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Can structured data fields accurately measure quality of care? The example of falls. David A. Ganz, MD, PhD; Shone Almeida, BS; Carol P. Roth, RN, MPH; David B. Reuben, MD; Neil S. Wenger, MD, MPH. Aim
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Can structured data fields accurately measure quality of care? The example of falls David A. Ganz, MD, PhD; Shone Almeida, BS; Carol P. Roth, RN, MPH; David B. Reuben, MD; Neil S. Wenger, MD, MPH
Aim • Determine whether quality of care can be accurately estimated from structured (non-free-text) fields in structured visit note (SVN) when SVN is part of routine documentation. • Relevance • By automating collection of data elements, electronic health records may simplify process of measuring quality of medical care.
Method • Used data from quality improvement initiative in primary care medical groups. • Determined whether quality of care for falls/fear of falling in outpatients aged 75+ could be accurately measured from codable data in SVN. • Criterion standard was traditional medical record review by trained abstractors. Sample SVN.
Results • 215 patient records reviewed. • SVN in 54% of charts within 3 mo of patients identified as having falls or fear of falling. • Automated algorithm based on codable data: • Reliability was at least good (kappa ≥ 0.61) vs. full medical record review for 3 care processes (ortho-static vital signs, vision test/eye examination, and home safety evaluation) recommended for patients with 2 falls or 1 fall with injury in past year. • Routinely underestimated quality of care.
Conclusion • Structured data should be used cautiously for measurement of quality of care and will likely underestimate actual care delivery. • Degree to which structured data accurately represent underlying care delivered varies according to type of care process. • Quality measurement systems using automated data will continue to benefit from validation against full medical record review.