Real-World Implications of Updated Surviving Sepsis Campaign Antibiotic Timing Recommendations.

OBJECTIVE: To evaluate real-world implications of updated Surviving Sepsis Campaign (SSC) recommendations for antibiotic timing. DESIGN: Retrospective cohort study. SETTING: Twelve hospitals in the Southeastern United States between 2017 and 2021. PATIENTS: One hundred sixty-six thousand five hundred fifty-nine adult hospitalized patients treated in the emergency department for suspected serious infection. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We determined the number and characteristics of patients affected by updated SSC recommendations for initiation of antibiotics that incorporate a risk- and probability-stratified approach. Using an infection prediction model with a cutoff of 0.5 to classify possible vs. probable infection, we found that 30% of the suspected infection cohort would be classified as shock absent, possible infection and thus eligible for the new 3-hour antibiotic recommendation. In real-world practice, this group had a conservative time to antibiotics (median, 5.5 hr; interquartile range [IQR], 3.2-9.8 hr) and low mortality (2%). Patients categorized as shock absent, probable infection had a median time to antibiotics of 3.2 hours (IQR, 2.1-5.1 hr) and mortality of 3%. Patients categorized as shock present, the probable infection had a median time to antibiotics 2.7 hours (IQR, 1.7-4.6 hr) and mortality of 17%, and patients categorized as shock present, the possible infection had a median time to antibiotics 6.9 hours (IQR, 3.5-16.3 hr) and mortality of 12%. CONCLUSIONS: These data support recently updated SSC recommendations to align antibiotic timing targets with risk and probability stratifications. Our results provide empirical support that clinicians and hospitals should not be held to 1-hour targets for patients without shock and with only possible sepsis.

Characterizing Program Delivery for an Effective Multicomponent Sepsis Recovery Intervention.

Rationale: A recent randomized controlled trial revealed that a multicomponent sepsis transition and recovery (STAR) program delivered through specialized nurse navigators was effective in reducing a composite of 30-day readmission and mortality. Better understanding of patterns of care provided by the STAR program is needed to promote implementation and dissemination of this effective program.Objectives: This study characterizes individual care activities and distinct "packages" of care delivered by the STAR program.Methods: We performed a secondary analysis of data from the intervention arm of the IMPACTS (Improving Morbidity during Post-Acute Care Transitions for Sepsis) randomized controlled trial, conducted at three urban hospitals in the southeastern United States from January 2019 to March 2020. We used a structured data collection process to identify STAR nurse navigator care activities from electronic health record documentation. We then used latent class analysis to identify groups of patients receiving distinct combinations of intervention components. We evaluated differences in patient characteristics and outcomes between groups receiving distinct intervention packages.Results: The 317 sepsis survivors enrolled into the intervention arm of the IMPACTS trial received one or more of nine unique care activities delivered by STAR nurse navigators (care coordination, health promotion counseling, emotional listening, symptom management, medication management, chronic disease management, addressing social determinants of health, care setting advice and guidance, and primary palliative care). Patients received a median of three individual care activities (interquartile range, 2-5). Latent class analysis revealed four distinct packages of care activities delivered to patients with different observable characteristics and different frequency of 30-day readmission and mortality.Conclusions: We identified nine care activities delivered by an effective STAR program and four distinct latent classes or packages of intervention delivery. These results can be leveraged to increase widespread implementation and provide targets to augment future program delivery.

Automated generation of comparator patients in the electronic medical record.

Background: Well-designed randomized trials provide high-quality clinical evidence but are not always feasible or ethical. In their absence, the electronic medical record (EMR) presents a platform to conduct comparative effectiveness research, central to the emerging academic learning health system (aLHS) model. A barrier to realizing this vision is the lack of a process to efficiently generate a reference comparison group for each patient. Objective: To test a multi-step process for the selection of comparators in the EMR. Materials and Methods: We conducted a mixed-methods study within a large aLHS in North Carolina. We (1) created a list of 35 candidate variables; (2) surveyed 270 researchers to assess the importance of candidate variables; and (3) built consensus rankings around survey-identified variables (ie, importance scores >7) across two panels of 7-8 clinical research experts. Prioritized algorithm inputs were collected from the EMR and applied using a greedy matching technique. Feasibility was measured as the percentage of patients with 100 matched comparators and performance was measured via computational time and Euclidean distance. Results: Nine variables were selected: age, sex, race, ethnicity, body mass index, insurance status, smoking status, Charlson Comorbidity Index, and neighborhood percentage in poverty. The final process successfully generated 100 matched comparators for each of 1.8 million candidate patients, executed in less than 100 min for the majority of strata, and had average Euclidean distance 0.043. Conclusion: EMR-derived matching is feasible to implement across a diverse patient population and can provide a reproducible, efficient source of comparator data for observational studies, with additional testing in clinical research applications needed.

Passing the SNF Test: A Secondary Analysis of a Sepsis Transition Intervention Trial Among Patients Discharged to Post-Acute Care.

OBJECTIVES: Sepsis survivors discharged to post-acute care facilities experience high rates of mortality and hospital readmission. This study compared the effects of a Sepsis Transition and Recovery (STAR) program vs usual care (UC) on 30-day mortality and hospital readmission among sepsis survivors discharged to post-acute care. DESIGN: Secondary analysis of a multisite pragmatic randomized clinical trial. SETTING AND PARTICIPANTS: Sepsis survivors discharged to post-acute care. METHODS: We conducted a secondary analysis of patients from the IMPACTS (Improving Morbidity During Post-Acute Care Transitions for Sepsis) randomized clinical trial who were discharged to post-acute care. IMPACTS evaluated the effectiveness of STAR, a nurse-navigator-led program to deliver best practice post-sepsis care. Subjects were randomized to receive either STAR or UC. The primary outcome was 30-day readmission and mortality. We also evaluated hospital-free days alive as a secondary outcome. RESULTS: Of 691 patients enrolled in IMPACTS, 175 (25%) were discharged to post-acute care [143 (82%) to skilled nursing facilities, 12 (7%) to long-term acute care hospitals, and 20 (11%) to inpatient rehabilitation]. Of these, 87 received UC and 88 received the STAR intervention. The composite 30-day all-cause mortality and readmission endpoint occurred in 26 (29.9%) patients in the UC group vs 18 (20.5%) in the STAR group [risk difference -9.4% (95% CI -22.2 to 3.4); adjusted odds ratio 0.58 (95% CI 0.28 to 1.17)]. Separately, 30-day all-cause mortality was 8.1% in the UC group compared with 5.7% in the STAR group [risk difference -2.4% (95% CI -9.9 to 5.1)] and 30-day all-cause readmission was 26.4% in the UC group compared with 17.1% in the STAR program [risk difference -9.4% (95% CI -21.5 to 2.8)]. CONCLUSIONS AND IMPLICATIONS: There are few proven interventions to reduce readmission among patients discharged to post-acute care facilities. These results suggest the STAR program may reduce 30-day mortality and readmission rates among sepsis survivors discharged to post-acute care facilities.

Evaluating Racial/Ethnic Differences in Care Escalation Among COVID-19 Patients in a Home-Based Hospital.

The novel coronavirus disease 2019 (COVID-19) has infected over 414 million people worldwide with 5.8 million deaths, as of February 2022. Telemedicine-based interventions to expand healthcare systems' capacity and reduce infection risk have rapidly increased during the pandemic, despite concerns regarding equitable access. Atrium Health Hospital at Home (AH-HaH) is a home-based program that provides advanced, hospital-level medical care and monitoring for patients who would otherwise be hospitalized in a traditional setting. Our retrospective cohort study of positive COVID-19 patients who were admitted to AH-HaH aims to investigate whether the rate of care escalation from AH-HaH to traditional hospitalization differed based on patients' racial/ethnic backgrounds. Logistic regression was used to examine the association between care escalation within 14 days from index AH-HaH admission and race/ethnicity. We found approximately one in five patients receiving care for COVID-19 in AH-HaH required care escalation within 14 days. Odds of care escalation were not significantly different for Hispanic or non-Hispanic Blacks compared to non-Hispanic Whites. However, secondary analyses showed that both Hispanic and non-Hispanic Black patients were younger and with fewer comorbidities than non-Hispanic Whites. The study highlights the need for new care models to vigilantly monitor for disparities, so that timely and tailored adaptations can be implemented for vulnerable populations.

A multimodal intervention to decrease inappropriate outpatient antibiotic prescribing for upper respiratory tract infections in a large integrated healthcare system.

OBJECTIVE: To evaluate the effectiveness of Carolinas Healthcare Outpatient Antimicrobial Stewardship Empowerment Network (CHOSEN), a multicomponent outpatient stewardship program to reduce inappropriate antibiotic prescribing for upper respiratory infections by 20% over 2 years. DESIGN: Before-and-after interrupted time series of antibiotics prescribed between 2 periods: April 2016-October 2017 and May 2018-March 2020. SETTING: The study included 162 primary-care practices within a large healthcare system in the greater Charlotte, North Carolina region. PARTICIPANTS: Adult and pediatric patients with encounters for upper respiratory infections for which an antibiotic is inappropriate. METHODS: Patient and provider educational materials, along with a web-based provider prescribing dashboard aimed at reducing inappropriate antibiotic prescribing were developed and distributed. Monthly antibiotic prescribing rates were calculated as the number of eligible encounters with an antibiotic prescribed divided by the total number of eligible encounters. A segmented regression analysis compared monthly antibiotic prescribing rates before versus after CHOSEN implementation, while also accounting for practice type and seasonal trends in prescribing. RESULTS: Overall, 286,580 antibiotics were prescribed during 704,248 preintervention encounters and 277,177 during 832,200 intervention encounters. Significant reductions in inappropriate prescribing rates were observed in all outpatient specialties: family medicine (relative difference before and after the intervention, -20.4%), internal medicine (-19.5%), pediatric medicine (-17.2%), and urgent care (-16.6%). CONCLUSIONS: A robust multimodal intervention that combined a provider prescribing dashboard with a targeted education campaign demonstrated significant decreases in inappropriate outpatient antibiotic prescribing for upper respiratory tract infections in a large integrated ambulatory network.

A Quantitative Study of Decision Thresholds for Initiation of Antibiotics in Suspected Sepsis.

BACKGROUND: Clinicians' decision thresholds for initiating antibiotics in patients with suspected sepsis have not been quantified. We aimed to define an average threshold of infection likelihood at which clinicians initiate antibiotics when treating a patient with suspected infection and to evaluate the influence of severity of illness and clinician-related factors on the threshold. DESIGN: This was a prospective survey of 153 clinicians responding to 8 clinical vignettes constructed from real-world data from 3 health care systems in the United States. We treated each hour in the vignette as a decision to treat or not treat with antibiotics and assigned an infection probability to each hour using a previously developed infection prediction model. We then estimated decision thresholds using regression models based on the timing of antibiotic initiation. We compared thresholds across categories of severity of illness and clinician-related factors. RESULTS: Overall, the treatment threshold occurred at a 69% probability of infection, but the threshold varied significantly across severity of illness categories-when patients had high severity of illness, the treatment threshold occurred at a 55% probability of infection; when patients had intermediate severity, the threshold for antibiotic initiation occurred at an infection probability of 69%, and the threshold was 84% when patients had low severity of illness (P < 0.001 for group differences). Thresholds differed significantly across specialty, highest among infectious disease and lowest among emergency medicine clinicians and across years of experience, decreasing with increasing years of experience. CONCLUSIONS: The threshold infection probability above which physicians choose to initiate antibiotics in suspected sepsis depends on illness severity as well as clinician factors. IMPLICATIONS: Incorporating these context-dependent thresholds into discriminating and well-calibrated models will inform the development of future sepsis clinical decision support systems. Clinician-related differences in treatment thresholds suggests potential unwarranted variation and opportunities for performance improvement. HIGHLIGHTS: Decision making about antibiotic initiation in suspected sepsis occurs under uncertainty, and little is known about clinicians' thresholds for treatment.In this prospective study, 153 clinicians from 3 health care systems reviewed 8 real-world clinical vignettes representing patients with sepsis and indicated the time that they would initiate antibiotics.Using a model-based approach, we estimated decision thresholds and found that thresholds differed significantly across illness severity categories and by clinician specialty and years of experience.

A Retrospective Evaluation of the Impacts of a Multidisciplinary Care Model for Managing Patients with Advanced Illness on Acute Care Utilization and Quality of Care at End of Life.

Background: A home-based goal-concordant care model targeting patients with advanced illnesses may reduce acute care utilization and improve quality outcomes at end of life. Aim: Study aim was to determine impact of the Advanced Illness Management (AIM) program on end-of-life utilization and quality of care. Design: A retrospective observational study design using propensity score fine stratum weighting methodologies was applied to decedent patients identified for AIM enrollment/eligibility in 2018 to 2019. Setting/Participants: A total of 3859 decedents, 216 of whom were AIM enrollees, were identified from a metropolitan health system's electronic medical records (EMR) and met study eligibility criteria. Results: Compared with usual care, AIM enrollees spent more days away from acute care in the last 30, 90, and 180 days of life. Furthermore, AIM enrollees were less likely to expire in an acute care hospital. Conclusions: Enrollment in programs such as AIM should be considered for patients with advanced illnesses approaching end of life.

The physiology of failure: Identifying risk factors for mortality in emergency general surgery patients using a regional health system integrated electronic medical record.

BACKGROUND: Emergency general surgery (EGS) patients have increased mortality risk compared with elective counterparts. Recent studies on risk factors have largely used national data sets limited to administrative data. Our aim was to examine risk factors in an integrated regional health system EGS database, including clinical and administrative data, hypothesizing that this novel process would identify clinical variables as important risk factors for mortality. METHODS: Our nine-hospital health system's billing data were queried for EGS International Classification of Disease codes between 2013 and 2018. Codes were grouped by diagnosis, and urgent or emergent encounters were included and merged with electronic medical record clinical data. Outcomes assessed were inpatient and 1-year mortality. Standard and multivariable statistics evaluated factors associated with mortality. RESULTS: There were 253,331 EGS admissions with 3.6% inpatient mortality rate. Patients who suffered inpatient and 1-year mortality were older, more likely to be underweight, and have neutropenia or elevated lactate. On multivariable analysis for inpatient mortality: age (odds ratio [OR], 1.7-6.7), underweight body mass index (OR, 1.6), transfer admission (OR, 1.8), leukopenia (OR, 2.0), elevated lactate (OR, 1.8), and ventilator requirement (OR, 7.1) remained associated with increased risk. Adjusted analysis for 1-year mortality demonstrated similar findings, with highest risk associated with older age (OR, 2.8-14.6), underweight body mass index (OR, 2.3), neutropenia (OR, 2.0), and tachycardia (OR, 1.7). CONCLUSION: After controlling for patient and disease characteristics available in administrative databases, clinical variables remained significantly associated with mortality. This novel yet simple process allows for easy identification of clinical data points imperative to the study of EGS diagnoses that are critical in understanding factors that impact mortality. LEVEL OF EVIDENCE: Prognostic and Epidemiologic; Level III.

The Assessment of Social Determinants of Health in Postsepsis Mortality and Readmission: A Scoping Review.

To summarize knowledge and identify gaps in evidence about the relationship between social determinants of health (SDH) and postsepsis outcomes. DATA SOURCES: We conducted a comprehensive search of PubMed/Medical Literature Analysis and Retrieval System Online, Excerpta Medica database, and the Cochrane Library. STUDY SELECTION: We identified articles that evaluated SDH as risk factors for mortality or readmission after sepsis hospitalization. Two authors independently screened and selected articles for inclusion. DATA EXTRACTION: We dual-extracted study characteristics with specific focus on measurement, reporting, and interpretation of SDH variables. DATA SYNTHESIS: Of 2,077 articles screened, 103 articles assessed risk factors for postsepsis mortality or readmission. Of these, 28 (27%) included at least one SDH variable. Inclusion of SDH in studies assessing postsepsis adverse outcomes increased over time. The most common SDH evaluated was race/ethnicity (n = 21, 75%), followed by payer type (n = 10, 36%), and income/wealth (n = 9, 32%). Of the studies including race/ethnicity, nine (32%) evaluated no other SDH. Only one study including race/ethnicity discussed the use of this variable as a surrogate for social disadvantage, and none specifically discussed structural racism. None of the studies specifically addressed methods to validate the accuracy of SDH or handling of missing data. Eight (29%) studies included a general statement that missing data were infrequent. Several studies reported independent associations between SDH and outcomes after sepsis discharge; however, these findings were mixed across studies. CONCLUSIONS: Our review suggests that SDH data are underutilized and of uncertain quality in studies evaluating postsepsis adverse events. Transparent and explicit ontogenesis and data models for SDH data are urgently needed to support research and clinical applications with specific attention to advancing our understanding of the role racism and racial health inequities in postsepsis outcomes.

Clinical Subtypes of Sepsis Survivors Predict Readmission and Mortality after Hospital Discharge.

Rationale: Sepsis survivors experience adverse outcomes including high rates of postdischarge mortality and rehospitalization. Given the heterogeneity of the condition, using a person-centered framework to identify subtypes within this population with different risks of postdischarge outcomes may optimize postsepsis care. Objectives: To classify individuals into subtypes and assess the association of subtypes with 30-day rehospitalization and mortality. Methods: We conducted a retrospective observational study between January 2014 and October 2017 among 20,745 patients admitted to one of 12 southeastern U.S. hospitals with a clinical definition of sepsis. We used latent class analysis to classify sepsis survivors into subtypes, which were evaluated against 30-day readmission and mortality rates using a specialized regression approach. A secondary analysis evaluated subtypes against readmission rate for ambulatory care-sensitive conditions. Results: Among 20,745 patients, latent class analysis identified five distinct subtypes as the optimal solution. Clinical subtype was associated with 30-day readmission, with the subtype existing poor health with severe illness and complex needs after discharge demonstrating highest risk (35%) and the subtype low risk, barriers to care demonstrating the lowest risk (9%). Forty-seven percent of readmissions in the subtype poor functional status were for ambulatory care-sensitive conditions, whereas 17% of readmissions in the subtype previously healthy with severe illness and complex needs after discharge, barriers to care were for ambulatory care-sensitive conditions. Subtype was significantly associated with 30-day mortality: highest in for existing poor health with severe illness and complex needs after discharge (8%) and lowest for low risk, barriers to care (0.1%). Conclusions: Sepsis survivors can be classified into subtypes representing nuanced constellations of characteristics, with differential 30-day mortality and readmission risk profiles. Predischarge classification may allow an individualized approach to postsepsis care.

Effect of a Multicomponent Sepsis Transition and Recovery Program on Mortality and Readmissions After Sepsis: The Improving Morbidity During Post-Acute Care Transitions for Sepsis Randomized Clinical Trial.

OBJECTIVES: To evaluate whether a nurse navigator-led, multicomponent Sepsis Transition And Recovery program improves 30-day mortality and readmission outcomes after sepsis hospitalization. DESIG: n: Multisite pragmatic randomized clinical trial. SETTING: Three hospitals in North Carolina from January 2019 to March 2020. PATIENTS: Eligible patients hospitalized for suspected sepsis and deemed high-risk for mortality or readmission by validated internal risk models. INTERVENTIONS: Patients were randomized to receive usual care alone (i.e., routine transition support, outpatient care; n = 342) or additional Sepsis Transition And Recovery support (n = 349). The 30-day intervention involved a multicomponent transition service led by a nurse navigator through telephone and electronic health record communication to facilitate best practice postsepsis care strategies during and after hospitalization including: postdischarge medication review, evaluation for new impairments or symptoms, monitoring comorbidities, and palliative care approach when appropriate. Clinical oversight was provided by a Hospital Medicine Transition Services team. MEASUREMENTS AND MAIN RESULTS: The primary outcome was a composite of mortality or hospital readmission at 30 days. Logistic regression models were constructed to evaluate marginal and conditional odds ratios (adjusted for prognostic covariates: age, comorbidity, and organ dysfunction at enrollment). Among 691 randomized patients (mean age = 63.7 ± 15.1 yr; 52% female), a lower percentage of patients in the Sepsis Transition And Recovery group experienced the primary outcome compared with the usual care group (28.7% vs 33.3%; risk difference, 4.7%; odds ratio, 0.80; 95% CI, 0.58-1.11; adjusted odds ratio, 0.80; 95% CI, 0.64-0.98). There were 74 deaths (Sepsis Transition And Recovery: 33 [9.5%] vs usual care: 41 [12.0%]) and 155 rehospitalizations (Sepsis Transition And Recovery: 71 [20.3%] vs usual care: 84 [24.6%]). CONCLUSIONS: In a multisite randomized clinical trial of patients hospitalized with sepsis, patients provided with a 30-day program using a nurse navigator to provide best practices for postsepsis care experienced a lower proportion of either mortality or rehospitalization within 30 days after discharge. Further research is needed to understand the contextual factors associated with successful implementation.

Laparoscopy is associated with decreased all-cause mortality in patients undergoing emergency general surgery procedures in a regional health system.

BACKGROUND: The aim of this study was to evaluate the use of laparoscopic surgery for common emergency general surgery (EGS) procedures within an integrated Acute Care Surgery (ACS) network. We hypothesized that laparoscopy would be associated with improved outcomes. METHODS: Our integrated health care system's EGS registry created from AAST EGS ICD-9 codes was queried from January 2013 to October 2015. Procedures were grouped as laparoscopic or open. Standard descriptive and univariate tests were performed, and a multivariable logistic regression controlling for open status, age, BMI, Charlson Comorbidity Index (CCI), trauma tier, and resuscitation diagnosis was performed. Laparoscopic procedures converted to open were identified and analyzed using concurrent procedure billing codes across episodes of care. RESULTS: Of 60,604 EGS patients identified over the 33-month period, 7280 (12.0%) had an operation and 6914 (11.4%) included AAST-defined EGS procedures. There were 4813 (69.6%) surgeries performed laparoscopically. Patients undergoing a laparoscopic procedure tended to be younger (45.7 ± 18.0 years vs. 57.2 ± 17.6, p < 0.001) with similar BMI (29.7 ± 9.0 kg/m2 vs. 28.8 ± 8.3, p < 0.001). Patients in the laparoscopic group had lower mean CCI score (1.6 ± 2.3 vs. 3.4 ± 3.2, p ≤ 0.0001). On multivariable analysis, open surgery had the highest association with inpatient mortality (OR 8.67, 4.23-17.75, p < 0.0001) and at all time points (30-, 90-day, 1-, 3-year). At all time points, conversion to open was found to be a statistically significant protective factor. CONCLUSION: Use of laparoscopy in EGS is common and associated with a decreased risk of all-cause mortality at all time points compared to open procedures. Conversion to open was protective at all time points compared to open procedures.

The Obesity Paradox in Emergency General Surgery Patients.

BACKGROUND: Operative management of emergency general surgery (EGS) diagnoses involves a range of procedures which can carry high morbidity and mortality. Little is known about the impact of obesity on patient outcomes. The aim of this study was to examine the association between body mass index (BMI) >30 kg/m2 and mortality for EGS patients. We hypothesized that obese patients would have increased mortality rates. METHODS: A regional integrated health system EGS registry derived from The American Association for the Surgery of Trauma EGS ICD-9 codes was analyzed from January 2013 to October 2015. Patients were stratified into BMI categories based on WHO classifications. The primary outcome was 30-day mortality. Longer-term mortality with linkage to the Social Security Death Index was also examined. Univariate and multivariable analyses were performed. RESULTS: A total of 60 604 encounters were identified and 7183 (11.9%) underwent operative intervention. Patient characteristics include 53% women, mean age 58.2 ± 18.7 years, 64.2% >BMI 30 kg/m2, 30.2% with chronic obstructive pulmonary disease, 19% with congestive heart failure, and 31.1% with diabetes. The most common procedure was laparoscopic cholecystectomy (36.4%). Overall, 90-day mortality was 10.9%. In multivariable analysis, all classes of obesity were protective against mortality compared to normal BMI. Underweight patients had increased risk of inpatient (OR = 1.9, CI = 1.7-2.3), 30-day (OR = 1.9, CI = 1.7-2.1), 90-day (OR = 1.8, CI 1.6-2.0), 1-year (OR = 1.8, CI = 1.7-2.0), and 3-year mortality (OR = 1.7, CI = 1.6-1.9). CONCLUSIONS: When stratified by BMI, underweight EGS patients have the highest odds of death. Paradoxically, obesity appears protective against death, even when controlling for potentially confounding factors. Increased rates of nonoperative management in the obese population may impact these findings.

Deficits in Identification of Goals and Goal-Concordant Care After Sepsis Hospitalization.

In a recent study, identifying and supporting patients' care goals was named the highest priority in hospital medicine. Although sepsis is one of the leading causes of death and postdischarge morbidity among hospitalized patients, little is known about how frequently care goals are assessed prior to discharge and adhered to in the 90 days after sepsis hospitalization. Evaluating a cohort of 679 high-risk sepsis survivors enrolled in a clinical trial, we found that care goals were documented explicitly in a standardized tool in 130 patients; an additional 139 patients were identified using all available clinical documentation, resulting in only 269 (40%) patients with goals that could be ascertained from the electronic health record (EHR). Among those categorized, goals were classified as prioritizing longevity (35%), function (52%), and comfort (12%). Based on expert review of the care provided during the 90 days subsequent to discharge, goal-concordant care was identified in 184 (68%) cases for which goals were specified. Documentation of goals in a standardized EHR tool was associated with increased likelihood of receiving goal-concordant care (odds ratio, 3.6; 95% CI, 2.4-5.5). Hospitalization and peridischarge time points represent important opportunities to address deficits in the documentation of goals and provision of goal-concordant care for sepsis survivors.

Protocol for a two-arm pragmatic stepped-wedge hybrid effectiveness-implementation trial evaluating Engagement and Collaborative Management to Proactively Advance Sepsis Survivorship (ENCOMPASS).

BACKGROUND: Sepsis survivors experience high morbidity and mortality, and healthcare systems lack effective strategies to address patient needs after hospital discharge. The Sepsis Transition and Recovery (STAR) program is a navigator-led, telehealth-based multicomponent strategy to provide proactive care coordination and monitoring of high-risk patients using evidence-driven, post-sepsis care tasks. The purpose of this study is to evaluate the effectiveness of STAR to improve outcomes for sepsis patients and to examine contextual factors that influence STAR implementation. METHODS: This study uses a hybrid type I effectiveness-implementation design to concurrently test clinical effectiveness and gather implementation data. The effectiveness evaluation is a two-arm, pragmatic, stepped-wedge cluster randomized controlled trial at eight hospitals in North Carolina comparing clinical outcomes between sepsis survivors who receive Usual Care versus care delivered through STAR. Each hospital begins in a Usual Care control phase and transitions to STAR in a randomly assigned sequence (one every 4 months). During months that a hospital is allocated to Usual Care, all eligible patients will receive usual care. Once a hospital transitions to STAR, all eligible patients will receive STAR during their hospitalization and extending through 90 days from discharge. STAR includes centrally located nurse navigators using telephonic counseling and electronic health record-based support to facilitate best-practice post-sepsis care strategies including post-discharge review of medications, evaluation for new impairments or symptoms, monitoring existing comorbidities, and palliative care referral when appropriate. Adults admitted with suspected sepsis, defined by clinical criteria for infection and organ failure, are included. Planned enrollment is 4032 patients during a 36-month period. The primary effectiveness outcome is the composite of all-cause hospital readmission or mortality within 90 days of discharge. A mixed-methods implementation evaluation will be conducted before, during, and after STAR implementation. DISCUSSION: This pragmatic evaluation will test the effectiveness of STAR to reduce combined hospital readmissions and mortality, while identifying key implementation factors. Results will provide practical information to advance understanding of how to integrate post-sepsis management across care settings and facilitate implementation, dissemination, and sustained utilization of best-practice post-sepsis management strategies in other heterogeneous healthcare delivery systems. TRIAL REGISTRATION: NCT04495946 . Submitted July 7, 2020; Posted August 3, 2020.