Publications by authors named "Nicolet de Keizer"

To address current trends in poor health-seeking behaviour and late cancer diagnosis in many low- and middle-income countries, like Uganda, it is important to explore innovative awareness building interventions. One possible intervention is a common digital format, an interactive voice response (IVR) system, which is suitable for individuals with low technological and reading literacy. It is increasingly acknowledged that developing digital interventions requires co-creation with relevant stakeholders and explication of program developers' assumptions, to make them effective, sustainable, and scalable.

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Objectives: Patient portals are increasingly implemented to improve patient involvement and engagement. We here seek to provide an overview of ways to mitigate existing concerns that these technologies increase inequity and bias and do not reach those who could benefit most from them.

Methods: Based on the current literature, we review the limitations of existing evaluations of patient portals in relation to addressing health equity, literacy and bias; outline challenges evaluators face when conducting such evaluations; and suggest methodological approaches that may address existing shortcomings.

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Background: The identification of risk factors for adverse outcomes and prolonged intensive care unit (ICU) stay in COVID-19 patients is essential for prognostication, determining treatment intensity, and resource allocation. Previous studies have determined risk factors on admission only, and included a limited number of predictors. Therefore, using data from the highly granular and multicenter Dutch Data Warehouse, we developed machine learning models to identify risk factors for ICU mortality, ventilator-free days and ICU-free days during the course of invasive mechanical ventilation (IMV) in COVID-19 patients.

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Objectives: To highlight the role of technology assessment in the management of the COVID-19 pandemic.

Method: An overview of existing research and evaluation approaches along with expert perspectives drawn from the International Medical Informatics Association (IMIA) Working Group on Technology Assessment and Quality Development in Health Informatics and the European Federation for Medical Informatics (EFMI) Working Group for Assessment of Health Information Systems.

Results: Evaluation of digital health technologies for COVID-19 should be based on their technical maturity as well as the scale of implementation.

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Background: Organizational readiness for change is a key factor in success or failure of electronic health record (EHR) system implementations. Readiness is a multifaceted and multilevel abstract construct encompassing individual and organizational aspects, which makes it difficult to assess. Available tools for assessing readiness need to be tested in different contexts.

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Background: Multiple factors contribute to mortality after ICU, but it is unclear how the predictive value of these factors changes during ICU admission. We aimed to compare the changing performance over time of the acute illness component, antecedent patient characteristics, and ICU length of stay (LOS) in predicting 1-year mortality.

Methods: In this retrospective observational cohort study, the discriminative value of four generalized mixed-effects models was compared for 1-year and hospital mortality.

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Background: Understanding functional and non-functional requirements is essential to successfully implement electronic medical record (EMR) systems. Actual requirements will be different for different contexts.

Objective: To elicit and prioritize requirements for implementing EMRs in oncology in low and middle income countries (LMICs), and to relate these to requirements from high-income countries.

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Health informatics as a young, interdisciplinary discipline lacks a unified terminology in some areas. This is especially true when trying to properly describe health informatics interventions developed and deployed to improve quality and efficiency of patient care. We aim at developing a health IT ontology which allows systematically describing health IT interventions.

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Objectives: To compare methods to adjust for confounding by disease severity during multicenter intervention studies in ICU, when different disease severity measures are collected across centers.

Design: In silico simulation study using national registry data.

Setting: Twenty mixed ICUs in The Netherlands.

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Objectives: This paper draws attention to: i) key considerations for evaluating artificial intelligence (AI) enabled clinical decision support; and ii) challenges and practical implications of AI design, development, selection, use, and ongoing surveillance.

Method: A narrative review of existing research and evaluation approaches along with expert perspectives drawn from the International Medical Informatics Association (IMIA) Working Group on Technology Assessment and Quality Development in Health Informatics and the European Federation for Medical Informatics (EFMI) Working Group for Assessment of Health Information Systems.

Results: There is a rich history and tradition of evaluating AI in healthcare.

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Systematic health IT evaluation studies are needed to ensure system quality and safety and to provide the basis for evidence-based health informatics. Well-trained health informatics specialists are required to guarantee that health IT evaluation studies are conducted in accordance with robust standards. Also, policy makers and managers need to appreciate how good evidence is obtained by scientific process and used as an essential justification for policy decisions.

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Low and middle income countries (LMICs) bear a disproportionate burden of major global health challenges. Health IT could be a promising solution in these settings but LMICs have the weakest evidence of application of health IT to enhance quality of care. Various systematic reviews show significant challenges in the implementation and evaluation of health IT.

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Progress in science is based on evidence from well-designed studies. However, publication quality of health IT evaluation studies is often low, making exploitation of published evidence within systematic reviews and meta-analysis a challenging task. Consequently, reporting guidelines have been published and recommended to be used.

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Research Objective: Reliable and unambiguously defined performance indicators are fundamental to objective and comparable measurements of hospitals' quality of care. In two separate case studies (intensive care and breast cancer care), we investigated if differences in definition interpretation of performance indicators affected the indicator scores.

Design: Information about possible definition interpretations was obtained by a short telephone survey and a Web survey.

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Indicators provide a practical method to monitor and benchmark eHealth progress towards objectives set in local, national and international policies, and to offer evidence for eHealth management. There is no agreed methodology to develop and define these indicators. The purpose of this paper is to present a proposal for an indicator development methodology and indicator classification.

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Tertiary teledermatology (TTD), where a general dermatologist consults a specialized dermatologist on difficult cases, is a relatively new telemedicine service. We evaluated TTD in a Dutch university hospital, where 13 general dermatologists used TTD to consult 11 specialized dermatologists and two residents at the university medical centre. We measured the avoided referrals to the university centre, the usability of the system and the user acceptance of it.

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Telemedicine is becoming widely used in healthcare. Dermatology, because of its visual character, is especially suitable for telemedicine applications. Most common is teledermatology between general practitioners and dermatologists (secondary teledermatology).

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