Advancing maturity modeling for precision oncology.

Introduction: This study aimed to map the maturity of precision oncology as an example of a Learning Health System by understanding the current state of practice, tools and informatics, and barriers and facilitators of maturity. Methods: We conducted semi-structured interviews with 34 professionals (e.g., clinicians, pathologists, and program managers) involved in Molecular Tumor Boards (MTBs). Interviewees were recruited through outreach at 3 large academic medical centers (AMCs) (n = 16) and a Next Generation Sequencing (NGS) company (n = 18). Interviewees were asked about their roles and relationships with MTBs, processes and tools used, and institutional practices. The interviews were then coded and analyzed to understand the variation in maturity across the evolving field of precision oncology. Results: The findings provide insight into the present level of maturity in the precision oncology field, including the state of tooling and informatics within the same domain, the effects of the critical environment on overall maturity, and prospective approaches to enhance maturity of the field. We found that maturity is relatively low, but continuing to evolve, across these dimensions due to the resource-intensive and complex sociotechnical infrastructure required to advance maturity of the field and to fully close learning loops. Conclusion: Our findings advance the field by defining and contextualizing the current state of maturity and potential future strategies for advancing precision oncology, providing a framework to examine how learning health systems mature, and furthering the development of maturity models with new evidence.

Maturity in enterprise data warehouses for research operations: Analysis of a pilot study.

Enterprise data warehouses for research (EDW4R) is a critical component of National Institutes of Health Clinical and Translational Science Award (CTSA) hubs. EDW4R operations have unique needs that require specialized skills and collaborations across multiple domains which limit the ability to apply existing models of information technology (IT) performance. Because of this uniqueness, we developed a new EDW4R maturity model based on prior qualitative study of operational practices for supporting EDW4Rs at CTSA hubs. In a pilot study, respondents from fifteen CTSA hubs completed the novel EDW4R maturity index survey by rating 33 maturity statements across 6 categories using a 5-point Likert scale. Of the six categories, respondents rated workforce as most mature (4.17 [3.67-4.42]) and relationship with enterprise IT as the least mature (3.00 [2.80-3.80]). Our pilot of a novel maturity index shows a baseline quantitative measure of EDW4R functions across fifteen CTSA hubs. The maturity index may be useful to faculty and staff currently leading an EDW4R by creating opportunities to explore the index in local context and comparison to other institutions.

Applying lessons from aviation safety culture in the hospitality industry: a review and road map.

It is widely accepted that positive safety culture improves organizations' safety performance and reduces the number of injuries and deaths. Safety culture has been well researched in high-risk industries; however, the hospitality industry until recently had no research of the concept unless related to food safety. This article explores theoretical grounds for research of safety culture in hospitality, based on the aviation safety culture body of knowledge. Using aviation as a foundation is motivated by the similarities in operations between aviation and hospitality, especially when hospitality is compared to other high-risk industries. The article proposes that aviation safety culture models and their dimensions could be valuable for hospitality industry's safety culture improvements. It's goal and aspiring contribution is to begin a discussion and build a theoretical base for future research about advancement of safety in hospitality operations and reduction of the industry's relatively high numbers of employee injuries.

Development of a social and environmental determinants of health informatics maturity model.

Introduction: Integrating social and environmental determinants of health (SEDoH) into enterprise-wide clinical workflows and decision-making is one of the most important and challenging aspects of improving health equity. We engaged domain experts to develop a SEDoH informatics maturity model (SIMM) to help guide organizations to address technical, operational, and policy gaps. Methods: We established a core expert group consisting of developers, informaticists, and subject matter experts to identify different SIMM domains and define maturity levels. The candidate model (v0.9) was evaluated by 15 informaticists at a Center for Data to Health community meeting. After incorporating feedback, a second evaluation round for v1.0 collected feedback and self-assessments from 35 respondents from the National COVID Cohort Collaborative, the Center for Leading Innovation and Collaboration's Informatics Enterprise Committee, and a publicly available online self-assessment tool. Results: We developed a SIMM comprising seven maturity levels across five domains: data collection policies, data collection methods and technologies, technology platforms for analysis and visualization, analytics capacity, and operational and strategic impact. The evaluation demonstrated relatively high maturity in analytics and technological capacity, but more moderate maturity in operational and strategic impact among academic medical centers. Changes made to the tool in between rounds improved its ability to discriminate between intermediate maturity levels. Conclusion: The SIMM can help organizations identify current gaps and next steps in improving SEDoH informatics. Improving the collection and use of SEDoH data is one important component of addressing health inequities.

Modification and Validation of a Maturity Assessment Tool for Public Health Information System Implementations in Sri Lanka.

INTRODUCTION: Maturity models assess the snapshot view of an organization and simultaneously guides the organization to advance on a road map towards ultimate levels of maturity. The health industry has recently embraced maturity models as a tool to improve the management of health information systems. Most electronic health information systems in Sri Lanka need assessment and monitoring and can benefit vastly by adopting maturity models. This study was conducted to modify and adopt a maturity model for public health institutions in Sri Lanka. METHODS: A review of the literature was done to identify a suitable model to measure the maturity of the public health information system implementations. A Modified Delphi study was then carried out with six experts to adapt the selected maturity tool, Public Health Information Technology (PHIT) maturity index, to the Sri Lankan context. Necessary modifications to the PHIT tool were done according to the comments gathered in the Modified Delphi rounds, and the validity of the tool was established. Finally, Key Informant Interviews were carried out with nine interviewees to qualitatively validate the instrument. RESULTS: The Public Health Information Technology maturity index developed by the University of Maryland, USA, was modified to suit the Sri Lankan context. Comments from the experts were accommodated during the initial rounds of the Modified Delphi study. It further derived the following values, indicating excellent content validity: I-CVI > 0.8 for 57 total items, S-CVI/Avg = 0.988, S-CVI/UA = 0.929 and Free-marginal kappa = 0.95. DISCUSSION AND CONCLUSIONS: Modified and validated PHIT tool can be used to measure the maturity of public health institutions in similar contexts.

Patient Safety Informatics: Criteria Development for Assessing the Maturity of Digital Patient Safety in Hospitals.

With the start of the 21st century, patient safety as a topic of special interest has attracted increasing attention in both academia and clinical practice. As technology has continued to develop since then, questions and focal points surrounding the topic have also shifted. In particular, questions regarding the impact of digitalization on patient safety and its measurement are now of high interest. This work aims to develop a maturity assessment instrument in the form of a criteria set for measuring structural requirements for digital patient safety in hospitals. Based on the results of a literature review and a derivation of maturity objects (MO) from known maturity models, 64 criteria across 11 categories were developed. Written comments of two digital patient safety experts as well as subsequent interviews were used to evaluate and refine the criteria catalog. The resulting catalog offers hospitals guidance for detecting possible areas of structural improvements in their information systems with regard to patient safety and represents a unique instrument for assessing digital maturity in this particular area.

A Safety Maturity Model for Technology-Induced Errors.

In this paper we describe a review of the literature and the development of an initial maturity model for the research literature in the area of technology-induced errors and health technology safety. The capability maturity model provides a way forward for organizations to formalize their health technology safety processes and also compare their efforts in this area to other organizations to support organizational learning. The application of maturity models to technology-induced error is described.

Desenvolvimento de um método para avaliação de maturidade digital de instituições de saúde / Development of a method to digital maturity assessment for healthcare organizations / Desarrollo de un método para evaluación de la madurez digital de las instituciones de salud

Objetivos: Desenvolver um método de avaliação de maturidade digital para instituições de saúde. Métodos: Este trabalho caracteriza-se como uma pesquisa exploratória e descritiva; a partir da revisão e da análise crítica de vários métodos, o Índice de Maturidade Digital para Instituições de Saúde (IMDIS) foi desenvolvido e validado por meio da aplicação em 107 instituições de saúde. Resultados: A análise da base resultou em um percentual médio de 44,4% de maturidade digital. Conclusão: As instituições de saúde devem melhor estruturar a sua jornada digital, não apenas adotando as tecnologias digitais, mas também possuindo uma estratégia, mudança de cultura, equipe capacitada, orçamento e apoio da diretoria. O IMDIS pode ser evoluído e servir de base para a criação de outros índices que, concreta e rotineiramente, avaliem a maturidade digital das instituições de saúde e acompanhem a evolução da Saúde Digital.

Objectives: Develop a method to digital maturity assessment for healthcare organizations. Methods: This paper is defined as exploratory and descriptive research. From revision and critical analysis of various methods, the Digital Maturity Index for Healthcare Organization (IMDIS) was developed and validated by its application for 107 healthcare organizations. Results: Database analysis presented 44,4% of percentage average of digital maturity. Conclusion: Healthcare organizations should improve the structure of its digital journey, not only adopting new digital technologies, but also having strategy, cultural change, well-trained team, budget and support from the board. The IMDIS can be evolved and serve as a basis to create other indexes that, concrete and routinely, evaluate digital maturity of healthcare organizations and following up digital health.

Objetivos: Desarrollar un método para evaluación de la madurez digital para instituciones de salud. Métodos: Este trabajo está caracterizado cómo una pesquisa exploratoria y descriptiva. A partir de la revisión y análisis crítico de varios métodos, se desarrolló y validó el Índice de Madurez Digital para Instituciones de Salud (IMDIS) mediante su aplicación en 107 instituciones de salud. Resultados: La análisis de la base de datos resultó en un porcentaje promedio del 44,4% de madurez digital. Conclusiones: Las instituciones de salud deberían estructurar mejor su jornada digital, no solo adoptando tecnologías digitales, sino también teniendo una estrategia, cambio de cultura, equipo calificado, presupuesto y apoyo de la junta directiva. El IMDIS puede evolucionar y servir de base para la creación de otros índices que, de manera concreta y rutinaria, podrían evaluar la madurez digital de las instituciones de salud y monitorear la evolución de la Salud Digital.

Monitoramento e Avaliação da Saúde Digital: atualização dos métodos e modelos de maturidade / Monitoring and Evaluation of Digital Health: methods and maturity models review / Monitoreo y Evaluación de la Salud Digital: actualización de los métodos y modelos de madurez

A Organização Mundial de Saúde (OMS) define Saúde Digital (SD) como "o uso da tecnologia de informação e comunicação no apoio à Saúde e a áreas relacionadas à Saúde". Monitorar a progressão da SD é fundamental, conforme também estabelecido na resolução da OMS sobre SD. Este artigo de revisão foi elaborado com o intuito de identificar os atuais métodos de avaliação, modelos e índices de maturidade digital utilizados para avaliar e/ou monitorar diversos aspectos da SD. Foram identificados 32 métodos, categorizados e descritos neste artigo. A partir dessa revisão, ficou evidente a necessidade do estabelecimento de critérios objetivos para melhor avaliar se tais métodos e modelos de maturidade são mesmo capazes de avaliar e monitorar a SD ou não.

The World Health Organization (WHO) defines Digital Health (DH) as "the use of information and communications technology in support of health and health-related fields". Monitoring the progression of DH is essential, in according to the resolution of WHO about DH. This paper was elaborated aiming to identify current evaluation methods, models and digital maturity indexes used to evaluate and monitor many aspects of DH. It was evaluated 32 methods, categorized and described in this article. From this review, it was clear the need for establishment of objective criteria to better evaluation whether such methods and maturity models are really able to evaluate and monitor DH progression or not.

La Organización Mundial de Salud (OMS) define la Salud Digital (SD) como "el uso de la tecnología de la información y la comunicación para apoyar las áreas de salud y relacionadas con la salud". El seguimiento de la progresión del SD es fundamental, em acuerdo con la resolución de la OMS acerca de SD. Este artículo de revisión he preparado con el objectivo de identificar los métodos de evaluación actuales, los modelos y los índices de madurez digital utilizados para evaluar y / o monitorear varios aspectos de la SD. En este artículo se identificaron, categorizaron y describieron 32 métodos. A partir de esta revisión, se hizo evidente la necesidad de establecer criterios objetivos para evaluar mejor si dichos métodos y modelos de madurez son capaces de evaluar y monitorear el SD o no.

Development and comparison of migration paths for smart grids using two case studies.

Due to the energy turnaround in German politics, it is necessary to integrate more and more wind and solar energy into the existing energy system. In particular, power generation is changing from a previously centralized to a decentralized structure, which also has consequences for requirements for safe, reliable and efficient grid operation. Generation and utilization characteristics will become more dynamic and flexible in the future. Increased demand for the measurement, control and automation of voltage and electricity will require the further development of grid infrastructure, the expansion of storage capacity and the introduction of information and communication technology (ICT)-based energy management (Appelrath et al., 2012). Utilities therefore need to know what migration paths into the future of a smart energy grid could look like. And this against the background of which technologies have to be installed, in which order this can happen and which dependencies have to be considered. The aim is to create roadmaps to the modern Smart Grid for two case studies. Within the framework of the Green Access project (Projekt Green Access, 2019), and (Flore & Kumm, 2020), a maturity model and, based on this, migration paths were developed for this purpose, which describe a path from one development stage to the next. It describes the necessary development steps that have to be implemented in the context of migration paths. These migration paths have been developed for a specially designed maturity model and describe the technologies used to move from one maturity level to the next. Finally, there will be a comparison of the developed migration paths of the two case studies.

Source Data for the Focus Area Maturity Model for Software Ecosystem Governance.

We define a software ecosystem as a set of organizations collaboratively serving a market for software and services. Typically these ecosystems are underpinned by a common technology, such as an extendable software platform. This data set supports the article that describes the Software Ecosystem Governance Maturity Model ( S E G - M 2 ) [50]. The model has the goal to support software ecosystem orchestrators in the management and governance of the actors in their ecosystems in a structured way. Through a critical structured literature review, 168 practices have been collected. These practices have been evaluated through six case studies at software ecosystem orchestrators. The practices are described with a practice code, a practice name, a practice description, required success conditions, the person responsible for the practice, and the associated literature where the practice was identified.

Maturity assessment and maturity models in health care: A multivocal literature review.

BACKGROUND: The maturity of practices and infrastructure in the health care domain directly impacts the quality and efficiency of health care services. Therefore, various health care administrations (e.g. from hospital management to the nationwide health authority) need to assess and improve their operational maturity. OBJECTIVE: This study aimed to review and classify studies that propose/use maturity assessment or maturity models (MMs) as a vehicle to achieve operational excellence in the health care domain. METHOD: To achieve this objective, we performed a multivocal literature review (MLR) - a form of systematic review that includes data from the grey literature (e.g. white papers and online documents) in addition to formal, peer-reviewed literature. RESULTS: Based on 101 sources, 80 from peer-reviewed literature and 21 from the grey literature, we identified 68 different MMs on, for example, telemedicine, care pathways and digital imaging. We reviewed them with respect to various aspects, including types of research and contribution, list of MMs proposed/used with their subject areas, elements of maturity/capability and application scope or scale. In the synthesis of empirical benefits of using MMs, two were found to be significant: (a) identifying issues and providing guidance for improvement in health care contexts, and (b) improving efficiency, effectiveness, performance and productivity. CONCLUSION: This MLR provides an overview of the landscape and serves as an index to the vast body of knowledge in this area. Our review creates an opportunity to cope with the challenges in obtaining an overview of the state-of-the-art and practice, choosing the most suitable models or developing new models with further specialties.

The NQRN Registry Maturational Framework: Evaluating the Capability and Use of Clinical Registries.

Clinical registries are increasingly used as national performance measurement platforms. In 2018, nearly 70 percent of the more than 50 specialty society registries in the United States were used by the Centers for Medicare & Medicaid Services (CMS) to measure the quality of clinical care. Private payers and evaluating organizations also use or desire to use registry information to inform quality improvement programs and value-based payment models. The requirements for an entity to become a CMS Qualified Clinical Data Registry (QCDR) constitute a minimum set of standards for the purpose of reporting to the CMS Quality Payment Program. Models and frameworks exist that can help classify registries by purpose and use, and maturity models are available for evaluating health IT systems generally. However, there is currently no framework that describes the capability that should be expected from a registry at different phases of its development and maturity. In response, the National Quality Registry Network (NQRN) has developed a registry maturational framework. The framework models early, intermediate and mature development phases, the capabilities anticipated during these phases and 17 domains across which registry programs support those capabilities. The framework was developed and refined by NQRN registry stewards, users and other stakeholders between 2013-2018. It is intended to be used as a developmental guide or for registry evaluation. The successful use of registry information to execute value-based payment models is a critical need in U.S. health care. The NQRN framework can help ensure that our national system of registries is rising to the occasion.

Towards a Clinical Analytics Adoption Maturity Framework for Primary Care.

Clinical decision support systems are evolving with growing analytics capabilities towards pervasive use of artificial intelligence. Maturity models can guide the adoption of these new technologies in clinical practice to improve patient outcomes in primary care settings. Our literature survey identified the "Health Analytics Adoption Maturity Model" by Canada Health Infoway as a suitable basis for developing an adoption maturity framework with primary care focus. We follow a design-science research paradigm to develop a scientifically-validated mixed-method approach for assessing and guiding the evolution of clinical analytics capabilities in primary care. This paper summarizes the first phase of our research in progress.

Maturity Assessment Methodology for HISMM - Hospital Information System Maturity Model.

Maturity models have been adopted in organizations from different sectors of activity, as guides and references for information system (IS) management. In the healthcare field, maturity models have also been used to deal with the enormous complexity and demands of hospital information systems (HIS). This article presents a research project that aimed to develop a new comprehensive model of maturity for a health area. HISMM (hospital information system maturity model) was developed to address the complexity of HIS and intends to offer a useful tool to meet the demands of its management. The HISMM has the peculiarity of combining a set of key maturity influence factors and their respective characteristics, enabling not only the assessment of the global maturity of an HIS but also of the individual maturities of its various dimensions. In this article, we present a methodology for the application and implementation of this model in HIS, thus contributing to its widespread practical application and acceptance.

Maturity of hospital information systems: Most important influencing factors.

Maturity models facilitate organizational management, including information systems management, with hospital organizations no exception. This article puts forth a study carried out with a group of experts in the field of hospital information systems management with a view to identifying the main influencing factors to be included in an encompassing maturity model for hospital information systems management. This study is based on the results of a literature review, which identified maturity models in the health field and relevant influencing factors. The development of this model is justified to the extent that the available maturity models for the hospital information systems management field reveal multiple limitations, including lack of detail, absence of tools to determine their maturity and lack of characterization for stages of maturity structured by different influencing factors.

Information System Maturity Models in Healthcare.

The use of information systems in healthcare (HIS) has been recognised as having crucial importance in improving the efficiency, cost-effectiveness, quality, and safety of medical care delivery. HIS has the potential to improve individuals' health and providers' performance by producing better quality, cost savings, and greater patient involvement in their own health. There have been two major drivers for the HIS investments in healthcare: The ever-increasing burden from chronic disease with costs growing significantly faster and the recognition of the need for greatly improved quality and safety in health delivery. Maturity models (MM) are based on the premises that people, organizations, functional areas and processes evolve through a process of development or growth towards a more advanced maturity, going through a distinct number of levels. Through a state-of-the-art review of HIS, focused on their maturity state, we identify and characterize a set of critical factors recognized as determinants in the context of HIS maturity. The article identifies a broad spectrum of MM applied to the health sector and its characteristics and reinforces the belief that the maturity of HIS can contribute to the quality of information and knowledge management in the sector.

Research IT maturity models for academic health centers: Early development and initial evaluation.

This paper proposes the creation and application of maturity models to guide institutional strategic investment in research informatics and information technology (research IT) and to provide the ability to measure readiness for clinical and research infrastructure as well as sustainability of expertise. Conducting effective and efficient research in health science increasingly relies upon robust research IT systems and capabilities. Academic health centers are increasing investments in health IT systems to address operational pressures, including rapidly growing data, technological advances, and increasing security and regulatory challenges associated with data access requirements. Current approaches for planning and investment in research IT infrastructure vary across institutions and lack comparable guidance for evaluating investments, resulting in inconsistent approaches to research IT implementation across peer academic health centers as well as uncertainty in linking research IT investments to institutional goals. Maturity models address these issues through coupling the assessment of current organizational state with readiness for deployment of potential research IT investment, which can inform leadership strategy. Pilot work in maturity model development has ranged from using them as a catalyst for engaging medical school IT leaders in planning at a single institution to developing initial maturity indices that have been applied and refined across peer medical schools.

Maturity Models of Healthcare Information Systems and Technologies: a Literature Review.

The maturity models are instruments to facilitate organizational management, including the management of its information systems function. These instruments are used also in hospitals. The objective of this article is to identify and compare the maturity models for management of information systems and technologies (IST) in healthcare. For each maturity model, it is identified the methodology of development and validation, as well as the scope, stages and their characteristics by dimensions or influence factors. This study resulted in the need to develop a maturity model based on a holistic approach. It will include a comprehensive set of influencing factors to reach all areas and subsystems of health care organizations.