Use of Self-Organizing Maps for Balanced Scorecard analysis to monitor the performance of dialysis clinic chains

Digital Health Support: Current Status and Future Development for Enhancing Dialysis Patient Care and Empowering Patients

Chronic kidney disease poses a growing global health concern, as an increasing number of patients progress to end-stage kidney disease requiring kidney replacement therapy, presenting various challenges including shortage of care givers and cost-related issues. In this narrative essay, we explore innovative strategies based on in-depth literature analysis that may help healthcare systems face these challenges, with a focus on digital health technologies (DHTs), to enhance removal and ensure better control of broader spectrum of uremic toxins, to optimize resources, improve care and outcomes, and empower patients. Therefore, alternative strategies, such as self-care dialysis, home-based dialysis with the support of teledialysis, need to be developed. Managing ESKD requires an improvement in patient management, emphasizing patient education, caregiver knowledge, and robust digital support systems. The solution involves leveraging DHTs to automate HD, implement automated algorithm-driven controlled HD, remotely monitor patients, provide health education, and enable caregivers with data-driven decision-making. These technologies, including artificial intelligence, aim to enhance care quality, reduce practice variations, and improve treatment outcomes whilst supporting personalized kidney replacement therapy. This narrative essay offers an update on currently available digital health technologies used in the management of HD patients and envisions future technologies that, through digital solutions, potentially empower patients and will more effectively support their HD treatments.

From electronic health records to clinical management systems: how the digital transformation can support healthcare services

Healthcare systems worldwide are currently undergoing significant transformations in response to increasing costs, a shortage of healthcare professionals and the growing complexity of medical needs among the population. Value-based healthcare reimbursement systems are emerging as an attempt to incentivize patient-centricity and cost containment. From a technological perspective, the transition to digitalized services is intended to support these transformations. A Health Information System (HIS) is a technological solution designed to govern the data flow generated and consumed by healthcare professionals and administrative staff during the delivery of healthcare services. However, the exponential growth of digital capabilities and applied advanced analytics has expanded their traditional functionalities and brought the promise of automating administrative procedures and simple repetitive tasks, while enhancing the efficiency and outcomes of healthcare services by incorporating decision support tools for clinical management. The future of HIS is headed towards modular architectures that can facilitate implementation and adaptation to different environments and systems, as well as the integration of various tools, such as artificial intelligence (AI) models, in a seamless way. As an example, we present the experience and future developments of the European Clinical Database (EuCliD®). EuCliD is a multilingual HIS used by 20 000 nurses and physicians on a daily basis to manage 105 000 patients treated in 1100 clinics in 43 different countries. EuCliD encompasses patients' follow-up, automatic reporting and mobile applications while enabling efficient management of clinical processes. It is also designed to incorporate multiagent systems to automate repetitive tasks, AI modules and advanced dynamic dashboards.

Choices in hemodialysis therapies: variants, personalized therapy and application of evidence-based medicine

The extent of removal of the uremic toxins in hemodialysis (HD) therapies depends primarily on the dialysis membrane characteristics and the solute transport mechanisms involved. While designation of ‘flux’ of membranes as well toxicity of compounds that need to be targeted for removal remain unresolved issues, the relative role, efficiency and utilization of solute removal principles to optimize HD treatment are better delineated. Through the combination and intensity of diffusive and convective removal forces, levels of concentrations of a broad spectrum of uremic toxins can be lowered significantly and successfully. Extended clinical experience as well as data from several clinical trials attest to the benefits of convection-based HD treatment modalities. However, the mode of delivery of HD can further enhance the effectiveness of therapies. Other than treatment time, frequency and location that offer clinical benefits and increase patient well-being, treatment- and patient-specific criteria may be tailored for the therapy delivered: electrolytic composition, dialysate buffer and concentration and choice of anticoagulating agent are crucial for dialysis tolerance and efficacy. Evidence-based medicine (EBM) relies on three tenets, i.e. clinical expertise (i.e. doctor), patient-centered values (i.e. patient) and relevant scientific evidence (i.e. science), that have deviated from their initial aim and summarized to scientific evidence, leading to tyranny of randomized controlled trials. One must recognize that practice patterns as shown by Dialysis Outcomes and Practice Patterns Study and personalization of HD care are the main driving force for improving outcomes. Based on a combination of the three pillars of EBM, and particularly on bedside patient–clinician interaction, we summarize what we have learned over the last 6 decades in terms of best practices to improve outcomes in HD patients. Management of initiation of dialysis, vascular access, preservation of kidney function, selection of biocompatible dialysers and use of dialysis fluids of high microbiological purity to restrict inflammation are just some of the approaches where clinical experience is vital in the absence of definitive scientific evidence. Further, HD adequacy needs to be considered as a broad and multitarget approach covering not just the dose of dialysis provided, but meeting individual patient needs (e.g. fluid volume, acid–base, blood pressure, bone disease metabolism control) through regular assessment—and adjustment—of a series of indicators of treatment efficiency. Finally, in whichever way new technologies (i.e. artificial intelligence, connected health) are embraced in the future to improve the delivery of dialysis, the human dimension of the patient–doctor interaction is irreplaceable. Kidney medicine should remain ‘an art’ and will never be just ‘a science’.

The use and design of the BSC in the health care sector: A systematic literature review for Italy, Spain, and Portugal

The aim of this paper is to gain a better understanding of how the balanced scorecard (BSC) has evolved in Spain, Italy, and Portugal. It reviews all the articles on the BSC in the health care sector written between 1992 and 2015 by Spanish, Italian, or Portuguese authors and published in Spanish, Italian, or Portuguese as well as in English. Our study first shows the state of knowledge on BSC in health care for a homogeneous group of Southern European countries. Second, it uncovers the perspectives, indicators, and generation used in the countries under observation to reveal the extent to which this management tool has evolved. Third, it analyses international variations in design and use within the health care context, especially in the United States. Moreover, it also highlights a number of important issues. The BSC is in its early stage of development in these 3 countries, which do not use it as a tool to implement strategy and align all of the elements that help integrate the organization.

Are performance measurement systems useful? Perceptions from health care

BACKGROUND

Prior literature identified the use of Performance Measurement Systems (PMS) as crucial in addressing improved processes of care. Moreover, a strategic use of PMS has been found to enhance quality, compared to non-strategic use, although a clear understanding of this linkage is still to be achieved. This paper deals with the test of direct and indirect models related to the link between the strategic use of PMS and the level of improved processes in health care organizations. Indirect models were mediated by the degree of perceived managerial discretion.

METHODS

A PLS analysis on a survey of 97 Italian managers working for health care organizations in the Lombardy region was conducted. The response rate was 77.6%.

RESULTS

The strategic use of PMS in health care organizations directly and significantly (p < 0.001) enhances performance in terms of improved processes. Perceived managerial discretion is positively and significantly (p < 0.001) affected by the strategic use of PMS, whereas the mediation effect is non-significant.

CONCLUSIONS

This study contributes to the literature investigating the design and implementation of a non-financial measurement tool, such as the non-financial information included into a balanced scorecard (BSC), in health care organizations. Managers in health care organizations can benefit from the strategic use of PMS to effectively allocate their time to strategic opportunities and threats, which might arise and affect organizational, output-related performance, such as improving processes.

Resilience Patterns: Improving Stress Adaptation Based on an Individual's Personal Features

Resilience, or the capacity to be able to develop oneself successfully despite adverse circumstances, has become a concept of interest in recent years. There is a clear relationship between resilience, psychological well-being, and coping strategies. This study looked at 890 subjects with a mean age of 46.77 (SD = 20.86) years, ranging from 18 and 95 years old. The participants were 40.6% men and 59.4% women. Using this sample, three clusters were developed by MATLAB R2010a and the Self-Organizing Maps toolbox. Two of these had high resilience, and the other one had low resilience; the psychological well-being variables and coping strategies were taken into account. Thereafter, multivariate analysis of variance showed a group effect for the resilience, psychological well-being, and coping strategies variables. Establishing resilient profiles based on variables such as psychological well-being and coping strategies reveals the best features for coping with stressful situations; this could help to promote nonpharmacological therapies for increasing resilience.

Computational intelligence for the Balanced Scorecard: studying performance trends of hemodialysis clinics

OBJECTIVES

The Balanced Scorecard (BSC) is a general, widely employed instrument for enterprise performance monitoring based on the periodic assessment of strategic Key Performance Indicators that are scored against preset targets. The BSC is currently employed as an effective management support tool within Fresenius Medical Care (FME) and is routinely analyzed via standard statistical methods. More recently, the application of computational intelligence techniques (namely, self-organizing maps) to BSC data has been proposed as a way to enhance the quantity and quality of information that can be extracted from it. In this work, additional methods are presented to analyze the evolution of clinic performance over time.

METHODS

Performance evolution is studied at the single-clinic level by computing two complementary indexes that measure the proportion of time spent within performance clusters and improving/worsening trends. Self-organizing maps are used in conjunction with these indexes to identify the specific drivers of the observed performance. The performance evolution for groups of clinics is modeled under a probabilistic framework by resorting to Markov chain properties. These allow a study of the probability of transitioning between performance clusters as time progresses for the identification of the performance level that is expected to become dominant over time.

RESULTS

We show the potential of the proposed methods through illustrative results derived from the analysis of BSC data of 109 FME clinics in three countries. We were able to identify the performance drivers for specific groups of clinics and to distinguish between countries whose performances are likely to improve from those where a decline in performance might be expected. According to the stationary distribution of the Markov chain, the expected trend is best in Turkey (where the highest performance cluster has the highest probability, P=0.46), followed by Portugal (where the second best performance cluster dominates, with P=0.50), and finally Italy (where the second best performance cluster has P=0.34).

CONCLUSION

These results highlight the ability of the proposed methods to extract insights about performance trends that cannot be easily extrapolated using standard analyses and that are valuable in directing management strategies within a continuous quality improvement policy.