Winifred Teuteberg

All Publications

• Electronic Health Record Serious Illness Conversation Dashboards: An Implementation Case Series. Journal of pain and symptom management Hachem, Y., Lakin, J., Teuteberg, W., Cullinan, A., Gonzales, M. J., Lindvall, C., Kumar, P., Dingfield, L., Kilpatrick, L., Greenwald, J., Miller, A., Keeney, T., Fromme, E. K., Paladino, J. 2024

  Abstract

  INTRODUCTION: Dashboards are used to track and visualize quality indicators within health systems to improve clinical performance. Structured serious illness conversation (SIC) documentation templates within electronic health records (EHR) have enabled the development of SIC dashboards for quality improvement. Little is known about the successes and challenges of SIC dashboards.METHODS: This implementation case series describes findings from semi-structured interviews and surveys with nine palliative care leaders in eight health systems that implemented SIC dashboards. Interviews and case information were analyzed to identify themes.RESULTS: Five themes were identified. First, dashboards focus on process metrics. By creating transparent and efficient access to data on EHR-documented SICs, dashboards facilitated monitoring of the results of clinician training and quality improvement efforts. Second, palliative care leaders used dashboard data on documented SICs to implement clinician practice change strategies (e.g. data feedback; quality incentives), but clinicians had mixed reactions to data. Third, dashboards facilitated leadership investment in SIC efforts and required financial and technical resources to build and maintain. Fourth, while dashboards streamlined data collection for implementation teams, participants noted challenges with data reliability, including inadequate clinician use of structured SIC documentation templates (which most dashboards rely on for measurement). Fifth, needs and tensions arose with integrating patient-centered outcome measures as part of dashboards.CONCLUSION: Dashboards can be powerful tools for identifying gaps in SIC and driving interventions for clinician practice change. However, challenges related to clinician adoption of structured templates for SIC documentation and mixed clinician receptivity to data feedback may limit their reliability and use.

  View details for DOI 10.1016/j.jpainsymman.2024.10.032

  View details for PubMedID 39510421

• Automated patient selection and care coaches to increase advance care planning for cancer patients. Journal of the National Cancer Institute Gensheimer, M. F., Teuteberg, W., Patel, M. I., Gupta, D., Noroozi, M., Ling, X., Fardeen, T., Seevaratnam, B., Lu, Y., Alves, N., Rogers, B., Asuncion, M. K., Denofrio, J., Hansen, J., Shah, N. H., Chen, T., Cabebe, E., Blayney, D. W., Colevas, A. D., Ramchandran, K. 2024

  Abstract

  Advance care planning/serious illness conversations can help clinicians understand patients' values and preferences. There are limited data on how to increase these conversations, and their effect on care patterns. We hypothesized that using a machine learning survival model to select patients for serious illness conversations, along with trained care coaches to conduct the conversations, would increase uptake in cancer patients at high risk of short-term mortality.We conducted a cluster-randomized stepped wedge study on the physician level. Oncologists entered the intervention condition in a random order over six months. Adult patients with metastatic cancer were included. Patients with <2 year computer-predicted survival and no prognosis documentation were classified as high-priority for serious illness conversations. In the intervention condition, providers received automated weekly emails highlighting high-priority patients and were asked to document prognosis for them. Care coaches reached out to these patients to conduct the remainder of the conversation. The primary endpoint was proportion of visits with prognosis documentation within 14 days.6,372 visits in 1,825 patients were included in the primary analysis. The proportion of visits with prognosis documentation within 14 days was higher in the intervention condition than control condition: 2.9% vs 1.1% (adjusted odds ratio 4.3, p < .0001). The proportion of visits with advance care planning documentation was also higher in the intervention condition: 7.7% vs 1.8% (adjusted odds ratio 14.2, p < .0001). In high-priority visits, advance care planning documentation rate in intervention/control visits was 24.2% vs 4.0%.The intervention increased documented conversations, with contributions by both providers and care coaches.

  View details for DOI 10.1093/jnci/djae243

  View details for PubMedID 39348179

• Coaches Activating, Reaching, and Engaging Patients to Engage in Advance Care Planning: A Randomized Clinical Trial. JAMA oncology Rodriguez, G. M., Parikh, D. A., Kapphahn, K., Gupta, D. M., Fan, A. C., Shah, S., Srinivas, S., Teuteberg, W., Seevaratnam, B., Asuncion, K., Chien, J., Moore, K., Ruiz, S. M., Patel, M. I. 2024

  Abstract

  Importance: Advance care planning (ACP) remains low among patients with advanced cancer. Multilevel interventions compared with clinician-level interventions may be more effective in improving ACP.Objective: To evaluate whether a multilevel intervention could improve clinician-documented ACP compared with a clinician-level intervention alone.Design, Setting, and Participants: This randomized clinical trial, performed from September 12, 2019, through May 12, 2021, included adults with advanced genitourinary cancers at an academic, tertiary hospital. Data analysis was performed by intention to treat from May 1 to August 10, 2023.Intervention: Participants were randomized 1:1 to a 6-month patient-level lay health worker structured ACP education along with a clinician-level intervention composed of 3-hour ACP training and integration of a structured electronic health record documentation template (intervention group) or to the clinician-level intervention alone (control group).Main Outcome and Measures: The primary outcome was ACP documentation in the electronic health record by the oncology clinician within 12 months after randomization. Secondary, exploratory outcomes included shared decision-making, palliative care use, hospice use, emergency department visits, and hospitalizations within 12 months after randomization.Results: Among 402 participants enrolled in the study, median age was 71 years (range, 21-102 years); 361 (89.8%) identified as male. More intervention group participants had oncology clinician-documented ACP than control group participants (82 [37.8%] vs 40 [21.6%]; odds ratio [OR], 2.29; 95% CI, 1.44-3.64). At 12-month follow-up, more intervention than control group participants had palliative care (72 [33.2%] vs 25 [13.5%]; OR, 3.18; 95% CI, 1.91-5.28) and hospice use (49 [22.6%] vs 19 [10.3%]; OR, 2.54; 95% CI, 1.44-4.51). There were no differences in the proportion of participants between groups with an emergency department visit (65 [30.0%] vs 61 [33.0%]; OR, 0.87; 95% CI, 0.57-1.33) or hospitalization (89 [41.0%] vs 85 [46.0%]; OR, 0.82; 95% CI, 0.55-1.22). Intervention group participants had fewer hospitalizations than control group participants (mean [SD] number of hospitalizations per year, 0.87 [1.60] vs 1.04 [1.77]) and a lower risk of hospitalization (incidence rate ratio, 0.80; 95% CI, 0.65-0.98).Conclusions and Relevance: In this randomized clinical trial, a multilevel intervention improved oncology clinician-documented ACP compared with a clinician-level intervention alone for patients with genitourinary cancer. The intervention is one approach to effectively increase ACP among patients with cancer.Trial Registration: ClinicalTrials.gov Identifier: NCT03856463.

  View details for DOI 10.1001/jamaoncol.2024.1242

  View details for PubMedID 38780960

• Lessons Learned from a Multi-Site, Team-Based Serious Illness Care Program Implementation at an Academic Medical Center. Journal of palliative medicine Seevaratnam, B., Wang, S., Fong, R., Hui, F., Callahan, A., Chobot, S., Gensheimer, M. F., Li, R. C., Nguyen, D., Ramchandran, K., Shah, N. H., Shieh, L., Zeng, J. G., Teuteberg, W. 2023

  Abstract

  Background: Patients with serious illness benefit from conversations to share prognosis and explore goals and values. To address this, we implemented Ariadne Labs' Serious Illness Care Program (SICP) at Stanford Health Care. Objective: Improve quantity, timing, and quality of serious illness conversations. Methods: Initial implementation followed Ariadne Labs' SICP framework. We later incorporated a team-based approach that included nonphysician care team members. Outcomes included number of patients with documented conversations according to clinician role and practice location. Machine learning algorithms were used in some settings to identify eligible patients. Results: Ambulatory oncology and hospital medicine were our largest implementation sites, engaging 4707 and 642 unique patients in conversations, respectively. Clinicians across eight disciplines engaged in these conversations. Identified barriers that included leadership engagement, complex workflows, and patient identification. Conclusion: Several factors contributed to successful SICP implementation across clinical sites: innovative clinical workflows, machine learning based predictive algorithms, and nonphysician care team member engagement.

  View details for DOI 10.1089/jpm.2023.0254

  View details for PubMedID 37935036

• Lessons Learned About System-Level Improvement in Serious Illness Communication: A Qualitative Study of Serious Illness Care Program Implementation in Five Health Systems JOINT COMMISSION JOURNAL ON QUALITY AND PATIENT SAFETY Paladino, J., Fromme, E. K., Kilpatrick, L., Dingfield, L., Teuteberg, W., Bernacki, R., Jackson, V., Sanders, J. J., Jacobsen, J., Ritchie, C., Mitchell, S. 2023; 49 (11): 620-633

  Abstract

  Serious illness communication is a key element of high-quality care, but it is difficult to implement in practice. The Serious Illness Care Program (SICP) is a multifaceted intervention that contributes to more, earlier, and better serious illness conversations and improved patient outcomes. This qualitative study examined the organizational and implementation factors that influenced improvement in real-world contexts.The authors performed semistructured interviews of 30 health professionals at five health systems that adopted SICP as quality improvement initiatives to investigate the organizational and implementation factors that appeared to influence improvement.After SICP implementation across the organizations studied, approximately 4,661 clinicians have been trained in serious illness communication and 56,712 patients had had an electronic health record (EHR)-documented serious illness conversation. Facilitators included (1) visible support from leaders, who financially invested in an implementation team and champions, expressed the importance of serious illness communication as an institutional priority, and created incentives for training and documenting serious illness conversations; (2) EHR and data infrastructure to foster performance improvement and accountability, including an accessible documentation template, a reporting system, and customized data feedback for clinicians; and (3) communication skills training and sustained support for clinicians to problem-solve communication challenges, reflect on communication experiences, and adapt the intervention. Inhibitors included leadership inaction, competing priorities and incentives, variable clinician acceptance of EHR and data tools, and inadequate support for clinicians after training.Successful implementation appeared to rely on multilevel organizational strategies to prioritize, reward, and reinforce serious illness communication. The insights derived from this research may function as an organizational road map to guide implementation of SICP or related quality initiatives.

  View details for DOI 10.1016/j.jcjq.2023.06.013

  View details for Web of Science ID 001150127400001

  View details for PubMedID 37537096

• Implementing an Interdisciplinary Team-Based Serious Illness Care Program (SICP) in Stanford Healthcare Giannitrapani, K., Garcia, R., Teuteberg, W., Brown-Johnson, C. ELSEVIER SCIENCE INC. 2023: E627-E628

  View details for Web of Science ID 001006227200215

• The Team-based Serious Illness Care Program, a qualitative evaluation of implementation and teaming. Journal of pain and symptom management Garcia, R., Brown-Johnson, C., Teuteberg, W., Seevaratham, B., Giannitrapani, K. 2023

  Abstract

  CONTEXT: Earlier and more frequent serious illness conversations with patients allow clinical teams to better align care with patients' goals and values. Non-physician clinicians often have unique perspectives and understanding of patients' wishes and are thus well-positioned to support conversations with seriously ill patients. The Team-based Serious Illness Care Program (SICP) at Stanford aimed to involve all care team members to support and conduct serious illness conversations with patients and their caregivers and families.OBJECTIVES: We conducted interviews with clinicians to understand how care teams implement team-based approaches to conduct serious illness conversations and navigate resulting team complexity.METHODS: We used a rapid qualitative approach to analyze semi-structured interviews of clinician and administrative stakeholders in two Team-based SICP implementation groups (i.e., inpatient oncology and hospital medicine) (n=25). Analysis was informed by frameworks/theory: cross-disciplinary role agreement, team formation and functioning, and organizational theory.RESULTS: Implementing Team-based SICP was feasible. Theme 1 centered on how teams formed and managed to come to agreement: teams with rapidly changing staffing/responsibilities prioritized communication, whereas teams with consistent staffing/responsibilities primarily relied on protocols. Theme 2 demonstrated that leaders and managers at multiple levels could support implementation. Theme 3 explored strengths and opportunities. Positively, Team-based SICP distributed work burden, timed conversations in alignment with patient needs, and added unique value from non-physician team members. Role ambiguity and conflict were attributed to miscommunication and ethical conflicts.CONCLUSION: Team-based serious illness communication is viable and valuable, with a range of successful workflow and leadership approaches.

  View details for DOI 10.1016/j.jpainsymman.2023.01.024

  View details for PubMedID 36764413

• Use of Machine Learning and Lay Care Coaches to Increase Advance Care Planning Conversations for Patients With Metastatic Cancer. JCO oncology practice Gensheimer, M. F., Gupta, D., Patel, M. I., Fardeen, T., Hildebrand, R., Teuteberg, W., Seevaratnam, B., Asuncion, M. K., Alves, N., Rogers, B., Hansen, J., DeNofrio, J., Shah, N. H., Parikh, D., Neal, J., Fan, A. C., Moore, K., Ruiz, S., Li, C., Khaki, A. R., Pagtama, J., Chien, J., Brown, T., Tisch, A. H., Das, M., Srinivas, S., Roy, M., Wakelee, H., Myall, N. J., Huang, J., Shah, S., Lee, H., Ramchandran, K. 2022: OP2200128

  Abstract

  Patients with metastatic cancer benefit from advance care planning (ACP) conversations. We aimed to improve ACP using a computer model to select high-risk patients, with shorter predicted survival, for conversations with providers and lay care coaches. Outcomes included ACP documentation frequency and end-of-life quality measures.In this study of a quality improvement initiative, providers in four medical oncology clinics received Serious Illness Care Program training. Two clinics (thoracic/genitourinary) participated in an intervention, and two (cutaneous/sarcoma) served as controls. ACP conversations were documented in a centralized form in the electronic medical record. In the intervention, providers and care coaches received weekly e-mails highlighting upcoming clinic patients with < 2 year computer-predicted survival and no prior prognosis documentation. Care coaches contacted these patients for an ACP conversation (excluding prognosis). Providers were asked to discuss and document prognosis.In the four clinics, 4,968 clinic visits by 1,251 patients met inclusion criteria (metastatic cancer with no prognosis previously documented). In their first visit, 28% of patients were high-risk (< 2 year predicted survival). Preintervention, 3% of both intervention and control clinic patients had ACP documentation during a visit. By intervention end (February 2021), 35% of intervention clinic patients had ACP documentation compared with 3% of control clinic patients. Providers' prognosis documentation rate also increased in intervention clinics after the intervention (2%-27% in intervention clinics, P < .0001; 0%-1% in control clinics). End-of-life care intensity was similar in intervention versus control clinics, but patients with ≥ 1 provider ACP edit met fewer high-intensity care measures (P = .04).Combining a computer prognosis model with care coaches increased ACP documentation.

  View details for DOI 10.1200/OP.22.00128

  View details for PubMedID 36395436

• Embedded Specialist Palliative Care in Cystic Fibrosis: Results of a Randomized Feasibility Clinical Trial. Journal of palliative medicine Kavalieratos, D., Lowers, J., Moreines, L. T., Hoydich, Z. P., Arnold, R. M., Yabes, J. G., Richless, C., Ikejiani, D. Z., Teuteberg, W., Pilewski, J. M. 2022

  Abstract

  Background: Cystic fibrosis (CF) is a progressive genetic disease characterized by multisystem symptom burden. Specialist palliative care (PC), as a model of care, has been shown to be effective in improving quality of life and reducing symptom burden in other conditions, but has not been tested in CF. Objectives: To develop and test the feasibility and acceptability of a specialist PC intervention embedded within an outpatient CF clinic. Design: Single-site, equal-allocation randomized pilot study comparing usual care with addition of four protocolized quarterly visits with a PC nurse practitioner. Participants: Adults with CF age ≥18 years with any of the following: FEV1% predicted ≤50, ≥2 CF-related hospitalizations in the past 12 months, supplemental oxygen use, or noninvasive mechanical ventilation use, and moderate-or-greater severity of any symptoms on the Edmonton Symptom Assessment Scale. Measurements: Randomization rate, intervention visit completion, data completements, participant ratings of intervention acceptability and benefit, and intervention delivery fidelity. Results: We randomized 50 adults with CF of 65 approached (77% randomization rate) to intervention (n=25) or usual care (n=25), mean age 38, baseline mean FEV1% predicted 41.8 (usual care), and 41.2 (intervention). No participants withdrew, five were lost to follow-up, and two died (88% retention). In the intervention group, 23 of 25 completed all study visits; 94% stated the intervention was not burdensome, and 97.6% would recommend the intervention to others with CF. More than 90% of study visits addressed topics prescribed by intervention manual. Conclusions: Adding specialist PC to standard clinic visits for adults with CF is feasible and acceptable.

  View details for DOI 10.1089/jpm.2022.0349

  View details for PubMedID 36350712

• Considerations in the reliability and fairness audits of predictive models for advance care planning Frontiers in Digital Health Lu, J., Sattler, A., Wang, S., Khaki, A. R., Callahan, A., Fleming, S., Fong, R., Ehlert, B., Li, R., Shieh, L., Ramchandran, K., Gensheimer, M., Chobot, S., Pfohl, S., Li, S., Shum, K., Parikh, N., Desai, P., Seevaratnam, B., Hanson, M., Smith, M., Xu, Y., Gokhale, A., Lin, S., Shah, N. 2022: 943768

  View details for DOI 10.3389/fdgth.2022.943768

• Use of a computer model and care coaches to increase advance care planning conversations for patients with metastatic cancer Gupta, D., Fardeen, T., Teuteberg, W., Seevaratnam, B., Asuncion, M., Alves, N., Rogers, B., Neal, J. W., Fan, A. C., Parikh, D., Patel, M. I., Shah, S., Srinivas, S., Huang, J. E., Reddy, S. A., Ganjoo, K. N., Bui, N., Hansen, J., Gensheimer, M. F., Ramchandran, K. LIPPINCOTT WILLIAMS & WILKINS. 2021

  View details for DOI 10.1200/JCO.2020.39.28_suppl.8

  View details for Web of Science ID 000707130200008

• Coaches Activating Reaching and Engaging Patients (CAREPlan): A randomized controlled trial combining two evidence-based interventions to improve goals of care documentation Parikh, D., Asuncion, M., Hansen, J., Seevaratnam, B., Khateeb, S., Rosenthal, E., Teuteberg, W., Patel, M. I. LIPPINCOTT WILLIAMS & WILKINS. 2021

  View details for DOI 10.1200/JCO.2020.39.28_suppl.2

  View details for Web of Science ID 000707130200002

• Earlier identification of seriously ill patients: an implementation case series. BMJ supportive & palliative care Lakin, J. R., Desai, M. n., Engelman, K. n., O'Connor, N. n., Teuteberg, W. G., Coackley, A. n., Kilpatrick, L. B., Gawande, A. n., Fromme, E. K. 2019

  Abstract

  To describe the strategies used by a collection of healthcare systems to apply different methods of identifying seriously ill patients for a targeted palliative care intervention to improve communication around goals and values.We present an implementation case series describing the experiences, challenges and best practices in applying patient selection strategies across multiple healthcare systems implementing the Serious Illness Care Program (SICP).Five sites across the USA and England described their individual experiences implementing patient selection as part of the SICP. They employed a combination of clinician screens (such as the 'Surprise Question'), disease-specific criteria, existing registries or algorithms as a starting point. Notably, each describes adaptation and evolution of their patient selection methodology over time, with several sites moving towards using more advanced machine learning-based analytical approaches.Involving clinical and programme staff to choose a simple initial method for patient identification is the ideal starting place for selecting patients for palliative care interventions. However, improving and refining methods over time is important and we need ongoing research into better patient selection methodologies that move beyond mortality prediction and instead focus on identifying seriously ill patients-those with poor quality of life, worsening functional status and medical care that is negatively impacting their families.

  View details for DOI 10.1136/bmjspcare-2019-001789

  View details for PubMedID 31253734

• UTILIZATION OF ELECTRONIC HEALTH RECORD PREFERENCE LISTS TO IMPROVE EFFICIENCY, CONSISTENCY AND SATISFACTION AMONG PROVIDERS IN THE AMBULATORY CARE SETTING Shah, S., Angelo, P., Teuteberg, W. G., Singh, B. SPRINGER. 2018: S837–S838

  View details for Web of Science ID 000442641404248