Analysing and Predicting Patient Arrival Times

2013 ◽  
pp. 77-85
Author(s):  
Tiberiu Chis ◽  
Peter G. Harrison
Keyword(s):  
Arrival Times ◽  
Patient Arrival

Abstract W MP100: Applying Real-Time Location Systems to Acute Stroke Workflow: A Novel Quality Improvement Tool

Stroke ◽  
2015 ◽  
Vol 46 (suppl_1) ◽  
Author(s):  
Adam Prater ◽  
Meredith Bowen ◽  
Emily Pavich ◽  
Thomas Loehfelm ◽  
Aaron M Anderson ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Acute Stroke ◽  
Real Time ◽  
Human Observer ◽  
Ct Scanner ◽  
Urban Hospital ◽  
Ir Detectors ◽  
Arrival Times ◽  
Patient Arrival ◽  
Location Systems

Background: Real-Time Location Systems (RTLS) utilize tracking tags and detectors to locate objects or people. This technology has been implemented in healthcare, chiefly to track hospital assets, and a few healthcare systems have applied this technology to track patients in the emergency department. This pilot study tested the feasibility of RTLS to monitor the acute stroke workflow in a large, urban hospital. Methods: An asset tracking RTLS was installed in a large, urban hospital. A series of 21 acute stroke patients were tracked throughout the workflow process by a human observer and via RTLS asset tag attached to the patient’s hospital equipment. A Wi-Fi detector documented initial patient arrival times in the ER Hallway, radiofrequency/infrared (RFID/IR) detectors documented ER CT scanner and ER patient room times. Patient Arrival and departure times in the emergency room (ER) and radiology CT scanner were measured. Time differences between human observer and RTLS were calculated. Results: A total of 21 patients were tracked with RTLS. The mean time difference, interquartile range and standard deviation in minutes are as follows: initial arrival (mean 106, IQR 112, SD 197); CT arrival ( mean 1, IQR 1, SD 0.86); CT departure (mean 2, IQR 2, SD 1.13); patient return to ED (mean 1, IQR 1, SD 0.94). Discussion: Our data demonstrate that RTLS can provide accurate, real-time patient location information, and has the potential to provide data for quality improvement. Combination RFID/IR detectors provided accurate time information while the Wi-Fi detector, proved unreliable for initial arrival times. Our preliminary data supports the development of an unique RTLS system specifically designed to allow for complete visualization of the stroke workflow from patient arrival to treatment along with a dashboard user interface to facilitate treatment team coordination.

15306 Improving patient arrival times in an outpatient dermatology clinic

2020 ◽  
Vol 83 (6) ◽  
pp. AB146
Author(s):  
Ashley McWilliams ◽  
Alex Ernst ◽  
Zisansha Zahirsha ◽  
Eric S. Armbrecht ◽  
Nicole Burkemper
Keyword(s):  
Arrival Times ◽  
Dermatology Clinic ◽  
Patient Arrival

Causes of chemotherapy infusion delays: Results of a time study in an academic cancer clinic in the community.

2012 ◽  
Vol 30 (34_suppl) ◽  
pp. 251-251 ◽  
Author(s):  
Ivy Altomare ◽  
Lisa Moss ◽  
Arif Kamal ◽  
Linda Sutton
Keyword(s):  
Nurse Practitioner ◽  
Time Study ◽  
Treatment Delays ◽  
Arrival Times ◽  
Chemotherapy Drugs ◽  
Chemotherapy Administration ◽  
Complex Process ◽  
Chemotherapy Infusion ◽  
Patient Arrival ◽  
Cancer Clinic

251 Background: Chemotherapy administration is a complex process involving several steps and checkpoints. Any of these can improve or delay efficiency in patients receiving timely care. We conducted a time study auditing delays to the start of chemo infusion to determine the main causes of treatment delays and identify areas for improvement. Methods: Within the Duke Oncology Network (DON), an outreach network assisting rural cancer clinics with clinical operations, we identified one site for the study. A DON nurse practitioner and chemotherapy nurse analyzed records from 157 patients who received intravenous (IV) chemotherapy from January to March of 2011. We collected data on timepoints from administrative schedules, nurses’ infusion records and faxes to and from the lab and pharmacy, and median times and ranges were calculated. Results: Causes of chemotherapy infusion delays can be investigated through usual patient and operational documentation. Clear and accurate data could be obtained regarding patient arrival times, time seated in infusion chair, time IV access was obtained, times labs were sent/resulted, times chemotherapy drugs were requested/received and times infusions were started. The longest delays generally involved the earlier steps, including from arrival to treatment start (see Table). Surprisingly, a thorough search did not find any literature-based benchmarks for comparison. Conclusions: It is logistically feasible and clinically helpful to conduct a time study of chemotherapy infusion delays by compiling data from timepoints available in infusion records, admin notations and faxed reports. Interestingly, in our study lab and pharmacy turnaround times were not the main cause of delays as initially expected, nor were MD visits. We identified concrete areas for improvement and will use this data to design a plan for administrators, nurses and clinicians to reduce delays to infusion start by 50%. [Table: see text]

The use of a self-check-in kiosk for early patient identification and queuing in the emergency department

CJEM ◽  
2019 ◽  
Vol 21 (6) ◽  
pp. 789-792 ◽  
Author(s):  
Natalie Coyle ◽  
Andrew Kennedy ◽  
Michael J. Schull ◽  
Alex Kiss ◽  
Darren Hefferon ◽  
...  
Keyword(s):  
Emergency Department ◽  
Primary Outcome ◽  
Intervention Group ◽  
Proof Of Concept ◽  
Patient Identification ◽  
Hospital System ◽  
Arrival Times ◽  
Ambulatory Patients ◽  
Compromise Patient Safety ◽  
Patient Arrival

ABSTRACTObjectiveDelays in triage processes in the emergency department (ED) can compromise patient safety. The aim of this study was to provide proof-of-concept that a self-check-in kiosk could decrease the time needed to identify ambulatory patients arriving in the ED. We compared the use of a novel automated self-check-in kiosk to identify patients on ED arrival to routine nurse-initiated patient identification.MethodsWe performed a prospective trail with random weekly allocation to intervention or control processes during a 10-week study period. During intervention weeks, patients used a self-check-in kiosk to self-identify on arrival. This electronically alerted triage nurses to patient arrival times and primary complaint before triage. During control weeks, kiosks were unavailable and patients were identified using routine nurse-initiated triage. The primary outcome was time-to-first-identification, defined as the interval between ED arrival and identification in the hospital system.ResultsMedian (interquartile range) time-to-first-identification was 1.4 minutes (1.0–2.08) for intervention patients and 9 minutes (5–18) for control patients. Regression analysis revealed that the adjusted time-to-first-identification was 13.6 minutes (95% confidence interval 12.8–14.5) faster for the intervention group.ConclusionA self-check-in kiosk significantly reduced the time-to-first-identification for ambulatory patients arriving in the ED.

Abstract 19: Reducing Time to Intra-Arterial Therapy in Acute Ischemic Stroke

Stroke ◽  
2013 ◽  
Vol 44 (suppl_1) ◽  
Author(s):  
Brijesh P Mehta ◽  
Thabele M Leslie-Mazwi ◽  
Ronil V Chandra ◽  
Donnie L Bell ◽  
James D Rabinov ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Work Hours ◽  
Multidisciplinary Teams ◽  
Anterior Circulation ◽  
Vessel Occlusion ◽  
Arrival Times ◽  
Patient Arrival ◽  
Treatment Window ◽  
Early Alert

Background: Time to recanalization is known to predict clinical outcome in acute ischemic stroke (AIS) patients with large vessel occlusion (LVO). Unlike for IV tPA, there is no established goal time to intra-arterial therapy (IAT), resulting in potential delays and worse outcomes. We assessed the effect of a quality improvement (QI) initiative on reducing door-to-angio suite arrival times modeled after similar efforts in the AHA Target Stroke program. Methods: We examined two cohorts: pre- and post-implementation of a protocol for early alert of the neurointerventional radiology (NIR) team based on patient presentation within the treatment window (anterior circulation 8 hours, posterior circulation 24 hours) and clinical suspicion for LVO (NIHSS >10). We compared time from patient arrival to completion of imaging and arrival into the angio suite by Wilcoxon and multivariable linear regression. Results: Seventy one patients (48 pre- vs. 23 post-QI) with mean age of 68 years (36 (51%) male; median NIHSS 16, IQR 14-20) were included. Of these, 37 (52%) presented during work hours (weekdays 6am to 6pm). Post-QI, the NIR team was alerted early in 83% of cases. Overall QI impact was a reduction in absolute median door-to-suite time of 48 minutes (124 vs. 76 min, p<0.0001) (Figure). Among time sub-intervals, the time from last imaging acquisition to suite arrival has decreased significantly (median 55 vs. 30 min, p=0.004) post-QI. Use of the early alert protocol and patient arrival during work hours were the only independent predictors of shorter door-to-suite times. Conclusions: Early notification of the NIR team resulted in a major reduction in time from door-to-angio suite arrival of ~50 minutes. This time savings was achieved through parallel work flow of the multidisciplinary teams during AIS evaluation. As the certification of Comprehensive Stroke Centers commences, such QI initiatives aimed at improving rapid delivery of time-sensitive therapies will be critical.

scholarly journals Reducing Wait Time Between Admission and Chemotherapy Initiation

2018 ◽  
Vol 14 (5) ◽  
pp. e316-e323 ◽  
Author(s):  
Arjun Gupta ◽  
Jenny Li ◽  
Bernard Tawfik ◽  
Thao Pham ◽  
Sudarshan Pathak ◽  
...  
Keyword(s):  
Length Of Stay ◽  
Multidisciplinary Team ◽  
Wait Time ◽  
Work Requirements ◽  
Secure Messaging ◽  
Arrival Times ◽  
Prolonged Length ◽  
Patient Dissatisfaction ◽  
Patient Arrival ◽  
Chemotherapy Initiation

Purpose: Reducing the length of stay is a high-priority objective for all health care institutions. Delays in chemotherapy initiation for planned preadmissions lead to patient dissatisfaction and prolonged length of stay. Patients and Methods: A multidisciplinary team was formed as part of the ASCO Quality Training Program. We aimed to reduce the time to initiation of chemotherapy from patient arrival at Parkland Hospital from a median of 6.2 hours at baseline to 4 hours over a 6-month period (35% reduction). The team identified inconsistency in blood work requirements, poor communication, and nonstandard patient arrival times as key causes of delay in the process. Plan-Do-Study-Act (PDSA) cycles were implemented based on identified improvement opportunities. The outcome measure was time from arrival to chemotherapy start. Data were obtained from time stamps in the electronic health record. Results: The first PDSA cycle included patient reminders to arrive at specific times, improved communication using a smartphone secure messaging application, and preadmission notes by oncology fellows detailing whether fresh blood work were needed on admission. Baseline data from 36 patients and postimplementation data from 28 patients were analyzed. Median time from admission to chemotherapy initiation preprocess change was 6.2 hours; it was 3.2 hours postchange. A sustained shift in the process was apparent on a control chart. Conclusion: Delays in initiation of chemotherapy can be prevented using classic quality improvement methodology and a multidisciplinary team. We aim to further refine our PDSA cycles and ensure sustainability of change.

Phänologische Trends bei den Waldbäumen in der Schweiz | Phenological trends regarding the forest trees in Switzerland

2005 ◽  
Vol 156 (6) ◽  
pp. 207-210 ◽  
Author(s):  
Claudio Defila
Keyword(s):  
Regional Differences ◽  
Early Growth ◽  
Horse Chestnut ◽  
Forest Trees ◽  
Spring Season ◽  
Arrival Times ◽  
The Past ◽  
Early Arrival ◽  
Southern Side ◽  
The Alps

Numerous publications are devoted to plant phenological trends of all trees, shrubs and herbs. In this work we focus on trees of the forest. We take into account the spring season (leaf and needle development) as well as the autumn (colour turning and shedding of leaves) for larch, spruce and beech, and,owing to the lack of further autumn phases, the horse chestnut. The proportion of significant trends is variable, depending on the phenological phase. The strongest trend to early arrival in spring was measured for needles of the larch for the period between 1951 and 2000 with over 20 days. The leaves of the horse chestnut show the earliest trend to turn colour in autumn. Beech leaves have also changed colour somewhat earlier over the past 50 years. The trend for shedding leaves, on the other hand, is slightly later. Regional differences were examined for the growth of needles in the larch where the weakest trends towards early growth are found in Canton Jura and the strongest on the southern side of the Alps. The warming of the climate strongly influences phenological arrival times. Trees in the forest react to this to in a similar way to other plants that have been observed (other trees, shrubs and herbs).

Behavior and Sensitivity of Phase Arrival Times (PHASE)

2014 ◽  
Author(s):  
Emmanuel Skarsoulis ◽  
Bruce Cornuelle ◽  
Matthew Dzieciuch
Keyword(s):  
Arrival Times

Comparison of Overnight Truck Parking Counts with GPS-Derived Counts for Truck Parking Facility Utilization Analysis

2019 ◽  
Vol 2673 (8) ◽  
pp. 377-387 ◽  
Author(s):  
Karla Diaz Corro ◽  
Taslima Akter ◽  
Sarah Hernandez
Keyword(s):  
Global Positioning System ◽  
Survey Methodology ◽  
Population Level ◽  
Department Of Transportation ◽  
Expansion Factor ◽  
Arrival Times ◽  
Global Positioning ◽  
Facility Type ◽  
Transportation Agencies ◽  
Parking Facilities

Increased demand for truck parking resulting from hours-of-service regulations and growing truck volumes, coupled with limited supply of parking facilities, is concerning for transportation agencies and industry stakeholders. To monitor truck parking congestion, the Arkansas Department of Transportation (ARDOT) conducts an annual observational survey of truck parking facilities. As a result of survey methodology, it cannot capture patterns of diurnal and seasonal use, arrival times, and duration. Truck Global Positioning System (GPS) data provide an apt alternative for monitoring parking facility utilization. The issue is that most truck GPS datasets represent a sample of the truck population and the representativeness of that sample may differ by application. Currently no method exists to accurately expand a GPS sample to reflect population-level truck parking facility utilization. This paper leverages the ARDOT study to estimate GPS “expansion factors” by parking facility type and defines two expansion factors: (1) the ratio of trucks parked derived from the GPS sample to those observed during the Overnight Study, and (2) the ratio of truck volume derived from the GPS sample to total truck volume measured on the nearest roadway. Varied expansion factors are found for public, private commercial (e.g., restaurant, retail store, etc.), and private truck stop facilities. Comparatively, the expansion factor based on roadway truck volumes was at least twice as high as that derived from the Overnight Study. Considering this, the method to determine expansion factors has significant implications on the estimated magnitudes of parking facility congestion, and thus will have consequences for investment prioritization.

scholarly journals A Fuzzy Optimization Model for the Berth Allocation Problem and Quay Crane Allocation Problem (BAP + QCAP) with n Quays

2021 ◽  
Vol 9 (2) ◽  
pp. 152
Author(s):  
Edwar Lujan ◽  
Edmundo Vergara ◽  
Jose Rodriguez-Melquiades ◽  
Miguel Jiménez-Carrión ◽  
Carlos Sabino-Escobar ◽  
...  
Keyword(s):  
Optimization Model ◽  
Fuzzy Optimization ◽  
Optimal Solution ◽  
Allocation Problem ◽  
Berth Allocation ◽  
Triangular Fuzzy Numbers ◽  
Berth Allocation Problem ◽  
Arrival Times ◽  
Decision Variables ◽  
Short Time

This work introduces a fuzzy optimization model, which solves in an integrated way the berth allocation problem (BAP) and the quay crane allocation problem (QCAP). The problem is solved for multiple quays, considering vessels’ imprecise arrival times. The model optimizes the use of the quays. The BAP + QCAP, is a NP-hard (Non-deterministic polynomial-time hardness) combinatorial optimization problem, where the decision to assign available quays for each vessel adds more complexity. The imprecise vessel arrival times and the decision variables—berth and departure times—are represented by triangular fuzzy numbers. The model obtains a robust berthing plan that supports early and late arrivals and also assigns cranes to each berth vessel. The model was implemented in the CPLEX solver (IBM ILOG CPLEX Optimization Studio); obtaining in a short time an optimal solution for very small instances. For medium instances, an undefined behavior was found, where a solution (optimal or not) may be found. For large instances, no solutions were found during the assigned processing time (60 min). Although the model was applied for n = 2 quays, it can be adapted to “n” quays. For medium and large instances, the model must be solved with metaheuristics.

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