Tobacco cessation intervention for pregnant women in Argentina and Uruguay: study protocol.

BACKGROUND: Argentina and Uruguay are among the countries with the highest proportion of pregnant women who smoke. The implementation of an effective smoking cessation intervention would have a significant impact on the health of mothers and infants. The "5 A's" (Ask, Advise, Assess, Assist, Arrange) is a strategy consisting of a brief cessation counseling session of 5-15 minutes delivered by a trained provider. The "5 A's" is considered the standard of care worldwide; however, it is under used in Argentina and Uruguay. METHODS: We will conduct a two-arm, parallel cluster randomized controlled trial of an implementation intervention in 20 prenatal care settings in Argentina and Uruguay. Prenatal care settings will be randomly allocated to either an intervention or a control group after a baseline data collection period. Midwives' facilitators in the 10 intervention prenatal clinics (clusters) will be identified and trained to deliver the "5 A's" to pregnant women and will then disseminate and implement the program. The 10 clusters in the control group will continue with their standard in-service activities. The intervention will be tailored by formative research to be readily applicable to local prenatal care services at maternity hospitals and acceptable to local pregnant women and health providers. Our primary hypothesis is that the intervention is feasible in prenatal clinics in Argentina and Uruguay and will increase the frequency of women receiving tobacco use cessation counseling during pregnancy in the intervention clinics compared to the control clinics. Our secondary hypotheses are that the intervention will decrease the frequency of women who smoke by the end of pregnancy, and that the intervention will increase the attitudes and readiness of midwives towards providing counseling to women in the intervention clinics compared to the control clinics.

Gestational diabetes mellitus and postpartum care practices of nurse-midwives.

INTRODUCTION: Postpartum screening for glucose intolerance among women with recent histories of gestational diabetes mellitus (GDM) is important for identifying women with continued glucose intolerance after birth, yet screening rates are suboptimal. In a thorough review of the literature, we found no studies of screening practices among certified nurse-midwives (CNMs). The objectives of our study were to estimate the prevalence of postpartum screening for abnormal glucose tolerance and related care by CNMs for women with recent histories of GDM and to identify strategies for improvement. METHODS: From October through December 2010, the Ohio Department of Health sent a survey by mail and Internet to all licensed CNMs practicing in Ohio. We calculated prevalence estimates for knowledge, attitudes, clinical practices, and behaviors related to postpartum diabetes screening. Chi-square statistics were used to assess differences in self-reported clinical behaviors by frequency of postpartum screening. RESULTS: Of the 146 CNMs who provided postpartum care and responded to the survey (62.2% response rate), 50.4% reported screening women with GDM-affected pregnancies for abnormal glucose tolerance at the postpartum visit. Of CNMs who screened postpartum, only 48.4% used fasting blood sugar or the 2-hour oral glucose tolerance test. Although 86.2% of all responding CNMs reported that they inform women with recent histories of GDM of their increased risk for type 2 diabetes mellitus, only 63.1% counseled these women to exercise regularly and 23.3% reported referring overweight/obese women to a diet support group or other nutrition counseling. CNMs reported that identification of community resources for lifestyle interventions and additional training in postpartum screening guidelines may help to improve postpartum care. DISCUSSION: CNMs in Ohio reported suboptimal levels of postpartum diabetes testing and use of a recommended postpartum test. Providing CNMs with additional training and identifying community resources to support needed lifestyle behavior change may improve care for women with recent GDM-affected pregnancies.

Development of an algorithm to identify pregnancy episodes in an integrated health care delivery system.

OBJECTIVE: To develop and validate a software algorithm to detect pregnancy episodes and maternal morbidities using automated data. DATA SOURCES/STUDY SETTING: Automated records from a large integrated health care delivery system (IHDS), 1998-2001. STUDY DESIGN: Through complex linkages of multiple automated information sources, the algorithm estimated pregnancy histories. We evaluated the algorithm's accuracy by comparing selected elements of the pregnancy history obtained by the algorithm with the same elements manually abstracted from medical records by trained research staff. DATA COLLECTION/EXTRACTION METHODS: The algorithm searched for potential pregnancy indicators within diagnosis and procedure codes, as well as laboratory tests, pharmacy dispensings, and imaging procedures associated with pregnancy. PRINCIPAL FINDINGS: Among 32,847 women with potential pregnancy indicators, we identified 24,680 pregnancies occuring to 21,001 women. Percent agreement between the algorithm and medical records review on pregnancy outcome, gestational age, and pregnancy outcome date ranged from 91 percent to 98 percent. The validation results were used to refine the algorithm. CONCLUSIONS: This pregnancy episode grouper algorithm takes advantage of databases readily available in IHDS, and has important applications for health system management and clinical care. It can be used in other settings for ongoing surveillance and research on pregnancy outcomes, pregnancy-related morbidities, costs, and care patterns.