OBJECTIVE: To define a core dataset for preoperative assessment to leverage uniform data collection in this domain. This uniformity is a prerequisite for data exchange between care providers and semantic interoperability between health record systems. METHODS: To design this core dataset a combination of literature review and expert consensus meetings were used. In the first meeting a working definition for "core dataset" was specified. Subgroups were formed to address major headings of the core dataset. In the following eight meetings data items for each subheading were discussed. The items in the resulting draft of the dataset were compared to those retrieved from an earlier literature review study. In the last two expert meetings modifications of the dataset were performed based on the result of this literature study. RESULTS: Based on expert consensus a draft dataset including 82 data items was designed. Seventy-six percent of data items in the draft dataset were covered by the literature study. Nine data items were modified in the draft and 14 data items were added to the dataset based on input from the literature review. The final dataset of 93 data items covers patient history, physical examination, supplementary examination and consultation, and final judgment. CONCLUSIONS: This preoperative-assessment dataset was defined based on expert consensus and literature review. Both methods proved to be valuable and complementary. This dataset opens the door for creating standardized approaches in data collection in the preoperative assessment field which will facilitate interoperability between different electronic health records and different users.
OBJECTIVE: To define a core dataset for preoperative assessment to leverage uniform data collection in this domain. This uniformity is a prerequisite for data exchange between care providers and semantic interoperability between health record systems. METHODS: To design this core dataset a combination of literature review and expert consensus meetings were used. In the first meeting a working definition for "core dataset" was specified. Subgroups were formed to address major headings of the core dataset. In the following eight meetings data items for each subheading were discussed. The items in the resulting draft of the dataset were compared to those retrieved from an earlier literature review study. In the last two expert meetings modifications of the dataset were performed based on the result of this literature study. RESULTS: Based on expert consensus a draft dataset including 82 data items was designed. Seventy-six percent of data items in the draft dataset were covered by the literature study. Nine data items were modified in the draft and 14 data items were added to the dataset based on input from the literature review. The final dataset of 93 data items covers patient history, physical examination, supplementary examination and consultation, and final judgment. CONCLUSIONS: This preoperative-assessment dataset was defined based on expert consensus and literature review. Both methods proved to be valuable and complementary. This dataset opens the door for creating standardized approaches in data collection in the preoperative assessment field which will facilitate interoperability between different electronic health records and different users.