End-Of-Life Care in the Time of COVID-19: Communication Matters More Than Ever.

CONTEXT: The COVID-19 pandemic resulted in visitation restrictions across most health care settings, necessitating the use of remote communication to facilitate communication among families, patients and health care teams. OBJECTIVE: To examine the impact of remote communication on families' evaluation of end-of-life care during the COVID-19 pandemic. METHODS: Retrospective, cross-sectional, mixed methods study using data from an after-death survey administered from March 17-June 30, 2020. The primary outcome was the next of kin's global assessment of care during the Veteran's last month of life. RESULTS: Data were obtained from the next-of-kin of 328 Veterans who died in an inpatient unit (i.e., acute care, intensive care, nursing home, hospice units) in one of 37 VA medical centers with the highest numbers of COVID-19 cases. The adjusted percentage of bereaved families reporting excellent overall end-of-life care was statistically significantly higher among those reporting Very Effective remote communication compared to those reporting that remote communication was Mostly, Somewhat, or Not at All Effective (69.5% vs. 35.7%). Similar differences were observed in evaluations of remote communication effectiveness with the health care team. Overall, 81.3% of family members who offered positive comments about communication with either the Veteran or the health care team reported excellent overall end-of-life care vs. 28.4% who made negative comments. CONCLUSIONS: Effective remote communication with the patient and the health care team was associated with significantly better ratings of the overall experience of end-of-life care by bereaved family members. Our findings offer timely insights into the importance of remote communication strategies.

Psychometric Evaluation of a Pain Intensity Measure for Persons with Dementia.

OBJECTIVE: The goal of this study was to conduct initial psychometric analyses of a seven-item pain intensity measure for persons with dementia (PIMD) that was developed using items from existing pain observational measures. DESIGN AND METHODS: We evaluated validity by examining associations with an expert clinician's pain intensity rating (ECPIR) and an established pain observation tool (Mobilization Observation Behaviour Intensity Dementia [MOBID]). We also examined correlations between the PIMD and known correlates of pain: depression, sleep disturbances, agitation, painful diagnoses, and caregiver pain reports. We examined the differences between PIMD scores for "at rest" and "during movement" observations. We assessed reliability by calculating Cronbach's alpha and estimating inter-rater reliability using intraclass correlations (ICCs). Finally, we examined whether six additional "recent changes in behavior" items improved the PIMD's ability to predict expert clinicians' pain ratings. SETTING: Sixteen nursing homes located in Alabama, Georgia, Pennsylvania, and New Jersey. PARTICIPANTS: One hundred ninety residents with moderate to severe cognitive impairment, mean age of 84 years, 49.5% female, and 70% white. RESULTS: PIMD during movement scores were highly correlated with the ECPIR and overall MOBID scores. As expected, there were large differences between at rest and during movement PIMD scores. Associations of PIMD with known correlates of pain were generally low and statistically nonsignificant. Internal consistency was supported with a Cronbach alpha of 0.72 and an inter-rater ICC of 0.82 for during movement PIMD scores. CONCLUSIONS: Initial evaluation of the PIMD supports its validity and reliability. Additional testing is needed to evaluate the tool's sensitivity to changes in pain intensity.

Developing a Pain Intensity Measure for Persons with Dementia: Initial Construction and Testing.

OBJECTIVE: The goal of this study was to identify a limited set of pain indicators that were most predicive of physical pain. We began with 140 items culled from existing pain observation tools and used a modified Delphi approach followed by statistical analyses to reduce the item pool. METHODS: Through the Delphi Method, we created a candidate item set of behavioral indicators. Next, trained staff observed nursing home residents and rated the items on scales of behavior intensity and frequency. We evaluated associations among the items and expert clinicians' assessment of pain intensity. SETTING: Four government-owned nursing homes and 12 community nursing homes in Alabama and Southeastern Pennsylvania. PARTICIPANTS: Ninety-five residents (mean age = 84.9 years) with moderate to severe cognitive impairment. RESULTS: Using the least absolute shrinkage and selection operator model, we identified seven items that best predicted clinicians' evaluations of pain intensity. These items were rigid/stiff body or body parts, bracing, complaining, expressive eyes, grimacing, frowning, and sighing. We also found that a model based on ratings of frequency of behaviors did not have better predictive ability than a model based on ratings of intensity of behaviors. CONCLUSIONS: We used two complementary approaches-expert opinion and statistical analysis-to reduce a large pool of behavioral indicators to a parsimonious set of items to predict pain intensity in persons with dementia. Future studies are needed to examine the psychometric properties of this scale, which is called the Pain Intensity Measure for Persons with Dementia.