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deBoisblanc, Bennett P.

Mayo Clinic

Louisiana State University Health Sciences Center New Orleans

Citations 3

Computer clinical decision support that automates personalized clinical care: a challenging but needed healthcare delivery strategy
Morris, Alan H. , Horvat, Christopher M. , Grainger, David W. , Orme, James F., Clemmer, Terry P., Weaver, Lindell K., Thomas, Frank O, Grissom, Colin K. , Hirshberg, Ellie , East, Thomas D. , Wallace, C. Jane, Young, Michael , Sittig, Dean F. , Pearl, James E., Pesenti, Antinio, Bombino, Michela, Beck, Eduardo, Sward, Katherine , Phansalkar, Shobha, Bernard, Gordon R. , Brower, Roy G., Truwit, Jonathon D. , Steingrub, Jay S. , Hiten, R Duncan, Willson, Douglas F., Randolph, Adrienne G. , Curley, Martha A. Q. , Newth, Christopher J. L. , Lacroix, Jacques, Agus, Michael S. D. , Lee, Kang Hoe, deBoisblanc, Bennett P., Moore, Frederick A. , Evans, R. Scott, Sorenson, Dean, Wong, Anthony, Boland, Michael V. , Dere, W. , Crandall, Alan S. , Huff, Stanley M. , Haug, Peter J. , Pielmeier, Ulrike , Rees, Stephen Edward , Karbing, Dan Stieper , Berger, Kenneth I. , Oppenheimer, Beno W. , Pickering, Brian W. , Schoenfeld, David , Tocino, Irena , Savitz, Lucy A., Dreyfuss, Didier, Slutsky, Arthur S. , Crapo, James D. , Pinsky, Michael R. , James, Brent C., Berwick, Donald M. , Sittig, Dean F , Sward, Katherine A , Weir, Charlene , Huff, Stanley M , Gonnering, Russell S , Randolph, Adrienne G , Stagg, Brian C. , Lanspa, Michael J. , Suchyta, Mary R. , Thompson, Bruce , Zimmerman, Jerry J. , Nadkarni, Vinay , Facelli, Julio Cesar , Andreassen, Steen , Fan, Eddy , Goldring, Roberta M. , Ely, Eugene Wesley , Pronovost, Peter J.

Journal of the American Medical Informatics Association | September 20, 2022 | Volume: 30 | Issue: 1 | Pages: 178-194

10.1093/jamia/ocac143 Get It

AbstractHow to deliver best care in various clinical settings remains a vexing problem. All pertinent healthcare-related questions have not, cannot, and will not be addressable with costly time- and resource-consuming controlled clinical trials. At present, evidence-based guidelines can address only a small fraction of the types of care that clinicians deliver. Furthermore, underserved areas rarely can access state-of-the-art evidence-based guidelines in real-time, and often lack the wherewithal to implement advanced guidelines. Care providers in such settings frequently do not have sufficient training to undertake advanced guideline implementation. Nevertheless, in advanced modern healthcare delivery environments, use of eActions (validated clinical decision support systems) could help overcome the cognitive limitations of overburdened clinicians. Widespread use of eActions will require surmounting current healthcare technical and cultural barriers and installing clinical evidence/data curation systems. The authors expect that increased numbers of evidence-based guidelines will result from future comparative effectiveness clinical research carried out during routine healthcare delivery within learning healthcare systems.
Enabling a learning healthcare system with automated computer protocols that produce replicable and personalized clinician actions
Morris, Alan H. , Orme, James F., Clemmer, Terry P., Weaver, Lindell K., Thomas, Frank, Grissom, Colin K. , Hirshberg, Ellie , East, Thomas D. , Wallace, C. Jane, Young, Michael , Sittig, Dean F. , Bombino, Michela, Beck, Eduardo, Sward, Katherine , Phansalkar, Shobha, Bernard, Gordon R. , Brower, Roy G., Truwit, Jonathon D. , Steingrub, Jay, Willson, Douglas F., Randolph, Adrienne G. , Curley, Martha A. Q. , Newth, Christopher J. L. , Lacroix, Jacques, Agus, Michael S. D. , Lee, Kang H., deBoisblanc, Bennett P., Evans, R. Scott, Sorenson, Dean, Wong, Anthony, Boland, Michael V. , Grainger, David W. , Dere, W. , Crandall, Alan S. , Huff, Stanley M. , Haug, Peter J. , Pielmeier, Ulrike , Rees, Stephen Edward , Karbing, Dan Stieper , Goldring, Roberta M. , Berger, Kenneth I. , Oppenheimer, Beno W. , Pickering, Brian W. , Schoenfeld, David , Tocino, Irena , Savitz, Lucy A., Dreyfuss, Didier, Slutsky, Arthur S. , Crapo, James D. , Pinsky, Michael R. , James, Brent C., Berwick, Donald M. , Sittig, Dean F , Weir, Charlene , Randolph, Adrienne G , Sward, Katherine A , Stagg, Brian C. , Lanspa, Michael J. , Pesenti, Antonio Maria , Thompson, Bruce , Hite, R. Duncan , Zimmerman, Jerry J. , Nadkarni, Vinay , Facelli, Julio Cesar , Andreassen, Steen , Fan, Eddy , Ely, Eugene Wesley , Gajic, Ognjen , Gonnering, Russell S , Pronovost, Peter J. , Angus, Derek C.

Journal of the American Medical Informatics Association | November 11, 2020 | Volume: 28 | Issue: 6 | Pages: 1330-1344

10.1093/jamia/ocaa294 Get It

AbstractClinical decision-making is based on knowledge, expertise, and authority, with clinicians approving almost every intervention—the starting point for delivery of “All the right care, but only the right care,” an unachieved healthcare quality improvement goal. Unaided clinicians suffer from human cognitive limitations and biases when decisions are based only on their training, expertise, and experience. Electronic health records (EHRs) could improve healthcare with robust decision-support tools that reduce unwarranted variation of clinician decisions and actions. Current EHRs, focused on results review, documentation, and accounting, are awkward, time-consuming, and contribute to clinician stress and burnout. Decision-support tools could reduce clinician burden and enable replicable clinician decisions and actions that personalize patient care. Most current clinical decision-support tools or aids lack detail and neither reduce burden nor enable replicable actions. Clinicians must provide subjective interpretation and missing logic, thus introducing personal biases and mindless, unwarranted, variation from evidence-based practice. Replicability occurs when different clinicians, with the same patient information and context, come to the same decision and action. We propose a feasible subset of therapeutic decision-support tools based on credible clinical outcome evidence: computer protocols leading to replicable clinician actions (eActions). eActions enable different clinicians to make consistent decisions and actions when faced with the same patient input data. eActions embrace good everyday decision-making informed by evidence, experience, EHR data, and individual patient status. eActions can reduce unwarranted variation, increase quality of clinical care and research, reduce EHR noise, and could enable a learning healthcare system.
Recommendations for the clinical management of patients receiving macitentan for pulmonary arterial hypertension (PAH): A Delphi consensus document
Rahaghi, Franck , Alnuaimat, Hassan, Awdish, Rana , Balasubramanian, Vijay , Bourge, Robert C. , Butler, John, Cauthen, C. Gregory, Chakinala, Murali M. , deBoisblanc, Bennett P., Eggert, Michael, Engel, Peter A., Feldman, Jeremy, McConnell, J.W. , Park, Myung, Sager, Jeffrey S., Sood, Namita , Palevsky, Harold I. , Burger, Charles D.

Pulmonary Circulation | July 17, 2017 | Volume: 7 | Issue: 3 | Pages: 702-711

10.1177/2045893217721695 Get It

In patients treated with macitentan (Opsumit®, Actelion Pharmaceuticals Ltd., Basel, Switzerland) for pulmonary arterial hypertension (PAH), prevention and/or effective management of treatment‐related adverse events may improve adherence. However, management of these adverse events can be challenging and the base of evidence and clinical experience for macitentan is limited. In the absence of evidence, consensus recommendations from physicians experienced in using macitentan to treat PAH may benefit patients and physicians who are using macitentan. Consensus recommendations were developed by a panel of physicians experienced with macitentan and PAH using a modified Delphi process. Over three iterations, panelists developed and refined a series of statements on the use of macitentan in PAH and rated their agreement with each statement on a Likert scale. The panel of 18 physicians participated and developed a total of 118 statements on special populations, add‐on therapy, drug–drug interactions, warnings and precautions, hospitalization and functional class, and adverse event management. The resulting consensus recommendations are intended to provide practical guidance on real‐world issues in using macitentan to treat patients with PAH.