Discussion: Variability in Catheter Associated Asymptomatic Bacteriuria Rates

Discussion: Variability in Catheter Associated Asymptomatic Bacteriuria Rates ORDER NOW FOR CUSTOMIZED AND ORIGINAL ESSAY PAPERS ON Discussion: Variability in Catheter Associated Asymptomatic Bacteriuria Rates I’m working on a Health & Medical exercise and need support. Discussion: Variability in Catheter Associated Asymptomatic Bacteriuria Rates Create two annotated bibliographies based on the health topics attached. Summarize the research study in your own words (at least 200 words). Include the major areas of the research study, such as the sample, geographic location, research purpose, question, hypotheses, methodology/design, sampling method, data collection, analyses, findings, conclusion & recommendations. Bibliographies should not include any direct quotes or in-text citation. health_articl_ii.pdf health_article_i.pdf Research JAMA | Original Investigation Association Between State-Mandated Protocolized Sepsis Care and In-hospital Mortality Among Adults With Sepsis Jeremy M. Kahn, MD, MS; Billie S. Davis, PhD; Jonathan G. Yabes, PhD; Chung-Chou H. Chang, PhD; David H. Chong, MD; Tina Batra Hershey, JD, MPH; Grant R. Martsolf, PhD, MPH, RN; Derek C. Angus, MD, MPH Editor’s Note page 250 IMPORTANCE Beginning in 2013, New York State implemented regulations mandating that Supplemental content hospitals implement evidence-based protocols for sepsis management, as well as report data on protocol adherence and clinical outcomes to the state government. The association between these mandates and sepsis outcomes is unknown. OBJECTIVE To evaluate the association between New York State sepsis regulations and the outcomes of patients hospitalized with sepsis. DESIGN, SETTING, AND PARTICIPANTS Retrospective cohort study of adult patients hospitalized with sepsis in New York State and in 4 control states (Florida, Maryland, Massachusetts, and New Jersey) using all-payer hospital discharge data (January 1, 2011-September 30, 2015) and a comparative interrupted time series analytic approach. EXPOSURES Hospitalization for sepsis before (January 1, 2011-March 31, 2013) vs after (April 1, 2013-September 30, 2015) implementation of the 2013 New York State sepsis regulations. MAIN OUTCOMES AND MEASURES The primary outcome was 30-day in-hospital mortality. Secondary outcomes were intensive care unit admission rates, central venous catheter use, Clostridium difficile infection rates, and hospital length of stay. RESULTS The final analysis included 1 012 410 sepsis admissions to 509 hospitals. The mean age was 69.5 years (SD, 16.4 years) and 47.9% were female. In New York State and in the control states, 139 019 and 289 225 patients, respectively, were admitted before implementation of the sepsis regulations and 186 767 and 397 399 patients, respectively, were admitted after implementation of the sepsis regulations. Unadjusted 30-day in-hospital mortality was 26.3% in New York State and 22.0% in the control states before the regulations, and was 22.0% in New York State and 19.1% in the control states after the regulations. Adjusting for patient and hospital characteristics as well as preregulation temporal trends and season, mortality after implementation of the regulations decreased significantly in New York State relative to the control states (P = .02 for the joint test of the comparative interrupted time series estimates). For example, by the 10th quarter after implementation of the regulations, adjusted absolute mortality was 3.2% (95% CI, 1.0% to 5.4%) lower than expected in New York State relative to the control states (P = .004). Discussion: Variability in Catheter Associated Asymptomatic Bacteriuria Rates The regulations were associated with no significant differences in intensive care unit admission rates (P = .09) (10th quarter adjusted difference, 2.8% [95% CI, ?1.7% to 7.2%], P = .22), a significant relative decrease in hospital length of stay (P = .04) (10th quarter adjusted difference, 0.50 days [95% CI, ?0.47 to 1.47 days], P = .31), a significant relative decrease in the C difficile infection rate (P < .001) (10th quarter adjusted difference, ?1.8% [95% CI, ?2.6% to ?1.0%], P < .001), and a significant relative increase in central venous catheter use (P = .02) (10th quarter adjusted difference, 4.8% [95% CI, 2.3% to 7.4%], P < .001). CONCLUSIONS AND RELEVANCE In New York State, mandated protocolized sepsis care was associated with a greater decrease in sepsis mortality compared with sepsis mortality in control states that did not implement sepsis regulations. Because baseline mortality rates differed between New York and comparison states, it is uncertain whether these findings are generalizable to other states. JAMA. 2019;322(3):240-250. doi:10.1001/jama.2019.9021 240 Author Affiliations: Author affiliations are listed at the end of this article. Corresponding Author: Jeremy M. Kahn, MD, MS, University of Pittsburgh, 3550 Terrace St, Scaife Hall, Room 602-B, Pittsburgh, PA 15261 (jeremykahn@pitt.edu). (Reprinted) jama.com © 2019 American Medical Association. All rights reserved. Association Between State-Mandated Protocolized Sepsis Care and In-hospital Adult Sepsis Mortality S epsis is a leading cause of morbidity and mortality in the United States. 1 Several treatments are of proven effectiveness in this population, including timely administration of antibiotics and early resuscitation with intravenous fluids.2 However, many patients with sepsis do not receive these evidence-based practices, leading to excess morbidity and mortality.3-5 To address this problem, policy makers are increasingly turning to regulatory mechanisms designed to mandate sepsis performance improvement in the form of care protocols for early recognition and treatment.6 A pioneering example of these mandates is the regulations issued by the New York State Department of Health during May 2013, known as Rory’s Regulations after a 12-year-old boy who died of sepsis.7 These regulations require all acute care hospitals in the state to develop and implement protocols for timely recognition and treatment of sepsis, including administration of antibiotics by 3 hours and resuscitation with intravenous fluid by 6 hours for patients with signs of hypoperfusion. The regulations also require hospitals to routinely train their staff in protocol implementation and report both protocol adherence and clinical outcomes to the state’s department of health. Although timely sepsis treatment is supported by robust observational and clinical trial data,8-10 the role of governmental mandates as a strategy to enforce the use of sepsis protocols remains controversial.11 Sepsis mandates could encourage uptake of evidence-based care practices, leading to reduced mortality, but could also encourage overuse of intravenous fluids and antibiotics, leading to adverse consequences.7 Discussion: Variability in Catheter Associated Asymptomatic Bacteriuria Rates The goal of this study was to examine sepsis outcomes before and after implementation of the sepsis regulations in New York State, comparing these changes with the outcomes in other states that did not implement sepsis regulations during this time. Methods Study Design We performed a retrospective cohort study of hospitalized patients with sepsis. The study was approved by the University of Pittsburgh Human Research Protection Office, which deemed the study exempt from human subjects review because it was a secondary analysis of existing data and waived the need for informed consent (PRO17110272). We used a comparative interrupted time series study design, comparing New York State with the 4 control states of Florida, Maryland, Massachusetts, and New Jersey. These control states were chosen because they have similar demographic characteristics to New York and, except for Florida, they are geographically proximal to New York. A comparative interrupted time series study compares the longitudinal outcome changes between an intervention group and a control group, thereby subtracting underlying secular trends and any other changes that may have occurred in both groups. By using this approach, we were able make inferences about the regulations that would not be possible using New York State data alone.12 jama.com Original Investigation Research Key Points Question Were the 2013 New York State regulations mandating the use of protocols for sepsis recognition and treatment associated with in-hospital mortality differences compared with states that did not implement sepsis regulations? Findings In this retrospective cohort study of 1 012 410 hospitalized adults with sepsis, mandated protocolized sepsis care in New York State was associated with a significantly greater decline in risk-adjusted mortality in New York compared with a group of control states that did not implement mandated protocolized sepsis care. By the 10th quarter after implementation of the regulations, the adjusted absolute mortality was 3.2% lower than expected in New York State relative to the control states. Meaning The New York State sepsis regulations were associated with significantly reduced sepsis mortality, but whether broader adoption of state-level sepsis mandates in other states would lead to further reductions in sepsis-related mortality is unknown. To support the rigor and reproducibility of our results, all analyses were prespecified prior to receipt of the final data set and a detailed statistical analysis plan (Supplement 1) was published online13 (additional details appear in the eMethods in Supplement 2). Discussion: Variability in Catheter Associated Asymptomatic Bacteriuria Rates Deviations from this plan due to unforeseen circumstances are noted as post hoc, and a rationale for all deviations appears in the eMethods in Supplement 2. Data Sources Our primary data source was the Agency for Healthcare Research and Quality’s Healthcare Cost and Utilization Project State Inpatient Database. The State Inpatient Database contains patient-level administrative data for all hospitalizations in participating states. We used the State Inpatient Database to identify hospitalizations that occurred from January 1, 2011, through September 30, 2015. We linked the data from the State Inpatient Database to hospital-level data from the 2015 Centers for Medicare & Medicaid Healthcare Cost Reporting Information System to obtain hospital characteristics such as hospital type, number of beds, and academic status; and used the 2010 US Census to obtain data on each hospital’s metropolitan statistical area population. Patients and Hospitals We identified hospital admissions with sepsis using validated International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis and procedure codes for infection and organ failure.14 This strategy, known as the Dombrovskiy strategy, is less specific but more sensitive than approaches that rely solely on the explicit ICD9-CM codes for sepsis,15 and captures a slightly larger patient population than is identified by retrospective chart review.16 In choosing a broad sepsis identification strategy, we sought to account for the fact that many patients with sepsis may be missed by chart review yet are still eligible for evidencebased practices. We excluded admissions for patients younger than 18 years, admissions to hospitals that could not be identified in the Healthcare Cost Reporting Information System, and admissions with missing data for key (Reprinted) JAMA July 16, 2019 Volume 322, Number 3 © 2019 American Medical Association. All rights reserved. 241 Research Original Investigation Association Between State-Mandated Protocolized Sepsis Care and In-hospital Adult Sepsis Mortality covariates. We further excluded hospitals that were not classified as short-stay acute care hospitals by the Healthcare Cost Reporting Information System, hospitals with no sepsis admissions, and, to create a more homogenous sample, hospital types that were not shared across New York State and the control states both before and after the introduction of the regulations (more detail on this process appears in the eMethods in Supplement 2). Discussion: Variability in Catheter Associated Asymptomatic Bacteriuria Rates Outcomes The primary outcome variable was 30-day in-hospital mortality. We also examined 4 secondary outcome variables that reflected potential adverse unintended consequences of the regulations: intensive care unit (ICU) admission rate, hospital length of stay, central venous catheter use, and Clostridium difficile infection rate. The ICU admission rates were examined as a marker for health care intensity because data suggest that protocolized sepsis treatment may increase ICU admissions.17 Hospital length of stay was examined as a proxy for resource use because data suggest that protocolized sepsis treatment may increase hospital costs.18 Rates for central venous catheter use were examined based on the hypothesis that the sepsis mandate could lead to an increase in invasive central catheter insertion for monitoring and resuscitation. 11 C difficile infection rates were examined based on the hypothesis that the sepsis mandate may encourage antibiotic overuse, leading to an increase in cases of C difficile infection.11 Additional Variables Variables for case-mix adjustment were based on a previously published risk-adjustment model for sepsis,19 and included age; sex; race and ethnicity; admission through the emergency department; transfer from an acute care hospital; cases of organ failure present at admission, which were defined similar to the study by Elias et al20; sepsis infection categories, which were defined similar to the study by Ames et al21; and Elixhauser chronic comorbid conditions.22 We included race as a potential confounder based on prior studies demonstrating an independent relationship between race and sepsis outcomes.23 Race and ethnicity were obtained directly from the hospital discharge record, which is based on patient selfreport either directly or via the patient’s primary insurer. A full list of variables and their definitions appears in eTable 1 in Supplement 2. Statistical Analysis Primary Analysis The hospital characteristics were compared between New York State and the control states using the ?2 test. We examined patient characteristics between New York State and the control states before and after implementation of the regulations, but did not formally test for differences because the large sample size made it likely that all tests would be significant. For cases in which unexpected differences were found between New York State and the control states, additional post hoc comparisons were performed to better understand and provide additional context for the results. 242 A comparative interrupted time series analysis was performed to test the relationship between the New York State sepsis regulations and outcomes. 24,25 We performed the analysis separately for each outcome variable described above. In specifying the models, we accounted for the possibility that the association between the regulations and the outcomes might change over time due to their staged implementation (eTable 2 in Supplement 2 contains a complete policy timeline). Accordingly, rather than specifying a single postimplementation temporal trend, we fit a model with indicators for each postimplementation quarter.Discussion: Variability in Catheter Associated Asymptomatic Bacteriuria Rates 26,27 The preimplementation period was defined as hospital discharge from January 1, 2011, through March 31, 2013, before the filing of the regulations. The postimplementation period was defined as hospital discharge from April 1, 2013, through September 30, 2015. All models were fit using linear regression with robust standard errors clustered at the hospital level. For binary outcomes, this approach corresponds to a linear probability model and the coefficients represent the between-group absolute risk differences. All models controlled for the patient and hospital characteristics listed above, as well as seasonality based on calendar quarter.28 We also controlled for preregulation temporal trends using a continuous time variable, implemented as quarters, as well as a treatment indicator × continuous time variable interaction term. This approach accounts for the fact that sepsis outcomes were generally improving over time,29 as well as the possibility that preimplementation temporal trends might differ between New York State and the control states.26,27 To test the association between the regulations and the patient outcomes, we included a postimplementation quarter × intervention group interaction term (ie, New York State vs the control states). The estimates for these interaction terms are interpreted as the difference in the deviations from the counterfactual preregulation trend between New York State and the control states during that quarter; or, more simply, the estimated association between the regulations and the patient outcomes during the given quarter. The primary test of the association between the regulations and the patient outcomes was a joint test that all of the quarterspecific estimates were equal to zero. To understand the direction and magnitude of any observed overall associations, we also calculated point estimates and 95% CIs for each individual interaction term. The results from the 10th quarter after implementation (ie, during 2015, quarter 3) are highlighted herein as a representative example of the quarter-specific associations. The comparative interrupted time series model can be simplified to a traditional difference-in-differences model if trends for the outcomes were parallel in New York State and in the control states prior to the regulations. We directly examined for this possibility by fitting a model containing a treatment indicator, a continuous time variable, the interaction of these 2 variables, and all patient- and hospital-level covariates, restricted to the preregulation period. We did this separately for each outcome. We considered parallel trends as being present if the interaction term from this JAMA July 16, 2019 Volume 322, Number 3 (Reprinted) © 2019 American Medical Association. Discussion: Variability in Catheter Associated Asymptomatic Bacteriuria Rates All rights reserved. jama.com Association Between State-Mandated Protocolized Sepsis Care and In-hospital Adult Sepsis Mortality model was not significant. In cases in which there were parallel trends, we simplified the comparative interrupted time series model to a difference-in-differences model by excluding the term for the interaction of the treatment indicator with the continuous time variable.26,27 The P values from the tests of parallel trends and the respective models used are presented alongside the model results. Secondary and Sensitivity Analyses A concern regarding the use of administrative codes to identify sepsis is that the regulations could have changed sepsis coding patterns, potentially biasing the results. To understand this issue, a secondary analysis was performed in which we fit a similar model as described above, except with all adult hospital admissions as the population and an indicator for sepsis as the primary dependent variable. A negative test of the interaction terms would indicate that the regulations were not associated with changes in administrative coding for sepsis. A number of prespecified sensitivity analyses were also performed to examine the robustness of the results to our design decisions. Specifically, we repeated the primary analysis, limiting the sample to patients with severe sepsis and septic shock as defined using the ICD-9-CM codes that explicitly identify sepsis and septic shock15; expanding the sample to patients with sepsis according to a broader definition that includes additional organ failures15; excluding New York City hospitals that had participated in an earlier Greater New York Hospital Association sepsis quality improvement initiative30; and shifting the preimplementation period back in time by 2 quarters to account for the possibility that hospitals began implementing the regulations when they were first announced. One post hoc sensitivity analysis was performed, restricting the control states to those with preregulation temporal trends that were most similar to New York to account for the possibility that the results were driven by unmeasured differences between New York State and the control states. In addition, we performed subgroup analyses on our primary model based on age, number of comorbidities, number of organ failures, emergency department use, hospital size, hospital academic status, and hospital sepsis volume. For each subgroup, we tested for heterogeneity of the association between the regulations and patient outcomes using 3-way interaction terms and applying the Bonferroni method to correct for multiple comparisons. Because of the potential for type I error due to multiple comparisons, findings for the analyses of the secondary end points should be interpreted as exploratory. Additional details about the modeling strategy appear in Supplement 1 and in the eMethods in Supple … Get a 10 % discount on an order above $ 100 Use the following coupon code : NURSING10