Temporal trends in the systemic inflammatory response syndrome, sepsis, and medical coding of sepsis

Improving Sepsis Outcomes in the Era of Pay-for-Performance and Electronic Quality Measures: A Joint IDSA/ACEP/PIDS/SHEA/SHM/SIDP Position Paper

The Centers for Medicare & Medicaid Services (CMS) introduced the Severe Sepsis/Septic Shock Management Bundle (SEP-1) as a pay-for-reporting measure in 2015 and is now planning to make it a pay-for-performance measure by incorporating it into the Hospital Value-Based Purchasing Program. This joint IDSA/ACEP/PIDS/SHEA/SHM/SIPD position paper highlights concerns with this change. Multiple studies indicate that SEP-1 implementation was associated with increased broad-spectrum antibiotic use, lactate measurements, and aggressive fluid resuscitation for patients with suspected sepsis but not with decreased mortality rates. Increased focus on SEP-1 risks further diverting attention and resources from more effective measures and comprehensive sepsis care. We recommend retiring SEP-1 rather than using it in a payment model and shifting instead to new sepsis metrics that focus on patient outcomes. CMS is developing a community-onset sepsis 30-day mortality electronic clinical quality measure (eCQM) that is an important step in this direction. The eCQM preliminarily identifies sepsis using systemic inflammatory response syndrome (SIRS) criteria, antibiotic administrations or diagnosis codes for infection or sepsis, and clinical indicators of acute organ dysfunction. We support the eCQM but recommend removing SIRS criteria and diagnosis codes to streamline implementation, decrease variability between hospitals, maintain vigilance for patients with sepsis but without SIRS, and avoid promoting antibiotic use in uninfected patients with SIRS. We further advocate for CMS to harmonize the eCQM with the Centers for Disease Control and Prevention's (CDC) Adult Sepsis Event surveillance metric to promote unity in federal measures, decrease reporting burden for hospitals, and facilitate shared prevention initiatives. These steps will result in a more robust measure that will encourage hospitals to pay more attention to the full breadth of sepsis care, stimulate new innovations in diagnosis and treatment, and ultimately bring us closer to our shared goal of improving outcomes for patients.

Blood culture utilization practices among febrile and/or hypothermic inpatients

Background

Predictors associated with the decision of blood culture ordering among hospitalized patients with abnormal body temperature are still underexplored, particularly non-clinical factors. In this study, we evaluated the factors affecting blood culture ordering in febrile and hypothermic inpatients.

Methods

We performed a retrospective study of 15,788 adult inpatients with fever (≥ 38.3℃) or hypothermia (< 36.0℃) from January 2016 to December 2017. We evaluated the proportion of febrile and hypothermic episodes with an associated blood culture performed within 24h. Generalized Estimating Equations were used to determine independent predictors associated with blood culture ordering among febrile and hypothermic inpatients.

Results

We identified 21,383 abnormal body temperature episodes among 15,788 inpatients (13,093 febrile and 8,290 hypothermic episodes). Blood cultures were performed in 36.7% (7,850/ 21,383) of these episodes. Predictors for blood culture ordering among inpatients with abnormal body temperature included fever ≥ 39℃ (adjusted odd ratio [aOR] 4.17, 95% confident interval [CI] 3.91–4.46), fever (aOR 3.48, 95% CI 3.27–3.69), presence of a central venous catheter (aOR 1.36, 95% CI 1.30–1.43), systemic inflammatory response (SIRS) plus hypotension (aOR 1.33, 95% CI 1.26–1.40), SIRS (aOR 1.26, 95% CI 1.20–1.31), admission to stem cell transplant / medical oncology services (aOR 1.09, 95% CI 1.04–1.14), and detection of abnormal body temperature during night shift (aOR 1.06, 95% CI 1.03–1.09) or on the weekend (aOR 1.05, 95% CI 1.01–1.08).

Conclusion

Blood culture ordering for hospitalized patients with fever or hypothermia is multifactorial; both clinical and non-clinical factors. These wide variations and gaps in practices suggest opportunities to improve utilization patterns.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07748-x.

Predicting in-hospital mortality in ICU patients with sepsis using gradient boosting decision tree

Sepsis is a leading cause of mortality in the intensive care unit. Early prediction of sepsis can reduce the overall mortality rate and cost of sepsis treatment. Some studies have predicted mortality and development of sepsis using machine learning models. However, there is a gap between the creation of different machine learning algorithms and their implementation in clinical practice.This study utilized data from the Medical Information Mart for Intensive Care III. We established and compared the gradient boosting decision tree (GBDT), logistic regression (LR), k-nearest neighbor (KNN), random forest (RF), and support vector machine (SVM).A total of 3937 sepsis patients were included, with 34.3% mortality in the Medical Information Mart for Intensive Care III group. In our comparison of 5 machine learning models (GBDT, LR, KNN, RF, and SVM), the GBDT model showed the best performance with the highest area under the receiver operating characteristic curve (0.992), recall (94.8%), accuracy (95.4%), and F1 score (0.933). The RF, SVM, and KNN models showed better performance (area under the receiver operating characteristic curve: 0.980, 0.898, and 0.877, respectively) than the LR (0.876).The GBDT model showed better performance than other machine learning models (LR, KNN, RF, and SVM) in predicting the mortality of patients with sepsis in the intensive care unit. This could be used to develop a clinical decision support system in the future.

Characterizing Bias Due to Differential Exposure Ascertainment in Electronic Health Record Data

Data derived from electronic health records (EHR) are heterogeneous with availability of specific measures dependent on the type and timing of patients' healthcare interactions. This creates a challenge for research using EHR-derived exposures because gold-standard exposure data, determined by a definitive assessment, may only be available for a subset of the population. Alternative approaches to exposure ascertainment in this case include restricting the analytic sample to only those patients with gold-standard exposure data available (exclusion); using gold-standard data, when available, and using a proxy exposure measure when the gold standard is unavailable (best available); or using a proxy exposure measure for everyone (common data). Exclusion may induce selection bias in outcome/exposure association estimates, while incorporating information from a proxy exposure via either the best available or common data approaches may result in information bias due to measurement error. The objective of this paper was to explore the bias and efficiency of these three analytic approaches across a broad range of scenarios motivated by a study of the association between chronic hyperglycemia and five-year mortality in an EHR-derived cohort of colon cancer survivors. We found that the best available approach tended to mitigate inefficiency and selection bias resulting from exclusion while suffering from less information bias than the common data approach. However, bias in all three approaches can be severe, particularly when both selection bias and information bias are present. When risk of either of these biases is judged to be more than moderate, EHR-based analyses may lead to erroneous conclusions.

Association of the Patient-Centered Medical Home Implementation with Chronic Disease Quality in Patients with Multimorbidity

BACKGROUND

The patient-centered medical home (PCMH) was established in part to improve chronic disease management, yet evidence is limited for effects on patients with multimorbidity.

OBJECTIVE

To examine the association of Patient-Aligned Care Team (PACT) implementation, the Veterans Health Administration (VA) PCMH model, and care quality for multimorbid patients enrolled in VA primary care from 2012 to 2014.

DESIGN

Retrospective cohort.

PATIENTS

318,764 multimorbid (> 3 chronic diseases) patients receiving care in 917 clinics.

MAIN MEASURES

PCMH implementation was measured using the PACT Implementation Progress Index (PI²) for clinics in 2012. The PI² is a validated composite measure of administrative and survey data with higher scores associated with greater care quality. Quality outcomes from 2013 to 2014 were assessed from External Peer Review Program (EPRP) metrics. Outcomes included preventative care, chronic disease management, and mental health and substance use metrics. We used generalized estimating equations to model associations adjusting for patient and clinic characteristics. We also examined associations for a subgroup with > 5 chronic diseases.

KEY RESULTS

For one-third of metrics (5/15), greater implementation of PACT in 2012 was associated with higher predicted probability of meeting the quality metric in 2013-2014. This association persisted for only two metrics (diabetic glycemic control, P < 0.001; lipid control in ischemic heart disease, P = 0.02) among patients with > 5 chronic diseases.

CONCLUSIONS

Multimorbid patients engaged in care from clinics with higher PCMH implementation received higher quality care across several quality domains, but this association was reduced in patients with > 5 chronic diseases.

Implementation of a whole of hospital sepsis clinical pathway in a cancer hospital: impact on sepsis management, outcomes and costs

Infection and sepsis are common problems in cancer management affecting up to 45% of patients and are associated with significant morbidity, mortality and healthcare utilisation.

Objective

To develop and implement a whole of hospital clinical pathway for the management of sepsis (SP) in a specialised cancer hospital and to measure the impact on patient outcomes and healthcare utilisation.

Methods

A multidisciplinary sepsis working party was established. Process mapping of practices for recognition and management of sepsis was undertaken across all clinical areas. A clinical pathway document that supported nurse-initiated sepsis care, prompt antibiotic and fluid resuscitation was implemented. Process and outcome measures for patients with sepsis were collected preimplementation (April-December 2012), postimplementation cohorts (April-December 2013), and from January to December 2014.

Results

323 patients were evaluated (111 preimplementation, 212 postimplementation). More patients with sepsis had lactate measured (75.0% vs 17.2%) and appropriate first dose antibiotic (90.1% vs 76.1%) (all p<0.05). Time to antibiotics was halved (55 vs 110 min, p<0.05). Patients with sepsis had lower rates of intensive care unit admission (17.1% vs 35.5%), postsepsis length of stay (7.5 vs 9.9 days), and sepsis-related mortality (5.0% vs 16.2%) (all p<0.05). Mean total hospital admission costs were lower in the SP cohort, with a significant difference in admission costs between historical and SP non-surgical groups of $A8363 (95% CI 81.02 to 16645.32, p=0.048) per patient on the pathway. A second cohort of 449 patients with sepsis from January to December 2014 demonstrated sustained improvement.

Conclusions

The SP was associated with significant improvement in patient outcomes and reduced costs. The SP has been sustained since 2013, and has been successfully implemented in another hospital with further implementations underway in Victoria.

Nontraumatic Acute Elevation of Pancreatic Enzymes following Percutaneous Nephrolithotomy: A Rare Complication

Herein, we report the case of a 48-year-old female who developed nontraumatic acute pancreatitis following left supracostal Percutaneous Nephrolithotomy. Three hours postoperatively, the patient developed fever with signs and symptoms consistent with hydrothorax, which was confirmed radiologically and was managed conservatively. The following days, the patient developed manifestations of Systemic Inflammatory Response Syndrome with epigastric pain, nausea, and vomiting. Blood, urine, and sputum cultures were negative. Serum amylase and lipase levels were elevated 3 and 13 times above the normal level, respectively. Imaging studies revealed no pathologic findings from pancreas. These findings were consistent with the diagnosis of acute pancreatitis.

Revised National Estimates of Emergency Department Visits for Sepsis in the United States

OBJECTIVES

The emergency department is an important venue for initial sepsis recognition and care. We sought to determine contemporary estimates of the epidemiology of U.S. emergency department visits for sepsis.

DESIGN

Analysis of data from the National Hospital Ambulatory Medical Care Survey.

SETTING

U.S. emergency department visits, 2009-2011.

PATIENTS

Adult (age, ≥ 18 yr) emergency department sepsis patients. We defined serious infection as an emergency department diagnosis of a serious infection or a triage temperature greater than 38°C or less than 36°C. We defined three emergency department sepsis classifications: 1) original emergency department sepsis-serious infection plus emergency department diagnosis of organ dysfunction, endotracheal intubation, or systolic blood pressure less than or equal to 90 mm Hg or explicit sepsis emergency department diagnoses; 2) quick Sequential Organ Failure Assessment emergency department sepsis-serious infection plus presence of at least two "quick" Sequential Organ Failure Assessment criteria (Glasgow Coma Scale ≤ 14, respiratory rate ≥ 22 breaths/min, or systolic blood pressure ≤ 100 mm Hg); and 3) revised emergency department sepsis-original or quick Sequential Organ Failure Assessment emergency department sepsis.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We used survey design and weighting variables to produce national estimates of annual adult emergency department visits using updated sepsis classifications. Over 2009-2011, there were 103,257,516 annual adult emergency department visits. The estimated number of emergency department sepsis visits were as follows: 1) original emergency department sepsis 665,319 (0.64%; 95% CI, 0.57-0.73); 2) quick Sequential Organ Failure Assessment emergency department sepsis 318,832 (0.31%; 95% CI, 0.26-0.37); and 3) revised emergency department sepsis 847,868 (0.82%; 95% CI, 0.74-0.91).

CONCLUSIONS

Sepsis continues to present a major burden to U.S. emergency departments, affecting up to nearly 850,000 emergency department visits annually. Updated sepsis classifications may impact national estimates of emergency department sepsis epidemiology.

Circulating bile acids predict outcome in critically ill patients

Background

Jaundice and cholestatic hepatic dysfunction are frequent findings in critically ill patients associated with increased mortality. Cholestasis in critically ill patients is closely associated with stimulation of pro-inflammatory cytokines resulting in impaired bile secretion and subsequent accumulation of bile acids.

Aim of this study was to evaluate the clinical role of circulating bile acids in critically ill patients.

Methods

Total and individual serum bile acids were assessed via high-performance liquid chromatography in 320 critically ill patients and 19 controls.

Results

Total serum bile acids were threefold higher in septic than cardiogenic shock patients and sixfold higher than in post-surgical patients or controls (p < 0.001). Elevated bile acid levels correlated with severity of illness, renal dysfunction and inflammation (p < 0.05). Total bile acids predicted 28-day mortality independently of sex, age, serum bilirubin and severity of illness (HR 1.041, 95% CI 1.013–1.071, p < 0.005). Best prediction of mortality of total bile acids was seen in patients suffering from septic shock.

Conclusions

Individual and total BAs are elevated by various degrees in different shock conditions. BAs represent an early predictor of short-term survival in a mixed cohort of ICU patients and may serve as marker for early risk stratification in critically ill patients. Future studies should elucidate whether modulation of BA metabolism and signalling influences the clinical course and outcome in critically ill patients.

Electronic supplementary material

The online version of this article (doi:10.1186/s13613-017-0272-7) contains supplementary material, which is available to authorized users.

Serum bile acids as marker for acute decompensation and acute-on-chronic liver failure in patients with non-cholestatic cirrhosis

BACKGROUND & AIMS

Retention of bile acids (BAs) plays a central role in hepatic damage and disturbed BA signalling in liver disease. However, there is lack of data regarding the association of BAs with clinical complications, acute decompensation (AD) and acute-on-chronic liver failure (ACLF). Thus, we aimed to evaluate the impact of circulating serum BAs for complications in patients with cirrhosis.

METHODS

One hundred and forty-three patients with cirrhosis were included in this prospective cohort-type observational study. Total serum BAs and individual BA composition were assessed in all patients on admission via high-performance liquid chromatography. Clinical complications with respect to AD, ACLF and 1-year transplant-free survival were recorded.

RESULTS

Total BAs and individual serum BAs were significantly higher in patients with bacterial infection, AD and ACLF (P<.001) and correlated significantly with model of end-stage liver disease (MELD) and hepatic venous pressure gradient (P<.001). Total BAs predicted new onset of AD or ACLF during follow-up (OR 1.025, 95% CI: 1.012-1.038, P<.001). Best cut-off predicting new onset of AD/ACLF and survival during course of time was total BAs ≥36.9 μmol/L.

CONCLUSIONS

Serum total and individual BAs are associated with AD and ACLF in patients with cirrhosis. Assessment of total BAs could serve as additional marker for risk stratification in cirrhotic patients with respect to new onset of AD and ACLF.

Use of explicit ICD9-CM codes to identify adult severe sepsis: impacts on epidemiological estimates

BACKGROUND

Severe sepsis is a challenge for healthcare systems, and epidemiological studies are essential to assess its burden and trends. However, there is no consensus on which coding strategy should be used to reliably identify severe sepsis. This study assesses the use of explicit codes to define severe sepsis and the impacts of this on the incidence and in-hospital mortality rates.

METHODS

We examined episodes of severe sepsis in adults aged ≥18 years registered in the 2006-2011 national hospital discharge database, identified in an exclusive manner by two ICD-9-CM coding strategies: (1) those assigned explicit ICD-9-CM codes (995.92, 785.52); and (2) those assigned combined ICD-9-CM infection and organ dysfunction codes according to modified Martin criteria. The coding strategies were compared in terms of the populations they defined and their relative implementation. Trends were assessed using Joinpoint regression models and expressed as annual percentage change (APC).

RESULTS

Of 222 846 episodes of severe sepsis identified, 138 517 (62.2 %) were assigned explicit codes and 84 329 (37.8 %) combination codes; incidence rates were 60.6 and 36.9 cases per 100 000 inhabitants, respectively. Despite similar demographic characteristics, cases identified by explicit codes involved fewer comorbidities, fewer registered pathogens, greater extent of organ dysfunction (two or more organs affected in 60 % versus 26 % of cases) and higher in-hospital mortality (54.5 % versus 29 %; risk ratio 1.86, 95 % CI 1.83, 1.88). Between 2006 and 2011, explicit codes were increasingly implemented. Standardised incidence rates in this cohort increased over time with an APC of 12.3 % (95 % CI 4.4, 20.8); in the combination code cohort, rates increased by 3.8 % (95 % CI 1.3, 6.3). A decreasing trend in mortality was observed in both cohorts though the APC was -8.1 % (95 % CI -10.4, -5.7) in the combination code cohort and -3.5 % (95 % CI -3.9, -3.2) in the explicit code cohort.

CONCLUSIONS

Our findings suggest greater and increasing use of explicit codes for adult severe sepsis in Spain. This trend will have substantial impacts on epidemiological estimates, because these codes capture cases featuring greater organ dysfunction and in-hospital mortality.

Sepsis surveillance from administrative data in the absence of a perfect verification

PURPOSE

Past studies of sepsis epidemiology did not address misclassification bias due to imperfect verification of sepsis detection methods to estimate the true prevalence.

METHODS

We examined 273,126 hospitalizations from 2008 to 2012 at a tertiary-care center to develop surveillance-aimed sepsis detection criteria, based on the presence of the sepsis-explicit International Classification of Diseases, Ninth Revision, Clinical Modification codes (995.92 or 785.52), blood culture orders, and antibiotics administration. We used Bayesian multinomial latent class models to estimate the true prevalence of sepsis, while adjusting for the imperfect sensitivity and specificity and the conditional dependence among the individual criteria.

RESULTS

The apparent annual prevalence of sepsis hospitalizations based on explicit International Classification of Diseases, Ninth Revision, Clinical Modification codes were 1.5%, 1.4%, 1.6%, 2.2%, and 2.5% for the years 2008 to 2012. Bayesian posterior estimates for the true prevalence of sepsis suggested that it remained stable from 2008, 19.2% (95% credible interval [CI]: 17.9%, 22.9%), to 2012, 17.8% (95% CI: 16.8%, 20.2%). The sensitivity of sepsis-explicit codes, however, increased from 7.6% (95% CI: 6.4%, 8.4%) in 2008 to 13.8% (95% CI: 12.2%, 14.9%) in 2012.

CONCLUSIONS

The true prevalence of sepsis remained high, but stable despite an increase in the sensitivity of sepsis-explicit codes in administrative data.

Longitudinal Study of the Effects of Bacteremia and Sepsis on 5-year Risk of Cardiovascular Events

BACKGROUND

The long-term and cumulative effect of multiple episodes of bacteremia and sepsis across multiple hospitalizations on the development of cardiovascular (CV) events is uncertain.

METHODS

We conducted a longitudinal study of 156 380 hospitalizations in 47 009 patients (≥18 years old) who had at least 2 inpatient admissions at an academic tertiary care center in St Louis, Missouri, from 1 January 2008 through 31 December 2012. We used marginal structural models, estimated by inverse probability weighting (IPW) of bacteremia or sepsis and IPW of censoring, to estimate the marginal causal effects of bacteremia and sepsis on developing the first observed incident CV event, including stroke, transient ischemic attack, and myocardial infarction (MI), during the study period.

RESULTS

Bacteremia and sepsis occurred during 4923 (3.1%) and 5544 (3.5%) hospitalizations among 3932 (8.4%) and 4474 (9.5%) patients, respectively. CV events occurred in 414 (10.5%) and 538 (12.0%) patients with prior episodes of bacteremia or sepsis, respectively, vs 3087 (7.2%) and 2963 (7.0%) patients without prior episodes of bacteremia or sepsis. The causal odds of experiencing a CV event was 1.52-fold (95% confidence interval [CI], 1.21- to 1.90-fold) and 2.39-fold (95% CI, 1.88- to 3.03-fold) higher in patients with prior instances of bacteremia or sepsis, respectively, compared to those without. Prior instances of septic shock resulted in a 6.91-fold (95% CI, 5.34- to 8.93-fold) increase in the odds of MI.

CONCLUSIONS

Prior instances of bacteremia and sepsis substantially increase the 5-year risk of CV events.

Codifying healthcare--big data and the issue of misclassification

The rise of electronic medical records has led to a proliferation of large observational studies that examine the perioperative period. In contrast to randomized controlled trials, these studies have the ability to provide quick, cheap and easily obtainable information on a variety of patients and are reflective of everyday clinical practice. However, it is important to note that the data used in these studies are often generated for billing or documentation purposes such as insurance claims or the electronic anesthetic record. The reliance on codes to define diagnoses in these studies may lead to false inferences or conclusions. Researchers should specify the code assignment process and be aware of potential error sources when undertaking studies using secondary data sources. While misclassification may be a short-coming of using large databases, it does not prevent their use in conducting meaningful effectiveness research that has direct consequences on medical decision making.