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Lawrence, Katharine

https://orcid.org/0000-0001-5640-2138

Mayo Clinic

New York University

Citations 2

Palliative Care Initiated in the Emergency Department
Siman, Nina , Adeyemi, Oluwaseun , Yamarik, Rebecca , Investigators, PRIM-ER, Bellolio, Fernanda , Bourenane, Sorayah, Brody, Abraham A. , Cameron, Lauren , Cooper, Julie J. , Deutsch, Ashley, Elsayem, Ahmed , Fleischer-Black, Jessica, Gang, Mauren, Goett, Rebecca , Heaton, Heather A. , Hill, Jacob , Isaacs, Eric, Jubanyik, Karen , Lamba, Sangeeta , Lin, Michelle , Loprinzi-Brauer, Caitlin , Madsen, Troy , Modrek, Ada, Otero, Ronny, Ouchi, Kei , Richardson, Christopher , Richardson, Lynne D. , Schoenfeld, Elizabeth , Shreves, Ashley, Tan, Audrey , Uspal, Julie, Venkat, Arvind , Walker, Laura , Wittman, Ian, Zimny, Erin, Miller, Joseph , Heaton, Heather, Bellolio, M Fernanda , Schoenfeld, Elizabeth M , Grudzen, Corita R. , Cuthel, Allison M. , Goldfeld, Keith S. , Investigators, PRIM-ER, Abella, Benjamin S. , Chodosh, Joshua , Elie, Marie‐Carmelle , Fernandez, Rosemarie , Gang, Mauren, Genes, Nicholas , Horwitz, Leora Idit , Lawrence, Katharine , Miller, Joseph S. A. , Ryan, Matthew, Shaw, Matthew, Southerland, Lauren T.

JAMA | January 15, 2025 | Volume: 333 | Issue: 7 | Pages: 599

10.1001/jama.2024.23696 Get It

Importance The emergency department (ED) offers an opportunity to initiate palliative care for older adults with serious, life-limiting illness. Objective To assess the effect of a multicomponent intervention to initiate palliative care in the ED on hospital admission, subsequent health care use, and survival in older adults with serious, life-limiting illness. Design, Setting, and Participants Cluster randomized, stepped-wedge, clinical trial including patients aged 66 years or older who visited 1 of 29 EDs across the US between May 1, 2018, and December 31, 2022, had 12 months of prior Medicare enrollment, and a Gagne comorbidity score greater than 6, representing a risk of short-term mortality greater than 30%. Nursing home patients were excluded. Intervention A multicomponent intervention (the Primary Palliative Care for Emergency Medicine intervention) included (1) evidence-based multidisciplinary education; (2) simulation-based workshops on serious illness communication; (3) clinical decision support; and (4) audit and feedback for ED clinical staff. Main Outcome and Measures The primary outcome was hospital admission. The secondary outcomes included subsequent health care use and survival at 6 months. Results There were 98 922 initial ED visits during the study period (median age, 77 years [IQR, 71-84 years]; 50% were female; 13% were Black and 78% were White; and the median Gagne comorbidity score was 8 [IQR, 7-10]). The rate of hospital admission was 64.4% during the preintervention period vs 61.3% during the postintervention period (absolute difference, −3.1% [95% CI, −3.7% to −2.5%]; adjusted odds ratio [OR], 1.03 [95% CI, 0.93 to 1.14]). There was no difference in the secondary outcomes before vs after the intervention. The rate of admission to an intensive care unit was 7.8% during the preintervention period vs 6.7% during the postintervention period (adjusted OR, 0.98 [95% CI, 0.83 to 1.15]). The rate of at least 1 revisit to the ED was 34.2% during the preintervention period vs 32.2% during the postintervention period (adjusted OR, 1.00 [95% CI, 0.91 to 1.09]). The rate of hospice use was 17.7% during the preintervention period vs 17.2% during the postintervention period (adjusted OR, 1.04 [95% CI, 0.93 to 1.16]). The rate of home health use was 42.0% during the preintervention period vs 38.1% during the postintervention period (adjusted OR, 1.01 [95% CI, 0.92 to 1.10]). The rate of at least 1 hospital readmission was 41.0% during the preintervention period vs 36.6% during the postintervention period (adjusted OR, 1.01 [95% CI, 0.92 to 1.10]). The rate of death was 28.1% during the preintervention period vs 28.7% during the postintervention period (adjusted OR, 1.07 [95% CI, 0.98 to 1.18]). Conclusions and Relevance This multicomponent intervention to initiate palliative care in the ED did not have an effect on hospital admission, subsequent health care use, or short-term mortality in older adults with serious, life-limiting illness. Trial Registration ClinicalTrials.gov Identifier: NCT03424109
Potential bias and lack of generalizability in electronic health record data: reflections on health equity from the National Institutes of Health Pragmatic Trials Collaboratory
Boyd, Andrew D. , Lawrence, Katharine , Patil, Crystal L. , Ezenwa, Miriam O. , O’Brien, Emily C. , Paek, Hyung , Adeyemi, Oluwaseun , Cuthel, Allison M. , Darby, Juanita E. , Zigler, Christina K. , Faurot, Keturah R, Staman, Karen L. , Dailey, Dana L. , Fiol, Guilherme Del , Knisely, Mitchell R. , Marsolo, Keith , Richesson, Rachel , Faurot, Keturah R. , Lawrence, Katharine , O'Brien, Emily , Cuthel, Allison M , Darby, Juanita E , Del Fiol, Guilherme , Richesson, Rachel L , Boyd, Andrew D , Faurot, Keturah R , Gonzalez-Guarda, Rosa Maria , Braciszewski, Jordan M. , Ho, P. Michael , Leigh, Jonathan W. , Cheville, Andrea , Grudzen, Corita R. , Schlaeger, Judith M.

Journal of the American Medical Informatics Association | June 15, 2023 | Volume: 30 | Issue: 9 | Pages: 1561-1566

10.1093/jamia/ocad115 Get It

Abstract Embedded pragmatic clinical trials (ePCTs) play a vital role in addressing current population health problems, and their use of electronic health record (EHR) systems promises efficiencies that will increase the speed and volume of relevant and generalizable research. However, as the number of ePCTs using EHR-derived data grows, so does the risk that research will become more vulnerable to biases due to differences in data capture and access to care for different subsets of the population, thereby propagating inequities in health and the healthcare system. We identify 3 challenges—incomplete and variable capture of data on social determinants of health, lack of representation of vulnerable populations that do not access or receive treatment, and data loss due to variable use of technology—that exacerbate bias when working with EHR data and offer recommendations and examples of ways to actively mitigate bias.