{"id":533,"date":"2020-12-04T15:35:42","date_gmt":"2020-12-04T20:35:42","guid":{"rendered":"https:\/\/health.uconn.edu\/health-interoperability-learning\/?p=533"},"modified":"2020-12-22T15:08:22","modified_gmt":"2020-12-22T20:08:22","slug":"analysis-of-medication-therapy-discontinuation-orders-in-new-electronic-prescriptions-and-opportunities-for-implementing-cancelrx","status":"publish","type":"post","link":"https:\/\/health.uconn.edu\/health-interoperability-learning\/2020\/12\/04\/analysis-of-medication-therapy-discontinuation-orders-in-new-electronic-prescriptions-and-opportunities-for-implementing-cancelrx\/","title":{"rendered":"Analysis of medication therapy discontinuation orders in new electronic prescriptions and opportunities for implementing CancelRx"},"content":{"rendered":"<div id=\"pl-533\"  class=\"panel-layout\" ><div id=\"pg-533-0\"  class=\"panel-grid panel-no-style\" ><div id=\"pgc-533-0-0\"  class=\"panel-grid-cell\" ><div id=\"panel-533-0-0-0\" class=\"so-panel widget widget_black-studio-tinymce widget_black_studio_tinymce panel-first-child panel-last-child\" data-index=\"0\" ><div class=\"textwidget\"><table width=\"0\" style=\"width: 101.305%;\">\n<tbody>\n<tr>\n<td width=\"98\" style=\"width: 10.303%;\">Study Type\/ Setting<\/td>\n<td width=\"111\" style=\"width: 26.7867%;\">Methods<\/td>\n<td width=\"117\" style=\"width: 28.7506%;\">Outcomes<\/td>\n<td width=\"144\" style=\"width: 24.9248%;\">Recommendations<\/td>\n<td width=\"367\" style=\"width: 8.5278%;\">Source<\/td>\n<\/tr>\n<tr>\n<td width=\"98\" style=\"width: 10.303%;\">Retrospective analysis<\/td>\n<td width=\"111\" style=\"width: 26.7867%;\">- N=1,400,000 - 410,591 prescribers using 734 EHRs<\/p>\n<p>- 7 day follow up (Nov 6, 2016-Nov 12, 2016)<\/p>\n<p>- The sample size was calculated to be representative with a margin of 0.8% error at a confidence level of 99.9%<\/p>\n<p>- Variable: New Rx with cancellation message vs CancelRx<\/td>\n<td width=\"117\" style=\"width: 28.7506%;\">- Identified 9735 (0.7% of the total) NewRx messages containing prescription cancellation instructions with 78.5% observed in the Notes field; 35.3% of identified NewRxs were associated with high-alert or LASA medications.<\/p>\n<p>- The most prevalent cancellation instruction types were medication strength or dosage changes (39.3%) and alternative therapy replacement orders (39.0%)<\/td>\n<td width=\"144\" style=\"width: 24.9248%;\">- Wider adoption of CancelRx in the EHR and pharmacy systems can significantly impact patient safety by reducing duplication and inappropriate medications<\/td>\n<td width=\"367\" style=\"width: 8.5278%;\">&nbsp;<\/p>\n<p><a href=\"https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC6342171\/\" target=\"blank\">Yang Y et al. (2018)<\/a><\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 10.303%;\" colspan=\"5\">Yang Y, Ward-Charlerie S, Kashyap N, Demayo R, Agresta T, Green J. Analysis of medication therapy discontinuation orders in new electronic prescriptions and<br \/>\nopportunities for implementing CancelRx. Journal of the American Medical Informatics Association. 2018;25(11):1516-1523.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div><\/div><\/div><\/div><\/div>","protected":false},"excerpt":{"rendered":"<p>Study Type\/ Setting Methods Outcomes Recommendations Source Retrospective analysis &#8211; N=1,400,000 &#8211; 410,591 prescribers using 734 EHRs &#8211; 7 day follow up (Nov 6, 2016-Nov 12, 2016) &#8211; The sample size was calculated to be representative with a margin of 0.8% error at a confidence level of 99.9% &#8211; Variable: New Rx with cancellation message [&hellip;]<\/p>\n","protected":false},"author":2053,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"wds_primary_category":0,"footnotes":""},"categories":[13],"tags":[14,15,16,10,11],"acf":[],"publishpress_future_action":{"enabled":false,"date":"2026-05-30 00:01:00","action":"change-status","newStatus":"draft","terms":[],"taxonomy":"category"},"_links":{"self":[{"href":"https:\/\/health.uconn.edu\/health-interoperability-learning\/wp-json\/wp\/v2\/posts\/533"}],"collection":[{"href":"https:\/\/health.uconn.edu\/health-interoperability-learning\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/health.uconn.edu\/health-interoperability-learning\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/health.uconn.edu\/health-interoperability-learning\/wp-json\/wp\/v2\/users\/2053"}],"replies":[{"embeddable":true,"href":"https:\/\/health.uconn.edu\/health-interoperability-learning\/wp-json\/wp\/v2\/comments?post=533"}],"version-history":[{"count":3,"href":"https:\/\/health.uconn.edu\/health-interoperability-learning\/wp-json\/wp\/v2\/posts\/533\/revisions"}],"predecessor-version":[{"id":755,"href":"https:\/\/health.uconn.edu\/health-interoperability-learning\/wp-json\/wp\/v2\/posts\/533\/revisions\/755"}],"wp:attachment":[{"href":"https:\/\/health.uconn.edu\/health-interoperability-learning\/wp-json\/wp\/v2\/media?parent=533"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/health.uconn.edu\/health-interoperability-learning\/wp-json\/wp\/v2\/categories?post=533"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/health.uconn.edu\/health-interoperability-learning\/wp-json\/wp\/v2\/tags?post=533"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}