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  • 1
    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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  • 2
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 35, No. 31_suppl ( 2017-11-01), p. 4-4
    Abstract: 4 Background: Advance care planning (ACP) should be initiated early and readdressed often for cancer patients. We hypothesize that a rules-based algorithm can predict decreased overall survival, and can be used to target patients who would benefit from readdressing ACP. Methods: We performed a retrospective analysis of 219 patients receiving palliative chemotherapy with leukemia, cholangiocarcinoma, esophageal, gastric, pancreatic, lung or urothelial cancer at the University of Chicago Medicine. Patients were included if they had an index outpatient oncology visit from April 1, 2015 through June 30, 2015. We examined a three-month window from the index visit for a “high-risk event,” defined as: 1. change in chemotherapy 2. emergency department visit 3. hospitalization. Patients were followed from index visit until date of death or last clinical encounter as of January 31, 2017. Each “high-risk event” was treated as a time-varying covariate in a Cox proportional hazards regression model to calculate a hazard ratio of death compared to those without an event. Results: Sixty-seven percent of patients (146/219) experienced at least one high-risk event. A change in chemotherapy regimen, an ED visit, and a hospitalization occurred in 54% (118/219), 10% (22/219) and 26% (57/219) of patients respectively. The hazard ratio of death for patients with at least one high-risk event when compared to those without was 1.72 (95% CI: 1.19-2.46, p=0.003), when adjusted for age, gender, race, marital status, disease type, ECOG, and Charlson score. Inpatient admission independently reached significant for hazard of death. (HR 2.74: 95% CI: 1.84-4.09, p 〈 0.001). Conclusions: The rules-based algorithm identified patients with a greater risk of death. Implementation of this algorithm in the electronic medical record can identify patients with increased urgency to readdress goals of care. [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: 2017
    detail.hit.zdb_id: 2005181-5
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  • 3
    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. e21510-e21510
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 35, No. 15_suppl ( 2017-05-20), p. e21510-e21510
    Abstract: e21510 Background: Advance care planning (ACP) should be initiated early and readdressed often for cancer patients. We hypothesize that a rules-based algorithm based on occurrence of high-risk events can predict decreased overall survival, and can be used to target patients who would benefit from readdressing ACP. Methods: We performed a retrospective analysis of 221 patients receiving palliative chemotherapy with a diagnosis of leukemia, cholangiocarcinoma, esophageal, gastric, pancreatic, lung or urothelial cancer at the University of Chicago Medicine. Patients were included if they had an index outpatient oncology visit from April 1, 2015 through June 30, 2015. Starting at the date of index visit, we examined a three-month window for a “high-risk event,” defined as: 1. change in chemotherapy 2. emergency department visit 3. hospitalization. Patients were followed from index visit until date of death or last clinical encounter as of January 31, 2017. Each “high-risk event” was treated as a time-varying covariate in a Cox proportional hazards regression model to calculate a hazard ratio of death compared to those without an event. Results: Sixty-six percent of patients (146/221) experienced at least one high-risk event over the 3 month time frame. A change in chemotherapy regimen, an ED visit, and a hospitalization occurred in 53% (118/221), 10% (22/221) and 26% (57/221) of patients respectively. The hazard ratio of death for patients with at least one high-risk event when compared to those without was 1.86 (95% CI: 1.26-2.74, p = 0.002), when adjusted for age, gender, and race. Inpatient admission had the highest hazard of death among the high-risk events (HR 2.52: 95% CI: 1.69-3.76, p 〈 0.001). Conclusions: The rules-based algorithm identified patients with a greater risk of death. Implementation of this algorithm in the electronic medical record can identify patients with increased urgency to readdress goals of care.
    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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  • 4
    Online Resource
    Online Resource
    American Society of Clinical Oncology (ASCO) ; 2021
    In:  Journal of Clinical Oncology Vol. 39, No. 15_suppl ( 2021-05-20), p. 1504-1504
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 39, No. 15_suppl ( 2021-05-20), p. 1504-1504
    Abstract: 1504 Background: Oncology patients are particularly vulnerable to adverse outcomes from COVID-19 and require careful monitoring to identify early deterioration and render higher level care when indicated. 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: Adult patients who had either tested positive for COVID-19 on an outpatient microbiology test or were discharged after hospitalization for the virus were eligible. Patients enrolled in the RPMP received a daily 10-question electronic patient-reported outcome assessment of COVID-19 symptoms and their responses generated alerts to a centralized monitoring team for new or worsening symptoms. A subset of high-risk patients also received a pulse oximeter which alerted when blood oxygen levels dropped below 93%. RPM was discontinued 14 days after a patient’s positive test result and following 3 days without worsening symptoms or fever. Patients who exited the program and had completed at least one assessment were sent a patient engagement survey. The objective of the survey was to evaluate the patient’s experience with digital monitoring and symptom management for COVID-19. The assessment was structured with objective response questions, including a net promoter score, and free text questions to elicit patient perspectives on RPM value. Free text responses were analyzed using grounded theory to identify primary themes regarding perceived value. Results: The survey was distributed to 452 patients; 241 responded as of June 10, 2020 (53% completion rate). The net promoter score was 91%. The table provides responses to objective questions. Qualitative analysis of free text responses identified the primary themes regarding patient perceived value which included: 1) Security: patients appreciated that the RPMP provided a clinical safety net; 2) Connection: patients appreciated the link to their clinical team during a period of isolation; 3) Empowerment: patients appreciated that the RPMP provided education on the virus and symptom management. Conclusions: RPMPs are perceived to be of value to oncology patients with COVID-19. A key barrier to maintaining these programs is cost. Policymakers should consider how these programs can be reimbursed in the future so that they can continue to provide care to vulnerable patients and keep them at home out of the acute care setting.[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: 2021
    detail.hit.zdb_id: 2005181-5
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  • 5
    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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  • 6
    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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  • 7
    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. 6548-6548
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 35, No. 15_suppl ( 2017-05-20), p. 6548-6548
    Abstract: 6548 Background: ICU admissions in the last 30 days of life are an indicator of poor care. Our prior research found nearly half of terminal oncology ICU hospitalizations are potentially avoidable. Methods: Data were derived from 72 patients consecutively cared for in an academic medical center’s oncology practice who died in an ICU between July 1, 2012 and June 30, 2013. Oncologists, intensivists, and hospitalists used a standardized assessment tool to review each patient’s electronic health record from 3 months prior to hospitalization until death; they made a clinical determination of avoidability. Two investigators, blinded to the specialty, used a grounded theory approach to extract clinical themes associated with the reviewer’s determination of avoidability. Total, direct, and indirect costs were abstracted for each avoidable hospitalization. Results: Thirty-four (47%) of the examined hospitalizations were deemed avoidable. The primary themes associated with avoidability, and the percentage by specialty, were as follows: 1) failure to initiate appropriate advance care planning in the outpatient setting (68% oncologists, 55% intensivists, 65% hospitalists), 2) failure to integrate understanding of limited prognosis (23% oncologists, 24% intensivists, 26% hospitalists), and 3) failure of clinical management (6% oncologists, 21% intensivists, 6% hospitalists). A failure to educate and integrate surrogates into timely medical decision-making was a prominent secondary theme for oncologists (22%), intensivists (18%), and hospitalists (29%). The total cost per patient averaged $44,532 with direct and indirect costs averaging $25,215 and $19,317, respectively. High cost areas were ICU level care (35%) and pharmaceuticals (16%). Conclusions: The themes identified suggest potential preventative interventions, including higher rates of outpatient advance care planning, oncology inpatient communication to promote patient’s prognostic understanding, prevention of failures in clinical management, and better education and integration of surrogates. Given 8% of oncology patients expire in the ICU and 47% were identified as avoidable, the potential national annual cost of these avoidable hospitalizations is $997MM.
    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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  • 8
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 36, No. 30_suppl ( 2018-10-20), p. 314-314
    Abstract: 314 Background: Acute care accounts for half of cancer expenditures and is a measure of poor quality care. Identifying patients at high risk for ED visits enables institutions to target symptom management 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 a predictive analytics framework for clinical use with attention to the modeling technique, clinician feedback, and application metrics. The model employs EHR data from initial visit to first antineoplastic administration for new 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. 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. Clinician review was performed to confirm EHR data input validity. The final regularized multivariate logistic regression model was chosen based on clinical and statistical significance. Parameter selection and model evaluation utilized the positive predictive value for the top 25% of observations ranked by model-determined risk. The final model was evaluated using a test set containing 20% of randomly held out data. The model was calibrated based on a 5-fold cross-validation scheme over the training set. Results: There are 5,752 antineoplastic 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. The 400 clinically relevant features draw from multiple areas in the EHR. For example, those features found to increase risk include: combination chemotherapy, low albumin, social work needs, and opioid use, whereas those found to decrease risk include stage 1 disease, never smoker status, and oral antineoplastic therapy. Conclusions: We have constructed a framework to build a clinically relevant 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: 2018
    detail.hit.zdb_id: 2005181-5
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  • 9
    Online Resource
    Online Resource
    American Society of Clinical Oncology (ASCO) ; 2018
    In:  Journal of Clinical Oncology Vol. 36, No. 15_suppl ( 2018-05-20), p. e20566-e20566
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 36, No. 15_suppl ( 2018-05-20), p. e20566-e20566
    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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  • 10
    Online Resource
    Online Resource
    American Society of Clinical Oncology (ASCO) ; 2018
    In:  Journal of Clinical Oncology Vol. 36, No. 15_suppl ( 2018-05-20), p. e21049-e21049
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 36, No. 15_suppl ( 2018-05-20), p. e21049-e21049
    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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