Brent C. James

All Publications

• Toward a National Health Digital and Data Architecture: Laying the Foundation for Digital Transformation: Commission on Investment Imperatives for a Healthy Nation. NAM perspectives Abernethy, A., Afsar, N., Anderson, B., Barfield, W., Bharel, M., Brown, J., Embi, P., Eschenlauer, A., Gordon, W., Gregurick, S., James, B., Jena, A., Lee, P., Maddox, T., Mandl, K., Parikh, R., Petersen-Lukenda, L., Sarich, T., Shaikh, A., Speyer, P., Yale, K. 2026; 2026

  View details for DOI 10.31478/202603b

  View details for PubMedID 42169969

• We Count Our Successes in Lives JOINT COMMISSION JOURNAL ON QUALITY AND PATIENT SAFETY James, B. C. 2025; 51 (2): 83-85

  View details for DOI 10.1016/j.jcjq.2024.12.006

  View details for Web of Science ID 001410744700001

  View details for PubMedID 39799067

• The Wasteful Neurosurgeon? World neurosurgery Sivaganesan, A., Sarikonda, A., Leibold, A., Harrop, J., Vaccaro, A. R., James, B. C. 2024

  View details for DOI 10.1016/j.wneu.2024.04.105

  View details for PubMedID 38749823

• Computer clinical decision support that automates personalized clinical care: a challenging but needed healthcare delivery strategy. Journal of the American Medical Informatics Association : JAMIA Morris, A. H., Horvat, C., Stagg, B., Grainger, D. W., Lanspa, M., Orme, J., Clemmer, T. P., Weaver, L. K., Thomas, F. O., Grissom, C. K., Hirshberg, E., East, T. D., Wallace, C. J., Young, M. P., Sittig, D. F., Suchyta, M., Pearl, J. E., Pesenti, A., Bombino, M., Beck, E., Sward, K. A., Weir, C., Phansalkar, S., Bernard, G. R., Thompson, B. T., Brower, R., Truwit, J., Steingrub, J., Hiten, R. D., Willson, D. F., Zimmerman, J. J., Nadkarni, V., Randolph, A. G., Curley, M. A., Newth, C. J., Lacroix, J., Agus, M. S., Lee, K. H., deBoisblanc, B. P., Moore, F. A., Evans, R. S., Sorenson, D. K., Wong, A., Boland, M. V., Dere, W. H., Crandall, A., Facelli, J., Huff, S. M., Haug, P. J., Pielmeier, U., Rees, S. E., Karbing, D. S., Andreassen, S., Fan, E., Goldring, R. M., Berger, K. I., Oppenheimer, B. W., Ely, E. W., Pickering, B. W., Schoenfeld, D. A., Tocino, I., Gonnering, R. S., Pronovost, P. J., Savitz, L. A., Dreyfuss, D., Slutsky, A. S., Crapo, J. D., Pinsky, M. R., James, B., Berwick, D. M. 2022

  Abstract

  How 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.

  View details for DOI 10.1093/jamia/ocac143

  View details for PubMedID 36125018

• Enabling a learning healthcare system with automated computer protocols that produce replicable and personalized clinician actions. Journal of the American Medical Informatics Association : JAMIA Morris, A. H., Stagg, B., Lanspa, M., Orme, J., Clemmer, T. P., Weaver, L. K., Thomas, F., Grissom, C. K., Hirshberg, E., East, T. D., Wallace, C. J., Young, M. P., Sittig, D. F., Pesenti, A., Bombino, M., Beck, E., Sward, K. A., Weir, C., Phansalkar, S. S., Bernard, G. R., Taylor Thompson, B., Brower, R., Truwit, J. D., Steingrub, J., Duncan Hite, R., Willson, D. F., Zimmerman, J. J., Nadkarni, V. M., Randolph, A., Curley, M. A., Newth, C. J., Lacroix, J., Agus, M. S., Lee, K. H., deBoisblanc, B. P., Scott Evans, R., Sorenson, D. K., Wong, A., Boland, M. V., Grainger, D. W., Dere, W. H., Crandall, A. S., Facelli, J. C., Huff, S. M., Haug, P. J., Pielmeier, U., Rees, S. E., Karbing, D. S., Andreassen, S., Fan, E., Goldring, R. M., Berger, K. I., Oppenheimer, B. W., Wesley Ely, E., Gajic, O., Pickering, B., Schoenfeld, D. A., Tocino, I., Gonnering, R. S., Pronovost, P. J., Savitz, L. A., Dreyfuss, D., Slutsky, A. S., Crapo, J. D., Angus, D., Pinsky, M. R., James, B., Berwick, D. 2021

  Abstract

  Clinical 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.

  View details for DOI 10.1093/jamia/ocaa294

  View details for PubMedID 33594410

• An Interview with Brent C. James JOINT COMMISSION JOURNAL ON QUALITY AND PATIENT SAFETY Savitz, L. A., James, B. C. 2019; 45 (7): 461–65

  View details for DOI 10.1016/j.jcjq.2019.04.002

  View details for Web of Science ID 000474294100001

  View details for PubMedID 31242964

• To Cut is to Cure The Surgeon's Role in Improving Value ANNALS OF SURGERY Jopling, J. K., Sheckter, C. C., James, B. C. 2018; 267 (5): 817–19

  View details for PubMedID 29189380

• The Case for Capitation It's the only way to cut waste while improving quality HARVARD BUSINESS REVIEW James, B. C., Poulsen, G. P. 2016; 94 (7-8): 103-111

  View details for Web of Science ID 000378580700022