Development of the ADFICE_IT clinical decision support system to assist deprescribing of fall-risk increasing drugs: A user-centered design approach.

Introduction: Deprescribing fall-risk increasing drugs (FRIDs) is promising for reducing the risk of falling in older adults. Applying appropriate deprescribing in practice can be difficult due to the outcome uncertainties associated with stopping FRIDs. The ADFICE_IT intervention addresses this complexity with a clinical decision support system (CDSS) that facilitates optimum deprescribing of FRIDs by using a fall-risk prediction model, aggregation of deprescribing guidelines, and joint medication management.

Evaluating Artificial Intelligence in Clinical Settings-Let Us Not Reinvent the Wheel.

Given the requirement to minimize the risks and maximize the benefits of technology applications in health care provision, there is an urgent need to incorporate theory-informed health IT (HIT) evaluation frameworks into existing and emerging guidelines for the evaluation of artificial intelligence (AI). Such frameworks can help developers, implementers, and strategic decision makers to build on experience and the existing empirical evidence base. We provide a pragmatic conceptual overview of selected concrete examples of how existing theory-informed HIT evaluation frameworks may be used to inform the safe development and implementation of AI in health care settings.

A systematic review of fall prediction models for community-dwelling older adults: comparison between models based on research cohorts and models based on routinely collected data.

Background: Prediction models can identify fall-prone individuals. Prediction models can be based on either data from research cohorts (cohort-based) or routinely collected data (RCD-based). We review and compare cohort-based and RCD-based studies describing the development and/or validation of fall prediction models for community-dwelling older adults.

A European survey of older peoples' preferences, and perceived barriers and facilitators to inform development of a medication-related fall-prevention patient portal.

Purpose: Falls are a major and growing health care problem in older adults. A patient portal has the potential to provide older adults with fall-prevention advice to reduce fall-risk. However, to date, the needs and preferences regarding a patient portal in older people who have experienced falls have not been explored.

An eHealth App (CAPABLE) Providing Symptom Monitoring, Well-Being Interventions, and Educational Material for Patients With Melanoma Treated With Immune Checkpoint Inhibitors: Protocol for an Exploratory Intervention Trial.

Background: Since treatment with immune checkpoint inhibitors (ICIs) is becoming standard therapy for patients with high-risk and advanced melanoma, an increasing number of patients experience treatment-related adverse events such as fatigue. Until now, studies have demonstrated the benefits of using eHealth tools to provide either symptom monitoring or interventions to reduce treatment-related symptoms such as fatigue. However, an eHealth tool that facilitates the combination of both symptom monitoring and symptom management in patients with melanoma treated with ICIs is still needed.

Effects of a clinical decision support system and patient portal for preventing medication-related falls in older fallers: Protocol of a cluster randomized controlled trial with embedded process and economic evaluations (ADFICE_IT).

Background: Falls are the leading cause of injury-related mortality and hospitalization among adults aged ≥ 65 years. An important modifiable fall-risk factor is use of fall-risk increasing drugs (FRIDs). However, deprescribing is not always attempted or performed successfully.

The need to strengthen the evaluation of the impact of Artificial Intelligence-based decision support systems on healthcare provision.

Despite the renewed interest in Artificial Intelligence-based clinical decision support systems (AI-CDS), there is still a lack of empirical evidence supporting their effectiveness. This underscores the need for rigorous and continuous evaluation and monitoring of processes and outcomes associated with the introduction of health information technology. We illustrate how the emergence of AI-CDS has helped to bring to the fore the critical importance of evaluation principles and action regarding all health information technology applications, as these hitherto have received limited attention.

Validation of the ADFICE_IT Models for Predicting Falls and Recurrent Falls in Geriatric Outpatients.

Objectives: Before being used in clinical practice, a prediction model should be tested in patients whose data were not used in model development. Previously, we developed the ADFICE_IT models for predicting any fall and recurrent falls, referred as Any_fall and Recur_fall. In this study, we externally validated the models and compared their clinical value to a practical screening strategy where patients are screened for falls history alone.

Development and Internal Validation of a Prediction Model for Falls Using Electronic Health Records in a Hospital Setting.

Objective: Fall prevention is important in many hospitals. Current fall-risk-screening tools have limited predictive accuracy specifically for older inpatients. Their administration can be time-consuming.

External validation of the Johns Hopkins Fall Risk Assessment Tool in older Dutch hospitalized patients.

Purpose: Fall prevention is a safety goal in many hospitals. The performance of the Johns Hopkins Fall Risk Assessment Tool (JHFRAT) in older inpatients is largely unknown. We aimed to assess the JHFRAT performance in a large sample of Dutch older inpatients, including its trend over time.

Use of an open-source electronic health record to establish a "virtual hospital": A tale of two curricula.

Background: The electronic health record (EHR) is central to medical informatics. Its use is also recognized as an important skill for future clinicians. Typically, medical students' first exposure to an EHR is when they start their clinical internships, and medical informatics students may or may not get experience with an EHR before graduation.

General Practitioners' needs and wishes for clinical decision support Systems: A focus group study.

Background: Shared decision making (SDM) can be beneficial for patients, healthcare professionals, but is often not applied in practice. A clinical decision support system (CDSS) can facilitate SDM. However, CDSS acceptance rates are rather low.

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.

Exploring supportive care and information needs through a proposed eHealth application among melanoma patients undergoing systemic therapy: a qualitative study.

Background: During and after systemic therapy, patients with high risk and advanced melanoma experience challenges regarding cancer-related symptoms, treatment-related adverse events, and an impact of these symptoms on their physical and psychosocial well-being. Few studies have investigated the specific needs of these patients and the potential role of eHealth applications in meeting those needs.

Objective: To explore the supportive care and information needs of high risk and advanced melanoma patients, and how these needs can be supported by eHealth applications.

Development of the ADFICE_IT Models for Predicting Falls and Recurrent Falls in Community-Dwelling Older Adults: Pooled Analyses of European Cohorts With Special Attention to Medication.

Background: Use of fall prevention strategies requires detection of high-risk patients. Our goal was to develop prediction models for falls and recurrent falls in community-dwelling older adults and to improve upon previous models by using a large, pooled sample and by considering a wide range of candidate predictors, including medications.

Methods: Harmonized data from 2 Dutch (LASA, B-PROOF) and 1 German cohort (ActiFE Ulm) of adults aged ≥65 years were used to fit 2 logistic regression models: one for predicting any fall and another for predicting recurrent falls over 1 year.

Barriers and facilitators in using a Clinical Decision Support System for fall risk management for older people: a European survey.

Purpose: Fall-Risk Increasing Drugs (FRIDs) are an important and modifiable fall-risk factor. A Clinical Decision Support System (CDSS) could support doctors in optimal FRIDs deprescribing. Understanding barriers and facilitators is important for a successful implementation of any CDSS.

Clinical validation of clinical decision support systems for medication review: A scoping review.

The aim of this scoping review is to summarize approaches and outcomes of clinical validation studies of clinical decision support systems (CDSSs) to support (part of) a medication review. A literature search was conducted in Embase and Medline. In total, 30 articles validating a CDSS were ultimately included.

Potentially inappropriate medications and their effect on falls during hospital admission.

Objective: to investigate the effect of potentially inappropriate medications (PIMs) on inpatient falls and to identify whether PIMs as defined by STOPPFall or the designated section K for falls of STOPP v2 have a stronger association with inpatient falls when compared to the general tool STOPP v2.

Methods: a retrospective observational matching study using an electronic health records dataset of patients (≥70 years) admitted to an academic hospital (2015-19), including free text to identify inpatient falls. PIMs were identified using the STOPP v2, section K of STOPP v2 and STOPPFall.

Anticipated Benefits and Concerns of Sharing Hospital Outpatient Visit Notes With Patients (Open Notes) in Dutch Hospitals: Mixed Methods Study.

Background: The past few years have seen an increase in interest in sharing visit notes with patients. Sharing visit notes with patients is also known as "open notes." Shared notes are seen as beneficial for patient empowerment and communication, but concerns have also been raised about potential negative effects.

Effect of Interventions With a Clinical Decision Support System for Hospitalized Older Patients: Systematic Review Mapping Implementation and Design Factors.

Background: Clinical decision support systems (CDSSs) form an implementation strategy that can facilitate and support health care professionals in the care of older hospitalized patients.

Objective: Our study aims to systematically review the effects of CDSS interventions in older hospitalized patients. As a secondary aim, we aim to summarize the implementation and design factors described in effective and ineffective interventions and identify gaps in the current literature.

Barriers and facilitators influencing medication-related CDSS acceptance according to clinicians: A systematic review.

Background: A medication-related Clinical Decision Support System (CDSS) is an application that analyzes patient data to provide assistance in medication-related care processes. Despite its potential to improve the clinical decision-making process, evidence shows that clinicians do not always use CDSSs in such a way that their potential can be fully realized. This systematic literature review provides an overview of frequently-reported barriers and facilitators for acceptance of medication-related CDSS.

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.