Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: This is the second in a series of two papers regarding the construction of data quality (DQ) assured repositories, based on population data from Electronic Health Records (EHR), for the reuse of information on infant feeding from birth until the age of two. This second paper describes the application of the computational process of constructing the first quality-assured repository for the reuse of information on infant feeding in the perinatal period, with the aim of studying relevant questions from the Baby Friendly Hospital Initiative (BFHI) and monitoring its deployment in our hospital.#R##N##R##N#The construction of the repository was carried out using 13 semi-automated procedures to assess, recover or discard clinical data. The initial information consisted of perinatal forms from EHR related to 2048 births (Facts of Study, FoS) beten 2009 and 2011, with a total of 433,308 observations of 223 variables. DQ was measured before and after the procedures using metrics related to eight quality dimensions: predictive value, correctness, duplication, consistency, completeness, contextualization, temporal-stability, and spatial-stability.#R##N##R##N#Once the predictive variables re selected and DQ was assured, the final repository consisted of 1925 births, 107,529 observations and 73 quality-assured variables. The amount of discarded observations mainly corresponds to observations of non-predictive variables (52.90%) and the impact of the de-duplication process (20.58%) with respect to the total input data. Seven out of thirteen procedures achieved 100% of valid births, observations and variables. Moreover, 89% of births and ~98% of observations re consistent according to the experts׳ criteria. A multidisciplinary approach along with the quantification of DQ has allod us to construct the first repository about infant feeding in the perinatal period based on EHR population data.
['Ricardo García-de-León-Chocano', 'Verónica Muñoz-Soler', 'Carlos Sáez', 'Ricardo García-de-León-González', 'Juan Miguel García-Gómez']
I am writing a research paper on a idea Construction of quality-assured infant feeding process of care data repositories: Construction of the perinatal repository (Part 2)
[{"from": "human", "value": "I am writing a research paper on a idea Construction of quality-assured infant feeding process of care data repositories: Construction of the perinatal repository (Part 2)"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: This is the second in a series of two papers regarding the construction of data quality (DQ) assured repositories, based on population data from Electronic Health Records (EHR), for the reuse of information on infant feeding from birth until the age of two. This second paper describes the application of the computational process of constructing the first quality-assured repository for the reuse of information on infant feeding in the perinatal period, with the aim of studying relevant questions from the Baby Friendly Hospital Initiative (BFHI) and monitoring its deployment in our hospital.#R##N##R##N#The construction of the repository was carried out using 13 semi-automated procedures to assess, recover or discard clinical data. The initial information consisted of perinatal forms from EHR related to 2048 births (Facts of Study, FoS) beten 2009 and 2011, with a total of 433,308 observations of 223 variables. DQ was measured before and after the procedures using metrics related to eight quality dimensions: predictive value, correctness, duplication, consistency, completeness, contextualization, temporal-stability, and spatial-stability.#R##N##R##N#Once the predictive variables re selected and DQ was assured, the final repository consisted of 1925 births, 107,529 observations and 73 quality-assured variables. The amount of discarded observations mainly corresponds to observations of non-predictive variables (52.90%) and the impact of the de-duplication process (20.58%) with respect to the total input data. Seven out of thirteen procedures achieved 100% of valid births, observations and variables. Moreover, 89% of births and ~98% of observations re consistent according to the experts\u05f3 criteria. A multidisciplinary approach along with the quantification of DQ has allod us to construct the first repository about infant feeding in the perinatal period based on EHR population data."}]