Emergency department resource utilization among nursing home residents, a National Cross-Sectional Study.

OBJECTIVES: Persons 65 years and older (older persons), particularly residents of nursing homes (NHs), disproportionately access the emergency department (ED) and utilize more medical resources. The goal of this study is to provide a contemporary description of healthcare utilization patterns and disposition decisions for United States (US) NH residents presenting to EDs. METHODS: Older persons presenting to EDs in the US were identified in the National Hospital Ambulatory Medical Care Survey (NHAMCS) 2017, 2018 and 2019 datasets. We examined demographic, clinical, and resource use characteristics and outcomes. After survey weighting, we compared the frequency of different imaging, medications, clinical interventions, and outcomes in the ED between NH residents and those residing outside NHs. RESULTS: From 2017 to 2019, older persons made 24,441,285 annual visits to the ED, comprising 17.5% of all visits. Among these, 1,579,916 visits (6.5%) were by NH residents. Compared with non-NH residents, NH residents were older (mean age: 81.2 [95%CI 81.5-82.9] vs 76.1 [95%CI 75.8-76.4]), underwent more imaging (82.8% [95%CI 79.5-86.1] vs 71.6% [95%CI 69.9-73.3]), were administered fewer potentially inappropriate medications (PIMs) in the ED or upon discharge (9.5% [95%CI 6.2-2.7] vs 17.1% [95%CI 15.8-18.4]), and had a higher proportion of visits resulting in hospital admission (44.1% [95%CI 38.2-49.9] vs 26.0% [95%CI 23.3, 28.7]). CONCLUSIONS: Older NH residents presenting to the ED use more resources and are more likely to be hospitalized compared to older persons residing outside NHs. The resource-intensive nature of these visits highlights the importance of targeted, multi-disciplinary interventions that optimize ED care for this population.

Collecting verbal autopsies: improving and streamlining data collection processes using electronic tablets.

BACKGROUND: There is increasing interest in using verbal autopsy to produce nationally representative population-level estimates of causes of death. However, the burden of processing a large quantity of surveys collected with paper and pencil has been a barrier to scaling up verbal autopsy surveillance. Direct electronic data capture has been used in other large-scale surveys and can be used in verbal autopsy as well, to reduce time and cost of going from collected data to actionable information. METHODS: We collected verbal autopsy interviews using paper and pencil and using electronic tablets at two sites, and measured the cost and time required to process the surveys for analysis. From these cost and time data, we extrapolated costs associated with conducting large-scale surveillance with verbal autopsy. RESULTS: We found that the median time between data collection and data entry for surveys collected on paper and pencil was approximately 3 months. For surveys collected on electronic tablets, this was less than 2 days. For small-scale surveys, we found that the upfront costs of purchasing electronic tablets was the primary cost and resulted in a higher total cost. For large-scale surveys, the costs associated with data entry exceeded the cost of the tablets, so electronic data capture provides both a quicker and cheaper method of data collection. CONCLUSIONS: As countries increase verbal autopsy surveillance, it is important to consider the best way to design sustainable systems for data collection. Electronic data capture has the potential to greatly reduce the time and costs associated with data collection. For long-term, large-scale surveillance required by national vital statistical systems, electronic data capture reduces costs and allows data to be available sooner.

What is the optimal recall period for verbal autopsies? Validation study based on repeat interviews in three populations.

BACKGROUND: One key contextual feature in Verbal Autopsy (VA) is the time between death and survey administration, or recall period. This study quantified the effect of recall period on VA performance by using a paired dataset in which two VAs were administered for a single decedent. METHODS: This study used information from the Population Health Metrics Research Consortium (PHMRC) Study, which collected VAs for "gold standard" cases where cause of death (COD) was supported by clinical criteria. This study repeated VA interviews within 3-52 months of death in PHMRC study sites in Andhra Pradesh, India, and Bohol and Manila, Philippines. The final dataset included 2113 deaths interviewed twice and with recall periods ranging from 0 to 52 months. COD was assigned by the Tariff method and its accuracy determined by comparison with the gold standard COD. RESULTS: The probability of a correct diagnosis of COD decreased by 0.55 % per month in the period after death. Site of data collection and survey module also affected the probability of Tariff Method correctly assigning a COD. The probability of a correct diagnosis in VAs collected 3-11 months after death will, on average, be 95.9 % of that in VAs collected within 3 months of death. CONCLUSIONS: These findings suggest that collecting VAs within 3 months of death may improve the quality of the information collected, taking the need for a period of mourning into account. This study substantiates the WHO recommendation that it is reasonable to collect VAs up to 1 year after death providing it is accepted that probability of a correct diagnosis is likely to decline month by month during this period.

The paradox of verbal autopsy in cause of death assignment: symptom question unreliability but predictive accuracy.

BACKGROUND: We believe that it is important that governments understand the reliability of the mortality data which they have at their disposable to guide policy debates. In many instances, verbal autopsy (VA) will be the only source of mortality data for populations, yet little is known about how the accuracy of VA diagnoses is affected by the reliability of the symptom responses. We previously described the effect of the duration of time between death and VA administration on VA validity. In this paper, using the same dataset, we assess the relationship between the reliability and completeness of symptom responses and the reliability and accuracy of cause of death (COD) prediction. METHODS: The study was based on VAs in the Population Health Metrics Research Consortium (PHMRC) VA Validation Dataset from study sites in Bohol and Manila, Philippines and Andhra Pradesh, India. The initial interview was repeated within 3-52 months of death. Question responses were assessed for reliability and completeness between the two survey rounds. COD was predicted by Tariff Method. RESULTS: A sample of 4226 VAs was collected for 2113 decedents, including 1394 adults, 349 children, and 370 neonates. Mean question reliability was unexpectedly low (kappa = 0.447): 42.5 % of responses positive at the first interview were negative at the second, and 47.9 % of responses positive at the second had been negative at the first. Question reliability was greater for the short form of the PHMRC instrument (kappa = 0.497) and when analyzed at the level of the individual decedent (kappa = 0.610). Reliability at the level of the individual decedent was associated with COD predictive reliability and predictive accuracy. CONCLUSIONS: Families give coherent accounts of events leading to death but the details vary from interview to interview for the same case. Accounts are accurate but inconsistent; different subsets of symptoms are identified on each occasion. However, there are sufficient accurate and consistent subsets of symptoms to enable the Tariff Method to assign a COD. Questions which contributed most to COD prediction were also the most reliable and consistent across repeat interviews; these have been included in the short form VA questionnaire. Accuracy and reliability of diagnosis for an individual death depend on the quality of interview. This has considerable implications for the progressive roll out of VAs into civil registration and vital statistics (CRVS) systems.

Validating estimates of prevalence of non-communicable diseases based on household surveys: the symptomatic diagnosis study.

BACKGROUND: Easy-to-collect epidemiological information is critical for the more accurate estimation of the prevalence and burden of different non-communicable diseases around the world. Current measurement is restricted by limitations in existing measurement systems in the developing world and the lack of biometry tests for non-communicable diseases. Diagnosis based on self-reported signs and symptoms ("Symptomatic Diagnosis," or SD) analyzed with computer-based algorithms may be a promising method for collecting timely and reliable information on non-communicable disease prevalence. The objective of this study was to develop and assess the performance of a symptom-based questionnaire to estimate prevalence of non-communicable diseases in low-resource areas. METHODS: As part of the Population Health Metrics Research Consortium study, we collected 1,379 questionnaires in Mexico from individuals who suffered from a non-communicable disease that had been diagnosed with gold standard diagnostic criteria or individuals who did not suffer from any of the 10 target conditions. To make the diagnosis of non-communicable diseases, we selected the Tariff method, a technique developed for verbal autopsy cause of death calculation. We assessed the performance of this instrument and analytical techniques at the individual and population levels. RESULTS: The questionnaire revealed that the information on health care experience retrieved achieved 66.1% (95% uncertainty interval [UI], 65.6-66.5%) chance corrected concordance with true diagnosis of non-communicable diseases using health care experience and 0.826 (95% UI, 0.818-0.834) accuracy in its ability to calculate fractions of different causes. SD is also capable of outperforming the current estimation techniques for conditions estimated by questionnaire-based methods. CONCLUSIONS: SD is a viable method for producing estimates of the prevalence of non-communicable diseases in areas with low health information infrastructure. This technology can provide higher-resolution prevalence data, more flexible data collection, and potentially individual diagnoses for certain conditions.

A shortened verbal autopsy instrument for use in routine mortality surveillance systems.

BACKGROUND: Verbal autopsy (VA) is recognized as the only feasible alternative to comprehensive medical certification of deaths in settings with no or unreliable vital registration systems. However, a barrier to its use by national registration systems has been the amount of time and cost needed for data collection. Therefore, a short VA instrument (VAI) is needed. In this paper we describe a shortened version of the VAI developed for the Population Health Metrics Research Consortium (PHMRC) Gold Standard Verbal Autopsy Validation Study using a systematic approach. METHODS: We used data from the PHMRC validation study. Using the Tariff 2.0 method, we first established a rank order of individual questions in the PHMRC VAI according to their importance in predicting causes of death. Second, we reduced the size of the instrument by dropping questions in reverse order of their importance. We assessed the predictive performance of the instrument as questions were removed at the individual level by calculating chance-corrected concordance and at the population level with cause-specific mortality fraction (CSMF) accuracy. Finally, the optimum size of the shortened instrument was determined using a first derivative analysis of the decline in performance as the size of the VA instrument decreased for adults, children, and neonates. RESULTS: The full PHMRC VAI had 183, 127, and 149 questions for adult, child, and neonatal deaths, respectively. The shortened instrument developed had 109, 69, and 67 questions, respectively, representing a decrease in the total number of questions of 40-55%. The shortened instrument, with text, showed non-significant declines in CSMF accuracy from the full instrument with text of 0.4%, 0.0%, and 0.6% for the adult, child, and neonatal modules, respectively. CONCLUSIONS: We developed a shortened VAI using a systematic approach, and assessed its performance when administered using hand-held electronic tablets and analyzed using Tariff 2.0. The length of a VA questionnaire was shortened by almost 50% without a significant drop in performance. The shortened VAI developed reduces the burden of time and resources required for data collection and analysis of cause of death data in civil registration systems.

Improving performance of the Tariff Method for assigning causes of death to verbal autopsies.

BACKGROUND: Reliable data on the distribution of causes of death (COD) in a population are fundamental to good public health practice. In the absence of comprehensive medical certification of deaths, the only feasible way to collect essential mortality data is verbal autopsy (VA). The Tariff Method was developed by the Population Health Metrics Research Consortium (PHMRC) to ascertain COD from VA information. Given its potential for improving information about COD, there is interest in refining the method. We describe the further development of the Tariff Method. METHODS: This study uses data from the PHMRC and the National Health and Medical Research Council (NHMRC) of Australia studies. Gold standard clinical diagnostic criteria for hospital deaths were specified for a target cause list. VAs were collected from families using the PHMRC verbal autopsy instrument including health care experience (HCE). The original Tariff Method (Tariff 1.0) was trained using the validated PHMRC database for which VAs had been collected for deaths with hospital records fulfilling the gold standard criteria (validated VAs). In this study, the performance of Tariff 1.0 was tested using VAs from household surveys (community VAs) collected for the PHMRC and NHMRC studies. We then corrected the model to account for the previous observed biases of the model, and Tariff 2.0 was developed. The performance of Tariff 2.0 was measured at individual and population levels using the validated PHMRC database. RESULTS: For median chance-corrected concordance (CCC) and mean cause-specific mortality fraction (CSMF) accuracy, and for each of three modules with and without HCE, Tariff 2.0 performs significantly better than the Tariff 1.0, especially in children and neonates. Improvement in CSMF accuracy with HCE was 2.5%, 7.4%, and 14.9% for adults, children, and neonates, respectively, and for median CCC with HCE it was 6.0%, 13.5%, and 21.2%, respectively. Similar levels of improvement are seen in analyses without HCE. CONCLUSIONS: Tariff 2.0 addresses the main shortcomings of the application of the Tariff Method to analyze data from VAs in community settings. It provides an estimation of COD from VAs with better performance at the individual and population level than the previous version of this method, and it is publicly available for use.

Measuring causes of death in populations: a new metric that corrects cause-specific mortality fractions for chance.

BACKGROUND: Verbal autopsy is gaining increasing acceptance as a method for determining the underlying cause of death when the cause of death given on death certificates is unavailable or unreliable, and there are now a number of alternative approaches for mapping from verbal autopsy interviews to the underlying cause of death. For public health applications, the population-level aggregates of the underlying causes are of primary interest, expressed as the cause-specific mortality fractions (CSMFs) for a mutually exclusive, collectively exhaustive cause list. Until now, CSMF Accuracy is the primary metric that has been used for measuring the quality of CSMF estimation methods. Although it allows for relative comparisons of alternative methods, CSMF Accuracy provides misleading numbers in absolute terms, because even random allocation of underlying causes yields relatively high CSMF accuracy. Therefore, the objective of this study was to develop and test a measure of CSMF that corrects this problem. METHODS: We developed a baseline approach of random allocation and measured its performance analytically and through Monte Carlo simulation. We used this to develop a new metric of population-level estimation accuracy, the Chance Corrected CSMF Accuracy (CCCSMF Accuracy), which has value near zero for random guessing, and negative quality values for estimation methods that are worse than random at the population level. RESULTS: The CCCSMF Accuracy formula was found to be CCSMF Accuracy = (CSMF Accuracy - 0.632) / (1 - 0.632), which indicates that, at the population-level, some existing and commonly used VA methods perform worse than random guessing. CONCLUSIONS: CCCSMF Accuracy should be used instead of CSMF Accuracy when assessing VA estimation methods because it provides a more easily interpreted measure of the quality of population-level estimates.

Using verbal autopsy to measure causes of death: the comparative performance of existing methods.

BACKGROUND: Monitoring progress with disease and injury reduction in many populations will require widespread use of verbal autopsy (VA). Multiple methods have been developed for assigning cause of death from a VA but their application is restricted by uncertainty about their reliability. METHODS: We investigated the validity of five automated VA methods for assigning cause of death: InterVA-4, Random Forest (RF), Simplified Symptom Pattern (SSP), Tariff method (Tariff), and King-Lu (KL), in addition to physician review of VA forms (PCVA), based on 12,535 cases from diverse populations for which the true cause of death had been reliably established. For adults, children, neonates and stillbirths, performance was assessed separately for individuals using sensitivity, specificity, Kappa, and chance-corrected concordance (CCC) and for populations using cause specific mortality fraction (CSMF) accuracy, with and without additional diagnostic information from prior contact with health services. A total of 500 train-test splits were used to ensure that results are robust to variation in the underlying cause of death distribution. RESULTS: Three automated diagnostic methods, Tariff, SSP, and RF, but not InterVA-4, performed better than physician review in all age groups, study sites, and for the majority of causes of death studied. For adults, CSMF accuracy ranged from 0.764 to 0.770, compared with 0.680 for PCVA and 0.625 for InterVA; CCC varied from 49.2% to 54.1%, compared with 42.2% for PCVA, and 23.8% for InterVA. For children, CSMF accuracy was 0.783 for Tariff, 0.678 for PCVA, and 0.520 for InterVA; CCC was 52.5% for Tariff, 44.5% for PCVA, and 30.3% for InterVA. For neonates, CSMF accuracy was 0.817 for Tariff, 0.719 for PCVA, and 0.629 for InterVA; CCC varied from 47.3% to 50.3% for the three automated methods, 29.3% for PCVA, and 19.4% for InterVA. The method with the highest sensitivity for a specific cause varied by cause. CONCLUSIONS: Physician review of verbal autopsy questionnaires is less accurate than automated methods in determining both individual and population causes of death. Overall, Tariff performs as well or better than other methods and should be widely applied in routine mortality surveillance systems with poor cause of death certification practices.

Emergency Department-Based Physical Function Measures for Falls in Older Adults and Outcomes: A Secondary Analysis of GAPcare.

BACKGROUND AND PURPOSE: Falls are the leading reason for injury-related emergency department (ED) visits for older adults. The Geriatric Acute and Post-acute Fall Prevention Intervention (GAPcare), an in-ED intervention combining a medication therapy management session delivered by a pharmacist and a fall risk assessment and plan by a physical therapist, reduced ED revisits at 6 months among older adults presenting after a fall. Our objective was to evaluate the relationship between measures of function obtained in the ED and clinical outcomes. METHODS: This was a secondary analysis of data from GAPcare, a randomized controlled trial conducted from January 2018 to October 2019 at 2 urban academic EDs. Standardized measures of function (Timed Up and Go [TUG] test, Barthel Activity of Daily Living [ADL], Activity Measure for Post Acute Care [AM-PAC] 6 clicks) were collected at the ED index visit. We performed a descriptive analysis and hypothesis testing (chi square test and analysis of variance) to assess the relationship of functional measures with outcomes (ED disposition, ED revisits for falls, and place of residence at 6 months). Emergency department disposition status refers to discharge location immediately after the ED evaluation is complete (eg, hospital admission, original residence, skilled nursing facility). RESULTS AND DISCUSSION: Among 110 participants, 55 were randomized to the GAPcare intervention and 55 received usual care. Of those randomized to the intervention, 46 received physical therapy consultation. Median age was 81 years; participants were predominantly women (67%) and White (94%). Seventy-three (66%) were discharged to their original residence, 14 (13%) were discharged to a skilled nursing facility and 22 (20%) were admitted. There was no difference in ED disposition status by index visit Barthel ADLs (P = .371); however, TUG times were faster (P = .016), and AM-PAC 6 clicks score was higher among participants discharged to their original residence (P ≤ .001). Participants with slower TUG times at the index ED visit were more likely to reside in nursing homes by six months (P = .002), while Barthel ADL and AM-PAC 6 clicks did not differ between those residing at home and other settings. CONCLUSIONS: Measures of function collected at the index ED visit, such as the AM-PAC 6 clicks and TUG time, may be helpful at predicting clinical outcomes for older adults presenting for a fall. Based on our study findings, we suggest a novel workflow to guide the use of these clinical measures for ED patients with falls.

Nursing Home to Emergency Care Transition Form Has Limited Uptake But Improves Documentation.

Critical information gaps exist in nursing home-to-emergency department (NH-ED) transfer documentation. Standardization of forms may address these gaps. In a single state, a Continuity of Care Acute Care Transfer (CoC) Form was standardized and mandated to be used for all NH-ED transfers. The objective of this study was to evaluate adoption and effectiveness of the standardized CoC form. We used a random cross-sectional sample of 2019-2022 electronic health record encounter data to determine NH-ED documentation completeness after standardized CoC form implementation. Using patient characteristic adjusted linear and logistic regressions, we examined if CoC form standardization was associated with the number of key elements present on NH-ED transfer documentation and hospital admission, respectively. We then compared documentation completeness (out of 15 key data elements) to previously published pre-implementation data (2015-2016, n = 474). Of the 203 NH-ED transfer visits after CoC standardization (2019-2022), mean patient age was 81.8 years and 41.4% had dementia. Any NH-ED transfer form was present for 80.8% (n = 164) of encounters and 28.6% (n = 58) used the standardized CoC form. In comparison with the 2015-2016 data, there was an increase in documentation for functional baseline (20% to 30%), cognitive baseline (25% to 37%), and reason for transfer (25% to 82%). Post implementation, the use of the standardized CoC form was (1) associated with 2.55 (95% CI, 1.66-3.44) more key data elements documented and (2) not associated with a decreased odds of admission [odds ratio (OR), 1.06; 95% CI, 0.54-2.05] after controlling for confounders. Implementation of a statewide standardized CoC form for NH-ED transfers improved documentation of key elements, yet significant information gaps remain. Implementation evaluation is needed to identify how to achieve greater uptake of the form and improve the quality of information exchange between NHs and EDs.

Frailty assessment tools in the emergency department: A geriatric emergency department guidelines 2.0 scoping review.

Objective: Given the aging population and growing burden of frailty, we conducted this scoping review to describe the available literature regarding the use and impact of frailty assessment tools in the assessment and care of emergency department (ED) patients older than 60 years. Methods: A search was made of the available literature using the Covidence system using various search terms. Inclusion criteria comprised peer-reviewed literature focusing on frailty screening tools used for a geriatric population (60+ years of age) presenting to EDs. An additional search of PubMed, EBSCO, and CINAHL for articles published in the last 5 years was conducted toward the end of the review process (January 2023) to search specifically for literature describing interventions for frailty, yielding additional articles for review. Exclusion criteria comprised articles focusing on an age category other than geriatric and care environments outside the emergency care setting. Results: A total of 135 articles were screened for inclusion and 48 duplicates were removed. Of the 87 remaining articles, 20 were deemed irrelevant, leaving 67 articles for full-text review. Twenty-eight were excluded for not meeting inclusion criteria, leaving 39 full-text studies. Use of frailty screening tools were reported in the triage, care, and discharge decision-making phases of the ED care trajectory, with varying reports of usefulness for clinical decision-making. Conclusion: The literature reports tools, scales, and instruments for identifying frailty in older patients at ED triage; multiple frailty scores or tools exist with varying levels of utilization. Interventions for frailty directed at the ED environment were scant. Further research is needed to determine the usefulness of frailty identification in the context of emergency care, the effects of care delivery interventions or educational initiatives for front-line medical professionals on patient-oriented outcomes, and to ensure these initiatives are acceptable for patients.

Physician Views of Telehealth for Special Populations of Older Adults: Preliminary Findings.

This study's objective was to determine how frontline physicians perceived telehealth for older adults with sensory impairments, cognitive impairments, mobility challenges, or those receiving end-of-life care. We conducted a multiple-methods study of US emergency, geriatric, and primary care physicians. Phase 1 involved semi-structured interviews with 48 physicians on their experiences using telehealth with older adults. In phase 2, we used those qualitative findings to generate a web-based survey administered to 74 physicians. In phase 3, we reintegrated qualitative data to enrich survey results. We identified 3 key findings: (1) 50% of emergency physicians, 33% of geriatricians, and 18% of primary care physicians considered telehealth to be a poor substitute for providing end-of-life care (p = .68); (2) for hearing, vision, and cognitive impairments, 61%, 58%, and 54%, respectively, saw telehealth as a good or fair substitute for providing care (p = .14); and (3) 98% indicated that telehealth was a good or fair substitute for in-person care for those with mobility impairment (p < .001). Preferences and comfort using telehealth with older adults vary by clinical context, patient population, and physician specialty, requiring tailored adaptations.

Optimal Emergency Department Care Practices for Persons Living With Dementia: A Scoping Review.

OBJECTIVES: To summarize research on optimal emergency department (ED) care practices for persons living with dementia (PLWDs) and develop research priorities. DESIGN: Systematic scoping review. SETTINGS AND PARTICIPANTS: PLWDs in the ED. METHODS: The following Patient-Intervention-Comparison-Outcome (PICO) questions were developed: PICO 1, What components of emergency department care improve patient-centered outcomes for persons with dementia? PICO 2, How do emergency care needs for persons with dementia differ from other patients in the emergency department? A scoping review was conducted following PRISMA-ScR guidelines and presented to the Geriatric Emergency care Applied Research 2.0 Advancing Dementia Care network to inform research priorities. RESULTS: From the 6348 publications identified, 23 were abstracted for PICO 1 and 26 were abstracted for PICO 2. Emergency care considerations for PLWDs included functional dependence, behavioral and psychological symptoms of dementia, and identification of and management of pain. Concerns regarding ED care processes, the ED environment, and meeting a PWLD's basic needs were described. A comprehensive geriatric assessment and dedicated ED unit, a home hospital program, and a low-stimulation bed shade and contact-free monitor all showed improvement in patient-centered or health care use outcomes. However, all were single-site studies evaluating different outcomes. These results informed the following research priorities: (1) training and dementia care competencies; (2) patient-centric and care partner-centric evaluation interventions; (3) the impact of community- and identity-based factors on ED care for PLWDs; (4) economic or other implementation science measures to address viability; and (5) environmental, operational, personnel, system, or policy changes to improve ED care for PLWDs. CONCLUSIONS AND IMPLICATIONS: A wide range of components of both ED care practices and ED care needs for PLWDs have been studied. Although many interventions show positive results, the lack of depth and reproducible results prevent specific recommendations on best practices in ED care for PLWDs.

Emergency department-to-community care transition barriers: A qualitative study of older adults.

BACKGROUND: Over one-half of older adults are discharged to the community after emergency department (ED) visits, and studies have shown there is increased risk of adverse health outcomes in the immediate post-discharge period. Understanding the experiences of older adults during ED-to-community care transitions has the potential to improve geriatric emergency clinical care and inform intervention development. We therefore sought to assess barriers experienced by older adults during ED-to-community care transitions. METHODS: We conducted a qualitative analysis of community-dwelling cognitively intact patients aged 65 years and older receiving care in four diverse EDs from a single U.S. healthcare system. We constructed a conceptual framework a priori to guide the development and iterative revision of a codebook, used purposive sampling, and conducted recorded, semi-structured interviews using a standardized guide. Two researchers coded the professionally transcribed data using a combined deductive and inductive approach and analyzed transcripts to identify dominant themes and representative quotations. RESULTS: Among 25 participants, 20 (80%) were women and 17 (68%) were white. We identified four barriers during the ED-to-community care transition: (1) ED discharge process was abrupt with missing information regarding symptom explanation and performed testing, (2) navigating follow-up outpatient clinical care was challenging, (3) new physical limitations and fears hinder performance of baseline activities, and (4) major and minor ramifications for caregivers impact an older adult's willingness to request or accept assistance. CONCLUSIONS: Older adults identified barriers to successful ED-to-community care transitions that can inform the development of novel and effective interventions.

Emergency department care transition barriers: A qualitative study of care partners of older adults with cognitive impairment.

INTRODUCTION: After emergency department (ED) discharge, persons living with cognitive impairment (PLWCI) and their care partners are particularly at risk for adverse outcomes. We sought to identify the barriers experienced by care partners of PLWCI during ED discharge care transitions. METHODS: We conducted a qualitative study of 25 care partners of PLWCI discharged from four EDs. We used the validated 4AT and care partner-completed AD8 screening tools, respectively, to exclude care partners of older adults with concern for delirium and include care partners of older adults with cognitive impairment. We conducted recorded, semi-structured interviews using a standardized guide, and two team members coded and analyzed all professional transcriptions to identify emerging themes and representative quotations. RESULTS: Care partners' mean age was 56.7 years, 80% were female, and 24% identified as African American. We identified four major barriers regarding ED discharge care transitions among care partners of PLWCI: (1) unique care considerations while in the ED setting impact the perceived success of the care transition, (2) poor communication and lack of care partner engagement was a commonplace during the ED discharge process, (3) care partners experienced challenges and additional responsibilities when aiding during acute illness and recovery phases, and (4) navigating the health care system after an ED encounter was perceived as difficult by care partners. DISCUSSION: Our findings demonstrate critical barriers faced during ED discharge care transitions among care partners of PLWCI. Findings from this work may inform the development of novel care partner-reported outcome measures as well as ED discharge care transition interventions targeting care partners.

Perceptions of Signs of Addiction Among Opioid Naive Patients Prescribed Opioids in the Emergency Department.

OBJECTIVES: Patient knowledge deficits related to opioid risks, including lack of knowledge regarding addiction, are well documented. Our objective was to characterize patients' perceptions of signs of addiction. METHODS: This study utilized data obtained as part of a larger interventional trial. Consecutively discharged English-speaking patients, age >17 years, at an urban academic emergency department, with a new opioid prescription were enrolled from July 2015 to August 2017. During a follow-up phone interview 7 to 14 days after discharge, participants were asked a single question, "What are the signs of addiction to pain medicine?" Verbatim transcribed answers were analyzed using a directed content analysis approach and double coding. These codes were then grouped into themes. RESULTS: There were 325 respondents, 57% female, mean age 43.8 years, 70.1% privately insured. Ten de novo codes were added to the 11 DSM-V criteria codes. Six themes were identified: (1) effort spent acquiring opioids, (2) emotional and physical changes related to opioid use, (3) opioid use that is "not needed, (4) increasing opioid use, (5) an emotional relationship with opioids, and (6) the inability to stop opioid use. CONCLUSIONS: Signs of addiction identified by opioid naive patients were similar to concepts identified in medical definitions. However, participants' understanding also included misconceptions, omissions, and conflated misuse behaviors with signs of addiction. Identifying these differences will help inform patient-provider risk communication, providing an opportunity for counseling and prevention.