Variation in hospital rates of induction of labour: a population-based record linkage study

BACKGROUND: Understanding the extent of hospital heterogeneity in induction of labour (IOL) practices to identify areas of practice improvement may result in improved maternity outcomes. We examined inter-hospital variation in rates of IOL to identify potential targets to reduce high rates of practice variation. METHODS: Population-based record linkage study of all births of ≥24 weeks gestation in 72 hospitals in New South Wales, Australia, 2010-2011. Births were categorized into 10 mutually exclusive groups, derived from the Robson caesarean section (CS) classification. These groups were categorised by parity, plurality, fetal presentation, prior CS and gestational age. Multilevel logistic regression was used to examine variation in hospital IOL rates by the groups, adjusted for differences in casemix. RESULTS: The overall IOL rate was 26.7% (46,922 of 175,444 maternities were induced), ranging from 9.7%- 41.2% (interquartile range 21.8%- 29.8%) between hospitals. Nulliparous and multiparous women at 39-40 weeks gestation with a singleton cephalic birth were the greatest contributors to the overall IOL rate (23.5% and 20.2% of all IOL respectively), and had persisting high unexplained variation after adjustment for casemix (adjusted hospital IOL rates ranging from 11.8%- 44.9% and 7.1%- 40.5% respectively). In contrast, there was little variation in inter-hospital IOL rates among multiparous women with a singleton cephalic birth at ≥41 weeks gestation, women with singleton non-cephalic pregnancies, and women with multifetal pregnancies. CONCLUSION: Seven of the 10 groups showed high or moderate unexplained variation in inter-hospital IOL rates, most pronounced for women at 39-40 weeks gestation with a singleton cephalic birth. Outcomes associated with divergent practice require determination, which may guide strategies to reduce practice variation.NHMRC, AR

Methods of classification for women undergoing induction of labour: a systematic review and novel classification system

OBJECTIVE To develop and demonstrate the applicability of a classification system for induction of labour (IOL) that fulfils recognised classification system attributes for clinical, surveillance and research purposes. DESIGN Proof of concept. SETTING, POPULATION Applicability demonstrated in a population cohort of 909,702 maternities in New South Wales, Australia, 2002-2011. METHODS A multidisciplinary collaboration developed a classification system through a systematic literature review, development of a clinically logical model, and presentation to stakeholders for feedback and refinement. Classification factors included parity (nulliparous, parous), previous caesarean section (CS), gestational age (≤36, 37-38, 39-40, ≥41 weeks gestation), number (singleton, multiple) and presentation of the fetus (cephalic, non-cephalic). We determined: the size of each classification group, the contribution each group made to overall IOL rates, and within-group IOL rates (calculated as proportions of all maternities, all maternities excluding prelabour CS and of all continuing maternities). MAIN OUTCOME MEASURES Applicability of IOL classification using routinely collected obstetric data. RESULTS A 10 group classification system was developed. Of all maternities, 25.4% were induced. Nulliparous and parous women without a prior CS at 39-40 weeks gestation with a singleton cephalic-presenting fetus were the largest groups (21.2% and 24.5% respectively) and accounted for the highest proportion of all IOL (20.7% and 21.5% respectively). The highest within group IOL rates were for nullipara (53.8%) and multipara (45.5%) ≥41 weeks gestation. CONCLUSION We propose a classification system for IOL that has the attributes of simplicity and clarity, utilises information that is readily and reliably collected and reported, and enables standard characterisation of populations of women having an IOL.NHMRC 1021025, ARC FT12010006

Quantifying under-reporting of pathology tests in Medical Benefits Schedule claims data

Objective We investigated the completeness of recording of pathology tests in Australian Medical Benefits Schedule (MBS) claims data, using the example of the prostate-specific antigen (PSA) test. With some exceptions, MBS claims data records only the three most expensive pathology items in an episode of care, and this practice ('episode coning') means that pathology tests can be under-recorded. Methods The analysis used MBS data for male participants in the 45 and Up Study. The number and cost of items in each episode of care were used to determine whether an episode contained a PSA screening test (Item 66655), or could have lacked a record of this item because of episode coning. Results MBS data for 1070392 episodes involving a request for a pathology test for 118074 men were analysed. Of these episodes, 11% contained a request for a PSA test; a further 7.5% may have been missing a PSA request that was not recorded because of episode coning. Conclusions It is important to consider under-reporting of pathology tests as a result of episode coning when interpreting MBS claims data. Episode coning creates uncertainty about whether a person has received any given pathology test. The extent of this uncertainty can be estimated by determining the proportion of episodes in which the test may have been performed but was not recorded due to episode coning. What is known about the topic Medical Benefits Schedule (MBS) claims data are a key resource for Australian health researchers. What does this paper add We investigated a feature of MBS claims data known as episode coning, which may cause some pathology tests to be under-reported. Using the example of requests for PSA tests, we estimated the uncertainty in the amount of use of PSA tests introduced by episode coning. What are the implications for practitioners Researchers using MBS data to identify use of specific pathology tests need to be aware of under-reporting caused by episode coning, and to estimate and report the uncertainty that this introduces into their findings

Cluster randomized controlled trial of a psycho-educational intervention for people with a family history of depression for use in general practice

Background: The strongest risk factor for depression is having a family history of the condition. Many individuals with a family history of depression are concerned about their personal risk for depression and report unmet educational and psychological support needs. No supportive and/or educational interventions are currently available that target this group of individuals. In this study we will develop and evaluate the first online psycho-educational intervention targeted to individuals with a family history of depression. Genetic risk information and evidence-rated information on preventive strategies for depression will be provided to such individuals in a general practice setting. The intervention will also incorporate a risk assessment tool. The content and delivery of the intervention will be pilot-tested. Methods/design: The proposed intervention will be evaluated in the general practitioner (GPs) setting, using a cluster randomized controlled trial. GP practices will be randomized to provide either access to the online, targeted psycho-educational intervention or brief generic information about depression (control) to eligible patients. Eligibility criteria include having at least one first-degree relative with either major depressive disorder (MDD) or bipolar disorder (BD). The primary outcome measure is 'intention to adopt, or actual adoption of, risk-reducing strategies'. Secondary outcome measures include: depression symptoms, perceived stigma of depression, knowledge of risk factors for development of depression and risk-reducing strategies, and perceived risk of developing depression or having a recurrence of family history. Over the course of the study, participants will complete online questionnaires at three time points: at baseline, and two weeks and six months after receiving the intervention or control condition. Discussion: This novel psycho-educational intervention will provide individuals with a family history of depression with information on evidence-based strategies for the prevention of depression, thus, we hypothesize, enabling them to make appropriate lifestyle choices and implement behaviors designed to reduce their risk for depression. The online psycho-educational intervention will also provide a model for similar interventions aimed at individuals at increased familial risk for other psychiatric disorders.10 page(s

Impact of personal genomic risk information on melanoma prevention behaviors and psychological outcomes: a randomized controlled trial

Purpose: We evaluated the impact of personal melanoma genomic risk information on sun-related behaviors and psychological outcomes. Methods: In this parallel group, open, randomized controlled trial, 1,025 Australians of European ancestry without melanoma and aged 18–69 years were recruited via the Medicare database (3% consent). Participants were randomized to the intervention (n = 513; saliva sample for genetic testing, personalized melanoma risk booklet based on a 40-variant polygenic risk score, telephone-based genetic counseling, educational booklet) or control (n = 512; educational booklet). Wrist-worn ultraviolet (UV) radiation dosimeters (10-day wear) and questionnaires were administered at baseline, 1 month postintervention, and 12 months postbaseline. Results: At 12 months, 948 (92%) participants completed dosimetry and 973 (95%) the questionnaire. For the primary outcome, there was no effect of the genomic risk intervention on objectively measured UV exposure at 12 months, irrespective of traditional risk factors. For secondary outcomes at 12 months, the intervention reduced sunburns (risk ratio: 0.72, 95% confidence interval: 0.54–0.96), and increased skin examinations among women. Melanoma-related worry was reduced. There was no overall impact on general psychological distress. Conclusion: Personalized genomic risk information did not influence sun exposure patterns but did improve some skin cancer prevention and early detection behaviors, suggesting it may be useful for precision prevention. There was no evidence of psychological harm.</p

Impact of personal genomic risk information on melanoma prevention behaviors and psychological outcomes: A randomized controlled trial

Purpose: We evaluated the impact of personal melanoma genomic risk information on sun-related behaviors and psychological outcomes. Methods: In this parallel group, open, randomized controlled trial, 1,025 Australians of European ancestry without melanoma and aged 18–69 years were recruited via the Medicare database (3% consent). Participants were randomized to the intervention (n = 513; saliva sample for genetic testing, personalized melanoma risk booklet based on a 40-variant polygenic risk score, telephone based genetic counseling, educational booklet) or control (n = 512; educational booklet). Wrist-worn ultraviolet (UV) radiation dosimeters (10-day wear) and questionnaires were administered at baseline, 1 month postintervention, and 12 months postbaseline. Results: At 12 months, 948 (92%) participants completed dosimetry and 973 (95%) the questionnaire. For the primary outcome, there was no effect of the genomic risk intervention on objectively measured UV exposure at 12 months, irrespective of traditional risk factors. For secondary outcomes at 12 months, the intervention reduced sunburns (risk ratio: 0.72, 95% confidence interval: 0.54–0.96), and increased skin examinations among women. Melanoma-related worry was reduced. There was no overall impact on general psychological distress. Conclusion: Personalized genomic risk information did not influence sun exposure patterns but did improve some skin cancer prevention and early detection behaviors, suggesting it may be useful for precision prevention. There was no evidence of psychological harm