Developing a telemedicine triage system to manage patient flow at a high volume cancer center urgent care.

2085 Background: The Memorial Sloan Kettering (MSK) Urgent Care Center (UCC) functions as the emergency room for MSK. With 23,000+ visits annually, increasing volume and acuity means more days over capacity. Patients experience increased wait times to see clinicians, complete evaluation, and transfer to an inpatient bed. The UCC TeleTriage Program is a remote triage program which aims to align patient volume and need with available resources, improve patient experience, and streamline flow through the UCC. By managing resources more efficiently and expediting initial evaluation, the program promotes timely patient access to care, while maintaining MSK's standard of care. Methods: UCC TeleTriage began July 2018 with the Gastrointestinal Medical Oncology service. The Service Nurse refers patients to TeleTriage on weekdays, from 9a.m.- 4:30p.m. The TeleTriage clinician contacts each patient within 30 minutes of referral, takes the history, and determines the initial plan. Patients are directed to a local ER, clinic, or UCC based on level of acuity, real-time GPS, and specific need. For stable patients coming to UCC, TeleTriage focuses on initiating testing prior to registration in UCC. Results: TeleTriage patients have (virtual) contact with a UCC clinician within 30 minutes of referral, whereas non-TeleTriage patients wait 110 minutes or more. TeleTriage patients are discharged from UCC up to 42 minutes more rapidly. TeleTriage patients who receive imaging prior to registration in UCC receive a final disposition up to 93 minutes sooner. About 4% of TeleTriage patients are managed at home. In a small number of TeleTriage patients with severe complications of cancer-treatment, significant morbidity was avoided due to early intervention and coordination of care. Conclusions: TeleTriage patients have contact with a UCC clinician measurably faster than non-TeleTriage patients. Their evaluation is also started earlier. By managing less acute patients at remote sites or at home, TeleTriage can help patients avoid unnecessary travel, (time) expenditure, and hospital contact. TeleTriage patients who come to UCC, spend less time in UCC than non-TeleTriage patients and they discharge faster. By utilizing cancer care expertise, TeleTriage can significantly impact patient outcomes and utilize resources more effectively.

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Modeling and improving chemotherapy patient flow.

Journal of Clinical Oncology ◽

10.1200/jco.2014.32.30_suppl.175 ◽

2014 ◽

Vol 32 (30_suppl) ◽

pp. 175-175 ◽

Cited By ~ 1

Author(s):

Inga Tolin Lennes ◽

Ana Cecelia Zenteno Langle ◽

Michael Duk ◽

Avital Levy Carlis ◽

Mara Bloom ◽

...

Keyword(s):

Operations Management ◽

Patient Flow ◽

Tracking System ◽

Physical Space ◽

High Volume ◽

Change Implementation ◽

Phase Iii ◽

Cancer Center ◽

Patient Tracking ◽

The Impact

175 Background: Chemotherapy administration scheduling is dependent on infusion room hours of operation, availability of oncologist, capacity for treatment, pharmacy hood time, nursing and pharmacy staffing, and physical space limitations. In 2013, the main infusion center at MGH Cancer Center had 45% room/chair utilization reported by the Ambulatory Patient Tracking System and 33% exam room utilization in the clinics. However our infusion center experienced extremely high volume during peak hours, 10am to 2pm, but was underutilized before 10am and after 2pm, making it difficult to add on additional patients. Methods: In November 2013, MGH Cancer Center began collaboration with MIT Operations Management experts to ultimately improve patient flow through the Cancer Center by flattening the bottleneck at peak hours of operation and improving utilization of the infusion area and clinics. In phase I of the project, data was reviewed and refined. Key role groups of schedulers, prescribers, pharmacists and infusion nurses were shadowed by collaborators to gain insight into complex scheduling practices. A multidisciplinary working group met weekly to discuss the progress and suggest areas for further investigation. In phase II, optimization models testing the impact of alternative scheduling practices, physical space changes and alternative clinic configurations will be created. Finally, in phase III, change implementation and measurement will take place. Results: Process flow maps of patient movement through the cancer center were created. Patient tracking data was manipulated to understand key operational metrics. Several insights include an overall same-day chemotherapy cancellation rate of 10.7%, with the majority of cancellations from thoracic, GI and GU disease centers. Our mean scheduled infusion treatment length was 2.13 hours and 25% of appointments booked into infusion are not linked with a same-day clinic appointment. Conclusions: Understanding and refining incomplete or problematic data was a key part of understanding the issues contributing to the middle of the day bottleneck in the infusion area. Future work on this project will include optimization modeling and change implementation.

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Teletriage at a High-Volume Specialty Cancer Center Urgent Care: Aligning Patient Volume and Need With Available Resource

Journal of Emergency Medicine ◽

10.1016/j.jemermed.2019.04.004 ◽

2019 ◽

Vol 57 (3) ◽

pp. 422-423

Author(s):

Robin E. Stutman ◽

Diane Reidy ◽

Jason Napoli ◽

Erika Duggan ◽

Danny Joseph ◽

...

Keyword(s):

High Volume ◽

Urgent Care ◽

Cancer Center ◽

Patient Volume

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Educational system for acquiring appropriate laparoscopic colorectal surgical skills: analysis in a Japanese high-volume cancer center

Surgical Endoscopy ◽

10.1007/s00464-020-07686-2 ◽

2020 ◽

Author(s):

Ryota Nakanishi ◽

Yosuke Fukunaga ◽

Toshiki Mukai ◽

Toshiya Nagasaki ◽

Tomohiro Yamaguchi ◽

...

Keyword(s):

Educational System ◽

High Volume ◽

Surgical Skills ◽

Cancer Center

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High volume pancreaticoduodenectomy performed at a community cancer center

HPB ◽

10.1016/j.hpb.2018.02.232 ◽

2018 ◽

Vol 20 ◽

pp. S38-S39

Author(s):

A. Sabesan ◽

B. Gough ◽

C. Anderson ◽

R. Abdel-Misih ◽

N.J. Petrelli ◽

...

Keyword(s):

High Volume ◽

Cancer Center

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The high volume of patients admitted during the SARS-CoV-2 pandemic has an independent harmful impact on in-hospital mortality from COVID-19

PLoS ONE ◽

10.1371/journal.pone.0246170 ◽

2021 ◽

Vol 16 (1) ◽

pp. e0246170

Author(s):

Alessandro Soria ◽

Stefania Galimberti ◽

Giuseppe Lapadula ◽

Francesca Visco ◽

Agata Ardini ◽

...

Keyword(s):

Hospital Mortality ◽

High Volume ◽

Hospitalized Patients ◽

Urgent Care ◽

Calendar Period ◽

Cox Models ◽

Hospital System ◽

Risk Of Death ◽

The Impact ◽

Age And Sex

Background During the Coronavirus disease 2019 (COVID-19) pandemic, advanced health systems have come under pressure by the unprecedented high volume of patients needing urgent care. The impact on mortality of this “patients’ burden” has not been determined. Methods and findings Through retrieval of administrative data from a large referral hospital of Northern Italy, we determined Aalen-Johansen cumulative incidence curves to describe the in-hospital mortality, stratified by fixed covariates. Age- and sex-adjusted Cox models were used to quantify the effect on mortality of variables deemed to reflect the stress on the hospital system, namely the time-dependent number of daily admissions and of total hospitalized patients, and the calendar period. Of the 1225 subjects hospitalized for COVID-19 between February 20 and May 13, 283 died (30-day mortality rate 24%) after a median follow-up of 14 days (interquartile range 5–19). Hospitalizations increased progressively until a peak of 465 subjects on March 26, then declined. The risk of death, adjusted for age and sex, increased for a higher number of daily admissions (adjusted hazard ratio [AHR] per an incremental daily admission of 10 patients: 1.13, 95% Confidence Intervals [CI] 1.05–1.22, p = 0.0014), and for a higher total number of hospitalized patients (AHR per an increase of 50 patients in the total number of hospitalized subjects: 1.11, 95%CI 1.04–1.17, p = 0.0004), while was lower for the calendar period after the peak (AHR 0.56, 95%CI 0.43–0.72, p<0.0001). A validation was conducted on a dataset from another hospital where 500 subjects were hospitalized for COVID-19 in the same period. Figures were consistent in terms of impact of daily admissions, daily census, and calendar period on in-hospital mortality. Conclusions The pressure of a high volume of severely ill patients suffering from COVID-19 has a measurable independent impact on in-hospital mortality.

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Factors Affecting Variation in Receipt of Surgical Intervention for Hepatic Malignancies at a High Volume Liver Cancer Center

Journal of Surgical Research ◽

10.1016/j.jss.2012.10.709 ◽

2013 ◽

Vol 179 (2) ◽

pp. 336

Author(s):

A.P. Chidi ◽

D.A. Geller ◽

C. Bryce ◽

A. Tsung

Keyword(s):

Liver Cancer ◽

Surgical Intervention ◽

High Volume ◽

Cancer Center ◽

Factors Affecting ◽

Hepatic Malignancies

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Rationale and design of a cohort study evaluating triage of acute chest pain in out-of-hours primary care in the Netherlands (TRACE)

Primary Health Care Research & Development ◽

10.1017/s1463423620000122 ◽

2020 ◽

Vol 21 ◽

Author(s):

Amy Manten ◽

Cuny J.J. Cuijpers ◽

Remco Rietveld ◽

Emma Groot ◽

Freek van de Graaf ◽

...

Keyword(s):

Primary Care ◽

Cohort Study ◽

Chest Pain ◽

The Netherlands ◽

Clinical Outcomes ◽

Acute Chest Pain ◽

Urgent Care ◽

Triage System ◽

Out Of Hours ◽

Coronary Syndrome

Abstract The aims of this study are (1) to evaluate the performance of current triage for chest pain; (2) to describe the case mix of patients undergoing triage for chest pain; and (3) to identify opportunities to improve performance of current Dutch triage system for chest pain. Chest pain is a common symptom, and identifying patients with chest pain that require urgent care can be quite challenging. Making the correct assessment is even harder during telephone triage. Temporal trends show that the referral threshold has lowered over time, resulting in overcrowding of first responders and emergency services. While various stakeholders advocate for a more efficient triage system, careful evaluation of the performance of the current triage in primary care is lacking. TRiage of Acute Chest pain Evaluation in primary care (TRACE) is a large cohort study designed to describe the current Dutch triage system for chest pain and subsequently evaluate triage performance in regard to clinical outcomes. The study consists of consecutive patients who contacted the out-of-hours primary care facility with chest pain in the region of Alkmaar, the Netherlands, in 2017, with follow-up for clinical outcomes out to August 2019. The primary outcome of interest is ‘major event’, which is defined as the occurrence of death from any cause, acute coronary syndrome, urgent coronary revascularization, or other high-risk diagnoses in which delay is inadmissible and hospitalization is necessary. We will evaluate the performance of the triage system by assessing the ability of the triage system to correctly classify patients regarding urgency (accuracy), the proportion of safe actions following triage (safety) as well as rightfully deployed ambulances (efficacy). TRACE is designed to describe the current Dutch triage system for chest pain in primary care and to subsequently evaluate triage performance in regard to clinical outcomes.

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Prior Authorization for Medications in a Breast Oncology Practice: Navigation of a Complex Process

Journal of Oncology Practice ◽

10.1200/jop.2016.017756 ◽

2017 ◽

Vol 13 (4) ◽

pp. e273-e282 ◽

Cited By ~ 10

Author(s):

Ankit Agarwal ◽

Rachel A. Freedman ◽

Felicia Goicuria ◽

Catherine Rhinehart ◽

Kathleen Murphy ◽

...

Keyword(s):

Care Delivery ◽

High Volume ◽

Cancer Center ◽

Prior Authorization ◽

Patient Demographics ◽

Approval Rate ◽

Decision Points ◽

Oncology Practice ◽

The Cost ◽

The Impact

Introduction: The cost and burden associated with prior authorization (PA) for specialty medications are concerns for oncologists, but the impact of the PA process on care delivery has not been well described. We examined PA processes and approval patterns within a high-volume breast oncology clinic at a major academic cancer center. Methods: We met with institutional staff to create a PA workflow and process map. We then abstracted pharmacy and medical records for all patients with breast cancer (N = 279) treated at our institution who required a PA between May and November 2015 (324 prescriptions). We examined PA approval rates, time to approval, and associations of these outcomes with the type of medication being prescribed, patient demographics, and method of PA. Results: Seventeen possible process steps and 10 decision points were required for patients to obtain medications requiring a PA. Of the 324 PAs tracked, 316 (97.5%) were approved on the first PA request after an average time of 0.82 days (range, 0 to 14 days). Approximately half of PAs were for either palbociclib (26.5%) or pegfilgrastim (22.2%), and 13.6% of PAs were for generic hormonal therapy. Requirements to fax PA requests were associated with greater delay in approval time (1.31 v 0.17 days for online requests; P < .001). The use of specialty pharmacies increased staff burden and delays in medication receipt. Conclusion: The PA process is complicated and labor intensive. Given the high PA approval rate, it is unlikely that PA requirements reduce medication utilization in practice, and these requirements may impose unnecessary burdens on patient care. The goals and requirements for PAs should be readdressed.

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