Deploying a national clinical text processing infrastructure.

OBJECTIVES: Clinical text processing offers a promising avenue for improving multiple aspects of healthcare, though operational deployment remains a substantial challenge. This case report details the implementation of a national clinical text processing infrastructure within the Department of Veterans Affairs (VA). METHODS: Two foundational use cases, cancer case management and suicide and overdose prevention, illustrate how text processing can be practically implemented at scale for diverse clinical applications using shared services. RESULTS: Insights from these use cases underline both commonalities and differences, providing a replicable model for future text processing applications. CONCLUSIONS: This project enables more efficient initiation, testing, and future deployment of text processing models, streamlining the integration of these use cases into healthcare operations. This project implementation is in a large integrated health delivery system in the United States, but we expect the lessons learned to be relevant to any health system, including smaller local and regional health systems in the United States.

Characterization of mesothelioma and tissues present in contrast-enhanced thoracic CT scans.

PURPOSE: The purpose of this study was to characterize the Hounsfield unit (HU) distributions of mesothelioma and other tissues present in contrast-enhanced thoracic CT scans, to compare the HU distributions of mesothelioma, muscle, and liver by scanner and reconstruction filter/kernel combination, and to assess interpatient HU distribution variability. METHODS: The database consisted of 28 contrast-enhanced thoracic CT scans from different patients. For each scan, regions of interest were manually outlined within each of 13 tissues, including mesothelioma. For each tissue, the empirical percentiles in HU values were calculated along with the interpatient variability. The HU distributions of select tissues were compared across three different scanner and reconstruction filter/kernel combinations. RESULTS: The HU distributions of blood-containing tissues demonstrated substantial overlap, as did the HU distributions of pleural effusion, mesothelioma, muscle, and liver. The HU distribution of fat had the least overlap with the other tissues. Fat and muscle had the lowest interpatient HU variability and the narrowest HU distributions, while blood-containing tissues had the highest interpatient HU variability. A soft-tissue reconstruction filter/kernel yielded the narrowest HU distribution, and fat with artifact had the widest HU distribution. CONCLUSIONS: Characterization of tissues in CT scans enhances the understanding of those tissues' HU distributions. Due to their overlapping HU distributions and close spatial proximity to one another, separating pleural effusion, mesothelioma, muscle, and liver from one another is a difficult task based on HU value thresholding alone. The results illustrate the wide distributions and large variability that exist for tissues present in clinical thoracic CT scans.

Heel calf capillary-support pressure in lithotomy positions.

A three-part analysis was undertaken to increase understanding of the occurrence of pressure ulcers in lithotomy positions. An innovative measuring device was used to determine capillary pressure. Ankle blood pressure was measured compared to ankle height in 11 participants. Ankle systolic and diastolic pressure decreased approximately 20 mmHg per foot of elevation. Calf and heel capillary-support pressures were measured in 15 participants in the standard lithotomy position. Capillary-support pressure for the calf was substantially less than for the heel. Heel capillary-support pressures were measured in 16 participants in the high lithotomy position. As heel height increased, capillary-support pressure also increased.

CT-based pulmonary artery measurements for the assessment of pulmonary hypertension.

RATIONALE AND OBJECTIVES: Pulmonary hypertension (PH) is a complex and fatal disease that is difficult to diagnose noninvasively. This study evaluated previously published computed tomography-based vessel measurement criteria and investigated the predictive power and diagnostic ability of the main pulmonary artery diameter (MPAD) and the ratio of MPAD to aorta diameter (rPA). MATERIALS AND METHODS: The database for this study consisted of 175 PH patients (for whom mean pulmonary artery pressure [mPAP] was known), 16 patients without PH but with known mPAP (non-PH patients), and 114 "normal" patients without known mPAP. The performance of previously published criteria, MPAD > 29 mm and rPA > 1, was determined. The relationship between vessel measurements and mPAP was evaluated through correlation and linear regression analysis. The ability of these measurements to discriminate between patients with and without PH was determined by receiver operating characteristic analysis. RESULTS: For discriminating between PH and "normal" patients, the sensitivity and specificity of the criterion MPAD > 29 mm were 0.89 (0.84-0.93) and 0.83 (0.76-0.90), respectively, and the sensitivity and specificity of the criterion rPA > 1 were 0.89 (0.85-0.94) and 0.82 (0.74-0.89), respectively. At a specificity of 0.95 in the task of separating PH and "normal" patients, the sensitivity of MPAD was 0.81 (0.72-0.90) and the sensitivity of rPA was 0.76 (0.66-0.85), but the specificity for both decreased when non-PH patients were included. For the combined PH and non-PH patient groups, the correlation between the vessel measurements and mPAP was significant but low, and the ability of the vessel measurements to predict mPAP was limited. CONCLUSION: This study found that the sensitivity of previously published vessel criteria for identifying PH patients is high, but the specificity may not be high enough for routine use in a clinical patient population.