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Characteristics and predictors of missed opportunities in lung cancer diagnosis: an electronic health record-based study.

ABSTRACT: Understanding delays in cancer diagnosis requires detailed information about timely recognition and follow-up of signs and symptoms. This information has been difficult to ascertain from paper-based records. We used an integrated electronic health record (EHR) to identify characteristics and predictors of missed opportunities for earlier diagnosis of lung cancer.Using a retrospective cohort design, we evaluated 587 patients of primary lung cancer at two tertiary care facilities. Two physicians independently reviewed each case, and disagreements were resolved by consensus. Type I missed opportunities were defined as failure to recognize predefined clinical clues (ie, no documented follow-up) within 7 days. Type II missed opportunities were defined as failure to complete a requested follow-up action within 30 days.Reviewers identified missed opportunities in 222 (37.8%) of 587 patients. Median time to diagnosis in cases with and without missed opportunities was 132 days and 19 days, respectively (P < .001). Abnormal chest x-ray was the clue most frequently associated with type I missed opportunities (62%). Follow-up on abnormal chest x-ray (odds ratio [OR], 2.07; 95% CI, 1.04 to 4.13) and completion of first needle biopsy (OR, 3.02; 95% CI, 1.76 to 5.18) were associated with type II missed opportunities. Patient adherence contributed to 44% of patients with missed opportunities.Preventable delays in lung cancer diagnosis arose mostly from failure to recognize documented abnormal imaging results and failure to complete key diagnostic procedures in a timely manner. Potential solutions include EHR-based strategies to improve recognition of abnormal imaging and track patients with suspected cancers.

SUBMITTER: Singh H

PROVIDER: S-EPMC2903328 | biostudies-other | 2010 Jul

REPOSITORIES: biostudies-other

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Characteristics and predictors of missed opportunities in lung cancer diagnosis: an electronic health record-based study.

Singh Hardeep H Hirani Kamal K Kadiyala Himabindu H Rudomiotov Olga O Davis Traber T Khan Myrna M MM Wahls Terry L TL

Journal of clinical oncology : official journal of the American Society of Clinical Oncology 20100607 20

<h4>Purpose</h4>Understanding delays in cancer diagnosis requires detailed information about timely recognition and follow-up of signs and symptoms. This information has been difficult to ascertain from paper-based records. We used an integrated electronic health record (EHR) to identify characteristics and predictors of missed opportunities for earlier diagnosis of lung cancer.<h4>Methods</h4>Using a retrospective cohort design, we evaluated 587 patients of primary lung cancer at two tertiary c ...[more]

PMID: 20530272

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Dataset Information

Characteristics and predictors of missed opportunities in lung cancer diagnosis: an electronic health record-based study.

Publications

Characteristics and predictors of missed opportunities in lung cancer diagnosis: an electronic health record-based study.

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