Quality Performance Measures Research Articles

Association Between Time of Day and the Decision for an Intrapartum Cesarean Delivery.

To examine whether the decision and indications for performing intrapartum cesarean delivery vary by time of day. We conducted a secondary analysis of a multicenter observational cohort of 115,502 deliveries (2008-2011), including nulliparous women with term, singleton, nonanomalous live gestations in vertex presentation who were attempting labor. Those who attempted home birth, or underwent cesarean delivery scheduled or decided less than 30 minutes after admission were excluded. Time of day was defined as cesarean delivery decision time among those who delivered by cesarean and delivery time among those who delivered vaginally, categorized by each hour of a 24-hour day. Primary outcomes were decision to perform cesarean delivery and the indications for cesarean delivery (labor dystocia, nonreassuring fetal status, or other indications). Secondary outcomes included whether a dystocia indication adhered to standards promoted to reduce cesarean delivery rates. Bivariate analyses were performed using χ and Kruskal-Wallis tests for categorical and continuous outcomes, respectively, and generalized additive models with smoothing splines explored nonlinear associations without adjustment for other factors. Seven thousand nine hundred fifty-six (22.1%) of 36,014 eligible women underwent cesarean delivery. Decision for cesarean delivery (P<.001) decreased from midnight (21.2%) to morning, reaching a nadir at 10:00 (17.9%) and subsequently rising to peak at 21:00 (26.2%). The frequency of cesarean delivery for dystocia also was significantly associated with time of day (P<.001) in a pattern mirroring overall cesarean delivery. Among cesarean deliveries for dystocia (n=5,274), decision for cesarean delivery at less than 5 cm dilation (P<.001), median duration from 5 cm dilation to cesarean delivery decision (P=.003), and median duration from complete dilation to cesarean delivery decision (P=.014) all significantly differed with time of day. The frequency of nonreassuring fetal status and "other" indications were not significantly associated with time of day (P>.05). Among nulliparous women who were attempting labor at term, the decision to perform cesarean delivery, particularly for dystocia, varied with time of day. Some of these differences correlate with labor management differences, given the changing frequency of latent phase cesarean delivery and median time in active phase.

Evidence-Based Performance Measures for Autologous Breast Reconstruction: An American Society of Plastic Surgeons Quality Performance Measure Set.

The American Society of Plastic Surgeons commissioned the Autologous Breast Reconstruction Performance Measure Development Work Group to identify and draft quality measures for the care of patients undergoing autologous breast reconstruction and other breast reconstruction surgery. Four outcome measures and one process measure were identified. Outcomes include patient satisfaction with information for all breast reconstruction, a subscale of the BREAST-Q, and the length of stay, operative time, and rate of blood transfusion for autologous blood transfusion. The process measure looks at coordination of care around managing the breast reconstruction patient's care, with the physician coordinating the ongoing care, be it an oncologist, radiologist, other specialist, or primary care physician. All measures in this report were approved by the American Society of Plastic Surgeons Quality and Performance Measures Work Group and the American Society of Plastic Surgeons Executive Committee. The Work Group recommends the use of these measures for quality initiatives, continuing medical education, maintenance of certification, American Society of Plastic Surgeons' Qualified Clinical Data Registry reporting, and national quality-reporting programs.

A robust reputation system using online reviews?

Evaluating sellers in an online marketplace is an important yet nontrivial task. Many online platforms such as eBay and Amazon rely on buyer reviews to estimate the reliability of sellers on their platform. Such reviews are, however, often biased by: (1) intentional attacks from malicious users and (2) conflation between a buyer?s perception of seller performance and item satisfaction. Here, we present a novel approach to mitigating these issues by decoupling measures of seller performance and item quality, while reducing the impact of malignant reviews. An extensive simulation study shows that our proposed method can recover seller reputations with high rank correlation even under assumptions of extreme noise.

A SERVPERF Based DEMING’S PDCA Mechanism for Quality Improvement of Management Educational Institutions

There are serious quality issues with higher education in developing countries. To change this situation and to accomplish appropriate quality it is essential to implement drastic techniques. Management Educational Institutions (MEI) needs to understand the customer centric philosophy. The application of Service Performance (SERVPERF) to measure quality performance providing service through institutions, also finding characteristics and quality components that meet the requirements of student as a customer of the system. The reliability and factor loading of 21 factors seen. Regression, correlation and anova also been tested. In MEI, the students are consumers of the services provided by the institution. Our paper gives the background theory and goes on to outline the results of a study on post graduate Business Administration students from particular MEI to get students outlook on models to improve quality of institutions. Based on outcome of SERVPERF Deming’s PDCA cycle is established for further quality improvements of these institutions.

Examining the financial and quality performance effects of group purchasing organizations.

Hospitals frequently enter into group purchasing organizations (GPOs) to manage supply costs, yet there is mixed evidence regarding the benefit for hospitals to participate in a GPO. However, the role of GPOs on hospital operations has expanded into dimensions of quality that have not been previously examined. The aim of this study was to examine the effect of hospital participation in a GPO, as well as GPO network characteristics, on both financial and quality performance outcomes. Data from multiple secondary sources regarding hospital and GPO characteristics were used to create an unbalanced panel of hospitals from 2012 to 2015. This data set was then aggregated to the GPO network level to address questions related to network characteristics, including concentration, bed size, geographic scope, and focus. We evaluated three hospital-level outcomes: supply expense, clinical processes of care score, and patient experience score. The mean of each outcome among all hospitals in a GPO in a given year was used for analyses at the network level. We used fixed and random effect models to assess the effect of hospital characteristics and network characteristics on three measures of financial and quality performance. We found no difference between GPO and non-GPO hospitals for any of the outcomes. However, analyses at the network level revealed network characteristics, including concentration, size, and scope, that affected both supply expense and patient experience scores, but not clinical processes of care. These results indicate that GPO participation may be motivated for reasons beyond cost and quality performance impacts. Hospitals and GPOs should consider network characteristics, such as the concentration and geographical dispersion of the GPO network. Alternatively, GPOs may seek to develop homogeneously sized networks dispersed locally in order to best deliver both financial and quality benefits to their members.

Three Wound Care Quality Performance Measures Are Now Public: Why It Matters

Three Wound Care Quality Performance Measures Are Now Public: Why It Matters

Influence of National Cultures on Operations Management and Supply Chain Management Practices—A Research Agenda

The role of national culture interactions is important in operations management and supply chain management decisions. Yet, cross‐cultural research in this field is limited. Our goal in this study is to review relevant research, to raise awareness about the critical role of national culture among operations management and supply chain management researchers, and to offer directions for future research. To achieve this goal, we report our research findings in three major categories: (i) Operational Decisions (innovation, and research and development, quality management, workforce management, performance measurement, and risk, security and disaster management); (ii) Supply Chain Management (buyer–supplier interactions, governance mechanisms, outsourcing, and offshore operations); and (iii) Interdisciplinary Topics (entrepreneurship, investments, joint ventures, and mergers and acquisitions). We also suggest methodological considerations for future research by those interested in studying national culture.

A framework for the evaluation of the perceived value added by internal auditing

PurposeThe purpose of this study is to propose a framework for the evaluation of the perceived value internal audit functions add to their organisations. The framework is based on service quality measurement principles, specifically SERVPERF, which is applied to internal auditing.Design/methodology/approachInsights obtained from the literature on internal auditing and service quality disciplines were synthesised to identify and structure value-adding attributes of internal auditing. A thematic analysis of published profiles (by Protiviti) of various organisations’ internal audit functions were analysed and evaluated against those attributes identified in the literature to formulate an evaluation framework based on service quality measurement principles.FindingsThe identified value-adding attributes were categorised according to the dimensions of the SERVPERF service quality measurement instrument to formulate a framework for evaluation of the value added by internal audit functions. It was found that the SERVPERF dimensions appear to be relevant to internal auditing. The SERVPERF instrument was therefore adapted to evaluate the value added by internal auditing as a service.Practical implicationsThis paper contributes to both the theory and practice of internal auditing by proposing formal dimensions of a value-adding internal audit service which can then serve as a reference point from which to evaluate the value added to an organisation. The framework can serve as a starting point for internal audit functions to develop their service offering and/or form the foundation of stakeholder satisfaction surveys.Originality/valueThe study contributes to the literature by applying service quality principles to internal auditing. A holistic framework that can be used for the evaluation of the value added by internal audit functions based on stakeholder perceptions is proposed. The framework juxtaposes attributes of value-adding internal auditing with recognised service quality performance measures. The notion of value added is investigated to better understand the concept in the context of internal auditing services.

Impact of a Resident-Centered Interprofessional Quality Improvement Intervention on Acute Care Length of Stay.

Competency in interprofessional quality improvement and performance measurement is required by the Accreditation Council for Graduate Medical Education. We implemented an interprofessional quality improvement project to support trainee involvement in systems-level improvement to reduce hospital length of stay and engage trainees in efforts to improve the validity and reliability of clinical documentation contributing to risk-adjusted performance measures. The intervention had three components: daily interprofessional disposition huddles to discuss discharge needs, medical documentation curriculum to improve clinical data accuracy, and scheduled coding huddles to provide real-time feedback on documentation. Outcome measures included an unadjusted and risk-adjusted measure of hospital length of stay. Case severity index (CSI) served as a process measure. Statistical process control charts were used to measure change over time. The mean unadjusted length of stay decreased from 5.84 to 4.98 days. Both the unadjusted and the risk-adjusted length of stay measures exceeded the lower control limit of the statistical control chart. The CSI increased and exceeded the upper control limit of the statistical control chart. Improvements were sustained in the year following implementation. The intervention offers a model for academic institutions to satisfy new Common Program Requirements by engaging trainees in performance measurement and interprofessional improvement efforts.

Optimal segmentation of high spatial resolution images for the classification of buildings using random forests

In the application of machine learning to geographic object based image analysis, several parameters influence overall classifier performance. One of the first parameters is segmentation size—for example, how many pixels should be grouped together to form an image object. Often, trial and error methods are used to obtain segmentation parameters that best delineate the borders of real world objects. Several attempts at automated methods have produced promising results, but manual intervention is still necessary. Meanwhile, numerous measures of segmentation quality have been defined, but their relationship to classifier performance is not then directly shown. For example, as measures of segmentation quality improve, do classification results improve as well? Our work considers the problem of building classification in high resolution aerial imagery of urban areas. Based on user defined training polygons generated with or without a reference segmentation, we have found several measures of segmentation quality and feature performance that can help users narrow the range of appropriate segmentations. Furthermore, our work finds that given this range, performance of machine learning algorithms remains relatively constant for any given segmentation as long as features used for classification are chosen correctly. We find that the range of scale parameters capable of producing an accurate classification is much broader than typically assumed and trial and error methods for finding this parameter may be an acceptable approach.

1261-P: Assessing Data Availability and Benchmarking Performance of Quality Measures for the T1D Exchange Quality Improvement Collaborative

The T1D Exchange QI Collaborative was formed in 2016 to accelerate quality improvement (QI) at clinics serving people with type 1 diabetes (T1D). Through an evidence-based review and idealized design process, the collaborative chose seven process and outcome measures to be the focus of improvement activities directed at high-risk T1D patients (2 or more A1c values &amp;gt;9% in the preceding year) aged 12-26 years. We report monthly aggregate statistics from seven Collaborative clinics for the measures and show the statistics for May and August 2018. A substantial percent of patients meet high risk criteria across all centers, and there is wide variation in performance measures. No center has the capacity to report on all measures, but there are incremental improvements in data availability. Outcomes remain suboptimal, particularly in this high-risk population. These measures will be continuously tracked to define network progress and to design QI interventions to improve glycemic outcomes. The work of the Collaborative and the creation of a technology platform will improve reporting capacity and drive QI activities. Disclosure A.B. Cabrera: None. G.T. Alonso: None. S. Corathers: None. J.M. Lee: Consultant; Self; Taiho Oncology, Inc. P. Prahalad: None. N. Rioles: None. Funding The Leona M. and Harry B. Helmsley Charitable Trust

Sustainability - Oriented Innovation and Performance of Small and Medium Enterprises in South Africa

The purpose of this study is to investigate the effect of sustainability-oriented innovation (SOI) on the performance of small and medium enterprises (SMEs) in South Africa. The study adopted a multi-dimensional measure of performance (financial, social, environmental, innovation and quality). The study used the quantitative research approach and the descriptive and causal research design. Data was collected from one hundred and ninety eight owners/managers of SMEs in the manufacturing sector. The cross-sectional survey method (self-administered questionnaire) was used for data collection. The participants in the study were conveniently sampled. Descriptive statistics, factor analysis, correlation and regression analysis were used for data analysis. The Cronbach’s alpha was used as a measure of reliability. The findings of the study indicate that economic, environmental and social dimensions of SOI have significant positive relationships with the five measures of performance. Limitations, areas for further study and recommendations to improve the SOI of SMEs are suggested.

Supply Chain Service Quality Improvement by E-marketplace Automation

E-marketplaces have become an essential part of e-commerce. In our research, a decentralized agent-based e-marketplace platform was devised. Although there are significant agent-based supply chain models in the literature, measuring quality performance using agents is still a subject of investigation. In order to improve overall supply chain service quality by allowing companies' agents to evaluate the service quality of their partners through the history of their transactions, this article proposes a service quality agent model. The model is designed using MCDM tools to suit different approaches to supply chain management. Consequently, since more informed procurement decisions are taking place continuously and autonomously at each node of a supply chain, supply chain service quality is being improved along the whole supply chain. At the end, the service quality valuation model of the supply chain is empirically evaluated.

Outdoor thermal comfort autonomy: Performance metrics for climate-conscious urban design

Thermal comfort in the built environment is a crucial factor impacting health, well-being, and productivity of urban dwellers. Accordingly, comprehensive analyses are needed to ensure that acceptable criteria of thermal comfort are defined and met in urban environments. The main objective of this study is to define such performance metrics and quality measures of outdoor thermal comfort (OTC), aiming to inform climate-conscious urban design. This article first discusses the motivations for introducing comprehensive thermal comfort metrics, addressing the shortcomings of conventional OTC evaluations that neglect the temporal or spatial variability of OTC. It then introduces four performance metrics, which collectively inform urban planners and designers on the performance of outdoor space with regards to thermal comfort. These metrics build upon the concept of “autonomy” previously introduced for indoor spaces and are extended to include the unique characteristics of outdoor thermal comfort. Second, we discuss the capability of these metrics given the limitations of modeling tools available for urban microclimate analysis, and evaluate the critical factors for an accurate evaluation of Outdoor Thermal Comfort Autonomy (OTCA). We observe that the spatial distribution of airflow at the pedestrian height is critical for OTCA calculation, while the consideration of realistic surface heating depends on the urban density. Lastly, we present an example of employing weather clustering methods such that OTC performance metrics are achieved on an annual basis in a comprehensive yet efficient way. By discussing the capability and the limitations of these metrics we aim to promote climate-conscious design using metrics that are tangible and accessible to non-simulationexperts.

Building Model-Driven Decision Support System in Product Redesign Plan

Product recovery strategy requires a thoughtful consideration of environmental implications of operational processes, undergone by a manufactured product in its entire product lifecycle, from stages of material processing, manufacturing, assembly, transportation, product use, product post-use and end-of-life. At the returns stream from product use stage, those parts and/or component assemblies from a used product have several disposition alternatives for recovery, such as direct reuse, remanufacture, recycle or disposal. Due to such complexity of the manufacturing processes in recovery, current decision methodologies focus on the performance measures of cost, time, waste and quality separately. In this article, an integrated decision model for used product returns stream is developed to measure the recovery of utilisation value in the aspects of cost, waste, time, and quality collectively. In addition, we proposed a model-driven decision support system (DSS) that may be useful for manufacturers in making recovery disposition alternatives. A case application was demonstrated with the use of model-driven DSS to measure recovery utilisation value for the used product disposition alternatives. Finally, the future work and contributions of this study are discussed.

Wood quality attribute models and their utility when integrated into density management decision-support systems for boreal conifers

The objectives of this study were to (1) develop wood quality prediction models for a suite of commercially-relevant jack pine (Pinus banksiana Lamb.) fibre attributes (wood density (Wd), microfibril angle (Ma), modulus of elasticity (Me), fibre coarseness (Co), tracheid wall thickness (Wt), tracheid radial (Dr) and tangential (Dt) diameters and specific surface area (Sa)), (2) given (1), incorporate the parameterized equations within structural stand density management models (SSDMMs), and (3) given (2), exemplify their utility in silvicultural decision-making via the comparative assessment of attribute outcomes arising from operationally-relevant crop plans. Analytically, the equations were developed deploying Silviscan-determined attributes derived from transverse breast-height radial xylem sequences obtained from 61 trees sampled from 2 geographically-separated thinning experiments located in the central region of the Canadian Boreal Forest Region. Hierarchical mixed-effects regression modeling combined with cross-validation procedures were used to specify, parameterize and evaluate the attribute-specific prediction equations. Overall, the results revealed that the attribute trajectories were size-dependent and the resultant models were adequate in terms of their goodness-of-fit characteristics (e.g., I2 values of 75, 71, 71, 66, 60, 55, 49 and 38% for Co, Me, Wt, Sa, Wd, Ma, Dr and Dt respectively), lack-of-fit indicators (e.g., temporally invariant patterns of absolute and relative errors devoid of evidence of systematic bias), and predictive performance (e.g., 95% probability that 95% of all future relative Dt, Dr, Sa, Wd, Co, Wt, Me and Ma errors would be within ±5, ±9, ±11, ±12, ±12, ±13, ±35 and ±43% of their true values, respectively). Incorporating the jack pine equations along with a similar suite of functions previously developed for black spruce (Picea mariana (Mill) B.S.P) into the SSDMM analytical framework, yielded a pair of enhanced stand-type-specific (natural-origin and planted stands) decision-support systems for each species. These systems enabled the estimation of attribute-specific developmental trajectories for the rotational tree population from which diameter-class and stand-level wood quality performance measures were derived. As exemplified, the development of size-dependent fibre attribute prediction models and their subsequent integration within SSDMMs provides forest managers with a decision-support platform for evaluating and comparing end-product-related consequences of selected crop plans.

Unintended consequences and challenges of quality measurements in dentistry

BackgroundIn recent years, several state dental programs, researchers and the Dental Quality Alliance (DQA) have sought to develop baseline quality measures for dentistry as a way to improve health outcomes, reduce costs and enhance patient experiences. Some of these measures have been tested and validated for various population groups. However, there are some unintended consequences and challenges with quality measurement in dentistry as observed from our previous work on refining and transforming dental quality measures into e-measures.Main bodySome examples of the unintended consequences and challenges associated with implementing dental quality measures include: a de-emphasis on patient-centeredness with process-based quality measures, an incentivization of unethical behavior due to fee-for-service reimbursement systems, the risk of compromising patient and provider autonomy with plan-level measures, a disproportionate benefits of dental quality measurement going toward payers, and the risk of alienating smaller dental offices due to the resource-intensive nature of quality measurement.ConclusionAs our medical counterparts have embraced quality measurement for improved health outcomes, so too must the dental profession. Our ultimate goal is to ensure the delivery of high quality, patient-centered dental care and effective quality measurement is the first step. By continuously monitoring the performance of dental quality measures and their continued refinement when unintended consequences are observed, we can improve patient and population health outcomes.

3200 Balancing Cost and Quality of Care in the US and Denmark: Lessons for Nations Transitioning from Volume-Based to Value-Based Care

OBJECTIVES/SPECIFIC AIMS: Promote knowledge translation and evidence-informed decision-making by assessing barriers and facilitators to balancing cost and quality of care within the US state of Maryland and nation of Denmark. METHODS/STUDY POPULATION: Open-ended and semi-structured key-informant interviews were conducted in 2016 and 2017 among high level decision-makers in Maryland (N=21) and the Danish (N=17) healthcare systems, including hospital, local, regional, and cross-organizational administrators and elected officials. The interviews consisted of questions related to: (1) currently practiced and preferred approaches to resource allocation and development and use of quality performance measures, and (2) preferred sources, formats/styles, modes of information, and decision-making strategies based on a shift from volume to quality-driven care. RESULTS/ANTICIPATED RESULTS: Decision-makers in Maryland expressed the need for collaboration in a changing environment, yet increasingly rely on cost and quality outcomes data to drive decisions and note the struggle to identify credible and useful information. Maryland decision-makers also face challenges in regulating utilization and costs without mandated participation of physician practices within the global budget cap model, which is perceived to be a primary driver of healthcare utilization in the hospital sector. Similarly, decision-makers in Denmark conveyed the importance of quantitative data to aid decisions, however, stress collaboration and dialogue as driving factors and important sources of information. Danish decision-makers also express challenges to wide-spread adoption of a quality-driven approach due to unsustained quality assurance regulatory bodies. DISCUSSION/SIGNIFICANCE OF IMPACT: The findings suggest implementation of value-based healthcare is highly driven and influenced by availability of credible data, which may significantly impact development of policies and innovative cost control strategies, and regulatory oversight to promote adoption of quality measures in decision-making. Furthermore, collaboration within and across healthcare organizations remains a key component to health system improvement as it fosters dialogue and sharing of best practices among stakeholders.

A pathway to developing and testing quality measures aimed at improving adult vaccination rates in the United States

Despite recommendations for vaccinating adults and widespread availability of immunization services (e.g., pharmacy venues, workplace wellness clinics), vaccination rates in the United States remain low. The U.S. National Adult Immunization Plan identified the development of quality measures as a priority and key strategy to address low adult vaccination coverage rates. The use of quality measures can provide incentives for increased utilization of preventive services. To address the lack of adult immunization measures, the National Adult and Influenza Immunization Summit, a coalition of adult immunization partners led by the Immunization Action Coalition, Centers for Disease Control and Prevention, and National Vaccine Program Office, spearheaded efforts to (1) identify gaps and priorities in adult immunization quality performance measurement; (2) explore feasibility of data collection on adult immunizations through pilot testing and engaging stakeholders; and (3) develop and test quality measure specifications. This paper outlines the process by which a public-private partnership drove the development of two adult immunization performance measures—an adult immunization status measure for influenza, tetanus and diphtheria (Td) and/or tetanus toxoid, reduced diphtheria toxoid, and acellular pertussis (Tdap), herpes zoster and pneumococcal vaccines, and a prenatal immunization status measure for influenza and Tdap vaccinations in pregnant women. These measures have recently been added to the 2019 Healthcare Effectiveness Data and Information Set (HEDIS®), a widely used set of performance measures reportable by private health plans.

Impact of Breast Center Accreditation on Compliance with Breast Quality Performance Measures at Commission on Cancer-Accredited Centers.

This study was designed to determine whether accreditation by the National Accreditation Program for Breast Centers (NAPBC) is associated with improved performance on six breast quality measures pertaining to adjuvant treatment, needle/core biopsy, and breast conservation therapy rates at Commission on Cancer (CoC) centers. National Cancer Database 2015 data were retrospectively reviewed to compare patients treated at CoC centers with and without NAPBC accreditation for compliance on six breast cancer quality measures. Mixed effects modeling determined performance on the quality measures adjusting for patient, tumor, and facility factors. Of 1308 CoC facilities, 484 (37%) were NAPBC-accredited and 111,547 patients (48%) were treated at NAPBC centers. More than 80% of patients treated at both NAPBC and non-NAPBC centers received care in compliance with breast quality measures. NAPBC centers achieved significantly higher performance on four of the five quality measures than non-NAPBC centers at the patient level and on five of six measures at the facility level. For two measures, needle/core biopsy before surgical treatment of breast cancer and breast conservation therapy rate of 50%, NAPBC centers were twice as likely as non-NAPBC centers to perform at the level expected by the CoC (respectively odds ratio [OR] 1.96, 95% confidence interval [CI] 1.85-2.08, p < 0.0001; and OR 2.05, 95% CI 1.94-2.15, p < 0.0001). While NAPBC accreditation at CoC centers is associated with higher performance on breast quality measures, the majority of patients at all centers receive guideline-concordant care. Future studies will determine whether higher performance translates into improved oncologic and patient-reported outcomes.