Figure. Relationship between the percentage of unreviewed tests and the time that the tests were available for review.
Ong M-S, Magrabi F, Jones G, Coiera E. Last Orders: Follow-up of Tests Ordered on the Day of Hospital Discharge. Arch Intern Med. Published online August 12, 2012. doi:10.1001/archinternmed.2012.2836
eTable 1. Prevalence of missed test results
eTable 2. Logistic regression model for missed follow-up of test results
eTable 3. Definition of reference range for individual tests
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Ong M, Magrabi F, Jones G, Coiera E. Last Orders: Follow-up of Tests Ordered on the Day of Hospital Discharge. Arch Intern Med. 2012;172(17):1347–1349. doi:10.1001/archinternmed.2012.2836
Failure to follow up test results contributes to patient harm, affecting between 20% and 61% of inpatient tests.1,2 Such missed results are clinically significant, with the potential to affect patient care.3-5 One factor that might shape test follow-up is the time available for review during admission. Tests requested early in an admission have more chance of being reviewed than those that are requested later in the hospital stay. Tests ordered on the day of discharge have a very limited chance of being reviewed. If time available for review is indeed a determinant of follow-up rates, there may be a potential to target the tests with limited review and increase the opportunity to improve follow-up rates. Previous studies have not accounted for this factor in their data analyses. In this study, we examined the risk for missed follow-up given the time available for follow-up. We hypothesized that test follow-up was a function of the opportunity for follow-up, measured as the number of admission days available for test review. We focused on tests ordered on the day of discharge, because this class of tests provides a unique opportunity for targeted intervention.
The study was conducted at a 370-bed metropolitan teaching hospital. Clinical pathology tests performed on inpatients between February and June 2011 were extracted from a computerized test-reporting system, excluding tests associated with deceased patients and tests communicated directly to the ordering physician. The prevalence of missed laboratory tests was determined by inspecting electronic time stamps that were generated when the tests were viewed and was calculated as the proportion of tests that were not reviewed at patient discharge or 2 months after discharge. All data were deidentified. The study was approved by the University of New South Wales, Sydney, Australia, as well as the hospital's research ethics committee.
A total of 733 891 individual tests were performed across 6736 inpatient admissions, with 662 858 meeting the inclusion criteria. Of these, 3.1% (n = 20 449) were not reviewed at discharge, decreasing to 1.5% (n = 10 043) 2 months after discharge (eTable 1). A total of 37.7% (n = 2542) of all inpatient admissions had 1 or more missed results before discharge, decreasing to 28.0% (n = 1886) 2 months after discharge.
While tests requested on the day of discharge represented only 6.8% (n = 44 953) of all tests performed, they contributed disproportionately to the total number of tests that were not followed up, accounting for 46.8% (n = 9573/20 449) of all missed results measured at discharge and 41.1% (n = 4123/10 043) of those measured 2 months after discharge. Not all test results were available at discharge, with 28.6% (n = 5850/20 449) of tests still pending. At discharge, 21.3% of tests ordered on that day were not followed up compared with 1.8% of tests ordered on other days (P < .001), and the disparity remained 2 months after discharge (9.2% vs 1.0%, P < .001).
Tests requested on the day of discharge had an increased risk of missed follow-up (odds ratio, 10.8; 95% CI, 10.4-11.1) (eTable 2). The review rates increased the longer a test result was available for review during admission (Figure). The rate of missed review was 2.7% for tests available for 2 days, 5.8% for those available for 1 day, and 21.3% for those available on the day of discharge. This relationship was evident for review rates both at discharge and 2 months after discharge.
Abnormal results accounted for 14.7% (n = 3014/20 449) of all unreviewed tests at discharge and for 10.8% (n = 1083/10 043) of all unreviewed tests 2 months after discharge (eTable 3). Tests ordered on the day of discharge accounted for 65.5% (n = 1975/3014) of all the abnormal results that were unreviewed at discharge and 68.0% (n = 736/1083) of all the abnormal results that were unreviewed 2 months after discharge.
Hospital discharge is a critical transition point for many patients, with 1 in 5 patients experiencing an adverse event in the transition from hospital to home and with 62% of these adverse events being preventable.6 Failure to follow up test results after discharge contributes to this risk.5,7
We have shown that poor test follow-up at or after discharge is disproportionately attributable to tests requested on the day of patient discharge, because such tests have a smaller time window available for review, and, indeed, not all tests will have results available at discharge. Yet, these discharge-day tests appear just as important as other tests, with similar rates of abnormal results.
It appears that at least some late admission tests represent an opportunity to optimize test ordering. Tests ordered as a result of poor discharge planning may well be unnecessary and are therefore strong candidates for targeted intervention. Improvement strategies include clearly communicating to all members of a clinical team that discharge is being planned and instituting team rules on appropriate testing and review procedures late in admission. Discharge protocols should require review of pending or unreviewed test results. When discharge dates are known, or the average length of stay for an admission is well defined, the time available for review can be estimated and used to trigger computer alerts when tests are being ordered electronically. Alerts could advise clinicians either that it is unlikely that results will be posted before discharge or that the tests simply have a high risk of being missed.
Correspondence: Dr Coiera, Centre for Health Informatics, University of New South Wales, Sydney NSW 2052, Australia (email@example.com).
Published Online: August 13, 2012. doi:10.1001/archinternmed.2012.2836
Author Contributions: Dr Ong had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Ong, Magrabi, and Coiera. Acquisition of data: Ong and Magrabi. Analysis and interpretation of data: Ong, Magrabi, Jones, and Coiera. Drafting of the manuscript: Ong. Critical revision of the manuscript for important intellectual content: Ong, Magrabi, Jones, and Coiera. Statistical analysis: Ong. Obtained funding: Coiera. Administrative, technical, and material support: Jones. Study supervision: Magrabi and Coiera.
Financial Disclosure: None reported.
Funding/Support: This project was supported in part by grant 568612 from the Australian National Health and Medical Research Council.
Additional Contributions: We thank Frank Lin, MBBS, PhD, for his involvement in the conception of the study and for sharing his expertise; David Roffe, Robert Flanagan, and Ed Tinker for providing access to the data; and Thuy Huynh for providing administrative assistance.