Redesigning Chronic Care Delivery Using Mobile Health Technology

Typical management of chronic conditions is through sporadic office visits. But health indicators (such as blood pressure) can fluctuate significantly within a day. The infrequent office visits, however, offer the provider little information about the medical history of the patient between office visits resulting in delayed and sometimes inappropriate interventions. Providing the right product (making appropriate interventions) at the right place (patient's location) at the right time (before the worsening condition leads to a costlier intervention) is the objective of effective supply chain management. Use of mobile health (mHealth) technology in clinical care can help achieve all three objectives. mHealth enables continuous monitoring of measurements resulting in bidirectional information flow between providers and patients, thereby reducing information asymmetry. Our study examines redesigning of chronic care delivery using mHealth. It is important to make sure the redesigned delivery process is both efficient (reduces cost) and effective (improves patient health). In this paper we first present a big picture of the redesigned care delivery process. We then show how this delivery process can improve patient health by analyzing a panel dataset of 1627 patients. We examine the relationship between use of mobile health applications (to remotely upload measurements and receive physician intervention) and quality of care delivery (as measured by blood pressure readings) for hypertensive patients. We observe the blood pressure readings to decrease with frequency of app usage and time since adoption. With the use of mHealth apps increasing in the post COVID-19 era, our analysis indicates an efficient use of physician's time and an increased role for support-staff under the supervision of the physician. The chronic care delivery process can therefore be redesigned with the help of mHealth, improving patient health and reducing cost for both patients and providers

Equilibrium analysis in multi-echelon supply chain with multi-dimensional utilities of inertial players

In a supply chain, the importance of information elicitation from the supply chain players is vital to design supply chain network. The rationality and self-centredness of these players causes the information asymmetry in the supply chain and thus situation of conflict and non-participation of the players in the network design process. In such situations, it is required to analyse the supply chain players’ behaviour in order to explore potential for coordination through incentives. In this paper, a novel approach of social utility analysis is proposed to elicit the information for supply chain coordination among the supply chain players in a dyadic relationship – supplier and buyer. In principal, we consider a monopsony situation where buyer is a dominant player. With the objective of maximizing the social utility, efforts have been made to value behavioural issues in supply chain. On the other hand, the reluctance of player due to the information asymmetry is measured in the form of inertia – an offset to the supply chain profit. The suppliers’ behaviour is analysed with three distinct level of risk for two types of the product in procurement process. The useful insight from this paper is in supplier selection process where the reluctance of supplier offsets supply chain profit. The paper provides recommendations to supply chain managers for efficient decision-making ability in supplier selection process

An Integrated Lean Supply Chain Framework for U.S. Hospitals

We apply a lean supply chain framework to the healthcare industry in the U.S., drawing support from lean systems philosophy. We conceptualize a view of the U.S. healthcare ecosystem that places a hospital and its admitted patients at the center and describes how all entities inside and outside the hospital work can implement lean principles to improve patients\u27 quality care. This application depicts how a holistic consideration of hospital resources available in both the internal and external supply chain would increase the optimal use of such resources and ultimately serve patients. We offer propositions suggesting that an integrated supply chain perspective would be helpful for delivering high quality of care to patients admitted to the hospital. This perspective suggests that hospitals need to streamline the three types of flows– physical product, information and financial–with elements in the internal supply chain and maintain collaborative relations with entities in their external supply chain. We discuss theoretical and practical implications of our research

Improving cost efficiency in healthcare supply chain organizations to increase quality : assessment of the creation of a Group Purchasing Organization in the Portuguese Healthcare System

One of the biggest challenges that the healthcare industry faces today is the accentuated growth of operating costs. Fighting this growth cannot be done without taking into account the quality of services provided in healthcare units. Improving cost efficiency through the implementation of more efficient and effective purchasing strategies is one way to reduce costs. The first objective of this dissertation was to understand the link between supply chain cost efficiency and quality in healthcare organizations taking the Portuguese Healthcare System as an example. The second objective was to assess the potential of increasing quality through cost reduction that the creation of a Group Purchasing Organization could have in the Portuguese Healthcare System. An analysis of the evolution of costs between 2011 and 2017 was made with secondary data from financial and operational reports made available by the Portuguese Healthcare System. It was found that positive variations in cost efficiency can generate positive variations in quality and therefore new purchasing strategies should be addressed to strengthen this linkage. Regarding the implementation of a Group Purchasing Organization, an analysis of the current purchasing model and its capacity to save financial resources was undertaken. It was concluded that the creation of a Group Purchasing Organization could increase quality due to its potential to save money and therefore boost cost efficiency.Um dos maiores desafios que o setor da saúde enfrenta atualmente é o crescimento acentuado dos custos operacionais. Tentar inverter esse crescimento não pode ser feito sem ter em conta a qualidade dos serviços prestados nas unidades de saúde. Melhorar a eficiência de custos através da implementação de estratégias de compras mais eficientes e eficazes é uma das formas de reduzir custos. O primeiro objetivo desta dissertação foi compreender a relação entre eficiência de custos na cadeia de abastecimento e qualidade nas organizações de saúde, tendo como exemplo o Serviço Nacional de Saúde Português. O segundo objetivo foi avaliar o potencial de aumento da qualidade através da redução de custos que a criação de uma Organização de Compras de Grupo (ou central de compras) poderia ter no Serviço Nacional de Saúde Português. Uma análise da evolução dos custos entre 2011 e 2017 foi feita com dados secundários de relatórios financeiros e operacionais disponibilizados pelo Serviço Nacional de Saúde Português. Verificou-se que variações positivas na eficiência de custos podem gerar variações positivas na qualidade e, portanto, novas estratégias de compra devem ser abordadas para fortalecer essa ligação. Em relação à implementação de uma Organização de Compras de Grupo, foi realizada uma análise do atual modelo de compras e sua capacidade de poupar recursos financeiros. Concluiu-se que a criação de uma Organização de Compras de Grupo poderia aumentar a qualidade devido ao seu potencial para poupar dinheiro e, portanto, aumentar a eficiência de custos

Modeling of selection of supply sources for hospitals

Most of the hospitals in the USA carry out their purchasing of supplies, including pharmaceuticals, through Group Purchasing Organizations (GPO). GPO is an organization, which aggregates procuring volumes of their member hospitals and negotiates low prices from manufacturers or vendors. According to 2013 statistics, 98% of hospitals in U.S. are purchasing their bulk health care products through GPOs, and it saves U.S. health care industry approximately $36 billion annually. Through these hospitals enjoy advantages by purchasing through their GPOs, there are some disadvantages such as paying membership fees to their GPOs, restricting the purchasing power of the hospitals outside their GPOs, making it more complicated to buy better or advanced products from new vendors. As various political and economic factors are forcing hospitals merge into large hospital associations, the concept of self-contracting or managing supplies directly, comes into the picture. In this research, the concepts of healthcare supply chains with GPOs are described in detail. Purchasing systems under self- contracting are then discussed. Three possible options for the hospitals are then examined, namely, continuing current purchasing through their GPOs, direct purchasing from manufacturers (self –contracting), and finally, forming an association with other hospitals and purchasing through this association. The preferable options are discussed under the concepts of Game Theory. This research also examines the changes needed in the supply chain if any of the above new options is selected. A regular supply-chain consists of Hospital, GPO, and vendor or manufacturer. As healthcare delivery systems are merging into one group or forming hospital associations, they have an additional option of carrying out their purchasing through these associations. In this work, it is assumed that the individual hospitals take their decisions based on total costs of supplies, and they chose the supplier by comparing the various options available. In this research, these questions are answered by following a game-theoretic model, by making some assumptions. Concepts of game theory such as Nash equilibrium, Mixed Strategy Nash Equilibrium (MSNE), etc. are discussed

Analysis of a group purchasing organization under demand and price uncertainty

Based on an industrial case study, we present a stochastic model of a supply chain consisting of a set of buyers and suppliers and a group purchasing organization (GPO). The GPO combines orders from buyers in a two-period model. Demand and price in the second period are random. An advance selling opportunity is available to all suppliers and buyers in the first-period market. Buyers decide how much to buy through the GPO in the first period and how much to procure from the market at a lower or higher price in the second period. Suppliers determine the amount of capacity to sell through the GPO in the first period and to hold in reserve in order to meet demand in the second period. The GPO conducts a uniform-price reverse auction to select suppliers and decides on the price that will be offered to buyers to maximize its profit. By determining the optimal decisions of buyers, suppliers, and the GPO, we answer the following questions: Do suppliers and buyers benefit from working with a GPO? How do the uncertainty in demand, the share of GPO orders in the advance sales market, and the uncertainty in price influence the players’ decisions and profits? What are the characteristics of an environment that would encourage suppliers and buyers to work with a GPO? We show that a GPO helps buyers and suppliers to mitigate demand and price risks effectively while collecting a premium by serving as an intermediary between them

Entropy-based Demand Splits in a Hospital-Warehouse Profit Center

Financial pressures on healthcare industry in the United States and elsewhere have forced the industry to address their supply costs, their fastest growing cost sector currently comprising over 40 % of their total spend. In the USA, the healthcare supplies market is dominated by a few large distributors and significant barriers to entry. Cost reducing measures to date have relied on Group Purchasing Organizations to leverage economies of scale in negotiating price reductions. Recently, the healthcare industry has been deemphasizing this practice. In doing so, healthcare organizations have merged to form large Integrated Delivery Networks, leveraging their collective purchasing capacity to negotiate price reductions. These organizations have essentially created their own internal Group Purchasing Organizations to compete with external suppliers. Although these ventures have been publicized to be “successful”, their overall success cannot be independently validated. Furthermore, the operational details of creating these ventures, financial analyses, and operations are not publically available. Our ultimate objective is to model the creation of ventures in which healthcare organizations enter price competitions with their external vendors using the currently prevalent market parameters and practices. Specifically, the models would identify and quantitate the parameters that determine venture success, here referred to as Venture Success Metrics. Such models would comprise multiple external suppliers of different products that belong to different categories. This thesis is our first step towards that objective. It represents a simplified venture in which the hospital runs its own warehouse as a profit center that competes with one external vendor on a single supply item. The model is based on currently prevalent healthcare industry practices. In particular, it incorporates discount schedules that accurately account for the unique healthcare industry practice of offering year-2 volume-based discounts based on year-1 volumes, restricted only to the contract period. Modeling a simplified venture enabled us to identify and quantitate the parameters that determine venture success. These parameters comprise the vendor and warehouse year-1 profit objectives as well as the bias of the hospital’s purchases from its own warehouse. Pursuing the models of the thesis induced the development of healthcare-relevant sigmoidal discount schedules. These functions accurately represent the tabular step-function discount schedules while averting the infinite and discontinuous derivatives of the latter. Their “continuous derivatives” advantage renders the sigmoidal discounts readily useable in computing price equilibria, a feat that was not easily achievable with the rigid step-function discounts. The thesis also introduces novel demand split functions in which a customer’s total demand can be equitably apportioned across all suppliers subject to diverse business objectives such as price constraints or biasing purchases in favor of one or more suppliers while retaining equitability. The ultimate economic goal for achieving equitability is to conserve supply source. The demand split methodology introduced in this thesis can be characterized as “achieving equitability under business constraints”. A series of examples are provided to illustrate the methods developed in this research. Finally, the thesis concludes with a synopsis of the findings and future extensions.1 yea

Dynamic Decision Models for Managing the Major Complications of Diabetes

Diabetes is the sixth-leading cause of death and a major cause of cardiovascular and renal diseases in the U.S. In this dissertation, we consider the major complications of diabetes and develop dynamic decision models for two important timing problems: Transplantation in prearranged paired kidney exchanges (PKEs) and statin initiation. Transplantation is the most viable renal replacement therapy for end-stage renal disease (ESRD) patients, but there is a severe disparity between the demand and supply of kidneys for transplantation. PKE, a cross-exchange of kidneys between incompatible patient-donor pairs, overcomes many difficulties in matching patients with incompatible donors. In a typical PKE, transplantation surgeries take place simultaneously so that no donor may renege after her intended recipient receives the kidney. We consider two autonomous patients with probabilistically evolving health statuses in a PKE, and model their transplant timing decisions as a discrete-time non-zero-sum stochastic game. We explore necessary and sufficient conditions for patients' decisions to form a stationary-perfect equilibrium, and formulate a mixed-integer linear programming (MIP) representation of equilibrium constraints to characterize a socially optimal stationary-perfect equilibrium. We calibrate our model using large scale clinical data. We quantify the social welfare loss due to patient autonomy and demonstrate that the objective of maximizing the number of transplants may be undesirable. Patients with Type 2 diabetes have higher risk of heart attack and stroke, and if not treated these risks are confounded by lipid abnormalities. Statins can be used to treat such abnormalities, but their use may lead to adverse outcomes. We consider the question of when to initiate statin therapy for patients with Type 2 diabetes. We formulate a Markov decision process (MDP) to maximize the patient's quality-adjusted life years (QALYs) prior to the first heart attack or stroke. We derive sufficient conditions for the optimality of control-limit policies with respect to patient's lipid-ratio (LR) levels and age and parameterize our model using clinical data. We compute the optimal treatment policies and illustrate the importance of individualized treatment factors by comparing their performance to those of the guidelines in use in the U.S