Maternal and neonatal outcomes by labor onset type and gestational age.

OBJECTIVE: We sought to determine maternal and neonatal outcomes by labor onset type and gestational age. STUDY DESIGN: We used electronic medical records data from 10 US institutions in the Consortium on Safe Labor on 115,528 deliveries from 2002 through 2008. Deliveries were divided by labor onset type (spontaneous, elective induction, indicated induction, unlabored cesarean). Neonatal and maternal outcomes were calculated by labor onset type and gestational age. RESULTS: Neonatal intensive care unit admissions and sepsis improved with each week of gestational age until 39 weeks (P < .001). After adjusting for complications, elective induction of labor was associated with a lower risk of ventilator use (odds ratio [OR], 0.38; 95% confidence interval [CI], 0.28-0.53), sepsis (OR, 0.36; 95% CI, 0.26-0.49), and neonatal intensive care unit admissions (OR, 0.52; 95% CI, 0.48-0.57) compared to spontaneous labor. The relative risk of hysterectomy at term was 3.21 (95% CI, 1.08-9.54) with elective induction, 1.16 (95% CI, 0.24-5.58) with indicated induction, and 6.57 (95% CI, 1.78-24.30) with cesarean without labor compared to spontaneous labor. CONCLUSION: Some neonatal outcomes improved until 39 weeks. Babies born with elective induction are associated with better neonatal outcomes compared to spontaneous labor. Elective induction may be associated with an increased hysterectomy risk.

Structural equation modeling of the medical outcome study: Short Form 36 (SF-36)

The factorial validity of the SF-36 was evaluated using confirmatory factor analysis (CFA) methods, structural equation modeling (SEM), and multigroup structural equation modeling (MSEM). First, the measurement and structural model of the hypothesized SF-36 was explicated. Second, the model was tested for the validity of a second-order factorial structure, upon evidence of model misfit, determined the best-fitting model, and tested the validity of the best-fitting model on a second random sample from the same population. Third, the best-fitting model was tested for invariance of the factorial structure across race, age, and educational subgroups using MSEM.^ The findings support the second-order factorial structure of the SF-36 as proposed by Ware and Sherbourne (1992). However, the results suggest that: (a) Mental Health and Physical Health covary; (b) general mental health cross-loads onto Physical Health; (c) general health perception loads onto Mental Health instead of Physical Health; (d) many of the error terms are correlated; and (e) the physical function scale is not reliable across these two samples. This hierarchical factor pattern was replicated across both samples of health care workers, suggesting that the post hoc model fitting was not data specific. Subgroup analysis suggests that the physical function scale is not reliable across the "age" or "education" subgroups and that the general mental health scale path from Mental Health is not reliable across the "white/nonwhite" or "education" subgroups.^ The importance of this study is in the use of SEM and MSEM in evaluating sample data from the use of the SF-36. These methods are uniquely suited to the analysis of latent variable structures and are widely used in other fields. The use of latent variable models for self reported outcome measures has become widespread, and should now be applied to medical outcomes research. Invariance testing is superior to mean scores or summary scores when evaluating differences between groups. From a practical, as well as, psychometric perspective, it seems imperative that construct validity research related to the SF-36 establish whether this same hierarchical structure and invariance holds for other populations.^ This project is presented as three articles to be submitted for publication. ^

Satisfaction with medical care among Mexican-Americans (Hispanic HANES, 1982--1984)

This research focussed on the extent to which the characteristics of a sample of 8,554 Mexican-Americans affected their satisfaction with medical care by: (1) describing satisfaction with medical care among the population, (2) examining the relationships between satisfaction with health services and personal characteristics of the population, and (3) comparing the results of the research with the results of studies of personal health services in other times, places, and populations.^ The distribution of sex among this population was close to even with men representing 50.4%, however respondents over age 50 years represent 11.3% of the sample. The highest grade attended was found in the Elementary (37.9%), and 70% responded they have a good health. Ninety-three percent of the sample were attended to within thirty minutes they arrived at their clinic/health center. Eighty-two percent of the sample were "Very Satisfied" with the care they received during their last visit.^ Ten hypotheses were tested in this research. Females tend to be more satisfied than males; age was found to correlate with satisfaction with respondents over 40 years reporting more satisfaction levels; there was no correlation between education and satisfaction with the educated expressing more skepticism about medical care; respondents covered by Medicare or Medicaid were more satisfied; perceived health status rating was highly correlated with satisfaction; respondents who spent less than 30 minutes traveling to the clinic/health center were more satisfied while 82% of respondents who had less than 30 minutes waiting time expressed more satisfaction.^ As remarked by Hulka and Aday that responses to client satisfaction questionnaire often provided socially acceptable answers, the results found in this sample was therefore not surprising. The author recommends that instruments for the collection of information on client satisfaction should be studied and modified where applicable to reduce what John Ware termed Acquiescent Response Set (ARS)--a tendency to agree with statement of opinion regardless of content. ^

Illustrated Catalogue of Standard Surgical Instruments and Allied Lines

Section "A": Dissecting and Post-Mortem Instruments Diagnostic Instruments and Apparatus Microscopes and Microscopic Accessories Laboratory Apparatus and Glass Ware Apparatus for Blood and Urine Analysis Apparatus for Phlebotomy, Cupping and Leeching Apparatus for Infusion and Transfusion Syringes for Aspiration and Injection Osteological Preparations Section "B": Anaesthetic, General Operating, Osteotomy, Trepanning, Bullet, Pocket Case, Cautery, Ligatures, Sutures, Dressings, Etc. Section "B" continued Section "C": Eye, Ear, Nasal, Dermal, Oral, Tonsil, Tracheal, Laryngeal,Esophageal, Stomach, Intestinal, Gall Bladder Section "C": continued Section "D": Rectal, Phimosis, Prostatic, Vesical, Urethral, Ureteral, Instruments Section "E": Gynecic, Hysterectomy, Obstetrical, Instrument Satchels, Medicine Cases Section "F": Electric Cautery Transformers, Electro-Cautery Burners and Accessories, Electric Current Controllers, Electro-Diagnostic Outfits, Electrolysis Instruments Electro-Therapeutic Lamps, Faradic Batteries, Galvanic Batteries Section "G": Office Furniture, Office Sterilizing Apparatus, Hospital Supplies, Surgical Rubber Goods, Sick Room Utensils, Invalid Rolling Chairs, Invalid Supplies Section "H": Artificial Limbs, Deformity Apparatus, Fracture Apparatus, Splints, Splint Material, Elastic Hosiery, Abdominal Supporters, Crutches, Trusses, Suspensories, Etc. Index