Disparities in Use of Novel Diabetes Medications by Insurance: A Nationally Representative Cohort Study.

BACKGROUND: Minority racial and ethnic populations have the highest prevalence of type 2 diabetes mellitus but lower use of sodium-glucose co-transporter-2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP1ra), novel medications that reduce morbidity and mortality. Observed disparities may be due to differences in insurance coverage, which have variable cost-sharing, prior authorization, and formulary restrictions that influence medication access. OBJECTIVE: To assess whether racial/ethnic differences in SGLT2i and GLP1ra use differ by payer. DESIGN: Cross-sectional analysis of 2018 and 2019 Medical Expenditure Panel Survey data. PARTICIPANTS: Adults ≥ 18 years old with diabetes. MAIN MEASURES: We defined insurance as private, Medicare, or Medicaid using ≥ 7 months of coverage in the calendar year. We defined race/ethnicity as White (non-Hispanic) vs non-White (including Hispanic). The primary outcome was use of ≥ 1 SGLT2i or GLP1ra medication. We used multivariable logistic regression to assess the interaction between payer and race/ethnicity adjusted for cardiovascular, socioeconomic, and healthcare access factors. KEY RESULTS: We included 4997 adults, representing 24.8 million US adults annually with diabetes (mean age 63.6 years, 48.8% female, 38.8% non-White; 33.5% private insurance, 56.8% Medicare, 9.8% Medicaid). In our fully adjusted model, White individuals with private insurance had significantly more medication use versus non-White individuals (16.1% vs 8.3%, p < 0.001), which was similar for Medicare beneficiaries but more attenuated (14.7% vs 11.0%, p = 0.04). Medication rates were similar among Medicaid beneficiaries (10.0% vs 9.0%, p = 0.74). CONCLUSIONS: Racial/ethnic disparities in novel diabetes medications were the largest among those with private insurance. There was no disparity among Medicaid enrollees, but overall prescription rates were the lowest. Given that disparities vary considerably by payer, differences in insurance coverage may account for the observed disparities in SGLT2i and GLP1ra use. Future studies are needed to assess racial/ethnic differences in novel diabetes use by insurance formulary restrictions and out-of-pocket cost-sharing.

The Impact of Block Ambulatory Scheduling on Internal Medicine Residencies: a Systematic Review.

BACKGROUND: Over the past decade, nearly half of internal medicine residencies have implemented block clinic scheduling; however, the effects on residency-related outcomes are unknown. The authors systematically reviewed the impact of block versus traditional ambulatory scheduling on residency-related outcomes, including (1) resident satisfaction, (2) resident-perceived conflict between inpatient and outpatient responsibilities, (3) ambulatory training time, (4) continuity of care, (5) patient satisfaction, and (6) patient health outcomes. METHOD: The authors reviewed the following databases: Ovid MEDLINE, Ovid MEDLINE InProcess, EBSCO CINAHL, EBSCO ERIC, and the Cochrane Library from inception through March 2017 and included studies of residency programs comparing block to traditional scheduling with at least one outcome of interest. Two authors independently extracted data on setting, participants, schedule design, and the outcomes of interest. RESULTS: Of 8139 studies, 11 studies of fair to moderate methodologic quality were included in the final analysis. Overall, block scheduling was associated with marked improvements in resident satisfaction (n = 7 studies, effect size range - 0.3 to + 0.9), resident-perceived conflict between inpatient and outpatient responsibilities (n = 5, effect size range + 0.3 to + 2.6), and available ambulatory training time (n = 5). Larger improvements occurred in programs implementing short (1 week) ambulatory blocks. However, block scheduling may result in worse physician continuity (n = 4). Block scheduling had inconsistent effects on patient continuity (n = 4), satisfaction (n = 3), and health outcomes (n = 3). DISCUSSION: Although block scheduling improves resident satisfaction, conflict between inpatient and outpatient responsibilities, and ambulatory training time, there may be important tradeoffs with worse care continuity.

An Evidence-Based Medicine Approach to Antihyperglycemic Therapy in Diabetes Mellitus to Overcome Overtreatment.

Overtreatment is pervasive in medicine and leads to potential patient harms and excessive costs in health care. Although evidence-based medicine is often derided as practice by rote algorithmic medicine, the appropriate application of key evidence-based medicine principles in clinical decision making is fundamental to preventing overtreatment and promoting high-value, individualized patient-centered care. Specifically, this article discusses the importance of (1) using absolute rather than relative estimates of benefits to inform treatment decisions; (2) considering the time horizon to benefit of treatments; (3) balancing potential harms and benefits; and (4) using shared decision making by physicians to incorporate the patient's values and preferences into treatment decisions. Here, we illustrate the application of these principles to considering the decision of whether or not to recommend intensive glycemic control to patients to minimize microvascular and cardiovascular complications in type 2 diabetes mellitus. Through this lens, this example will illustrate how an evidence-based medicine approach can be used to individualize glycemic goals and prevent overtreatment, and can serve as a template for applying evidence-based medicine to inform treatment decisions for other conditions to optimize health and individualize patient care.

Hospital-initiated transitional care interventions as a patient safety strategy: a systematic review.

Hospitals now have the responsibility to implement strategies to prevent adverse outcomes after discharge. This systematic review addressed the effectiveness of hospital-initiated care transition strategies aimed at preventing clinical adverse events (AEs), emergency department (ED) visits, and readmissions after discharge in general medical patients. MEDLINE, CINAHL, EMBASE, and Cochrane Database of Clinical Trials (January 1990 to September 2012) were searched, and 47 controlled studies of fair methodological quality were identified. Forty-six studies reported readmission rates, 26 reported ED visit rates, and 9 reported AE rates. A "bridging" strategy (incorporating both predischarge and postdischarge interventions) with a dedicated transition provider reduced readmission or ED visit rates in 10 studies, but the overall strength of evidence for this strategy was low. Because of scant evidence, no conclusions could be reached on methods to prevent postdischarge AEs. Most studies did not report intervention context, implementation, or cost. The strategies hospitals should implement to improve patient safety at hospital discharge remain unclear.

Survival, Function, and Cognition After Hospitalization in Long-Term Acute Care Hospitals.

Importance: More than 70 000 Medicare beneficiaries receive care in long-term acute care hospitals (LTCHs) annually for prolonged acute illness. However, little is known about long-term functional and cognitive outcomes of middle-aged and older adults after hospitalization in an LTCH. Objective: To describe survival, functional, and cognitive status after LTCH hospitalization and to identify factors associated with an adverse outcome. Design, Setting, and Participants: This retrospective cohort study included middle-aged and older adults enrolled in the Health and Retirement Study (HRS) with linked fee-for-service Medicare claims. Included participants were aged 50 years or older with an LTCH admission between January 1, 2003, and December 31, 2016, with HRS interviews available before admission. Data were analyzed between November 1, 2021, and June 30, 2023. Main Outcomes and Measures: Function and cognition were ascertained from HRS interviews conducted every 2 years. The primary outcome was death or severe impairment in the 2.5 years after LTCH hospitalization, defined as dependencies in 2 or more activities of daily living (ADLs) or dementia. Multivariable logistic regression was performed to evaluate associations with a priori selected risk factors including pre-LTCH survival prognosis (Lee index score), pre-LTCH impairment status, and illness severity characterized by receipt of mechanical ventilation and prolonged intensive care unit stay of 3 days or longer. Results: This study included 396 participants, with a median age of 75 (IQR, 68-82) years. Of the participants, 201 (51%) were women, 125 (28%) had severe impairment, and 318 (80%) died or survived with severe impairment (functional, cognitive, or both) within 2.5 years of LTCH hospitalization. After accounting for acute illness characteristics, prehospitalization survival prognosis as determined by the Lee index score and severe baseline impairment (functional, cognitive, or both) were associated with an increased likelihood of death or severe impairment in the 2.5 years after LTCH hospitalization (adjusted odds ratio [AOR], 3.2 [95% CI, 1.7 to 6.0] for a 5-point increase in Lee index score; and AOR, 4.5 [95% CI, 1.3 to 15.4] for severe vs no impairment). Conclusions and Relevance: In this cohort study, 4 of 5 middle-aged and older adults died or survived with severe impairment within 2.5 years of LTCH hospitalization. Better preadmission survival prognosis and functional and cognitive status were associated with lower risk of an adverse outcome, and these findings should inform decision-making for older adults with prolonged acute illness.

Identifying patients with diabetes and the earliest date of diagnosis in real time: an electronic health record case-finding algorithm.

BACKGROUND: Effective population management of patients with diabetes requires timely recognition. Current case-finding algorithms can accurately detect patients with diabetes, but lack real-time identification. We sought to develop and validate an automated, real-time diabetes case-finding algorithm to identify patients with diabetes at the earliest possible date. METHODS: The source population included 160,872 unique patients from a large public hospital system between January 2009 and April 2011. A diabetes case-finding algorithm was iteratively derived using chart review and subsequently validated (n = 343) in a stratified random sample of patients, using data extracted from the electronic health records (EHR). A point-based algorithm using encounter diagnoses, clinical history, pharmacy data, and laboratory results was used to identify diabetes cases. The date when accumulated points reached a specified threshold equated to the diagnosis date. Physician chart review served as the gold standard. RESULTS: The electronic model had a sensitivity of 97%, specificity of 90%, positive predictive value of 90%, and negative predictive value of 96% for the identification of patients with diabetes. The kappa score for agreement between the model and physician for the diagnosis date allowing for a 3-month delay was 0.97, where 78.4% of cases had exact agreement on the precise date. CONCLUSIONS: A diabetes case-finding algorithm using data exclusively extracted from a comprehensive EHR can accurately identify patients with diabetes at the earliest possible date within a healthcare system. The real-time capability may enable proactive disease management.

Characterizing patients hospitalized without an acute care indication: A retrospective cohort study.

BACKGROUND: Hospitalizations by patients who do not meet acute inpatient criteria are common and overburden healthcare systems. Studies have characterized these alternate levels of care (ALC) but have not delineated prolonged (pALC) versus short ALC (sALC) stays. OBJECTIVE: To descriptively compare pALC and sALC hospitalizations-groups we hypothesize have unique needs. DESIGNS, SETTINGS, AND PARTICIPANTS: A retrospective study of hospitalizations from March-April 2018 at an academic safety-net hospital. MAIN OUTCOME AND MEASURES: Levels of care for pALC (>3 days) and sALC (1-3 days) were determined using InterQual©, an industry standard utilization review tool for determining the clinical appropriateness of hospitalization. We examined sociodemographic and clinical characteristics. RESULTS: Of 2365 hospitalizations, 215 (9.1%) were pALC, 277 (11.7%) were sALC, and 1873 (79.2%) had no ALC days. There were 17,683 hospital days included, and 28.3% (n = 5006) were considered ALC. Compared to patients with sALC, those with pALC were older and more likely to be publicly insured, experience homelessness, and have substance use or psychiatric comorbidities. Patients with pALC were more likely to be admitted for care meeting inpatient criteria (89.3% vs. 66.8%, p < .001), had significantly more ALC days (median 8 vs. 1 day, p < .001), and were less likely to be discharged to the community (p < .001). CONCLUSIONS: Patients with prolonged ALC stays were more likely to be admitted for acute care, had greater psychosocial complexity, significantly longer lengths of stay, and unique discharge needs. Given the complexity and needs for hospitalizations with pALC days, intensive interdisciplinary coordination and resource mobilization are necessary.

Visit and Between-Visit Interaction Frequency Before and After COVID-19 Telehealth Implementation.

Importance: Telehealth implementation associated with the COVID-19 public health emergency (PHE) affected patient-clinical team interactions in numerous ways. Yet, studies have narrowly examined billed patient-clinician visits rather than including visits with other team members (eg, pharmacists) or between-visit interactions. Objective: To evaluate rates of change over time in visits (in-person, telehealth) and between-visit interactions (telephone calls, patient portal messages) overall and by key patient characteristics. Design, Setting, and Participants: This retrospective cohort study included adults with diabetes receiving primary care at urban academic (University of California San Francisco [UCSF]) and safety-net (San Francisco Health Network [SFHN]) health care systems. Encounters from April 2019 to March 2021 were analyzed. Exposure: Telehealth implementation over 3 periods: pre-PHE (April 2019 to March 2020), strict shelter-in-place (April to June 2020), and hybrid-PHE (July 2020 to March 2021). Main Outcomes and Measures: The main outcomes were rates of change in monthly mean number of total encounters, visits with any health care team member, visits with billing clinicians, and between-visit interactions. Key patient-level characteristics were age, race and ethnicity, language, and neighborhood socioeconomic status (nSES). Results: Of 15 148 patients (4976 UCSF; 8975 SFHN) included, 2464 (16%) were 75 years or older, 7734 (51%) were female patients, 9823 (65%) self-identified as racially or ethnically minoritized, 6223 (41%) had a non-English language preference, and 4618 (31%) lived in the lowest nSES quintile. After accounting for changes to care delivery through an interrupted time-series analysis, total encounters increased in the hybrid-PHE period (UCSF: 2.3% per patient/mo; 95% CI, 1.6%-2.9% per patient/mo; SFHN: 1.8% per patient/mo, 95% CI, 1.3%-2.2% per patient/mo), associated primarily with growth in between-visit interactions (UCSF: 3.1% per patient/mo, 95% CI, 2.3%-3.8% per patient/mo; SFHN: 2.9% per patient/mo, 95% CI, 2.3%-3.4% per patient/mo). In contrast, rates of visits were stable during the hybrid-PHE period. Although there were fewer differences in visit use by key patient-level characteristics during the hybrid-PHE period, pre-PHE differences in between-visit interactions persisted during the hybrid-PHE period at SFHN. Asian and Chinese-speaking patients at SFHN had fewer monthly mean between-visit interactions compared with White patients (0.46 [95% CI, 0.42-0.50] vs 0.59 [95% CI, 0.53-0.66] between-visit interactions/patient/mo; P < .001) and English-speaking patients (0.52 [95% CI, 0.47-0.58] vs 0.61 [95% CI, 0.56-0.66] between-visit interactions/patient/mo; P = .03). Conclusions and Relevance: In this study, pre-PHE growth in overall patient-clinician encounters persisted after PHE-related telehealth implementation, driven in both periods by between-visit interactions. Differential utilization based on patient characteristics was observed, which may indicate disparities. The implications for health care team workload and patient outcomes are unknown, particularly regarding between-visit interactions. Therefore, to comprehensively understand care utilization for patients with chronic diseases, research should expand beyond billed visits.

Photocatalytic Activity of Ti-SBA-15/C3N4 for Degradation of 2,4-Dichlorophenoxyacetic Acid in Water under Visible Light.

In the present study, the photocatalytic activity of Ti-SBA-15/C3N4 catalysts was investigated to degrade 2,4-Dichlorophenoxyacetic acid (2,4-D) herbicides in water under visible light irradiation. The catalysts were synthesized via a simple hydrothermal method and characterized by various analytical techniques, including SAXS, N2 adsorption-desorption isotherms, Zeta potential, PL, FT-IR, XRF, TGA, and UV-DRS. Our study indicated that the 2.5Ti-SBA-15/C3N4 had higher efficiency in the degradation of 2,4-D than Ti-SBA-15 and C3N4. The decomposition of 2,4-D reached 60% under 180 minutes of visible light irradiation at room temperature on 2.5Ti-SBA-15/C3N4. Moreover, the degradation of 2,4-D on Ti-SBA-15/C3N4 was pseudo-first-order kinetics with the highest rate constant (0.00484 min-1), which was much higher than that obtained for other photocatalysts reported recently. Furthermore, the catalyst can be reused at least two times for photodegradation of 2,4-D solution under visible light irradiation within a slight decrease in catalytic activity.

Social Determinants of Health and 30-Day Readmissions Among Adults Hospitalized for Heart Failure in the REGARDS Study.

BACKGROUND: It is not known which social determinants of health (SDOH) impact 30-day readmission after a heart failure (HF) hospitalization among older adults. We examined the association of 9 individual SDOH with 30-day readmission after an HF hospitalization. METHODS AND RESULTS: Using the REGARDS study (Reasons for Geographic and Racial Differences in Stroke), we included Medicare beneficiaries who were discharged alive after an HF hospitalization between 2003 and 2014. We assessed 9 SDOH based on the Healthy People 2030 Framework: race, education, income, social isolation, social network, residential poverty, Health Professional Shortage Area, rural residence, and state public health infrastructure. The primary outcome was 30-day all-cause readmission. For each SDOH, we calculated incidence per 1000 person-years and multivariable-adjusted hazard ratios of readmission. Among 690 participants, the median age was 76 years at hospitalization (interquartile range, 71-82), 44.3% were women, 35.5% were Black, 23.5% had low educational attainment, 63.0% had low income, 21.0% had zip code-level poverty, 43.5% resided in Health Professional Shortage Areas, 39.3% lived in states with poor public health infrastructure, 13.1% were socially isolated, 13.3% had poor social networks, and 10.2% lived in rural areas. The 30-day readmission rate was 22.4%. In an unadjusted analysis, only Health Professional Shortage Area was significantly associated with 30-day readmission; in a fully adjusted analysis, none of the 9 SDOH were individually associated with 30-day readmission. CONCLUSIONS: In this modestly sized national cohort, although prevalent, none of the SDOH were associated with 30-day readmission after an HF hospitalization. Policies or interventions that only target individual SDOH to reduce readmissions after HF hospitalizations may not be sufficient to prevent readmission among older adults.

Time to ACT: launching an Addiction Care Team (ACT) in an urban safety-net health system.

Across the USA, morbidity and mortality from substance use are rising as reflected by increases in acute care hospitalisations for substance use complications and substance-related deaths. Patients with substance use disorders (SUD) have long and costly hospitalisations and higher readmission rates compared to those without SUD. Hospitalisation presents an opportunity to diagnose and treat individuals with SUD and connect them to ongoing care. However, SUD care often remains unaddressed by hospital providers due to lack of a systems approach and addiction medicine knowledge, and is compounded by stigma. We present a blueprint to launching an interprofessional inpatient addiction care team embedded in the hospital medicine division of an urban, safety-net integrated health system. We describe key factors for successful implementation including: (1) demonstrating the scope and impact of SUD in our health system via a needs assessment; (2) aligning improvement areas with health system leadership priorities; (3) involving executive leadership to create goal and initiative alignment; and (4) obtaining seed funding for a pilot programme from our Medicaid health plan partner. We also present challenges and lessons learnt.

Incidence, Predictors, and Outcomes of Hospital-Acquired Anemia.

BACKGROUND: Although hypothesized to be a hazard of hospitalization, it is unclear whether hospital-acquired anemia (HAA) is associated with increased adverse outcomes following discharge. OBJECTIVE: To examine the incidence, predictors, and postdischarge outcomes associated with HAA. DESIGN: Observational cohort study using electronic health record data. SUBJECTS: Consecutive medicine discharges between November 1, 2009 and October 30, 2010 from 6 Texas hospitals, including safety-net, teaching, and nonteaching sites. Patients with anemia on admission or missing hematocrit values at admission or discharge were excluded. MEASURES: HAA was defined using the last hematocrit value prior to discharge and categorized by severity. The primary outcome was a composite of 30-day mortality and nonelective readmission. RESULTS: Among 11,309 patients, one-third developed HAA (21.6% with mild HAA; 10.1% with moderate HAA; and 1.4% with severe HAA). The 2 strongest potentially modifiable predictors of developing moderate or severe HAA were length of stay (adjusted odds ratio [OR], 1.26 per day; 95% confidence interval [CI], 1.23-1.29) and receipt of a major procedure (adjusted OR, 5.09; 95% CI, 3.79-6.82). Patients without HAA had a 9.7% incidence for the composite outcome versus 16.4% for those with severe HAA. Severe HAA was independently associated with a 39% increase in the odds for 30-day readmission or death (95% CI, 1.09-1.78). Most patients with severe HAA (85%) underwent a major procedure, had a discharge diagnosis of hemorrhage, and/or a discharge diagnosis of hemorrhagic disorder. CONCLUSIONS: Severe HAA is associated with increased odds for 30-day mortality and readmission after discharge; however, it is uncertain whether severe HAA is preventable. Journal of Hospital Medicine 2017;12:317-322.

The prevalence and risk behaviours associated with the transmission of blood-borne viruses among ethnic-Vietnamese injecting drug users.

OBJECTIVE: To measure the prevalence and determinants of blood-borne virus (BBV) transmission in ethnic Vietnamese injecting drug users (IDUs). METHODS: The study was conducted in Melbourne, Australia, in 2003. It was a cross-sectional design with participants recruited from street-based illicit drug markets predominately using a snowball technique. One hundred and twenty-seven participants completed a questionnaire that asked about illicit drug use and participants' blood samples were tested for HIV, HCV and HBV. RESULTS: One hundred and three (81.1%) ethnic Vietnamese IDU study participants were HCV positive and three (2.4%) were HIV positive. More than 60% had evidence of being infected with HBV (either in the past, acute infection or chronic infection). Almost 60% had injected daily over the past 12 months. Fifty-nine participants had recently travelled to Vietnam; 24 (41%) had injected drugs in Vietnam; and three (12.5%) reported sharing injecting equipment in Vietnam. CONCLUSION: The prevalence of BBVs was higher in this study's IDU population compared with IDUs in Australia generally, despite the fact that the injecting risk behaviours were similar to IDUs more generally. IMPLICATIONS: Culturally sensitive drug treatment and education programs need to be developed in Australia for both ethnic Vietnamese IDUs and their families to reduce this group's risk of contracting a BBV.

Predicting the Risk of Readmission in Pneumonia. A Systematic Review of Model Performance.

RATIONALE: Predicting which patients are at highest risk for readmission after hospitalization for pneumonia could enable hospitals to proactively reallocate scarce resources to reduce 30-day readmissions. OBJECTIVES: To synthesize the available literature on readmission risk prediction models for adults who are hospitalized because of pneumonia and describe their performance. METHODS: We systematically searched Ovid MEDLINE, Embase, The Cochrane Library, and Cumulative Index to Nursing and Allied Health Literature databases from inception through July 2015. We included studies of adults discharged with pneumonia that developed or validated a model that predicted hospital readmission. Two independent reviewers abstracted data and assessed the risk of bias. MEASUREMENTS AND MAIN RESULTS: Of 992 citations reviewed, 7 studies met inclusion criteria, which included 11 unique risk prediction models. All-cause 30-day readmission rates ranged from 11.8 to 20.8% (median, 17.3%). Model discrimination (C statistic) ranged from 0.59 to 0.77 (median, 0.63) with the highest-quality, best-validated model, the Centers for Medicare and Medicaid Services Pneumonia Administrative Model performing modestly (C Statistic of 0.63 in 4 separate multicenter cohorts). The best performing model (C statistic of 0.77) was a single-site study that lacked internal validation. The models had adequate calibration, with patients predicted as high risk for readmission having a higher average observed readmission rate than those predicted to be low risk. None of the studies included pneumonia illness severity scores, and only one included measures of in-hospital clinical trajectory and stability on discharge, robust predictors of readmission. CONCLUSIONS: We found a limited number of validated pneumonia-specific readmission models, and their predictive ability was modest. To improve predictive accuracy, future models should include measures of pneumonia illness severity, hospital complications, and stability on discharge.

Transient and progressive electrophysiological alterations in the corticostriatal pathway in a mouse model of Huntington's disease.

Alterations in the corticostriatal pathway may precede symptomatology and striatal cell death in Huntington's disease (HD) patients. Here we examined spontaneous EPSCs in striatal medium-sized spiny neurons in slices from a mouse model of HD (R6/2). Spontaneous EPSC frequency was similar in young (3-4 weeks) transgenics and controls but decreased significantly in transgenics when overt behavioral symptoms began (5-7 weeks) and was most pronounced in severely impaired transgenics (11-15 weeks). These differences were maintained after bicuculline or tetrodotoxin, indicating they were specific to glutamatergic input and likely presynaptic in origin. Decreases in presynaptic and postsynaptic protein markers, synaptophysin and postsynaptic density-95, occurred in 11-15 week R6/2 mice, supporting the electrophysiological results. Furthermore, isolated, large-amplitude synaptic events (>100 pA) occurred more frequently in transgenic animals, particularly at 5-7 weeks, suggesting additional dysregulation of cortical inputs. Large events were blocked by tetrodotoxin, indicating a possible cortical origin. Addition of bicuculline and 4-aminopyridine facilitated the occurrence of large events. Riluzole, a compound that decreases glutamate release, reduced these events. Together, these observations indicate that both progressive and transient alterations occur along the corticostriatal pathway in experimental HD. These alterations are likely to contribute to the selective vulnerability of striatal medium-sized spiny neurons.

Use of cardiac biomarker testing in the emergency department.

IMPORTANCE: Cardiac biomarker testing is not routinely indicated in the emergency department (ED) because of low utility and potential downstream harms from false-positive results. However, current rates of testing are unknown. OBJECTIVE: To determine the use of cardiac biomarker testing overall, as well as stratified by disposition status and selected characteristics. DESIGN, SETTING, AND PARTICIPANTS: Retrospective study of ED visits by adults (≥18 years old) selected from the 2009 and 2010 National Hospital Ambulatory Medical Care Survey, a probability sample of ED visits in the United States. EXPOSURES: Selected patient, visit, and ED characteristics. MAIN OUTCOMES AND MEASURES: Receipt of cardiac biomarker testing during the ED visit. RESULTS: Of 44,448 ED visits, cardiac biomarkers were tested in 16.9% of visits, representing 28.6 million visits. Biomarker testing occurred in 8.2% of visits in the absence of acute coronary syndrome (ACS)-related symptoms, representing 8.5 million visits, almost one-third of all visits with biomarker testing. Among individuals subsequently hospitalized, cardiac biomarkers were tested in 47.0% of all visits. In this group, biomarkers were tested in 35.4% of visits despite the absence of ACS-related symptoms. Among all ED visits, the number of other tests or services performed was the strongest predictor of biomarker testing independent of symptoms of ACS. Compared with 0 to 5 other tests or services performed, more than 10 other tests or services performed was associated with 59.55 (95% CI, 39.23-90.40) times the odds of biomarker testing. The adjusted probabilities of biomarker testing if 0 to 5, 6 to 10, or more than 10 other tests or services performed were 6.3%, 34.3%, and 62.3%, respectively. CONCLUSIONS AND RELEVANCE: Cardiac biomarker testing in the ED is common even among those without symptoms suggestive of ACS. Cardiac biomarker testing is also frequently used during visits with a high volume of other tests or services independent of the clinical presentation. More attention is needed to develop strategies for appropriate use of cardiac biomarkers.

Diagnostic accuracy and effectiveness of automated electronic sepsis alert systems: A systematic review.

BACKGROUND: Although timely treatment of sepsis improves outcomes, delays in administering evidence-based therapies are common. PURPOSE: To determine whether automated real-time electronic sepsis alerts can: (1) accurately identify sepsis and (2) improve process measures and outcomes. DATA SOURCES: We systematically searched MEDLINE, Embase, The Cochrane Library, and Cumulative Index to Nursing and Allied Health Literature from database inception through June 27, 2014. STUDY SELECTION: Included studies that empirically evaluated 1 or both of the prespecified objectives. DATA EXTRACTION: Two independent reviewers extracted data and assessed the risk of bias. Diagnostic accuracy of sepsis identification was measured by sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and likelihood ratio (LR). Effectiveness was assessed by changes in sepsis care process measures and outcomes. DATA SYNTHESIS: Of 1293 citations, 8 studies met inclusion criteria, 5 for the identification of sepsis (n = 35,423) and 5 for the effectiveness of sepsis alerts (n = 6894). Though definition of sepsis alert thresholds varied, most included systemic inflammatory response syndrome criteria ± evidence of shock. Diagnostic accuracy varied greatly, with PPV ranging from 20.5% to 53.8%, NPV 76.5% to 99.7%, LR+ 1.2 to 145.8, and LR- 0.06 to 0.86. There was modest evidence for improvement in process measures (ie, antibiotic escalation), but only among patients in non-critical care settings; there were no corresponding improvements in mortality or length of stay. Minimal data were reported on potential harms due to false positive alerts. CONCLUSIONS: Automated sepsis alerts derived from electronic health data may improve care processes but tend to have poor PPV and do not improve mortality or length of stay.

Trends in Long-Term Acute Care Hospital Use in Texas from 2002-2011.

OBJECTIVE: To assess regional trends in long-term acute care hospital (LTAC) use over time. DESIGN SETTING PARTICIPANTS: Retrospective study using 100% Texas Medicare data. Separate cohorts were created for each year from 2002-2011, which included all beneficiaries residing in 23 hospital referral regions (HRRs) with continuous enrollment in Parts A and B in the previous and current year, or until death. MEASUREMENTS: LTAC utilization rate was defined as the number of individuals with a LTAC stay per 100,000 Medicare beneficiaries residing in the HRR. Baseline LTAC use at the HRR-level was categorized by tertiles of use in 2002. RESULTS: Overall, LTAC use increased 35% from 2002-2011 and coincided with major Medicare policy changes. However, there were marked regional differences in LTAC utilization trends. From 2002-2011, HRRs in the lowest tertile of baseline LTAC use, which included regions with 0 to 1 LTAC facilities in 2002, had an increase in utilization by 211%, from 190 to 591 individuals per 100,000 persons. In contrast, HRRs in the highest tertile of baseline LTAC use, which included some of the most densely LTAC-bedded regions in the country, experienced a 21% decline (915 to 719 individuals per 100,000 persons; p<0.001 for interaction of LTAC utilization and tertile of baseline use). CONCLUSION: These findings suggest substantial regional variation in the trends in LTAC use over time. Further research is needed to estimate how much of this variation is due to differences in clinical need due to increasing number of severely ill older adults versus regional market supply.