Background and aims accurate knowledge of a Patient’s medical problem is critical for clinical decision making, quality measurement, and clinical research. Common structured sources of problem information, include patient problem list and billing data; however, these sources are often inaccurate and incomplete. Innovative computerized inference algorithm (ICIA) based decision support system was developed for Pediatric Primary Care in 2009. ICIA system will navigate Physicians; how to take patients’ histories, what to write on physical examinations, and what to do for laboratory and medication. We evaluated the performance of ICIA technology by analyzing the quality of medical record data.

Methods We compared the quality of the manual chart (data used: before 2008) and the ICIA supported chart (data used: after 2010). The data used, were 1,000 randomly sampled from 100,000 patients’ data, respectively. Each chart were scored by 3 physicians, who are highly trained and experienced in clinical research. The average score were used for analysis. Seven parameters (score) were defined as, clinical accuracy (0–10), legal accuracy (0–10), scientific accuracy (0–10), logical description (0–5), definition of terms (0–5), evidence based medicine (0–5), treatment plan (0–5) and total score (0–50).

Result The average of the total score was 38.0(±2.5) for the manual chart, and 43.0(±1.4) for the ICIA supported chart [P-value <0.001].

Conclusion The ICIA based decision support system improved the quality in medical record data, dramatically. The ICIA technology, from management sciences and engineering, will change the quality in patients’ safety, clinical research and risk-management.