Performance Frontier Research Articles

Hospital productivity and value in pay-for-performance healthcare programs

ABSTRACT Pay-for-performance (P4P) reimbursement models were launched in 2013 to incentivise the value of healthcare delivered by including quality outcomes, such as mortality, readmission, and patient satisfaction, in hospital reimbursement in the U.S. Although a decade has passed, the efficacy of these P4P programs remains unclear. This research intends to evaluate their long-term performance implications along two critical dimensions – productivity and healthcare value. Drawing on a nationwide sample of U.S. hospitals collected from 2008 to 2019, we utilise data envelopment analysis to measure hospital performance and the Malmquist index to evaluate their longitudinal trends. Although average hospital productivity and value improved since the rollout of the P4P programs, we observe that a large proportion of laggard hospitals were unable to catch up with improvements to the performance frontier, raising concerns about disparities in the impact of future value-based programs. Our analyses also indicate that horizontal integration across hospitals is associated with greater productivity and value. While greater physician-hospital (vertical) integration is associated with higher hospital productivity, it does not have a positive impact on value. Our study provides new insights into the antecedents and performance consequences of implementing value-based healthcare initiatives and their implications for hospital managers and policymakers.

Scaling performance frontiers across multiple perioperative services

BackgroundOne of the primary principles governing operating room management includes maximizing clinical efficiency and optimizing the time used in the high-cost, high-revenue environments represented by operating rooms. Under-utilized and over-utilized times are elementary metrics that describe the operating room performance. Performance frontiers, the graphical representation of a hypothetical maximum performance of a manufacturing unit given a set of operating choices, visualize the maximal efficiency of systems and their existing constraints. MethodsMonthly aggregated operating room metrics from services at the University of Vermont Medical Center (UVM), Stanford Hospital, and the University of Alabama (UAB) at Birmingham Hospital were extracted. Paired under- and over-utilized times were plotted against each other. Performance frontiers representing the optimal performance of each service were overlaid. ResultsThe Kolmogorov-Smirnov test for goodness-of-fit at 95 % level of significance confirms that the performance frontiers representing UVM and Stanford (K-S = 0.9507, p < 0.0001), UVM and UAB (K-S = 0.9989, p < 0.0001), and Stanford and UAB (K-S = 0.9773, p < 0.0001), indicating each service is represented by a different performance frontier. ConclusionsOur analysis shows that the performance frontier defining the optimal efficiency of UVM is more efficient than that of Stanford and UAB. Differences in efficiency may be the result of a collection of factors that must be the subject of future research, including but not limited to organizational differences limited in scale of institutions. Choices in operating room management must be made in relation to the existing organizational structures of each institution and their specific capacity to make changes in tactical decisions. Systemic interventions should be implemented via qualitative analysis of more efficient services, defined by the relative positioning of relevant performance frontiers.

Using data envelopment analysis to measure and improve organizational performance

AbstractOrganizations are complex and have many goals while almost all analytical tools measure performance using only one goal. Thus, analysts often rely on multiple analytical tools to produce a bewildering array of performance measures that often lack internal consistency and a clear focus. In this article, we show how data envelopment analysis (DEA) builds a performance frontier (analogous to a production frontier) that measures organizational performance in the presence of multiple organizational measures. The DEA frontier produces target values for each organizational measure based on the observed performance of organizations in the comparison set. In addition, DEA provides factor performance levels for each performance measure for each organization and can detect circumstances in which an organization has a strong overall performance measure but still has weaknesses in one or more measures. We will illustrate this approach with applications to several examples using real data. Analyzing organizational performance data is critical in the organizational improvement process. The data must directly reflect the organization's goals and the analytical tools used must be appropriate. However, organizations are complex and have many goals while univariate analytical tools measure performance relative to only one goal. Thus, analysts often rely on multiple analytical tools to produce a collection of performance measures, sometimes resulting in a bewildering array of measures that lack focus.

FlexiBERT: Are Current Transformer Architectures too Homogeneous and Rigid?

The existence of a plethora of language models makes the problem of selecting the best one for a custom task challenging. Most state-of-the-art methods leverage transformer-based models (e.g., BERT) or their variants. However, training such models and exploring their hyperparameter space is computationally expensive. Prior work proposes several neural architecture search (NAS) methods that employ performance predictors (e.g., surrogate models) to address this issue; however, such works limit analysis to homogeneous models that use fixed dimensionality throughout the network. This leads to sub-optimal architectures. To address this limitation, we propose a suite of heterogeneous and flexible models, namely FlexiBERT, that have varied encoder layers with a diverse set of possible operations and different hidden dimensions. For better-posed surrogate modeling in this expanded design space, we propose a new graph-similarity-based embedding scheme. We also propose a novel NAS policy, called BOSHNAS, that leverages this new scheme, Bayesian modeling, and second-order optimization, to quickly train and use a neural surrogate model to converge to the optimal architecture. A comprehensive set of experiments shows that the proposed policy, when applied to the FlexiBERT design space, pushes the performance frontier upwards compared to traditional models. FlexiBERT-Mini, one of our proposed models, has 3% fewer parameters than BERT-Mini and achieves 8.9% higher GLUE score. A FlexiBERT model with equivalent performance as the best homogeneous model has 2.6× smaller size. FlexiBERT-Large, another proposed model, attains state-of-the-art results, outperforming the baseline models by at least 5.7% on the GLUE benchmark.

Examining Strategy Improvements in Hospitals: Linking Trade-Offs to Performance Frontiers

The notion of trade-offs has long been recognized by operations management scholars as a necessary constraint to operations strategy. The increasing importance of this concept is reflected in numerous scholarly works, all seeking an understanding on how firms compete with their limited set of resources. A large majority of the past studies have primarily focused on the empirical validation of trade-offs mainly in manufacturing, with few that have visualized trade-offs as a result of performance frontiers in service sectors. In this article, using longitudinal data, we test and validate trade-offs in a public healthcare service-based setting through a performance frontier lens. Our analyses show that better performing hospitals on the basis of quality and cost-efficiency are those that are closer to their performance frontiers and exhibit a cost trade-off. Those that are situated further away demonstrate a trend for quality and cost improvements. However, despite the positions on the frontier, quality always seemed to be the prerequisite dimension for all hospitals. We believe this reaffirms the logic surrounding the sand cone model, albeit in old industry not known for quality.

An Efficiency-Frontier Based Procedure to Improve Operations Strategy

This paper intends to describe a procedural framework for identifying the operations strategy efficiency frontier and, based on this, establish initiatives to improve a given company’s competitiveness position. Each step of the framework is explained, including recommendations on how results should be interpreted. Empirical data are used to exemplify the implementation of the procedural framework. The process contributes to knowledge on the current needs, thereby supporting agile decision making. The contribution also enables dynamic mapping the competitive environment, enabling an current picture of the industry’s competitive context and supporting the establishment of emerging strategies. Two literature gaps are covered: first the lack of focus on identifying the performance frontier process within the context of operations strategy and second, the deployment of the competitive priorities in a market-based view approach.

A DEA-based approach to assess manufacturing performance through operations strategy lenses

While operations strategy is critical in competitiveness, research gaps exist in applying performance frontier methodologies to identify competitive priorities in operations strategy. The concept of performance efficiency frontier can identify the competitiveness drivers specifying the maximum performance that can be achieved by a given set of inputs. This paper proposes and tests a process to measure, assess, and address improvements in manufacturing performance by operations strategy. A five-step procedure, based on the super-efficiency data envelopment analysis (DEA), supports the improvement recommendations. Secondary data of the fourth round of the High-Performance Manufacturing (HPM) survey grounds the benchmarking analysis and assessment. The proposed framework is tested using the in-depth case of a company from the Brazilian automotive industry. The results identified the main gaps of the company to become a market leader through the enhancement of its operations strategic positioning. Improvement recommendations are developed based on a gap analysis of the input variables. By integrating the operations strategy definition within the performance frontier analysis, we guided the competitiveness improvement of the case company.

Ambidextrous Cybersecurity: The Seven Pillars (7Ps) of Cyber Resilience

Organizational ambidexterity balances exploitative and exploratory behaviors so that organizations are able to exploit their existing competencies while simultaneously exploring new opportunities. Similarly, ambidextrous cybersecurity (AMBI-CYBER) focuses on the protection of data, systems, and networks, while fostering the rapid introduction of new technologies within a company. This balance is linked to cybersecurity absorptive capacity and defines the “Cybersecurity Efficient Frontier.” In this paper, we view AMBI-CYBER as a combination of organizational as well as technological and cultural competences which rely upon a multifaceted, multimodal, multinodal, and multilevel set of skills and capabilities. We outline the anatomy of the AMBI-CYBER architecture adopting a balanced scorecard, multistage approach under a 7Ps stage gate model (Patient, Persistent, Persevering, Proactive, Predictive, Preventive, and Preemptive). Such an approach emphasizes the need to enable a complex, nonlinear, adaptive process of dynamic intangible organizational assets, resources, and capabilities across a performance frontier where we aim to optimize safety, security, and privacy effectiveness and efficiency. We also suggests that the Quadruple/Quintuple Helix Innovation model may promote AMBI-CYBER enabling a locus-centric and triple-bottom-line-centric entrepreneurial process of discovery followed by development, exploration, exploitation, and deployment.

Definition of input and output variables to assess operations strategy efficiency frontier

PurposeTo investigate the relationship between performance frontier and operations strategy. A two-level conceptual framework is proposed based on performance elements that act as output/input variables and delimit the scope of the frontier analysis.Design/methodology/approachThe framework proposition is based on the fourth round of high-performance manufacturing survey data. A representative set of variables for assessing performance based on operations strategy constructs is defined through multivariate data analysis techniques. The main method used is the principal component analysis.FindingsThe proposed first-level conceptual framework formalizes the relationships between performance frontier analysis techniques and operations strategy, delimiting the scope and the structural definitions. The second-level conceptual framework defines the constructs of the input and output dimensions for frontier analysis studies.Originality/valueThe paper contribution is developed in the gap of market-led orientation to study operations strategy performance frontier since most related literature focuses on capabilities development with a main focus on the resource-based view (RBV) approach. A conceptual framework based on the competitive priorities is therefore proposed to represent the operations strategy in the view of the frontier techniques. The value lies in defining performance measures which are not a straightforward task as the growth of organization competitiveness and complexity require multiple performance measures. A deeper understanding of frontier estimation on the operations strategy context is also provided, contributing to positively influence firms to succeed in the current dynamic competitive environments.

Condition-based maintenance for major airport baggage systems

PurposeThe aim of this paper is to develop a contribution to knowledge that adds to the empirical evidence of predictive condition-based maintenance by demonstrating how the availability and reliability of current assets can be improved without costly capital investment, resulting in overall system performance improvementsDesign/methodology/approachThe empirical, experimental approach, technical action research (TAR), was designed to study a major Middle Eastern airport baggage handling operation. A predictive condition-based maintenance prototype station was installed to monitor the condition of a highly complex system of static and moving assets.FindingsThe research provides evidence that the performance frontier for airport baggage handling systems can be improved using automated dynamic monitoring of the vibration and digital image data on baggage trays as they pass a service station. The introduction of low-end innovation, which combines advanced technology and low-cost hardware, reduced asset failures in this complex, high-speed operating environment.Originality/valueThe originality derives from the application of existing hardware with the combination of edge and cloud computing software through architectural innovation, resulting in adaptations to an existing baggage handling system within the context of a time-critical logistics system.

Frontlog scheduling in aircraft line maintenance: From explorative solution design to theoretical insight into buffer management

AbstractBased on a multi‐year research engagement with practice, we present a novel solution design for frontlog scheduling in aircraft line maintenance and offer theoretical insights into buffer management in operations. The field problem of the case airline was to improve departure reliability for long‐haul aircraft without increasing maintenance resources, and without using backup aircraft. Frontlog scheduling is the purposeful introduction of over‐maintenance as a buffer of maintenance tasks that can be opportunistically postponed. A detailed simulation of the solution introduced in the airline's operations indicates a performance frontier shift, concurrently improving departure reliability, and reducing maintenance cost. We position the novel practice in operations and maintenance management literature, arguing that the frontlog creates a new type of time buffer, available in contexts where capacity serves predictable as well as unpredictable demand. Further theoretical elaboration leads us to reconceptualize buffer management along time and capacity dimensions, reducing inventory to a special case of time buffering.

Revisiting the cumulative capability model (CCM) among manufacturing firms in developing countries

We examine the applicability of the competitive cumulative capability model among firms in developing economies within the context of the manufacturing industry. We specifically investigate whether the pattern in which competitive capabilities are pursued differs among firms in different developing countries, as well as whether these firms pursue their capabilities in a cumulative fashion. Using a global dataset and focussing on firms in three developing countries that are geographically dispersed – Nigeria, India, and Vietnam – we investigate relationships for firms both within and across countries. Although notions of the cumulative capability model were confirmed, the pattern of the progression is different among firms in the three countries studied. The findings suggest that firms in different developing countries exhibit different manufacturing strategies based on their relative location to their performance frontier, their country’s current state of economic development, as well as the extent of western manufacturing influence in each country.

Intelligent self-designing production control strategy: Dynamic allocation hybrid pull-type mechanism applicable to closed-loop supply chains

The objective of this research is to establish an approach to select the best performing production control strategy for a Closed-Loop Supply Chain (CLSC) system with stochastic supply and demand. To test the operational performance of several pull-type production control strategies, a simulation-based methodology is applied to serial lines with variable processing times. The strategies experimented are: Hybrid Extended Kanban CONWIP (HEKC-II) with modifications, Hybrid Kanban CONWIP (HKC), Dynamic Allocation Hybrid Extended Kanban CONWIP (DNC HEKC-II) special case, Dynamic Allocation Hybrid Kanban CONWIP (DNC HKC) and the newly postulated Intelligent Self-Designing Production Control Strategy (ISD). The successful implementation and the highly positive experimental results for the new strategy provided a major shift of the Pareto performance frontier, simultaneously minimising the conflicting objectives of reducing customer demand backlog (by over 80%) and reducing the WIP (by over 22%) relative to an optimised HKC strategy, the control group.

Economies of collaboration in build‐to‐model operations

AbstractThe direct‐from‐model and tool‐less manufacturing process of 3D printing (3DP) embodies a general‐purpose technology, facilitating capacity sharing and outsourcing. Starting from a case study of a 3DP company (Shapeways) and a new market entrant (Panalpina), we develop dynamic practices for partial outsourcing in build‐to‐model manufacturing. We propose a new outsourcing scheme, bidirectional partial outsourcing (BPO), where 3D printers share capacity by alternating between the role of outsourcer and subcontractor based on need. Coupled with order book smoothing (OBS), where orders are released gradually to production, this provides 3D printers with two distinct ways to manage demand variability. By combining demand and cost field data with an analytical model, we find that BPO improves 3DP cost efficiency and delivery performance as the number of 3DP firms in the network increases. OBS is sufficient for an established 3D printer when alternatives to in‐house manufacturing are few, or of limited capacity. Nevertheless, OBS comes at the cost of reduced responsiveness, whereas BPO shifts the cost and delivery performance frontier. Our analysis shows how BPO combined with OBS makes 3DP companies more resilient to downward movements in both demand and price levels.

The quest for process operations variability reduction in manufacturing firms in South Africa

In an era characterised by a volatile economy, intense competition, and rising energy and material costs, improving operational efficiency has become a necessity for margin purposes and long-term business success. This research study attempts to develop a model for process operations variability reduction that integrates the fundamental drivers, the intermediate measures and the four traditional competitive capabilities: quality, cost, delivery reliability and speed of delivery. In addition, it highlights the precise mechanisms in plants that lead to multiple competitive capabilities development. The concept of a routine-based approach to capabilities development provides a nexus between the earlier actions by the organisation and competitive advantage. Using longitudinal data from the Manufacturing Circle of South Africa, a statistical analysis was conducted to support the model, and path analysis models were developed which confirmed that the performance frontier is really a surface that spans many different dimensions. It is observed that the model clearly outlines pathways to process operations variability reduction through better execution of the routines concerned with maintaining the performance by current processes, improving existing processes, and transforming or changing to new processes.

Are Pediatric Antibiotic Formulations Potentials Risk Factors for Dental Caries and Dental Erosion?

Introduction: One of the most frequent parents’ concerns is that oral antibiotic formulations induce dental damage in their children’s. This study aimed to assess the cariogenic and erosive potentials of 29 pediatric antibiotics.Materials and Methods: Replicates of each antibiotic were analyzed for the concentration of sugars (sucrose, glucose and fructose) and sorbitol by high performance liquid chromatography (HPLC). The pH was determined by digital pHmeter. Titratable acidity was determined in triplicate using the same pHmeter by gradual addition of 0.1N sodium hydroxide (NaOH) until pH 7.0. Viscosity measurements were carried out using a viscosimeter. In order to rank the relative performance of each medicine, the DEA (Data Envelopment Analysis) methodology was used. Results:Sucrose was present in most samples (n=24) with concentrations ranging from 26 to ≈ 100g% (w/w). Only one antibiotic contained sorbitol (66.9g%). Twenty seven antibiotics presented pH values ranging from 4.1 to 6.9 and most of them (n=15) showed the pH below the critical value for dissolution of hydroxyapatite. The values of titratable acidity and viscosity ranged from 0.26 to 40.48 ml and from 20 to 1780cP, respectively. DEA methodology showed that two medicines were distant from the performance frontier (Klaricid® 50mg and Zinnat® 250mg), which means that these medicines showed the worst performance and, therefore, greater potential for dissolution of dental enamel.Conclusion:Many antibiotics presented high concentration of sugars, high titratable acidity, pH below the critical value and high viscosity which can be considered risk factors for dental caries and erosion, when consumed frequently.

Sustainable Global Agrifood Supply Chains: Exploring the Barriers

SummaryThe article investigates the factors that make businesses postpone integrating the performance dimension of sustainability in global agrifood supply chains. Based on literature‐based conceptual reasoning, the article conceptualizes a double company lens distinguishing between substantial supply chain management and mere public relations endeavors as a major obstacle for businesses pursuing comprehensive supply chain performance in global agrifood chains. We point out that many supply chain performance attributes represent, in fact, credence attributes that cannot be verified by the consumer, hence entailing an information asymmetry between the company and its consumers. Rational business responses to this situation tend to focus on symbolic actions and communication efforts by means of sustainability reports and other brand‐enhancing marketing tools that may be decoupled from substantial operations and supply chain improvements. The research propositions developed have partly been corroborated by a content analysis of annual and sustainability reports of four major agrifood companies (Nestlé, PepsiCo, Unilever, and Mondelez International). The conceptual arguments and empirical analysis presented in the article may serve as the basis for managers and academics to develop innovative inter‐ and intraorganizational business processes that reconcile trade‐offs between various agrifood supply chain performance dimensions, thus pushing the performance frontier outward, and that provide the necessary transparency for overcoming the currently adverse setting of incentives inherent in the food production, processing, retailing, and consumption system.

The quest for process operations variability reduction in manufacturing firms in South Africa

In an era characterised by a volatile economy, intense competition, and rising energy and material costs, improving operational efficiency has become a necessity for margin purposes and long-term business success. This research study attempts to develop a model for process operations variability reduction that integrates the fundamental drivers, the intermediate measures and the four traditional competitive capabilities: quality, cost, delivery reliability and speed of delivery. In addition, it highlights the precise mechanisms in plants that lead to multiple competitive capabilities development. The concept of a routine-based approach to capabilities development provides a nexus between the earlier actions by the organisation and competitive advantage. Using longitudinal data from the Manufacturing Circle of South Africa, a statistical analysis was conducted to support the model, and path analysis models were developed which confirmed that the performance frontier is really a surface that spans many different dimensions. It is observed that the model clearly outlines pathways to process operations variability reduction through better execution of the routines concerned with maintaining the performance by current processes, improving existing processes, and transforming or changing to new processes.

Improving the effectiveness of service delivery in the public healthcare sector: the case of ophthalmology services in Malaysia.

BackgroundRising demand of ophthalmology care is increasingly straining Malaysia’s public healthcare sector due to its limited human and financial resources. Improving the effectiveness of ophthalmology service delivery can promote national policy goals of population health improvement and system sustainability. This study examined the performance variation of public ophthalmology service in Malaysia, estimated the potential output gain and investigated several factors that might explain the differential performance.MethodsData for 2011 and 2012 on 36 ophthalmology centres operating in the Ministry of Health hospitals were used in this analysis. We first consulted a panel of ophthalmology service managers to understand the production of ophthalmology services and to verify the production model. We then assessed the relative performance of these centres using Data Envelopment Analysis (DEA). Efficiency scores (ES) were decomposed into technical, scale, and congestion component. Potential increase in service output was estimated. Sensitivity analysis of model changes was performed and stability of the result was assessed using bootstrap approach. Second stage Tobit regression was conducted to determine if hospital type, availability of day services and population characteristics were related to the DEA scores.ResultsIn 2011, 33 % of the ophthalmology centres were found to have ES > 1 (mean ES = 1.10). Potential output gains were 10 % (SE ± 2.92), 7.4 % (SE ± 2.06), 6.9 % (SE ± 1.97) if the centres could overcome their technical, scale and congestion inefficiencies. More centres moved to the performance frontier in 2012 (mean ES = 1.07), with lower potential output gain. The model used has good stability. Robustness checks show that the DEA correctly identified low performing centres. Being in state hospital was significantly associated with better performance.ConclusionsUsing DEA to benchmarking service performance of ophthalmology care could provide insights for policy makers and service managers to intuitively visualise the overall performance of resource use in an otherwise difficult to assess scenario. The considerable potential output gain estimated indicates that effort should be invested to understand what drove the performance variation and optimise them. Similar performance assessment should be undertaken for other healthcare services in the country in order to work towards a sustainable health system.Electronic supplementary materialThe online version of this article (doi:10.1186/s12913-015-1011-0) contains supplementary material, which is available to authorized users.

Job shop control: In search of the key to delivery improvements

The last major performance breakthroughs in job shop control stem from the 1980s and 1990s. We generate a new search direction for designing job shop control policies, providing a key to delivery improvements. Based on a common characteristic shared by the most effective job shop control policies, we posit that control should have a specific focus during high load periods. A probability analysis reveals that substantial periods of high load are common, and even occur under assumptions of stationarity and moderate utilization. Subsequent simulations show nearly all tardy deliveries can be attributed to high load periods; and that the success of the best control policies can be explained by their ability to switch focus specifically during these periods, from reducing the dispersion of lateness to speeding up the average throughput time. Building on this, we demonstrate that for example small capacity adjustments targeted at handling high load periods can improve the percentage tardy and other delivery-related performance measures to a much greater extent than the best existing policies. Sensitivity analysis confirms the robustness of this approach and identifies a performance frontier reflecting the trade-off between capacity resources used and delivery performance realized. We conclude that a paradigm shift in job shop research is required: instead of developing single policies for application under all conditions, new policies are needed that respond differently to temporary high load periods. The new paradigm can be used as a design principle for realizing improvements across a range of planning and control decisions relevant to job shops.