Quality Performance Metrics Research Articles

Hospital compound level surgical training quality performance metrics: more than a score?

In the dynamic climate of surgical training, we examine whether hospital units influence variations in attainment.

On the relations between focus, experience, and hospital performance.

In the United States, a long-standing debate has existed over advantages/disadvantages of general versus specialty hospitals. A recent stream of research has investigated whether general hospitals accrue performance benefits from a focus strategy; a strategy of specializing in certain clinical conditions while remaining a multiproduct firm. In contrast, a substantial and long-standing body of research on hospitals has been concerned with the absolute volume of cases in a service area as an indication of experience based largely on the idea that absolute volume confers learning opportunities. We investigated whether hospital focus and experience in a service area have complementary effects or are largely substitutive for hospital performance. Key data sources were patient discharge records and hospital discharge profiles from California's Office of Statewide Health Policy and Development for years 2010-2014. We specified hospital focus as the proportion of total cardiology-related discharges and hospital experience as the cumulative volume of cardiology-related discharges for each hospital. Performance was specified using quality (inpatient mortality and 30-day readmission) and efficiency (length of stay and cost) patient-level performance metrics. We analyzed the data using logistic and log-linear ordinary least squares regression models. Study results generally supported our hypotheses that focus and experience are related to better quality and efficiency performance and that the effects are largely substitutive for hospitals. Our study extends the literature by finding that hospitals exhibit distinct and stable patterns regarding their positioning on focus and experience and that these patterns have important implications for hospitals' performance in terms of quality and efficiency. Many general hospitals in the United States may be stretched too thin across service areas for which they lack necessary patient volumes for clinical proficiency. A viable alternative is to select a limited set of service areas on which to focus.

Performance of image pre-processing filters for noise removal in transformer oil images at different temperatures

The important goal of this paper is to investigate the performance of the image pre-processing filters for the removal of noise in real time transformer oil images which are captured at different temperatures. An experiment conducted to acquire transformer oil images instantaneously at the temperatures of 30 °C, 60 °C, 90 °C and 120 °C. Digital images need to be corrected before it is used for a particular application since they are generally corrupted by noise during image acquisition. In this paper, the acquired images are enhanced using different preprocessing filtering techniques such as mean, median, wiener and non local means filters. The performance of these image enhancement filters are validated using image quality performance metrics such as Mean Square Error [MSE] and Peak Signal to Noise Ratio [PSNR]. Through this study, it was found that non local means filter execute most excellent results compared to other filtering techniques.

Cepstrum adaptive plateau histogram for dark IR night vision images enhancement

This paper presents a novel enhancement algorithm for infrared (IR) images. This suggested algorithm mixes the benefits of the adaptive plateau histogram equalization (APH) and the cepstrum of homomorphic filtering enhancement (CHFE). The main idea of this approach depends on applying the APH on the IR image. Then, the resultant image is applied on the frequency domain by using the CHFE. This CHFE model is depending on the image has produced high energy that received from object. The energy received is determined by illumination radiation source and the features of reflectance of the object itself. Applying this model on the APH gives more details in the IR image and the IR night vision images show like as in the morning. The performance quality metrics for the suggested approach are entropy, average gradient, contrast, and Sobel edge magnitude. Simulation results reveal the success of the proposed approach in enhancing the quality of IR images.

Patient classification based on volume and case-mix in the emergency department and their association with performance.

Predicting daily patient volume is necessary for emergency department (ED) strategic and operational decisions, such as resource planning and workforce scheduling. For these purposes, forecast accuracy requires understanding the heterogeneity among patients with respect to their characteristics and reasons for visits. To capture the heterogeneity among ED patients (case-mix), we present a patient coding and classification scheme (PCCS) based on patient demographics and diagnostic information. The proposed PCCS allows us to mathematically formalize the arrival patterns of the patient population as well as each class of patients. We can then examine the volume and case-mix of patients presenting to an ED and investigate their relationship to the ED's quality and time-based performance metrics. We use data from five hospitals in February, July and November for the years of 2007, 2012, and 2017 in the city of Calgary, Alberta, Canada. We find meaningful arrival time patterns of the patient population as well as classes of patients in EDs. The regression results suggest that patient volume is the main predictor of time-based ED performance measures. Case-mix is, however, the key predictor of quality of care in EDs. We conclude that considering both patient volume and the mix of patients are necessary for more accurate strategic and operational planning in EDs.

The Effect of Hospital‐Physician Integration on Operational Performance: Evaluating Physician Employment for Cardiovascular Services

ABSTRACTA dramatic change in the hospital industry is the increasing emphasis on linking provider payment to quality performance metrics. This is one of several considerations leading hospitals to employ physicians. Yet, there is little evidence regarding whether physician employment as a form of hospital‐physician integration leads to better operational performance. Using data from 201 California hospitals that experienced a total of 405,766 eligible opportunities to conform to external performance metrics (conformance quality) for treating patients in the cardiovascular service area, we empirically evaluated the relationship between physician employment and conformance quality. We also evaluated whether the presence of core capabilities in the hospital's cardiovascular service area complements or substitutes for physician employment. Findings suggest that physician employment is not only positively associated with conformance quality, but also associated with more consistent conformance quality. Moreover, the presence of core capabilities in the service area substitutes for physician employment. Theoretical, managerial, and policy implications are discussed.

Eligibility of BPMN Models for Business Process Redesign

Business process redesign (BPR) is an organizational initiative for achieving competitive multi-faceted advantages regarding business processes, in terms of cycle time, quality, cost, customer satisfaction and other critical performance metrics. In spite of the fact that BPR tools and methodologies are increasingly being adopted, process innovation efforts have proven ineffective in delivering the expected outcome. This paper investigates the eligibility of BPMN process models towards the application of redesign methods inspired by data-flow communities. In previous work, the transformation of a business process model to a directed acyclic graph (DAG) has yielded notable optimization results for determining average performance of process executions consisting of ad-hoc processes. Still, the utilization encountered drawbacks due to a lack of input specification, complexity assessment and normalization of the BPMN model and application to more generic business process cases. This paper presents an assessment mechanism that measures the eligibility of a BPMN model and its capability to be effectively transformed to a DAG and be further subjected to data-centric workflow optimization methods. The proposed mechanism evaluates the model type, complexity metrics, normalization and optimization capability of candidate process models, while at the same time allowing users to set their desired complexity thresholds. An indicative example is used to demonstrate the assessment phases and to illustrate the usability of the proposed mechanism towards the advancement and facilitation of the optimization phase. Finally, the authors review BPMN models from both an SOA-based business process design (BPD) repository and relevant literature and assess their eligibility.

International expert consensus on a scientific approach to training novice cardiac resynchronization therapy implanters using performance quality metrics

AimsPacing and Cardiac Resynchronization Therapy (CRT) procedural training for novice operators usually takes place in-vivo and methods vary across countries/institutions. No common system exists to objectively assess trainee ability to perform required tasks at predetermined performance levels prior to in-vivo practice. We sought to characterize and validate with experts a reference approach to pacing/CRT implants based on objective and explicit performance quality metrics, for the development of a reproducible, simulation-based, training curriculum aiming to operator proficiency. MethodsThree experienced CRT implanters, a behavioural scientist and two engineers performed a detailed task deconstruction of the pacing/CRT procedure and identified the performance metrics (phases, steps, errors, critical errors) that constitute an optimal CRT implant for training purposes. The metrics were stress tested to determine reliability and score-ability and then subjected to detailed systematic review by an international panel of 15 expert implanters in a modified Delphi process. ResultsThirteen procedure phases were identified, consisting of 196 steps, 122 errors, 50 critical errors. The expert panel deliberation added 16 metrics, deleted 12, and modified 43. Unanimous panel consensus on the resulting CRT procedure metrics was obtained, which verified face and content validity. ConclusionA reference pacing/CRT procedure and metrics created by a core group of experts accurately characterize the essential components of performance and were endorsed by an international panel of experienced peers. The metrics will underpin quality-assured novice implanter training.

Fatores críticos de sucesso na gestão de projetos: Análise dos indicadores que constituem os predecessores da estratégia, pessoas e operações

Fatores Críticos de Sucesso (FCS) representam práticas que, quando bem executadas, contribuem para aumentar as probabilidades de êxito de qualquer atividade. Na gestão de projetos podem ser utilizados para acompanhamento dos projetos, tomada de decisão e avaliação de desempenho. O estudo de abordagem quantitativa e natureza descritiva, através de survey aplicada em 115 profissionais envolvidos na gestão de projetos, identifica, dentre os indicadores utilizados para mensurar os construtos estratégia, pessoas e operações, aqueles FCS que são mais importantes para explicar o desempenho do Project Management Office, para, então, com base na relação importância-desempenho discutir os fatores que correspondem a FCS no que se refere a gestão de projetos. A pesquisa utilizou a Partial Least Squares Structural Equation Modeling e o Importance-Performance Map Analysis. Os resultados mostram que a estratégia é o preditor mais importante e seus principais FCS são a metodologia de gerenciamento de projetos, a estrutura organizacional, o alinhamento de intenções e a viabilidade econômico-financeira. Nas operações, os principais FCS são a estabilidade do ambiente de projetos sobre o gerenciamento de riscos, o sistema de gestão da qualidade, as métricas de desempenho, as auditorias e verificações das entregas e a comunicação com as partes interessadas. Para as pessoas, os principais FCS são a aquisição de competências em gestão de projetos e o treinamento dos recursos humanos, ambos na perspectiva de disseminação do conhecimento vinculado as boas práticas, metodologias, ferramentas e técnicas que favorecem a execução dos projetos.

Enhancement of IR images using histogram processing and the Undecimated additive wavelet transform

This paper presents a fabulous enhancement approach for infrared (IR) images. This approach mixes the benefits of the undecimated Additive Wavelet Transform (AWT) with the homomorphic transform and Contrast Limited Adaptive Histogram Equalization (CLAHE). The basic idea of this approach depends on applying the CLAHE on the IR image. Then, the resultant image is decomposed into sub-bands using the AWT. The homomorphic enhancement is implemented on each sub-band, separately, up to the sixth sub-band. The homomorphic enhancement is applied on the IR image in the log domain by decomposing the image into illumination and reflectance components. The illumination is attenuated, while the reflectance is magnified. Applying this method on each sub-band gives more details in the IR image. The performance quality metrics for the suggested approach are entropy, average gradient, contrast, and Sobel edge magnitude. Simulation results reveal the success of the proposed approach in enhancing the quality of IR images.

Efficient interpolated compressed sensing reconstruction scheme for 3D MRI

3D magnetic resonance imaging (3D MRI) is one of the most preferred medical imaging modalities for the analysis of anatomical structures where acquisition of multiple slices along the slice select gradient direction is very common. In 2D multi-slice acquisition, adjacent slices are highly correlated because of very narrow inter-slice gaps. Application of compressed sensing (CS) in MRI significantly reduces traditional MRI scan time due to random undersampling. The authors first propose a fast interpolation technique to estimate missing samples in the k-space of a highly undersampled slice (H-slice) from k-space (s) of neighbouring lightly undersampled slice/s (L-slice). Subsequently, an efficient multislice CS-MRI reconstruction technique based on weighted wavelet forest sparsity, and joint total variation regularisation norms is applied simultaneously on both interpolated H and non-interpolated L-slices. Simulation results show that the proposed CS reconstruction for 3D MRI is not only computationally faster but significant improvements in terms of visual quality and quantitative performance metrics are also achieved compared to the existing methods.

Vertical Integration and Hospital Performance:Evaluating Physician Employment in Hospitals

A dramatic change in the hospital industry is the increasing emphasis on linking provider payment to quality performance metrics. This is one of several considerations leading hospitals to vertical...

Transient analysis of quality performance in two-stage manufacturing systems with remote quality information feedback

Abstract Recently modeling and analysis of product quality propagation in multi-stage manufacturing systems has received lots of attention. However, most existing results are focused on steady state performance, while transient analysis of system quality remains largely unexplored. When product changeover or scheduled maintenance happens, the system quality may undergo transients, which describe the system quality behavior before approaching the steady state at targeted levels of quality and cost. It is of practical importance to comprehensively investigate the quality performance especially during transients in order to reduce quality loss and improve product quality. In this paper, a Markov model is developed to address quality propagation in a two-stage manufacturing system with remote quality information feedback during transients. Based on the proposed mathematical model, analytical formulas for evaluating transient quality performance including the real-time product quality, settling time, and quality loss due to transients, are derived. In addition, the monotonicity properties of critical transient system characteristics and quality performance metrics are explored. The proposed method is validated with numerical data and real-world data, and the results demonstrate the effectiveness for transient quality analysis in two-stage manufacturing systems.

Successful Incorporation of Performance Based Payments for Trauma Center Readiness Costs into the Georgia Trauma System

As quality and outcomes have moved to the fore front of medicine in this era of healthcare reform, a state trauma system Performance Based Payments (PBP) program has been incorporated into trauma center readiness funding. The purpose of this study was to evaluate the impact of a PBP on trauma center revenue. From 2010 to 2016, a percentage of readiness costs funding to trauma centers was placed in a PBP and withheld until the PBP criteria were completed. To introduce the concept, only three performance criteria and 10 per cent of readiness costs funding were tied to PBP in 2010. The PBP has evolved over the last several years to now include specific criteria by level of designation with an increase to 50 per cent of readiness costs funding being tied to PBP criteria. Final PBP distribution to trauma centers was based on the number of performance criteria completed. During 2016, the PBP criteria for Level I and II trauma centers included participation in official state meetings/conference calls, required attendance to American College of Surgeons state chapter meetings, Trauma Quality Improvement Program, registry reports, and surgeon participation in Peer Review Committee and trauma alert response times. Over the seven-year study period, $36,261,469 was available for readiness funds with $11,534,512 eligible for the PBP. Only $636,383 (6%) was withheld from trauma centers. A performance-based program was successfully incorporated into trauma center readiness funding, supporting state performance measures without adversely affecting the trauma center revenue. Future PBP criteria may be aligned to designation standards and clinical quality performance metrics.

A decade of health assessments in Appalachia

PurposeThe purpose of this paper is to describe standardized clinical process of care and quality performance metrics at Roane Medical Center (RMC) and compare data from 2005 to 2015.Design/methodology/approachInformation was extracted from a nationwide sample of short-term acute care hospitals using the Hospital Quality Alliance (HQA) database, evaluating multiple parameters measured at RMC. HQA data from RMC were matched against state and national benchmarks; findings were also compared with similar reports from the same facility in 2005.FindingsInformation collected by HQA expanded substantially in ten years and queried different parameters over time, thus exact comparisons between 2005 and 2015 cannot be easily calculated. Nevertheless, analysis of process of care data for 2015 placed RMC at or above state- and national-average performance in 64.9 percent (24 of 37) and 56.5 percent (26 of 46) categories, respectively. RMC registered superior process of care scores in heart failure care, pneumonia care, thrombus prevention and care, as well as stroke care. While RMC continues to perform favorably against state and national reference groups, the differences between RMC vs state and RMC vs national averages using current reporting metrics were both statistically smaller in 2015 compared to 2005 (p<0.05).Research limitations/implicationsPerhaps the most significant interval health event for the RMC service area since 2005 was a coal ash spill at the nearby Tennessee Valley Authority facility in December 2008. Although reports on environmental and health effects following one of the largest domestic industrial toxin releases reached a number of important conclusions, the consequences for RMC in terms of potential added clinical burden on emergency services and impact on chronic health conditions have not been specifically studied. This could explain data reported on emergency department services at RMC but additional research will be needed to establish causality.Practical implicationsWhile tracking of care processes at all US hospitals will be facilitated by refinements in HQA tools, longitudinal evaluations for any specific unit will be more meaningful if the assessment instrument undergoes limited change over time.Social implicationsAppalachia remains one of several regions in the USA often identified as medically underserved. Hospitals here have confronted the challenge of diminished reimbursement, high expenses, limited staffing and other financial hardships in a variety of ways. Since the last published report on RMC, a particularly severe global recession has placed additional stress on organizations offering crucial health services in the region.Originality/valueAs a follow-up study to track potential changes which have been registered in the decade 2005-2015, this is the first report to provide original, longitudinal analysis on RMC, an institution operating in a rural and underserved area.

P1.03-021 Initial Results from A Novel and Low Cost Method For Measuring CT Image Quality

Accurate measurement of change in tumor size in Computed Tomography images is critical for lung nodule differential diagnosis. Standard CT scanner calibration phantoms and methods are routinely relied upon to ensure that image quality is generally sufficient for a wide range of imaging tasks. However, high precision medical imaging applications, such as RECIST and volumetric tumor change measurement, require much greater attention to maintaining consistently high image quality characteristics. A new ultra-low cost, and cloud based method has been developed to quickly assess the image quality of CT scanners and imaging protocols that provides both estimates of clinical task performance, such as lung tumor size measurement error rates, and fundamental image quality performance metrics. In addition, multiple large imaging organizations have made available lung cancer screening guidance documents indicating that CT slice thicknesses of <= 1.25 mm are either required or preferred. To demonstrate the image quality site measurement capability a global challenge was launched during May and June of 2016 that allowed lung cancer screening sites to scan three rolls of 3M ¾ × 1000 inch Scotch Magic ™ Tape placed at increasing distances from iso-center on the CT table and using their standard low dose lung cancer screening protocol. Fully automated software detected the rolls of tape and estimated fundamental image quality parameters including CT linearity, 3D resolution, noise, and level of edge enhancement. In addition, metrics indicating the expected detection and volume change measurement performance for different diameter lung nodules were calculated. A total of 27 clinical sites participated in the challenge and provided CT imaging data on over 54 CT scanners representing 18 scanner models made by Siemens, GE, Philips, and Toshiba. 17 out of 27 (63%) clinical sites provided data with ≤ 1.25mm DICOM specified slice thickness. However, only 19% of sites used ≤ 1.25mm slice thickness and a reconstruction kernel that avoided excessive smoothing and avoided high levels of edge enhancement. A new rapid, ultra-low cost, and cloud based method for assessing the quality of CT imaging studies has revealed poor adherence to recommended protocols and large levels of variation in fundamental image quality properties. Utilization of these new tools has the potential to help correct image quality issues in clinical studies.

Water quality and filter performance of nutrient-, oxidant- and media-enhanced drinking water biofilters

Enhancement strategies provided mixed outcomes for both water quality and filter performance metrics.

Quality Metrics in Urology

IntroductionThe focus of quality metrics is to ensure that physicians provide and practice within a standard of care, and to maximize patient benefit and safety. Several quality reporting programs in urology such as SCIP (Surgical Care Improvement Project, PQRS (Physician Quality Reporting System) and OPPE (Ongoing Professional Practice Evaluation)/FPPE (Focused Professional Practice Evaluation) have been used to review and monitor standards of care and improve medical care quality. Urological databases are emerging with the main focus of reviewing and assessing health care delivery quality and patient outcomes. Such data will likely influence future quality improvement measures and standards. Awareness and understanding of these programs and measurements are vital to continued successful urological practice. MethodsAUA (American Urological Association) and CMS (Centers for Medicare and Medicaid Services) documents were used. We reviewed program specific requirements, including minimal required data, timeline requirements, and specific incentives and penalties. ResultsQuality measures and programs in urology aim to monitor, standardize and improve medical care delivery in the United States. Since the implementation of electronic health records, the ability to review individual and group medical practices has become available and reviewable by outside agencies. Universal practice standards and government monitoring of individual and group achievement of those expectations are the current direction of health care. This is exemplified by the United States DHHS (Department of Health and Human Services) announcement of transitioning Medicare to a value based reimbursement model and the 9 HCTTF (Health Care Transformation Task Force) principles for accountable care organization footprint expansion. ConclusionsThe quality era has arrived. Its continued impact on health care delivery will be noted as public reporting and payment modifications based on quality indicators and performance metrics.

Data quality monitoring and performance metrics of a prospective, population-based observational study of maternal and newborn health in low resource settings.

BackgroundTo describe quantitative data quality monitoring and performance metrics adopted by the Global Network’s (GN) Maternal Newborn Health Registry (MNHR), a maternal and perinatal population-based registry (MPPBR) based in low and middle income countries (LMICs).MethodsOngoing prospective, population-based data on all pregnancy outcomes within defined geographical locations participating in the GN have been collected since 2008. Data quality metrics were defined and are implemented at the cluster, site and the central level to ensure data quality. Quantitative performance metrics are described for data collected between 2010 and 2013.ResultsDelivery outcome rates over 95% illustrate that all sites are successful in following patients from pregnancy through delivery. Examples of specific performance metric reports illustrate how both the metrics and reporting process are used to identify cluster-level and site-level quality issues and illustrate how those metrics track over time. Other summary reports (e.g. the increasing proportion of measured birth weight compared to estimated and missing birth weight) illustrate how a site has improved quality over time.ConclusionHigh quality MPPBRs such as the MNHR provide key information on pregnancy outcomes to local and international health officials where civil registration systems are lacking. The MNHR has measures in place to monitor data collection procedures and improve the quality of data collected. Sites have increasingly achieved acceptable values of performance metrics over time, indicating improvements in data quality, but the quality control program must continue to evolve to optimize the use of the MNHR to assess the impact of community interventions in research protocols in pregnancy and perinatal health.Trial registration numberNCT01073475

Data quality monitoring and performance metrics of a prospective, population-based observational study of maternal and newborn health in low resource settings

Data quality monitoring and performance metrics of a prospective, population-based observational study of maternal and newborn health in low resource settings