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Five guiding principles can help your organization achieve revenue cycle success: Have appropriate job functions and work flow design in place. Elevate staff performance through quality and productivity goals. Ensure effective technology infrastructure is in place. Deploy at all levels a comprehensive management tool set and report card metric (dashboard). Sustain a culture of accountability.
Many dental schools consider the successful completion of a state or regional dental licensure examination as one of the significant benchmarks for assessing effectiveness of the curriculum. At the University of Florida College of Dentistry (UFCD), performance on the state dental licensure examination is monitored and compared with senior year mock board performance and clinical productivity to identify factors that may contribute to state board "pass" rates. A retrospective analysis was conducted of "first-time" performance on the Florida Dental Licensure Exam for graduates from classes 1996 to 2003. Using ANOVA, licensure exam performance data was analyzed and compared with performance on the senior mock board exam and clinical productivity, determined by numbers of procedures completed in each discipline. Significant relationships were noted between four of thirteen aspects of mock board performance and clinical productivity data and performance on the Florida Dental Licensure Exam. First, a significant relationship (p<0.05) was found between passing the senior mock board fixed prosthodontic preparation and successful completion of that procedure on the state licensure exam. Second, a significant relationship (p<0.05) was noted between the clinical (patient-based) Class II amalgam on the senior mock board and passing that procedure on the state licensure exam. Third, a significant relationship was noted (p<0.05) between the number of Class IV clinical composite procedures completed during dental school and passing the licensure exam Class IV manikin composite procedure. Fourth, there was a significant relationship (p<0.01) between the number of clinical Class II amalgam procedures completed during the junior and senior years and passing the state licensure exam clinical amalgam procedure. No significance was found between the remaining five mock board procedures (Class II composites, Class IV composites, pin amalgams, endodontic, and periodontal scaling/root planing) and performance on the like procedures on the licensure exam. Likewise, no significance was found between the remaining four productivity measures (numbers of Class II composites, endodontic teeth treated, crowns and abutments completed, and quadrants of periodontal scaling/root planing) and performance of these procedures on the state licensure exam.
OBJECTIVE: To design and test a model of the factors that influence frontline and midlevel managers' perceptions of usefulness of comparative reports of hospital performance. STUDY SETTING: A total of 344 frontline and midlevel managers with responsibility for stroke and medical cardiac patients in 89 acute care hospitals in the Canadian province of Ontario. STUDY DESIGN: Fifty-nine percent of managers responded to a mail survey regarding managers' familiarity with a comparative report of hospital performance, ratings of the report's data quality, relevance and complexity, improvement culture of the organization, and perceptions of usefulness of the report. EXTRACTION METHODS: Exploratory factor analysis was performed to assess the dimensionality of performance data characteristics and improvement culture. Antecedents of perceived usefulness and the role of improvement culture as a moderator were tested using hierarchical regression analyses. PRINCIPAL FINDINGS: Both data characteristics variables including data quality, relevance, and report complexity, as well as organizational factors including dissemination intensity and improvement culture, explain significant amounts of variance in perceptions of usefulness of comparative reports of hospital performance. The total R2 for the full hierarchical regression model = .691. Improvement culture moderates the relationship between data relevance and perceived usefulness. CONCLUSIONS: Organizations and those who fund and design performance reports need to recognize that both report characteristics and organizational context play an important role in determining line managers' response to and ability to use these types of data.
A proton dose computational algorithm, performing an analytical superposition of infinitely narrow proton beamlets (ASPB) is introduced. The algorithm uses the standard pencil beam technique of laterally distributing the central axis broad beam doses according to the Moliere scattering theory extended to slablike varying density media. The purpose of this study was to determine the accuracy of our computational tool by comparing it with experimental and Monte Carlo (MC) simulation data as benchmarks. In the tests, parallel wide beams of protons were scattered in water phantoms containing embedded air and bone materials with simple geometrical forms and spatial dimensions of a few centimeters. For homogeneous water and bone phantoms, the proton doses we calculated with the ASPB algorithm were found very comparable to experimental and MC data. For layered bone slab inhomogeneity in water, the comparison between our analytical calculation and the MC simulation showed reasonable agreement, even when the inhomogeneity was placed at the Bragg peak depth. There also was reasonable agreement for the parallelepiped bone block inhomogeneity placed at various depths, except for cases in which the bone was located in the region of the Bragg peak, when discrepancies were as large as more than 10%. When the inhomogeneity was in the form of abutting air-bone slabs, discrepancies of as much as 8% occurred in the lateral dose profiles on the air cavity side of the phantom. Additionally, the analytical depth-dose calculations disagreed with the MC calculations within 3% of the Bragg peak dose, at the entry and midway depths in the phantom. The distal depth-dose 20%-80% fall-off widths and ranges calculated with our algorithm and the MC simulation were generally within 0.1 cm of agreement. The analytical lateral-dose profile calculations showed smaller (by less than 0.1 cm) 20%-80% penumbra widths and shorter fall-off tails than did those calculated by the MC simulations. Overall, this work validates the usefulness of our ASPB algorithm as a reasonably fast and accurate tool for quality assurance in planning wide beam proton therapy treatment of clinical sites either composed of homogeneous materials or containing laterally extended inhomogeneities that are comparable in density and located away from the Bragg peak depths.
Mitochondrial proteome reconstruction from eukaryotic sequence data typically relies on prediction of mitochondrial targeting signals (MTSs). However, MTS predictors are primarily trained on model organisms and may perform poorly in phylogenetically divergent lineages or in organisms with atypical or reduced targeting sequences. Accurate reconstruction therefore requires integration of complementary sources of evidence beyond targeting prediction alone. We developed Comprehensive Mitochondrial Reconstructor (CoMR), an integrative workflow that combines targeting prediction, curated homology searches, large-scale similarity searches, and automated phylogenetic analysis within a unified scoring framework. Benchmarking on the model yeast Saccharomyces cerevisiae yielded strong discriminatory performance [receiver operating characteristic (ROC)-area under the curve (AUC) = 0.92], exceeding standalone prediction with TargetP2, a predictor of N-terminal targeting peptides (ROC-AUC = 0.72). In the divergent anaerobic protist Paratrimastix pyriformis, CoMR maintained robust performance (ROC-AUC = 0.86) validated with an experimental proteome despite extreme class imbalance, achieving a precision-recall AUC of 0.183 (~78-fold enrichment over random expectation and ~10-fold improvement over TargetP2). Ablation analyses demonstrate that predictive performance is robust to individual evidence-layer removal, while overlap analyses showed that homology-based searches recovered candidates missed by targeting predictors, particularly in P. pyriformis. Overall, CoMR improves mitochondrial proteome reconstruction over targeting prediction alone and provides a reproducible workflow for predicting mitochondrial and mitochondrion-related organelle protein repertoires across eukaryotes to aid investigations of organelle evolution and proteome reduction.
BACKGROUND: The first stage in computerised processing of the electrocardiogram is beat detection. This involves identifying all cardiac cycles and locating the position of the beginning and end of each of the identifiable waveform components. The accuracy at which beat detection is performed has significant impact on the overall classification performance, hence efforts are still being made to improve this process. METHODS: A new beat detection approach is proposed based on the fundamentals of cross correlation and compared with two benchmarking approaches of non-syntactic and cross correlation beat detection. The new approach can be considered to be a multi-component based variant of traditional cross correlation where each of the individual inter-wave components are sought in isolation as opposed to being sought in one complete process. Each of three techniques were compared based on their performance in detecting the P wave, QRS complex and T wave in addition to onset and offset markers for 3000 cardiac cycles. RESULTS: Results indicated that the approach of multi-component based cross correlation exceeded the performance of the two benchmarking techniques by firstly correctly detecting more cardiac cycles and secondly provided the most accurate marker insertion in 7 out of the 8 categories tested. CONCLUSION: The main benefit of the multi-component based cross correlation algorithm is seen to be firstly its ability to successfully detect cardiac cycles and secondly the accurate insertion of the beat markers based on pre-defined values as opposed to performing individual gradient searches for wave onsets and offsets following fiducial point location.
Despite the enormous time and energy that goes into strategy development, many companies have little to show for their efforts. Indeed, research by the consultancy Marakon Associates suggests that companies on average deliver only 63% of the financial performance their strategies promise. In this article, Michael Mankins and Richard Steele of Marakon present the findings of this research. They draw on their experience with high-performing companies like Barclays, Cisco, Dow Chemical, 3M, and Roche to establish some basic rules for setting and delivering strategy: Keep it simple, make it concrete. Avoid long, drawn-out descriptions of lofty goals and instead stick to clear language describing what your company will and won't do. Debate assumptions, not forecasts. Create cross-functional teams drawn from strategy, marketing, and finance to ensure the assumptions underlying your long-term plans reflect both the real economics of your company's markets and its actual performance relative to competitors. Use a rigorous analytic framework. Ensure that the dialogue between the corporate center and the business units about market trends and assumptions is conducted within a rigorous framework, such as that of "profit pools". Discuss resource deployments early. Create more realistic forecasts and more executable plans by discussing up front the level and timing of critical deployments. Clearly identify priorities. Prioritize tactics so that employees have a clear sense of where to direct their efforts. Continuously monitor performance. Track resource deployment and results against plan, using continuous feedback to reset assumptions and reallocate resources. Reward and develop execution capabilities. Motivate and develop staff. Following these rules strictly can help narrow the strategy-to-performance gap.
This article describes a risk-adjusted approach for profiling hospitals and physicians on clinical quality indicators using readily available administrative data. By comparing risk-adjusted rates of mortality, complications, and readmissions to peers, national norms, and benchmarks, this approach enables purchasers and providers to identify both favorable and adverse outcomes performance.
Performance management is an important mechanism for ensuring accountability and improving the quality of health-care services. The last decade has witnessed a proliferation in the development of performance measurement systems for assessing health-care processes and outcomes at the program, hospital, district, system and national level. This has allowed for comparison and benchmarking between similar aspects of care at each of these levels. Unfortunately, most performance systems are devoid of clear mechanisms for translating feedback from measures into strategies for action, thus leaving largely unfulfilled the quality and management aspect necessary to improve health-care services. Therefore, the thinking that goes into designing these systems must change. This article outlines a management framework called systematic outcome mapping that provides for performance management rather than just performance measurement by allowing for quality improvement to be built into performance indicator development. It utilizes evidence-based medicine and expert consensus opinion to establish linkages between processes of care and their outcomes with the clear intent that feedback from information provided by performance indicators can be used to modify health-care activities so as to improve health outcomes. This fulfils the quality improvement aspect of performance measurement and makes it an integral part of a performance management framework that reinforces organizational learning through feedback from outcomes and the assessment of organizational routines.
The Department of Defense issued a Request for Proposal (RFP) for its next generation Picture Archiving and Communications System in January of 1997. The RFP was titled Digital Imaging Network-Picture Archiving and Communications System (DIN-PACS). Benchmark testing of the proposed vendors' systems occurred during the summer of 1997. This article highlights the methods for test material and test system organization, the major areas tested, and conduct of actual testing. Department of Defense and contract personnel wrote test procedures for benchmark testing based on the important features of the DIN-PACS Request for Proposal. Identical testing was performed with each vendor's system. The Digital Imaging and Communications in Medicine (DICOM) standard images used for the Benchmark Testing included all modalities. The images were verified as being DICOM standard compliant by the Mallinckrodt Institute of Radiology, Electronic Radiology Laboratory. The Johns Hopkins University Applied Physics Laboratory prepared the Unix-based server for the DICOM images and operated it during testing. The server was loaded with the images and shipped to each vendor's facility for on-site testing. The Defense Supply Center, Philadelphia (DSCP), the Department of Defense agency managing the DIN-PACS contract, provided representatives at each vendor site to ensure all tests were performed equitably and without bias. Each vendor's system was evaluated in the following nine major areas: DICOM Compliance; System Storage and Archive of Images; Network Performance; Workstation Performance; Radiology Information System Performance; Composite Health Care System/Health Level 7 communications standard Interface Performance; Teleradiology Performance; Quality Control; and Failover Functionality. These major sections were subdivided into workable test procedures and were then scored. A combined score for each section was compiled from this data. The names of the involved vendors and the scoring for each is contract sensitive and therefore can not be discussed. All of the vendors that underwent the benchmark testing did well. There was no one vendor that was markedly superior or inferior. There was a typical bell shaped curve of abilities. Each vendor had their own strong points and weaknesses. A standardized benchmark protocol and testing system for PACS architectures would be of great value to all agencies planning to purchase a PACS. This added information would assure the purchased system meets the needed functional requirements as outlined by the purchasers PACS Request for Proposal.
Various methods exist to calculate confidence intervals for the benchmark dose in risk analysis. This study compares the performance of three such methods in fitting nonlinear dose-response models: the delta method, the likelihood-ratio method, and the bootstrap method. A data set from a developmental toxicity test with continuous, ordinal, and quantal dose-response data is used for the comparison of these methods. Nonlinear dose-response models, with various shapes, were fitted to these data. The results indicate that a few thousand runs are generally needed to get stable confidence limits when using the bootstrap method. Further, the bootstrap and the likelihood-ratio method were found to give fairly similar results. The delta method, however, resulted in some cases in different (usually narrower) intervals, and appears unreliable for nonlinear dose-response models. Since the bootstrap method is more time consuming than the likelihood-ratio method, the latter is more attractive for routine dose-response analysis. In the context of a probabilistic risk assessment the bootstrap method has the advantage that it directly links to Monte Carlo analysis.
This article discusses methods of mapping and standardizing processes in physician offices and ambulatory settings. It reviews the phenomenon of process shift: how a process, once established, changes over time and loses its effectiveness. The article presents the importance of this shift and how it leads to poor performance, along with methods to prevent it from occurring. The author details the development of process measures and internal benchmarking as a way of ensuring the ongoing integrity of office operations and maintenance of a high-performing office. The author also reviews the need to link job descriptions to process flowcharts.
New York State has been collecting performance data from managed care plans that serve the Medicaid population since 1993. The data come to the state via the Quality Assurance Reporting Requirements--a series of quality of care, access, and utilization measures, largely based on the Health Plan Employer Data and Information Set, as well as several New York State-specific measures. In addition to collecting the data, the state publishes the information, works with plans that have below average rates of performance and provides a number of program and financial rewards to plans for rates that demonstrate high quality care. An analysis conducted on quality of care measures indicates that: (1) performance rates are increasing over time, (2) Quality Assurance Reporting Requirements rates are generally higher than national benchmarks, (3) the disparity between commercial plan rates and Medicaid rates is diminishing, and (4) the variability in performance across plans is decreasing. The analysis conducted indicates that the performance measurement system constructed in New York is an effective means to monitor health plan performance, while at the same time enabling the state and local health units to monitor population health and accomplishment of key public health objectives (complete immunization, cancer screening, etc.)
Bank failure prediction is an important issue for the regulators of the banking industries. The collapse and failure of a bank could trigger an adverse financial repercussion and generate negative impacts such as a massive bail out cost for the failing bank and loss of confidence from the investors and depositors. Very often, bank failures are due to financial distress. Hence, it is desirable to have an early warning system (EWS) that identifies potential bank failure or high-risk banks through the traits of financial distress. Various traditional statistical models have been employed to study bank failures [J Finance 1 (1975) 21; J Banking Finance 1 (1977) 249; J Banking Finance 10 (1986) 511; J Banking Finance 19 (1995) 1073]. However, these models do not have the capability to identify the characteristics of financial distress and thus function as black boxes. This paper proposes the use of a new neural fuzzy system [Foundations of neuro-fuzzy systems, 1997], namely the Generic Self-organising Fuzzy Neural Network (GenSoFNN) [IEEE Trans Neural Networks 13 (2002c) 1075] based on the compositional rule of inference (CRI) [Commun ACM 37 (1975) 77], as an alternative to predict banking failure. The CRI based GenSoFNN neural fuzzy network, henceforth denoted as GenSoFNN-CRI(S), functions as an EWS and is able to identify the inherent traits of financial distress based on financial covariates (features) derived from publicly available financial statements. The interaction between the selected features is captured in the form of highly intuitive IF-THEN fuzzy rules. Such easily comprehensible rules provide insights into the possible characteristics of financial distress and form the knowledge base for a highly desired EWS that aids bank regulation. The performance of the GenSoFNN-CRI(S) network is subsequently benchmarked against that of the Cox's proportional hazards model [J Banking Finance 10 (1986) 511; J Banking Finance 19 (1995) 1073], the multi-layered perceptron (MLP) and the modified cerebellar model articulation controller (MCMAC) [IEEE Trans Syst Man Cybern: Part B 30 (2000) 491] in predicting bank failures based on a population of 3635 US banks observed over a 21 years period. Three sets of experiments are performed-bank failure classification based on the last available financial record and prediction using financial records one and two years prior to the last available financial statements. The performance of the GenSoFNN-CRI(S) network as a bank failure classification and EWS is encouraging.
Activation barriers and reaction energetics for the three main classes of 1,3-dipolar cycloadditions, including nine different reactions, were evaluated with the MPW1K and B3LYP density functional methods, MP2, and the multicomponent CBS-QB3 method. The CBS-QB3 values were used as standards for 1,3-dipolar cycloaddition activation barriers and reaction energetics, and the density functional theory (DFT) and MP2 methods were benchmarked against these values. The MPW1K/6-31G* method and basis set performs best for activation barriers, with a mean absolute deviation (MAD) value of 1.1 kcal/mol. The B3LYP/6-31G* method and basis set performs best for reaction enthalpies, with a MAD value of 2.4 kcal/mol, while the MPW1K method shows large errors for reaction energetics. The MP2 method gives the expected systematic underestimation of barriers. Concerted and nearly synchronous transition structures are predicted by all DFT and MP2 methods. Also reported are revised estimated 0 K experimental activation enthalpies for a standard set of hydrocarbon pericyclic reactions and updated comparisons to experiment for DFT, ab initio, and multicomponent methods. B3LYP and MPW1K methods with MAD values of 1.5 and 2.1 kcal/mol, respectively, fortuitously outperform the multicomponent CBS-QB3 method, which has a MAD value of 2.3. The MAD value of the O3LYP functional improves to 2.4 kcal/mol from the previously reported 3.0 kcal/mol.
Despite improved understanding and treatment of community acquired pneumonia (CAP), variations in clinical practice and patient outcomes still exists, resulting in excess healthcare dollars spent and decreased patient satisfaction. The use of treatment and outcomes research data can help providers improve their methods and standardize techniques to control costs and provide the best care for their patients. To better understand the utility and capabilities of this research, this article will compare several administrative and clinical databases. Two, data sources in particular, the EPI-Q Inc. CAP-Compare database and the University HealthSystem Consortium's (UHC) CAP Benchmarking Program contain clinical and utilization data specific to CAP. In addition there are several government and non-government sponsored data sources that include administrative data on many diagnosis including CAP. These include: Healthcare Benchmarking Systems International's EXPLORE database, the Center for Healthcare Industry Performance Studies database, the National Center for Health Statistics'--National Hospital Discharge Survey, and the Medicare Provider Analysis and Review data files.
A novel electronic eigenvalue (EEVA) descriptor of molecular structure for use in the derivation of predictive QSAR/QSPR models is described. Like other spectroscopic QSAR/QSPR descriptors, EEVA is also invariant as to the alignment of the structures concerned. Its performance was tested with respect to the CBG (corticosteroid binding globulin) affinity of 31 benchmark steroids. It appeared that the electronic structure of the steroids, i.e., the "spectra" derived from molecular orbital energies, is directly related to the CBG binding affinities. The predictive ability of EEVA is compared to other QSAR approaches, and its performance is discussed in the context of the Hammett equation. The good performance of EEVA is an indication of the essential quantum mechanical nature of QSAR. The EEVA method is a supplement to conventional 3D QSAR methods, which employ fields or surface properties derived from Coulombic and van der Waals interactions.
An effective potential function is critical for protein structure prediction and folding simulation. Simplified protein models such as those requiring only Calpha or backbone atoms are attractive because they enable efficient search of the conformational space. We show residue-specific reduced discrete-state models can represent the backbone conformations of proteins with small RMSD values. However, no potential functions exist that are designed for such simplified protein models. In this study, we develop optimal potential functions by combining contact interaction descriptors and local sequence-structure descriptors. The form of the potential function is a weighted linear sum of all descriptors, and the optimal weight coefficients are obtained through optimization using both native and decoy structures. The performance of the potential function in a test of discriminating native protein structures from decoys is evaluated using several benchmark decoy sets. Our potential function requiring only backbone atoms or Calpha atoms have comparable or better performance than several residue-based potential functions that require additional coordinates of side-chain centers or coordinates of all side-chain atoms. By reducing the residue alphabets down to size 10 for contact descriptors, the performance of the potential function can be further improved. Our results also suggest that local sequence-structure correlation may play important role in reducing the entropic cost of protein folding.