Medication Reconciliation during Transitions of Care Across Institutions: A Quantitative Analysis of Challenges and Opportunities

Alejandro Araya; Logan R. Thornton; Deukwoo Kwon; Gayla M. Ferguson; Linda D. Highfield; Kevin O. Hwang; Holly M. Holmes; Elmer V. Bernstam

doi:10.1055/a-2178-0197

Applied Clinical Informatics, Inhaltsverzeichnis

CC BY-NC-ND 4.0 · Appl Clin Inform 2023; 14(05): 923-931
DOI: 10.1055/a-2178-0197

Research Article

Medication Reconciliation during Transitions of Care Across Institutions: A Quantitative Analysis of Challenges and Opportunities

Alejandro Araya

¹D. Bradley McWilliams School of Biomedical Informatics, The University of Texas Health Science Center (UTHealth), Houston, Texas, United States

,

Logan R. Thornton

²Division of Population Health and Evidence-Based Practice, Healthcare Transformation Initiatives, The University of Texas Health Science Center at Houston (UTHealth) John P. and Kathrine G. McGovern Medical School, Houston, Texas, United States

,

Deukwoo Kwon

³Division of Clinical and Translation Sciences, Department of Internal Medicine, The University of Texas Health Science Center at Houston (UTHealth) John P. and Kathrine G. McGovern Medical School, Houston, Texas, United States

,

Gayla M. Ferguson

⁴Department of Management, Policy and Community Health, The University of Texas Health Science Center at Houston (UTHealth) School of Public Health, Houston, Texas, United States

,

Linda D. Highfield

⁴Department of Management, Policy and Community Health, The University of Texas Health Science Center at Houston (UTHealth) School of Public Health, Houston, Texas, United States

⁵Department of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas Health Science Center at Houston (UTHealth) School of Public Health, Houston, Texas, United States

⁶Department of Internal Medicine, The University of Texas Health Science Center at Houston (UTHealth) John P. and Kathrine G. McGovern Medical School, Houston, Texas, United States

,

Kevin O. Hwang

⁷Division of General Internal Medicine, Department of Internal Medicine, The University of Texas Health Science Center at Houston (UTHealth) John P. and Kathrine G. McGovern Medical School, Houston, Texas, United States

,

Holly M. Holmes

⁸Division of Geriatrics, Department of Internal Medicine, The University of Texas Health Science Center at Houston (UTHealth) John P. and Kathrine G. McGovern Medical School, Houston, Texas, United States

,

Elmer V. Bernstam

¹D. Bradley McWilliams School of Biomedical Informatics, The University of Texas Health Science Center (UTHealth), Houston, Texas, United States

⁷Division of General Internal Medicine, Department of Internal Medicine, The University of Texas Health Science Center at Houston (UTHealth) John P. and Kathrine G. McGovern Medical School, Houston, Texas, United States

› Institutsangaben

Abstract

Objective Medication discrepancies between clinical systems may pose a patient safety hazard. In this paper, we identify challenges and quantify medication discrepancies across transitions of care.

Methods We used structured clinical data and free-text hospital discharge summaries to compare active medications' lists at four time points: preadmission (outpatient), at-admission (inpatient), at-discharge (inpatient), and postdischarge (outpatient). Medication lists were normalized to RxNorm. RxNorm identifiers were further processed using the RxNav API to identify the ingredient. The specific drugs and ingredients from inpatient and outpatient medication lists were compared.

Results Using RxNorm drugs, the median percentage intersection when comparing active medication lists within the same electronic health record system ranged between 94.1 and 100% indicating substantial overlap. Similarly, when using RxNorm ingredients the median percentage intersection was 94.1 to 100%. In contrast, the median percentage intersection when comparing active medication lists across EHR systems was significantly lower (RxNorm drugs: 6.1–7.1%; RxNorm ingredients: 29.4–35.0%) indicating that the active medication lists were significantly less similar (p < 0.05).

Medication lists in the same EHR system are more similar to each other (fewer discrepancies) than medication lists in different EHR systems when comparing specific RxNorm drug and the more general RxNorm ingredients at transitions of care. Transitions of care that require interoperability between two EHR systems are associated with more discrepancies than transitions where medication changes are expected (e.g., at-admission vs. at-discharge). Challenges included lack of access to structured, standardized medication data across systems, and difficulty distinguishing medications from orderable supplies such as lancets and diabetic test strips.

Conclusion Despite the challenges to medication normalization, there are opportunities to identify and assist with medication reconciliation across transitions of care between institutions.

Keywords

medical records' systems - computerized - medication reconciliation - patient safety

Volltext

Referenzen

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