Conducting a representative national randomized control trial of tailored clinical decision support for nurses remotely: Methods and implications.
Contemp Clin Trials
; 118: 106712, 2022 07.
Article
em En
| MEDLINE
| ID: mdl-35235823
ABSTRACT
Clinical Decision Support (CDS) systems, patient specific evidence delivered to clinicians via the electronic health record (EHR) at the right time and in the right format, has the potential to improve patient outcomes. Unfortunately, outcomes of CDS research are mixed. A potential cause lies in its testing. Many CDS are implemented in practice without sufficient testing, potentially leading to patient harm. When testing is conducted, most research has focused on "what" evidence to provide with little attention to the impact of the CDS display format (e.g., textual, graphical) on the user. In an adequately powered randomized control trial with 220 hospital based registered nurses, we will compare 4 randomly assigned CDS format groups (text, text table, text graphs, tailored to subject's graph literacy score) for effects on decision time and simulated patient outcomes. We recruit using state based professional registries, which allows access to participants from multiple institutions across the nation. We use online survey software (REDCap) for efficient study workflow including screening, informed consent documentation, pre-experiment demographic data collection including a graph literacy questionnaire used in randomization. The CDS prototype is accessed via a web app and the simulation-based experiment is conducted remotely at a subject's local computer using video-conferencing software. Also included are 6 post intervention surveys to assess cognitive workload, usability, numeracy, format preference, CDS utilization rationale, and CDS interpretation. Our methods are replicable and scalable for testing of health information technologies and have the potential to improve the safety and effectiveness of these technologies across disciplines.
Palavras-chave
Texto completo:
1
Bases de dados:
MEDLINE
Assunto principal:
Sistemas de Apoio a Decisões Clínicas
Tipo de estudo:
Clinical_trials
/
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
Contemp Clin Trials
Assunto da revista:
MEDICINA
/
TERAPEUTICA
Ano de publicação:
2022
Tipo de documento:
Article