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Applying multiple methods to assess the readability of a large corpus of medical documents.

TitleApplying multiple methods to assess the readability of a large corpus of medical documents.
Publication TypeJournal Article
Year of Publication2013
AuthorsT Y Wu, D, Hanauer, DA, Mei, Q, Clark, PM, An, LC, Lei, J, Proulx, J, Zeng-Treitler, Q, Zheng, K
JournalStud Health Technol Inform
Date Published2013

Medical documents provided to patients at the end of an episode of care, such as discharge summaries and referral letters, serve as an important vehicle to convey critical information to patients and families. Increasingly, healthcare institutions are also experimenting with granting patients direct electronic access to other types of clinical narratives that are not typically shared unless explicitly requested, such as progress notes. While these efforts have great potential to improve information transparency, their value can be severely diminished if patients are unable to read and thus unable to properly interpret the medical documents shared to them. In this study, we approached the problem by contrasting the 'readability' of two types of medical documents: referral letters vs. other genres of narrative clinician notes not explicitly intended for direct viewing by patients. To establish a baseline for comparison, we also computed readability scores of MedlinePlus articles - exemplars of fine patient education materials carefully crafted for lay audiences. We quantified document readability using four different measures. Differences in the results obtained through these measures are also discussed.

Alternate JournalStud Health Technol Inform
PubMed ID23920636
Grant ListUL1 RR024986 / RR / NCRR NIH HHS / United States
UL1RR024986 / RR / NCRR NIH HHS / United States
David Hanauer
University of Michigan Comprehensive Cancer Center at North Campus Reserach Complex
1600 Huron Parkway, Bldg 100, Rm 100 
Mailing Address: 2800 Plymouth Rd, NCRC 100-1004
Ann Arbor, MI 48109-2800 
Ph. (734) 764-8848 Fax. (734) 615-0517
Please acknowledge the Cancer Center Support Grant (P30 CA046592) when publishing manuscripts or abstracts that utilized the services of the University of Michigan's Comprehensive Cancer Center's Shared Resource: Cancer Informatics.
Suggested language: "Research reported in this [publication/press release] was supported by the National Cancer Institute of the National Institutes of Health under award number P30CA046592."

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