bluuebunny/crossref_metadata_2025_split huggingface dataset:
Management and reproductive counseling in cervical, caesarean scar and interstitial ectopic pregnancies over 11 years: identifying the need for a modern management algorithm
Authors: Shah Jaimin S , Nasab Susan , Papanna Ramesha , Chen Han-Yang , Promecene Pamela , Berens Pamela , Johnson Anthony , Bhalwal Asha 
Published: September 2019

Abstract

STUDY QUESTION
Do management strategies (treatment type and order), including provision of reproductive counseling, differ in patients with non-tubal pregnancies?

SUMMARY ANSWER
Medical and surgical treatment strategies varied widely for each type of non-tubal pregnancy and reproductive counseling in this patient population is lacking.

WHAT IS KNOWN ALREADY
Owing to the rarity of non-tubal pregnancies, there is no consensus regarding treatment strategies or protocol. Furthermore, there is limited data on how patients with a non-tubal pregnancy are counseled about future fertility.

STUDY DESIGN, SIZE, DURATION
This is a descriptive retrospective study. Data were collected from January 2006 to December 2017. A total of 50 patients were included in the study.

PARTICIPANTS/MATERIALS, SETTING, METHODS
Patients with an ultrasound diagnosis of a non-tubal ectopic pregnancy (e.g. cervical ectopic pregnancy [CEP], Caesarean scar pregnancy [CSP] or interstitial ectopic pregnancy [IEP]) were included. This study was performed at a university-based institution tertiary referral center. Demographic and clinical characteristics, treatment type and order, reproductive counseling and outcomes were collected. Descriptive statistics were used for analyses.

MAIN RESULTS AND THE ROLE OF CHANCE
Of the 50 patients identified, 13 were CEP (26%), 8 were CSP (16%) and 29 were IEP (58%). Patients with a CSP had a higher parity (median = 3, P = 0.02) and number of prior Caesarean deliveries (mean = 2.1, P < 0.001). A total of 66% (23/35) of patients expressed a desire for future fertility prior to treatment and only 56% (28/50) of patients received reproductive counseling according to the electronic medical records. Among all non-tubal pregnancies, there were variations in the type and the order of treatments that patients received.

LIMITATIONS, REASONS FOR CAUTION
This study was performed in a tertiary referral center therefore the management strategy could have been influenced by the prior interventions and patient response. The descriptive retrospective design precluded any assumption of causation.

WIDER IMPLICATIONS OF THE FINDINGS
The management for non-tubal pregnancies has wide variations. Reproductive counseling in this patient population is lacking. The findings highlight the need for the development of a treatment algorithm and a reproductive counseling protocol for each non-tubal pregnancy to better standardize treatment strategy.

STUDY FUNDING/COMPETING INTEREST(S)
There was no funding for this study. The authors have no conflict of interest to report.
Education protects against coronary heart disease and stroke independently of cognitive function: evidence from Mendelian randomization
Authors: Gill Dipender , Efstathiadou Anthoula , Cawood Kristopher , Tzoulaki Ioanna , Dehghan Abbas 
Published: September 2019

AbstractBackgroundThere is evidence that education protects against cardiovascular disease. However, it is not known whether such an effect is independent of cognition.MethodsWe performed two-sample Mendelian randomization (MR) analyses to investigate the effect of education and cognition, respectively, on risk of CHD and ischaemic stroke. Additionally, we used multivariable MR to adjust for the effects of cognition and education in the respective analyses to measure the effects of these traits independently of each other.ResultsIn unadjusted MR, there was evidence that education is causally associated with both CHD and stroke risk [CHD: odds ratio (OR) 0.65 per 1-standard deviation (SD; 3.6 years) increase in education; 95% confidence interval (CI) 0.61–0.70, stroke: OR 0.77; 95% CI 0.69–0.86]. This effect persisted after adjusting for cognition in multivariable MR (CHD: OR 0.76; 95% CI 0.65–0.89, stroke OR 0.74; 95% CI 0.59–0.92). Cognition had an apparent effect on CHD risk in unadjusted MR (OR per 1-SD increase 0.80; 95% CI 0.74–0.85), however after adjusting for education this was no longer observed (OR 1.03; 95% CI 0.86–1.25). Cognition did not have any notable effect on the risk of developing ischaemic stroke, with (OR 0.97; 95% CI 0.87–1.08) or without adjustment for education (OR 1.04; 95% CI 0.79–1.36).ConclusionsThis study provides evidence to support that education protects against CHD and ischaemic stroke risk independently of cognition, but does not provide evidence to support that cognition protects against CHD and stroke risk independently of education. These findings could have implications for education and health policy.
Real-World Effectiveness From the Asia Pacific Rim Liver Consortium for HBV Risk Score for the Prediction of Hepatocellular Carcinoma in Chronic Hepatitis B Patients Treated With Oral Antiviral Therapy
Authors: Yang Hwai-I , Yeh Ming-Lun , Wong Grace L , Peng Cheng-Yuan , Chen Chien-Hung , Trinh Huy N , Cheung Ka-Shing , Xie Qing , Su Tung-Hung , Kozuka Ritsuzo , Lee Dong-Hyun , Ogawa Eiichi , Zhao Changqing , Ning Hui-Bin , Huang Rui , Li Jiayi , Zhang Jian Q , Ide Tatsuya , Xing Huichun , Iwane Shinji , Takahashi Hirokazu , Wong Christopher , Wong Clifford , Lin Chia-Hsin , Hoang Joseph , Le An , Henry Linda , Toyoda Hidenori , Ueno Yoshiyuki , Gane Edward J , Eguchi Yuichiro , Kurosaki Masayuki , Wu Chao , Liu Chenghai , Shang Jia , Furusyo Norihiro , Enomoto Masaru , Kao Jia-Horng , Yuen Man-Fung , Yu Ming-Lung , Nguyen Mindie H 
Published: September 2019

AbstractBackgroundPatients on oral antiviral (OAV) therapy remain at hepatocellular carcinoma (HCC) risk. Risk prediction tools distinguishing treated patients with residual HCC risk are limited. The aim of this study was to develop an accurate, precise, simple-to-use HCC risk score using routine clinical variables among a treated Asian cohort.MethodsAdult Asian chronic hepatitis B (CHB) patients on OAV were recruited from 25 centers in the United States and the Asia-Pacific region. Excluded persons were coinfected with hepatitis C, D, or human immunodeficiency virus, had HCC before or within 1 year of study entry, or their follow-up was &lt;1 year. Patients were randomized to derivation and validation cohorts on a 2:1 ratio. Statistically significant predictors from multivariate modeling formed the Real-world Effectiveness from the Asia Pacific Rim Liver Consortium for HBV (REAL-B) score.ResultsA total of 8048 patients were randomized to the derivation (n = 5365) or validation group (n = 2683). The REAL-B model included 7 variables (male gender, age, alcohol use, diabetes, baseline cirrhosis, platelet count, and alpha fetoprotein), and scores were categorized as follows: 0–3 low risk, 4–7 moderate risk, and 8–13 high risk. Area under receiver operating characteristics were &gt;0.80 for HCC risk at 3, 5, and 10 years, and these were significantly higher than other risk models (p &lt; .001).ConclusionsThe REAL-B score provides 3 distinct risk categories for HCC development in Asian CHB patients on OAV guiding HCC surveillance strategy.
Organization quality systems and department-level strategies: refinement of the Deepening our Understanding in Quality in Australia (DUQuA) organization and department-level scales
Authors: Clay-Williams Robyn , Taylor Natalie , Winata Teresa , Ting Hsuen P , Arnolda Gaston , Braithwaite Jeffrey 
Published: September 2019

Abstract

Objective
The aim of this study was to develop and refine indices to measure organization and care pathway-level quality management systems in Australian hospitals.

Design
A questionnaire survey and audit tools were derived from instruments validated as part of the Deepening Our Understanding of Quality improvement in Europe (DUQuE) study, adapted for Australian hospitals through expert opinion. Statistical processes were used to explore the factor structure, reliability and non-redundancy and descriptive statistics of the scales.

Setting
Thirty-two large Australian public hospitals.

Participants
Audit of quality management processes at organization-level and care pathway processes at department level for three patient conditions (acute myocardial infarction (AMI), hip fracture and stroke) and senior quality manager, at each of the 32 participating hospitals.

Main Outcome Measure(s)
The degree of quality management evident at organization and care pathway levels.

Results
Analysis yielded seven quality systems and strategies scales. The three hospital-level measures were: the Quality Management Systems Index (QMSI), the Quality Management Compliance Index (QMCI) and the Clinical Quality Implementation Index (CQII). The four department-level measures were: Specialised Expertise and Responsibility (SER), Evidence-Based Organisation of Pathways (EBOP), Patient Safety Strategies (PSS) and Clinical Review (CR). For QMCI, and for seven out of eight subscales in QMSI, adequate internal consistency (Cronbach’s $\alpha$ &gt;0.8) was achieved. For CQII, lack of variation and ceiling effects in the data resulted in very low internal consistency scores, but items were retained for theoretical reasons. Internal consistency was high for CR (Cronbach’s $\alpha$ 0.74–0.88 across the three conditions), and this was supported by all item-total correlations exceeding the desired threshold. For EBOP, Cronbach’s $\alpha$ was acceptable for hip fracture (0.80) and stroke (0.76), but only moderate for AMI (0.52). PSS and SER scales were retained for theoretical reasons, although internal consistencies were only moderate (SER) to poor (PSS).

Conclusions
The Deepening our Understanding of Quality in Australia (DUQuA) organization and department scales can be used by Australian hospital managers to assess and measure improvement in quality management at organization and department levels within their hospitals and are readily modifiable for other health systems depending on their needs.
Validation of the patient measure of safety (PMOS) questionnaire in Australian public hospitals
Authors: Taylor Natalie , Clay-Williams Robyn , Ting Hsuen P , Winata Teresa , Arnolda Gaston , Hogden Emily , Lawton Rebecca , Braithwaite Jeffrey 
Published: September 2019

Abstract

Objective
Patients can provide a unique perspective on the safety of care in hospitals. Understanding that the extent to which the way hospitals are organized for quality and safety is associated with patient perceptions of care is becoming increasingly valued and necessary for the direction of targeted interventions across healthcare systems. The UK-developed patient measure of safety (PMOS) assesses eight domains of ward safety from the patient point of view and has recently been adapted and piloted in Australia. The aim of this study is to test the psychometric properties of PMOS-Australia (PMOS-A) amongst a large cohort of hospitalized patients.

Design
Cross-sectional questionnaire validation assessment.

Setting and participants
As part of the DUQuA project, the PMOS-A survey was distributed within acute myocardial infarction, hip fracture and stroke departments across 32 large public hospitals in Australia. Patients could complete the PMOS-A independently, or request the assistance of a family member/guardian, or staff on the wards—space was included to record mode of completion.

Main outcome measures
Confirmatory factor analysis (CFA) was undertaken on a calibration sample to generate the model, and a validation sample was used to cross-validate the model. A subset of only those participants who received assistance for PMOS-A completion was also tested using CFA on a calibration and validation sample. Model fit indices (chi-square to degrees of freedom ratio [Chi-square:DF], root mean square error of approximation [RMSEA], comparative fit indices [CFI], standardized root mean squared residual [SRMR]), Cronbach’s α, average inter-item correlations, construct reliability and cross-loadings were examined with reference to recommended thresholds to establish the extent of convergent validity and discriminant validity. A marker of criterion validity was assessed through testing associations between the PMOS-A and adherence to clinical guidelines.

Results
Across the calibration and validation samples of the full (N = 911) and assisted completers only subset (N = 490), three (Chi-square:DF, SRMR, RMSEA) of the four indices consistently or almost always met thresholds for acceptable model fit. CFI indices did not meet the recommended limits (0.72–0.78, against a target &gt; 0.9). Positive relationships were found for all tests between PMOS-A and adherence to clinical guidelines, and these were significant when assessed in the calibration datasets for the full and assisted completion samples.

Conclusion
A sufficiently reliable and valid measure of patient perceptions of safety has been developed. These findings should provide adequate support to justify the use of this measure to assess patient perceptions of safety in Australian hospitals and can be modified for use elsewhere.
Conclusion: the road ahead: where should we go now to improve healthcare quality in acute settings?
Authors: Braithwaite Jeffrey , Taylor Natalie , Clay-Williams Robyn , Ting Hsuen P , Arnolda Gaston 
Published: September 2019

AbstractThis final article in our 12-part series articulating a suite of quality improvement studies completes our report on the Deepening our Understanding of Quality in Australia (DUQuA) program of work. Here, we bring the Supplement’s key findings and contributions together, tying up loose ends. Traversing the DUQuA articles, we first argued the case for the research, conducted so that an in-depth analysis of one country’s health system, completed 5 years after the landmark Deepening our Understanding of Quality Improvement in Europe (DUQuE), was available. We now provide a digest of the learning from each article. Essentially, we have contributed an understanding of quality and safety activities in 32 of the largest acute settings in Australia, developed a series of scales and tools for use within Australia, modifiable for other purposes elsewhere, and provided a platform for future studies of this kind. Our main message is, despite the value of publishing an intense study of quality activities in 32 hospitals in one country, there is no gold standard, one-size-fits-all methodology or guarantee of success in quality improvement activities, whether the initiatives are conducted at departmental, organization-wide or whole-of-systems levels. Notwithstanding this, armed with the tools, scales and lessons from DUQuA, we hope we have provided many more options and opportunities for others going about strengthening their quality improvement activities, but we do not claim to have solved all problems or provided a definitive approach. In our view, quality improvement initiatives are perennially challenging, and progress hard-won. Effective measurement, evaluating progress over time, selecting a useful suite of quality methods and having the persistence to climb the improvement gradient over time, using all the expertise and tools available, is at the core of the work of quality improvement and will continue to be so.
Do organization-level quality management systems influence department-level quality? A cross-sectional study across 32 large hospitals in Australia
Authors: Taylor Natalie , Clay-Williams Robyn , Ting Hsuen P , Arnolda Gaston , Winata Teresa , Hogden Emily , Braithwaite Jeffrey 
Published: September 2019

Abstract

Objective
Little is known about the influence that hospital quality systems have on quality at department level, in Australia and elsewhere. This study assessed the relationships between organizational-level quality management systems, and the extent to which hospital-level quality management systems and department-level quality management strategies are related.

Design
A multi-level, cross-sectional, mixed-method study.

Setting and participants
As part of the Deepening our Understanding of Quality in Australia (DUQuA) project, we invited all large hospitals in Australia (~200 or more beds) which provided acute myocardial infarction (AMI), hip fracture and stroke care. The quality managers of these hospitals were the respondents for one of seven measures of hospital quality management systems and strategies. Data across the six remaining measures were collected through site visits by external surveyors assessing the participating hospitals.

Main outcome measures
Relationships were assessed between three organization-level quality management system measures: a self-report measure assessing organization-level quality activities (quality management systems index, QMSI); externally assessed organization-level compliance to procedures used to plan, monitor and improve quality of care (quality management compliance index, QMCI); and externally assessed implementation of quality systems (clinical quality implementation index, CQII). Associations were also assessed between organization-level quality management systems and department-level quality management strategies: how clinical responsibilities are assigned for a particular condition; whether department organization processes are organized to facilitate evidence-based care recommendations; compliance with selected recommendations of international agencies; and whether clinical reviews are performed systematically.

Results
Of 78 invited hospitals, 32 participated in the study. QMSI was positively associated with QMCI and CQII, but after controlling for QMSI, no relationship was found between QMCI and CQII. There appears to be a cluster of relationships between QMSI and department-level measures, but this was not consistent across all departments.

Conclusion
This is the first national study undertaken in Australia to assess relationships within and between organization-level and department-level quality management systems. These quality management system tools align with many components of accreditation standards and may be useful for hospitals in continuously monitoring and driving improvement.
Implementation and data-related challenges in the Deepening our Understanding of Quality in Australia (DUQuA) study: implications for large-scale cross-sectional research
Authors: Arnolda Gaston , Winata Teresa , Ting Hsuen P , Clay-Williams Robyn , Taylor Natalie , Tran Yvonne , Braithwaite Jeffrey 
Published: September 2019

Abstract
Healthcare organisations vary in the degree to which they implement quality and safety systems and strategies. Large-scale cross-sectional studies have been implemented to explore whether this variation is associated with outcomes relevant at the patient level. The Deepening our Understanding of Quality in Australia (DUQuA) study draws from earlier research of this type, to examine these issues in 32 Australian hospitals. This paper outlines the key implementation and analysis challenges faced by DUQuA. Many of the logistical difficulties of implementing DUQuA derived from compliance with the administratively complex and time-consuming Australian ethics and governance system designed principally to protect patients involved in clinical trials, rather than for low-risk health services research. The complexity of these processes is compounded by a lack of organizational capacity for multi-site health services research; research is expected to be undertaken in addition to usual work, not as part of it. These issues likely contributed to a relatively low recruitment rate for hospitals (41% of eligible hospitals). Both sets of issues need to be addressed by health services researchers, policymakers and healthcare administrators, if health services research is to flourish. Large-scale research also inevitably involves multiple measurements. The timing for applying these measures needs to be coherent, to maximise the likelihood of finding real relationships between quality and safety systems and strategies, and patient outcomes; this timing was less than ideal in DUQuA, in part due to administrative delays. Other issues that affected our study include low response rates for measures requiring recruitment of clinicians and patients, missing data and a design that necessarily included multiple statistical comparisons. We discuss how these were addressed. Successful completion of these projects relies on mutual and ongoing commitment, and two-way communication between the research team and hospital staff at all levels. This will help to ensure that enthusiasm and engagement are established and maintained.
Can benchmarking Australian hospitals for quality identify and improve high and low performers? Disseminating research findings for hospitals
Authors: Hibbert Peter , Saeed Faisal , Taylor Natalie , Clay-Williams Robyn , Winata Teresa , Clay Chrissy , Hussein Wadaha , Braithwaite Jeffrey 
Published: September 2019

Abstract
This paper examines the principles of benchmarking in healthcare and how benchmarking can contribute to practice improvement and improved health outcomes for patients. It uses the Deepening our Understanding of Quality in Australia (DUQuA) study published in this Supplement and DUQuA’s predecessor in Europe, the Deepening our Understanding of Quality improvement in Europe (DUQuE) study, as models. Benchmarking is where the performances of institutions or individuals are compared using agreed indicators or standards. The rationale for benchmarking is that institutions will respond positively to being identified as a low outlier or desire to be or stay as a high performer, or both, and patients will be empowered to make choices to seek care at institutions that are high performers. Benchmarking often begins with a conceptual framework that is based on a logic model. Such a framework can drive the selection of indicators to measure performance, rather than their selection being based on what is easy to measure. A Donabedian range of indicators can be chosen, including structure, process and outcomes, created around multiple domains or specialties. Indicators based on continuous variables allow organizations to understand where their performance is within a population, and their interdependencies and associations can be understood. Benchmarking should optimally target providers, in order to drive them towards improvement. The DUQuA and DUQuE studies both incorporated some of these principles into their design, thereby creating a model of how to incorporate robust benchmarking into large-scale health services research.