The overall goal of the IQ-MAPLE project is to improve the quality of care provided to patients with several heart, lung and blood conditions by facilitating more accurate and complete problem list documentation. In the first aim, the investigators will design and validate a series of problem inference algorithms, using rule-based techniques on structured data in the electronic health record (EHR) and natural language processing on unstructured data. Both of these techniques will yield candidate problems that the patient is likely to have, and the results will be integrated. In Aim 2, the investigators will design clinical decision support interventions in the EHRs of the four study sites to alert physicians when a candidate problem is detected that is missing from the patient's problem list - the clinician will then be able to accept the alert and add the problem, override the alert, or ignore it entirely. In Aim 3, the investigators will conduct a randomized trial and evaluate the effect of the problem list alert on three endpoints: alert acceptance, problem list addition rate and clinical quality.
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Measuring the rate of acceptance of alerts calculated by number of acceptances for each alert divided by the total number of unique presentations of the alert
Timeframe: Through study completion, or up to 1 year
Determining the effect of problem list completion by comparing the number of study-related problems added to problem lists in the electronic health record
Timeframe: Through study completion, or up to 1 year
Determining the quality of care impact of adding suggested problems to the problem list based on 4 outcome measures from NCQA's HEDIS 2013 measure set
Timeframe: Through study completion, or up to 1 year