Annotation of Opioid Use Disorder Entity Modifiers in Clinical Text.

Natural Language Processing can be used to identify opioid use disorder in patients from clinical text1. We annotate a corpus of clinical text for mentions of concepts associated with unhealthy use of opiates including concept modifiers such as negation, subject, uncertainty, relation to document time and illicit use.

Delirium Due to Potentially Avoidable Hospitalizations Among Older Adults.

BACKGROUND: Delirium is a common complication during acute care hospitalizations in older adults. A substantial percentage of admissions are for ambulatory care-sensitive conditions (ACSCs) or potentially avoidable hospitalizations-conditions that might be treated early in the outpatient setting to prevent hospitalization and hospital complications. METHODS: This retrospective cross-sectional study examined rates of delirium among older adults hospitalized for ACSCs. Participants were 39 933 older adults ≥65 years of age admitted from January 1, 2015 to December 31, 2019 to general inpatient units and ICUs of a large Southeastern academic medical center. Delirium was defined as a score ≥ 2 on the Nursing Delirium Screening Scale or positive on the Confusion Assessment Method for the Intensive Care Unit during admission, and ACSCs were identified from the primary admission diagnosis using standardized definitions. Generalized linear mixed models were used to examine the association between ACSCs and delirium, compared with admissions for non-ACSC diagnoses, adjusting for covariates and repeated observations for individuals with multiple admissions. RESULTS: Delirium occurred in 15.6% of admissions for older adults. Rates were lower for ACSC admissions versus admissions for other conditions (13.9% vs 15.8%, p < .001). Older age and higher comorbidity were significant predictors of the development of delirium. CONCLUSIONS: Rates of delirium among older adults hospitalized for ACSCs were lower than rates for non-ACSC hospitalization but still substantial. Optimizing the treatment of ACSCs in the outpatient setting is an important goal not only for reducing hospitalizations but also for reducing risks for hospital-associated complications such as delirium.

Delirium Mediates Incidence of Hospital-Associated Disability Among Older Adults.

OBJECTIVE: To examine whether delirium predicts occurrence of hospital-associated disability (HAD), or functional decline after admission, among hospitalized older adults. DESIGN: Retrospective cross-sectional study. SETTING AND PARTICIPANTS: General inpatient (non-ICU) units of a large regional Southeastern US academic medical center, involving 33,111 older adults ≥65 years of age admitted from January 1, 2015, to December 31, 2019. METHODS: Delirium was defined as a score ≥2 on the Nursing Delirium Screening Scale (NuDESC) during hospital admission. HAD was defined as a decline on the Katz Activities of Daily Living (ADL) scale from hospital admission to discharge. Generalized linear mixed models were used to examine the association between delirium and HAD, adjusting for covariates and repeated observations with multiple admissions. We performed multivariate and mediation analyses to examine strength and direction of association between delirium and HAD. RESULTS: One-fifth (21.6%) of older adults developed HAD during hospitalization and experienced higher delirium rates compared to those not developing HAD (24.3% vs 14.3%, P < .001). Age, presence of delirium, Elixhauser Comorbidity Score, admission cognitive status, admission ADL function, and length of stay were associated (all P < .001) with incident HAD. Mediational analyses found 46.7% of the effect of dementia and 16.7% of the effect of comorbidity was due to delirium (P < .001). CONCLUSIONS AND IMPLICATIONS: Delirium significantly increased the likelihood of HAD within a multivariate predictor model that included comorbidity, demographics, and length of stay. For dementia and comorbidity, mediation analysis showed a significant portion of their effect attributable to delirium. Overall, these findings suggest that reducing delirium rates may diminish HAD rates.

Hospital-associated disability due to avoidable hospitalizations among older adults.

BACKGROUND: Hospital-associated disability (HAD) is a common complication during the course of acute care hospitalizations in older adults. Many admissions are for ambulatory care sensitive conditions (ACSCs), considered potentially avoidable hospitalizations-conditions that might be treated in outpatient settings to prevent hospitalization and HAD. We compared the incidence of HAD between older adults hospitalized for ACSCs versus those hospitalized for other diagnoses. METHODS: We conducted a retrospective cohort study in inpatient (non-ICU) medical and surgical units of a large southeastern regional academic medical center. Participants were 38,960 older adults ≥ 65 years of age admitted from January 1, 2015, to December 31, 2019. The primary outcome was HAD, defined as decline on the Katz Activities of Daily Living (ADL) scale from hospital admission to discharge. We used generalized linear mixed models to examine differences in HAD between hospitalizations with a primary diagnosis for an ACSC using standard definitions versus primary diagnosis for other conditions, adjusting for covariates and repeated observations for individuals with multiple hospitalizations. RESULTS: We found that 10% of older adults were admitted for an ACSC, with rates of HAD in those admitted for ACSCs lower than those admitted for other conditions (16% vs. 20.7%, p < 0.001). Age, comorbidity, admission functional status, and admission cognitive impairment were significant predictors for development of HAD. ACSC admissions to medical and medical/surgical services had lower odds of HAD compared with admissions for other conditions, with no significant differences between ACSC and non-ACSC admissions to surgical services. CONCLUSIONS: Rates of HAD among older adults hospitalized for ACSCs are substantial, though lower than rates of HAD with hospitalization for other conditions, reflecting that acute care hospitalization is not a benign event in this population. Treatment of ACSCs in the outpatient setting could be an important component of efforts to reduce HAD.

Identification of Gout Flares in Chief Complaint Text Using Natural Language Processing.

Many patients with gout flares treated in the Emergency Department (ED) often do not receive optimal continuity of care after an ED visit. Thus, developing methods to identify patients with gout flares in the ED and referring them to appropriate outpatient gout care is required. While Natural Language Processing (NLP) has been used to detect gout flares retrospectively, it is much more challenging to identify patients prospectively during an ED visit where documentation is usually minimal. We annotate a corpus of ED triage nurse chief complaint notes for the presence of gout flares and implement a simple algorithm for gout flare ED alerts. We show that the chief complaint alone has strong predictive power for gout flares. We make available a de-identified version of this corpus annotated for gout mentions, which is to our knowledge the first free text chief complaint clinical corpus available.