From Travel Time and Cost Savings to Value of Mobility

2018 ◽  
pp. 35-43 ◽  
Author(s):  
Tatiana Kováčiková ◽  
Giuseppe Lugano ◽  
Ghadir Pourhashem
Keyword(s):  
Travel Time ◽  
Cost Savings

Socioeconomic patient benefits of a pediatric neurosurgery telemedicine clinic

2020 ◽  
Vol 25 (2) ◽  
pp. 204-208 ◽  
Author(s):  
Kelsey Hayward ◽  
Sabrina H. Han ◽  
Alexander Simko ◽  
Hector E. James ◽  
Philipp R. Aldana
Keyword(s):  
Travel Time ◽  
Cost Savings ◽  
Transportation Cost ◽  
Pediatric Neurosurgery ◽  
University Of Florida ◽  
Remote Location ◽  
Socioeconomic Data ◽  
The University ◽  
Time Away

OBJECTIVEThe objective of this study was to examine the socioeconomic benefits to the patients and families attending a regional pediatric neurosurgery telemedicine clinic (PNTMC).METHODSA PNTMC was organized by the Division of Pediatric Neurosurgery of the University of Florida College of Medicine–Jacksonville based at Wolfson Children’s Hospital and by the Children’s Medical Services (CMS) to service the Southeast Georgia Health District. Monthly clinics are held with the CMS nursing personnel at the remote location. A retrospective review of the clinic population was performed, socioeconomic data were extracted, and cost savings were calculated.RESULTSClinic visits from August 2011 through January 2017 were reviewed. Fifty-five patients were seen in a total of 268 initial and follow-up PNTMC appointments. The average round-trip distance for a family from home to the University of Florida Pediatric Neurosurgery (Jacksonville) clinic location versus the PNTMC remote location was 190 versus 56 miles, respectively. The families saved an average of 2.5 hours of travel time and 134 miles of travel distance per visit. The average transportation cost savings for all visits per family and for all families was $180 and $9711, respectively. The average lost work cost savings for all visits per family and for all families was $43 and $2337, respectively. The combined transportation and work cost savings for all visits totaled $223 per family and $12,048 for all families. Average savings of $0.68/mile and $48.50/visit in utilizing the PNTMC were calculated.CONCLUSIONSManaging pediatric neurosurgery patients and their families via telemedicine is feasible and saves families substantial travel time, travel cost, and time away from work.

Evaluation of Patient Experience from Telemedicine Use for an Anesthesiology Pain Division: Time, Cost, and Patient Satisfaction Analysis (Preprint)

2021 ◽  
Author(s):  
Laleh Jalilian ◽  
Irene Wu ◽  
Jakun Ing ◽  
Xuezhi Dong ◽  
George Pan ◽  
...  
Keyword(s):  
Patient Satisfaction ◽  
Pain Management ◽  
Travel Time ◽  
Medical Center ◽  
Academic Medical Center ◽  
Cost Savings ◽  
Travel Distance ◽  
Patient Cost ◽  
Academic Medical ◽  
Pain Patients

BACKGROUND An increasing number of patients require outpatient and interventional pain management. To help meet the rising demand for anesthesia pain subspecialty care in rural and metropolitan areas, healthcare providers have utilized telemedicine for pain management of both interventional and chronic pain patients. OBJECTIVE This study describes telemedicine implementation for pain management at an academic pain division in a large metropolitan area. The study estimates patient cost savings from telemedicine, before and after the California COVID-19 "Safer at Home" directive, and patient satisfaction with telemedicine for pain management care. METHODS This was a retrospective, observational case series study of telemedicine use in a pain division at an urban academic medical center. From August 2019 to June 2020, we evaluated 1,398 patients and conducted 2,948 video visits for remote pain management care. We utilize publicly available IRS Statistics of Income data to estimate hourly earnings by zip code in order to estimate patient cost savings. We estimate median travel time, travel distance, direct cost of travel, and time-based opportunity savings and report patient satisfaction scores. RESULTS Telemedicine patients avoided an estimated median roundtrip driving distance of 26 miles and a median travel time of 69 minutes during afternoon traffic conditions. Within sample, the median hourly earnings was $28/hr. Patients saved a median of $22 on gas and parking and a total of $52 per telemedicine visit based on estimated hourly earnings and travel time. Patients evaluated serially with telemedicine for medication management saved a median of $156 over three visits. 91% of patients surveyed (n = 313) were satisfied with their telemedicine experience. CONCLUSIONS Telemedicine use for pain management reduced travel distance, travel time, and travel and time-based opportunity costs for pain patients. We achieved the successful implementation of telemedicine across a pain division in an urban academic medical center with high patient satisfaction and patient cost savings.

Online Charging and Routing of Electric Vehicles in Stochastic Time-Varying Networks

2017 ◽  
Vol 2667 (1) ◽  
pp. 61-70 ◽  
Author(s):  
Ehsan Jafari ◽  
Stephen D. Boyles
Keyword(s):  
Travel Time ◽  
A Priori ◽  
Cost Savings ◽  
Time Varying ◽  
Charging Station ◽  
Current State ◽  
Time Varying Networks ◽  
Charging Stations ◽  
Generalized Cost ◽  
Stochastic Time

This paper formulates the problem of online charging and routing of a single electric vehicle in a network with stochastic and time-varying travel times. Public charging stations, with nonidentical electricity prices and charging rates, exist through the network. Upon arrival at each node, the traveler learns the travel time on all downstream arcs and the waiting time at the charging station, if one is available. The traveler aims to minimize the expected generalized cost—formulated as a weighted sum of travel time and charging cost—by considering the current state of the vehicle and availability of information in the future. The paper also discusses an offline algorithm by which all routing and charging decisions are made a priori. The numerical results demonstrate that cost savings of the online policy, compared with that for the offline algorithm, is more significant in larger networks and that the number of charging stations and vehicle efficiency rate have a significant impact on those savings.

Optimizing efficiency of height modeling for extensive forest inventories

2006 ◽  
Vol 36 (9) ◽  
pp. 2259-2269 ◽  
Author(s):  
T M Barrett
Keyword(s):  
Travel Time ◽  
Programming Model ◽  
Sampling Error ◽  
Estimation Error ◽  
Cost Savings ◽  
Data Set ◽  
Potential Measurement ◽  
Forest Inventories ◽  
Alternative Measurement ◽  
Measurement Strategies

Although critical to monitoring forest ecosystems, inventories are expensive. This paper presents a generalizable method for using an integer programming model to examine tradeoffs between cost and estimation error for alternative measurement strategies in forest inventories. The method is applied to an example problem of choosing alternative height-modeling strategies for 1389 plots inventoried by field crews traveling within an 82.5 × 106 ha region of the west coast of North America during one field season. In the first part of the application, nonlinear regional height models were constructed for 38 common species using a development data set of 137 374 measured tree heights, with root mean square error varying from 6.7 to 2.1 m. In the second part of the application, alternative measurement strategies were examined using a minimal cost objective subject to constraints on travel time and estimation error. Reduced travel time for field crews can be a significant portion of the cost savings from modeling tree heights. The optimization model was used to identify a height-modeling strategy that, given assumptions made, resulted in <10% of maximum average plot volume error, >33% of potential measurement cost savings, and small bias for estimates of regional volume and associated sampling error (0.1% and 0.4%, respectively).

The effects of travel time and cost savings on commuters’ decision to travel on public transport routes involving transfers

2015 ◽  
Vol 43 ◽  
pp. 151-159 ◽  
Author(s):  
Subeh Chowdhury ◽  
Avishai (Avi) Ceder ◽  
Bradley Schwalger
Keyword(s):  
Travel Time ◽  
Public Transport ◽  
Cost Savings

scholarly journals INNV-22. PROSPECTIVE ANALYSIS OF UTILIZATION OF TELEMEDICINE IN NEURO-ONCOLOGY

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii121-ii121
Author(s):  
Aman Kalra
Keyword(s):  
Clinical Trials ◽  
Quality Of Care ◽  
Travel Time ◽  
Cost Savings ◽  
Study Cohort ◽  
Daily Routine ◽  
Burden Of Care ◽  
Travel Time Savings ◽  
Time Savings

Abstract OBJECTIVE to offer neuro-oncology care to patients in rural/suburban settings that may not otherwise have access to urban amenities, specialists, and clinical trials. To test the feasibility of telemedicine in Neuro-Oncology by measuring cost savings, travel time savings, and burden of care. To screen patients for clinical trials. BACKGROUND Neuro-Oncology services are primarily available only at tertiary care hospitals. This increases the burden of care for patients who live in suburban and rural areas, as they have to travel long distances for their care. Hence, some families and patients do not seek care as travel time increases the stress on patients and their caretakers who are already dealing with the devastating diagnosis of a brain tumor. Similarly, these patient groups do not have access to clinical trials. METHODS To help ease above hardships on patients, we built a telemedicine Neuro-Oncology program that is studying the quality of care compared with daily routine visits in the cancer center. We are enrolling 30 patients in each cohort of the study, cohort A, telemedicine visits and cohort B, regular clinic visits for a total of 60 patients after obtaining written consent. We are providing them survey identifying quality measures of care (24 questions). The survey is provided to the patients and their caregivers at the end of their visit. RESULTS Survey answers are inputted into Survey Monkey. After the completion of 60 total patient visits, surveys will be evaluated and the results will be analyzed. CONCLUSION We are looking for the long-term feasibility of utilizing telemedicine care in rural/suburban settings for Neuro-Oncology patients. We anticipate that there will be cost savings, travel time savings and reduction in burden of care without compromising patient satisfaction or quality of care provided. We are also studying the feasibility of screening patients for clinical trials.

Travel, Time, and Cost Savings Associated with a University Medical Center's Video Medical Interpreting Program

2020 ◽  
Vol 26 (10) ◽  
pp. 1234-1239
Author(s):  
Ilana Sigal ◽  
Parul Dayal ◽  
Jeffrey S. Hoch ◽  
Jamie L. Mouzoon ◽  
Elena Morrow ◽  
...  
Keyword(s):  
Travel Time ◽  
Cost Savings ◽  
Medical Interpreting

The impact of telemedicine in cancer care

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. e20508-e20508 ◽  
Author(s):  
F. Yunus ◽  
S. Gray ◽  
K. C. Fox ◽  
J. W. Allen ◽  
J. Sachdev ◽  
...  
Keyword(s):  
Travel Time ◽  
Cancer Care ◽  
High Speed ◽  
Unmet Need ◽  
Cost Savings ◽  
Cost Benefit ◽  
Initial Care ◽  
Oncology Care ◽  
Rural Sites ◽  
The Impact

e20508 Background: The Technology Exchange for Cancer Health Network is a collaborative, multi-state effort using Telemedicine and integrated electronic health records to provide rural cancer care management. Methods: The purpose of the study was to compare quality, safety, and cost outcomes for patients receiving rural Telehealth care versus “routine” urban care. Patients with a cancer diagnosis requiring treatment for at least 1 year were eligible for the study. Telehealth patients saw their oncologist in person at rural sites for initial care and via telemedicine for about half of subsequent visits, allowing clinicians in-person clinical assessments while still taking advantage of time savings associated with telemedicine. Results: 217 patients (134 rural, 83 urban) were enrolled from 05/25/05 to 09/30/08. Patient satisfaction was high; 95 % of patients indicated their telemedicine visit was as good as or better than an in-person visit. Telemedicine patients also reported significant time and travel cost savings. Cost analysis comparing cost savings (physician travel time) with telemedicine costs (equipment, high speed lines) indicated that cost-benefit is driven by distance to rural facility and number of physician trips avoided. Telemedicine must save at least 5 hours of physician travel time per month to break even. Telemedicine was also associated with improvements in access to care. Using patient self-reported health care visit data (verified with local providers), we identified a significant decline in disparities between urban and rural patients (see Table ). Conclusions: Telemedicine offers a promising method for increasing access to oncology care that is convenient for and well-accepted by patients at reasonable costs. Our results also suggest that telemedicine facilitates access to more than just oncology care. The regular follow-up care provided through telemedicine visits may identify unmet need that might otherwise go untreated, yielding improvements in patient outcomes. [Table: see text] No significant financial relationships to disclose.

scholarly journals Optimized Skip-Stop Metro Line Operation Using Smart Card Data

2017 ◽  
Vol 2017 ◽  
pp. 1-17 ◽  
Author(s):  
Peitong Zhang ◽  
Zhanbo Sun ◽  
Xiaobo Liu
Keyword(s):  
Travel Time ◽  
Smart Card ◽  
Low Cost ◽  
Optimal Solution ◽  
Cost Savings ◽  
Passenger Demand ◽  
Passenger Travel ◽  
Smart Card Data ◽  
Transit Agencies ◽  
The Right

Skip-stop operation is a low cost approach to improving the efficiency of metro operation and passenger travel experience. This paper proposes a novel method to optimize the skip-stop scheme for bidirectional metro lines so that the average passenger travel time can be minimized. Different from the conventional “A/B” scheme, the proposed Flexible Skip-Stop Scheme (FSSS) can better accommodate spatially and temporally varied passenger demand. A genetic algorithm (GA) based approach is then developed to efficiently search for the optimal solution. A case study is conducted based on a real world bidirectional metro line in Shenzhen, China, using the time-dependent passenger demand extracted from smart card data. It is found that the optimized skip-stop operation is able to reduce the average passenger travel time and transit agencies may benefit from this scheme due to energy and operational cost savings. Analyses are made to evaluate the effects of that fact that certain number of passengers fail to board the right train (due to skip operation). Results show that FSSS always outperforms the all-stop scheme even when most passengers of the skipped OD pairs are confused and cannot get on the right train.

Understanding Ridesplitting Behavior with Interpretable Machine Learning Models Using Chicago Transportation Network Company Data

2021 ◽  
pp. 036119812110363
Author(s):  
Hoseb Abkarian ◽  
Ying Chen ◽  
Hani S. Mahmassani
Keyword(s):  
Machine Learning ◽  
Travel Time ◽  
Market Share ◽  
Transportation Network ◽  
Cost Savings ◽  
Community Level ◽  
Machine Learning Techniques ◽  
Future Research ◽  
Marginal Effect ◽  
Travel Time Reliability

As congestion levels increase in cities, it is important to analyze people’s choices of different services provided by transportation network companies (TNCs). Using machine learning techniques in conjunction with large TNC data, this paper focuses on uncovering complex relationships underlying ridesplitting market share. A real-world dataset provided by TNCs in Chicago is used in analyzing ridesourcing trips from November 2018 to December 2019 to understand trends in the city. Aggregated origin–destination trip-level characteristics, such as mean cost, mean time, and travel time reliability, are extracted and combined with origin–destination community-level characteristics. Three tree-based algorithms are then utilized to model the market share of ridesplitting trips. The most significant factors are extracted as well as their marginal effect on ridesplitting behavior, using partial dependency plots for interpretation of the machine learning model results. The results suggest that, overall, community-level factors are as or more important than trip-level characteristics. Additionally, the percentage of White people highly affects ridesplitting market share as well as the percentage of bachelor’s degree holders and households with two people residing in them. Travel time reliability and cost variability are also deemed more important than travel time and cost savings. Finally, the potential impact of taxes, crimes, cultural differences, and comfort is discussed in driving the market share, and suggestions are presented for future research and data collection attempts.

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