Use of Electronic Health Records by Nurses for Symptom Management in Inpatient Settings: A Systematic Review

Agreement between patient-reported and clinically documented symptoms of acute myeloid leukemia: Study protocol

AIM

To describe our methods to compare patient-reported symptoms of acute myeloid leukemia and the corresponding documentation by healthcare providers in the electronic health record.

BACKGROUND

Patients with acute myeloid leukemia experience many distressing symptoms, particularly related to chemotherapy. The timely recognition and provision of evidence-based interventions to manage these symptoms can improve outcomes. However, lack of standardized formatting for symptom documentation within electronic health records leads to challenges for clinicians when accessing and comprehending patients' symptom information, as it primarily exists in narrative forms in various parts of the electronic health record. This variability raises concerns about over- or under-reporting of symptoms. Consistency between patient-reported symptoms and clinician's symptom documentation is important for patient-centered symptom management, but little is known about the degree of agreement between patient reports and their documentation. This is a detailed description of the study's methodology, procedures and design to determine how patient-reported symptoms are similar or different from symptoms documented in electronic health records by clinicians.

DESIGN

Exploratory, descriptive study.

METHODS

Forty symptoms will be assessed as patient-reported outcomes using the modified version of the Memorial Symptom Assessment Scale. The research team will annotate symptoms from the electronic health record (clinical notes and flowsheets) corresponding to the 40 symptoms. The degree of agreement between patient reports and electronic health record documentation will be analyzed using positive and negative agreement, kappa statistics and McNemar's test.

CONCLUSION

We present innovative methods to comprehensively compare the symptoms reported by acute myeloid leukemia patients with all available electronic health record documentation, including clinical notes and flowsheets, providing insights into symptom reporting in clinical practice.

IMPACT

Findings from this study will provide foundational understanding and compelling evidence, suggesting the need for more thorough efforts to assess patients' symptoms. Methods presented in this paper are applicable to other symptom-intensive diseases.

Factors Influencing Electronic Health Record Workflow Integration Among Nurses in Saudi Arabia: Cross-Sectional Study

Introduction

Globally, healthcare organizations have transitioned from paper-based documentation to electronic health records (EHR), including in Saudi Arabia. However, the adoption of EHR at the national level in Saudi Arabia needs more attention. Thus, this study aimed to determine the workflow integration of EHR and associated factors.

Objectives

The specific aims were to examine the level of EHR use and workflow integration among nurses, to determine the differences in EHR use and workflow integration based on nurses' demographic characteristics, and to determine the association between the predictive factors and EHR workflow integration.

Methods

This is a cross-sectional, correlational descriptive study. The data were collected from 293 nurses using the convenience sampling method. The participating nurses completed a questionnaire that included two measures: the Information System Use Survey and the Workflow Integration Survey (WIS). The data were analyzed using descriptive and multivariate statistics with SPSS software.

Results

The nurses had a positive perception of EHR use and workflow. The EHR use scores differed based on workplace (P < .01), education level (P < .05), and area of practice (P < .001). Similarly, the EHR workflow integration scores varied according to workplace (P < .05), education level (P < .05), and area of practice (P < .001). Education level and workplace significantly predicted information system use. Furthermore, education level and information system use significantly predicted the EHR integration into nurses' workflow.

Conclusion

The nurses expressed a greater perceived use of EHR regarding the integrated health information system, which was a predictor of EHR integration into nurses' workflow.

Patient Race, Ethnicity, Language, and Pain Severity in Primary Care: A Retrospective Electronic Health Record Study

BACKGROUND

Patient race, ethnicity, and culture including language are intertwined and may influence patient reporting of pain severity.

PURPOSE

To describe documentation of patient's self-reported pain presence and severity by race, ethnicity, and language, specifically, Spanish, Hmong, Lao, or Khmer requiring an interpreter or English.

DESIGN AND SAMPLE

Retrospective, electronic health record clinical data mining study of 79,195 patient visits with documented pain scores from one primary care clinic.

METHODS

Hurdle regression was used to explore the effect of race, ethnicity, and language on the chances of having any pain (vs. no pain) and pain severity for visits with pain scores ≥1, controlling for age, sex, and documentation of a pain diagnosis. Mann-Whitney tests were used to explore the influence of English vs. non-English language on pain severity within a race or ethnicity category.

RESULTS

Pain scores were higher for limited English proficiency, compared with English-speaking, patients within the Asian race or Hispanic/Latino ethnicity category. Older age, female sex, pain diagnosis, Black or African American race, and Spanish or Lao language increased the chance of having any pain. These same factors, plus American Indian or Alaska Native race, contributed to higher pain severity. Asian race, in contrast, decreased the chance of reporting any pain and contributed to lesser pain severity.

CONCLUSIONS

Race, in addition to a new area of focus, language, impacted both the chances of reporting any pain and pain severity. Additional research is needed on the impact of language barriers on pain severity reporting, documentation, and differences in pain outcomes and disparities.

Using the MDASI-Adolescent for Early Symptom Identification and Mitigation of Symptom Impact on Daily Living in Adolescent and Young Adult Stem Cell Transplant Patients

Hematopoietic stem cell transplantation (HSCT) requires an intensive pre- and post-procedure course that leads to symptoms including fatigue, nausea/vomiting, and pain, all of which interfere significantly with activities of daily living. These symptoms place a substantial burden on patients during the time period surrounding transplant as well as during long-term recovery. The MD Anderson Symptom Inventory (MDASI) is a symptom-reporting survey that has been successfully used in adult patients with cancer and may have utility in the adolescent and young adult (AYA) population. At the Children’s Cancer Hospital at MD Anderson Cancer Center, we adopted a modified version of the MDASI, the MDASI-adolescent (MDASI-Adol), as a standard of care for clinical practice in assessing the symptom burden of patients in the peri-transplant period. We then conducted a retrospective chart review to describe the clinical utility of implementing this symptom-screening tool in AYA patients admitted to our pediatric stem cell transplant service. Here, we report our findings on the symptom burden experienced by pediatric and AYA patients undergoing stem cell transplantation as reported on the MDASI-Adol. Our study confirmed that the MDASI-Adol was able to identify a high symptom burden related to HSCT in the AYA population and that it can be used to guide symptom-specific interventions prior to transplant and during recovery. Implementing a standard symptom-screening survey proved informative to our clinical practice and could mitigate treatment complications and alleviate symptom burden.

Not another box to check! Using the UTAUT to explore nurses' psychological adaptation to electronic health record usability

BACKGROUND

As the integration of electronic health records (EHRs) continues to expand throughout healthcare organizations worldwide, nurses are faced with the challenge to acclimate to a dynamic technology-based environment of patient care. As technology advances, EHR usability may influence nurses' clinical performance and require nurses to adapt to a wide range of situations associated with electronic documentation. While perceived benefits of EHRs include improvements in healthcare delivery and patient outcomes, there are also unintended consequences associated with EHR usability.

AIMS

The aim of this article is to explore dimensions of EHR usability that may influence nurses' psychological adaptation to the use of EHRs in daily practice.

MATERIALS AND METHODS

The unified theory of acceptance and use of technology (UTAUT) consists of four constructs theorized to have a direct influence on end-user behavior and acceptance of technology: performance expectancy, effort expectancy, social influence, and facilitating conditions. The UTAUT provides the framework to explore EHR usability as found in literature and describe the positive and negative psychological responses of nurses related to the use of EHRs in daily practice.

RESULTS

Integration of EHRs into daily nursing practice can result in positive experiences or have a negative impact on nurses ability to perform their role as patient caregivers.

DISCUSSION

While integration of EHRs into healthcare systems can facilitate improvements in patient outcomes, the delivery of patient care and nurses' daily practices can simultaneously be complicated by EHR usability issues.

CONCLUSION

Although positive and negative experiences of nurses in relationship to EHR usability can be found in literature, there is limited evidence on nurses' psychological adaptation to use of EHRs. Further research on EHR usability is needed based on nursing perspectives and feedback to determine the psychological impact EHRs exert on nurses, discover effective methods for resolving issues, and promote positive trends associated with EHR usability.

Hypoactive Sexual Desire Disorder in Women: Physiology, Assessment, Diagnosis, and Treatment

Nearly half of women in the United States report problems with sexual function. Many health care providers do not ask about sexual concerns during routine clinical encounters because of personal discomfort, lack of familiarity with treatment, or the belief that they lack adequate time to address this complex issue. This may be especially true for hypoactive sexual desire disorder (HSDD), the most commonly identified sexual problem among women. HSDD is characterized by a deficiency of sexual thoughts, feelings, or receptiveness to sexual stimulation that has been present for at least 6 months, causes personal distress, and is not due to another medical condition. This is an up-to-date overview of HSDD for clinicians, discussing its physiology, assessment, diagnosis, and treatment strategies. Although a definitive physiology of HSDD is still unknown, multiple hormones and neurotransmitters likely participate in a dual-control model to balance excitation and inhibition of sexual desire. For assessment and diagnosis, validated screening tools are discussed, and the importance of a biopsychosocial assessment is emphasized, with guidance on how this can be implemented in clinical encounters. The 2 recently approved medications for HSDD, flibanserin and bremelanotide, are reviewed as well as off-label treatments. Overall, HSDD represents a common yet likely underrecognized disorder that midwives and other health care providers who care for women across the life span are in a unique position to address.

Mining tasks and task characteristics from electronic health record audit logs with unsupervised machine learning

OBJECTIVE

The characteristics of clinician activities while interacting with electronic health record (EHR) systems can influence the time spent in EHRs and workload. This study aims to characterize EHR activities as tasks and define novel, data-driven metrics.

MATERIALS AND METHODS

We leveraged unsupervised learning approaches to learn tasks from sequences of events in EHR audit logs. We developed metrics characterizing the prevalence of unique events and event repetition and applied them to categorize tasks into 4 complexity profiles. Between these profiles, Mann-Whitney U tests were applied to measure the differences in performance time, event type, and clinician prevalence, or the number of unique clinicians who were observed performing these tasks. In addition, we apply process mining frameworks paired with clinical annotations to support the validity of a sample of our identified tasks. We apply our approaches to learn tasks performed by nurses in the Vanderbilt University Medical Center neonatal intensive care unit.

RESULTS

We examined EHR audit logs generated by 33 neonatal intensive care unit nurses resulting in 57 234 sessions and 81 tasks. Our results indicated significant differences in performance time for each observed task complexity profile. There were no significant differences in clinician prevalence or in the frequency of viewing and modifying event types between tasks of different complexities. We presented a sample of expert-reviewed, annotated task workflows supporting the interpretation of their clinical meaningfulness.

CONCLUSIONS

The use of the audit log provides an opportunity to assist hospitals in further investigating clinician activities to optimize EHR workflows.

Nursing decision support system: application in electronic health records†

The clinical decision support system makes electronic health records (EHRs) structured, intelligent, and knowledgeable. The nursing decision support system (NDSS) is based on clinical nursing guidelines and nursing process to provide intelligent suggestions and reminders. The impact on nurses’ work is mainly in shortening the recording time, improving the quality of nursing diagnosis, reducing the incidence of nursing risk events, and so on. However, there is no authoritative standard for the NDSS at home and abroad. This review introduces development and challenges of EHRs and recommends the application of the NDSS in EHRs, namely the nursing assessment decision support system, the nursing diagnostic decision support system, and the nursing care planning decision support system (including nursing intervene), hoping to provide a new thought and method to structure impeccable EHRs.

Pilot of a Pediatric Palliative Care Early Intervention Instrument

Current research demonstrates that pediatric symptom management care is often initiated in the late stages of disease once clinicians are no longer able to meaningfully impact symptom burden. Given that physicians or nurse practitioners are responsible for initiating palliative care referrals, it is incumbent upon registered nurses to advocate when improved symptom management care is needed. The pediatric palliative care screening instrument pilot provides a centralized instrument to document and quantify a patient's symptom profile, giving registered nurses the opportunity to objectively communicate and track a patient's need for improved symptom management care within the areas of pain, secretions, dyspnea, intractable seizures, nausea, vomiting, constipation, diarrhea, anorexia, cachexia, sleep disturbance, lethargy, anxiety, depression, and/or agitation. The 4-week quality improvement project at an academic teaching hospital formally incorporated the bedside registered nurses' symptom assessment into a centralized document. Fifty-three patients were identified as having an uncontrolled symptom burden in at least one of the symptom domains, indicating that excessive and untreated symptom burden was present on the acute care floor. The pediatric palliative care screening instrument could act as a conduit between bedside registered nurses and the palliative care team, serving to reduce the time between onset of excessive symptom burden and initiation of symptom management services.