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Sensitivity of the Kaiser Permanente early-onset sepsis calculator: A systematic review and meta-analysis.

ABSTRACT: Background:Determining which babies should receive antibiotics for potential early onset sepsis (EOS) is challenging. We performed a meta-analysis quantifying how many EOS cases might be 'missed' using the Kaiser Permanente electronic calculator, compared with National Institute for Health and Care Excellence (NICE) guidelines. Methods:A systematic literature search was carried out for studies citing the article in which the calculator was publicised. Studies were eligible if they presented data evaluating the calculator, either by retrospective case review or prospective cohort study. The primary outcome measure was numbers of culture positive EOS cases where the calculator did not recommend empirical antibiotics, but NICE guidelines would have. Data were pooled using a random effect meta-analysis. A subgroup analysis was performed using data from studies of babies exposed to chorioamnionitis. Findings:Eleven studies were included. There were a total of 75 EOS cases across the studies and a minimum of 14 (best case scenario), and a maximum of 22 (worst case scenario) cases where use of the calculator would have resulted in delayed or missed treatment, compared to if NICE guidelines had been followed. The probability of missed/delayed treatment for an EOS case were best case 0.19 [95% confidence intervals 0.11 - 0.29], worst case 0.31 [95% CI 0.17 - 0.49]. The probability of missing cases was significantly more in babies exposed to chorioamnionitis. Interpretation:A large proportion of EOS cases were 'missed' by the calculator. Further evaluation of the calculator is recommended before it is introduced into UK clinical practice. Funding:None.

SUBMITTER: Pettinger KJ

PROVIDER: S-EPMC7046522 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Sensitivity of the Kaiser Permanente early-onset sepsis calculator: A systematic review and meta-analysis.

Pettinger Katherine J KJ Mayers Katie K McKechnie Liz L Phillips Bob B

EClinicalMedicine 20191222

<h4>Background</h4>Determining which babies should receive antibiotics for potential early onset sepsis (EOS) is challenging. We performed a meta-analysis quantifying how many EOS cases might be 'missed' using the Kaiser Permanente electronic calculator, compared with National Institute for Health and Care Excellence (NICE) guidelines.<h4>Methods</h4>A systematic literature search was carried out for studies citing the article in which the calculator was publicised. Studies were eligible if they ...[more]

PMID: 32140666

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Project description:BackgroundThe Kaiser Permanente model of integrated health delivery is highly regarded for high-quality and efficient health care. Efforts to reproduce Kaiser's success have mostly failed. One factor that has received little attention and that could explain Kaiser's advantage is its commitment to and investment in nursing as a key component of organizational culture and patient-centered care.PurposeThe aim of this study was to investigate the role of Kaiser's nursing organization in promoting quality of care.MethodologyThis was a cross-sectional analysis of linked secondary data from multiple sources, including a detailed survey of nurses, for 564 adult, general acute care hospitals from California, Florida, Pennsylvania, and New Jersey in 2006-2007. We used logistic regression models to examine whether patient (mortality and failure-to-rescue) and nurse (burnout, job satisfaction, and intent-to-leave) outcomes in Kaiser hospitals were better than in non-Kaiser hospitals. We then assessed whether differences in nursing explained outcomes differences between Kaiser and other hospitals. Finally, we examined whether Kaiser hospitals compared favorably with hospitals known for having excellent nurse work environments-Magnet hospitals.FindingsPatient and nurse outcomes in Kaiser hospitals were significantly better compared with non-Magnet hospitals. Kaiser hospitals had significantly better nurse work environments, staffing levels, and more nurses with bachelor's degrees. Differences in nursing explained a significant proportion of the Kaiser outcomes advantage. Kaiser hospital outcomes were comparable with Magnet hospitals, where better outcomes have been largely explained by differences in nursing.ImplicationsAn important element in Kaiser's success is its investment in professional nursing, which may not be evident to systems seeking to achieve Kaiser's advantage. Our results suggest that a possible strategy for achieving outcomes like Kaiser may be for hospitals to consider Magnet designation, a proven and cost-effective strategy to improve process of care through investments in nursing.

Project description:ImportanceThe neonatal early-onset sepsis (EOS) calculator is a clinical risk stratification tool increasingly used to guide the use of empirical antibiotics for newborns. Evidence on the effectiveness and safety of the EOS calculator is essential to inform clinicians considering implementation.ObjectiveTo assess the association between management of neonatal EOS guided by the neonatal EOS calculator (compared with conventional management strategies) and reduction in antibiotic therapy for newborns.Data sourcesElectronic searches in MEDLINE, Embase, Web of Science, and Google Scholar were conducted from 2011 (introduction of the EOS calculator model) through January 31, 2019.Study selectionAll studies with original data that compared management guided by the EOS calculator with conventional management strategies for allocating antibiotic therapy to newborns suspected to have EOS were included.Data extraction and synthesisFollowing PRISMA-P guidelines, relevant data were extracted from full-text articles and supplements. CHARMS (Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modeling Studies) and GRADE (Grades of Recommendation, Assessment, Development and Evaluation) tools were used to assess the risk of bias and quality of evidence. Meta-analysis using a random-effects model was conducted for studies with separate cohorts for EOS calculator and conventional management strategies.Main outcomes and measuresThe difference in percentage of newborns treated with empirical antibiotics for suspected or proven EOS between management guided by the EOS calculator and conventional management strategies. Safety-related outcomes involved missed cases of EOS, readmissions, treatment delay, morbidity, and mortality.ResultsThirteen relevant studies analyzing a total of 175 752 newborns were included. All studies found a substantially lower relative risk (range, 3%-60%) for empirical antibiotic therapy, favoring the EOS calculator. Meta-analysis revealed a relative risk of antibiotic use of 56% (95% CI, 53%-59%) in before-after studies including newborns regardless of exposure to chorioamnionitis. Evidence on safety was limited, but proportions of missed cases of EOS were comparable between management guided by the EOS calculator (5 of 18 [28%]) and conventional management strategies (8 of 28 [29%]) (pooled odds ratio, 0.96; 95% CI, 0.26-3.52; P = .95).Conclusions and relevanceUse of the neonatal EOS calculator is associated with a substantial reduction in the use of empirical antibiotics for suspected EOS. Available evidence regarding safety of the use of the EOS calculator is limited, but shows no indication of inferiority compared with conventional management strategies.

Project description:BackgroundThe early-onset sepsis calculator (EOSC) reduces unnecessary antibiotic treatment in newborns. However, its performance in identifying cases with early-onset disease (EOD) is unclear. We compared the sensitivity of the EOSC to the current Dutch and National Institute for Health and Care Excellence (NICE) guidelines when applied to a cohort of newborns with culture-positive early-onset sepsis and meningitis.MethodsCulture-positive Streptococcus agalactiae (GBS) and Escherichia coli (E. coli) sepsis and meningitis patients ≤3 days old with a gestational age ≥34 weeks, identified between 1/1/2018 and 31/1/2021 in a Dutch prospective nationwide cohort study were included. Cases were identified by treating physicians and microbiological surveillance. Primary outcome was the proportion of patients that would have been treated according to the EOSC, the Dutch, and the NICE EOD prevention guidelines. Differences between proportions were analysed using McNemar's test.FindingsWe included 81 GBS and 7 E. coli EOD cases. At 4 h after birth, the EOSC would have recommended antibiotic treatment in 32 (36%) patients, compared to 44 (50%) by the Dutch (p<0·01) and 48 (55%) by the NICE guideline (p<0·01). The EOSC would have initially recommended routine care for 52% of patients compared to 31% and 30% for the Dutch and NICE guidelines (p<0·01). At 24 h after birth, the EOSC would have recommended antibiotic treatment in 54 (61%) infants compared to 64 (73%) by the Dutch (p = 0·02) and 63 (72%) by the NICE guidelines (p = 0·06).InterpretationThe sensitivity of the EOSC in identifying cases of EOD is lower compared to both Dutch and NICE guidelines, especially directly after birth. The EOSC relies more on clinical symptoms and results in less overtreatment of healthy newborns at the cost of later antibiotic treatment in initially well-appearing EOD patients.FundingThis work was supported by grants received from Netherlands Organization for Health Research and Development (ZonMw; NWO-Vidi-Grant (grant number 917·17·308); NWO-Vici-Grant (grant number 918·19·627)), the Academic Medical Centre (AMC Innovative Impulse Grant) and Steun Emma Foundation Grant.

Project description:BackgroundTo inform Danish health care reform efforts, we compared health care system inputs and performance and assessed the usefulness of these comparisons for informing policy.MethodsRetrospective analysis of secondary data in the Danish Health Care System (DHS) with 5.3 million citizens and the Kaiser Permanente integrated delivery system (KP) with 6.1 million members in California. We used secondary data to compare population characteristics, professional staff, delivery structure, utilisation and quality measures, and direct costs. We adjusted the cost data to increase comparability.ResultsA higher percentage of KP patients had chronic conditions than did patients in the DHS: 6.3% vs. 2.8% (diabetes) and 19% vs. 8.5% (hypertension), respectively. KP had fewer total physicians and staff compared to DHS, with 134 physicians/100,000 individuals versus 311 physicians/100,000 individuals. KP physicians are salaried employees; in contrast, DHS primary care physicians own and run their practices, remunerated by a mixture of capitation and fee-for-service payments, while most specialists are employed at largely public hospitals. Hospitalisation rates and lengths of stay (LOS) were lower in KP, with mean acute admission LOS of 3.9 days versus 6.0 days in the DHS, and, for stroke admissions, 4.2 days versus 23 days. Screening rates also differed: 93% of KP members with diabetes received retinal screening; only 46% of patients in the DHS with diabetes did. Per capita operating expenditures were PPP$1,951 (KP) and PPP $1,845 (DHS).ConclusionCompared to the DHS, KP had a population with more documented disease and higher operating costs, while employing fewer physicians and resources like hospital beds. Observed quality measures also appear higher in KP. However, simple comparisons between health care systems may have limited value without detailed information on mechanisms underlying differences or identifying translatable care improvement strategies. We suggest items for more in-depth analyses that could improve the interpretability of findings and help identify lessons that can be transferred.

Project description:BackgroundThe incidence of early-onset colorectal cancer (EOCRC), which means colorectal cancer diagnosed in patients under 50 years, has been increasing around the world. However, the etiology remains unclear. This study aims to identify risk factors for EOCRC.MethodsThis systematic review was conducted in PubMed, Embase, Scopus, and Cochrane Library databases from inception to November 25, 2022. We examined risk factors for EOCRC, including demographic factors, chronic conditions, and lifestyle behaviors or environmental factors. Random-effects/fixed-effects meta-analysis was adopted to combine effect estimates from published data. Study quality was evaluated with the Newcastle-Ottawa Scale (NOS). Statistical analysis was performed Revman5.3. Studies not suitable for the meta-analysis were analyzed by a systematic review.ResultsA total of 36 studies were identified for this review, and 30 studies were included in the meta-analysis. Significant risk factors for EOCRC included male (OR=1.20; 95% CI, 1.08-1.33), Caucasian (OR=1.44; 95% CI, 1.15-1.80), a family history of CRC (OR=5.90; 95% CI, 3.67-9.48), inflammatory bowel disease (OR=4.43; 95% CI, 4.05-4.84), obesity (OR=1.52; 95%CI, 1.20-1.91), overweight (OR=1.18; 95% CI, 1.12-1.25), triglycerides (OR=1.12; 95% CI, 1, 08-1.18), hypertension (OR=1.16; 95% CI, 1.12-1.21), metabolic syndrome (OR=1.29; 95% CI, 1.15-1.45), smoking (OR=1.44; 95% CI, 1.10-1.88), alcohol consumption (OR=1.41; 95% CI, 1.22-1.62), a sedentary lifestyle (OR=1.24; 95% CI, 1.05-1.46), red meat (OR=1.10; 95% CI, 1.04-1.16), processed meat (OR=1.53; 95% CI, 1.13-2.06), Western dietary patterns (OR=1.43; 95% CI, 1.18-1.73) and sugar-sweetened beverages (OR=1.55; 95% CI, 1.23-1.95). However, no statistical differences were found for hyperlipidemia and hyperglycemia. Vitamin D may be a protective factor (OR=0.72; 95% CI, 0.56-0.92). There was considerable heterogeneity among studies (I2>60%).ConclusionsThe study provides an overview of the etiology and risk factors of EOCRC. Current evidence can provide baseline data for risk prediction models specific to EOCRC and risk-tailored screening strategies.

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Sensitivity of the Kaiser Permanente early-onset sepsis calculator: A systematic review and meta-analysis.

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Sensitivity of the Kaiser Permanente early-onset sepsis calculator: A systematic review and meta-analysis.

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