Healthcare Trajectories and Outcomes in the First Year After Tracheostomy Based on Patient Characteristics.

OBJECTIVES: To define healthcare trajectories after tracheostomy to inform shared decision-making efforts for critically ill patients. DESIGN: Retrospective epidemiologic cohort study. SETTING: California Patient Discharge Database 2018-2019. PATIENTS: Patients who received a tracheostomy. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We tracked 1-year outcomes after tracheostomy, including survival and time alive in and out of a healthcare facility (HCF. Patients were stratified based on surgical status (did the patient require a major operating room procedure or not), age (65 yr old or older and less than 65 yr), pre-ICU comorbid states (frailty, chronic organ dysfunction, cancer, and robustness), and the need for dialysis during the tracheostomy admission. We identified 4,274 nonsurgical adults who received a tracheostomy during the study period with 50.9% being 65 years old or older. Among adults 65 years old or older, median survival after tracheostomy was less than 3 months for individuals with frailty, chronic organ dysfunction, cancer, or dialysis. Median survival was 3 months for adults younger than 65 years with cancer or dialysis. Most patients spent the majority of days alive after a tracheostomy in an HCF in the first 3 months. Older adults had very few days alive and out of an HCF in the first 3 months after tracheostomy. Most patients who ultimately died in the first year after tracheostomy spent almost all days alive in an HCF. CONCLUSIONS: Cumulative mortality and median survival after a tracheostomy were very poor across most ages and groups. Older adults and several subgroups of younger adults experienced high rates of prolonged hospitalization with few days alive and out of an HCF. This information may aid some patients, surrogates, and providers in decision-making.

Association of Proximity to a Long-Term Acute Care Hospital With Hospital Tracheostomy Practices.

OBJECTIVES: Availability of long-term acute care hospitals has been associated with hospital discharge practices. It is unclear if long-term acute care hospital availability can influence patient care decisions. We sought to determine the association of long-term acute care hospital availability at different hospitals with the likelihood of tracheostomy. DESIGN: Retrospective cohort study. SETTING: California Patient Discharge Database, 2016-2018. PATIENTS: Adult patients receiving mechanical ventilation for respiratory failure. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Using the California Patient Discharge Database 2016-2018, we identified all mechanically ventilated patients and those who received tracheostomy. We determine the association between tracheostomy and the distance between each hospital and the nearest long-term acute care hospital and the number of long-term acute care hospital beds within 20 miles of each hospital. Among 281,502 hospitalizations where a patient received mechanical ventilation, 22,899 (8.1%) received a tracheostomy. Patients admitted to a hospital closer to a long-term acute care hospital compared with those furthest from a long-term acute care hospital had 38.9% (95% CI, 33.3-44.6%) higher odds of tracheostomy (closest hospitals 8.7% vs furthest hospitals 6.3%, adjusted odds ratio = 1.65; 95% CI, 1.40-1.95). Patients had a 32.4% (95% CI, 27.6-37.3%) higher risk of tracheostomy when admitted to a hospital with more long-term acute care hospital beds in the immediate vicinity (most long-term acute care hospital beds within 20 miles 8.9% vs fewest long-term acute care hospital beds 6.7%, adjusted odds ratio = 1.54; 95% CI, 1.31-1.80). Distance to the nearest long-term acute care hospital was inversely correlated with hospital risk-adjusted tracheostomy rates (ρ = -0.25; p < 0.0001). The number of long-term acute care hospital beds within 20 miles was positively correlated with hospital risk-adjusted tracheostomy rates (ρ = 0.22; p < 0.0001). CONCLUSIONS: Proximity and availability of long-term acute care hospital beds were associated with patient odds of tracheostomy and hospital tracheostomy practices. These findings suggest a hospital effect on tracheostomy decision-making over and above patient case-mix. Future studies focusing on shared decision-making for tracheostomy are needed to ensure goal-concordant care for prolonged mechanical ventilation.

Stability of Do-Not-Resuscitate Orders in Hospitalized Adults: A Population-Based Cohort Study.

OBJECTIVES: Prior work has shown substantial between-hospital variation in do-not-resuscitate orders, but stability of do-not-resuscitate preferences between hospitalizations and the institutional influence on do-not-resuscitate reversals are unclear. We determined the extent of do-not-resuscitate reversals between hospitalizations and the association of the readmission hospital with do-not-resuscitate reversal. DESIGN: Retrospective cohort study. SETTING: California Patient Discharge Database, 2016-2018. PATIENTS: Nonsurgical patients admitted to an acute care hospital with an early do-not-resuscitate order (within 24 hr of admission). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We identified nonsurgical adult patients who survived an initial hospitalization with an early-do-not-resuscitate order and were readmitted within 30 days. The primary outcome was the association of do-not-resuscitate reversal with readmission to the same or different hospital from the initial hospital. Secondary outcomes included association of readmission to a low versus high do-not-resuscitate-rate hospital with do-not-resuscitate reversal. Among 49,336 patients readmitted within 30 days following a first do-not-resuscitate hospitalization, 22,251 (45.1%) experienced do-not-resuscitate reversal upon readmission. Patients readmitted to a different hospital versus the same hospital were at higher risk of do-not-resuscitate reversal (59.5% vs 38.5%; p < 0.001; adjusted odds ratio = 2.4; 95% CI, 2.3-2.5). Patients readmitted to low versus high do-not-resuscitate-rate hospitals were more likely to have do-not-resuscitate reversals (do-not-resuscitate-rate quartile 1 77.0% vs quartile 4 27.2%; p < 0.001; adjusted odds ratio = 11.9; 95% CI, 10.7-13.2). When readmitted to a different versus the same hospital, patients with do-not-resuscitate reversal had higher rates of mechanical ventilation (adjusted odds ratio = 1.9; 95% CI, 1.6-2.1) and hospital death (adjusted odds ratio = 1.2; 95% CI, 1.1-1.3). CONCLUSIONS: Do-not-resuscitate reversals at the time of readmission are more common than previously reported. Although changes in patient preferences may partially explain between-hospital differences, we observed a strong hospital effect contributing to high do-not-resuscitate-reversal rates with significant implications for patient outcomes and resource.

An Electronically delivered, Patient-activation tool for Intensification of medications for Chronic Heart Failure with reduced ejection fraction: Rationale and design of the EPIC-HF trial.

BACKGROUND: Heart failure with reduced ejection fraction (HFrEF) benefits from initiation and intensification of multiple pharmacotherapies. Unfortunately, there are major gaps in the routine use of these drugs. Without novel approaches to improve prescribing, the cumulative benefits of HFrEF treatment will be largely unrealized. Direct-to-consumer marketing and shared decision making reflect a culture where patients are increasingly involved in treatment choices, creating opportunities for prescribing interventions that engage patients. HYPOTHESIS: Encouraging patients to engage providers in HFrEF prescribing decisions will improve the use of guideline-directed medical therapies. DESIGN: The Electronically delivered, Patient-activation tool for Intensification of Chronic medications for Heart Failure with reduced ejection fraction (EPIC-HF) trial randomizes patients with HFrEF to usual care versus patient-activation tools-a 3-minute video and 1-page checklist-delivered prior to cardiology clinic visits that encourage patients to work collaboratively with their clinicians to intensify HFrEF prescribing. The study assesses the effectiveness of the EPIC-HF intervention to improve guideline-directed medical therapy in the month after its delivery while using an implementation design to also understand the reach, adoption, implementation, and maintenance of this approach within the context of real-world care delivery. Study enrollment was completed in January 2020, with a total 305 patients. Baseline data revealed significant opportunities, with <1% of patients on optimal HFrEF medical therapy. SUMMARY: The EPIC-HF trial assesses the implementation, effectiveness, and safety of patient engagement in HFrEF prescribing decisions. If successful, the tool can be easily disseminated and may inform similar interventions for other chronic conditions.

A multicenter trial of a shared DECision Support Intervention for Patients offered implantable Cardioverter-DEfibrillators: DECIDE-ICD rationale, design, Medicare changes, and pilot data.

Shared decision making (SDM) facilitates delivery of medical therapies that are in alignment with patients' goals and values. Medicare national coverage decision for several interventions now includes SDM mandates, but few have been evaluated in nationwide studies. Based upon a detailed needs assessment with diverse stakeholders, we developed pamphlet and video patient decision aids (PtDAs) for implantable cardioverter/defibrillator (ICD) implantation, ICD replacement, and cardiac resynchronization therapy with defibrillation to help patients contemplate, forecast, and deliberate their options. These PtDAs are the foundation of the Multicenter Trial of a Shared Decision Support Intervention for Patients Offered Implantable Cardioverter-Defibrillators (DECIDE-ICD), a multicenter, randomized trial sponsored by the National Heart, Lung, and Blood Institute aimed at understanding the effectiveness and implementation of an SDM support intervention for patients considering ICDs. Finalization of a Medicare coverage decision mandating the inclusion of SDM for new ICD implantation occurred shortly after trial initiation, raising novel practical and statistical considerations for evaluating study end points. METHODS/DESIGN: A stepped-wedge randomized controlled trial was designed, guided by the RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) planning and evaluation framework using an effectiveness-implementation hybrid type II design. Six electrophysiology programs from across the United States will participate. The primary effectiveness outcome is decision quality (defined by knowledge and values-treatment concordance). Patients with heart failure who are clinically eligible for an ICD are eligible for the study. Target enrollment is 900 participants. DISCUSSION: Study findings will provide a foundation for implementing decision support interventions, including PtDAs, with patients who have chronic progressive illness and are facing decisions involving invasive, preference-sensitive therapy options.

Perceived Stress and Depressive Symptoms as Predictors of Decisional Conflict in Dyads Considering a Left Ventricular Assist Device.

BACKGROUND: The decision to pursue a left ventricular assist device (LVAD) commits loved ones to major caregiving responsibilities and, often, medical decision-making. How emotional domains overlap within patients and their caregivers and contribute to conflict around the decision to pursue LVAD remains largely unexplored. METHODS AND RESULTS: The associations within and between individuals in patient-caregiver dyads considering LVAD were estimated in a specific type of structural equation model known as the Actor-Partner Interdependence Model. This model tested whether each person's depression and stress predicted their own decisional conflict (actor effects), as well as their partner's decisional conflict (partner effects). At the time of study enrollment when a formal LVAD evaluation was initiated, 162 patient-caregiver dyads completed assessments of decisional conflict using the Decisional Conflict Scale, depressive symptoms using the Patient Health Questionnaire-2, and stress using the Perceived Stress Scale. Across both models, decisional conflict was significantly correlated within patient-caregiver dyads (ß=0.47 and 0.44, for depression and perceived stress models, respectively, P<0.001). Greater perceived stress in both the patient (ß=0.18; P<0.05) and caregiver (ß=0.28; P<0.001) was significantly related to greater decisional conflict (both actor effects). Greater patient depressive symptoms were related to greater patient decisional conflict (ß=0.16; P<0.05), whereas caregiver depression symptoms was not related to their own decisional conflict (ß=0.07; P=0.37). There were no partner effects identified between decisional conflict and perceived stress or depressive symptoms. CONCLUSIONS: Patient and caregiver conflict over the decision to pursue an LVAD was highly correlated in this sample, with greater perceived stress significantly predicting greater decisional conflict in both patients and caregivers. Depressive symptoms in patients also predicted greater patient decisional conflict. No partner effects were identified in predicting decisional conflict. These results contribute to a larger body of work acknowledging the importance of patient-caregiver well-being in serious illness. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02344576.

Decision-Making About Intracranial Pressure Monitor Placement in Children With Traumatic Brain Injury.

OBJECTIVES: Little is known about how clinicians make the complex decision regarding whether to place an intracranial pressure monitor in children with traumatic brain injury. The objective of this study was to identify the decisional needs of multidisciplinary clinician stakeholders. DESIGN: Semi-structured qualitative interviews with clinicians who regularly care for children with traumatic brain injury. SETTING: One U.S. level I pediatric trauma center. SUBJECTS: Twenty-eight clinicians including 17 ICU nurses, advanced practice providers, and physicians and 11 pediatric surgeons and neurosurgeons interviewed between August 2017 and February 2018. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Participants had a mean age of 43 years (range, 30-66 yr), mean experience of 10 years (range, 0-30 yr), were 46% female (13/28), and 96% white (27/28). A novel conceptual model emerged that related the difficulty of the decision about intracranial pressure monitor placement (y-axis) with the estimated outcome of the patient (x-axis). This model had a bimodal shape, with the most difficult decisions occurring for patients who 1) had a good opportunity for recovery but whose neurologic examination had not yet normalized or 2) had a low but uncertain likelihood of neurologically functional recovery. Emergent themes included gaps in medical knowledge and information available for decision-making, differences in perspective between clinical specialties, and ethical implications of decision-making about intracranial pressure monitoring. Experienced clinicians described less difficulty with decision-making overall. CONCLUSIONS: Children with severe traumatic brain injury near perceived transition points along a spectrum of potential for recovery present challenges for decision-making about intracranial pressure monitor placement. Clinician experience and specialty discipline further influence decision-making. These findings will contribute to the design of a multidisciplinary clinical decision support tool for intracranial pressure monitor placement in children with traumatic brain injury.

Hospital Mechanical Ventilation Volume and Patient Outcomes: Too Much of a Good Thing?

OBJECTIVES: Prior studies investigating hospital mechanical ventilation volume-outcome associations have had conflicting findings. Volume-outcome relationships within contemporary mechanical ventilation practices are unclear. We sought to determine associations between hospital mechanical ventilation volume and patient outcomes. DESIGN: Retrospective cohort study. SETTING: The California Patient Discharge Database 2016. PATIENTS: Adult nonsurgical patients receiving mechanical ventilation. INTERVENTIONS: The primary outcome was hospital death with secondary outcomes of tracheostomy and 30-day readmission. We used multivariable generalized estimating equations to determine the association between patient outcomes and hospital mechanical ventilation volume quartile. MEASUREMENTS AND MAIN RESULTS: We identified 51,689 patients across 274 hospitals who required mechanical ventilation in California in 2016. 38.2% of patients died in the hospital with 4.4% receiving a tracheostomy. Among survivors, 29.5% required readmission within 30 days of discharge. Patients admitted to high versus low volume hospitals had higher odds of death (quartile 4 vs quartile 1 adjusted odds ratio, 1.40; 95% CI, 1.17-1.68) and tracheostomy (quartile 4 vs quartile 1 adjusted odds ratio, 1.58; 95% CI, 1.21-2.06). However, odds of 30-day readmission among survivors was lower at high versus low volume hospitals (quartile 4 vs quartile 1 adjusted odds ratio, 0.77; 95% CI, 0.67-0.89). Higher hospital mechanical ventilation volume was weakly correlated with higher hospital risk-adjusted mortality rates (ρ = 0.16; p = 0.008). These moderately strong observations were supported by multiple sensitivity analyses. CONCLUSIONS: Contrary to previous studies, we observed worse patient outcomes at higher mechanical ventilation volume hospitals. In the setting of increasing use of mechanical ventilation and changes in mechanical ventilation practices, multiple mechanisms of worse outcomes including resource strain are possible. Future studies investigating differences in processes of care between high and low volume hospitals are necessary.

Variation in Management of Patients With Obstructive Coronary Artery Disease: Insights From the Veterans Affairs Clinical Assessment and Reporting Tool (VA CART) Program.

BACKGROUND: Little is known about facility-level variation in the use of revascularization procedures for the management of stable obstructive coronary artery disease. Furthermore, it is unknown if variation in the use of coronary revascularization is associated with use of other cardiovascular procedures. METHODS AND RESULTS: We evaluated all elective coronary angiograms performed in the Veterans Affairs system between September 1, 2007, and December 31, 2011, using the Clinical Assessment and Reporting Tool and identified patients with obstructive coronary artery disease. Patients were considered managed with revascularization if they received percutaneous coronary intervention (PCI) or coronary artery bypass grafting within 30 days of diagnosis. We calculated risk-adjusted facility-level rates of overall revascularization, PCI, and coronary artery bypass grafting. In addition, we determined the association between facility-level rates of revascularization and post-PCI stress testing. Among 15 650 patients at 51 Veterans Affairs sites who met inclusion criteria, the median rate of revascularization was 59.6% (interquartile range, 55.7%-66.7%). Across all facilities, risk-adjusted rates of overall revascularization varied from 41.5% to 88.1%, rate of PCI varied from 23.2% to 80.6%, and rate of coronary artery bypass graftingvariedfrom 7.5% to 36.5%. Of 6179 patients who underwent elective PCI, the median rate of stress testing in the 2 years after PCI was 33.7% (interquartile range, 30.7%-47.1%). There was no evidence of correlation between facility-level rate of revascularization and follow-up stress testing. CONCLUSIONS: Within the Veterans Affairs system, we observed large facility-level variation in rates of revascularization for obstructive coronary artery disease, with variation driven primarily by PCI. There was no association between facility-level use of revascularization and follow-up stress testing, suggesting use rates are specific to a particular procedure and not a marker of overall facility-level use.