Risk stratification and outreach to hematology/oncology patients during the COVID-19 pandemic
Open accessAbstract
Purpose Cancer patients have many medical and psychosocial needs, which may increase during the COVID-19 pandemic. We sought to (1) risk-stratify hematology/oncology patients using general medicine and cancer-specific methods to identify those at high risk for acute care utilization, (2) measure the correlation between two risk stratification methods, and (3) perform a telephone-based needs assessment with intervention for high-risk patients.Methods Patients were risk-stratified using a general medical health composite score (HCS) and a cancer-specific risk (CSR) stratification based on disease and treatment characteristics. The correlation between HCS and CSR was measured using Spearman's correlation. A multi-disciplinary team developed a focused needs assessment script with recommended interventions for patients categorized as high-risk by either method. The number of patient needs identified and referrals for services made in the first month of outreach are reported.Results A total of 1697 patients were risk-stratified, with 17% high-risk using HCS and 22% high-risk using CSR. Correlation between HCS and CSR was modest (ρ = 0.41). During the first month of the pilot, 286 patients were called for outreach with 245 contacted (86%). Commonly identified needs were financial difficulties (17%), uncontrolled symptoms (15%), and interest in advance care planning (13%), resulting in referral for supportive services for 33% of patients.Conclusion There is a high burden of unmet medical and psychosocial needs in hematology/oncology patients during the COVID-19 pandemic. A telephone-based outreach program results in the identification of and intervention for these needs; however, additional cancer-specific risk models are needed to improve targeting to high-risk patients.
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- Findingown data
The correlation between the Health Composite Score and the cancer-specific risk stratification was 0.41 (modest/moderate).
“The correlation between HCS and CSR was moderate at 0.41.”
- Also stated in: § Results · plain
“Correlation between HCS and CSR was modest (ρ = 0.41).”
Quote in the paperNot a substantial claim - Also stated in: § Results · plain
- Findingown data
Interest in advance care planning was identified in 13% of the patients reached by outreach.
“Commonly identified patient issues were financial difficulties (17%), uncontrolled symptoms (15%), and interest in ACP (13%) (Table 1).”
- Also stated in: § Results · plain
“Commonly identified needs were financial difficulties (17%), uncontrolled symptoms (15%), and interest in advance care planning (13%), resulting in referral for supportive services for 33% of patients.”
Quote in the paperNot a substantial claim - Also stated in: § Results · plain
- Findingown data
Uncontrolled symptoms were identified in 15% of the patients reached by outreach.
“Commonly identified patient issues were financial difficulties (17%), uncontrolled symptoms (15%), and interest in ACP (13%) (Table 1).”
- Also stated in: § Results · plain
“Commonly identified needs were financial difficulties (17%), uncontrolled symptoms (15%), and interest in advance care planning (13%), resulting in referral for supportive services for 33% of patients.”
Quote in the paperNot a substantial claim - Also stated in: § Results · plain
- Findingown data
Financial difficulties were identified in 17% of the patients reached by outreach.
“Commonly identified patient issues were financial difficulties (17%), uncontrolled symptoms (15%), and interest in ACP (13%) (Table 1).”
- Also stated in: § Results · plain
“Commonly identified needs were financial difficulties (17%), uncontrolled symptoms (15%), and interest in advance care planning (13%), resulting in referral for supportive services for 33% of patients.”
Quote in the paperNot a substantial claim - Also stated in: § Results · plain
- Findingown data
33% of the patients reached by outreach were referred for additional services.
“Overall, 33% of patients were referred for additional services (Online Resource 3).”
- Also stated in: § Results · plain
“Commonly identified needs were financial difficulties (17%), uncontrolled symptoms (15%), and interest in advance care planning (13%), resulting in referral for supportive services for 33% of patients.”
Quote in the paperNot a substantial claim - Also stated in: § Results · plain
- Premisecitation
Few cancer-specific risk stratification models exist.
“Reducing acute healthcare utilization requires the identification of high-risk patients, and few cancer-specific risk stratification models exist [7].”
- Also stated in: § Introduction · plain
“The applicability of general medical risk stratification tools to oncology patients is unclear, and few cancer-specific models exist.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [7] Handley NR, Schuchter LM, Bekelman JE (2018) Best Practices for Reducing Unplanned Acute Care for Patients With Cancer. J Oncol Pract 14:306–313. https://doi.org/10.1200/jop.17.00081 source
Not checked in the free run.
- Also stated in: § Introduction · plain
- Interpretationown data
Having a protocol for interventions produced a high rate of referrals to address identified needs.
“A protocol for interventions resulted in a high rate of referrals to address these needs.”
Quote in the paperSubstantial claim - Interpretationown data
Hematology/oncology patients carry a high burden of unmet medical and psychosocial needs during the COVID-19 pandemic.
“There is a high burden of unmet medical and psychosocial needs in hematology/oncology patients during the COVID-19 pandemic.”
- Also stated in: § Discussion · plain
“Importantly, despite a robust nurse navigation program available to all our oncology patients, 33% of patients had additional needs uncovered through outreach during the COVID-19 pandemic.”
Quote in the paperSubstantial claim - Also stated in: § Discussion · plain
- Premisecitation
The cancer-specific risk stratification used in this study was adapted from a model developed by Rocque and colleagues.
“Our CSR stratification was adapted from the model developed by Rocque and colleagues [3].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [3] Rocque GB, Pisu M, Jackson BE, Kvale EA, Demark-Wahnefried W, Martin MY, Meneses K, Li Y, Taylor RA, Acemgil A, Williams CP, Lisovicz N, Fouad M, Kenzik KM, Partridge EE, for the Patient Care Connect Group (2017) Resource use and medicare costs during lay navigation for geriatric patients with cancer. JAMA Oncol 3:817–825. https://doi.org/10.1001/jamaoncol.2016.6307 source
Not checked in the free run.
- Interpretationown data
A telephone-based outreach program leads to the identification of and intervention for unmet needs in this population.
“A telephone-based outreach program results in the identification of and intervention for these needs; however, additional cancer-specific risk models are needed to improve targeting to high-risk patients.”
Quote in the paperSubstantial claim - Study design and conductnone given
Applying the Health Composite Score and cancer-specific risk stratification to the patients of 16 providers produced a sample representative of the major cancer types.
“For this pilot, the HCS and CSR were applied to the patients of 16 providers, creating a sample representative of the major cancer types.”
Quote in the paperNot a substantial claim - Premisecitation
Oncology navigation programs and proactive symptom management can reduce emergency room visits and hospitalizations.
“Oncology navigation programs and proactive symptom management can decrease ER visits and hospitalizations [3–5].”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [3] Rocque GB, Pisu M, Jackson BE, Kvale EA, Demark-Wahnefried W, Martin MY, Meneses K, Li Y, Taylor RA, Acemgil A, Williams CP, Lisovicz N, Fouad M, Kenzik KM, Partridge EE, for the Patient Care Connect Group (2017) Resource use and medicare costs during lay navigation for geriatric patients with cancer. JAMA Oncol 3:817–825. https://doi.org/10.1001/jamaoncol.2016.6307 source
Not checked in the free run.
- cites [4] Rocque GB, Partridge EE, Pisu M, Martin MY, Demark-Wahnefried W, Acemgil A, Kenzik K, Kvale EA, Meneses K, Li X, Li Y, Halilova KI, Jackson BE, Chambless C, Lisovicz N, Fouad M, Taylor RA (2016) The Patient Care Connect Program: transforming health care through lay navigation. J Oncol Pract 126:e633–e642. https://doi.org/10.1200/jop.2015.008896 source
Not checked in the free run.
- cites [5] Barkley R, Soobader M-J, Wang J, Blau S, Page RD (2019) Reducing cancer costs through symptom management and triage pathways. J Oncol Pract 15:e91–e97. https://doi.org/10.1200/jop.18.00082 source
Not checked in the free run.
- May combine two claims. 6
- Classified as probably not a substantial claim. 4
May combine two claims.
Findingown dataIn the first month of outreach, 286 patients were called and 245 (86%) were successfully contacted.
“During the first month of outreach, 286 patients were called with 245 (86%) successfully contacted.”
- Also stated in: § Results · plain
“During the first month of the pilot, 286 patients were called for outreach with 245 contacted (86%).”
Quote in the paperNot a substantial claim- Also stated in: § Results · plain
May combine two claims.
Findingown dataAmong the 1697 hematology/oncology patients risk-stratified, the general medicine Health Composite Score classified 17% as high risk, 49% as moderate risk, and 34% as low risk.
“A total of 1697 patients were risk-stratified (Online Resource 2). By HCS, 17%, 49%, and 34% of patients were high, moderate, and low risk, respectively.”
- Also stated in: § Results · plain
“A total of 1697 patients were risk-stratified, with 17% high-risk using HCS and 22% high-risk using CSR.”
Quote in the paperNot a substantial claim- Rests on an assumption: The general medicine Health Composite Score, developed and validated in a general medicine population, is applicable to hematology/oncology patients.
- Also stated in: § Results · plain
Probably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataThe mean duration of the outreach calls was 14 minutes.
“Most calls were made by nurse navigators (66%), with a mean call duration of 14 min.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataAmong the 1697 patients risk-stratified, the cancer-specific risk stratification classified 22% as high risk, 37% as moderate risk, and 41% as low risk.
“By CSR, 22%, 37%, and 41% of patients were high, moderate, and low risk, respectively.”
- Also stated in: § Results · plain
“A total of 1697 patients were risk-stratified, with 17% high-risk using HCS and 22% high-risk using CSR.”
Quote in the paperNot a substantial claim- Also stated in: § Results · plain
Probably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataNurse navigators made most (66%) of the outreach calls.
“Most calls were made by nurse navigators (66%), with a mean call duration of 14 min.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
InterpretationreasoningBecause the pilot ran at a well-resourced academic center, its results may not generalize to lower-resourced settings.
“Our pilot was implemented at a well-resourced academic center and may have limited generalizability to lower-resourced settings.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationThe Health Composite Score, developed at the University of North Carolina, predicts 90-day hospitalization in a general medicine population.
“The HCS was developed at the University of North Carolina (UNC) and is predictive of 90-day hospitalization in a general medicine population [6].”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [6] Jarmul JA, Whitney A, Gwynne M et al (2017) Validation of a composite health score to predict 90-day all-cause hospitalization in a population of general medicine and family medicine patients seen at two large, academic faculty practices. J Gen Intern Med 32(Suppl 2)
Not checked in the free run.
May combine two claims.
Interpretationown dataThe general medicine composite score correlates only modestly with the cancer-specific risk stratification and does not capture the risks associated with a cancer diagnosis and its treatment.
“In this pilot, we found that a general medicine composite score has only modest correlation with a cancer-specific risk stratification, failing to capture risks associated with a cancer diagnosis and treatment.”
Quote in the paperSubstantial claim- Rests on an assumption: The general medicine Health Composite Score, developed and validated in a general medicine population, is applicable to hematology/oncology patients.
Probably not a substantial claim: may not pass S2 (checkable).
InterpretationreasoningFurther cancer-specific risk models are required to better target high-risk patients.
“additional cancer-specific risk models are needed to improve targeting to high-risk patients.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationOncology patients are at high risk of contracting COVID-19 and suffering its complications, making prevention of acute healthcare utilization increasingly important during the pandemic.
“Due to the high risk for contracting and suffering complications of COVID-19 among oncology patients, prevention of acute healthcare utilization, such as emergency room (ER) visits and hospitalizations, is increasingly important during the COVID-19 pandemic [1, 2].”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [1] Liang W, Guan W, Chen R, Wang W, Li J, Xu K, Li C, Ai Q, Lu W, Liang H, Li S, He J (2020) Cancer patients in SARS-CoV-2 infection: a nationwide analysis in China. Lancet Oncol 21:335–337. https://doi.org/10.1016/S1470-2045(20)30096-6 source
Not checked in the free run.
- cites [2] He W, Chen L, Chen L, Yuan G, Fang Y, Chen W, Wu D, Liang B, Lu X, Ma Y, Li L, Wang H, Chen Z, Li Q, Gale RP (2020) COVID-19 in persons with haematological cancers. Leukemia. 34:1637–1645. https://doi.org/10.1038/s41375-020-0836-7 source
Not checked in the free run.
The paper relies on this without support.
The general medicine Health Composite Score, developed and validated in a general medicine population, is applicable to hematology/oncology patients.
“The applicability of general medical risk stratification tools to oncology patients is unclear, and few cancer-specific models exist.”
“Given the need to risk stratify patients expediently, we explored whether a pre-existing HCS could be applied.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Many participants irrespective of age, cancer type, or treatment regimen expressed unmet needs related to psychological or emotional domains of well-being, including fear of contracting COVID-19 compounded by increased risk recognition leading to anxiety and distress, fear of the unknown long-term impact, and a positive association between fear of COVID-19 and increased psychological distress and
“Many of the participants irrespective of age, cancer type, or treatment regimen expressed unmet needs related to psychological or emotional domains of well-being [19–21, 24–28].”
From The unmet supportive care needs of people affected by cancer during the COVID-19 pandemic: an integrative review (2023) · cites this paper as [28]
Cites
Cancer patients in SARS-CoV-2 infection: a nationwide analysis in China
Liang, W., Guan, W., Chen, R., Wang, W., Li, J., Xu, K., Li, C., Ai, Q., Lu, W., Liang, H., et al. (2020) · The Lancet Oncology · doi:10.1016/s1470-2045(20)30096-6 · Cited by 4,384 · cited 1× · see citing works
“Due to the high risk for contracting and suffering complications of COVID-19 among oncology patients, prevention of acute healthcare utilization, such as emergency room (ER) visits and hospitalizations, is increasingly important during the COVID-19 pandemic [1, 2].”
BackgroundCOVID-19 in persons with haematological cancers
He, W., Chen, L., Chen, L., Yuan, G., Fang, Y., Chen, W., Wu, D., Liang, B., Lu, X., Ma, Y., et al. (2020) · Leukemia · doi:10.1038/s41375-020-0836-7 · Cited by 462 · cited 1× · see citing works
“Due to the high risk for contracting and suffering complications of COVID-19 among oncology patients, prevention of acute healthcare utilization, such as emergency room (ER) visits and hospitalizations, is increasingly important during the COVID-19 pandemic [1, 2].”
BackgroundResource Use and Medicare Costs During Lay Navigation for Geriatric Patients With Cancer
Rocque, G. B., Pisu, M., Jackson, B. E., Kvale, E. A., Demark-Wahnefried, W., Martin, M. Y., Meneses, K., Li, Y., Taylor, R. A., Acemgil, A., et al. (2017) · JAMA Oncology · doi:10.1001/jamaoncol.2016.6307 · Cited by 166 · see citing works
Best Practices for Reducing Unplanned Acute Care for Patients With Cancer
Handley, N. R., Schuchter, L. M., & Bekelman, J. E. (2018) · Journal of Oncology Practice · doi:10.1200/jop.17.00081 · Cited by 137 · see citing works
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Background
Flagged first, then by citations
Cited by
Sorted by citations
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Redox stress in COVID-19: Implications for hematologic disorders
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“in financial difficulties (Osterman et al., 2021), facilitated family e-meetings (Kuntz et al.”
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Senology at the time of the coronavirus – What we did or should learn from the COVID-19 pandemic
Pagani, O. (2021) · Senologie - Zeitschrift für Mammadiagnostik und -therapie · doi:10.1055/a-1367-3888
- Authors
- Osterman, C. K., Triglianos, T., Winzelberg, G. S., Nichols, A. D., Rodriguez-O’Donnell, J., Bigelow, S. M., van Deventer, H., Sanoff, H. K., & Ray, E. M.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- Corresponding author
- Osterman, Chelsea K.
- Venue
- Supportive Care in Cancer
- Published
- 2020-10-12
- Volume
- 29
- Issue
- 3
- Pages
- 1161-1164
- ISSN
- 0941-4355 (ISSN-L)
- 1433-7339
- PMC
- PMC7549726
- OpenAlex
- W3092026775
- Cited by
- 10
- References
- 8
- Citations by year
- 2024: 1 · 2023: 5 · 2022: 3 · 2021: 1
- FWCI
- 0.81
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Supportive Care in Cancer (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- UNC Libraries
- Funders
- Agency for Healthcare Research and Quality (5T32H2000032)
- Topics
- Health Sciences › Medicine › Oncology › COVID-19 and healthcare impacts
- Health Sciences › Medicine › Oncology › Cancer survivorship and care
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
- Keywords
- risk stratification, hematologic patients, cancer patients, COVID-19 pandemic, telephone outreach, needs assessment, acute care utilization, financial hardship, advance care planning, psychosocial needs
- MeSH terms
- COVID-19, SARS-CoV-2, Health Services, Hematologic Diseases, Humans, Neoplasms, Surveys and Questionnaires, Referral and Consultation, Risk Assessment, Needs Assessment
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