PURPOSE: Cancer staging is critical for prognostication, treatment planning, and determining clinical trial eligibility. Electronic health records (EHRs) have structured staging modules, but physician use is inconsistent. Typically, stage is entered as unstructured free text in clinical notes and cannot easily be used for reporting. METHODS: We created an Epic Best Practice Advisory (BPA) decision support tool that requires physicians to enter cancer stage in a structured module. If certain conditions are met, the BPA is triggered as a hard stop, and the physician cannot chart until staging is complete or a reason for not staging is selected. We used Plan, Do, Study, Act methodology to inform the intervention and compared preexisting staging rates to rates at 4, 8, and 12 months postintervention. RESULTS: For 12 months before BPA implementation, 1,480 of 5,222 (28%) patients had cancer stage structured within the Epic problem list. From 1 to 4 months after the BPA 2,057 of 1,788 (115%) cases were staged in Epic. In the 5- to 8-month period after the BPA, 1,057 of 1,893 (56%) cases were staged, and 9 to 12 months after the BPA 1,082 of 1,817 (60%) were staged. CONCLUSION: Electronic decision support improves the rate of structured cancer staging at our institution. The staging rates between 56% and 60% for the 5- to 8-month and 9- to 12-month periods likely reflect accurate postintervention staging rates, whereas the initial 115% rate for 1 to 4 months is inflated by providers staging cancers diagnosed before the BPA.
PURPOSE:Cancer staging is critical for prognostication, treatment planning, and determining clinical trial eligibility. Electronic health records (EHRs) have structured staging modules, but physician use is inconsistent. Typically, stage is entered as unstructured free text in clinical notes and cannot easily be used for reporting. METHODS: We created an Epic Best Practice Advisory (BPA) decision support tool that requires physicians to enter cancer stage in a structured module. If certain conditions are met, the BPA is triggered as a hard stop, and the physician cannot chart until staging is complete or a reason for not staging is selected. We used Plan, Do, Study, Act methodology to inform the intervention and compared preexisting staging rates to rates at 4, 8, and 12 months postintervention. RESULTS: For 12 months before BPA implementation, 1,480 of 5,222 (28%) patients had cancer stage structured within the Epic problem list. From 1 to 4 months after the BPA 2,057 of 1,788 (115%) cases were staged in Epic. In the 5- to 8-month period after the BPA, 1,057 of 1,893 (56%) cases were staged, and 9 to 12 months after the BPA 1,082 of 1,817 (60%) were staged. CONCLUSION: Electronic decision support improves the rate of structured cancer staging at our institution. The staging rates between 56% and 60% for the 5- to 8-month and 9- to 12-month periods likely reflect accurate postintervention staging rates, whereas the initial 115% rate for 1 to 4 months is inflated by providers staging cancers diagnosed before the BPA.
Authors: Emily M Powers; Richard N Shiffman; Edward R Melnick; Andrew Hickner; Mona Sharifi Journal: J Am Med Inform Assoc Date: 2018-11-01 Impact factor: 4.497
Authors: Magaly Ramirez; Richard Maranon; Jeffery Fu; Janet S Chon; Kimberly Chen; Carol M Mangione; Gerardo Moreno; Douglas S Bell Journal: J Am Med Inform Assoc Date: 2018-09-01 Impact factor: 4.497
Authors: Hamid Emamekhoo; Cibele B Carroll; Chelsea Stietz; Jeffrey B Pier; Michael D Lavitschke; Daniel Mulkerin; Mary E Sesto; Amye J Tevaarwerk Journal: JCO Clin Cancer Inform Date: 2022-06
Authors: Selen Bozkurt; Christopher J Magnani; Martin G Seneviratne; James D Brooks; Tina Hernandez-Boussard Journal: Front Digit Health Date: 2022-06-02
Authors: Andrew M Namen; Daniel Forest; Amit K Saha; Kang Rui Xiang; Kelly Younger; Sarah Ellen E Stephens; Sheila Maurer; Arjun B Chatterjee; Alexander Sy; Cormac O'Donovan; Sandhya Kumar; Clark Pinyan; Ronald Carroll; Stephen P Peters; Edward F Haponik Journal: J Clin Sleep Med Date: 2022-08-01 Impact factor: 4.324