{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T18:34:16Z","timestamp":1790706856721,"version":"4.1.0"},"reference-count":60,"publisher":"BMJ","issue":"12","content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["BMJ Open"],"accepted":{"date-parts":[[2016,10,3]]},"published-print":{"date-parts":[[2016,12]]},"abstract":"<jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>We aimed to construct widely useable summary measures of the net impact of antibiotic resistance on empiric therapy. Summary measures are needed to communicate the importance of resistance, plan and evaluate interventions, and direct policy and investment.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design, setting and participants<\/jats:title>\n                    <jats:p>As an example, we retrospectively summarised the 2011 cumulative antibiogram from a Toronto academic intensive care unit.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Outcome measures<\/jats:title>\n                    <jats:p>We developed two complementary indices to summarise the clinical impact of antibiotic resistance and drug availability on empiric therapy. The Empiric Coverage Index (ECI) measures susceptibility of common bacterial infections to available empiric antibiotics as a percentage. The Empiric Options Index (EOI) varies from 0 to \u2018the number of treatment options available\u2019, and measures the empiric value of the current stock of antibiotics as a depletable resource. The indices account for drug availability and the relative clinical importance of pathogens. We demonstrate meaning and use by examining the potential impact of new drugs and threatening bacterial strains.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>\n                      In our intensive care unit coverage of device-associated infections measured by the ECI remains high (98%), but 37\u201344% of treatment potential measured by the EOI has been lost. Without reserved drugs, the ECI is 86\u201388%. New cephalosporin\/\u03b2-lactamase inhibitor combinations could increase the EOI, but no single drug can compensate for losses. Increasing methicillin-resistant\n                      <jats:italic>Staphylococcus aureus<\/jats:italic>\n                      (MRSA) prevalence would have little overall impact (ECI=98%, EOI=4.8\u20135.2) because many Gram-positives are already resistant to \u03b2-lactams. Aminoglycoside resistance, however, could have substantial clinical impact because they are among the few drugs that provide coverage of Gram-negative infections (ECI=97%, EOI=3.8\u20134.5). Our proposed indices summarise the local impact of antibiotic resistance on empiric coverage (ECI) and available empiric treatment options (EOI) using readily available data. Policymakers and drug developers can use the indices to help evaluate and prioritise initiatives in the effort against antimicrobial resistance.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1136\/bmjopen-2016-012040","type":"journal-article","created":{"date-parts":[[2016,12,24]],"date-time":"2016-12-24T13:35:38Z","timestamp":1482586538000},"page":"e012040","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":22,"title":["How to measure the impacts of antibiotic resistance and antibiotic development on empiric therapy: new composite indices"],"prefix":"10.1136","volume":"6","author":[{"given":"Josie S","family":"Hughes","sequence":"first","affiliation":[{"name":"Centre for Disease Modelling, York University, Toronto, Ontario, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amy","family":"Hurford","sequence":"additional","affiliation":[{"name":"Department of Biology and Department of Mathematics and Statistics, Memorial University of Newfoundland, St. John's, Newfoundland, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rita L","family":"Finley","sequence":"additional","affiliation":[{"name":"Centre for Food-borne, Environmental and Zoonotic Infectious Diseases, Public Health Agency of Canada, Guelph, Ontario, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David M","family":"Patrick","sequence":"additional","affiliation":[{"name":"Centre for Disease Control, Vancouver, British Columbia, Canada"},{"name":"School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianhong","family":"Wu","sequence":"additional","affiliation":[{"name":"Centre for Disease Modelling, York University, Toronto, Ontario, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew M","family":"Morris","sequence":"additional","affiliation":[{"name":"Department of Medicine, Mount Sinai Hospital and University Health Network, Toronto, Ontario, Canada"},{"name":"Department of Medicine, University of Toronto, Toronto, Ontario, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"239","published-online":{"date-parts":[[2016,12,16]]},"reference":[{"key":"2025121603342808000_6.12.e012040.1","unstructured":"CDC: Centers for Disease Control and Prevention. 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