BACKGROUND: Delayed patient recruitment is a common problem in clinical trials. According to the literature, only about a third of medical research studies recruit their planned number of patients within the time originally specified. OBJECTIVES: To provide a method to estimate patient accrual rates in clinical trials based on routine data from hospital information systems (HIS). METHODS: Based on inclusion and exclusion criteria for each trial, a specific HIS report is generated to list potential trial subjects. Because not all information relevant for assessment of patient eligibility is available as coded HIS items, a sample of this patient list is reviewed manually by study physicians. Proportions of matching and non-matching patients are analyzed with a Chi-squared test. An estimation formula for patient accrual rate is derived from this data. RESULTS: The method is demonstrated with two datasets from cardiology and oncology. HIS reports should account for previous disease episodes and eliminate duplicate persons. CONCLUSION: HIS data in combination with manual chart review can be applied to estimate patient recruitment for clinical trials.
BACKGROUND: Delayed patient recruitment is a common problem in clinical trials. According to the literature, only about a third of medical research studies recruit their planned number of patients within the time originally specified. OBJECTIVES: To provide a method to estimate patient accrual rates in clinical trials based on routine data from hospital information systems (HIS). METHODS: Based on inclusion and exclusion criteria for each trial, a specific HIS report is generated to list potential trial subjects. Because not all information relevant for assessment of patient eligibility is available as coded HIS items, a sample of this patient list is reviewed manually by study physicians. Proportions of matching and non-matching patients are analyzed with a Chi-squared test. An estimation formula for patient accrual rate is derived from this data. RESULTS: The method is demonstrated with two datasets from cardiology and oncology. HIS reports should account for previous disease episodes and eliminate duplicate persons. CONCLUSION: HIS data in combination with manual chart review can be applied to estimate patient recruitment for clinical trials.
Authors: Catherine C Beauharnais; Mary E Larkin; Adrian H Zai; Emily C Boykin; Jennifer Luttrell; Deborah J Wexler Journal: Clin Trials Date: 2012-02-03 Impact factor: 2.486
Authors: Iñaki Soto-Rey; Benjamin Trinczek; Yannick Girardeau; Eric Zapletal; Nadir Ammour; Justin Doods; Martin Dugas; Fleur Fritz Journal: BMC Med Res Methodol Date: 2015-05-01 Impact factor: 4.615
Authors: Chin Yee Shim; Si Yee Chan; Yuan Wei; Hazim Ghani; Liyana Ahmad; Hanisah Sharif; Mohammad Fathi Alikhan; Saifuddien Haji Bagol; Surita Taib; Chee Wah Tan; Xin Mei Ong; Lin-Fa Wang; Yan Wang; An Qi Liu; Hong Shen Lim; Justin Wong; Lin Naing; Anne Catherine Cunningham Journal: Front Public Health Date: 2022-09-12