Designing a Health Treatment Network: Optimizing Performance in the Modern Health Care Delivery System

Student research poste

Using prediction to facilitate patient flow in a health care delivery chain

Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 163-178).A health care delivery chain is a series of treatment steps through which patients flow. The Emergency Department (ED)/Inpatient Unit (IU) chain is an example chain, common to many hospitals. Recent literature has suggested that predictions of IU admission, when patients enter the ED, could be used to initiate IU bed preparations before the patient has completed emergency treatment and improve flow through the chain. This dissertation explores the merit and implications of this suggestion. Using retrospective data collected at the ED of the Veterans Health Administration Boston Health Care System (VHA BHS), three methods are selected for making admission predictions: expert opinion, naive Bayes conditional probability and linear regression with a logit link function (logit-linear regression). The logit-linear regression is found to perform best. Databases of historic data are collected from four hospitals including VHA BHS. Logit-linear regression prediction models generated for each individual hospital perform well based on multiple measures. The prediction model generated for the VHA BHS hospital continues to perform well when predictive data are collected and coded prospectively by nurses. For two weeks, predictions are made on each patient that enters the VHA BHS ED. This data is then summarized and displayed on the VHA BHS internet homepage. No change was observed in key ED flow measures; however, interviews with hospital staff exposed ways in which the prediction information was valuable: planning individual patient admissions, personal scheduling, resource scheduling, resource alignment, and hospital network coordination. A discrete event simulation of the system shows that if IU staff emphasizes discharge before noon, flow measures improve as compared to a baseline scenario where discharge priority begins at 1pm. Sharing ED crowding or prediction information leads to best patient flow performance when using specific schedules dictating IU response to the information. This dissertation targets the practical and theoretical implications of using prediction to improve flow through the ED/IU health care delivery chain. It is suggested that the results will have impact on many other levels of health care delivery that share the delivery chain structure.by Jordan Shefer Peck.Ph.D

Applying manufacturing systems methods towards understanding and redesigning a hospital emergency department

Thesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2008.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 85-88).Emergency Departments have been referred to as the "Safety Net" of our Healthcare system. This is because of their ability to catch all patients who would otherwise slip through the system, due to lack of funds, insurance, time, transportation and knowledge, etc. Because of this, as demand for health treatment increases, the occurrence of crowding in our nation's emergency departments is also increasing. At the same time hospitals are being expected to perform more, with lower funding. Observation of a hospital emergency department yields similarities between the emergency department and a manufacturing system. This is not completely a new concept, yet there have been barriers towards adopting manufacturing system practices into healthcare systems due to differences in culture, economics, politics, and the nature of the system itself. The focus of this thesis is to select manufacturing systems methods and apply them to an emergency department. This application is done with an understanding of the fundamental differences between the two systems. The first applied method is Axiomatic Design, a system design method that clearly maps out the functional requirements of a system to design solutions more efficiently. Upon applying Axiomatic Design to show that it can be used to discover and describe problems in an Emergency Department, the specific problem of patient flow is selected. Discrete Event Simulation is used in order to analyze patient flow in the Emergency Department. This results in actionable changes in the operations of an emergency department fast track. One significant actionable change is the creation of a new index for assigning patients a level based on their expected time in the Emergency Room to be used in conjunction with the current index which is based on acuity level. The purpose of this exercise is to show that manufacturing methods can be applied in an emergency department/healthcare system while taking the differences between the two systems into account.by Jordan S. PeckS.M

A Modified SIR Model Equivalent to a Generalized Logistic Model, with Standard Logistic Approximations

https://knowledgeconnection.mainehealth.org/lambrew-retreat-2021/1000/thumbnail.jp

Hypohidrotic Ectodermal Dysplasia and Immunodeficiency with Coincident NEMO and EDA Mutations

Ectodermal dysplasias (ED) are uncommon genetic disorders resulting in abnormalities in ectodermally derived structures. Many ED-associated genes have been described, of which ectodysplasin-A (EDA) is one of the more common. The NF-κB essential modulator (NEMO encoded by the IKBKG gene) is unique in that mutations result in severe humoral and cellular immunologic defects in addition to ED. We describe three unrelated kindreds with defects in both EDA and IKBKG resulting from X-chromosome crossover. This demonstrates the importance of thorough immunologic consideration of patients with ED even when an EDA etiology is confirmed, and raises the possibility of a specific phenotype arising from coincident mutations in EDA and IKBKG

Development of a Certificate in Healthcare Improvement for Inter-Professional Teams

Introduction To address gaps in care team improvement-science education and connect geographically dispersed learners, we created a healthcare improvement certificate program, now completing the third program year, for inter-professional (IP) healthcare teams, including third year medical students. Methods This hybrid learning program consists of five modules: Learning Healthcare Systems, Improvement Science, Patient Safety and Diagnostic Error, Population Health and Health Equity and Leading Change. The curricular materials are comprised of focused readings, concise videos, faculty-moderated discussion boards, weekly synchronous calls of participants with faculty, and a longitudinal improvement project. The faculty are content experts, and worked with a curricular designer to define learning objectives and develop content. Results We have completed three years of this six-month program, training 61 participants (17 of whom were medical students) at 14 sites. In the third year, several medical students participated without an IP team. Development of the materials has been iterative, with feedback from learners and faculty used to shape the materials. Discussion We demonstrate the development and rollout of a hybrid-learning program for diverse and geographically dispersed IP teams, including medical students. Time restrictions limited the depth of topics, and scheduling overlap caused some participants to miss the interactive calls. We plan to evaluate the utility of the program for participants over time, using qualitative methods. Conclusion This educational model is feasible for IP teams studying improvement science and implementing change projects, and can be adopted to dispersed geographic settings

Enhancing Quality and Impact of Early Phase Dose-Finding Clinical Trial Protocols:The SPIRIT DoseFinding Extension (SPIRIT-DEFINE) Guidance The SPIRIT-DEFINE Statement

International audienc

Enhancing Reporting Quality and Impact of Early Phase Dose-Finding Clinical Trials:The CONSORT Dose-Finding Extension (CONSORT-DEFINE) Guidance The CONSORT-DEFINE Statement

International audienceThe CONSORT (CONsolidated Standards Of Reporting Trials) 2010 statement is the standard guideline for reporting completed randomised trials. The CONSORT Dose-finding Extension (DEFINE) extends the guidance (with 21 new items and 19 modified items) to early phase dose-finding trials with interim dose escalation or de-escalation strategies. Such trials generally focus on safety, tolerability, activity, and recommending dosing and scheduling regimens for further clinical development. These trials are often inadequately reported, hampering their informativeness and making evidence informed decisions difficult. The CONSORT-DEFINE guidance aims to develop an international, consensus driven guideline for reporting early phase dose-finding trials to promote transparency, completeness, reproducibility, and facilitate the interpretation of the results. The CONSORT-DEFINE guidance provides recommendations for essential items that should be reported in early phase dose-finding trials to promote greater clarity, reproducibility, informativeness, and usefulness of results