Impact of telehealth implementation on diagnosis of hypertensive disorders of pregnancy.

BACKGROUND: COVID-19 caused a rapid integration of telehealth into prenatal care. This raises questions about the ability to screen for hypertensive disorders of pregnancy when caring for patients remotely. OBJECTIVE: This study aimed to assess the effect of telehealth adaptation on the timing and severity of diagnosis of hypertensive disorders of pregnancy. STUDY DESIGN: This was a retrospective study of patients with hypertensive disorders of pregnancy who delivered from April 2019 to October 2019 (before the pandemic) and April 2020 to October 2020 (during the pandemic) at 1 urban tertiary care center. The primary outcome was mean gestational age at diagnosis of a hypertensive disorder of pregnancy. The secondary outcomes included severity of diagnosis, both initially and at the time of delivery. The results were adjusted for baseline characteristic difference at P<.10, using multivariable logistic regression and analysis of covariance, as appropriate. The sample size was calculated based on a previous cohort study of patients who developed preeclampsia, with a mean gestational age at delivery of 36.3 weeks and a standard deviation of 2.8 weeks. A sample size of 124 patients would be needed per group to detect a gestational age difference of 1 week with 80% power and a 95% confidence interval. RESULTS: Overall, 498 patients were included, with 231 from 2019 and 267 from 2020. Of note, 17.1% of patients had preeclampsia with severe features initially, and 29.3% of patients met the criteria at delivery. In 2020, 80.5% of patients used telehealth (vs 0.9% of patients in 2019), doing so for a mean of 29.0% of prenatal appointments. Unadjusted and adjusted analyses showed no significant difference in gestational age at diagnosis or diagnosis severity between cohorts. In the adjusted analysis, cohort year was not significantly associated with severity of initial diagnosis (adjusted odds ratio, 0.86; 95% confidence interval, 0.53-1.39; P=.53) or severity of diagnosis at delivery (adjusted odds ratio, 0.97; 95% confidence interval, 0.64-1.46; P=.87). However, Black race was significantly associated with increased risk of having severe preeclampsia at initial diagnosis (adjusted odds ratio, 1.70; 95% confidence interval, 1.01-2.85; P=.046). In addition, Black race (adjusted odds ratio, 2.62; 95% confidence interval, 1.60-4.28; P<.001), Hispanic ethnicity (adjusted odds ratio for non-Hispanic, 0.40; 95% confidence interval, 0.19-0.82; P=.01), and initial body mass index (adjusted odds ratio, 1.04; 95% confidence interval, 1.01-1.06; P=.005) were significantly associated with a diagnosis of severe preeclampsia at delivery. CONCLUSION: The adaptation of telehealth was not associated with delays in the diagnosis of hypertensive disorders of pregnancy or with increased severity of diagnoses.

Anticancer Therapy at the End of Life: Lessons From a Community Cancer Institute.

INTRODUCTION: Studies have shown aggressive cancer care at the end of life is associated with decreased quality of life, decreased median survival, and increased cost of care. This study describes the patients most likely to receive systemic anticancer therapy at the end of life in a community cancer institute. MATERIALS AND METHODS: We performed a retrospective cohort study of 201 patients who received systemic anticancer therapy in our institution and died between July 2016 and April 2017. Data collected included primary malignancy, hospice enrollment, healthcare utilization, Oncology Care Model (OCM) enrollment, and clinical assessments at last office visit prior to a treatment decision before death. We defined our outcome variable as the receipt of anticancer treatment in the last 14 days of a patient's life. We evaluated 20 clinical exposure variables with respect to the outcome classes. Risk ratios along with their associated confidence intervals and P values were calculated. Significance was determined using the Benjamini-Hochberg procedure to account for multiple testing. RESULTS: Of the 201 patients who died of cancer, 36 (17%) received anticancer therapy within the last 14 days of life. Several risk factors were significantly positively associated with receiving anticancer therapy at the end of life including hospitalization within 30 days of end of life, number of hospitalizations per patient (≥2), death in hospital, enrollment in OCM, and a diagnosis of hematologic malignancy. CONCLUSION: Our findings demonstrate those enrolled in the OCM and those with hematologic malignancies have a higher risk of receiving anticancer therapy in the last 14 days of life. These observations highlight the need for better identifying the needs of high-risk patients and providing good quality care throughout the disease trajectory to better align end-of-life care with patients' wishes.

Illness Understanding of Oncology Patients in a Community-Based Cancer Institute.

PURPOSE: Several studies have demonstrated that patients have a poor understanding of prognosis, survival, and effectiveness of chemotherapy, particularly in the setting of advanced cancer. This study examines oncology patients' understanding of their illness based on accurate reporting of stage at diagnosis and knowledge of cancer status (ie, free of cancer or in remission v active disease). MATERIALS AND METHODS: Two hundred eight patients with cancer previously treated at our large community-based cancer institute participated in the Consumer-Based Cancer Care Value Index field survey. Electronic medical record documentation of stage at diagnosis and cancer status was compared with patients' self-reported responses. Concordance of responses and variables influencing discordance were evaluated. RESULTS: In 51.0% of patients, self-reported cancer stage matched the abstracted stage, with the highest concordance in patients with advanced cancer (72%) versus patients with stage I to III disease (36.4% to 61.5%). Unexpectedly, discordance was lower among patients with advanced cancer compared with patients with stage I to III cancer ( P = .0528). Patients who were concordant for cancer stage at diagnosis were significantly more likely to be female ( P = .001), be younger than age 65 years ( P = .01), have an income > $60,000 ( P = .03), and have more education ( P = .02). In 64.4% of patients, self-reported cancer status (ie, free of cancer or in remission v active disease) matched the abstracted status. Nearly 30% of patients were not sure about their status, even when they were free of cancer or in remission. CONCLUSION: Our findings confirm that more than one quarter of patients with advanced cancer have poor illness understanding and highlight that an even greater number of patients with early stage I to III cancer have poor illness understanding. These observations highlight the need to improve illness understanding for patients across the entire cancer continuum.