Abstract Background The symptom burden associated with cancer and its treatment can negatively affect patients’ quality of life and survival. Symptom-focused collaborative care model (CCM) interventions can improve outcomes, but only if patients engage with them. We assessed the receptivity of severely symptomatic oncology patients to a remote nurse-led CCM intervention. Methods In a pragmatic, cluster-randomized, stepped-wedge trial conducted as part of the National Cancer Institute IMPACT Consortium (E2C2, NCT03892967), patients receiving cancer care were asked to rate their sleep disturbance, pain, anxiety, emotional distress, fatigue, and limitations in physical function. Patients reporting at least 1 severe symptom (≥7/10) were offered phone consultation with a nurse symptom care manager (RN SCM). Initially, patients had to “opt-in” to receive a call, but the protocol was later modified so they had to “opt-out” if they did not want a call. We assessed the impact of opt-in vs opt-out framing and patient characteristics on receptiveness to RN SCM calls. All statistical tests were 2-sided. Results Of the 1204 symptom assessments (from 864 patients) on which at least 1 severe symptom was documented, 469 (39.0%) indicated receptivity to an RN SCM phone call. The opt-out period (odds ratio [OR] = 1.61, 95% confidence interval [CI] = 1.12 to 2.32, P = .01), receiving care at a tertiary care center (OR = 3.59, 95% CI = 2.18 to 5.91, P < .001), and having severe pain (OR = 1.80, 95% CI = 1.24 to 2.62, P = .002) were associated with statistically significantly greater willingness to receive a call. Conclusions Many severely symptomatic patients were not receptive to an RN SCM phone call. Better understanding of reasons for refusal and strategies for improving patient receptivity are needed.
Abstract 15348: Higher Mortality in Patients with Undiagnosed Hypertension: Is the Electronic Medical Record the Key to Their Identification?
Introduction: Patients with hypertension (HTN) may remain undiagnosed as the diagnosis requires systolic blood pressure (SBP) ≥ 140 mmHg or diastolic blood pressure (DBP) ≥ 90 mmHg on ≥ 2 different occasions. Hypothesis: We sought to evaluate outcomes of patients without diagnosed hypertension who have elevated BP meeting current thresholds for hypertension on 2 consecutive episodes. Methods: Together with retrospective billing and clinical data, electronic records of all outpatient visits in 2009 were used to identify 24,277 patients with 2 consecutive visits (2CHBP) with SBP ≥ 140mmHg or DBP ≥ 90 mmHg and were compared with a previously identified cohort of 53,998 known hypertension patients. Among the 2CHBP group, 6,071 (25%) were identified without a prior diagnosis of hypertension and were categorized as undiagnosed hypertension. They were compared with patients with known hypertension who had ≥ 1 visit in 2009. Cross-sectional analysis of cardiovascular comorbidities and proportional hazards for survival were done. Results: Of 5,978 undiagnosed HTN patients, 49% were female compared to 51% of 10,311 known HTN. In the undiagnosed HTN group, 19.5% were ≥ 80 years compared to 30.4% of known HTN patients. Cardiovascular comorbidities were generally lower in the undiagnosed HTN group compared to the known HTN group - heart failure (7% v 8%; OR 0.88, 95% CI: 0.77 - 0.99; p < 0.038), atrial fibrillation (11% v 12%, OR 0.88 95% CI 0.79 - 0.97) and coronary artery disease (17% v 26%, OR 0.57 95% CI 0.52 - 0.61). However after a four year followup, mortality was higher in the undiagnosed HTN group with unadjusted hazard ratio HR 1.4 (95% CI 1.29 - 1.60, p<0.0001) and HR 2.41 (2.16 -2.68, p<0.0001) when adjusted for age, sex, heart failure and diabetes. Conclusions: Over a quarter of patients meeting current thresholds on 2 consecutive visits did not carry a known diagnosis of hypertension. Although younger and with less cardiovascular comorbidities than those with diagnosed hypertension, mortality after 4 years was significantly higher in those with undiagnosed hypertension. Electronic records can be used to identify these high risk patients.
Symptom identification and management in epithelial ovarian cancer.
5554 Background: A better understanding regarding the burden of treatment side effects in patients with gynecological malignancies could help guide symptom interventions and oncologic therapy decision-making. We aim to inform understanding of symptom burden in epithelial ovarian cancer (EOC) by analyzing patient-reported symptom data from patients treated for this condition over a 16-month period. Methods: Patients receiving medical oncology care at Mayo Clinic Rochester and at Midwest Mayo Clinic Health System community sites have received symptom-focused surveys prior to each medical oncology visit since March 28, 2019 through the Enhanced Electronic Health Record Facilitated Cancer Symptom Control Study (E2C2). These surveys, administered either through the electronic medical record portal or on a clinic tablet prior to each oncology office visit, no more frequently than every 2 weeks, include six linear analogue scales measuring sleep disturbance, pain, anxiety, emotional distress, and fatigue (SPADE), as well as physical dysfunction on a scale of 0 (none) to 10 (as bad as you can imagine). Scores of 0-3 were considered mild symptoms, 4-6 moderate symptoms, and 7-10 severe symptoms. We collected survey results from March 28, 2019 to July 20, 2020 for patients with EOC and reviewed the number of surveys per patient in addition to the average symptom scores. Results: From March 2019 to July 2020, for patients with EOC, there were 2974 encounter-based surveys from 762 patients. The number of surveys completed by each patient ranged from 1-20. The following number of patients returned the correlating number of surveys: 1 survey:240 patients; 2 surveys:145; 3 surveys:79; 4 surveys:56; 5 surveys:58; 6 surveys:45; 7 surveys:38; 8 surveys:27; 9 surveys:22; ≥10 surveys:52. The average score from all surveys for each symptom was: 2.41 for sleep disturbance, 2.03 for pain, 2.32 for anxiety, 1.97 for emotional distress, 3.26 for fatigue, and 2.50 for physical dysfunction. Please see the table for the proportion of surveys that reported symptoms as mild, moderate, or severe. Conclusions: Fatigue and physical dysfunction were reported most frequently in patients with EOC, while emotional distress and pain were reported least frequently. 20% of surveys reported moderate to severe emotional distress, while 40% reported moderate to severe fatigue. A targeted approach to symptom management is needed for patients undergoing EOC evaluation and treatment. Our next steps in this analysis include an assessment of potential predictors of greater symptom burden (e.g., specific treatments, age, and other clinical and sociodemographic characteristics). Clinical trial information: NCT03892967. [Table: see text]
A Yet Unrealized Promise: Structured Advance Care Planning Elements in the Electronic Health Record
Background: Electronic health records (EHRs) may help enable reliable, rapid data management for many uses, such as facilitating communication of advance care planning (ACP). However, issues with validity and accuracy of EHRs hinder the use of ACP information for practical applications. Design: We present a cross-sectional pilot study of 433 older adults with cancer from three large health care systems, participating in an ongoing multisite pragmatic trial (4UH3AG060626-02). We compared data extracted from dedicated structured EHR fields for ACP to a chart review of corresponding ACP documentation contained in the medical chart. Results: Structured ACP data existed for 43.2% of patients and varied by site (25.7% −48.9%). Of the identified structured ACP data elements, 59.2% of recorded elements were correct, 23.7% were incorrect, and 17.1% were duplicates with heterogeneity across sites. Conclusion: Structured ACP data in EHRs were frequently incorrect. This represents a problem for patients and their families, as well as quality improvement and research efforts. Clinical Trials Registration: NCT03609177.
Care Transitions Program for High‐Risk Frail Older Adults is Most Beneficial for Patients with Cognitive Impairment
BACKGROUNDAlthough posthospitalization care transitions programs (CTP) are highly diverse, their overall program thoroughness is most predictive of their success.OBJECTIVETo identify components of a successful homebased CTP and patient characteristics that are most predictive of reduced 30‐day readmissions.DESIGNRetrospective cohort.PATIENTSA total of 315 community‐dwelling, hospitalized, older adults (≥60 years) at high risk for readmission (Elder Risk Assessment score ≥16), discharged home over the period of January 1, 2011 to June 30, 2013.SETTINGMidwest primary care practice in an integrated health system.INTERVENTIONEnrollment in a CTP during acute hospitalization.MEASUREMENTSThe primary outcome was all‐cause readmission within 30 days of the first CTP evaluation. Logistic regression was used to examine independent variables, including patient demographics, comorbidities, number of medications, completion, and timing of program fidelity measures, and prior utilization of healthcare.RESULTSThe overall 30‐day readmission rate was 17.1%. The intensity of follow‐up varied among patients, with 17.1% and 50.8% of the patients requiring one and ≥3 home visits, respectively, within 30 days. More than half (54.6%) required visits beyond 30 days. Compared with patients who were not readmitted, readmitted patients were less likely to exhibit cognitive impairment (29.6% vs 46.0%; P = .03) and were more likely to have high medication use (59.3% vs 44.4%; P = .047), more emergency department (ED; 0.8 vs 0.4; P = .03) and primary care visits (4.0 vs 3.0; P = .018), and longer cumulative time in the hospital (4.6 vs 2.5 days; P = .03) within 180 days of the index hospitalization. Multivariable analysis indicated that only cognitive impairment and previous ED visits were important predictors of readmission.CONCLUSIONSNo single CTP component reliably predicted reduced readmission risk. Patients with cognitive impairment and polypharmacy derived the most benefit from the program.
Incorporating the Last Four Digits of Social Security Numbers Substantially Improves Linking Patient Data from De‐identified Hospital Claims Databases
ObjectiveAssess algorithms for linking patients across de‐identified databases without compromising confidentiality.Data Sources/Study SettingHospital discharges from 11 Mayo Clinic hospitals during January 2008–September 2012 (assessment and validation data). Minnesota death certificates and hospital discharges from 2009 to 2012 for entire state (application data).Study DesignCross‐sectional assessment of sensitivity and positive predictive value (PPV) for four linking algorithms tested by identifying readmissions and posthospital mortality on the assessment data with application to statewide data.Data Collection/Extraction MethodsDe‐identified claims included patient gender, birthdate, and zip code. Assessment records were matched with institutional sources containing unique identifiers and the last four digits of Social Security number (SSNL4).Principal FindingsGender, birthdate, and five‐digit zip code identified readmissions with a sensitivity of 98.0 percent and a PPV of 97.7 percent and identified postdischarge mortality with 84.4 percent sensitivity and 98.9 percent PPV. Inclusion of SSNL4 produced nearly perfect identification of readmissions and deaths. When applied statewide, regions bordering states with unavailable hospital discharge data had lower rates.ConclusionAddition of SSNL4 to administrative data, accompanied by appropriate data use and data release policies, can enable trusted repositories to link data with nearly perfect accuracy without compromising patient confidentiality. States maintaining centralized de‐identified databases should add SSNL4 to data specifications.
Health Care Outcomes and Advance Care Planning in Older Adults Who Receive Home-Based Palliative Care: A Pilot Cohort Study
Background: The inclusion of mental health issues in the evaluation of multimorbidity generally has been as the presence or absence of the condition rather than severity, complexity, or stage. The hypothesis for this study was that clinical outcome of the depression 6 months after enrollment into collaborative care management would have a role in predicting future complexity of care tier. Methods: This study was a retrospective chart review of 1894 primary care patients who were diagnosed with major depressive disorder or dysthymia as of December 2012. Multiple logistic regression analysis was used to test the independent associations between each variable and the odds of being included in the higher tiers (HT) group. Results: Age (odds ratio [OR] = 1.022, confidence interval [CI] = 1.013-1.030, P < .001), female gender (OR = 1.380, CI = 1.020-1.868, P = .037), being married (OR = 0.730, CI = 0.563-0.947, P = .018), and the presence of comorbidities (1, OR = 1.986, CI = 1.485-2.656, P < .001; ≥2, OR = 4.678, CI = 3.242-6.750, P < .001) were independently associated with future HT levels. The presence of persistent depressive symptoms (PHQ-9 ≥10) at 6 months conferred 2.280 (CI = 1.673-3.107, P < .001) times likely odds of HT level compared with clinical remission at 6 months. Conclusion: Patients with the diagnosis of major depression or dysthymia had greater odds of complex tier levels in the future, if depression was not treated to remission by 6 months. This study demonstrated the importance of the goal of significant improvement (ie, remission) of depression symptoms by 6 months (especially those older patients with more comorbidity) from entering into the higher complexity tiers.