Validation of Prediction Models for Critical Care Outcomes Using Natural Language Processing of Electronic Health Record Data.

Importance: Accurate prediction of outcomes among patients in intensive care units (ICUs) is important for clinical research and monitoring care quality. Most existing prediction models do not take full advantage of the electronic health record, using only the single worst value of laboratory tests and vital signs and largely ignoring information present in free-text notes. Whether capturing more of the available data and applying machine learning and natural language processing (NLP) can improve and automate the prediction of outcomes among patients in the ICU remains unknown.

Geographic Variation in Postoperative Imaging for Low-Risk Breast Cancer.

The objective of this study was to examine the presence and magnitude of US geographic variation in use rates of both recommended and high-cost imaging in young patients with early-stage breast cancer during the 18 month period after surgical treatment of their primary tumor. Using the Truven Health MarketScan Commercial Database, a descriptive analysis was conducted of geographic variation in annual rates of dedicated breast imaging and high-cost body imaging of 36,045 women aged 18 to 64 years treated with surgery for invasive unilateral breast cancer between 2010 and 2012. Multivariate hierarchical analysis examined the relationship between likelihood of imaging and patient characteristics, with metropolitan statistical area (MSA) serving as a random effect.

Revisit rates and associated costs after an emergency department encounter: a multistate analysis.

Background: Return visits to the emergency department (ED) or hospital after an index ED visit strain the health system, but information about rates and determinants of revisits is limited.

Objective: To describe revisit rates, variation in revisit rates by diagnosis and state, and associated costs.

Design: Observational study using the Healthcare Cost and Utilization Project databases.

Thirty-day hospital readmissions in systemic lupus erythematosus: predictors and hospital- and state-level variation.

Objective: Systemic lupus erythematosus (SLE) has one of the highest hospital readmission rates among chronic conditions. This study was undertaken to identify patient-level, hospital-level, and geographic predictors of 30-day hospital readmissions associated with SLE.

Methods: Using hospital discharge databases from 5 geographically dispersed states, we studied all-cause readmission of SLE patients between 2008 and 2009.

Multidisciplinary Critical Care and Intensivist Staffing: Results of a Statewide Survey and Association With Mortality.

Purpose: The role of multidisciplinary teams in improving the care of intensive care unit (ICU) patients is not well defined, and it is unknown whether the use of such teams helps to explain prior research suggesting improved mortality with intensivist staffing. We sought to investigate the association between multidisciplinary team care and survival of medical and surgical patients in nonspecialty ICUs.

Materials And Methods: We conducted a community-based, retrospective cohort study of data from 60 330 patients in 181 hospitals participating in a statewide public reporting initiative, the California Hospital Assessment and Reporting Taskforce (CHART).

N-gram support vector machines for scalable procedure and diagnosis classification, with applications to clinical free text data from the intensive care unit.

Background: Existing risk adjustment models for intensive care unit (ICU) outcomes rely on manual abstraction of patient-level predictors from medical charts. Developing an automated method for abstracting these data from free text might reduce cost and data collection times.

Objective: To develop a support vector machine (SVM) classifier capable of identifying a range of procedures and diagnoses in ICU clinical notes for use in risk adjustment.

The effect of race and ethnicity on outcomes among patients in the intensive care unit: a comprehensive study involving socioeconomic status and resuscitation preferences.

Objective: We sought to determine whether race or ethnicity is independently associated with mortality or intensive care unit length of stay among critically ill patients after accounting for patients' clinical and demographic characteristics including socioeconomic status and resuscitation preferences.

Design: Historical cohort study of patients hospitalized in intensive care units.

Setting: Adult intensive care units in 35 California hospitals during the years 2001-2004.

Predictors of early postdischarge mortality in critically ill patients: a retrospective cohort study from the California Intensive Care Outcomes project.

Purpose: Existing intensive care unit (ICU) mortality measurement systems address in-hospital mortality only. However, early postdischarge mortality contributes significantly to overall 30-day mortality. Factors associated with early postdischarge mortality are unknown.

Relationship between discharge practices and intensive care unit in-hospital mortality performance: evidence of a discharge bias.

Context: Current intensive care unit performance measures include in-hospital mortality after intensive care unit admission. This measure does not account for deaths occurring after transfer to another hospital or soon after discharge and therefore, may be biased.

Objective: Determine how transfer rates to other acute care hospitals and early post-discharge mortality rates impact hospital performance assessments using an in-hospital mortality model.

Mortality probability model III and simplified acute physiology score II: assessing their value in predicting length of stay and comparison to APACHE IV.

Background: To develop and compare ICU length-of-stay (LOS) risk-adjustment models using three commonly used mortality or LOS prediction models.

Methods: Between 2001 and 2004, we performed a retrospective, observational study of 11,295 ICU patients from 35 hospitals in the California Intensive Care Outcomes Project. We compared the accuracy of the following three LOS models: a recalibrated acute physiology and chronic health evaluation (APACHE) IV-LOS model; and models developed using risk factors in the mortality probability model III at zero hours (MPM(0)) and the simplified acute physiology score (SAPS) II mortality prediction model.

Variation in ICU risk-adjusted mortality: impact of methods of assessment and potential confounders.

Background: Federal and state agencies are considering ICU performance assessment and public reporting; however, an accurate method for measuring performance must be selected. In this study, we determine whether a substantial variation in ICU mortality performance still exists in modern ICUs, and compare the predictive accuracy, reliability, and data burden of existing ICU risk-adjustment models.

Methods: A retrospective chart review of 11,300 ICU patients from 35 California hospitals from 2001 to 2004 was performed.

Race/ethnicity, socioeconomic status and the health of pregnant women.

We examined how traditional (income, education) and nontraditional (public assistance, material deprivation, subjective social standing) socioeconomic status (SES) indicators were associated with self-rated health, physical functioning, and depression in ethnically diverse pregnant women. Using multiple regression, we estimated the association of race/ethnicity (African American, Latino, Asian/Pacific Islander (PI) and white) and sets of SES measures on each health measure. Education, material deprivation, and subjective social standing were independently associated with all health measures.

Changes in the health status of women during and after pregnancy.

Objective: To characterize the changes in health status experienced by a multi-ethnic cohort of women during and after pregnancy.

Design: Observational cohort.

Setting/participants: Pregnant women from 1 of 6 sites in the San Francisco area (N=1,809).

Prepregnancy health status and the risk of preterm delivery.

Background: Despite extensive evaluation, our understanding of risk factors for premature delivery is incomplete.

Objective: To examine whether a woman's health status and risk factors before pregnancy are associated with a woman's risk of preterm delivery, independent of risk factors that occur during pregnancy.

Design, Setting, And Participants: Prospective cohort of pregnant women in the San Francisco Bay area who delivered a singleton infant (n = 1619).

Differences in mortality among patients with community-acquired pneumonia in California by ethnicity and hospital characteristics.

Purpose: To determine ethnic disparities in mortality for patients with community-acquired pneumonia, and the potential effects of hospital characteristics on disparities, we compared the risk-adjusted mortality of white, African American, Hispanic, and Asian American patients hospitalized for community-acquired pneumonia.

Methods: We studied patients discharged with community-acquired pneumonia in 1996 from an acute care hospital in California (n = 54,874). Logistic regression models were used to examine the association between ethnicity and hospital characteristics and 30-day mortality after adjusting for clinical characteristics.