Necessity is the “mother of invention” and the COVID-19 pandemic has indeed spurred innovation and workflow redesign in order to transform healthcare delivery. Demand for inpatient acute care bed capacity has increased during the pandemic necessitating the discharge of patients earlier in the day to facilitate throughput. Responsively, in May 2020, nurse leaders and at a 1,200-bed Magnet® hospital identified an opportunity to leverage and optimize existing technology through a virtual discharge nurse (VDN) pilot on four medical-surgical units. This innovation utilizes an off-site nurse to remotely provide support for care tasks that may be completed with limited physical interaction. Goals of the VDN initiative are to conserve personal protective equipment (PPE), facilitate throughput, support the bedside RN and bolster the patient experience by efficiently attending to the education and care coordination needs evident upon discharge.
This presentation describes the implementation of a VDN initiative that informs attendees of valuable insights associated with the conference goal of sharing strategies and workflow design which utilize healthcare technology throughout the continuum of care to optimize patient outcomes and equip nurses to lead well in this new environment. Supported by Lewin’s model of change nursing, key tactics which enabled the launch of the VDN project from a 7-day period of idea to inception included assembling and engaging a group of interprofessional stakeholders from clinical informatics, staffing operations, and nursing leadership who defined the project’s scope, milestones, and created project inclusion and exclusion criteria. Current applications were evaluated and reconfigured to meet remote project needs and documentation tools in the electronic medical record were operationalized to increase the transparency of discharge readiness. Roles and responsibilities of the VDN were established, workflows created, scripted patient discharge information developed, existing off-site telehealth support engaged, and non-budgeted or redeployed staff positions were utilized. Crucial was the creation of provider/caregiver communication processes to avoid redundancy or gaps in care. Virtual patient discharges have expanded to eight medical-surgical units. One virtual nurse FTE was responsible for 4.8% of all discharges from the facility between May and November 2020 (731/15,338).
Preliminary findings reflected an average decrease of > 84 minutes from traditional discharges to VDN on pilot units, with encouraging trends associated with discharge order to complete times and virtual discharges completed before noon. Future metrics include 7- and 30-day readmission rates, length of stay, and staff/provider satisfaction. Next steps include expansion across workflows, locations and technologies and a request for formal, budgeted VDN positions. Information gained during this presentation can be incorporated within a wide variety of settings to utilize virtual care nursing to support continuity of care and meet the growing demands of patients and nurses.
Learning Outcome: After completing this learning activity, the participant will be able to assess innovations being used by other professionals in the specialty and evaluate the potential of implementing the improvements into practice.
Purpose: To assess the feasibility of the Two Happy Hearts (THH) technology-based self-management model for improving perinatal health. The THH is a home-based stress-reduction intervention that promotes the health and well-being of both mother and infant.
Background/significance: During pregnancy, women experience several physical and psychological changes that affect their quality of life. Moreover, maternal stress has been found to be associated with poor birth outcomes, including low birth weight, pre-term birth, and neurodevelopmental disorders, all of which may have long-term health consequences in childhood, extending into adulthood. Personalized health management interventions, in addition to social support, are effective strategies for alleviating stress during pregnancy. Particularly, the increasingly widespread adoption of modern health technology such as mobile health (mHealth) and telehealth comprise methods to ensure equitable access to adequate and timely resources for at-risk pregnant women. Not only are these technological approaches cost-effective methods with the potential to reduce national health expenditure, but they also increase health equity by improving access to quality care for underserved women who may otherwise be excluded from essential health services. The Two Happy Hearts (THH) technology-based self-management model proposes to address these gaps.
Methods: In line with the goal of increasing health equity across at-risk socio-economic and demographic groups, this feasibility study is designed to assess the THH theory-driven model. The sample is composed of at-risk adult women with a singleton pregnancy who have access to a smartphone. This research model integrates mHealth and telehealth to collect objective and subjective physical and mental health data throughout pregnancy. Using the THH mHealth in the form of smartphone-based surveys and wearable devices (smartwatch and ring), pregnant women are empowered to monitor their emotional states, stressors, sleep, steps, and heart rate. This app-based intervention includes mindful breathing and safe exercise routines, all of which have been carefully developed by experts in line with the American College of Obstetricians and Gynecologists guidelines. Particularly, the triage system incorporated into the mHealth application captures high-risk mental health concerns for timely response. In addition, telehealth is delivered virtually by trained community health workers (CHWs) who provide health education and guide women through personalized coaching, compassionate listening, and social support.
Results: Preliminary data from the ongoing feasibility study indicate successful recruitment of at-risk pregnant women who often wear the smartwatch and ring. Completion of the smartphone-based surveys provides evidence about the acceptability of mHealth. In addition, women are motivated to track their emotional states, stressors, sleep, steps, and heart rate to practice appropriate coping strategies on a regular basis and when needed. Similarly, pregnant women have expressed positive experiences with the virtual visits and health coaching by the CHWs. Thus far, attrition rates are very low.
Conclusions/implications: The THH technology-based model endeavors to promote self-management of mental and physical health for vulnerable pregnant women by providing personalized health education and support. We anticipate that results generated from this research study will ultimately increase health equity and improve the quality of maternal and infant care.
Leaning Outcome:
After completing this learning activity, the participant will be able to assess innovations being used by other professionals in the specialty and evaluate the potential of implementing the improvements into practice.
Background/significance: Pressure injury is one of the key patient safety and care quality indicators. To monitor PI prevalence and explore risk factors, electronic health records (EHRs), have been adopted in PI research. However, a recent NLM study found great discrepancies in both prevalence and cases with a Venn diagram comparing the identified PI cases in the diagnosis, stage data in the chart events, and clinical notes in MIMIC III, a freely accessible critical care database.
Purpose: Since other available PI features such as site in the chart events and the number of PI on each patient have not been compared, this study thus aims to further and more comprehensively compare all identified PI cases based on diagnosis codes, chart events, clinical notes, and procedures in MIMIC-III.
Methods: ICD-9 diagnosis codes, chart event item IDs, keywords, and CPT numbers for PI were used to extract PI datasets. As Venn diagram gets complex when visualizing over 4 sets, we applied UpSetR to generate static UpSet plots to visualize and compare the identified PI set interactions based on the ICD-9 diagnosis codes, chart events, clinical notes, and CPT events. The numbers of PI site and stage were analyzed and then also compared to see if they were the same among patients with diagnosis or chart event data.
Results: 32,211 patients in MIMIC III with either of the following data were included: 1) diagnoses on PI stage or site within up to #39 total diagnoses; 2) chart events on Braden risk sub or total scale score, #1 to #3 PI’s site, stage, depth, drainage, width, cleansing, treatment, wound base, odor, pressure support, pressure reduce device, heal, amount (drainage), or length items from one system CareVue or up to #10 stages from MetaVision, the other system; 3) detected and non-negative PI clinical notes; and 4) procedures of wound debridement or wet-to-dry dressings. PI documented in the MetaVision chart event system and CPT events were incomplete. The number of patients with PI were 1837, 2850 and 6994 respectively based on the diagnosis, chart events, and clinical notes.
UpSet visualizations presented the great discrepancies in PI documentation: (1) chart events captured much more PIs; (2) stage was less documented than site in the diagnosis or charts; (3) PI number was not a chart feature and inconsistent across diagnosis or chart when comparing site with stage; (4) chart events on PI depth, width, drainage amount, odor, and cleansing were less documented when compared with other features in the chart events. The differences in the number of PI (site – stage) ranged from -2 to 4 in the diagnosis and from -3 to 2 in the chart events. For patients with both site and stage data, 810 patients (44.1%) reported the same number of site and stage in the diagnosis and 2,211 (98.0%) in the charts.
Conclusions/implications: PI documentation needs improvement. Upset plots could be used as clinical informatics tools to inform documentation quality. PI research may use EHR chart event data and needs to validate the results.
Purpose: Since other available PI features such as site in the chart events and the number of PI on each patient have not been compared, this study thus aims to further and more comprehensively compare all identified PI cases based on diagnosis codes, chart events, clinical notes, and procedures in MIMIC-III.
Methods: ICD-9 diagnosis codes, chart event item IDs, keywords, and CPT numbers for PI were used to extract PI datasets. As Venn diagram gets complex when visualizing over 4 sets, we applied UpSetR to generate static UpSet plots to visualize and compare the identified PI set interactions based on the ICD-9 diagnosis codes, chart events, clinical notes, and CPT events. The numbers of PI site and stage were analyzed and then also compared to see if they were the same among patients with diagnosis or chart event data.
Results: 32,211 patients in MIMIC III with either of the following data were included: 1) diagnoses on PI stage or site within up to #39 total diagnoses; 2) chart events on Braden risk sub or total scale score, #1 to #3 PI’s site, stage, depth, drainage, width, cleansing, treatment, wound base, odor, pressure support, pressure reduce device, heal, amount (drainage), or length items from one system CareVue or up to #10 stages from MetaVision, the other system; 3) detected and non-negative PI clinical notes; and 4) procedures of wound debridement or wet-to-dry dressings. PI documented in the MetaVision chart event system and CPT events were incomplete. The number of patients with PI were 1837, 2850 and 6994 respectively based on the diagnosis, chart events, and clinical notes.
UpSet visualizations presented the great discrepancies in PI documentation: (1) chart events captured much more PIs; (2) stage was less documented than site in the diagnosis or charts; (3) PI number was not a chart feature and inconsistent across diagnosis or chart when comparing site with stage; (4) chart events on PI depth, width, drainage amount, odor, and cleansing were less documented when compared with other features in the chart events. The differences in the number of PI (site – stage) ranged from -2 to 4 in the diagnosis and from -3 to 2 in the chart events. For patients with both site and stage data, 810 patients (44.1%) reported the same number of site and stage in the diagnosis and 2,211 (98.0%) in the charts.
Learning Outcome: After completing this learning activity, the participant will be able to assess innovations being used by other professionals in the specialty and evaluate the potential of implementing the improvements into practice.
Transitions in patient care are held together by interdisciplinary handoff communications intended to coordinate the patient’s ongoing care requirements. Patients with complexity in care encumber the transfer of care process requiring a higher level of care coordination between the interdisciplinary team. While the literature is abundant on the characteristics and quality of handoff communications, it is limited on the requirements of what data is necessary for ongoing care following transfer communications.
Poor communication and incomplete information transfer contribute to gaps in ongoing care following critical patient care transitions. Information loss has been reported to occur 100% of time and contributions between 15%-67% to adverse events. Incomplete information transfer following surgical interventions has contributed to delays in diagnostic and therapeutic interventions with potential deterioration in the patient’s status. With nurses often viewing EHR documentation as a universal communication source, abridged verbal interactions with other patient care providers leads to critical information loss for patient care. Despite the use of handoff tools, there has been no progress made on the data requirements to be included in EHRs for continuity in ongoing patient care.
Findings from a recent study exploring the verbal information transferred during operating room to post-anesthesia care unit nursing handoff communications and whether the data is captured in the electronic health record (EHR) to represent the necessary information for ongoing patient care and care planning. Findings examine how the data, information, knowledge, and wisdom framework supported the research and the emerging Kennedy integrated theoretical framework (KITF). The KITF integrates cognition theory, patterns of knowledge theory, and clinical communication space theory to support the human-technology characteristics within transitions in patient care (e.g., perioperative handoffs). Evidence of wisdom, in addition to elements of non-verbal communication patterns emerging from shared common ground, were identified as new contributions for the framework’s expansion.
To understand contributions by nursing terminologies (i.e., perioperative nursing data set [PNDS]) to post-surgical care transitions, the study examined nursing diagnoses, interventions, interim outcomes, and goals relationships to the handoff data communicated between OR and PACU registered nurses.
Study findings revealed a complex fragmented process of verbal communications and electronic documentation for the handoff process. While the EHR is prominent in data procurement for the handoff process, the design of handoff artifacts (e.g., paper, electronic) significantly impact the value of information received. Incomplete handoff tools or missing EHR data adds to a cycle of information decay while contributing to increase cognitive load and potentiating opportunities for information and knowledge loss. The absence of nursing diagnoses in the automation of the PNDS challenges the integrity of the language within the documentation platform and raises considerations for hierarchical representation within interface terminologies.
Study findings also reinforce current literature recommendations to reconsider user requirements in the design and functionality of healthcare information technology to enable data and information flow and preserve knowledge development.
Learining Outcome: After completing this learning activity, the participant will be able to assess innovations being used by other professionals in the specialty and evaluate the potential of implementing the improvements into practice.