7,924 research outputs found
Guidelines for Scheduling in Primary Care: An Empirically Driven Mathematical Programming Approach
Primary care practices play a vital role in healthcare delivery since they are the first point of contact for most patients, and provide health prevention, counseling, education, diagnosis and treatment. Practices, however, face a complex appointment scheduling problem because of the variety of patient conditions, the mix of appointment types, the uncertain service times with providers and non-provider staff (nurses/medical assistants), and no-show rates which all compound into a highly variable and unpredictable flow of patients. The end result is an imbalance between provider idle time and patient waiting time.
To understand the realities of the scheduling problem we analyze empirical data collected from a family medicine practice in Massachusetts. We study the complete chronology of patient flow on nine different workdays and identify the main patient types and sources of inefficiency. Our findings include an easy-to-identify patient classification, and the need to focus on the effective coordination between nurse and provider steps.
We incorporate these findings in an empirically driven stochastic integer programming model that optimizes appointment times and patient sequences given three well-differentiated appointment types. The model considers a session of consecutive appointments for a single-provider primary care practice where one nurse and one provider see the patients. We then extend the integer programming model to account for multiple resources, two nurses and two providers, since we have observed that such team primary care practices are common in the course of our data collection study. In these practices, nurses prepare patients for the providers’ appointments as a team, while providers are dedicated to their own patients to ensure continuity of care. Our analysis focuses on finding the value of nurse flexibility and understanding the interaction between the schedules of the two providers. The team practice leads us to a challenging and novel multi step multi-resource mixed integer stochastic scheduling formulation, as well as methods to tackle the ensuing computational challenge. We also develop an Excel scheduling tool for both single provider and team practices to explore the performance of different schedules in real time.
Overall, the main objective of the dissertation is to provide easy-to-implement scheduling guidelines for primary care practices using both an empirically driven stochastic optimization model and a simulation tool
Provider Scheduling at the Worcester VA Community Based Outpatient Clinic
The implementation of a Patient-Centered Medical Home (PCMH) concept, known as the Patient Aligned Care Team (PACT) model at the Worcester Community Based Outpatient Clinic (CBOC), revealed provider scheduling and utilization challenges. A linear programming based planning tool described in this report identifies optimal provider schedules The planning tool, named ProSkedge, is able to be modified to fit the varying operating constraints the CBOC faces. Also included is a simulation model to validate the linear program and to perform scenario analysis. Additional recommendations for improved facility operations are provided based on observation and a review of the literature
Analyzing Fast-Track Effectiveness at ReadyMED Plus Worcester
Reliant Medical Group is looking to decrease the average patient wait time at its urgent care location, ReadyMED Plus, in Worcester, Massachusetts. ReadyMED Plus management implemented a fast-track system within their urgent care system to streamline patient flow. This project identifies inefficiencies in ReadyMEDs current fast-track system and provides recommendations to reduce patient wait times. The team performed a sensitivity analysis on the current system by developing a simulation model. This model was used to generate recommendations for process flow, and a tool was created to support operational decision making within the urgent care system
Energy use in residential buildings: Impact of building automation control systems on energy performance and flexibility
This work shows the results of a research activity aimed at characterizing the energy habits of Italian residential users. In detail, by the energy simulation of a buildings sample, the opportunity to implement a demand/response program (DR) has been investigated. Italian residential utilities are poorly electrified and flexible loads are low. The presence of an automation system is an essential requirement for participating in a DR program and, in addition, it can allow important reductions in energy consumption. In this work the characteristics of three control systems have been defined,
based on the services incidence on energy consumptions along with a sensitivity analysis on some energy drivers. Using the procedure established by the European Standard EN 15232, the achievable
energy and economic savings have been evaluated. Finally, a financial analysis of the investments has been carried out, considering also the incentives provided by the Italian regulations. The payback
time is generally not very long: depending on the control system features it varies from 7 to 10 years; moreover, the automation system installation within dwellings is a relatively simple activity, which is
characterized by a limited execution times and by an initial expenditure ranging in 1000 € to 4000 €, related to the three sample systems
ACHIEVING UNIVERSAL LIAISONS AND HEALTHCARE CONTACT CENTER CENTRALIZATION THROUGH THE USE OF DECISION SUPPORT TOOLS
Healthcare contact centers often experience a large volume of calls and traditional standardized guidelines can be difficult to follow during an active call. While more common workflows can be memorized, they change often because Healthcare is a dynamic field. Constant updates to workflows, an abundance of different processes and provider preferences, and a fast paced environment can lead Customer Service Liaisons (CSLs) to handle patient inquiries incorrectly. Active decision support tools enable a CSL to follow an updated workflow without needing to navigate through complex guidelines and emails. This research shows that contact center centralization through the use of decision support tools can reduce Average Speed to Answer by 70 seconds even with an increase to Average Handle Time by 30 seconds. This research also identifies key features the tool may need to facilitate widespread adoption by clinicians and CSL alike
Developing A Personal Decision Support Tool for Hospital Capacity Assessment and Querying
This article showcases a personal decision support tool (PDST) called
HOPLITE, for performing insightful and actionable quantitative assessments of
hospital capacity, to support hospital planners and health care managers. The
tool is user-friendly and intuitive, automates tasks, provides instant
reporting, and is extensible. It has been developed as an Excel Visual Basic
for Applications (VBA) due to its perceived ease of deployment, ease of use,
Office's vast installed userbase, and extensive legacy in business. The
methodology developed in this article bridges the gap between mathematical
theory and practice, which our inference suggests, has restricted the uptake
and or development of advanced hospital planning tools and software. To the
best of our knowledge, no personal decision support tool (PDST) has yet been
created and installed within any existing hospital IT systems, to perform the
aforementioned tasks. This article demonstrates that the development of a PDST
for hospitals is viable and that optimization methods can be embedded quite
simply at no cost. The results of extensive development and testing indicate
that HOPLITE can automate many nuanced tasks. Furthermore, there are few
limitations and only minor scalability issues with the application of free to
use optimization software. The functionality that HOPLITE provides may make it
easier to calibrate hospitals strategically and/or tactically to demands. It
may give hospitals more control over their case-mix and their resources,
helping them to operate more proactively and more efficiently.Comment: 33 pages, 11 tables, 17 figure
Improving Changeover Efficiency in Opticap XL Encapsulation Process
This project studied MilliporeSigma’s changeover efficiency within the Opticap® XL encapsulation process to alleviate throughput issues associated with increasing demand. Our team conducted time and observational studies, together with stakeholder interviews, to identify and prioritize improvement areas. We developed a production schedule optimization tool, Single Minute Exchange of Dies analysis for changeover tasks, and conditions to streamline melt-check procedures. We recommend our deliverables be implemented to improve changeover efficiency, and estimate that 230 minutes can be saved in changeover time over two days
Developing a distributed electronic health-record store for India
The DIGHT project is addressing the problem of building a scalable and highly available information store for the Electronic Health Records (EHRs) of the over one billion citizens of India
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