Value Tools for Patients in Cancer Care

Winckworth-Prejsnar, Katy; Lentz, Lisa Korin; Nardi, Elizabeth A.; Pruthi, Sandhya; Fitzgerald, Clara; Carlson, R. W.

doi:10.6004/jnccn.2017.0118

Cited by 5 publications

(3 citation statements)

References 5 publications

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“…People with cancer value communication with their treating oncologist and shared decision making throughout the disease spectrum, especially at times of treatment modifications. 7,8,16,39 Oncologists must therefore remain well informed on the emerging data addressing COVID-19 and cancer, dynamically incorporating the COVID-19 climate into patient care to achieve an acceptable balance between risk of infection and risk of untreated cancer. Furthermore, oncologists must screen patients for their psychosocial wellbeing and establish a robust framework of patient support, recognizing that communication is a critical clinical tool to improve QOL in these times.…”

Section: Commentmentioning

confidence: 99%

Impact of the coronavirus disease 2019 pandemic on the quality of life for women with ovarian cancer

Frey

Ellis

Zeligs

et al. 2020

American Journal of Obstetrics and Gynecology

103

135

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BACKGROUND: The coronavirus disease 2019 pandemic has resulted in unprecedented challenges for the oncology community. For people living with cancer, treatments are interrupted, surgeries cancelled, and regular oncology evaluations rescheduled. People with cancer and their physicians must balance plausible fears of coronavirus disease 2019 and cancer treatment with the consequences of delaying cancer care. OBJECTIVE: We aim to evaluate the experience of women with ovarian cancer during the coronavirus disease 2019 pandemic. STUDY DESIGN: Women with a current or previous diagnosis of ovarian cancer completed an online survey focusing on treatment interruptions and quality of life. The quality of life was measured with the Cancer Worry Scale and Hospital Anxiety and Depression Scale. The survey was distributed through survivor networks and social media. Univariate and multivariable linear regression analysis were used to evaluate the effect of participant characteristics on quality of life survey scores. RESULTS: A total of 603 women, from 41 states, visited the survey website between March 30, 2020, and April 13, 2020, and 555 (92.0%) completed the survey. The median age was 58 years (range, 20e85). At the time of survey completion, 217 participants (43.3%) were in active treatment. A total of 175 participants (33%) experienced a delay in some component of their cancer care. Ten (26.3%) of the 38 participants scheduled for surgery experienced a delay, as did 18 (8.3%) of the 217 participants scheduled for nonsurgical cancer treatment. A total of 133 participants (24.0%) had a delayed physician appointment, 84 (15.1%) laboratory tests, and 53 (9.6%) cancer-related imaging. Among the cohort, 88.6% (489) reported significant cancer worry, 51.4% (285) borderline or abnormal anxiety, and 26.5% (147) borderline or abnormal depression. On univariate analysis, age less than 65 years, being scheduled for cancer treatment or cancer surgery, delay in oncology care, being self-described as immunocompromised, and use of telemedicine were all associated with higher levels of cancer worry. Higher anxiety scores were associated with age less than 65 years and being selfdescribed as immunocompromised. Higher depression scores were associated with age less than 65 years, being scheduled for cancer surgery, delay in oncology care, being self-described as immunocompromised, and use of telemedicine. On multivariable linear regression analysis, age less than 65 and being self-described as immunocompromised were independently predictive of greater cancer worry, anxiety, and depression, and delay in cancer care was predictive of anxiety and depression. CONCLUSION: The coronavirus disease 2019 crisis is affecting care of patients with ovarian cancer; surgeries, treatments, scheduled physician appointments, laboratory tests, and imaging are cancelled or delayed. Younger age, presumed immunocompromise, and delay in cancer care were associated with significantly higher levels of cancer worry, anxiety, and depression. Providers must work with...

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Section: Commentmentioning

confidence: 99%

Impact of the coronavirus disease 2019 pandemic on the quality of life for women with ovarian cancer

Frey

Ellis

Zeligs

et al. 2020

American Journal of Obstetrics and Gynecology

103

135

View full text Add to dashboard Cite

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“…Local patient care, if well organized and coordinated, is certainly patient-centered and can be very timely, cost-effective, and efficient and can result in high patient satisfaction. 36,37 Due to the small size of our community, the majority of our patients are already known to us from prior episodes of care or treatment of friends and family members. Many of our cancer patients are neighbors, friends, or co-workers.…”

Section: Safe and Effectivementioning

confidence: 99%

Quality and Value in Rural Cancer Care

Sarap

2022

The American Surgeon™

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Nearly 60 million people reside in rural America with only 10% of US general surgeons providing for their surgical care. Rural cancer care has been maligned in the literature due to a lack of understanding of local resource limitations and to the difficulties involved in documenting the quality of local cancer care in small and rural communities. A majority of US cancer patients are diagnosed and treated in community cancer programs, many of which are Commission on Cancer Accredited and deliver care that is of high quality and value. The article discusses the components of high quality health care and offers suggestions for solo or small group rural surgeons to assist in collection of their own quality data and comparison to national benchmarks. One small rural program in Appalachian Ohio is used for a best-case example.

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“…[9][10][11][12] Eastern Cooperative Oncology Group (ECOG) Performance Status and Karnofsky Performance Status (KPS) are two of the most prevalent methods of measuring performance status. 13,14 Table 1 describes the scoring systems and mapping between these two measures.…”

Section: Introductionmentioning

confidence: 99%

Facilitating clinical research through automation: Combining optical character recognition with natural language processing

et al. 2022

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Background/Aims Performance status is crucial for most clinical research, as an eligibility criterion, a comorbidity covariate, or a trial endpoint. Yet information on performance status often is embedded as free text within a patient’s electronic medical record, rather than coded directly, thereby making this concept extremely difficult to extract for research. Furthermore, performance status information frequently resides in outside reports, which are scanned into the electronic medical record along with thousands of clinic notes. The image format of scanned documents also is a major obstacle to the search and retrieval of information, as natural language processing cannot be applied to unstructured text within an image. We, therefore, utilized optical character recognition software to convert images to a searchable format, allowing the application of natural language processing to identify pertinent performance status data elements within scanned electronic medical records. Methods Our study cohort consisted of 189 subjects diagnosed with diffuse large B-cell lymphoma for whom performance status was a required data element for analysis of prognostic factors related to recurrence and survival. Manual abstraction of performance status was previously conducted by a clinical Subject Matter Expert, serving as the gold standard. Leveraging our data warehouse, we extracted relevant scanned electronic medical record documents and applied optical character recognition to these images using the ABBYY FineReader software. The Linguamatics i2e natural language processing software was then used to run queries for performance status against the corpus of electronic medical record documents. We evaluated our optical character recognition/natural language processing pipeline for accuracy and reduction in data extraction effort. Results We found that there was high accuracy and reduced time for extraction of performance status data by applying our optical character recognition/natural language processing pipeline. The transformed scanned documents from a random sample of patients yielded excellent precision, recall, and F score, with <1% incorrect results. Time savings from a second cohort showed that median time to review documents for patients with performance status data present was reduced by a third. The major time savings was in the review of those documents that in fact did not contain performance status information: median of 18 minutes versus 108 minutes for manual review, an 83% reduction in data abstraction effort. Conclusion By applying this optical character recognition/natural language processing pipeline, we achieved significant operational improvement and reduced time for information retrieval to support clinical research. Our study demonstrated that optical character recognition software provides an effective mechanism to transform scanned electronic medical record images to allow the application of natural language processing, yielding highly accurate data abstraction. We conclude that our optical character recognition/natural language processing pipeline can greatly facilitate research data abstraction by providing a highly focused data review, eliminating unnecessary manual review of the entire chart, and thus freeing time for abstracting other data elements requiring more human interpretation.

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Value Tools for Patients in Cancer Care

Cited by 5 publications

References 5 publications

Impact of the coronavirus disease 2019 pandemic on the quality of life for women with ovarian cancer

Impact of the coronavirus disease 2019 pandemic on the quality of life for women with ovarian cancer

Quality and Value in Rural Cancer Care

Facilitating clinical research through automation: Combining optical character recognition with natural language processing

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