Balanced Scorecards and sustainability Balanced Scorecards for corporate social responsibility strategic alignment: A systematic literature review.

The integration of social and environmental issues into their business model is today a major issue for companies facing the challenge of sustainability. This is leading them to redefine their models of performance measurement. In this perspective, integrated and multi-dimensional frameworks such as Balanced Scorecards (BSCs) and Sustainability Balanced Scorecards (SBSCs) offer attractive opportunities. Drawing on a systematic literature review (SRL), this article provides an analysis of the literature to identify the main trends in research on (S)BSCs and their contribution to CSR and sustainability issues. While the SLR reveals a major stream of instrumentalist and functionalist research aimed at demonstrating the relevance of SBSC in the strategic alignment of CSR, more critical approaches question the foundations, purposes and architecture of these instruments regarding the macroscopic challenges of sustainability. More precisely, focused on an organizational performance measurement, these tools would struggle to embrace the full complexity of sustainability issues. The article contributes novel insights to expand current models of SBSC from the perspective of a real contribution to strong sustainability challenges.

Improving Compliance With Evidence-Based Laboratory Testing Recommendations and Monitoring Associated Patient Outcomes.

A team comprising nursing, medical staff, and administrative leaders at an urban academic orthopedic hospital in the northeastern United States sought to revise a preoperative laboratory testing protocol based on evidence and practice guidelines. The goal was to decrease unnecessary tests by 20% without negatively affecting patient outcomes. After adding the revised protocol to the electronic health record, audits revealed that the target goal was not met and additional strategies were implemented, including educational webinars for surgeon office personnel who ordered tests, additional webinars for advanced practice professionals, and the creation of scorecards to track surgeons' progress. Overall, a downward trend in the ordering of unnecessary laboratory tests for patients without identified risks was observed, but a 20% reduction was not achieved. Surgical complications during the project were not associated with laboratory tests. Clinicians continue to use the revised preoperative laboratory testing protocol at the facility.

Value-Based Health Care for Prostate Cancer Centers by Implementing Specific Key Performance Indicators Using a Balanced Score Card.

BACKGROUND: Prostate cancer (PC) is the most common cancer in men in 112 countries, and accounts for 15% of cancers. Because it cannot be prevented, the rise in cases is inevitable, and improvements in diagnostic pathways and treatments are needed, as there is still a shortage of cost-effective diagnostics and widespread oncologically safe treatment options with measurable quality. As part of the implementation of a Full Cycle of Care, instruments have been developed to achieve value-based medicine, such as consistent commitment to measurability. One of these instruments is the Balanced Scorecard (BSC). Here, we propose the first BSC for prostate cancer (PC) treatment. METHODS: BSCs are used to assess performance in healthcare organizations across four dimensions: financial, patient and referrer, process, and learning and development. This study aimed to identify Key Performance Indicators (KPIs) for each perspective. A systematic literature search was conducted according to PRISMA guidelines using multiple databases and specific search terms to identify KPIs for PC care, excluding case reports and conference abstracts. In total, 44 reports were included in analyses and development of the PC-specific BSC. RESULTS: In the present study, a PC-specific BSC and KPIs were defined for the four classic perspectives, as well as for a newly developed PC-Specific Disease and Outcome perspective, including patient-related parameters from the German Cancer Society and the International Consortium for Health Outcomes Measurement. In addition, the Process perspective includes KPIs of fulfillment of continuing education of residents and the metrics of structured training of the radical prostatectomy procedure in the Learning and Development perspective. CONCLUSIONS: The developed BSC provides a comprehensive set of perspectives for an Integrated Practice Unit or center in PC care, ensuring that the indicators remain manageable and applicable. The BSC facilitates value creation in line with Porter's Full Cycle of Care by systematically collecting and providing economic, personnel, and medical results, actions, and indicators. In particular, this BSC includes KPIs of structured training of practitioners and metrics of the German Cancer Society, that recently proved to improve PC patients outcomes.

Development of performance indicators by the Delphi study for foodservice operations in senior welfare centers: application of the balanced scorecard.

With the rapid growth of the elderly population, the number of elderly welfare centers has expanded significantly. However, the current regulations and standards for foodservice management in these centers are inadequate. To address this issue, this study aimed to develop objective and integrated performance indicators based on the Balanced Scorecard for foodservice programs in elderly welfare centers. To evaluate the validity and reliability of the performance indicators, two Delphi studies were conducted in April 2017. The Delphi survey included the evaluation of strategic goals, financial perspective, customer perspective, learning and growth perspective, and the internal process perspective. The degree of consensus among experts was assessed using Kendall's W-test. As a result of the study, the study ultimately identified 33 performance indicators from 12 strategic goals in four perspectives, which could be used as an efficient tool to evaluate, supplement, and improve foodservice in elderly welfare centers. Supplementary Information: The online version contains supplementary material available at 10.1007/s10068-023-01468-x.

Keep-or-drop multidimensional control systems in professional organisations: evidence on the use of the balanced scorecard in healthcare.

PURPOSE: During the 1990s, Italian healthcare organisations (HOs) underwent a process of corporatisation, and the most innovative HOs introduced the balanced scorecard (BSC) to address the need for broader accountability. Currently, there is a limited understanding of the dynamics and outcomes of such a process. Therefore, this study aims to explore whether the BSC is still considered an effective performance management tool and analyse the factors driving and hindering its evolution and endurance in public and non-profit HOs. DESIGN/METHODOLOGY/APPROACH: We conducted a retrospective longitudinal analysis of two pioneering cases in the adoption of the BSC: one in a public hospital and the other in a non-profit hospital. Data collection relied on accessing institutional documents and reports from the early 2000s to the present, as well as conducting semi-structured interviews with the internal sponsors of the BSC. FINDINGS: We found evidence of three main categories of factors that trigger or hinder the adoption and development of the BSC: (1) the role of the internal sponsor and professionals' commitment; (2) information technology and the controller's technological skills; and (3) the relationship between the management and professionalism logics during the implementation process. At the same time, there is no evidence to suggest that specific technical features of the BSC influence its endurance. ORIGINALITY/VALUE: The paper contributes to the debate on the key factors for implementing and sustaining multidimensional control systems in professional organisations. It emphasises the importance of knowledge-based assets and distinctive internal capabilities for the success of the business. The implications of the BSC legacy are discussed, along with future developments of multidimensional control tools aimed at supporting strategy execution.

Diabetes prediction model for unbalanced community follow-up data set based on optimal feature selection and scorecard.

Objectives: Diabetes is a metabolic disease and early detection is crucial to ensuring a healthy life for people with prediabetes. Community care plays an important role in public health, but the association between community follow-up of key life characteristics and diabetes risk remains unclear. Based on the method of optimal feature selection and risk scorecard, follow-up data of diabetes patients are modeled to assess diabetes risk. Methods: We conducted a study on the diabetes risk assessment model and risk scorecard using follow-up data from diabetes patients in Haizhu District, Guangzhou, from 2016 to 2023. The raw data underwent preprocessing and imbalance handling. Subsequently, features relevant to diabetes were selected and optimized to determine the optimal subset of features associated with community follow-up and diabetes risk. We established the diabetes risk assessment model. Furthermore, for a comprehensible and interpretable risk expression, the Weight of Evidence transformation method was applied to features. The transformed features were discretized using the quantile binning method to design the risk scorecard, mapping the model's output to five risk levels. Results: In constructing the diabetes risk assessment model, the Random Forest classifier achieved the highest accuracy. The risk scorecard obtained an accuracy of 85.16%, precision of 87.30%, recall of 80.26%, and an F1 score of 83.27% on the unbalanced research dataset. The performance loss compared to the diabetes risk assessment model was minimal, suggesting that the binning method used for constructing the diabetes risk scorecard is reasonable, with very low feature information loss. Conclusion: The methods provided in this article demonstrate effectiveness and reliability in the assessment of diabetes risk. The assessment model and scorecard can be directly applied to community doctors for large-scale risk identification and early warning and can also be used for individual self-examination to reduce risk factor levels.

Credit risk assessment of small and micro enterprise based on machine learning.

Small and micro enterprises are pivotal in national economic and social development. To foster their growth, managing their credit risks scientifically is crucial. This study starts by examining the credit information of these enterprises. We use imbalanced sample processing algorithms to ensure a balanced representation of minority-class samples. Then, a machine learning classifier is employed to identify key factors contributing to these enterprises' low credibility. Based on these factors, an XGBoost scoring card model is developed. The study reveals: firstly, the integration of the SMOTE algorithm with the XGBoost model exhibits certain performance advantages in handling imbalanced datasets; secondly, trustworthy financial information remains at the heart of crucial risk determinants; thirdly, the XGBoost scoring card model based on significant features effectively enhances the accuracy of credit risk assessment. These insights provide both theoretical references and practical tools for enhancing the robustness of small and micro enterprises, facilitating early warnings on credit risks, and refining financing efficiency.

Assessing midwifery services in Iran via the balanced scorecard framework.

This study investigates the impact of intra-organizational information, midwife job satisfaction and performance assessment on the quality of midwife services. The questions are empirically tested with survey data obtained from 276 midwives, specialist doctors and nurses, and mothers who recently gave birth in a cross-section of Iranian public healthcare organizations. The results from a structural equation model suggest that an improved performance assessment system leads to higher quality midwife services. In addition, the results indicate that midwife job satisfaction and intra-organizational information increases the quality of midwife services, both directly and indirectly, through the mediating effect of a performance assessment system. Our study contributes to the growing research exploring the interface between accounting and health issues by recognizing the importance of a performance assessment system of midwifery services via the balanced scorecard framework for understanding the quality of midwife services.

Predicting the Outcome of Patients with Aneurysmal Subarachnoid Hemorrhage: A Machine-Learning-Guided Scorecard.

Aneurysmal subarachnoid hemorrhage (aSAH) frequently causes long-term disability, but predicting outcomes remains challenging. Routine parameters such as demographics, admission status, CT findings, and blood tests can be used to predict aSAH outcomes. The aim of this study was to compare the performance of traditional logistic regression with several machine learning algorithms using readily available indicators and to generate a practical prognostic scorecard based on machine learning. Eighteen routinely available indicators were collected as outcome predictors for individuals with aSAH. Logistic regression (LR), random forest (RF), support vector machines (SVMs), and fully connected neural networks (FCNNs) were compared. A scorecard system was established based on predictor weights. The results show that machine learning models and a scorecard achieved 0.75~0.8 area under the curve (AUC) predicting aSAH outcomes (LR 0.739, RF 0.749, SVM 0.762~0.793, scorecard 0.794). FCNNs performed best (~0.95) but lacked interpretability. The scorecard model used only five factors, generating a clinically useful tool with a total cutoff score of ≥5, indicating poor prognosis. We developed and validated machine learning models proven to predict outcomes more accurately in individuals with aSAH. The parameters found to be the most strongly predictive of outcomes were NLR, lymphocyte count, monocyte count, hypertension status, and SEBES. The scorecard system provides a simplified means of applying predictive analytics at the bedside using a few key indicators.

Evaluating event-based surveillance capacity in Africa: Use of the Africa CDC scorecard, 2022-2023.

Introduction: Event-based surveillance (EBS) is a critical component of Early Warning, Alert and Response (EWAR) capacity needed for outbreak prevention and control. To better understand existing EBS and monitor the progress of capacity-building efforts over time, Africa CDC developed an EBS scorecard as part of a revision to the EBS Framework. Methods: We distributed the scorecard to African Union (AU) Member States (MSs). Survey responses from the MSs' human health sector were aggregated, cleaned, and analysed. MS, regional, and continental EBS capacity was assessed. Results: Between 21 July 2022 and 4 April 2023, a total of 63 respondents representing 49 (89%) of 55 MSs completed the survey. Given Africa CDC's public health mandate, we acknowledged the importance of One Health collaboration in MSs but focused on and analysed only the human health sector responses. Thirty-four (71%) MSs stated having EBS in place; hotline was the most common type of EBS implemented (76%). Seventeen (50%) MSs reported multisectoral, One Health collaboration as part of EBS implementation. Scorecard outcomes showed a minimal (score of <60%) to average (score between 60-80%) level of EBS capacity in 29 and five (5) MSs respectively. Discussion: Current EBS capacity levels need to be strengthened in Africa to ensure the continent remains prepared for future public health threats. The Africa CDC EBS scorecard provides a useful way to measure and track this capacity over time. Results can be used to advocate for and target resources for capacity building to foster public health emergency preparedness efforts.

Implementing an intervention to improve leadership/management of public healthcare services in the Free State Province, South Africa: lessons learned.

Background: Based on the World Health Organization's health systems strengthening framework, the Health Systems Governance and Accountability (HSGA) intervention to strengthen public health leadership/management, service integration and outcomes was developed in the Free State. Objectives: This study describes the process to implement and measure the effects of the HSGA intervention for system-wide improvement of leadership/management under routine conditions in a resource-constrained setting. Methods: Based on normalisation process theory, participatory discussions were held with health managers, staff and local stakeholders to attain buy-in. Evaluation of the implementation process considered progress in improving leadership/management through application of the Balanced Scorecard (BSC). All provincial reporting units were assessed during 2014/15 and again during 2015/16. Results: The mean scores on three BSC perspectives improved statistically significantly from 2014/15 to 2015/16: customer (p=0.0085), internal business processes (p=0.0008) and finance (p=0.0001). Overall leadership/management also improved significantly (p=0.0007). Conclusion: Improvement in leadership/management resulting from implementation of the HSGA intervention was observed during the two years under study. From this experience, successful implementation of a health systems strengthening intervention hinges on a participatory design, appropriate use of theory, as well as application of an evaluation approach to assess the success of implementation.

Resolving the practical factors in the healthcare system management by considering a combine approach of AHP and ANP methods.

Healthcare System Management (HSM) is a technique for integrating technology in public hospitals. Knowledge of strategies and decision-making issues is crucial for improving hospital services during the HSM implementation since it directly impacts the efficiency of the hospital and the level of the patient healthcare system. To address the research gap, this study presents a hybrid decision making model that combines the Analysis Hierarchical Process (AHP) method and the Analytic Network Process (ANP) to select Balanced Scorecard Policy (BSP) indicators for evaluating HSM application in a resource-limited background. The hybrid modeling approach not only assists in allocating resources for the execution of HSM but also in determining the significance of the relationship between each analyzed aspect. The hierarchical structure used in this study's quantitative and qualitative relations assessment can also assist various medical facilities in determining how the evaluation criteria and the resources needed to provide HSM services are related. In addition, the management decision policy is shown by the BSP in a healthcare center by combining the two methods mentioned satisfy the goal of strategy weights and limited resources. Finally, the article results indicate that the proposed method increases the efficiency of decisions and maximizes the can improve the reliability in HSM.

Ending preventable stillbirths and improving bereavement care: a scorecard for high- and upper-middle income countries.

BACKGROUND: Despite progress, stillbirth rates in many high- and upper-middle income countries remain high, and the majority of these deaths are preventable. We introduce the Ending Preventable Stillbirths (EPS) Scorecard for High- and Upper Middle-Income Countries, a tool to track progress against the Lancet's 2016 EPS Series Call to Action, fostering transparency, consistency and accountability. METHODS: The Scorecard for EPS in High- and Upper-Middle Income Countries was adapted from the Scorecard for EPS in Low-Income Countries, which includes 20 indicators to track progress against the eight Call to Action targets. The Scorecard for High- and Upper-Middle Income Countries includes 23 indicators tracking progress against these same Call to Action targets. For this inaugural version of the Scorecard, 13 high- and upper-middle income countries supplied data. Data were collated and compared between and within countries. RESULTS: Data were complete for 15 of 23 indicators (65%). Five key issues were identified: (1) there is wide variation in stillbirth rates and related perinatal outcomes, (2) definitions of stillbirth and related perinatal outcomes vary widely across countries, (3) data on key risk factors for stillbirth are often missing and equity is not consistently tracked, (4) most countries lack guidelines and targets for critical areas for stillbirth prevention and care after stillbirth and have not set a national stillbirth rate target, and (5) most countries do not have mechanisms in place for reduction of stigma or guidelines around bereavement care. CONCLUSIONS: This inaugural version of the Scorecard for High- and Upper-Middle Income Countries highlights important gaps in performance indicators for stillbirth both between and within countries. The Scorecard provides a basis for future assessment of progress and can be used to help hold individual countries accountable, especially for reducing stillbirth inequities in disadvantaged groups.

Evaluating the adoption of cybersecurity and its influence on organizational performance.

Cyberattacks negatively impact the performance of enterprises all around the globe. While organizations invest more in cybersecurity to avoid cyberattacks, studies on the factors affecting their overall cybersecurity adoption and awareness are sparse. In this paper, by integrating the diffusion of innovation theory (DOI), technology acceptance model (TAM), and technology-organization-environment (TOE) with the balanced scorecard approach, we propose a comprehensive set of factors that influence cybersecurity adoption and assess the effects of these factors on organizational performance. Data are collected through a survey of IT experts in small and medium-sized enterprises (SMEs) in the United Kingdom, with 147 valid responses. Structural equation modeling based on a statistical package for the social sciences (SPSS) was used to assess the model. The findings identify and confirm the importance of eight factors affecting SMEs' cybersecurity adoption. Moreover, cybersecurity technology adoption is found to positively impacts organizational performance. The proposed framework depicts variables influencing cybersecurity technology adoption and assesses their importance. The outcomes of this study provide a basis for future research and can be adopted by IT and cybersecurity managers to identify the most appropriate cybersecurity technologies that positively impact their company's performance.

An assessment of the laboratory network in Ghana: A national-level ATLAS survey (2019-2020).

Background: Integrated health systems with strong laboratory networks are critical in improving public health. The current study assessed the laboratory network in Ghana and its functionality using the Assessment Tool for Laboratory Services (ATLAS). Intervention: A national-level laboratory network survey was conducted among stakeholders of the Ghanaian laboratory network in Accra. Face-to-face interviews were conducted from December 2019 to January 2020, with follow-up phone interviews between June and July 2020. Also, we reviewed supporting documents provided by stakeholders for supplementary information and transcribed these to identify themes. Where possible, we completed the Laboratory Network scorecard using data obtained from the ATLAS. Lessons learnt: The Laboratory Network (LABNET) scorecard assessment was a valuable addition to the ATLAS survey as it quantified the functionality of the laboratory network and its overall advancement toward achieving International Health Regulations (2005) and Global Health Security Agenda targets. Two significant challenges indicated by respondents were laboratory financing and delayed implementation of the Ghana National Health Laboratory Policy. Recommendations: Stakeholders recommended a review of the country's funding landscape, such as funding laboratory services from the country's internally generated funds. Also, they recommended laboratory policy implementation to ensure adequate laboratory workforce and standards.

Engaging physicians and nurses in balanced scorecard evaluation-An implication at Palestinian hospitals and recommendations for policy makers.

Introduction: Healthcare workers (HCWs) are seldom involved in balanced scorecard (BSC) deployments. This study aims to incorporate Palestinian HCWs in the BSC to create health policy recommendations and action plans using BSC-HCW1, a survey designed and validated based on BSC dimensions. Methodology: In this cross-sectional study, the BSC-HCW1 survey was delivered to HCWs in 14 hospitals from January to October 2021 to get them involved in PE. The differences between physicians' and nurses' evaluations were assessed by the Mann-Whitney U-test. The causal relationships between factors were analyzed using multiple linear regression. The multicollinearity of the model was checked. Path analysis was performed to understand the BSC strategic maps based on the Palestinian HCWs' evaluations. Results: Out of 800 surveys, 454 (57%) were retrieved. No evaluation differences between physicians and nurses were found. The BSC-HCW1 model explains 22-35% of HCW loyalty attitudes, managerial trust, and perceived patient trust and respect. HCWs' workload time-life balance, quality and development initiatives, and managerial performance evaluation have a direct effect on improving HCWs' loyalty attitudes (ß = 0.272, P < 0.001; ß = 0.231, P < 0.001; ß = 0.199, P < 0.001, respectively). HCWs' engagement, managerial performance evaluation, and loyalty attitudes have a direct effect on enhancing HCWs' respect toward managers (ß = 0.260, P < 0.001; ß = 0.191, P = 0.001; ß = 0.135, P = 0.010, respectively). Quality and development initiatives, HCWs' loyalty attitudes, and workload time-life balance had a direct effect on improving perceived patient respect toward HCWs (ß = 254, P < 0.001; ß = 0.137, P = 0.006, ß = 0.137, P = 0.006, respectively). Conclusion: This research shows that it is important to improve low-performing indicators, such as the duration of time HCWs spend with patients, their knowledge of medications and diseases, the quality of hospital equipment and maintenance, and the inclusion of strengths and weaknesses in HCWs' evaluations, so that HCWs are more loyal and less likely to want to leave. For Palestinian hospital managers to be respected more, they must include HCWs in their action plans and explain their evaluation criteria. Patients will respect Palestinian HCWs more if they prioritize their education and work quality, spend more time with patients, and reflect more loyalty. The results can be generalized since it encompassed 30% of Palestinian hospitals from all categories.

A comprehensive bibliometric study of the balanced scorecard.

This research provides a deeper knowledge in the Balanced Scorecard (BSC) insight by using the bibliometric technique. The existing gap between the traditional literatura reviews and previous bibliometric studies, is covered as it is the first comprehensive analysis carried out in applying quantity, quality, and structural indicators. Web of Science Core Collection was used as the source of information, considering it the most accurate and suitable data base for these studies. This research covers the wider period-of-time possible, from 1992 to 2020, with a final sample of 771 articles in 466 reviews. Quantity indicators show the high interest that the BSC still has in the scholar's community, pointing out Kaplan and Norton as the most productive authors,and confirming that 'management', 'business' and 'accountability' are its most common field of activity, although others as 'systems' and sustainability' are coming to prominence; 'Balanced Scorecard' appears as the most remarkable keyword. Quality indicators found 32,706 citations, with Kaplan and Norton occupying again top positions as well as 'Harvard Business Review' as the most impacting review both in cited articles and in average. Co-citation analysis reveals the existence of a triple corecluster for articles, based on the theory, literature reviews, and case-studies.

Measuring circularity of a manufacturing organization by using sustainable balanced scorecard.

In recent years, circular economy has become a matter of great importance because of its ability to contribute toward economic, environmental, and social aspects of the sustainability. The circular economy approaches help in resource conservation by reducing, reusing, and recycling products/parts/components/materials. On the other hand, Industry 4.0 is coupled with emerging technologies, which support the firms in efficient resource utilization. These innovative technologies can transform the present manufacturing organizations by reducing resource extraction, CO2 emissions, environmental damage, and power consumption and improve it into a more sustainable manufacturing organization. Industry 4.0 along with circular economy concepts greatly improves the circularity performance. However, there is no framework found for measuring the circularity performance of the firm. Therefore, the current study aims to develop a framework for measuring performance in terms of circularity percentage. In this work, graph theory and matrix approach are employed for measuring the performance based on a sustainable balanced scorecard such as internal process, learning and growth, customer and financial with environmental and social perspectives. A case of an Indian barrel manufacturing organization is discussed for the illustration of proposed methodology. Based on "circularity index" of the organization and the maximum possible circularity index, the circularity was found to be 5.10%. It indicates that there is a huge potential for the improvement in the circularity of the organization. An in-depth sensitivity analysis and comparison are also performed to validate the findings. There are very few studies on measuring the circularity. The study developed the approach for measuring circularity, which may be utilized by industrialists and practitioners for improving the circularity.

Pregnancy Apps for Self-Monitoring: Scoping Review of the Most Popular Global Apps Available in Australia.

Digital health tools, such as apps, have the potential to promote healthy behaviours, especially self-monitoring, which can facilitate pregnancy management and reduce the risk of associated pregnancy health conditions. While pregnancy apps are popular amongst pregnant women, there is limited information about the overall quality of their content or self-monitoring tools and the number of behaviour change techniques (BCTs) that they include. The aim of this study was thus to assess the quality of pregnancy apps for self-monitoring, and their usage of BCTs. We identified pregnancy apps by web scraping the most popular global apps for self-monitoring in the Apple App Store and Google Play Store available in Australia. The app quality was evaluated using the scorecard approach and the inclusion of BCTs was evaluated using the ABACUS tool. We identified 31 pregnancy apps that met our eligibility criteria. We found that pregnancy apps tended to score the highest in the domains of 'cost and time', 'usability', and 'technical', and lowest on 'clinical' and 'end-user requirements'. Additionally, the majority of apps contained minimal BCTs. Based on our findings, we propose a digital health scorecard visualisation that would break down app quality criteria and present them in a more accessible way to clinicians and pregnant users. We conclude that these findings highlight the shortcomings of available commercial pregnancy apps and the utility of a digital health scorecard visualisation that would empower users to make more informed decisions about which apps are the most appropriate for their needs.