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). MEASUREMENTS AND MAIN RESULTS:Women who agreed to participate were asked to complete a series of telephone surveys that ascertained health status as well as demographic and medical factors. Substantial changes in health status occurred over the course of pregnancy. For example, physical function declined, from a mean score of 95.2 prior to pregnancy to 58.1 during the third trimester (0-100 scale, where 100 represents better health), and improved during the postpartum period (mean score, 90.7). The prevalence of depressive symptoms rose from 11.7% prior to pregnancy to 25.2% during the third trimester, and then declined to 14.2% during the postpartum period. Insufficient money for food or housing and lack of exercise were associated with poor health status before, during, and after pregnancy. CONCLUSIONS:Women experience substantial changes in health status during and after pregnancy. These data should guide the expectations of women, their health care providers, and public policy. W hile pregnancy is a common event for reproductive-age women, surprisingly little has been published about the physical and emotional changes that typically occur during pregnancy and the postpartum period.1-3 Better understanding of the changes in health status that occur over the course of pregnancy could help women define their expectations, and provide data to inform public policies related to the health and function of women. For example, three quarters of reproductive-age women are in the work force. 4 Over 90% of working women continue to work while pregnant, with the majority working into the month before delivery. Of the 60% of women who return to work within 1 year of the birth of their first child, two thirds are back at work within 3 months. 4 Evidence about the health status of women could inform policies related to leave and disability around the time of pregnancy. Finally, better characterization of the physical and emotional changes that typically occur would allow the definition of risk factors for greater or persistent declines in functional status, so that women at risk could be targeted for interventions to promote health and well-being. Because primary care providers provide care for women of reproductive age before, during, and after pregnancy, it is particularly important for them to be aware of the changes in health status that women experience around the time of pregnancy. 5,6Several small studies suggest that the functional status of reproductive-age women is lower during pregnancy and the postpartum period than at other times. [1][2][3]7 A study of 393Canadian women found that pregnant women had more limitations due to emotional problems, and lower levels of vitality, physical functioning, and social functioning than a sample of nonpregnant women. 2 Less is kno...

A broader focus on the health of women prior to pregnancy may improve rates of preterm delivery.

Agency for Healthcare Research and Quality.

Objective We sought to determine whether race or ethnicity is independently associated with mortality or intensive care unit (ICU) length of stay (LOS) 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. Patients A total of 9,518 ICU patients (6334 white, 655 black, 1917 Hispanic and 612 Asian/Pacific Islander patients). Measurements and Main Results The primary outcome was risk-adjusted mortality and a secondary outcome was risk-adjusted ICU LOS. Crude hospital mortality was 15.9% among the entire cohort. Asian patients had the highest crude hospital mortality at 18.6% and black patients had the lowest at 15.0%. After adjusting for age and gender, Hispanic and Asian patients had a higher risk of death compared to white patients, but these differences were not significant after additional adjustment for severity of illness. Black patients had more acute physiologic derangements at ICU admission and longer unadjusted ICU LOS. ICU LOS was not significantly different among racial/ethnic groups after adjustment for demographic, clinical, socioeconomic factors and do-not-resuscitate status. In an analysis restricted only to those who died, decedent black patients averaged 1.1 additional days in the ICU (95% CI – 0.26 to 2.6) compared to white patients who died, although this was not statistically significant. Conclusions Hospital mortality and ICU LOS did not differ by race or ethnicity among this diverse cohort of critically ill patients after adjustment for severity of illness, resuscitation status, SES, insurance status and admission type. Black patients had more acute physiologic derangements at ICU admission and were less likely to have a DNR order. These results suggest that among ICU patients, there are not racial or ethnic differences in mortality within individual hospitals. If disparities in ICU care exist, they may be explained by differences in the quality of care provided by hospitals that serve high proportions of minority patients.

Objective Systemic lupus erythematosus (SLE) has among the highest hospital readmission rates among chronic conditions. We sought to identify patient-level, hospital-level, and geographic predictors of 30-day hospital readmissions in SLE. Methods Using hospital discharge databases from 5 geographically dispersed states, we performed a study of all-cause SLE readmissions between 2008 and 2009. We evaluated each hospitalization as a possible index event leading up to a readmission, our primary outcome. We accounted for clustering of hospitalizations within patients and within hospitals and adjusted for hospital case-mix. Using multi-level mixed-effects logistic regression, we examined factors associated with 30-day readmissions and calculated risk-standardized hospital-level and state-level readmission rates. Results We examined 55,936 hospitalizations among 31,903 patients with SLE. 9,244 (16.5%) hospitalizations resulted in readmission within 30 days. In adjusted analyses, age was inversely related to risk of readmission. Black and Hispanic patients were more likely to be readmitted compared to white patients, as were those with Medicare or Medicaid insurance (versus private insurance). Several lupus clinical characteristics, including lupus nephritis, serositis and thrombocytopenia were associated with readmission. Readmission rates varied significantly between hospitals after accounting for patient-level clustering and hospital case mix. There was also geographic variation, with risk-adjusted readmission rates lower in New York and higher in Florida compared to California. Conclusions We found that about 1 in 6 hospitalized patients with SLE were readmitted within 30 days, with higher rates in historically underserved populations. Significant geographic and hospital-level variation in risk-adjusted readmission rates suggests potential for quality improvement.

Key Points Question Can a prediction model for mortality in the intensive care unit be improved by using more laboratory values, vital signs, and clinical text in electronic health records? Findings In this cohort study of 101 196 patients in the intensive care unit, a machine learning–based model using all available measurements of vital signs and laboratory values, plus clinical text, exhibited good calibration and discrimination in predicting in-hospital mortality, yielding an area under the receiver operating characteristic curve of 0.922. Meaning Applying methods from machine learning and natural language processing to information already routinely collected in electronic health records, including laboratory test results, vital signs, and clinical free-text notes, significantly improves a prediction model for mortality in the intensive care unit compared with approaches that use only the most abnormal vital sign and laboratory values.

No abstract

Importance Commercial virtual visits are an increasingly popular model of care for the management of common, acute illnesses. In commercial virtual visits, patients access a website to be connected synchronously—via videoconference, telephone, or webchat—to a physician with whom they have no prior relationship. There has been no assessment of whether the care delivered through those websites is similar, or whether quality varies among the sites. Objective To assess the variation in quality of care among virtual visit companies. Design We performed an audit study using trained standardized patients. Setting The standardized patients presented to commercial virtual visit companies with six common, acute illnesses (ankle pain, streptococcal pharyngitis, viral pharyngitis, acute rhinosinusitis, low back pain, and recurrent urinary tract infection). Participants The eight commercial virtual visit websites with the highest web traffic. Main Outcome Measures The primary outcomes were completeness of histories and physical examinations, naming the correct diagnosis (versus an incorrect diagnosis or not naming any diagnosis), and adherence to guidelines of key management decisions. Results Standardized patients completed 599 commercial virtual visits from May 2013 to July 2014. Histories and physical examinations were complete in 69.6% (95% confidence interval [CI], 67.7%-71.6%) of virtual visits, diagnoses were correctly named in 76.5% (CI, 72.9%-79.9%), and key management decisions were adherent to guidelines in 54.3% (CI, 50.2%-58.3%). Rates of guideline-adherent care ranged from 34.4% to 66.1% across the eight websites. Variation across websites was significantly greater for viral pharyngitis and acute rhinosinusitis (12.8-82.1%) than for streptococcal pharyngitis and low back pain (74.6-96.5%) or ankle pain and recurrent urinary tract infection (3.4-40.4%). There was no statistically significant variation in guideline adherence by mode of communication (video vs. telephone vs. webchat). Conclusions We found significant variation in quality among companies providing virtual visits for management of common acute illnesses. There was more variation in performance for some conditions than for others, but there was no variation by mode of communication.