit if statins are started before cardiovascular (CV) risk is high. Methods: We used a nationally representative sample of American adults to estimate effects of initiating a statin when 1...

Background: Payment models, including the Hospital Readmissions Reduction Program and bundled payments, place pressures on hospitals to limit readmissions. Against this backdrop, we sought to investigate the association of post-acute care after major surgery and readmission rates. Methods: We identified patients undergoing high-risk surgery (abd...

To manage chronic disease patients effectively, clinicians must know (1) how to monitor each patient (i.e., when to schedule the next visit and which tests to take), and (2) how to control the disease (i.e., what levels of controllable risk factors will sufficiently slow progression). Our research addresses these questions simultaneously and provid...

Purpose: To determine whether a machine learning technique called Kalman filtering (KF) can accurately forecast future values of mean deviation (MD), pattern standard deviation, and intraocular pressure for patients with normal tension glaucoma (NTG). Design: Development and testing of a forecasting model for glaucoma progression. Methods: We...

While operations research has contributed heavily to the derivation of optimal treatment guidelines for chronic diseases, patient adherence to treatment plans is low and variable. One mechanism for improving patient adherence to guidelines is to tailor coinsurance rates for prescription medications to patient characteristics. We seek to find coinsu...

This paper seeks an efficient way to screen a population of patients at risk for hepatocellular carcinoma when (1) each patient’s disease evolves stochastically and (2) there are limited screening resources shared by the population. Recent medical discoveries have shown that biological information can be learned at each screening to differentiate p...

Background The Comprehensive Care for Joint Replacement (CJR) bundle was created to decrease total knee arthroplasty (TKA) cost. To help accomplish this, there is a focus on reducing TKA readmissions. However, there is a lack of national representative sample of all-payer hospital admissions to direct strategy, identify risk factors for readmission...

Research Objective: Polygenic risk scores can improve prediction of first-time cardiovascular disease (CVD). Prediction of future events is the central factor in statin use in current guidelines Therefore, we hypothesized that if polygenic risk scores were added to current risk scores, statin use could become more efficient. We performed a cost-eff...

Hospital readmissions affect hundreds of thousands of patients every year, negatively impacting patients and placing a tremendous burden on the national healthcare system. Post‐discharge checkup policies can reduce readmissions through early detection of health conditions, however, the methods behind designing effective checkup policies are poorly...

Purpose: To generate personalized forecasts of how patients with open-angle glaucoma (OAG) experience disease progression at different intraocular pressure (IOP) levels to aid clinicians with setting personalized target IOPs. Design: Secondary analyses using longitudinal data from 2 randomized controlled trials. Participants: Participants with...

Nonalcoholic steatohepatitis (NASH) cirrhosis is the fastest growing indication for liver transplantation (LT) in the United States. We aimed to determine the temporal trend behind the rise in obesity and NASH-related additions to the LT waitlist in the United States and make projections for future NASH burden on the LT waitlist. We used data from...

Background: Clinical decisions require weighing possible risks and benefits, which are often based on the provider's sense of treatment burden. Patients often have a different view of how heavily treatment burden should be weighted. Objective: To examine how much small variations in patient treatment burden would influence optimal use of antihypert...

Background To reduce the geographic heterogeneity in liver transplant (LT) allocation the United Network of Organ Sharing (UNOS) has proposed redistricting, which is impacted by both donor supply and LT demand. We aimed to determine the impact of demographic changes on the redistricting proposal and characterize causes behind geographic heterogenei...

Background: The Hospital Readmissions Reduction Program reduces payments to hospitals with excess readmissions for three common medical conditions and recently extended its readmission program to surgical patients. We sought to investigate readmission intensity as measured by readmission cost for high-risk surgeries and examine predictors of highe...

Background: Markov decision process (MDP) models are powerful tools. They enable the derivation of optimal treatment policies but may incur long computational times and generate decision rules that are challenging to interpret by physicians. Methods: In an effort to improve usability and interpretability, we examined whether Poisson regression can...

Background: Radical cystectomy has one of the highest 30-d hospital readmission rates but circumstances leading to readmission remain poorly understood. Objective: To examine the postdischarge period and better understand hospital readmission after radical cystectomy. Design, setting, and participants: We conducted a retrospective cohort study...

Analysts predict impending shortages in the health care workforce, yet wages for health care workers already account for over half of U.S. health expenditures. It is thus increasingly important to adequately plan to meet health workforce demand at reasonable cost. Using infinite linear programming methodology, we propose an infinite-horizon model f...

Purpose: Radical cystectomy has one of the highest readmission rates across all surgical procedures at approximately 25%. We developed a mathematical model to optimize outpatient followup regimens for radical cystectomy. Materials and Methods: We used delay-time analysis, a systems engineering approach, to maximize the probability of detecting pati...

Background: Neonatal nurse practitioners (NNPs) play a vital role in the medical care of newborns and infants. There is expected to be a shortage of NNPs in the near future. Purpose: To assess the present NNP workforce and study the impact of potential policy changes to alleviate forecasted shortages. Methods: We modeled the education and work...

Background: Renal transplantation is a lifesaving intervention for end-stage renal disease. The demand for renal transplantation outweighs the availability of organs; however, up to 20% of recovered kidneys are discarded before transplantation. We aimed to better characterize the risk factors for deceased donor kidney discard. Methods: We perfor...

To effectively manage chronic disease patients, clinicians must know (1) how to monitor each patient (i.e., when to schedule the next visit and which tests to take), and (2) how to control the disease (i.e., what levels of controllable risk factors will sufficiently slow progression). Our research addresses these questions simultaneously and provid...

In managing chronic diseases such as glaucoma, the timing of periodic examinations is crucial, as it may significantly impact patients outcomes. We address the question of when to monitor a glaucoma patient by integrating a dynamic, stochastic state space system model of disease evolution with novel optimization approaches to predict the likelihood...

With the ageing US population, demographic shifts, and obesity epidemic, there is potential for further exacerbation of the current liver donor shortage. We aimed to project the availability of liver grafts in the US. We performed a secondary analysis of the Organ Procurement and Transplantation Network database of all adult donors from 2000-2012 a...

Purpose: Radical cystectomy has one of the highest readmission rates across all surgical procedures at approximately 25%. Our objective is to develop a mathematical model to optimize outpatient follow-up regimens for radical cystectomy. Materials and methods: We used delay-time analysis, a systems engineering approach, to maximize the probabilit...

To assess the current pediatric nurse practitioner (PNP) workforce and to investigate the impact of potential policy changes to address forecasted shortages. We modeled the admission of students into nursing bachelor's programs and followed them through advanced clinical programs. Prediction models were combined with optimal decision-making to dete...

Purpose: Hospital readmissions after radical cystectomy vary with respect to intensity in terms of impact on patients and health care systems. Therefore, we conducted a population based study to examine factors associated with increasing readmission intensity after radical cystectomy for bladder cancer. Materials and methods: Using SEER (Surveil...

We investigate the problem faced by a healthcare system wishing to allocate its constrained screening resources across a population at risk for developing a disease. A patient's risk of developing the disease depends on his/her biomedical dynamics. However, knowledge of these dynamics must be learned by the system over time. Three classes of reinfo...

Purpose To determine whether dynamic and personalized schedules of visual field (VF) testing and intraocular pressure (IOP) measurements result in an improvement in disease progression detection compared with fixed interval schedules for performing these tests when evaluating patients with open-angle glaucoma (OAG). Design Secondary analyses using...

Readmissions after radical cystectomy are common, burdensome, and poorly understood. For these reasons, the authors conducted a population-based study that focused on the causes of and time to readmission after radical cystectomy. Using Surveillance, Epidemiology, and End Results-Medicare data, at total of 1782 patients who underwent radical cystec...

Open-angle glaucoma (OAG) is a prevalent, degenerate ocular disease which can lead to blindnesswithout proper clinical management. The tests used to assess disease progression are susceptible toprocess and measurement noise. The aim of this study was to develop a methodology which accountsfor the inherent noise in the data and improve significant d...

Purpose: We investigated how using filtered longitudinal data as input for logistic regression to predict glaucoma progression affects the classification ability of the logistic regression function. Methods: A Kalman filter was developed to reduce the process and measurement noise present in longitudinal data from the Collaborative Initial Glauco...

Purpose: We developed and compared the performance of two novel dynamic control algorithms for determining personalized time between testing for patients diagnosed with open angle glaucoma (OAG) against fixed interval monitoring schedules. Methods: We developed a Kalman filter which combines population disease dynamics with the individual patient...

Interactive voice response (IVR) calls enhance health systems' ability to identify health risk factors, thereby enabling targeted clinical follow-up. However, redundant assessments may increase patient dropout and represent a lost opportunity to collect more clinically useful data. We determined the extent to which previous IVR assessments predicte...

BACKGROUND & AIMS: Current screening algorithms for hepatocellular carcinoma (HCC) view each testing interval independently, without considering prior test results. We investigated whether measurements of α-fetoprotein (AFP), over time, can be used to identify patients most likely to develop HCC. METHODS: We performed a nested case-control study us...

Purpose: To confirm findings from an earlier report showing that neoadjuvant (NA) prostate-specific antigen (PSA) halving time (PSAHT) impacts biochemical failure (BF) rates, and to examine its association with prostate cancer-specific survival (PCSS), in a large prospective cohort of patients. Methods and materials: A total of 502 patients were...

This study investigated whether emergency department (ED) variables could be used in mathematical models to predict a future surge in ED volume based on recent levels of use of physician capacity. The models may be used to guide decisions related to on-call staffing in non-crisis-related surges of patient volume. A retrospective analysis was conduc...

We present a novel approach to model individual disease progression of prostate cancer patients who receive hormone therapy before radiation therapy. Our model is used to decide when to initiate radiation therapy based on the patient's prostate specific antigen (PSA) dynamics. Each patient's PSA dynamics is modeled by a log quadratic curve. Prior d...

This paper describes a linear programming hierarchical planning model that determines the optimal number of nurses to train, promote to management and recruit over a 20 year planning horizon to achieve specified workforce levels. Age dynamics and attrition rates of the nursing workforce are key model components. The model was developed to help poli...

The authors explore the power and flexibility of using an operations research methodology known as linear programming to support health human resources (HHR) planning. The model takes as input estimates of the future need for healthcare providers and, in contrast to simulation, compares all feasible strategies to identify a long-term plan for achie...

In 2001, the Federal Emergency Management Agency (FEMA) required every Florida county to identify potential locations of disaster recovery centers (DRCs). The DRCs are to be opened and staffed by FEMA personnel, subsequent to any declared disaster. The Emergency Management Division of the Alachua County Department of Fire/Rescue Services sponsored...