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Results for “Performance benchmarking”

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PubMed1995

Culture audits: a tool for change.

The culture audit, which has five phases--needs awareness, diagnosis, planning, action, and evaluation--is a critical tool for easing cultural transformation in healthcare organizations. The objective of the audit--usually conducted by outsiders--is to help leaders better understand the current culture and adapt the culture to enhance organizational performance. Most leaders contract with an outsider to facilitate the needs exploration process, often with the guidelines of an advisory team of managers and staff. During the diagnosis phase, the audit team chooses the data-gathering methods, collects and analyzes the data, and develops a model of the culture. The third phase of the culture audit involves planning interventions. Once leaders have a clear picture of their organization's culture, they must ascertain whether the culture will enhance or impede the changes demanded by healthcare reform and an increasingly competitive environment. During the action phase, the culture begins to move toward its desired future. This transition generally requires change in all the organization's systems, including technology, structure, rewards, decision making, budgeting, and managing. Finally, the organization assesses the impact of its culture on its performance. Using the original diagnosis as a baseline and the organization performance goals, the evaluation process maps the changing culture against the benchmark beginning and the goals.

Data Collection↗

PubMed2001

System analysis for optimal control of a wastewater treatment benchmark.

The paper presents an analysis and optimisation of a wastewater treatment benchmark. The benchmark is a simulation environment defining a plant layout, simulation model, influent data, test procedures and evaluating criteria that should be used for comparing different control strategies. In this paper an analysis of the benchmark which addresses the influences of potential manipulated variables on control performance under different operating conditions is presented. In the study optimisation is used to define the optimal values of the manipulated variables under constant as well as dynamic influent conditions. The results indicate that such an analysis and optimisation give important information about the manipulated variables under varying influent conditions and consequently about possible control strategies.

Computer Simulation↗

PubMed2005

A benchmark study of controlled emptying of equalization basins.

Storm tanks, or equalization basins, have been used for many years in sewer or wastewater treatment systems to reduce the amount of combined sewer overflows. In this paper, a systematic control of an equalization basin is used not only to dampen or reduce the hydraulic load, but also to systematically improve the effluent quality in a nitrogen removal plant. It is demonstrated that the effluent ammonia concentration is the key component. The Benchmark Simulation Model 1, implemented in MATLAB/Simulink, has been used to perform the evaluations. It has been extended with systematic rainfall generations. Intuitively, it is apparent that the equalization basin should be emptied before a rainfall. This requires a prediction capacity. It is shown that the choice of prediction time is by no means trivial and it is not true that a long prediction horizon is always advantageous.

Computer Simulation↗

PubMed2006

Three-year trends in the costs of residency training in family medicine.

BACKGROUND AND OBJECTIVES: A 3-year follow-up survey was performed to update and examine trends in the financial and operational benchmarking data for family medicine residency programs within the University of Washington Network. METHODS: Using the standardized approach that had been used in 2000, data were systematically collected by standardized questionnaire, evaluated for quality and verified, and then analyzed. Updated data regarding revenues, expenses, faculty structures, productivity, and family medicine center staffing models are reported, as well as data on trends in each of these areas for the 3-year period. RESULTS: Although revenues increased during this time, expenses increased relatively more, leading to an overall increase in the "cost per resident" among the Network programs. Particular factors leading to increased costs were salary expenses and the cost of malpractice insurance in these states. CONCLUSIONS: The results of this study contribute to the establishment of normative data for budgeting and operational evaluation of family medicine programs and projections of cost variations over time.

Costs and Cost Analysis↗

PubMed2006

More care not necessarily better care, study says.

High-intensity care also results in lower patient satisfaction levels, according to study. High-intensity care also results in lower patient satisfaction levels, according to study. Benchmarking is necessary to obtain a truly objective view of your performance.

Chronic Disease↗

PubMedDate not supplied

Using benchmarking to manage your laboratory.

How does your cost per test compare with the competition? Does your productivity measure up? Benchmarking data provide the answers, but you may not realize just how far the information can go. In times of budget cuts, comparing your laboratory operations with the best performers can be crucial. The Virginia Commonwealth University Health System (VCUHS) Pathology Department in Richmond, Virginia, demonstrated that benchmarking is more than a paper exercise. It literally saved the laboratory. The keys were clarification, consistency, and communication.

Benchmarking↗

PubMed2005

Bayesian sonar detection performance prediction in the presence of interference in uncertain environments.

The detection performance of sonar systems can be greatly limited by the presence of interference and environmental uncertainty. The classic sonar equation does not take into account these two limiting factors and is inaccurate in predicting sonar detection performance. Here we have developed closed-form receiver operating characteristic (ROC) performance expressions for the Bayesian detector in the presence of interference in uncertain environments. Various scenarios extended from a NRL benchmark shallow-water model were used to test the analytical ROC expressions and to analyze the effects of interference and environmental uncertainty on detection performance. The results show that (1) the degradation on detection performance due to interference is greatly magnified by the presence of environmental uncertainty; (2) Bayesian sonar detection performance depends on the following fundamental parameters: the signal-to-noise ratio, the rank of the signal matrix, and the signal-to-interference coefficient; (3) the proposed analytical ROC performance predictions can be computed much faster than performance evaluations with commonly used Monte Carlo techniques.

Journal Article↗

PubMed1999

Benchmarking guide '99.

The right data: You can't benchmark without it. For our third annual guide to benchmarking under managed care, we turned to six prominent organizations. We've tapped their databases and creativity to help you gauge your performance on financial, operational, and service targets by degree of managed care penetration.

Benchmarking↗

PubMed2026

Comprehensive in silico genomics analysis of global trends and host-specific emergence of aminoglycoside resistance in Staphylococcus aureus: a One-Health perspective.

BACKGROUND: Aminoglycosides remain clinically valuable against Staphylococcus aureus. Aminoglycoside resistance in S. aureus represents a critical One Health concern and is primarily driven by aminoglycoside-modifying enzymes (AMEs), which are frequently plasmid-encoded. Although regional studies have provided valuable insights, the global epidemiology of aminoglycoside resistance determinants remains poorly characterized because comprehensive data integrating human, animal, and environmental reservoirs are still lacking. This study addresses this gap by analyzing over 110,000 S. aureus genomes (2000-2025) to map the global resistome, quantify temporal and host-specific trends, and assess the association between genetic determinants and phenotypic resistance. METHODS: We performed a retrospective One Health meta-analysis of 110,309 S. aureus genomes collected between 2000 and 2025 from 128 countries. Genomes were quality-filtered and aminoglycoside resistance determinants were identified using NCBI AMRFinderPlus (v4.0.23). Multilocus sequence typing and host-source harmonization (Human, Animal, Environment, Unknown) enabled clonal and reservoir stratification. Temporal trends in gene prevalence and resistance burden were modeled with robust regression. Geographic and host-associated structuring of key genes was assessed via χ2 and enrichment tests. Machine-learning models (elastic-net, random forests, XGBoost) were benchmarked for minimum inhibitory concentration (MIC) prediction via nested cross-validation, with performance evaluated by mean absolute error, RMSE, and SHAP-based feature importance. All analyses were conducted in R and Python using publicly available, de-identified genomic data. RESULTS: Aminoglycoside resistance-associated genes were dominated by modifying enzyme determinants, with ant(6)-Ia, ant(9)-Ia, aph(3')-IIIa, sat4, aadD1, and aac(6')-Ie/aph(2'')-Ia occurring in 14-22% of isolates worldwide. Temporal analysis revealed significant declines in several major determinants, most notably ant(9)-Ia (-2.22 percentage points per year, p < 0.001), whereas apmA exhibited a non-significant decreasing trend in animal isolates. Host structuring was marked: human clinical isolates concentrated common determinants, while animal and environmental isolates harbored rare alleles (apmA, spw, str, spd). Geographic mapping confirmed near-universal distribution of common genes but focal restriction of rare ones. Publicly available phenotypic data indicated strong activity of amikacin, whereas gentamicin showed a distinct resistant subpopulation that closely corresponded with AME gene carriage. Genotype-phenotype analyses demonstrated strong concordance, with gene-rich complements predicting resistant MIC strata and absence of determinants predicting susceptibility. Analysis across different gene classes revealed frequent co-occurrence of aminoglycoside resistance genes with determinants from other classes, such as mecA, blaZ, and MLS_B, embedding them within multidrug-resistant (MDR) genomic contexts. CONCLUSION: Over 25 years, the prevalence of aminoglycoside resistance-associated genes in S. aureus has declined for several common determinants, while rare veterinary-linked alleles are emerging in animal isolates. Strong genotype-phenotype concordance supports genomic prediction for gentamicin and amikacin, where MIC data are available, although phenotypic confirmation remains essential. The frequent co-occurrence of aminoglycoside resistance genes with other antimicrobial resistance determinants indicates their integration within co-occurrence patterns of MDR genes, defined here as clusters of co-occurring resistance genes often carried on shared mobile genetic elements. These patterns highlight the need for integrated One Health surveillance combining clinical, veterinary, and environmental monitoring with plasmid-context resolution to anticipate emerging threats.

Aminoglycosides↗

PubMed2026

Discovery and validation of a multi-protein panel for predicting non-fatal major adverse cardiovascular events in diabetic kidney disease.

OBJECTIVE: To identify plasma protein biomarkers associated with incident non-fatal major adverse cardiovascular events (MACE) in diabetic kidney disease (DKD) patients. RESEARCH DESIGN AND METHODS: We analyzed 317 DKD patients from the UK Biobank. Plasma proteomics and clinical data (demographics, metabolism, renal function) were integrated. In an exploratory discovery phase, three sequential Cox regression models (crude, socio-demographic-adjusted, socio-demographic-metabolic adjusted) screened non-fatal MACE-associated proteins. To prevent information leakage, the cohort was then randomly split into training (70%) and testing (30%) sets; machine-learning feature selection, hyperparameter optimization, and final model development were performed exclusively within the training set. The associated proteins were input into the four-step machine-learning pipeline (LASSO-Cox, random survival forest, Boruta, XGBoost-Cox). Predictive performance was validated using Kaplan-Meier survival analyses, longitudinal trajectory modeling, and ROC benchmarking. An interactive web application was deployed for clinical implementation. RESULTS: Of 1,463 plasma proteins, 561 were associated with non-fatal MACE across Cox models, with 14 overlapping proteins. Nine core proteins (ANG, IL1R1, CXCL14, ESAM, PTGDS, HAVCR1, FGFR2, IGSF8, CCL3) were validated: ANG showed the strongest non-fatal MACE association (HR = 3.88, 95%CI 2.33-6.48, p<0.001), and all high-expression groups had elevated non-fatal MACE risk. GO/KEGG enrichment highlighted inflammatory-immune pathways like positive regulation of MAPK cascade, Cytokine-cytokine receptor interaction and PI3K-Akt signaling pathway as key mechanisms. The model integrating proteins, demographic factors, and clinical variables achieved the highest predictive performance across non-fatal MACE (AUC = 0.768), myocardial infarction (MI) (0.808), and stroke (0.816) outcomes, with superior stability in cross-validation. CoxBoost + Elastic Net framework was selected as the optimal framework via benchmarking of 101 algorithms. The model demonstrated favorable calibration in high-risk patients and yielded positive net clinical benefit across decision thresholds of 5% to 45%. The web tool (https://jiangli2941.github.io/MACE-prediction-v2/) enables input of 28 variables, outputs non-fatal MACE risk status, risk probability, and highlights abnormal indicators. CONCLUSION: Plasma proteomics combined with machine learning identifies robust non-fatal MACE predictors in DKD.

Humans↗

PubMedDate not supplied

National databases and clinical practice specialist: decreasing postoperative atrial fibrillation following cardiac surgery.

In this article, we document how an interdisciplinary committee of health professionals led to an approximate 50% reduction in the incidence of postoperative atrial fibrillation (AF) following a cardiac surgery procedure by using preoperative loading and dosing of PO amiodarone and beta blockade. Patients in this report (n = 3397) included all coronary artery bypass surgery (CABG) and valve replacement/repair procedures from January 1, 2000 to June 30, 2002. The incidence of postoperative AF for a CABG or valve replacement/repair procedure was 19.0% for period A (preprotocol) and 13.5% for period B (postprotocol). This translates into an absolute risk reduction of 5.5% or 113 actual cases of postoperative AF reduced. The role of the clinical practice specialist, a master's prepared nurse, and participation in the national Society of Thoracic Surgeon's database allowed us to track our CABG outcomes, benchmark our outcomes against both national and regional institutions, and make changes in outcomes incidence through performance improvement.

Adrenergic beta-Antagonists↗

PubMedDate not supplied

The competency question.

JCAHO mandates "processes that are designed to ensure that the competency of all staff members is assessed, maintained, demonstrated, and improved on an ongoing basis." However, it is difficult to collect aggregate data regarding staff competency patterns and trends. How many facilities have the time or energy to collect aggregate data, let alone statistically analyze it for patterns and trends? Not many in today's environment. I saw the need to create a test to evaluate staff competency at my facility, but soon realized I would have no way of knowing if the results were good or bad. The only way to judge the results would be to have a standardized test that was used by multiple facilities. As president of the Houston X-ray Quality Society, I brought the topic up at a meeting in 1995, and a committee was set up to work on the test. The result is two competency tests--one for staff radiographers and one for mammographers--which are currently used by 35 to 40 facilities, with approximately 1,000 technologists taking the test each year. The tests include practical questions that reflect the knowledge required to perform daily exams. Each test has five sections that assess different areas of competency. The scoring system allows technologists to fail one or more individual sections but still pass the test overall. Twenty to 30 percent of the questions are new each year. That gives us the ability to look for improvement on previous year's questions, and at the same time, avoid producing a static and ineffective test. There are 60 questions on the staff radiographer test and 65 questions on the mammographer test, which also includes clinical images. Facilities must sign an agreement that states that they cannot use the test as a disciplinary tool in the employee's evaluation, or in any other way against the technologist. As a profession, radiology administration not only has regulatory requirements to evaluate competency, but also a moral duty to insure that patients receive the best possible care. We should not cover up or ignore the blemishes that we all know exist. Instead, we should take them on, as professional and personal challenges to improve the competency of our staff.

Benchmarking↗

PubMed2006

Impact of isolated clinical performance feedback on clinical productivity of an academic surgical faculty.

BACKGROUND: There is increasing financial pressure to maximize clinical productivity for academic physicians. We examined whether clinical performance feedback alone could contribute to improving the clinical productivity of surgeons in an academic department of surgery. STUDY DESIGN: We implemented a clinical performance feedback program in January 2003. We then compared clinical productivity in terms of relative value units (RVUs) of surgeons for 18 months before and 18 months after this intervention, using each surgeon as his or her own control. Regression was performed with dependent variable ln (monthly RVUs) and independent variables "calendar month," "pre/post" January 2003, and "surgeon." The coefficient on "pre/post" reflected average change in RVUs. We also surveyed faculty on their use of and attitudes toward this feedback. RESULTS: There was a 58% survey response. Ninety-two percent of responding faculty reported that they viewed and used the performance feedback, and that it affected their practice. Ninety-two percent believed the information accurately reflected their performance, 89% thought that the comparisons were useful, and 79% desired more feedback information, specifically, comparisons with external benchmarks. When RVU data were examined, the coefficient on change pre- and postintervention indicated a 7.4% increase in productivity (p < 0.001), or a 6.0% increase (p=0.003) after exclusion of outliers. CONCLUSIONS: Performance feedback was associated with a small (6.0%) but significant improvement in productivity in this academic surgical faculty group. Performance feedback can be useful and should be used in conjunction with other management tools for this population.

Academic Medical Centers↗

PubMedDate not supplied

Bayesian segmental models with multiple sequence alignment profiles for protein secondary structure and contact map prediction.

In this paper, we develop a segmental semi-Markov model (SSMM) for protein secondary structure prediction which incorporates multiple sequence alignment profiles with the purpose of improving the predictive performance. The segmental model is a generalization of the hidden Markov model where a hidden state generates segments of various length and secondary structure type. A novel parameterized model is proposed for the likelihood function that explicitly represents multiple sequence alignment profiles to capture the segmental conformation. Numerical results on benchmark data sets show that incorporating the profiles results in substantial improvements and the generalization performance is promising. By incorporating the information from long range interactions in beta-sheets, this model is also capable of carrying out inference on contact maps. This is an important advantage of probabilistic generative models over the traditional discriminative approach to protein secondary structure prediction. The Web server of our algorithm and supplementary materials are available at http://public.kgi.edu/-wild/bsm.html.

Algorithms↗

PubMed2005

An evaluation, comparison, and accurate benchmarking of several publicly available MS/MS search algorithms: sensitivity and specificity analysis.

MS/MS and associated database search algorithms are essential proteomic tools for identifying peptides. Due to their widespread use, it is now time to perform a systematic analysis of the various algorithms currently in use. Using blood specimens used in the HUPO Plasma Proteome Project, we have evaluated five search algorithms with respect to their sensitivity and specificity, and have also accurately benchmarked them based on specified false-positive (FP) rates. Spectrum Mill and SEQUEST performed well in terms of sensitivity, but were inferior to MASCOT, X!Tandem, and Sonar in terms of specificity. Overall, MASCOT, a probabilistic search algorithm, correctly identified most peptides based on a specified FP rate. The rescoring algorithm, PeptideProphet, enhanced the overall performance of the SEQUEST algorithm, as well as provided predictable FP error rates. Ideally, score thresholds should be calculated for each peptide spectrum or minimally, derived from a reversed-sequence search as demonstrated in this study based on a validated data set. The availability of open-source search algorithms, such as X!Tandem, makes it feasible to further improve the validation process (manual or automatic) on the basis of "consensus scoring", i.e., the use of multiple (at least two) search algorithms to reduce the number of FPs. complement.

Algorithms↗

PubMed2025

MNMO: discover driver genes from a multi-omics data based-multi-layer network.

MOTIVATION: Cancer as a public health problem is driven by genomic variations in "cancer driver" genes. The identification of driver genes is critical for the discovery of key biomarkers and the development of personalized therapy. RESULTS: We propose a prediction method MNMO: a multi-layer network model based on multi-omics data. MNMO firstly constructs a dynamically adjusted four-layer network composed of miRNAs and three kinds of genes with different features. Then three kinds of scores, i.e. control capacity, mutation score, and network score, are devised and calculated by harmonic mean to produce the integrated gene score. Experiments were performed on three kinds of real cancer data to compare the identification performance of method MNMO with that of six state-of-the-art ones. The results indicate that method MNMO presents the best identification performance under most circumstances. The genes prioritized by method MNMO not only have a better match to the benchmark ones than those identified by the other methods, but also are all associated with the development and progression of cancers. In addition, some extended versions of method MNMO can further achieve better performance on most evaluation metrics for some specific datasets. They may be more conducive to identifying tissue-specific genes, which has been verified through a number of experiments. AVAILABILITY AND IMPLEMENTATION: The source code and the R package "MNMO" are available at https://github.com/Zheng-D/MNMO. The dataset and code are archived at https://doi.org/10.5281/zenodo.14969986.

Humans↗

PubMed1999

The five-year evolution of a malnutrition treatment program in a community hospital.

BACKGROUND: Studies suggest that 30%-55% of hospitalized patients are at risk for malnutrition, an avoidable comorbidity contributing to increases in hospitalization and readmission, length of stay, complications, and mortality. Yet a variety of issues have impeded many hospitals' implementation of effective nutrition intervention programs. BENCHMARKING STUDY: St Francis Hospital (SFH), a 395-bed community acute care facility in Wilmington, Delaware, participated in a nationwide benchmark study in fall 1993. In comparison with the 12-hospital means, data for SFH showed both delays in initiating a nutrition care plan for acutely ill patients and a significantly higher risk for malnutrition. NUTRITION SCREENING PILOT: A pilot study was implemented in 1994 to identify nutrition needs within 48 hours of admission as a first step in the improvement process. Although interventions occurred earlier for a greater number of high-risk patients, nutrition intervention was not being provided in a uniform and timely manner. THE MALNUTRITION CLINICAL PATHWAY: A free-standing hospital committee, the Nutrition Care Committee (NCC), with guidance from the care management department, began developing a malnutrition pathway that would serve as an integrated plan for providing nutrition care to high-risk patients. The original pathway was organized into four stages that outlined the progression and timing of care--identification of the patient at high risk for malnutrition, nutrition care decisions, treatment in progress (the remainder of the patient's hospitalization), and discharge planning. OUTCOME STUDIES: Outcome studies were conducted in 1996 and again in 1998 to assess the malnutrition treatment pathway's impact on patient health outcomes and the cost of care. The 1996 outcome study indicated significant improvements in the identification of high-risk patients (from 25.9% to 86%) and the timeliness of nutrition intervention (from 6.9 days to 2.4 days). A second outcome study was conducted in 1998, following revision of the pathway. Comparison of the 1996 after-pathway patient population with a matched study group in 1998 indicated reductions in average length of stay from 10.8 to 8.1 days; the incidence of major complications from 75.3% to 17.5%; and 30-day readmission rates from 16.5% to 7.1%. DISCUSSION: The performance improvement project described in this article began with SHF's voluntary participation in an interdisciplinary benchmarking study and continued when it was apparent that SFH had an opportunity for performance improvement. Forming an NCC at SFH was the first step in a process that gained the administrative support necessary to fully develop the program. SUMMARY AND CONCLUSIONS: SFH has developed and implemented a malnutrition treatment program that is integrated into the care plan of all acute care patients and is included in the discharge planning process. Outcome studies have demonstrated the effect of the malnutrition treatment program on patient recovery and cost of care.

Algorithms↗

PubMed2006

Evaluation of target scores and benchmarks for the traversal task scenario of the Minimally Invasive Surgical Trainer-Virtual Reality (MIST-VR) laparoscopy simulator.

BACKGROUND: The Minimally Invasive Surgical Trainer-Virtual Reality (MIST-VR) simulator is validated for laparoscopy training, but benchmarks and target scores for assessing single tasks are needed. METHODS: Control data for the MIST-VR traversal task scenario were collected from 61 novices who performed the task 10 times over 3 days (1 h daily). Data were collected on the time taken, error score, economy of movement, and total score. Test differences were analyzed through percentage scores and t-tests for paired samples. RESULTS: Improvement was greatest over tests 1 to 5 (improvement: test(1.2), 38.07%; p = 0.000; test(4.5), 10.66%; p = 0.010): between tests 5 and 10, improvement slowed and scores stabilized. Variation in participants' performance fell steadily over the 10 tests. CONCLUSION: Trainees should perform at least 10 tests of the traversal task-five to get used to the equipment and task (automation phase; target total score, 95.16) and five to stabilize and consolidate performance (test 10 target total score, 74.11).

Adult↗