The Role of Formative Evaluation in Promoting Digitally-based Health Equity and Reducing Bias for Resilient Health Systems: The Case of Patient Portals.

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.

Risk factors for adverse outcomes during mechanical ventilation of 1152 COVID-19 patients: a multicenter machine learning study with highly granular data from the Dutch Data Warehouse.

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.

Managing Pandemic Responses with Health Informatics - Challenges for Assessing Digital Health Technologies.

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.

Adjusting for Disease Severity Across ICUs in Multicenter Studies.

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.

Artificial Intelligence in Clinical Decision Support: Challenges for Evaluating AI and Practical Implications.

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.

Evaluation of Health IT in Low-Income Countries.

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.

Publishing Health IT Evaluation Studies.

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.

Influences of definition ambiguity on hospital performance indicator scores: examples from The Netherlands.

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.

A pilot study on tertiary teledermatology: feasibility and acceptance of telecommunication among dermatologists.

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.

Tertiary teledermatology: a systematic review.

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).