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  • 1
    Online Resource
    Online Resource
    American Society of Clinical Oncology (ASCO) ; 2017
    In:  Journal of Clinical Oncology Vol. 35, No. 15_suppl ( 2017-05-20), p. e18230-e18230
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 35, No. 15_suppl ( 2017-05-20), p. e18230-e18230
    Abstract: e18230 Background: Chemotherapy wait times can dramatically affect patient experience. MSK’s largest outpatient facility has 76 infusion spaces and 250-300 daily visits. A retrospective review of the facility’s infusion area wait times suggested that the lab (where all patients go to get their vitals and blood drawn) was a major bottleneck leading to process delays in infusion. Methods: We conducted a pilot program using a multi-pronged approach. Our goal was to decrease wait time from 40 minutes to an average of 15 minutes. Our initiative was defined as follows: (1) to redefine lab parameters that are relevant for toxicity and to only consider drawing those necessary labs; additionally, we created guidelines for timing of the labs prior to infusion treatment, (2) to introduce a program known as “ChemoExpress” which offers patients the opportunity to get blood work done prior to the day of their infusion appointment. After the labs result, the outpatient RN calls the patient, assesses symptoms and “clears them” for treatment cueing the pharmacy to prepare and “premix” the drug on the day of treatment. Results: 150 patients have enrolled in ChemoExpress. Patient satisfaction was high based on patient satisfaction surveys (n = 20). Average wait time was 9 minutes (76% less) in ChemoExpress participants as compared to an average wait of 39 minutes for those who did not participate in ChemoExpress. Conclusions: Implementing a process that enables patients to have their bloodwork drawn prior to the day of treatment and drugs prepared in advance of their treatment appointment results in greater efficiency in the overall workflow. It also offers the patient a lower wait time and a more efficient and satisfying experience.
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2017
    detail.hit.zdb_id: 2005181-5
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  • 2
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 37, No. 15_suppl ( 2019-05-20), p. 6554-6554
    Abstract: 6554 Background: Acute care accounts for half of cancer expenditures and is a measure of poor quality care. Identifying patients at high risk for emergency department (ED) visits enables institutions to target resources to those most likely to benefit. Risk stratification models developed to date have not been meaningfully employed in oncology, and there is a need for clinically relevant models to improve patient care. Methods: We established and applied a predictive framework for clinical use with attention to modeling technique, clinician feedback, and application metrics. The model employs electronic health record data from initial visit to first antineoplastic administration for patients at our institution from January 2014 to June 2017. The binary dependent variable is occurrence of an ED visit within the first 6 months of treatment. The final regularized multivariable logistic regression model was chosen based on clinical and statistical significance. In order to accommodate for the needs to the program, parameter selection and model calibration were optimized to suit the positive predictive value of the top 25% of observations as ranked by model-determined risk. Results: There are 5,752 antineoplastic administration starts in our training set, and 1,457 in our test set. The positive predictive value of this model for the top 25% riskiest new start antineoplastic patients is 0.53. From over 1,400 data features, the model was refined to include 400 clinically relevant ones spanning demographics, pathology, clinician notes, labs, medications, and psychosocial information. At the patient level, specific features determining risk are surfaced in a web application, RiskExplorer, to enable clinician review of individual patient risk. This physician facing application provides the individual risk score for the patient as well as their quartile of risk when compared to the population of new start antineoplastic patients. For the top quartile of patients, the risk for an ED visit within the first 6 months of treatment is greater than or equal to 49%. Conclusions: We have constructed a framework to build a clinically relevant risk model. We are now piloting it to identify those likely to benefit from a home-based, digital symptom management intervention.
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2019
    detail.hit.zdb_id: 2005181-5
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  • 3
    In: JAMA Network Open, American Medical Association (AMA), Vol. 5, No. 3 ( 2022-03-04), p. e221078-
    Type of Medium: Online Resource
    ISSN: 2574-3805
    Language: English
    Publisher: American Medical Association (AMA)
    Publication Date: 2022
    detail.hit.zdb_id: 2931249-8
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  • 4
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 36, No. 15_suppl ( 2018-05-20), p. e18509-e18509
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2018
    detail.hit.zdb_id: 2005181-5
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  • 5
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 38, No. 15_suppl ( 2020-05-20), p. 2027-2027
    Abstract: 2027 Background: Early detection and management of symptoms in patients with cancer improves outcomes, however, the optimal approach to symptom monitoring and management is unknown. This pilot program uses a mobile health intervention to capture and make accessible symptom data for high-risk patients to mitigate symptom escalation. Methods: Patients initiating antineoplastic treatment at a Memorial Sloan Kettering regional location were eligible. A dedicated staff of RNs and nurse practitioners managed the patients remotely. The technology supporting the program included: 1) a predictive model that identified patients at high risk for a potentially preventable acute care visit; 2) a patient portal enabling daily ecological momentary assessments (EMA); 3) alerts for concerning symptoms; 4) an application that allowed staff to review and trend symptom data; and 5) a secure messaging platform to support communications and televisits between staff and patients. Feasibility and acceptability were evaluated through enrollment (goal ≥25% of new treatment starts) and response rates (completion of 〉 50% of daily symptom assessments); symptom alerts; perceived value based on qualitative interviews with patients and providers; and acute care usage. Results: Between October 15, 2018 and July 10, 2019, the pilot enrolled 100 high-risk patients with solid tumors and lymphoma initiating antineoplastic treatment (median age: 66 years, 45% female). This represented 29% of patients starting antineoplastics. Over six months of follow-up, the response rate to the daily assessments was 56% and 93% of patients generated a severe symptom alert (Table). Both patients and providers perceived value in the program and 5,010 symptom-related secure messages were shared between staff and enrolled patients during the follow-up period. There was a preliminary signal in acute care usage with a 17% decrease in ED visits compared to a cohort of high-risk unenrolled patients. Conclusions: This pilot program of intensive monitoring of high-risk patients is feasible and holds significant potential to improve patient care and decrease hospital resources. Future work should focus on the optimal cadence of EMAs, the workforce to support remote symptom management, and how best to return symptom data to patients and clinical teams. [Table: see text]
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2020
    detail.hit.zdb_id: 2005181-5
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  • 6
    In: JCO Oncology Practice, American Society of Clinical Oncology (ASCO), Vol. 17, No. 9 ( 2021-09), p. e1278-e1285
    Abstract: Oncology patients are vulnerable to adverse outcomes associated with COVID-19, and clinical deterioration must be identified early. Several institutions launched remote patient monitoring programs (RPMPs) to care for patients with COVID-19. We describe patients' perspectives on a COVID-19 RPMP at a National Comprehensive Cancer Center. METHODS: Patients who tested positive for COVID-19 were eligible. Enrolled patients received a daily electronic COVID-19 symptom assessment, and a subset of high-risk patients also received a pulse oximeter. Monitoring was provided by a centralized team and was discontinued 14 days after a patient's positive test result and following 3 days without worsening symptoms. Patients who completed at least one assessment and exited the program were sent a patient engagement survey to evaluate the patient's experience with digital monitoring for COVID-19. RESULTS: The survey was distributed to 491 patients, and 257 responded (52% completion rate). The net promoter score was 85%. Most patients agreed that the RPMP was worthwhile, enabled better management of their COVID-19 symptoms, made them feel more connected to their healthcare team, and helped prevent emergency room visits. Identified themes regarding patient-perceived value of a RPMP included (1) security: a clinical safety net; (2) connection: a link to their clinical team during a period of isolation; and (3) empowerment: an education on the virus and symptom management. CONCLUSION: RPMPs are perceived to be of value to oncology patients with COVID-19. Policymakers should consider how these programs can be reimbursed to keep vulnerable patients at home and out of the acute care setting.
    Type of Medium: Online Resource
    ISSN: 2688-1527 , 2688-1535
    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2021
    detail.hit.zdb_id: 3005549-0
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  • 7
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 40, No. 16_suppl ( 2022-06-01), p. 1578-1578
    Abstract: 1578 Background: Acute care visits (emergency department [ED] visits or inpatient admissions) for patients with cancer are growing disproportionately. Traditional oncology care models have not effectively identified and managed at-risk patients to prevent acute care. A next step is to harness advances in technology and mobile applications to enable patients to report symptoms any time, enabling “digital hovering” - intensive monitoring and management of high-risk patients. Our objective was to evaluate a digital platform that identifies and remotely monitors high-risk patients initiating intravenous antineoplastic therapy with the goal of preventing unnecessary acute care visits. Methods: This was a single-institution matched cohort quality improvement study conducted at an NCI-designated cancer center between January 1, 2019 and March 31, 2020. Eligible patients were those initiating intravenous antineoplastic therapy who were identified as high-risk for seeking acute care. Patients were identified as high-risk for an acute care visit by their oncologist with decision support from a web-based machine learning model. Enrolled patients’ symptoms were monitored using a digital platform. The platform is integrated into the EMR and includes: 1) a secure patient portal enabling communication and daily delivery of electronic patient-reported outcomes symptom assessments; 2) clinical alerts for concerning symptoms; and 3) a symptom trending application. A dedicated team of registered nurses and nurse practitioners managed reported symptoms. These clinicians acted as an extension of the primary oncology team, assisting with patient management exclusively through the platform. The primary outcomes evaluated were incidence of ED visits and inpatient admissions within six months of intravenous antineoplastic initiation. Results: Eighty-one high-risk patients from the intervention arm were matched by stage and disease with contemporaneous high-risk control patients. Matched cohorts had similar baseline characteristics, including age, sex, race, and treatment. ED visits and hospitalizations within six months of treatment initiation were analyzed using cumulative incidence analyses with a competing risk of death. The cumulative incidence of an ED visit for the intervention cohort was 0.27 (95% CI: 0.17, 0.37) at six months compared to 0.47 (95% CI: 0.36, 0.58) in the control group (p = 0.01). The cumulative incidence of an inpatient admission was 0.23 (95% CI: 0.14, 0.33) in the intervention group versus 0.41 (95% CI: 0.30, 0.51) in the control group (p = 0.02). Conclusions: The narrow employment of technology solutions to complex care delivery challenges in oncology can improve outcomes and innovate care. This program was a first step in using a digital platform and a remote team to improve symptom care in the home for high-risk patients.
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2022
    detail.hit.zdb_id: 2005181-5
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  • 8
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 37, No. 15_suppl ( 2019-05-20), p. 6535-6535
    Abstract: 6535 Background: Monitoring and managing patient reported outcomes (PROs) has been recommended for oncology patients on active treatment but can be time and resource intensive. Identifying patients likely to benefit and the optimal frequency of PRO capture is still under investigation. We tested the feasibility of monitoring patients who are high-risk risk for acute care with daily PROs. Methods: Using data from our institution, we developed a model that employs over 400 clinical variables to calculate a patient’s risk of an emergency room visit within 6 months following the onset of treatment. From October 15, 2018 to January 23, 2019, we enrolled patients identified as high risk through a technology-enabled program to monitor and manage those patients’ symptoms. Enrolled patients entered PRO assessments daily via an online portal. Symptoms were monitored and managed by a centralized clinical team. Tiered notifications informed the team of concerning or escalating symptoms. We assessed how frequently patients completed symptom assessments and the frequency of symptom notifications. Results: During the pilot, 28 patients were identified as high risk and enrolled in the program (median age 65; 64% percent female). Disease types were: 15 (54%) thoracic, 7 (25%) gynecologic, 6 (21%) gastrointestinal. Median time in the program was 50 (6-98) days. Patients completed 840 of 1,350 assessments (62%). There were 328 assessments that triggered moderate alerts (39%) and 220 that triggered severe alerts (26%). The table describes the prevalence of symptoms at the patient-level. Conclusions: A model can be employed to identify high-risk patients in collaboration with clinicians. Our adherence rate with a daily symptom assessment was similar to those found in studies of less frequent PRO capture. Future work will expand to a larger patient population with other cancer types, evaluate impact on outcomes, and assess optimal frequency for PRO collection and alert thresholds. [Table: see text]
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2019
    detail.hit.zdb_id: 2005181-5
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  • 9
    Online Resource
    Online Resource
    American Society of Clinical Oncology (ASCO) ; 2020
    In:  Journal of Clinical Oncology Vol. 38, No. 15_suppl ( 2020-05-20), p. 2030-2030
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 38, No. 15_suppl ( 2020-05-20), p. 2030-2030
    Abstract: 2030 Background: With improved overall cancer survival, increasing number of cancer patients are undergoing active treatment. This, in return, add burden in acute symptom management related to disease and treatment. This has resulted in increasing unplanned emergency room (ER) visits and negatively impacted patients experience and health cost. We establish Symptom Care Clinic (SCC) embedded in suburban ambulatory oncology centers to reduce unplanned ER lists and to improve patient experience. Methods: Together with all stakeholders, we developed six SCCs at regional ambulatory centers in NY and NJ. Clearly defined work flow and algorithm were developed to ensure appropriate patient referral. On-site radiology and laboratory services are available. The SCCs are staffed with combination of Advanced Practice Provided (APP) and physicians or APP alone supported by on site medical oncologist or remote central Urgent Care Center Attendings. We evaluated clinic volumes, reduction ins unplanned ER visits and patient experience. Results: From October 2017 to December 2019, total of 17,542 SCC visits were documented. Total of 17,479 lab and 5,355 radiology tests as well as 3,915 infusions were performed. The top five most common laboratory tests are CBC, blood cultures, CMP, respiratory panel and urine culture. The most common symptoms are fever, nausea/vomiting/dehydration, rash and pain. Among all SCC visits during this period, 83% were discharged home and 17% were transferred to ER or hospitals. During 2019, total 10,736 SCC visits were recored, APP evaluated 73.7% of visits and physicians 16.3% with comaprable recidivism rate, 2.52% and 2.75%, respectively. Conservatively, we estimated that approximately 40% of visits would have been Er visits based on numbers of CBC and other testes performed. Qualitative feedbacks from patients indicated positive experience in convenient access, cohesive care coordination and time saving from traveling to and waiting in ER. Conclusions: We successfully implemented an effective acute symptom management system in busy ambulatory oncology centers that is patient centric. Out data showed that SCC reduced unplanned ER visits and that APP/physician model has low recidivism rate.
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2020
    detail.hit.zdb_id: 2005181-5
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  • 10
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 40, No. 16_suppl ( 2022-06-01), p. 1517-1517
    Abstract: 1517 Background: Strategies to improve transitions from the hospital to home for patients with cancer are considered an important component of quality, patient-centered care in oncology. CMS evaluates cancer hospital performance based on the 30-day unplanned hospital readmission rate, and this measure has been endorsed by the National Quality Forum. Nationally, the 30-day readmission rate for oncology patients ranges from 19%-27%. These readmissions come at high psychosocial, physical, and financial costs for patients and caregivers. A remote monitoring intervention that includes frequent contacts with the patient is likely to be effective in improving this transition. Methods: We evaluated the feasibility, acceptability, and perceived value of a mobile health intervention to monitor and manage symptoms of adult medical and surgical oncology patients discharged from an NCI-designated cancer center to home. Patients were monitored for 10 days, which is the median time to readmission for an oncology patient. The technology supporting the program included: 1) a patient portal enabling daily electronic patient-reported outcomes assessments; 2) a pulse oximeter to provide data on blood oxygen level and heart rate; 3) alerts for concerning symptoms; 4) an application to allow staff to review and trend symptom data; 5) a secure platform to support communications and televisits between staff and patients; 6) an advanced feedback report to provide just-in-time patient symptom education. Feasibility and acceptability were evaluated through engagement (goal: 〉 50% response rate) and symptom alerts and perceived value was measured through a patient engagement survey that included a net promoter score (how likely the patient is to recommend the program to similar patients; goal 〉 0.7). Results: Between September 27, 2020 to December 31, 2021, the program enrolled 1,091 medical oncology (median age: 63 years, 55% female) and 4,222 surgical oncology patients (median age: 63 years,55% female). Of those enrolled, 65% of medical and 74% of surgical oncology patients participated in home remote monitoring by self-reporting symptom data. This resulted in 2,869 completed symptom assessment from medical and 16,009 completed assessments from surgical patients. Sixty-three percent of medical oncology assessments resulted in a yellow (moderate) or red (severe) symptom alert compared with 26% for surgical oncology patients. Pain was the predominant symptom generating red alerts for medical oncology patients (17%). Fifty-two percent of patients completed the engagement survey, and the net promoter score was 0.82. Conclusions: A remote monitoring program after discharge was feasible, acceptable, and perceived to be of value by oncology patients discharged from a cancer center. Surgical and medical patients have similar response rates but differ in symptom burden. Future work will evaluate the value of a remote symptom monitoring platform in decreasing readmissions.
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2022
    detail.hit.zdb_id: 2005181-5
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