Conceptualizations of health, ability to act upon those definitions and desire for supports among families from historically marginalized communities.

Respect for parents' values and clinician-parent collaboration is less common among families from historically marginalized communities. We investigated how parents from marginalized communities operationalize health and their preferences for paediatric primary care. We recruited families who spoke English, Haitian Creole or Spanish with at least one child younger than 6 years old. Staff queried families' values and life experiences, perspectives on health and healthcare, social supports and resources. Fourteen interviews with the parents of 26 children were thematically analysed. Interviews revealed the following four themes: (1) parents' definitions of 'health' extend beyond physical health; (2) families' ability to actuate health definitions is complicated by poverty's impact on agency; (3) parents engage in ongoing problem recognition and identify solutions, but enacting solutions can be derailed by barriers and (4) parents want support from professionals and peers who acknowledged the hard work of parenting. Eliciting parents' multidimensional conceptualizations of health can support families' goal achievement and concern identification in the context of isolation, limited agency and few resources. Efforts to improve family centred care and reduce disparities in paediatric primary care must be responsive to the strengths, challenges, resources and priorities of marginalized families.

Using Electronic Health Records to Identify Asthma-Related Acute Care Encounters.

OBJECTIVE: Leveraging "big data" to improve care requires that clinical concepts be operationalized using available data. Electronic health record (EHR) data can be used to evaluate asthma care, but relying solely on diagnosis codes may misclassify asthma-related encounters. We created streamlined, feasible and transparent prototype algorithms for EHR data to classify emergency department (ED) encounters and hospitalizations as "asthma-related." METHODS: As part of an asthma program evaluation, expert clinicians conducted a multi-phase iterative chart review to evaluate 467 pediatric ED encounters and 136 hospitalizations with asthma diagnosis codes from calendar years 2017 and 2019, rating the likelihood that each encounter was actually asthma-related. Using this as a reference standard, we developed rule-based algorithms for EHR data to classify visits. Accuracy was evaluated using sensitivity, specificity, and positive and negative predictive values (PPV, NPV). RESULTS: Clinicians categorized 38% of ED encounters as "definitely" or "probably" asthma-related; 13% as "possibly" asthma-related; and 49% as "probably not" or "definitely not" related to asthma. Based on this reference standard, we created two rule-based algorithms to identify "definitely" or "probably" asthma-related encounters, one using text and non-text EHR fields and another using non-text fields only. Sensitivity, specificity, PPV, and NPV were >95% for the algorithm using text and non-text fields and >87% for the algorithm using only non-text fields compared to the reference standard. We created a two-rule algorithm to identify asthma-related hospitalizations using only non-text fields. CONCLUSIONS: Diagnostic codes alone are insufficient to identify asthma-related visits, but EHR-based prototype algorithms that include additional methods of identification can predict clinician-identified visits with sufficient accuracy.