Use of a Person-Centered Narrative Intervention in an Outpatient Palliative Care Setting: A Feasibility Study.

Person-centered narrative interventions offer potential solutions to facilitate a connection between the person receiving care and the person delivering the care, to improve quality of care, and positively impact a patient's biopsychosocial well-being. This single-arm feasibility study investigates patient-reported outcomes and barriers/facilitators to the implementation of an all-virtually delivered person-centered narrative intervention into the person's electronic health record. Overall, electronic data collection for the patient-reported outcomes was feasible. All 15 participants felt participating in the study was "easy" and "enjoyable," and "not a burden." The facilitators of implementation included: "helpful to the clinician," "appreciated looking at me as whole person," "be seen and heard," "had a connection and trust," and "felt comfortable and relaxing." The barriers to implementation included: "completing all the paperwork," "being rushed for time to complete the PCNI," and some "emotion" during collection of narrative. The use of person-centered narrative interventions is a way to deploy dedicated tools to shift dehumanized healthcare delivery to a more humanized person-centered care that treats people as experts in their own life narratives by incorporating their beliefs, values, and preferences into their plan of care.

Integration of Person-Centered Narratives Into the Electronic Health Record.

BACKGROUND: Care delivery that is not person-centered has been called discordant care . There has been a shift to incorporate more of a person's narrative into their individual healthcare treatment plan to reduce discordant care. Aligning with this shift in healthcare delivery, we developed a person-centered narrative intervention (PCNI) to address existing gaps in delivery of person-centered care. OBJECTIVES: This study aimed to evaluate the feasibility of conducting a randomized study and describe the outcomes of PCNI to usual care on the following person (patient)-reported outcomes: perceptions of the quality of communication with their nurses and their psychosocial and existential well-being. METHODS: This study's design was an Obesity-Related Behavioral Intervention Trials model Phase II proof-of-concept randomized study. The participants were people admitted to an acute care hospital diagnosed with heart failure and/or end-stage renal disease. RESULTS: Despite COVID-19 challenges, the PCNI was feasible in an acute care setting; it showed a moderate positive difference between conditions in the person's perception of their quality of communication and a small positive difference in their perception of feeling heard and understood. For our secondary outcomes of anxiety, depression, and psychosocial illness effect, there were small or no effects in the acute care setting. DISCUSSION: Using a person-centered narrative, such as the PCNI, can help inform delivery of care that incorporates a person's (patient's) beliefs, values, and preferences into their healthcare. This study used a pragmatic approach to evaluate the PCNI in real time in an acute care setting to assess patient-reported outcomes. These positive results in a small sample indicate the need for continued testing of the PCNI. These promising effects require further testing in a Phase III efficacy study within a larger randomized controlled clinical trial.

An Electronically Delivered Person-Centered Narrative Intervention for Persons Receiving Palliative Care: Protocol for a Mixed Methods Study.

BACKGROUND: In the health care setting, electronic health records (EHRs) are one of the primary modes of communication about patients, but most of this information is clinician centered. There is a need to consider the patient as a person and integrate their perspectives into their health record. Incorporating a patient's narrative into the EHR provides an opportunity to communicate patients' cultural values and beliefs to the health care team and has the potential to improve patient-clinician communication. This paper describes the protocol to evaluate the integration of an adapted person-centered narrative intervention (PCNI). This adaptation builds on our previous research centered on the implementation of PCNIs. The adaptation for this study includes an all-electronic delivery of a PCNI in an outpatient clinical setting. OBJECTIVE: This research protocol aims to evaluate the feasibility, usability, and effects of the all-electronic delivery of a PCNI in an outpatient setting on patient-reported outcomes. The first objective of this study is to identify the barriers and facilitators of an internet-based-delivered PCNI from the perspectives of persons living with serious illness and their clinicians. The second objective is to conduct acceptability, usability, and intervention fidelity testing to determine the essential requirements for the EHR integration of an internet-based-delivered PCNI. The third objective is to test the feasibility of the PCNI in an outpatient clinic setting. METHODS: Using a mixed method design, this single-arm intervention feasibility study was delivered over approximately 3 to 4 weeks. Patient participant recruitment was conducted via screening outpatient palliative care clinic schedules weekly for upcoming new palliative care patient visits and then emailing potential patient participants to notify them about the study. The PCNI was delivered via email and Zoom app. Patient-reported outcome measures were completed by patient participants at baseline, 24 to 48 hours after PCNI, and after the initial palliative care clinic visit, approximately 1 month after baseline. Inclusion criteria included having the capacity to give consent and having an upcoming initial outpatient palliative care clinic visit. RESULTS: The recruitment of participants began in April 2021. A total of 189 potential patient participants were approached via email, and 20 patient participants were enrolled, with data having been collected from May 2021 to September 2022. A total of 7 clinician participants were enrolled, with a total of 3 clinician exit interviews and 1 focus group (n=5), which was conducted in October 2022. Data analysis is expected to be completed by the end of June 2023. CONCLUSIONS: The findings from this study, combined with those from other PCNI studies conducted in acute care settings, have the potential to influence clinical practices and policies and provide innovative avenues to integrate more person-centered care delivery. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/41787.

Real-time electronic health record mortality prediction during the COVID-19 pandemic: a prospective cohort study.

OBJECTIVE: To rapidly develop, validate, and implement a novel real-time mortality score for the COVID-19 pandemic that improves upon sequential organ failure assessment (SOFA) for decision support for a Crisis Standards of Care team. MATERIALS AND METHODS: We developed, verified, and deployed a stacked generalization model to predict mortality using data available in the electronic health record (EHR) by combining 5 previously validated scores and additional novel variables reported to be associated with COVID-19-specific mortality. We verified the model with prospectively collected data from 12 hospitals in Colorado between March 2020 and July 2020. We compared the area under the receiver operator curve (AUROC) for the new model to the SOFA score and the Charlson Comorbidity Index. RESULTS: The prospective cohort included 27 296 encounters, of which 1358 (5.0%) were positive for SARS-CoV-2, 4494 (16.5%) required intensive care unit care, 1480 (5.4%) required mechanical ventilation, and 717 (2.6%) ended in death. The Charlson Comorbidity Index and SOFA scores predicted mortality with an AUROC of 0.72 and 0.90, respectively. Our novel score predicted mortality with AUROC 0.94. In the subset of patients with COVID-19, the stacked model predicted mortality with AUROC 0.90, whereas SOFA had AUROC of 0.85. DISCUSSION: Stacked regression allows a flexible, updatable, live-implementable, ethically defensible predictive analytics tool for decision support that begins with validated models and includes only novel information that improves prediction. CONCLUSION: We developed and validated an accurate in-hospital mortality prediction score in a live EHR for automatic and continuous calculation using a novel model that improved upon SOFA.

Real-Time Electronic Health Record Mortality Prediction During the COVID-19 Pandemic: A Prospective Cohort Study.

BACKGROUND: The SARS-CoV-2 virus has infected millions of people, overwhelming critical care resources in some regions. Many plans for rationing critical care resources during crises are based on the Sequential Organ Failure Assessment (SOFA) score. The COVID-19 pandemic created an emergent need to develop and validate a novel electronic health record (EHR)-computable tool to predict mortality. RESEARCH QUESTIONS: To rapidly develop, validate, and implement a novel real-time mortality score for the COVID-19 pandemic that improves upon SOFA. STUDY DESIGN AND METHODS: We conducted a prospective cohort study of a regional health system with 12 hospitals in Colorado between March 2020 and July 2020. All patients >14 years old hospitalized during the study period without a do not resuscitate order were included. Patients were stratified by the diagnosis of COVID-19. From this cohort, we developed and validated a model using stacked generalization to predict mortality using data widely available in the EHR by combining five previously validated scores and additional novel variables reported to be associated with COVID-19-specific mortality. We compared the area under the receiver operator curve (AUROC) for the new model to the SOFA score and the Charlson Comorbidity Index. RESULTS: We prospectively analyzed 27,296 encounters, of which 1,358 (5.0%) were positive for SARS-CoV-2, 4,494 (16.5%) included intensive care unit (ICU)-level care, 1,480 (5.4%) included invasive mechanical ventilation, and 717 (2.6%) ended in death. The Charlson Comorbidity Index and SOFA scores predicted overall mortality with an AUROC of 0.72 and 0.90, respectively. Our novel score predicted overall mortality with AUROC 0.94. In the subset of patients with COVID-19, we predicted mortality with AUROC 0.90, whereas SOFA had AUROC of 0.85. INTERPRETATION: We developed and validated an accurate, in-hospital mortality prediction score in a live EHR for automatic and continuous calculation using a novel model, that improved upon SOFA. TAKE HOME POINTS: Study Question: Can we improve upon the SOFA score for real-time mortality prediction during the COVID-19 pandemic by leveraging electronic health record (EHR) data?Results: We rapidly developed and implemented a novel yet SOFA-anchored mortality model across 12 hospitals and conducted a prospective cohort study of 27,296 adult hospitalizations, 1,358 (5.0%) of which were positive for SARS-CoV-2. The Charlson Comorbidity Index and SOFA scores predicted all-cause mortality with AUROCs of 0.72 and 0.90, respectively. Our novel score predicted mortality with AUROC 0.94.Interpretation: A novel EHR-based mortality score can be rapidly implemented to better predict patient outcomes during an evolving pandemic.

Clinical informatics accelerates health system adaptation to the COVID-19 pandemic: examples from Colorado.

OBJECTIVE: Large health systems responding to the coronavirus disease 2019 (COVID-19) pandemic face a broad range of challenges; we describe 14 examples of innovative and effective informatics interventions. MATERIALS AND METHODS: A team of 30 physician and 17 nurse informaticists with an electronic health record (EHR) and associated informatics tools. RESULTS: To meet the demands posed by the influx of patients with COVID-19 into the health system, the team built solutions to accomplish the following goals: 1) train physicians and nurses quickly to manage a potential surge of hospital patients; 2) build and adjust interactive visual pathways to guide decisions; 3) scale up video visits and teach best-practice communication; 4) use tablets and remote monitors to improve in-hospital and posthospital patient connections; 5) allow hundreds of physicians to build rapid consensus; 6) improve the use of advance care planning; 7) keep clinicians aware of patients' changing COVID-19 status; 8) connect nurses and families in new ways; 9) semi-automate Crisis Standards of Care; and 10) predict future hospitalizations. DISCUSSION: During the onset of the COVID-19 pandemic, the UCHealth Joint Informatics Group applied a strategy of "practical informatics" to rapidly translate critical leadership decisions into understandable guidance and effective tools for patient care. CONCLUSION: Informatics-trained physicians and nurses drew upon their trusted relationships with multiple teams within the organization to create practical solutions for onboarding, clinical decision-making, telehealth, and predictive analytics.

When Nursing Assertion Stops: A Qualitative Study to Examine the Cultural Barriers Involved in Escalation of Care in a Pediatric Hospital.

Pediatric codes outside the ICU are associated with increased morbidity and mortality. This qualitative research highlights results from confidential interviews with 10 pediatric nurses with experience of caring for children who required rapid response, code response, or transfer to intensive care. Detailed examination of nurses' experiences revealed local factors that facilitate and inhibit timely transfer of critical patients. Nurses identified themes including the impact of nurse assertiveness, providers' lack of understanding of nursing, team communication, and other hospital cultural barriers.