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Results for “Performance benchmarking”

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PubMed2001

Confidentiality in health records: evidence of current performance from a population survey in South Australia.

OBJECTIVE: To determine attitudes towards doctors and hospitals as data custodians, and patients' experiences of unauthorised information releases from health services. DESIGN: Analysis of data from a cross-sectional, descriptive household survey (October-November 1999). SETTING: South Australian community. PARTICIPANTS: 3,013 randomly selected residents over 15 years of age. MAIN OUTCOME MEASURES: Level of confidence in doctors and hospitals as data custodians, and patient-reported experience of unauthorised information releases by health services. RESULTS: 288 survey participants (9.6%) were not confident that healthcare providers keep and use information responsibly, 108 (3.6%) reported that healthcare providers had released information without their consent (although at least 48 of these disclosures were legally defensible), and 57 (1.9%) reported harm arising from unauthorised disclosures by health services. Projecting these findings to the South Australian population, over 2,000 people experienced harm arising from unauthorised information release in 1999. However, in the same period, there were fewer than 20 formal complaints to major agencies (eg, Ombudsman, Medical Board). CONCLUSIONS: Healthcare providers have lost the confidence of a minority of patients. For some, this mistrust is based on experience of unauthorised information release. Some disclosures are mandated by legislation. These findings provide baseline performance measures for benchmarking trends in patient confidence and prevalence of unauthorised release of patient information.

Adult↗
PubMed1994

Benchmarking in healthcare organizations: an introduction.

Business survival is increasingly difficult in the contemporary world. In order to survive, organizations need a commitment to excellence and a means of measuring that commitment and its results. Benchmarking provides one method for doing this. As the author describes, benchmarking is a performance improvement method that has been used for centuries. Recently, it has begun to be used in the healthcare industry where it has the potential to improve significantly the efficiency, cost-effectiveness, and quality of healthcare services.

Commerce↗
PubMed2000

Self-organizing neural networks for modeling 3D QSAR--a comparative study.

Different architectures of self-organizing neural networks (SOM) have been used for modeling 3D QSAR. The atomic coordinates and partial atomic charges were used as input signals. In particular, the steroids complexing corticosteroid binding globulin (CBG) that are used as a benchmark measuring the performance of drug design methods have been applied to compare between individual methods. The sensitivity of the different architectures for changes of the alignments of the molecules within series, as well as the possibility for alignments based on the molecular inertial axes have been tested.

Drug Design↗
PubMed2001

Demonstrating the cost effectiveness of an expert occupational and environmental health nurse: application of AAOHN's success tools. American Association of Occupational Health Nurses.

According to DiBenedetto, "Occupational health nurses enhance and maximize the health, safety, and productivity of the domestic and global work force" (1999b). This project clearly defined the multiple roles and activities provided by an occupational and environmental health nurse and assistant, supported by a part time contract occupational health nurse. A well defined estimate of the personnel costs for each of these roles is helpful both in demonstrating current value and in future strategic planning for this department. The model highlighted both successes and a business cost savings opportunity for integrated disability management. The AAOHN's Success Tools (1998) were invaluable in launching the development of this cost effectiveness model. The three methods were selected from several tools of varying complexities offered. Collecting available data to develop these metrics required internal consultation with finance, human resources, and risk management, as well as communication with external health, safety, and environmental providers in the community. Benchmarks, surveys, and performance indicators can be found readily in the literature and online. The primary motivation for occupational and environmental health nurses to develop cost effectiveness analyses is to demonstrate the value and worth of their programs and services. However, it can be equally important to identify which services are not cost effective so knowledge and skills may be used in ways that continue to provide value to employers (AAOHN, 1996). As evidence based health care challenges the occupational health community to demonstrate business rationale and financial return on investment, occupational and environmental health nurses must meet that challenge if they are to define their preferred future (DiBenedetto, 2000).

Cost-Benefit Analysis↗
PubMed2003

Automated quality checks on repeat prescribing.

BACKGROUND: Good clinical practice in primary care includes periodic review of repeat prescriptions. Markers of prescriptions that may need review have been described, but manually checking all repeat prescriptions against the markers would be impractical. AIM: To investigate the feasibility of computerising the application of repeat prescribing quality checks to electronic patient records in United Kingdom (UK) primary care. DESIGN OF STUDY: Software performance test against benchmark manual analysis of cross-sectional convenience sample of prescribing documentation. SETTING: Three general practices in Greater Manchester, in the north west of England, during a 4-month period in 2001. METHOD: A machine-readable drug information resource, based on the British National Formulary (BNF) as the 'gold standard' for valid drug indications, was installed in three practices. Software raised alerts for each repeat prescribed item where the electronic patient record contained no valid indication for the medication. Alerts raised by the software in two practices were analysed manually. Clinical reaction to the software was assessed by semi-structured interviews in three practices. RESULTS: There was no valid indication in the electronic medical records for 14.8% of repeat prescribed items. Sixty-two per cent of all alerts generated were incorrect. Forty-three per cent of all incorrect alerts were as a result of errors in the drug information resource, 44% to locally idiosyncratic clinical coding, 8% to the use of the BNF without adaptation as a gold standard, and 5% to the inability of the system to infer diagnoses that, although unrecorded, would be 'obvious' to a clinical reading the record. The interviewed clinicians supported the goals of the software. CONCLUSION: Using electronic records for secondary decision support purposes will benefit from (and may require) both more consistent electronic clinical data collection across multiple sites, and reconciling clinicians' willingness to infer unstated but 'obvious' diagnoses with the machine's inability to do the same.

Clinical Pharmacy Information Systems↗
PubMed2004

Support vector machines with profile-based kernels for remote protein homology detection.

Two new techniques for remote protein homology detection particulary suited for sparse data are introduced. These methods are based on position specific scoring matrices or profiles and use a support vector machine (SVM) for discrimination. The performance on standard benchmarks outperforms previous non-discriminative techniques and is comparable to that of other SVM-based methods while giving distinct advantages.

Algorithms↗
PubMed1989

Validation of methods used in dental caries diagnosis.

Accurate diagnosis of caries is critical both in clinical practice and epidemiology. Current knowledge of the validity of conventional caries diagnostic methods is reviewed and some theoretical aspects of the design and conduct of validation studies discussed. Four studies of the validity of clinical diagnostic methods are described and their findings summarized and compared. The results indicate that a trained and experienced examiner using a visual diagnostic technique can detect dentine caries, when it is shown to be present experimentally in borderline lesions, with a sensitivity exceeding 0.6, and can return a negative finding where disease is absent with a specificity exceeding 0.8. It is suggested that a visual technique of diagnosis which emphasizes specificity at the expense of some loss of sensitivity is the clinical method of choice, given a climate of low prevalence and slow progression of disease, the perceptual inability of imperfectly standardized examiners, and the adverse consequences of false-positive diagnoses. Selecting teeth with borderline lesions and balanced numbers of diseased and non-diseased sites is recommended for validation studies to allow standardized comparisons to be made and benchmarks for diagnostic performance to be established. However, an uncritical extrapolation of experimental findings to the general population of teeth is likely to lead to spurious assumptions about the consequences--in particular, of false-positive treatment decisions.

Dental Caries↗
PubMed1995

Including oncology outcomes of care in the computer-based patient record.

Changes in the health care system have caused a shift in research to outcomes of care, effectiveness, efficiencies, clinical practice guidelines, and costs. The greater use of computer systems, including decision support systems, quality assurance systems, effectiveness systems, cost containment systems, and networks, will be required to integrate administrative and patient care data for use in determining outcomes and resource management. This article describes developments to look forward to in the decade ahead, including the integration of outcomes data and clinical practice guidelines as content into computer-based patient records; the development of review criteria from clinical practice guidelines to be used in translating guidelines into critical paths; and feedback systems to monitor performance measures and benchmarks of care, and ultimately cost out cancer care.

Costs and Cost Analysis↗
PubMed1998

Identifying achievable benchmarks of care: concepts and methodology.

Webster's Dictionary defines a benchmark as 'something that serves as a standard by which others can be measured'. Benchmarking pervades the health care quality improvement literature, and benchmarks are usually based on subjective assessment rather than on measurements derived from data. As such, benchmarks may fail to yield an achievable level of excellence that can be replicated under specific conditions. In this paper, we provide an overview of benchmarking in health care. We then describe the evolution of our data-driven method for identifying an Achievable Benchmark of Care (ABC) on the basis of process-of-care indicators. Here, our experience leads us to postulate the following premises for sound benchmarks: (i) benchmarks should represent a level of excellence; (ii) benchmarks should be demonstrably attainable; (iii) providers with high performance should be selected from among all providers in a predefined way using reliable data; (iv) all providers with high performance levels should contribute to the benchmark level; and (v) providers with high performance levels but small numbers of cases should not unduly influence the level of the benchmark. An example of an ABC applied to the cooperative cardiovascular project leads the reader through the computation of an ABC. Finally, we consider several refinements of the original ABC concept that are in progress, e.g. how to approach the special problems posed by very small denominators. The ABC methodology has been well accepted in multiple quality improvement projects. This approach lends objectivity and reliability to benchmarks that have been a widely used, but until now, arbitrarily defined tool.

Alabama↗
PubMed2006

Laboratory benchmarking: the College of American Pathologists' experience.

Benchmarking is an important part of performance evaluation in the clinical laboratory. When used effectively, benchmarking can lead to significant changes and performance improvement. This article reviews the experience of the College of American Pathologists (CAP) with benchmarking clinical laboratory expenses and presents data that summarizes recent laboratory trends identified through CAP's benchmark data.

Benchmarking↗
PubMed1998

A fast neural-network algorithm for VLSI cell placement.

Cell placement is an important phase of current VLSI circuit design styles such as standard cell, gate array, and Field Programmable Gate Array (FPGA). Although nondeterministic algorithms such as Simulated Annealing (SA) were successful in solving this problem, they are known to be slow. In this paper, a neural network algorithm is proposed that produces solutions as good as SA in substantially less time. This algorithm is based on Mean Field Annealing (MFA) technique, which was successfully applied to various combinatorial optimization problems. A MFA formulation for the cell placement problem is derived which can easily be applied to all VLSI design styles. To demonstrate that the proposed algorithm is applicable in practice, a detailed formulation for the FPGA design style is derived, and the layouts of several benchmark circuits are generated. The performance of the proposed cell placement algorithm is evaluated in comparison with commercial automated circuit design software Xilinx Automatic Place and Route (APR) which uses SA technique. Performance evaluation is conducted using ACM/SIGDA Design Automation benchmark circuits. Experimental results indicate that the proposed MFA algorithm produces comparable results with APR. However, MFA is almost 20 times faster than APR on the average.

Journal Article↗
PubMedDate not supplied

The development of a benchmarking system for a cancer patient population.

Benchmarking, while a useful way to compare outcomes among health care institutions, has been less useful for institutions dealing with specialty patient populations such as cancer, rehabilitation, or psychiatry. Because of regulatory requirements mandating the use of benchmarking for accreditation and performance improvement purposes, a group of comprehensive cancer centers developed a specialized database for benchmarking outcomes for cancer patients. This article describes the development of the database and some of the obstacles encountered by the group. It also outlines solutions to the obstacles. Key words: benchmarking, cancer, quality

Benchmarking↗
PubMed2002

Benchmarking Veterans Affairs Medical Centers in the delivery of preventive health services: comparison of methods.

OBJECTIVE: To identify consistent provision of clinical preventive services, we sought to benchmark all acute care Veterans Affairs Medical Centers (VAMCs) against each other nationally on the basis of multiple evidence-based, performance measures to identify facilities performing consistently higher and lower than expected. METHODS: The 1998 Veterans Health Survey assessed the self-reported delivery of evidence-based clinical preventive services in a stratified national sample of 450 ambulatory care patients seen at each VAMC. Proportions appropriately receiving each service within the recommended time interval were calculated for 138 VAMCs. Percentile ranks for each outcome were assigned. Two approaches were used for benchmarking performance. First, a scaled score for each facility was calculated across the set of 12 measures. Second, facilities were ranked based on the sum of the percentile ranks over a range of specific high cutoffs (eg, 70-80%) and above a range of lower cutoffs (eg, 40-50%). Ranking was validated by comparing with deciles of ranks on chart audit (External Peer Review Program, EPRP) data using Kendall's tau-b and chi2 quality-of-fit test. Differences between consistently high adherence (CHA) and low adherence (CLA) facilities were compared using the Wilcoxon rank sum test on 14 VHS and 11 EPRP outcomes. RESULTS: Data from 39,939 patients (67% response rate) were examined. In combination, cutoffs of greater than 50th percentile and greater than 75th percentile rank yielded 12 of 14 VHS and 6 of 11 EPRP measures different between CHA and CLA facilities. The scaled-score approach resulted in 20 CHA and 14 CLA facilities. The sum of outcomes ranked above 50th percentile and over 75th percentile for CHA facilities (n = 17) was 15 or more. The sum of outcomes ranked above the same cutoffs for CLA facilities (n = 16) was 3 or less. EPRP and 1998 VHS data demonstrated that the survey measures and benchmarking approaches were both reliable and valid. Both approaches resulted in multiple differences between CHA and CLA facilities; differences were greater using the percentile rank approach. CONCLUSIONS: The VA has successfully encouraged adoption of evidence-based clinical preventive services throughout its health care system. However, facilities show wide variation in their levels of delivery and can be distinguished on the basis of their consistently high or low levels of adherence. Examining service delivery across multiple performance indicators allows identification of opportunities to improve clinical practice guideline implementation and the delivery of preventive services. This approach identifies model institutions where focused investigation of factors associated with consistent performance may be particularly fruitful.

Adult↗
PubMed1999

Hidden Markov models that use predicted secondary structures for fold recognition.

There are many proteins that share the same fold but have no clear sequence similarity. To predict the structure of these proteins, so called "protein fold recognition methods" have been developed. During the last few years, improvements of protein fold recognition methods have been achieved through the use of predicted secondary structures (Rice and Eisenberg, J Mol Biol 1997;267:1026-1038), as well as by using multiple sequence alignments in the form of hidden Markov models (HMM) (Karplus et al., Proteins Suppl 1997;1:134-139). To test the performance of different fold recognition methods, we have developed a rigorous benchmark where representatives for all proteins of known structure are matched against each other. Using this benchmark, we have compared the performance of automatically-created hidden Markov models with standard-sequence-search methods. Further, we combine the use of predicted secondary structures and multiple sequence alignments into a combined method that performs better than methods that do not use this combination of information. Using only single sequences, the correct fold of a protein was detected for 10% of the test cases in our benchmark. Including multiple sequence information increased this number to 16%, and when predicted secondary structure information was included as well, the fold was correctly identified in 20% of the cases. Moreover, if the correct secondary structure was used, 27% of the proteins could be correctly matched to a fold. For comparison, blast2, fasta, and ssearch identifies the fold correctly in 13-17% of the cases. Thus, standard pairwise sequence search methods perform almost as well as hidden Markov models in our benchmark. This is probably because the automatically-created multiple sequence alignments used in this study do not contain enough diversity and because the current generation of hidden Markov models do not perform very well when built from a few sequences.

Amino Acid Sequence↗