Toward Alleviating Clinician Documentation Burden: A Scoping Review of Burden Reduction Efforts.

BACKGROUND: Studies have shown that documentation burden experienced by clinicians may lead to less direct patient care, increased errors, and job dissatisfaction. Implementing effective strategies within health care systems to mitigate documentation burden can result in improved clinician satisfaction and more time spent with patients. However, there is a gap in the literature regarding evidence-based interventions to reduce documentation burden. OBJECTIVES: The objective of this review was to identify and comprehensively summarize the state of the science related to documentation burden reduction efforts. METHODS: Following Joanna Briggs Institute Manual for Evidence Synthesis and Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines, we conducted a comprehensive search of multiple databases, including PubMed, Medline, Embase, CINAHL Complete, Scopus, and Web of Science. Additionally, we searched gray literature and used Google Scholar to ensure a thorough review. Two reviewers independently screened titles and abstracts, followed by full-text review, with a third reviewer resolving any discrepancies. Data extraction was performed and a table of evidence was created. RESULTS: A total of 34 articles were included in the review, published between 2016 and 2022, with a majority focusing on the United States. The efforts described can be categorized into medical scribes, workflow improvements, educational interventions, user-driven approaches, technology-based solutions, combination approaches, and other strategies. The outcomes of these efforts often resulted in improvements in documentation time, workflow efficiency, provider satisfaction, and patient interactions. CONCLUSION: This scoping review provides a comprehensive summary of health system documentation burden reduction efforts. The positive outcomes reported in the literature emphasize the potential effectiveness of these efforts. However, more research is needed to identify universally applicable best practices, and considerations should be given to the transfer of burden among members of the health care team, quality of education, clinician involvement, and evaluation methods.

Patient and Caregiver Perceptions of an Interface Design to Communicate Artificial Intelligence-Based Prognosis for Patients With Advanced Solid Tumors.

PURPOSE: Use of artificial intelligence (AI) in cancer care is increasing. What remains unclear is how best to design patient-facing systems that communicate AI output. With oncologist input, we designed an interface that presents patient-specific, machine learning-based 6-month survival prognosis information designed to aid oncology providers in preparing for and discussing prognosis with patients with advanced solid tumors and their caregivers. The primary purpose of this study was to assess patient and caregiver perceptions and identify enhancements of the interface for communicating 6-month survival and other prognosis information when making treatment decisions concerning anticancer and supportive therapy. METHODS: This qualitative study included interviews and focus groups conducted between November and December 2022. Purposive sampling was used to recruit former patients with cancer and/or former caregivers of patients with cancer who had participated in cancer treatment decisions from Utah or elsewhere in the United States. Categories and themes related to perceptions of the interface were identified. RESULTS: We received feedback from 20 participants during eight individual interviews and two focus groups, including four cancer survivors, 13 caregivers, and three representing both. Overall, most participants expressed positive perceptions about the tool and identified its value for supporting decision making, feeling less alone, and supporting communication among oncologists, patients, and their caregivers. Participants identified areas for improvement and implementation considerations, particularly that oncologists should share the tool and guide discussions about prognosis with patients who want to receive the information. CONCLUSION: This study revealed important patient and caregiver perceptions of and enhancements for the proposed interface. Originally designed with input from oncology providers, patient and caregiver participants identified additional interface design recommendations and implementation considerations to support communication about prognosis.

Factors Influencing Medication Administration Outcomes Among New Graduate Nurses Using Bar Code-Assisted Medication Administration.

Paramount to patient safety is the ability for nurses to make clinical decisions free from human error. Yet, the dynamic clinical environment in which nurses work is characterized by uncertainty, urgency, and high consequence, necessitating that nurses make quick and critical decisions. The aim of this study was to examine the influence of human and environmental factors on the decision to administer among new graduate nurses in response to alert generation during bar code-assisted medication administration. The design for this study was a descriptive, longitudinal, observational cohort design using EHR audit log and administrative data. The study was set at a large, urban medical center in the United States and included 132 new graduate nurses who worked on adult, inpatient units. Research variables included human and environmental factors. Data analysis included descriptive and inferential analyses. This study found that participants continued with administration of a medication in 90.75% of alert encounters. When considering the response to an alert, residency cohort, alert category, and previous exposure variables were associated with the decision to proceed with administration. It is important to continue to study factors that influence nurses' decision-making, particularly during the process of medication administration, to improve patient safety and outcomes.

Describing Medication Administration and Alert Patterns Experienced by New Graduate Nurses During the First Year of Practice.

The aim of this study was to describe medication administration and alert patterns among a cohort of new graduate nurses over the first year of practice. Medical errors related to clinical decision-making, including medication administration errors, may occur more frequently among new graduate nurses. To better understand nursing workflow and documentation workload in today's clinical environment, it is important to understand patterns of medication administration and alert generation during barcode-assisted medication administration. Study objectives were addressed through a descriptive, longitudinal, observational cohort design using secondary data analysis. Set in a large, urban medical center in the United States, the study sample included 132 new graduate nurses who worked on adult, inpatient units and administered medication using barcode-assisted medication administration. Data were collected through electronic health record and administration sources. New graduate nurses in the sample experienced a total of 587 879 alert and medication administration encounters, administering 772 unique medications to 17 388 unique patients. Nurses experienced an average medication workload of 28.09 medications per shift, 3.98% of which were associated with alerts, over their first year of practice. In addition to high volume of medication administration, new graduate nurses administer many different types of medications and are exposed to numerous alerts while using barcode-assisted medication administration.

Impact of an automated, remote monitoring and coaching intervention in reducing hospice cancer family caregiving burden: A multisite randomized controlled trial.

BACKGROUND: Care for those with life-limiting cancer heavily involves family caregivers who may experience significant physical and emotional burden. The purpose of this study was to test the impact of Symptom Care at Home (SCH), an automated digital family caregiver coaching intervention, during home hospice, when compared to usual hospice care (UC) on the primary outcome of overall caregiver burden. Secondary outcomes included Caregiver Burden at weeks 1 and 8, Mood and Vitality subscales, overall moderate-to-severe caregiving symptoms, and sixth month spouse/partner bereavement outcomes. METHODS: Using a randomized, multisite, nonblinded controlled trial, 332 cancer family caregivers were enrolled and analyzed (159 SCH vs. 173 UC). Caregivers were primarily White (92%), female (69%), and spouse caregivers (53%). Caregivers provided daily reports on severity levels (0-10 scale) for their anxiety, depressed mood, fatigue, disturbed sleep, and caregiving interference with normal activities. These scores combined constituted the Caregiver Burden primary outcome. Based on reported symptoms, SCH caregivers received automated, tailored coaching about improving their well-being. Reports of moderate-to-severe caregiving symptoms also triggered hospice nurse notification. Secondary outcomes of Mood and Vitality were subcomponents of the Caregiver Burden score. A combined bereavement adjustment tool captured sixth month bereavement. RESULTS: The SCH intervention reduced overall Caregiver Burden compared to UC (p < .001), with a 38% reduction at 8 weeks and a medium-to-large effect size (d = .61). SCH caregivers experienced less (p < .001) disruption in both Mood and Vitality. There were higher levels of moderate-to-severe caregiving symptoms overtime in UC (OR, 2.722). All SCH caregivers benefited regardless of caregiver: sex, caregiver relationship, age, patient diagnosis and family income. SCH spouse/partner caregivers achieved better sixth month bereavement adjustment than UC (p < .007). CONCLUSIONS: The SCH intervention significantly decreased caregiving burden over UC and supports the maintenance of family caregiver mood and vitality throughout caregiving with extended benefit into bereavement.

Design of an interface to communicate artificial intelligence-based prognosis for patients with advanced solid tumors: a user-centered approach.

OBJECTIVES: To design an interface to support communication of machine learning (ML)-based prognosis for patients with advanced solid tumors, incorporating oncologists' needs and feedback throughout design. MATERIALS AND METHODS: Using an interdisciplinary user-centered design approach, we performed 5 rounds of iterative design to refine an interface, involving expert review based on usability heuristics, input from a color-blind adult, and 13 individual semi-structured interviews with oncologists. Individual interviews included patient vignettes and a series of interfaces populated with representative patient data and predicted survival for each treatment decision point when a new line of therapy (LoT) was being considered. Ongoing feedback informed design decisions, and directed qualitative content analysis of interview transcripts was used to evaluate usability and identify enhancement requirements. RESULTS: Design processes resulted in an interface with 7 sections, each addressing user-focused questions, supporting oncologists to "tell a story" as they discuss prognosis during a clinical encounter. The iteratively enhanced interface both triggered and reflected design decisions relevant when attempting to communicate ML-based prognosis, and exposed misassumptions. Clinicians requested enhancements that emphasized interpretability over explainability. Qualitative findings confirmed that previously identified issues were resolved and clarified necessary enhancements (eg, use months not days) and concerns about usability and trust (eg, address LoT received elsewhere). Appropriate use should be in the context of a conversation with an oncologist. CONCLUSION: User-centered design, ongoing clinical input, and a visualization to communicate ML-related outcomes are important elements for designing any decision support tool enabled by artificial intelligence, particularly when communicating prognosis risk.

External Validation of a Machine Learning Model to Predict 6-Month Mortality for Patients With Advanced Solid Tumors.

This prognostic study performed external validation of a machine learning model to predict 6-month mortality among patients with advanced solid tumors.

Technology-Assisted mHealth Caregiver Support to Manage Cancer Patient Symptoms: A Randomized Controlled Trial.

CONTEXT: Caregivers managing symptoms of family members with cancer during home hospice care, often feel ill-prepared and need patient care coaching. OBJECTIVES: This study tested the efficacy of an automated mHealth platform that included caregiver coaching on patient symptom care and nurse notifications of poorly controlled symptoms. The primary outcome was caregiver perception of patients' overall symptom severity throughout hospice care and at weeks one, two, four, and eight. Secondary outcomes compared individual symptom severity. METHODS: Caregivers (n = 298) were randomly assigned to the Symptom Care at Home (SCH) intervention (n = 144) or usual hospice care (UC) (n = 154). All caregivers placed daily calls to the automated system that assessed the presence and severity of 11 end-of-life patient physical and psychosocial symptoms. SCH caregivers received automated coaching on symptom care based on reported patient symptoms and their severity. Moderate-to-severe symptoms were also relayed to the hospice nurse. RESULTS: The SCH intervention produced a mean overall symptom reduction benefit, over UC, of 4.89 severity points (95% CI 2.86-6.92) (P < 0.001), with a moderate effect size (d = 0.55). The SCH benefit also occurred at each timepoint (P < 0.001- 0.020). There was a 38% reduction in days reporting moderate-to-severe patient symptoms compared to UC (P < 0.001) with 10/11 symptoms significantly reduced in SCH compared to UC. CONCLUSION: Automated mHealth symptom reporting by caregivers, paired with tailored caregiver coaching on symptom management and nurse notifications, reduces cancer patients' physical and psychosocial symptoms during home hospice, providing a novel and efficient approach to improving end-of-life care.

Nurse Cognition, Decision Support, and Barcode Medication Administration: A Conceptual Framework for Research, Practice, and Education.

This article synthesizes theoretical perspectives related to nurse cognition. We present a conceptual model that can be used by multiple stakeholders to study and contemplate how nurses use clinical decision support systems, and specifically, Barcode-Assisted Medication Administration, to make decisions during the delivery of care. Theoretical perspectives integrated into the model include dual process theory, the Cognitive Continuum Theory, human factors engineering, and the Recognition-Primed Decision model. The resulting framework illustrates the process of nurse cognition during Barcode-Assisted Medication Administration. Additionally, the model includes individual or human and environmental factors that may influence nurse cognition and decision making. It is important to consider the influence of individual, human, and environmental factors on the process of nurse cognition and decision making. Specifically, it is necessary to explore the impact of heuristics and biases on clinician decision making, particularly related to the development of alarm and alert fatigue. Aided by the proposed framework, stakeholders may begin to identify heuristics and cognitive biases that influence the decision of clinicians to accept or override a clinical decision support system alert and whether heuristics and biases are associated with inappropriate alert override.

Alert Types and Frequencies During Bar Code-Assisted Medication Administration: A Systematic Review.

BACKGROUND: Existing literature explores the effectiveness of bar code-assisted medication administration (BCMA) on the reduction of medication administration error as well as on nurse workarounds during BCMA. However, there is no review that comprehensively explores types and frequencies of alerts generated by nurses during BCMA. PURPOSE: The purpose was to describe alert generation type and frequency during BCMA. METHODS: A systematic review of the literature using PRISMA guidelines was conducted using CINAHL, PubMed, EMBASE, and Ovid Medline databases. RESULTS: After screening for inclusion and exclusion criteria, a total of 8 articles were identified and included in the review. Alert types included patient mismatch, wrong medication, and wrong dose, though other alert types were also reported. The frequency of alert generation varied across studies, from 0.18% to 42%, and not all alerts were clinically meaningful. CONCLUSIONS: This systematic review synthesized literature related to alert type and frequency during BCMA. However, further studies are needed to better describe alert generation patterns as well as factors that influence alert generation.

Quality of Care for PTSD and Depression in the Military Health System: Final Report.

The U.S. Department of Defense (DoD) strives to maintain a physically and psychologically healthy, mission-ready force, and the care provided by the Military Health System (MHS) is critical to meeting this goal. Attention has been directed to ensuring the quality and availability of programs and services for posttraumatic stress disorder (PTSD) and depression. This study is a comprehensive assessment of the quality of care delivered by the MHS in 2013-2014 for over 38,000 active-component service members with PTSD or depression. The assessment includes performance on 30 quality measures to evaluate the receipt of recommended assessments and treatments. These measures draw on multiple data sources including administrative encounter data, medical record review data, and patient self-reported outcome monitoring data. The assessment identified strengths and areas for improvement for the MHS. In particular, the MHS excels at screening for suicide risk and substance use, but rates of appropriate follow-up for service members with suicide risk are lower. Most service members received at least some psychotherapy, but less than half of psychotherapy delivered was evidence-based. In analyses focused on Army soldiers, outcome monitoring increased notably over time, yet preliminary analyses suggest that more work is needed to ensure that services are effective in reducing symptoms. When comparing performance between 2012-2013 and 2013-2014, most measures demonstrated slight improvement, but targeted efforts will be needed to support further improvements. RAND provides recommendations for strategies to improve the quality of care delivered for these conditions.

Comparing Quality of Care in Veterans Affairs and Non-Veterans Affairs Settings.

BACKGROUND: Congress, veterans' groups, and the press have expressed concerns that access to care and quality of care in Department of Veterans Affairs (VA) settings are inferior to access and quality in non-VA settings. OBJECTIVE: To assess quality of outpatient and inpatient care in VA at the national level and facility level and to compare performance between VA and non-VA settings using recent performance measure data. MAIN MEASURES: We assessed Patient Safety Indicators (PSIs), 30-day risk-standardized mortality and readmission measures, and ORYX measures for inpatient safety and effectiveness; Healthcare Effectiveness Data and Information Set (HEDIS®) measures for outpatient effectiveness; and Consumer Assessment of Healthcare Providers and Systems Hospital Survey (HCAHPS) and Survey of Healthcare Experiences of Patients (SHEP) survey measures for inpatient patient-centeredness. For inpatient care, we used propensity score matching to identify a subset of non-VA hospitals that were comparable to VA hospitals. KEY RESULTS: VA hospitals performed on average the same as or significantly better than non-VA hospitals on all six measures of inpatient safety, all three inpatient mortality measures, and 12 inpatient effectiveness measures, but significantly worse than non-VA hospitals on three readmission measures and two effectiveness measures. The performance of VA facilities was significantly better than commercial HMOs and Medicaid HMOs for all 16 outpatient effectiveness measures and for Medicare HMOs, it was significantly better for 14 measures and did not differ for two measures. High variation across VA facilities in the performance of some quality measures was observed, although variation was even greater among non-VA facilities. CONCLUSIONS: The VA system performed similarly or better than the non-VA system on most of the nationally recognized measures of inpatient and outpatient care quality, but high variation across VA facilities indicates a need for targeted quality improvement.

Evidence for Misspecification of a Nationally Used Quality Measure for Substance Use Treatment.

OBJECTIVES: The National Committee for Quality Assurance's (NCQA) measure "Initiation and Engagement of Alcohol and Other Drug Dependence Treatment" captures the proportion of substance use patients with (1) treatment initiation within 14 days and (2) treatment engagement within 30 days thereafter. The definition of treatment considers only counseling but not medication-assisted treatment (MAT), although MAT is supported by current guidelines. Our research question is whether this omission results in meaningful measurement error. STUDY DESIGN AND METHODS: We analyze claims data for members of commercial health plans to investigate whether including MAT would meaningfully change the measure rate and health plan rankings. RESULTS: Including MAT increased both the initiation and engagement rates. The initiation and engagement rates increased 2.4% (38.9-39.8%) and 9.9% (12.9-14%), respectively. These differences imply that 19% of health plans would change their ranking by at least one quintile for the initiation measure and 27% for the engagement measure. CONCLUSIONS: The current specifications result in erroneous conclusions about the quality of care provided by different health plans. Our results suggest that aligning the measure specifications with guideline recommendations, as recently proposed by NCQA, would result in more accurate information.

Comparing VA and Non-VA Quality of Care: A Systematic Review.

BACKGROUND: The Veterans Affairs (VA) health care system aims to provide high-quality medical care to veterans in the USA, but the quality of VA care has recently drawn the concern of Congress. The objective of this study was to systematically review published evidence examining the quality of care provided at VA health care facilities compared to quality of care in other facilities and systems. METHODS: Building on the search strategy and results of a prior systematic review, we searched MEDLINE (from January 1, 2005, to January 1, 2015) to identify relevant articles on the quality of care at VA facilities compared to non-VA facilities. Articles from the prior systematic review published from 2005 and onward were also included and re-abstracted. Studies were classified, analyzed, and summarized by the Institute of Medicine's quality dimensions. RESULTS: Sixty-nine articles were identified (including 31 articles from the prior systematic review and 38 new articles) that address one or more Institute of Medicine quality dimensions: safety (34 articles), effectiveness (24 articles), efficiency (9 articles), patient-centeredness (5 articles), equity (4 articles), and timeliness (1 article). Studies of safety and effectiveness indicated generally better or equal performance, with some exceptions. Too few articles related to timeliness, equity, efficiency, and patient-centeredness were found from which to reliably draw conclusions about VA care related to these dimensions. DISCUSSION: The VA often (but not always) performs better than or similarly to other systems of care with regard to the safety and effectiveness of care. Additional studies of quality of care in the VA are needed on all aspects of quality, but particularly with regard to timeliness, equity, efficiency, and patient-centeredness.

Resources and Capabilities of the Department of Veterans Affairs to Provide Timely and Accessible Care to Veterans.

The Veterans Access, Choice, and Accountability Act of 2014 addressed the need for access to timely, high-quality health care for veterans. Section 201 of the legislation called for an independent assessment of various aspects of veterans' health care. The RAND Corporation was tasked with an assessment of the Department of Veterans Affairs (VA) current and projected health care capabilities and resources. An examination of data from a variety of sources, along with a survey of VA medical facility leaders, revealed the breadth and depth of VA resources and capabilities: fiscal resources, workforce and human resources, physical infrastructure, interorganizational relationships, and information resources. The assessment identified barriers to the effective use of these resources and capabilities. Analysis of data on access to VA care and the quality of that care showed that almost all veterans live within 40 miles of a VA health facility, but fewer have access to VA specialty care. Veterans usually receive care within 14 days of their desired appointment date, but wait times vary considerably across VA facilities. VA has long played a national leadership role in measuring the quality of health care. The assessment showed that VA health care quality was as good or better on most measures compared with other health systems, but quality performance lagged at some VA facilities. VA will require more resources and capabilities to meet a projected increase in veterans' demand for VA care over the next five years. Options for increasing capacity include accelerated hiring, full nurse practice authority, and expanded use of telehealth.

Quality of Care for PTSD and Depression in the Military Health System: Phase I Report.

The U.S. Department of Defense (DoD) strives to maintain a physically and psychologically healthy, mission-ready force, and the care provided by the Military Health System (MHS) is critical to meeting this goal. Given the rates of posttraumatic stress disorder (PTSD) and depression among U.S. service members, attention has been directed to ensuring the quality and availability of programs and services targeting these and other psychological health (PH) conditions. Understanding the current quality of care for PTSD and depression is an important step toward improving care across the MHS. To help determine whether service members with PTSD or depression are receiving evidence-based care and whether there are disparities in care quality by branch of service, geographic region, and service member characteristics (e.g., gender, age, pay grade, race/ethnicity, deployment history), DoD's Defense Centers of Excellence for Psychological Health and Traumatic Brain Injury (DCoE) asked the RAND Corporation to conduct a review of the administrative data of service members diagnosed with PTSD or depression and to recommend areas on which the MHS could focus its efforts to continuously improve the quality of care provided to all service members. This study characterizes care for service members seen by MHS for diagnoses of PTSD and/or depression and finds that while the MHS performs well in ensuring outpatient follow-up following psychiatric hospitalization, providing sufficient psychotherapy and medication management needs to be improved. Further, quality of care for PTSD and depression varied by service branch, TRICARE region, and service member characteristics, suggesting the need to ensure that all service members receive high-quality care.

Medicare Home Visit Program Associated With Fewer Hospital And Nursing Home Admissions, Increased Office Visits.

Clinical home visit programs for Medicare beneficiaries are a promising approach to supporting aging in place and avoiding high-cost institutional care. Such programs combine a comprehensive geriatric assessment by a clinician during a home visit with referrals to community providers and health plan resources to address uncovered issues. We evaluated UnitedHealth Group's HouseCalls program, which has been offered to Medicare Advantage plan members in Arkansas, Georgia, Missouri, South Carolina, and Texas since January 2008. We found that, compared to non-HouseCalls Medicare Advantage plan members and fee-for-service beneficiaries, HouseCalls participants had reductions in admissions to hospitals (1 percent and 14 percent, respectively) and lower risk of nursing home admission (0.67 percent and 1.3 percent, respectively). In addition, participants' numbers of office visits--chiefly to specialists--increased 2-6 percent (depending on the comparison group). The program's effects on emergency department use were mixed. These results indicate that a thorough home-based clinical assessment of a member's health and home environment combined with referral services can support aging in place, promote physician office visits, and preempt costly institutional care.

Improving Care for Chronic Conditions: Current Practices and Future Trends in Health Plan Programs.

The need for better management of chronic conditions is urgent. About 141 million people in the United States were living with one or more chronic conditions in 2010, and this number is projected to increase to 171 million by 2030. To address this challenge, many health plans have piloted and rolled out innovative approaches to improving care for their members with chronic conditions. This article documents the current range of chronic care management services, identifies best practices and industry trends, and examines factors in the plans' operating environment that limit their ability to optimize chronic care programs. The authors conducted telephone surveys with a representative sample of health plans and made in-depth case studies of six plans. All plans in the sample provide a wide range of products and services around chronic care, including wellness/lifestyle management programs for healthy members, disease management for members with common chronic conditions, and case management for high-risk members regardless of their underlying condition. Health plans view these programs as a "win-win" situation and believe that they improve care for their most vulnerable members and reduce cost of coverage. Plans are making their existing programs more patient-centric and are integrating disease and case management, and sometimes lifestyle management and behavioral health, into a consolidated chronic care management program, believing that this will increase patient engagement and prevent duplication of services and missed opportunities.

Measuring the Quality of Care for Psychological Health Conditions in the Military Health System: Candidate Quality Measures for Posttraumatic Stress Disorder and Major Depressive Disorder.

In recent years, the number of U.S. service members treated for psychological health conditions has increased substantially. In particular, at least two psychological health conditions-posttraumatic stress disorder (PTSD) and major depressive disorder (MDD)-have become more common, with prevalence estimates up to 20 percent for PTSD and 37 percent for MDD. Delivering quality care to service members with these conditions is a high-priority goal for the military health system (MHS). Meeting this goal requires understanding the extent to which the care the MHS provides is consistent with evidence-based clinical practice guidelines and its own standards for quality. To better understand these issues, RAND Corporation researchers developed a framework to identify and classify a set of measures for monitoring the quality of care provided by the MHS for PTSD and MDD. The goal of this project was to identify, develop, and describe a set of candidate quality measures to assess care for PTSD and MDD. To accomplish this goal, the authors performed two tasks: (1) developed a conceptual framework for assessing the quality of care for psychological health conditions and (2) identified a candidate set of measures for monitoring, assessing, and improving the quality of care for PTSD and MDD. This article describes their research approach and the candidate measure sets for PTSD and MDD that they identified. The current task did not include implementation planning but provides the foundation for future RAND work to pilot a subset of these measures.