Background Deaths from pneumonia were decreasing globally prior to the COVID-19 pandemic, but it is unclear whether this was due to changes in patient populations, illness severity, diagnosis, hospitalization thresholds, or treatment. Using clinical data from the electronic health record among a national cohort of patients initially diagnosed with pneumonia, we examined temporal trends in severity of illness, hospitalization, and short- and long-term deaths. Design Retrospective cohort Participants All patients >18 years presenting to emergency departments (EDs) at 118 VA Medical Centers between 1/1/2006 and 12/31/2016 with an initial clinical diagnosis of pneumonia and confirmed by chest imaging report. Exposures Year of encounter. Main Measures Hospitalization and 30-day and 90-day mortality. Illness severity was defined as the probability of each outcome predicted by machine learning predictive models using age, sex, comorbidities, vital signs, and laboratory data from encounters during years 2006–2007, and similar models trained on encounters from years 2015 to 2016. We estimated the changes in hospitalizations and 30-day and 90-day mortality between the first and the last 2 years of the study period accounted for by illness severity using time covariate decompositions with model estimates. Results Among 196,899 encounters across the study period, hospitalization decreased from 71 to 63%, 30-day mortality 10 to 7%, 90-day mortality 16 to 12%, and 1-year mortality 29 to 24%. Comorbidity risk increased, but illness severity decreased. Decreases in illness severity accounted for 21–31% of the decrease in hospitalizations, and 45–47%, 32–24%, and 17–19% of the decrease in 30-day, 90-day, and 1-year mortality. Findings were similar among underrepresented patients and those with only hospital discharge diagnosis codes. Conclusions Outcomes for community-onset pneumonia have improved across the VA healthcare system after accounting for illness severity, despite an increase in cases and comorbidity burden. Supplementary Information The online version contains supplementary material available at 10.1007/s11606-022-07413-8.

Objective: Surveillance of non–ventilator-associated hospital-acquired pneumonia (NV-HAP) is complicated by subjectivity and variability in diagnosing pneumonia. We compared a fully automatable surveillance definition using routine electronic health record data to manual determinations of NV-HAP according to surveillance criteria and clinical diagnoses. Methods: We retrospectively applied an electronic surveillance definition for NV-HAP to all adults admitted to Veterans’ Affairs (VA) hospitals from January 1, 2015, to November 30, 2020. We randomly selected 250 hospitalizations meeting NV-HAP surveillance criteria for independent review by 2 clinicians and calculated the percent of hospitalizations with (1) clinical deterioration, (2) CDC National Healthcare Safety Network (CDC-NHSN) criteria, (3) NV-HAP according to a reviewer, (4) NV-HAP according to a treating clinician, (5) pneumonia diagnosis in discharge summary; and (6) discharge diagnosis codes for HAP. We assessed interrater reliability by calculating simple agreement and the Cohen κ (kappa). Results: Among 3.1 million hospitalizations, 14,023 met NV-HAP electronic surveillance criteria. Among reviewed cases, 98% had a confirmed clinical deterioration; 67% met CDC-NHSN criteria; 71% had NV-HAP according to a reviewer; 60% had NV-HAP according to a treating clinician; 49% had a discharge summary diagnosis of pneumonia; and 82% had NV-HAP according to any definition according to at least 1 reviewer. Only 8% had diagnosis codes for HAP. Interrater agreement was 75% (κ = 0.50) for CDC-NHSN criteria and 78% (κ = 0.55) for reviewer diagnosis of NV-HAP. Conclusions: Electronic NV-HAP surveillance criteria correlated moderately with existing manual surveillance criteria. Reviewer variability for all manual assessments was high. Electronic surveillance using clinical data may therefore allow for more consistent and efficient surveillance with similar accuracy compared to manual assessments or diagnosis codes.

Despite research suggesting that the Glasgow Coma Scale (GCS) has limitations, its results are regarded as the gold standard in assessments of patient consciousness levels. This article discusses and evaluates the GCS, and reviews the literature on the advantages and limitations of the tool, and considers whether the Lowry Coma Record (Lowry 1999) should be used instead.

Background Surveillance of Non-Ventilator Hospital-Acquired Pneumonia (NV-HAP) is limited by the ambiguity in diagnosing pneumonia. We implemented electronic surveillance criteria for NV-HAP across the VA healthcare system and tested for reliability, validity and meaning of the electronic criteria vs manual chart review. Methods We defined NV-HAP surveillance criteria as oxygen deterioration concurrent with fever or abnormal WBC count, ≥3 days of antibiotics, and orders for chest imaging. We applied these criteria to EHR data from all patients hospitalized ≥3 days at all VA acute care facilities from 1/1/2015-12/31/2020 and calculated NV-HAP incidence and inpatient mortality. Clinician reviewers used a consensus review guide to independently review and adjudicate 47 cases meeting NV-HAP surveillance criteria for 1) clinical deterioration, 2) CDC-NHSN pneumonia criteria, 3) treating clinicians’ assessment, and 4) reviewer’s diagnosis. All reviewers subsequently adjudicated all cases and conducted an error analysis to identify sources of discordance. Results Among 2.3M hospitalizations, 14,023 met NV-HAP surveillance criteria (0.6 per 100 admissions). Inpatient mortality was 26% (vs 2% for non-flagged hospitalizations). Among 47 hospitalizations flagged by surveillance criteria, 45 (97%) had a confirmed clinical deterioration, (the other 2 were immediate post-operative cases), 20 (43%) met CDC-NHSN pneumonia criteria, 21 (47%) had possible pneumonia per treating clinicians, and 25 (53%) had possible or probable NV-HAP per reviewers. Agreement among the 3 reviewers before adjudication was 51% (Fleiss’ κ 0.43) for CDC-NHSN and 58% (Fleiss’ κ 0.33) for NV-HAP. The most common source of discordance between reviewers was chest imaging classification (15/19 discordant cases). Conclusion NV-HAP electronic surveillance criteria demonstrated high precision for identifying clinical deterioration and moderate concordance with CDC-NHSN pneumonia criteria or reviewer diagnosis. Agreement between electronic surveillance criteria vs manual chart review was low but similar to agreement amongst manual reviewers applying NHSN criteria. Electronic surveillance may provide greater consistency than human review while facilitating wide-scale automated surveillance. Disclosures Chanu Rhee, MD, MPH, UpToDate (Other Financial or Material Support, Chapter Author) Michael Klompas, MD, MPH, UpToDate (Other Financial or Material Support, Chapter Author)