Association Between Medicare's Sepsis Reporting Policy (SEP-1) and the Documentation of a Sepsis Diagnosis in the Clinical Record.

STUDY DESIGN: Interrupted time series analysis of a retrospective, electronic health record cohort. OBJECTIVE: To determine the association between the implementation of Medicare's sepsis reporting measure (SEP-1) and sepsis diagnosis rates as assessed in clinical documentation. BACKGROUND: The role of health policy in the effort to improve sepsis diagnosis remains unclear. PATIENTS AND METHODS: Adult patients hospitalized with suspected infection and organ dysfunction within 6 hours of presentation to the emergency department, admitted to one of 11 hospitals in a multi-hospital health system from January 2013 to December 2017. Clinician-diagnosed sepsis, as reflected by the inclusion of the terms "sepsis" or "septic" in the text of clinical notes in the first two calendar days following presentation. RESULTS: Among 44,074 adult patients with sepsis admitted to 11 hospitals over 5 years, the proportion with sepsis documentation was 32.2% just before the implementation of SEP-1 in the third quarter of 2015 and increased to 37.3% by the fourth quarter of 2017. Of the 9 post-SEP-1 quarters, 8 had odds ratios for a sepsis diagnosis >1 (overall range: 0.98-1.26; P value for a joint test of statistical significance = 0.005). The effects were clinically modest, with a maximum effect of an absolute increase of 4.2% (95% CI: 0.9-7.8) at the end of the study period. The effect was greater in patients who did not require vasopressors compared with patients who required vasopressors ( P value for test of interaction = 0.02). CONCLUSIONS: SEP-1 implementation was associated with modest increases in sepsis diagnosis rates, primarily among patients who did not require vasoactive medications.

Patient Outcomes After Long-Term Acute Care Hospital Closures.

Importance: Long-term acute care hospitals (LTCHs) are common sites of postacute care for patients recovering from severe respiratory failure requiring mechanical ventilation (MV). However, federal payment reform led to the closure of many LTCHs in the US, and it is unclear how closure of LTCHs may have affected upstream care patterns at short-stay hospitals and overall patient outcomes. Objective: To estimate the association between LTCH closures and short-stay hospital care patterns and patient outcomes. Design, Setting, and Participants: This retrospective, national, matched cohort study used difference-in-differences analysis to compare outcomes at short-stay hospitals reliant on LTCHs that closed during 2012 to 2018 with outcomes at control hospitals. Data were obtained from the Medicare Provider Analysis and Review File, 2011 to 2019. Participants included Medicare fee-for-service beneficiaries aged 66 years and older receiving MV for at least 96 hours in an intensive care unit (ie, patients at-risk for prolonged MV) and the subgroup also receiving a tracheostomy (ie, receiving prolonged MV). Data were analyzed from October 2022 to June 2023. Exposure: Admission to closure-affected hospitals, defined as those discharging at least 60% of patients receiving a tracheostomy to LTCHs that subsequently closed, vs control hospitals. Main Outcomes and Measures: Upstream hospital care pattern outcomes were short-stay hospital do-not-resuscitate orders, palliative care delivery, tracheostomy placement, and discharge disposition. Patient outcomes included hospital length of stay, days alive and institution free within 90 days, spending per days alive within 90 days, and 90-day mortality. Results: Between 2011 and 2019, 99 454 patients receiving MV for at least 96 hours at 1261 hospitals were discharged to 459 LTCHs; 84 LTCHs closed. Difference-in-differences analysis included 8404 patients (mean age, 76.2 [7.2] years; 4419 [52.6%] men) admitted to 45 closure-affected hospitals and 45 matched-control hospitals. LTCH closure was associated with decreased LTCH transfer rates (difference, -5.1 [95% CI -8.2 to -2.0] percentage points) and decreased spending-per-days-alive (difference, -$8701.58 [95% CI, -$13 323.56 to -$4079.60]). In the subgroup of patients receiving a tracheostomy, there was additionally an increase in do-not-resuscitate rates (difference, 10.3 [95% CI, 4.2 to 16.3] percentage points) and transfer to skilled nursing facilities (difference, 10.0 [95% CI, 4.2 to 15.8] percentage points). There was no significant association of closure with 90-day mortality. Conclusions and Relevance: In this cohort study, LTCH closure was associated with changes in discharge patterns in patients receiving mechanical ventilation for at least 96 hours and advanced directive decisions in the subgroup receiving a tracheostomy, without change in mortality. Further studies are needed to understand how LTCH availability may be associated with other important outcomes, including functional outcomes and patient and family satisfaction.

Measuring Performance on the ABCDEF Bundle During Interprofessional Rounds via a Nurse-Based Assessment Tool.

BACKGROUND: Nurse-led rounding checklists are a common strategy for facilitating evidence-based practice in the intensive care unit (ICU). To streamline checklist workflow, some ICUs have the nurse or another individual listen to the conversation and customize the checklist for each patient. Such customizations assume that individuals can reliably assess whether checklist items have been addressed. OBJECTIVE: To evaluate whether 1 critical care nurse can reliably assess checklist items on rounds. METHODS: Two nurses performed in-person observation of multidisciplinary ICU rounds. Using a standardized paper-based assessment tool, each nurse indicated whether 17 items related to the ABCDEF bundle were discussed during rounds. For each item, generalizability coefficients were used as a measure of reliability, with a single-rater value of 0.70 or greater considered sufficient to support its assessment by 1 nurse. RESULTS: The nurse observers assessed 118 patient discussions across 15 observation days. For 11 of 17 items (65%), the generalizability coefficient for a single rater met or exceeded the 0.70 threshold. The generalizability coefficients (95% CIs) of a single rater for key items were as follows: pain, 0.86 (0.74-0.97); delirium score, 0.74 (0.64-0.83); agitation score, 0.72 (0.33-1.00); spontaneous awakening trial, 0.67 (0.49-0.83); spontaneous breathing trial, 0.80 (0.70-0.89); mobility, 0.79 (0.69-0.87); and family (future/past) engagement, 0.82 (0.73-0.90). CONCLUSION: Using a paper-based assessment tool, a single trained critical care nurse can reliably assess the discussion of elements of the ABCDEF bundle during multidisciplinary rounds.

Assessment of Hospital Characteristics and Interhospital Transfer Patterns of Adults With Emergency General Surgery Conditions.

Importance: Although patients with emergency general surgery (EGS) conditions frequently undergo interhospital transfers, the transfer patterns and associated factors are not well understood. Objective: To examine whether patients with EGS conditions are consistently directed to hospitals with more resources and better outcomes. Design, Setting, and Participants: This cohort study performed a network analysis of interhospital transfers among adults with EGS conditions from January 1 to December 31, 2016. The analysis used all-payer claims data from the 2016 Healthcare Cost and Utilization Project state inpatient and emergency department databases in 8 states. A total of 728 hospitals involving 85 415 transfers of 80 307 patients were included. Patients were eligible for inclusion if they were 18 years or older and had an acute care hospital encounter with a diagnosis of an EGS condition as defined by the American Association for the Surgery of Trauma. Data were analyzed from January 1, 2020, to June 17, 2021. Exposures: Hospital-level measures of size (total bed capacity), resources (intensive care unit [ICU] bed capacity, teaching status, trauma center designation, and presence of trauma and/or surgical critical care fellowships), EGS volume (annual EGS encounters), and EGS outcomes (risk-adjusted failure to rescue and in-hospital mortality). Main Outcomes and Measures: The main outcome was hospital-level centrality ratio, defined as the normalized number of incoming transfers divided by the number of outgoing transfers. A higher centrality ratio indicated more incoming transfers per outgoing transfer. Multivariable regression analysis was used to test the hypothesis that a higher hospital centrality ratio would be associated with more resources, higher volume, and better outcomes. Results: Among 80 307 total patients, the median age was 63 years (interquartile range [IQR], 50-75 years); 52.1% of patients were male and 78.8% were White. The median number of outgoing and incoming transfers per hospital were 106 (IQR, 61-157) and 36 (IQR, 8-137), respectively. A higher log-transformed centrality ratio was associated with more resources, such as higher ICU capacity (eg, >25 beds vs 0-10 beds: ß = 1.67 [95% CI, 1.16-2.17]; P < .001), and higher EGS volume (eg, quartile 4 [highest] vs quartile 1 [lowest]: ß = 0.78 [95% CI, 0-1.57]; P = .01). However, a higher log-transformed centrality ratio was not associated with better outcomes, such as lower in-hospital mortality (eg, quartile 4 [highest] vs quartile 1 [lowest]: ß = 0.30 [95% CI, -0.09 to 0.68]; P = .83) and lower failure to rescue (eg, quartile 4 [highest] vs quartile 1 [lowest]: ß = -0.50 [95% CI, -1.13 to 0.12]; P = .27). Conclusions and Relevance: In this study, EGS transfers were directed to high-volume hospitals with more resources but were not necessarily directed to hospitals with better clinical outcomes. Optimizing transfer destination in the interhospital transfer network has the potential to improve EGS outcomes.

The centralization of bladder cancer care and its implications for patient travel distance.

OBJECTIVES: To evaluate the impact of centralized surgical and nonsurgical care (i.e., radiation and chemotherapy) on travel distances and survival outcomes for patients with advanced bladder cancer. Bladder cancer is a disease with high mortality for which treatment access is paramount and survival is superior in patients receiving surgery at high-volume centers. METHODS: Using SEER-Medicare, we identified patients 66 years or older diagnosed with bladder cancer between 2004-2013. We categorized patients as treated with either surgical (i.e., radical cystectomy) or nonsurgical (i.e., radiation or chemotherapy) care. We fit a linear probability model to generate the predicted proportion of patients treated at the top quintile of volume over time and assessed travel distance, 1-year all-cause mortality, and 1-year bladder cancer-specific mortality over time. RESULTS: A total of 6,756 and 10,383 patients underwent surgical and nonsurgical care, respectively. The percentage of patients treated at high-volume centers increased over the study period for both surgical care (53% to 62%) and nonsurgical care (47% to 55%), (both P< 0.001). Median travel distance increased (11.8 to 20.3 miles) for surgical care and (6.5 to 8.3 miles) for nonsurgical care, (both P < 0.001). The 1-year adjusted all-cause mortality and 1-year adjusted bladder-cancer specific mortality decreased significantly for both surgical and nonsurgical care (both P < 0.05). CONCLUSIONS: Over time, centralization of surgical and nonsurgical care for bladder cancer patients increased, which was associated with increasing patient travel distance and decreased all-cause and bladder-cancer specific mortality.

Treatment Patterns and Clinical Outcomes After the Introduction of the Medicare Sepsis Performance Measure (SEP-1).

BACKGROUND: Medicare requires that hospitals report on their adherence to the Severe Sepsis and Septic Shock Early Management Bundle (SEP-1). OBJECTIVE: To evaluate the effect of SEP-1 on treatment patterns and patient outcomes. DESIGN: Longitudinal study of hospitals using repeated cross-sectional cohorts of patients. SETTING: 11 hospitals within an integrated health system. PATIENTS: 54 225 encounters between January 2013 and December 2017 for adults with sepsis who were hospitalized through the emergency department. INTERVENTION: Onset of the SEP-1 reporting requirement in October 2015. MEASUREMENTS: Changes in SEP-1-targeted processes, including antibiotic administration, lactate measurement, and fluid administration at 3 hours from sepsis onset; repeated lactate and vasopressor administration for hypotension within 6 hours of sepsis onset; and sepsis outcomes, including risk-adjusted intensive care unit (ICU) admission, in-hospital mortality, and home discharge among survivors. RESULTS: Two years after its implementation, SEP-1 was associated with variable changes in process measures, with the greatest effect being an increase in lactate measurement within 3 hours of sepsis onset (absolute increase, 23.7 percentage points [95% CI, 20.7 to 26.7 percentage points]; P < 0.001). There were small increases in antibiotic administration (absolute increase, 4.7 percentage points [CI, 1.9 to 7.6 percentage points]; P = 0.001) and fluid administration of 30 mL/kg of body weight within 3 hours of sepsis onset (absolute increase, 3.4 percentage points [CI, 1.5 to 5.2 percentage points]; P < 0.001). There was no change in vasopressor administration. There was a small increase in ICU admissions (absolute increase, 2.0 percentage points [CI, 0 to 4.0 percentage points]; P = 0.055) and no changes in mortality (absolute change, 0.1 percentage points [CI, -0.9 to 1.1 percentage points]; P = 0.87) or discharge to home. LIMITATION: Data are from a single health system. CONCLUSION: Implementation of the SEP-1 mandatory reporting program was associated with variable changes in process measures, without improvements in clinical outcomes. Revising the measure may optimize its future effect. PRIMARY FUNDING SOURCE: Agency for Healthcare Research and Quality.

Emergency Department and Ambulatory Care Visits in the First Twelve Months of Coverage Under Medicaid Expansion: A Group-Based Trajectory Analysis.

STUDY OBJECTIVE: More than 17 million people have gained health insurance coverage through the Patient Protection and Affordable Care Act's Medicaid expansion. Few studies have examined heterogeneity within the Medicaid expansion population. We do so based on time-varying patterns of emergency department (ED) and ambulatory care use, and characterize diagnoses associated with ED and ambulatory care visits to evaluate whether certain diagnoses predominate in individual trajectories. METHOD: We used group-based multitrajectory modeling to jointly estimate trajectories of ambulatory care and ED utilization in the first 12 months of enrollment among Pennsylvania Medicaid expansion enrollees from 2015 to 2017. RESULTS: Among 601,877 expansion enrollees, we identified 6 distinct groups based on joint trajectories of ED and ambulatory care use. Mean ED use varied across groups from 3.4 to 48.7 visits per 100 enrollees in the first month and between 2.8 and 44.0 visits per 100 enrollees in month 12. Mean ambulatory visit rates varied from 0.0 to 179 visits per 100 enrollees in the first month and from 0.0 to 274 visits in month 12. Rates of ED visits did not change over time, but rates of ambulatory care visits increased by at least 50% among 4 groups during the study period. Groups varied on chronic condition diagnoses, including mental health and substance use disorders, as well as diagnoses associated with ambulatory care visits. CONCLUSION: We found substantial variation in rates of ED and ambulatory care use across empirically defined subgroups of Medicaid expansion enrollees. We also identified heterogeneity among the diagnoses associated with these visits. This data-driven approach may be used to target resources to encourage efficient use of ED services and support engagement with ambulatory care clinicians.

Association Between State Medicaid Expansion and Emergency Access to Acute Care Hospitals in the United States.

Importance: State decisions not to expand Medicaid under the Patient Protection and Affordable Care Act could reduce emergency access to acute care hospitals. Objective: To determine the relationship between state Medicaid expansion and emergency access to acute care hospitals in the United States. Design, Setting, and Participants: This cross-sectional study linked hospital-level data from the Centers for Medicare & Medicaid Services from 2007 to 2017 to US Census data for all 50 US states and the District of Columbia. Geospatial analyses and difference-in-differences regression models were used to compare temporal changes in the size of the population without 30-minute access to acute care hospitals between 32 states that expanded Medicaid with the population without access in 19 that did not, before and after expansion. Analyses focused on the total population and those with low incomes; secondary analyses examined emergency access to safety-net hospitals. Exposures: State-level Medicaid expansion. Main Outcomes and Measures: Population without emergency access to an acute care hospital, defined as living outside a 30-minute drive of any hospital. Results: States that did not expand Medicaid experienced an increase in the population without access to hospitals overall (without expansion: 6.76% to 6.79% [0.03%]; vs with expansion: 5.65% to 5.35% [-0.30%]; difference-in-differences, 0.33%; 95% CI, 0.33%-0.34%; P < .001) and for low-income persons (without expansion: 7.43% to 7.39% [-0.04%]; vs with expansion: 6.25% to 6.15% [-0.10%]; difference-in-differences, 0.06%; 95% CI, 0.05%-0.07%; P < .001). If access changes in nonexpansion states were the same as expansion states, an estimated 421 000 more persons overall and 48 000 more low-income persons would have retained access. States that did not expand Medicaid experienced an increase in the population without access to safety-net hospitals overall (46.91% to 47.70% [0.79%] vs 33.94% to 33.07% [-0.87%]; difference-in-differences, 1.66%; 95% CI, 1.64%-1.66%; P < .001) and for low-income persons (45.28% to 46.14% [0.86%] vs 33.00% to 32.23% [-0.77%]; difference-in-differences, 1.63%; 95% CI, 1.63%-1.67%; P < .001). If access changes in nonexpansion states were the same as expansion states, an estimated 2 242 000 more persons overall and 364 000 more low-income persons would have retained access. Conclusions and Relevance: States that did not expand Medicaid under the Patient Protection and Affordable Care Act were associated with worse emergency access to acute care hospitals compared with states that expanded Medicaid.

Economic Analysis of Mandated Protocolized Sepsis Care in New York Hospitals.

OBJECTIVES: Initial evidence suggests that state-level regulatory mandates for sepsis quality improvement are associated with decreased sepsis mortality. However, sepsis mandates require financial investments on the part of hospitals and may lead to increased spending. We evaluated the effects of the 2013 New York State sepsis regulations on the costs of care for patients hospitalized with sepsis. DESIGN: Retrospective cohort study using state discharge data from the U.S. Healthcare Costs and Utilization Project and a comparative interrupted time series analytic approach. Costs were calculated from admission-level charge data using hospital-specific cost-to-charge ratios. SETTING: General, short stay, acute care hospitals in New York, and four control states: Florida, Massachusetts, Maryland, and New Jersey. PATIENTS: All patients hospitalized with sepsis between January 1, 2011, and September 30, 2015. INTERVENTIONS: The 2013 New York mandate that all hospitals develop and implement protocols for sepsis identification and treatment, educate staff, and report performance data to the state. MEASUREMENTS AND MAIN RESULTS: The analysis included 1,026,664 admissions in 520 hospitals. Mean unadjusted costs per hospitalization in New York State were $42,036 ± $60,940 in the pre-regulation period and $39,719 ± $59,063 in the post-regulation period, compared with $34,642 ± $52,403 pre-regulation and $31,414 ± $48,155 post-regulation in control states. In the comparative interrupted time series analysis, the regulations were not associated with a significant difference in risk-adjusted mean cost per hospitalization (p = 0.12) or risk-adjusted mean cost per hospital day (p = 0.44). For example, in the 10th quarter after implementation of the regulations, risk-adjusted mean cost per hospitalization was $3,627 (95% CI, -$681 to $7,934) more than expected in New York State relative to control states. CONCLUSIONS: Mandated protocolized sepsis care was not associated with significant changes in hospital costs in patients hospitalized with sepsis in New York State.

Telemedicine and Outpatient Subspecialty Visits Among Pediatric Medicaid Beneficiaries.

OBJECTIVE: Live interactive telemedicine is increasingly covered by state Medicaid programs, but whether telemedicine is improving equity in utilization of subspecialty care is not known. We examined patterns of telemedicine use for outpatient pediatric subspecialty care within the state Medicaid programs. METHODS: We identified children ≤17 years old in 2014 Medicaid Analysis eXtract data for 12 states. We identified telemedicine-using and telemedicine-nonusing medical and surgical subspecialists. Among children cared for by telemedicine-using subspecialists, we assessed child and subspecialist characteristics associated with any telemedicine visit using logistic regression with subspecialist-level random effects. Among children cared for by telemedicine-using and nonusing subspecialists, we compared visit rates across child characteristics by assessing negative binomial regression interaction terms. RESULTS: Of 12,237,770 pediatric Medicaid beneficiaries, 2,051,690 (16.8%) had ≥1 subspecialist visit. Of 42,695 subspecialists identified, 146 (0.3%) had ≥1 telemedicine claim. Among children receiving care from telemedicine-using subspecialists, likelihood of any telemedicine use was increased for rural children (odds ratio [OR] 10.4, 95% confidence interval [CI] 6.3-17.1 compared to large metropolitan referent group) and those >90 miles from the subspecialist (OR 13.4, 95% CI 10.2-17.7 compared to 0-30 mile referent group). Compared to children receiving care from telemedicine-nonusing subspecialists, matched children receiving care from telemedicine-using subspecialists had larger differences in visit rates by distance to care, county rurality, ZIP code median income, and child race/ethnicity (P < .001 for interaction terms). CONCLUSIONS: Children in rural communities and at distance to subspecialists had increased likelihood of telemedicine use. Use overall was low, and results indicated that early telemedicine policies and implementation did not close disparities in subspecialty visit rates by child geographic and sociodemographic characteristics.

The Development and Validation of Prostate Cancer-specific Physician-Hospital Networks.

OBJECTIVE: To develop prostate cancer-specific physician-hospital networks to define hospital-based units that more accurately group hospitals, providers, and the patients they serve. METHODS: Using Surveillance, Epidemiology, and End Results-Medicare, we identified men diagnosed with localized prostate cancer between 2007 and 2011. We created physician-hospital networks by assigning each patient to a physician and each physician to a hospital based on treatment patterns. We assessed content validity by examining characteristics of hospitals anchoring the physician-hospital networks and of the patients associated with these hospitals. RESULTS: We identified 42,963 patients associated with 344 physician-hospital networks. Networks anchored by a teaching hospital (compared to a nonteaching hospital) had higher median numbers of prostate cancer patients (117 [interquartile range {71-189} vs 82 {50-126}]) and treating physicians (7 [4-11] vs 4 [3-6]) (both P <0.001). On average, patients traveled farther to networks anchored by a teaching hospital (49 miles [standard deviation] [207] vs 41 [183]; P <.001). Hospitals known as high-volume centers for robotic prostatectomies, proton-beam therapy, and active surveillance had network rates for these procedures well above the mean. Hospitals known as safety net providers served higher proportions of minorities. CONCLUSION: We empirically developed prostate-cancer specific physician-hospital networks that exhibit content validity and are relevant from a clinical and policy perspective. They have the potential to become targets for policy interventions focused on improving the delivery of prostate cancer care.

Connected Subspecialty Care: Applying Telehealth Strategies to Specific Referral Barriers.

Nearly a quarter of families of children with need of subspecialty care report difficulty accessing that care. Telehealth is a method to overcome barriers to subspecialty care. However, improving access to subspecialty care through telehealth requires granular identification of specific subspecialty barriers and recognition of the strengths and limitations of each telehealth strategy for addressing identified barriers. Focusing on each sequential step in subspecialty referrals and potential associated barriers, we summarize specific telehealth and technology-enabled strategies to improve access to subspecialty care, including electronic consultations, live interactive telemedicine, store-and-forward telemedicine, tele-mentoring, patient portals, and remote patient monitoring. Intentionally selecting telehealth strategies to target specific subspecialty referral barriers may avoid risks from misapplication of telehealth, may more clearly elevate equitable access as an essential goal within telehealth initiatives, and may also lead to synergistic use of strategies that overcome sequential barriers.

Validation of use of billing codes for identifying telemedicine encounters in administrative data.

BACKGROUND: Telemedicine is the use of telecommunication technology to remotely provide healthcare services. Evaluation of telemedicine use often relies on administrative data, but the validity of identifying telemedicine encounters in administrative data is not known. The objective of this study was to assess the accuracy of billing codes for identifying telemedicine use. METHODS: In this retrospective study of encounters within a large integrated health system from January 2016 to December 2017, we examined the accuracy of billing codes for identifying live-interactive and store-and-forward telemedicine encounters compared to manual chart review. To further examine external validity, we applied these codes and assessed patient and visit characteristics for identified live-interactive telemedicine encounters and store-and-forward telemedicine encounters in a second data set. RESULTS: In manual review of 390 encounters, 75 encounters were live-interactive telemedicine and 158 were store-and-forward telemedicine. In weighted analysis, the presence of the GT modifier in the absence of the GQ modifier or CPT code 99444 yielded 100% sensitivity and 99.99% specificity for identification of live-interactive telemedicine encounters. The presence of either the GQ modifier or the CPT code 99444 had 100% sensitivity and 100% specificity for identification of store-and-forward telemedicine encounters. Applying these algorithms to a second data set (n = 5,917,555) identified telemedicine encounters with expected patient and visit characteristics. CONCLUSIONS: These findings provide support for use of CPT codes to perform telemedicine research in administrative data, aiding ongoing work to understand the role of non-face-to-face care in optimizing health care delivery.

Association of Practitioner Interfacility Triage Performance With Outcomes for Severely Injured Patients With Fee-for-Service Medicare Insurance.

Importance: Despite evidence that treatment of severely injured patients at trauma centers is associated with reduced mortality, nearly half of all such patients are treated at nontrauma centers (undertriaged). Little is known about whether interfacility undertriage occurs because of practitioner decision-making or institutional and regional factors. Objectives: To assess the associations between variation in triage practitioners at nontrauma centers and between practitioner-level variation and patient outcomes after injury. Design, Setting, and Participants: This retrospective cohort study used Medicare claims data from severely injured patients presenting to nontrauma centers and the practitioners who evaluated them in the emergency department from January 1, 2010, to October 15, 2015. Data analysis was performed from January 15, 2018, to March 21, 2019. Main Outcomes and Measures: Proportion of variation in undertriage associated with practitioners, practitioner rates of undertriage, practitioner characteristics associated with undertriage, and 30-day case-fatality rate. Results: A total of 124 008 severely injured patients (mean [SD] age, 81 [8.4] years; 67 253 [54.2%] female) and the 25 376 practitioners (5564 [21.9%] female) who evaluated the patients in the emergency department of nontrauma centers were included in the study. Undertriage occurred among 85 403 patients (68.9%), with 40.6% of total variation associated with practitioners, 37.8% with hospitals, and 6.7% with regions. Compared with physicians with National Provider Identification (NPI) enumeration before 2007, those with an NPI enumerated between 2007 and 2010 had an undertriage risk ratio (RR) of 0.98 (95% CI, 0.97-0.99), and those with an NPI enumerated after 2010 had an undertriage RR of 0.96 (95% CI, 0.94-0.99). Hospitals with neurosurgeons had an undertriage RR of 1.51 (95% CI, 1.45-1.57) compared with those that did not; hospitals with spine surgeons had an undertriage RR of 1.10 (95% CI, 1.06-1.13); hospitals with general surgeons had an undertriage RR of 1.13 (95% CI, 1.09-1.17). Compared with practitioners who undertriaged 25% or less of patients, a statistically significant increase was found in the odds of death for patients treated by practitioners with a triage rate of less than 25% to 50% (odds ratio [OR], 1.08; 95% CI, 1.05-1.20) and less than 50% to 75% undertriage (OR, 1.12; 95% CI, 1.09-1.26) but not undertriage at greater than 75% (OR, 1.03, 95% CI, 1.00-1.18). In sensitivity analyses to adjust for unmeasured confounding, the association between triage practices and the case fatality rate became monotonic; compared with patients treated by practitioners with an undertriage rate of 25% or less, the odds of case fatality were 1.13 (95% CI, 1.05-1.21; P = .001) among patients treated by practitioners with undertriage rates less than 25% to 50%, 1.22 (95% CI, 1.13-1.32; P < .001) for patients treated by practitioners with undertriage rates less than 50% to 75%, and 1.20 (95% CI, 1.10-1.30; P < .001) for patients treated by practitioners with undertriage rates greater than 75%. Conclusions and Relevance: The findings suggest that individual practitioner practices are an important source of variation in triage and represent a potential locus of intervention to reduce preventable deaths after injury.

Sepsis quality in safety-net hospitals: An analysis of Medicare's SEP-1 performance measure.

PURPOSE: Newly enacted policies at the state and federal level in the United States require acute care hospitals to engage in sepsis quality improvement. However, responding to these policies requires considerable resources and may disproportionately burden safety-net hospitals. To better understand this issue, we analyzed the relationship between hospital safety-net status and performance on Medicare's SEP-1 quality measure. MATERIALS AND METHODS: We linked multiple publicly-available datasets with information on SEP-1 performance, structural hospital characteristics, hospital financial case mix, and health system affiliation. We analyzed the relationship between hospital safety-net status and SEP-1 performance, as well as whether hospital characteristics moderated that relationship. RESULTS: We analyzed data from 2827 hospitals, defining safety-net hospitals using financial case mix data. The 703 safety-net hospitals performed worse on Medicare's SEP-1 quality measure (adjusted difference 2.3% compliance, 95% CI -4.0%--0.6%). This association was most evident in hospitals not affiliated with health systems, in which the difference between safety-net and non-safety-net hospitals was 6.8% compliance (95% CI -10.4%--3.3%). CONCLUSIONS: Existing sepsis policies may harm safety-net hospitals and widen health disparities. Our findings suggest that strategies to promote collaboration among hospitals may be an avenue for sepsis performance improvement in safety-net hospitals.

Effects of Changes in ICU Bed Supply on ICU Utilization.

BACKGROUND: The availability of intensive care unit (ICU) beds may influence the demand for critical care. Although small studies support a model of supply-induced demand in the ICU, there is a paucity of system-wide data. OBJECTIVE: The objective of this study was to determine the relationship between ICU bed supply and ICU admission in United States hospitals. RESEARCH DESIGN: Retrospective cohort study using all-payer inpatient records from Florida, Massachusetts, New Jersey, New York, and Washington from 2010 to 2012, linked to hospital data from Medicare's Healthcare Cost Reporting Information System. SUBJECTS: Three patient groups with a low likelihood of benefiting from ICU admission-low severity patients with acute myocardial infarction and pulmonary embolism; and high severity patients with metastatic cancer at the end of life. MEASURES: We compared the risk-adjusted probability of ICU admission at hospitals that increased their ICU bed supply over time to matched hospitals that did not, using a difference-in-differences approach. RESULTS: For patients with acute myocardial infarction, ICU supply increases were associated with an increase in the probability of ICU admission that diminished over time. For patients with pulmonary embolism, there was a trend toward an association between change in ICU supply and ICU admission that did not meet statistical significance. For patients with metastatic cancer, admission to hospitals with an increasing ICU supply was not associated with changes in the probability of ICU admission. CONCLUSIONS: Increases in ICU bed supply were associated with inconsistent changes in the probability of ICU admission that varied across patient subgroups.

Referring Hospital Characteristics Associated With Potentially Avoidable Emergency Department Transfers.

OBJECTIVE: Many emergency department (ED) transfers of children may be avoidable. Identifying hospital-level variables associated with avoidable transfers may guide system-level interventions to improve pediatric emergency care. We sought to examine hospital characteristics associated with ED transfers deemed "probably avoidable" in a large state Medicaid program. METHODS: We performed a retrospective cohort study using 2009 to 2013 claims data for Pennsylvania Medicaid beneficiaries. We categorized all ED transfers of children < 17 years old as "probably avoidable," "possibly avoidable", or "unavoidable" based on ultimate disposition and procedures (including subspecialty consultations) at the receiving ED. Using descriptive statistics and multivariable regression, we examined hospital characteristics associated with probably avoidable transfers. RESULTS: Among 2,839,379 pediatric visits to EDs across 158 Pennsylvania hospitals, 20,304 resulted in transfer. Among these, 3,764 (18.5%) were categorized as probably avoidable and 6,091 (30.0%) as possibly avoidable transfers. In adjusted analysis, compared to hospitals with no pediatric-specific capabilities, probably avoidable transfers were less likely from referring hospitals with pediatric-specific EDs and no other pediatric-specific capabilities (adjusted odds ratio [aOR] = 0.38, 95% confidence interval [CI] = 0.21-0.71) and from referring hospitals with pediatric-specific EDs and inpatient capabilities (aOR = 0.36, 95% CI = 0.20-0.64). Probably avoidable transfers were more likely from referring hospitals in large metropolitan areas (aOR = 2.64, 95% CI = 1.46-4.80) compared to those in rural areas. CONCLUSIONS: Among pediatric emergency transfers in a large state Medicaid program with a nearly 20% probably avoidable transfer rate, there was significant hospital-level variation in the proportion of probably avoidable transfers. Transfers from hospitals in large metropolitan areas and transfers from hospitals without pediatric-specific capabilities had increased odds of being probably avoidable transfers, such that these hospitals may represent targets for interventions to reduce these transfers.

Protocol and Fidelity Monitoring Plan for Four Supports. A Multicenter Trial of an Intervention to Support Surrogate Decision Makers in Intensive Care Units.

Individuals acting as surrogate decision makers for critically ill patients frequently struggle in this role and experience high levels of long-term psychological distress. Prior interventions designed to improve the sharing of information by the clinical team with surrogate decision makers have demonstrated little effect on surrogates' outcomes or clinical decisions. In this report, we describe the study protocol and corresponding intervention fidelity monitoring plan for a multicenter randomized clinical trial testing the impact of a multifaceted surrogate support intervention (Four Supports) on surrogates' psychological distress, the quality of decisions about goals of care, and healthcare use. We will randomize the surrogates of 300 incapacitated critically ill patients at high risk of death and/or severe long-term functional impairment to receive the Four Supports intervention or an education control. The Four Supports intervention adds to the intensive care unit (ICU) team a trained interventionist (family support specialist) who delivers four types of protocolized support-emotional support; communication support; decisional support; and, if indicated, anticipatory grief support-to surrogates through daily interactions during the ICU stay. The primary outcome is surrogates' symptoms of anxiety and depression at 6-month follow-up, measured with the Hospital Anxiety and Depression Scale. Prespecified secondary outcome measures are the Patient Perception of Patient Centeredness Scale (modified for use with surrogates) and Impact of Event Scale scores at 3- and 6-month follow-up, respectively, together with ICU and hospital lengths of stay and total hospital cost among decedents. The fidelity monitoring plan entails establishing and measuring adherence to the intervention using multiple measurement methods, including daily checklists and coding of audiorecorded encounters. This approach to intervention fidelity may benefit others designing and testing behavioral interventions in the ICU setting. Clinical trial registered with www.clinicaltrials.gov (NCT01982877).