Literature DB >> 32479177

Designing, Conducting, and Reporting Clinical Decision Support Studies: Recommendations and Call to Action.

Kensaku Kawamoto1, Clement J McDonald2.   

Abstract

By enabling more efficient and effective medical decision making, computer-based clinical decision support (CDS) could unlock widespread benefits from the significant investment in electronic health record (EHR) systems in the United States. Evidence from high-quality CDS studies is needed to enable and support this vision of CDS-facilitated care optimization, but limited guidance is available in the literature for designing and reporting CDS studies. To address this research gap, this article provides recommendations for designing, conducting, and reporting CDS studies to: 1) ensure that EHR data to inform the CDS are available; 2) choose decision rules that are consistent with local care processes; 3) target the right users and workflows; 4) make the CDS easy to access and use; 5) minimize the burden placed on users; 6) incorporate CDS success factors identified in the literature, in particular the automatic provision of CDS as a part of clinician workflow; 7) ensure that the CDS rules are adequately tested; 8) select meaningful evaluation measures; 9) use as rigorous a study design as is feasible; 10) think about how to deploy the CDS beyond the original host organization; 11) report the study in context; 12) help the audience understand why the intervention succeeded or failed; and 13) consider the financial implications. If adopted, these recommendations should help advance the vision of more efficient, effective care facilitated by useful and widely available CDS.

Year:  2020        PMID: 32479177     DOI: 10.7326/M19-0875

Source DB:  PubMed          Journal:  Ann Intern Med        ISSN: 0003-4819            Impact factor:   25.391


  14 in total

Review 1.  Evaluation in Life Cycle of Information Technology (ELICIT) framework: Supporting the innovation life cycle from business case assessment to summative evaluation.

Authors:  Polina V Kukhareva; Charlene Weir; Guilherme Del Fiol; Gregory A Aarons; Teresa Y Taft; Chelsey R Schlechter; Thomas J Reese; Rebecca L Curran; Claude Nanjo; Damian Borbolla; Catherine J Staes; Keaton L Morgan; Heidi S Kramer; Carole H Stipelman; Julie H Shakib; Michael C Flynn; Kensaku Kawamoto
Journal:  J Biomed Inform       Date:  2022-02-12       Impact factor: 6.317

2.  Systematic review of prediction models for postacute care destination decision-making.

Authors:  Erin E Kennedy; Kathryn H Bowles; Subhash Aryal
Journal:  J Am Med Inform Assoc       Date:  2021-12-28       Impact factor: 4.497

3.  Clinical Decision Support for Fall Prevention: Defining End-User Needs.

Authors:  Hannah Rice; Pamela M Garabedian; Kristen Shear; Ragnhildur I Bjarnadottir; Zoe Burns; Nancy K Latham; Denise Schentrup; Robert J Lucero; Patricia C Dykes
Journal:  Appl Clin Inform       Date:  2022-06-29       Impact factor: 2.762

Review 4.  Implementation of App-Based Diabetes Medication Management: Outpatient and Perioperative Clinical Decision Support.

Authors:  Jeehoon Jang; Ashley A Colletti; Colbey Ricklefs; Holly J Snyder; Kimberly Kardonsky; Elizabeth W Duggan; Guillermo E Umpierrez; Vikas N O'Reilly-Shah
Journal:  Curr Diab Rep       Date:  2021-12-13       Impact factor: 5.430

5.  Special Commentary: Using Clinical Decision Support Systems to Bring Predictive Models to the Glaucoma Clinic.

Authors:  Brian C Stagg; Joshua D Stein; Felipe A Medeiros; Barbara Wirostko; Alan Crandall; M Elizabeth Hartnett; Mollie Cummins; Alan Morris; Rachel Hess; Kensaku Kawamoto
Journal:  Ophthalmol Glaucoma       Date:  2020-08-15

6.  Developing an Ophthalmology Clinical Decision Support System to Identify Patients for Low Vision Rehabilitation.

Authors:  Xinxing Guo; Bonnielin K Swenor; Kerry Smith; Michael V Boland; Judith E Goldstein
Journal:  Transl Vis Sci Technol       Date:  2021-03-01       Impact factor: 3.283

7.  Multicomponent intervention to improve blood pressure management in chronic kidney disease: a protocol for a pragmatic clinical trial.

Authors:  John L Kilgallon; Michael Gannon; Zoe Burns; Gearoid McMahon; Patricia Dykes; Jeffrey Linder; David Westfall Bates; Sushrut Waikar; Stuart Lipsitz; Heather J Baer; Lipika Samal
Journal:  BMJ Open       Date:  2021-12-22       Impact factor: 3.006

8.  Effects of computerised clinical decision support systems (CDSS) on nursing and allied health professional performance and patient outcomes: a systematic review of experimental and observational studies.

Authors:  Teumzghi F Mebrahtu; Sarah Skyrme; Rebecca Randell; Anne-Maree Keenan; Karen Bloor; Huiqin Yang; Deirdre Andre; Alison Ledward; Henry King; Carl Thompson
Journal:  BMJ Open       Date:  2021-12-15       Impact factor: 2.692

9.  Factors associated with smoking cessation attempts in a public, safety-net primary care system.

Authors:  Leslie W Suen; Henry Rafferty; Thao Le; Kara Chung; Elana Straus; Ellen Chen; Maya Vijayaraghavan
Journal:  Prev Med Rep       Date:  2022-01-19

10.  Establishing a multidisciplinary initiative for interoperable electronic health record innovations at an academic medical center.

Authors:  Kensaku Kawamoto; Polina V Kukhareva; Charlene Weir; Michael C Flynn; Claude J Nanjo; Douglas K Martin; Phillip B Warner; David E Shields; Salvador Rodriguez-Loya; Richard L Bradshaw; Ryan C Cornia; Thomas J Reese; Heidi S Kramer; Teresa Taft; Rebecca L Curran; Keaton L Morgan; Damian Borbolla; Maia Hightower; William J Turnbull; Michael B Strong; Wendy W Chapman; Travis Gregory; Carole H Stipelman; Julie H Shakib; Rachel Hess; Jonathan P Boltax; Joseph P Habboushe; Farrant Sakaguchi; Kyle M Turner; Scott P Narus; Shinji Tarumi; Wataru Takeuchi; Hideyuki Ban; David W Wetter; Cho Lam; Tanner J Caverly; Angela Fagerlin; Chuck Norlin; Daniel C Malone; Kimberly A Kaphingst; Wendy K Kohlmann; Benjamin S Brooke; Guilherme Del Fiol
Journal:  JAMIA Open       Date:  2021-07-31
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