Havyer, Rachel D.

Abstract Breast cancer survivorship guidelines recommend at least annual follow-up visits, yet the degree to which this occurs in clinical practice is uncertain. Claims data from a US commercial insurance database (OptumLabs) were used to identify women treated with curative intent surgery for newly diagnosed breast cancer between 2006 and 2014. In 25 035 women, median follow-up was 3 years. In the second year after surgery, 9.6% of the patients did not visit a primary care provider, an oncologist, or a surgeon (guideline-nonadherent). The guideline-nonadherent proportion increased from 7.8% in women diagnosed in 2006 to 12.2% in those diagnosed in 2014 (two-sided Wald P < .001). During years 2–6, guideline-nonadherence was also associated with older age, nonwhite race, no radiation, no chemotherapy, no endocrine therapy, and increasing time after surgery. There is a substantial and increasing rate of inadequate follow-up among breast cancer survivors. This has the potential to impair outcomes.

Family caregiver engagement in clinical encounters can promote relationship-centered care and optimize outcomes for people with Alzheimer’s disease and related dementias (ADRD). Little is known, however, about effective ways for health care providers to engage family caregivers in clinical appointments to provide the highest quality care. We describe what caregivers of people with ADRD and people with mild cognitive impairment (MCI) consider potential best practices for engaging caregivers as partners in clinical appointments. Seven online focus groups were convened. Three groups included spousal caregivers ( n = 42), three included non-spousal caregivers ( n = 36), and one included people with MCI ( n = 15). Seven potential best practices were identified, including the following: “acknowledge caregivers’ role and assess unmet needs and capacity to care” and “communicate directly with person with ADRD yet provide opportunities for caregivers to have separate interactions with providers.” Participants outlined concrete steps for providers and health care systems to improve care delivery quality for people with ADRD.

PURPOSE: We aimed to better understand how similarly patients with colorectal cancer and caregivers view care quality and to assess factors that may influence concordance. MATERIALS AND METHODS: We conducted a secondary analysis of paired patient and caregiver quality ratings of colorectal cancer care in three specific domains: surgery, chemotherapy overall, and chemotherapy nursing. Agreement was assessed with difference scores, concordance with Gwet second-order agreement statistics (AC2), and variation in agreement with stratified analyses. We examined whether the care experiences of patients and caregivers were associated with top-box (most-positive) ratings and examined variations in concordance on the basis of the presence of a top-box score. RESULTS: Four hundred seventeen patient-caregiver dyads completed the surveys. Quality-of-care ratings were positively skewed, with most dyads indicating top-box ratings. Patient and caregiver care experiences were highly associated with top-box ratings. Overall patient-caregiver concordance was very high for all three care domains (surgery: AC2, 0.87 [95% CI, 0.83 to 0.90]; chemotherapy overall: AC2, 0.84 [95% CI, 0.79 to 0.88]; chemotherapy nursing: AC2, 0.91 [95% CI, 0.87 to 0.94]). Stratified analyses of patient and caregiver characteristics did not identify any patterns that consistently affected concordance. The concordance statistic significantly decreased for all three outcomes ( P < .001), however, when the patient or caregiver assessed quality as anything other than top box. CONCLUSION: Caregiver and patient reports on care quality were highly concordant for top-box care and did not vary with patient or caregiver factors. Additional exploration is needed to identify reasons for increased variability when the quality scores were less than a top-box response.

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.

Chronic obstructive pulmonary disease (COPD) poses challenges not only in symptom management but also in prognostication. Managing COPD requires clinicians to be proficient in the primary palliative care skills of symptom management and communication focused on eliciting goals and preferences. Dyspnea should initially be managed with the combination of long-acting muscarinic antagonists and long-acting β-agonist inhalers, adding inhaled corticosteroids if symptoms persist. Opioids for the relief of dyspnea are safe when used at appropriate doses. Oxygen is only effective for relieving dyspnea in patients with severe hypoxemia. The relapsing-remitting nature of COPD makes prognostication challenging; however, there are tools to guide clinicians and patients in making plans both with respect to prognosis and symptom burden. Preparedness planning techniques promote detailed culturally appropriate conversations which allow patients and clinicians to consider disease-specific complications and develop goal-concordant treatment plans.

BACKGROUNDUpdated knowledge of the palliative care (PC) literature is needed to maintain competency and best address the PC needs of hospitalized patients. We critiqued the recent PC literature with the highest potential to impact hospital practice.METHODSWe reviewed articles published between January 2016 and December 2016, which were identified through a handsearch of leading journals and a MEDLINE search. The final 9 articles selected were determined by consensus based on scientific rigor, relevance to hospital medicine, and impact on practice.RESULTSKey findings include the following: scheduled antipsychotics were inferior to a placebo for nonterminal delirium; a low‐dose morphine was superior to a weak opioid for moderate cancer pain; methadone as a coanalgesic improved high‐intensity cancer pain; many hospitalized patients on comfort care still receive antimicrobials; video decision aids improved the rates of advance care planning (ACP) and hospice use and decreased costs; standardized, PC‐led intervention did not improve psychological outcomes in families of patients with a chronic critical illness; caregivers of patients surviving a prolonged critical illness experienced high and persistent rates of depression; people with non‐normative sexuality or gender faced additional stressors with partner loss; and physician trainees experienced significant moral distress with futile treatments.CONCLUSIONSRecent research provides important guidance for clinicians caring for hospitalized patients with serious illnesses, including symptom management, ACP, moral distress, and outcomes of critical illness.

Objectives To assess the degree to which self‐reported symptoms predict unplanned readmission or emergency department ( ED ) care within 30 days of high‐risk, elderly adults enrolled in a posthospitalization care transition program ( CTP ). Design Retrospective cohort study. Setting Posthospitalization CTP at Mayo Clinic, Rochester, Minnesota, from January 1, 2013, through March 3, 2015. Participants Frail, elderly adults (N = 230; mean age 83.5 ± 8.3, 46.5% male). Measurements Charlson Comorbidity Index ( CCI ) and self‐reported symptoms, measured using the Edmonton Symptom Assessment System ( ESAS ), were ascertained upon CTP enrollment. Results Mean CCI was 3.9 ± 2.3. Of 51 participants returning to the hospital within 30 days of discharge, 13 had ED visits, and 38 were readmitted. Age, sex, and CCI were not significantly different between returning and nonreturning participants, but returning participants were significantly more likely to report shortness of breath ( P = .004), anxiety ( P = .02), depression ( P = .02), and drowsiness ( P = .01). Overall ESAS score was also a significant predictor of hospital return ( P = .01). Conclusion Four self‐reported symptoms and overall ESAS score, but not CCI , ascertained after hospital discharge were strong predictors of hospital return within 30 days. Including symptoms in risk stratification of high‐risk elderly adults may help target interventions and reduce readmissions.

While dementia caregivers are regarded as a population with high unmet needs, there is little consensus as to how caregivers’ needs should be conceptualized and measured. This article describes how dementia caregivers’ needs are currently assessed in the scientific literature with the goal of suggesting guidelines for the enhancement of future measurement of caregiver needs. A review of 26 articles identified overarching themes within measurement approaches including variation in methodological rigor, proxy indicators of need, dual needs assessment of caregiver and person with dementia (PWD), and third-party needs assessment. We recommend future research dedicate theoretical attention to the conceptualization and classification of caregivers’ needs to build a stronger foundation for measurement. The measurement development process should capitalize on mixed-methodology and follow instrument development and validation guidelines set forth by measurement theory. Reliable and valid instruments are essential to developing services and policies that address dementia caregivers’ needs.

AbstractBackgroundThe Choosing Wisely campaign has called for better engagement of palliative and hospice care services for patients in the emergency department (ED). PREDICT is a clinical prediction tool that was derived in an Australian ED cohort. It assesses a patient's risk of mortality at 1 year to select those who would benefit from advanced care planning. Such goals‐of‐care discussion can improve patients’ ability to communicate what they want out of their healthcare and, in cases of end of life, potentially reduce the number of futile interventions. Using a cutoff of 13 points, PREDICT had a reported 95.3% specificity and 53.9% sensitivity for 1‐year mortality. We externally validated PREDICT and derived a simpler modified PREDICT tool to systematically identify high‐risk patients eligible for goals‐of‐care discussions and palliative care consultation in the ED.MethodsThis was an observational cohort study of a random sample of 927 patients aged 55+ seen in the ED in 2014. We identified advance healthcare directives (AHDs) on file. We summarized diagnostic accuracy of the clinical tool to predict 1‐year mortality using sensitivity, specificity, and area under the curve (AUC). We refined PREDICT using multivariable modeling. We followed reporting guidelines including STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) for cohort studies and Standards for Reporting of Diagnostic Accuracy (STARD).ResultsA total of 927 patients were included: 55.0% were male, 63 (7.0%) were nursing home residents, 389 (42.0%) patients had an AHD in their medical record at the time of ED visit, and 245 (26.4%) were deceased at 1 year. Of the 780 patients with PREDICT scores < 13, a total of 164 (21.0%; 95% confidence interval [CI] = 18.3–24.1) were deceased at 1 year, and of the 147 patients with PREDICT scores ≥ 13, a total of 81 (55.1%; 95% CI = 46.7–63.2) were deceased at 1 year. The AUC of the PREDICT score was 0.717 (95% CI = 0.680–0.754), sensitivity was 33.1% (95% CI = 27.3–39.4), and specificity was 90.3% (95% CI = 87.8–92.4) to predict 1‐year mortality. The modified PREDICT tool resulted in an AUC of 0.709 (95% CI = 0.671–0.747). We decided to select this model as the preferred model, as the variable of intensive care unit (ICU) admission with multiorgan failure can be difficult to assess in the ED and may delay advanced care planning. Reweighting the score did not improve fit or the AUC, so points assigned to each variable were not adjusted.ConclusionPREDICT is an easy tool to administer to be able to identify patients who are at high risk of 1‐year mortality and who could benefit from AHDs, goals‐of‐care discussion, and when appropriate in the context of an end‐of‐life setting, palliative medicine consultation. External validation of PREDICT was successful in our population. We simplified PREDICT and derived a new tool, the modified PREDICT minus ICU tool, without significantly altering the sensitivity, specificity, and AUC for death at 1 year. The next steps include external validation of the newly derived rule and prospective implementation.