{"doi":"10.1016/j.mayocp.2023.05.025","title":"Clinical Decision Support: Moving Beyond Interruptive “Pop-up” Alerts","abstract":"We cannot afford to commit genericide with clinical decision support (CDS). Genericide refers to when a product or service becomes so widely used that consumers refer to generic versions with the brand name. Copying a document is xeroxing. Searching for information on the internet is googling. Digitally altering an image is photoshopping. Videoconferencing is zooming. Clinical decision support, however, is so much broader than the narrow offering of a “best practice advisory”—an interruptive “pop-up” triggered by an if/then criterion—and should not be genericized as such. Clinical decision support can also electronically deliver patient-specific recommendations in less obtrusive ways as reminders, information display, info buttons, order sets, documentation templates, algorithms, and calculators. Given the pervasiveness of interruptive pop-up alerts, health care workers tend to think of them as one and the same as CDS—overriding pop-ups up to 96% of the times they fire without taking action or even recognizing the recommendation being offered.1Phansalkar S. Desai A.A. Bell D. et al.High-priority drug-drug interactions for use in electronic health records.J Am Med Inform Assoc. 2012; 19: 735-743Crossref PubMed Scopus (110) Google Scholar These interruptions are not without consequence. They necessitate task switching, which in turn increases cognitive load and introduces the opportunity for error and task abandonment, both of which threaten patient safety.2Westbrook J.I. Raban M.Z. Walter S.R. Douglas H. Task errors by emergency physicians are associated with interruptions, multitasking, fatigue and working memory capacity: a prospective, direct observation study.BMJ Qual Saf. 2018; 27655663Crossref Scopus (149) Google Scholar In situations in which pop-up alerts are dismissed, CDS is not having its intended consequence, probably because of a failure to adhere to the “5 rights” of CDS: delivery of the right information to the right person in the right format through the right channel and at the right time in the workflow.3Sirajuddin A.M. Osheroff J.A. Sittig D.F. Chuo J. Velasco F. Collins D.A. Implementation pearls from a new guidebook on improving medication use and outcomes with clinical decision support. Effective CDS is essential for addressing healthcare performance improvement imperatives.J Healthc Inf Manag. 2009; 23: 38-45PubMed Google Scholar Here, we present evidence of 2 interventions that have done this and the technology that will allow similar solutions to become more commonplace, thereby displacing ineffective pop-up alerts. To date, CDS has had limited and at times unintended effects on outcomes with implementation rarely optimized for workflow unless it has been designed with rigorous end user evaluation.4Powers E.M. Shiffman R.N. Melnick E.R. Hickner A. Sharifi M. Efficacy and unintended consequences of hard-stop alerts in electronic health record systems: a systematic review.J Am Med Inform Assoc. 2018; 25: 1556-1566Crossref PubMed Scopus (57) Google Scholar, 5Hussain M.I. Reynolds T.L. Zheng K. Medication safety alert fatigue may be reduced via interaction design and clinical role tailoring: a systematic review.J Am Med Inform Assoc. 2019; 26: 1141-1149Crossref Scopus (49) Google Scholar, 6Stone E.G. Unintended adverse consequences of a clinical decision support system: two cases.J Am Med Inform Assoc. 2017; 25: 564-567Crossref Scopus (18) Google Scholar, 7Strom B.L. Schinnar R. Aberra F. et al.Unintended effects of a computerized physician order entry nearly hard-stop alert to prevent a drug interaction: a randomized controlled trial.Arch Intern Med. 2010; 170: 1578-1583Crossref PubMed Scopus (168) Google Scholar One study, a 2020 meta-analysis across 122 randomized trials of CDS including more than 1.2 million patients, found that CDS systems were associated with a less than 6% increase in average number of patients achieving the desired outcome.8Kwan J.L. Lo L. Ferguson J. et al.Computerised clinical dec","journal":"Mayo Clinic Proceedings","year":2023,"id":329722,"datarank":0.4493598410330987,"base_score":2.995732273553991,"endowment":2.995732273553991,"self_citation_contribution":0.4493598410330987,"citation_network_contribution":0.0,"self_endowment_contribution":0.4493598410330987,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":19,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9568,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":413218,"name":"Mona Sharifi","orcid":"0000-0002-1632-7038","position":1,"is_corresponding":false},{"id":274810,"name":"Deborah J. Rhodes","orcid":"0000-0003-4408-6451","position":2,"is_corresponding":false},{"id":34339,"name":"Edward R. Melnick","orcid":"0000-0002-6509-9537","position":3,"is_corresponding":false},{"id":1052869,"name":"Rohit B. Sangal","orcid":"0000-0002-0435-7029","position":0,"is_corresponding":true}],"reference_count":21,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T01:09:05.843139Z","pmid":"37661138","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}