Development and validation of automated electronic health record data reuse for a multidisciplinary quality dashboard.
Digit Health
; 9: 20552076231191007, 2023.
Article
en En
| MEDLINE
| ID: mdl-37529541
ABSTRACT
Objective:
To describe the development and validation of automated electronic health record data reuse for a multidisciplinary quality dashboard. Materials andmethods:
Comparative study analyzing a manually extracted and an automatically extracted dataset with 262 patients treated for HNC cancer in a tertiary oncology center in the Netherlands in 2020. The primary outcome measures were the percentage of agreement on data elements required for calculating quality indicators and the difference between indicators results calculated using manually collected and indicators that used automatically extracted data.Results:
The results of this study demonstrate high agreement between manual and automatically collected variables, reaching up to 99.0% agreement. However, some variables demonstrate lower levels of agreement, with one variable showing only a 20.0% agreement rate. The indicator results obtained through manual collection and automatic extraction show high agreement in most cases, with discrepancy rates ranging from 0.3% to 3.5%. One indicator is identified as a negative outlier, with a discrepancy rate of nearly 25%.Conclusions:
This study shows that it is possible to use routinely collected structured data to reliably measure the quality of care in real-time, which could render manual data collection for quality measurement obsolete. To achieve reliable data reuse, it is important that relevant data is recorded as structured data during the care process. Furthermore, the results also imply that data validation is conditional to development of a reliable dashboard.
Texto completo:
1
Banco de datos:
MEDLINE
Tipo de estudio:
Prognostic_studies
Idioma:
En
Revista:
Digit Health
Año:
2023
Tipo del documento:
Article
País de afiliación:
Países Bajos