bluuebunny/crossref_metadata_2025_split huggingface dataset:
Unmet need for family planning and associated factors among currently married reproductive age women in Tiro Afeta District, South West Ethiopia, 2017: cross-sectional study
Authors: Solomon Tesfaye , Nigatu Mamo , Gebrehiwot Tsegaye Tewelde , Getachew Biniam 
Published: December 2019

Abstract
Background
Unmet need for family planning in Oromia region was very high (28.9%) compared to other regions in Ethiopia. To address problems associated with unmet need for family planning locally available evidences are essential, however, there were no clear evidences on unmet need for family planning in Tiro Afeta district. This study aims to assess the magnitude and associated factors of unmet need for family planning among currently married women in Tiro Afeta district, South West Ethiopia, 2017.

Methods
Community based cross sectional study was conducted in April, 2017. A total of 348 currently married women of reproductive age were enrolled from eight villages selected by simple random sampling and using proportional to size allocation. Data were entered using EpiData 3.1 and analyzed by SPSS version 22. Adjusted odds ratios at 95% confidence interval with p-value of < 0.05 were considered as significant variables.

Results
Unmet need for family planning among currently married women in Tiro Afeta was 26.1%. Factors significantly associated with unmet need for family planning were: never use of family planning before survey (AOR: 5.09, 95% CI: 2.73–9.50); multiparity (AOR: 3.02, 95% CI: 1.56–5.85); perceived husband’s attitude as disapproval (AOR: 2.75, 95% CI: 1.43–5.26); lack of counseling from health workers (AOR: 2.07, 95% CI: 1.11–3.85); and unavailability of Radio and/or Television in the house (AOR: 2.05, 95% CI: 1.15–3.66).

Conclusion
Unmet need for family planning in Tiro Afeta was higher than national average but lower than Oromia region. Never use of family planning, women’s parity, husband’s attitude towards contraceptives, women counseling and unavailability of Radio and/or Television in the respondent’s home were significantly associated factors with unmet need for family planning. Therefore, the service providers and the district health office should strengthen counseling and partner involvement to reduce unmet need for family planning.
Dying too soon or living too long? Withdrawing treatment from patients with prolonged disorders of consciousness after Re Y
Authors: Huxtable Richard 
Published: December 2019

AbstractBackgroundIn the ruling inY[2018], the UK Supreme Court has confirmed that there is no general requirement for the courts in England and Wales to authorise the withdrawal of clinically assisted nutrition and hydration from patients with prolonged disorders of consciousness. The perceived requirement, which originated in a court ruling in 1993, encompassed those in the vegetative state and those in the minimally conscious state. The ruling inYconfirms that the court may still be approached to decide difficult or contested cases, but there is otherwise no routine requirement that the judges be approached.Main bodyThere is much to welcome in this ruling, particularly as it means that these decisions for these patients are no longer (unusually) singled out for a judicial decision, with all the financial and emotional costs that court proceedings can entail. However, there is also a risk that the ruling might have unwelcome consequences. First, there is the possibility that patients might die too soon, particularly if doctors should now adopt the courts’ previous reasoning, which has suggested that patients in the vegetative state lack interests, so treatment may – perhaps must – be withdrawn. Secondly, there is the converse possibility that patients might live too long, since empirical research suggests that – whether intentionally or not – patients’ families, clinicians, and the health system appear to promote treatment-by-default.ConclusionRather than adopt general positions, which may be contestable and potentially risky, this article argues, on a pluralistic basis, that the individual patient should be the focus of any decision made in his or her ‘best interests’. The existing legal framework in England and Wales, which is provided by the Mental Capacity Act 2005, already points in this direction, although more efforts may be needed to ensure that those involved in making these decisions are suitably educated and supported. Fortunately, new guidance from the British Medical Association could help clinicians and families to make decisions in the future, which are appropriate for the incapacitated individual patient in question.
The implementation of natural language processing to extract index lesions from breast magnetic resonance imaging reports
Authors: Liu Yi , Liu Qing , Han Chao , Zhang Xiaodong , Wang Xiaoying 
Published: December 2019

Abstract
Background
There are often multiple lesions in breast magnetic resonance imaging (MRI) reports and radiologists usually focus on describing the index lesion that is most crucial to clinicians in determining the management and prognosis of patients. Natural language processing (NLP) has been used for information extraction from mammography reports. However, few studies have investigated NLP in breast MRI data based on free-form text. The objective of the current study was to assess the validity of our NLP program to accurately extract index lesions and their corresponding imaging features from free-form text of breast MRI reports.

Methods
This cross-sectional study examined 1633 free-form text reports of breast MRIs from 2014 to 2017. First, the NLP system was used to extract 9 features from all the lesions in the reports according to the Breast Imaging Reporting and Data System (BI-RADS) descriptors. Second, the index lesion was defined as the lesion with the largest number of imaging features. Third, we extracted the values of each imaging feature and the BI-RADS category from each index lesion. To evaluate the accuracy of our system, 478 reports were manually reviewed by two individuals. The time taken to extract data by NLP was compared with that by reviewers.

Results
The NLP system extracted 889 lesions from 478 reports. The mean number of imaging features per lesion was 6.5 ± 2.1 (range: 3–9; 95% CI: 6.362–6.638). The mean number of imaging features per index lesion was 8.0 ± 1.1 (range: 5–9; 95% CI: 7.901–8.099). The NLP system demonstrated a recall of 100.0% and a precision of 99.6% for correct identification of the index lesion. The recall and precision of NLP to correctly extract the value of imaging features from the index lesions were 91.0 and 92.6%, respectively. The recall and precision for the correct identification of the BI-RADS categories were 96.6 and 94.8%, respectively. NLP generated the total results in less than 1 s, whereas the manual reviewers averaged 4.47 min and 4.56 min per report.

Conclusions
Our NLP method successfully extracted the index lesion and its corresponding information from free-form text.
Forecasting one-day-forward wellness conditions for community-dwelling elderly with single lead short electrocardiogram signals
Authors: Fan Xiaomao , Zhao Yang , Wang Hailiang , Tsui Kwok Leung 
Published: December 2019

Abstract
Background
The accelerated growth of elderly population is creating a heavy burden to the healthcare system in many developed countries and regions. Electrocardiogram (ECG) analysis has been recognized as effective approach to cardiovascular disease diagnosis and widely utilized for monitoring personalized health conditions.

Method
In this study, we present a novel approach to forecasting one-day-forward wellness conditions for community-dwelling elderly by analyzing single lead short ECG signals acquired from a station-based monitoring device. More specifically, exponentially weighted moving-average (EWMA) method is employed to eliminate the high-frequency noise from original signals at first. Then, Fisher-Yates normalization approach is used to adjust the self-evaluated wellness score distribution since the scores among different individuals are skewed. Finally, both deep learning-based and traditional machine learning-based methods are utilized for building wellness forecasting models.

Results
The experiment results show that the deep learning-based methods achieve the best fitted forecasting performance, where the forecasting accuracy and F value are 93.21% and 91.98% respectively. The deep learning-based methods, with the merit of non-hand-crafted engineering, have superior wellness forecasting performance towards the competitive traditional machine learning-based methods.

Conclusion
The developed approach in this paper is effective in wellness forecasting for community-dwelling elderly, which can provide insights in terms of implementing a cost-effective approach to informing healthcare provider about health conditions of elderly in advance and taking timely interventions to reduce the risk of malignant events.
A Bayesian decision support sequential model for severity of illness predictors and intensive care admissions in pneumonia
Authors: Baez Amado Alejandro , Cochon Laila , Nicolas Jose Maria 
Published: December 2019

AbstractBackgroundCommunity-acquired pneumonia (CAP) is one of the leading causes of morbidity and mortality in the USA. Our objective was to assess the predictive value on critical illness and disposition of a sequential Bayesian Model that integrates Lactate and procalcitonin (PCT) for pneumonia.MethodsSensitivity and specificity of lactate and PCT attained from pooled meta-analysis data. Likelihood ratios calculated and inserted in Bayesian/ Fagan nomogram to calculate posttest probabilities. Bayesian Diagnostic Gains (BDG) were analyzed comparing pre and post-test probability. To assess the value of integrating both PCT and Lactate in Severity of Illness Prediction we built a model that combined CURB65 with PCT as the Pre-Test markers and later integrated the Lactate Likelihood Ratio Values to generate a combined CURB 65 + Procalcitonin + Lactate Sequential value.ResultsThe BDG model integrated a CUBR65 Scores combined with Procalcitonin (LR+ and LR-) for Pre-Test Probability Intermediate and High with Lactate Positive Likelihood Ratios. This generated for the PCT LR+ Post-test Probability (POSITIVE TEST) Posterior probability: 93% (95% CI [91,96%]) and Post Test Probability (NEGATIVE TEST) of: 17% (95% CI [15–20%]) for the Intermediate subgroup and 97% for the high risk sub-group POSITIVE TEST: Post-Test probability:97% (95% CI [95,98%]) NEGATIVE TEST: Post-test probability: 33% (95% CI [31,36%]) . ANOVA analysis for CURB 65 (alone) vs CURB 65 and PCT (LR+) vs CURB 65 and PCT (LR+) and Lactate showed a statistically significant difference (Pvalue = 0.013).ConclusionsThe sequential combination of CURB 65 plus PCT with Lactate yielded statistically significant results, demonstrating a greater predictive value for severity of illness thus ICU level care.
Multi-level models for heart failure patients’ 30-day mortality and readmission rates: the relation between patient and hospital factors in administrative data
Authors: Roshanghalb Afsaneh , Mazzali Cristina , Lettieri Emanuele 
Published: December 2019

Abstract
Background
This study aims at gathering evidence about the relation between 30-day mortality and 30-day unplanned readmission and patient and hospital factors. By definition, we refer to 30-day mortality and 30-day unplanned readmission as the number of deaths and non-programmed hospitalizations for any cause within 30 days after the incident heart failure (HF). In particular, the focus is on the role played by hospital-level factors.

Methods
A multi-level logistic model that combines patient- and hospital-level covariates has been developed to better disentangle the role played by the two groups of covariates. Later on, hospital outliers in term of better-than-expected/worst-than-expected performers have been identified by comparing expected cases vs. observed cases. Hospitals performance in terms of 30-day mortality and 30-day unplanned readmission rates have been visualized through the creation of funnel plots. Covariates have been selected coherently to past literature. Data comes from the hospital discharge forms for Heart Failure patients in the Lombardy Region (Northern Italy). Considering incident cases for HF in the timespan 2010–2012, 78,907 records for adult patients from 117 hospitals have been collected after quality checks.

Results
Our results show that 30-day mortality and 30-day unplanned readmissions are explained by hospital-level covariates, paving the way for the design and implementation of evidence-based improvement strategies. While the percentage of surgical DRG (OR = 1.001; CI (1.000–1.002)) and the hospital type of structure (Research hospitals vs. non-research public hospitals (OR = 0.62; CI (0.48–0.80)) and Non-research private hospitals vs. non-research hospitals OR = 0.75; CI (0.63–0.90)) are significant for mortality, the mean length of stay (OR = 0.96; CI (0.95–0.98)) is significant for unplanned readmission, showing that mortality and readmission rates might be improved through different strategies.

Conclusion
Our results confirm that hospital-level covariates do affect quality of care, and that 30-day mortality and 30-day unplanned readmission are affected by different managerial choices. This confirms that hospitals should be accountable for their “added value” to quality of care.
Prescribing errors in electronic prescriptions for outpatients intercepted by pharmacists and the impact of prescribing workload on error rate in a Chinese tertiary-care women and children’s hospital
Authors: Yang Jian-hui , Liao Yu-fang , Lin Wu-bin , Wu Wen 
Published: December 2019

Abstract
Background
Prescribing errors may, influenced by some risk factors, cause adverse drug events. Most studies in this field focus on errors in prescriptions for hospital inpatients, with only a few on those for outpatients. Our study aimed to explore the incidence of prescribing errors in electronic prescriptions and illustrate the trend of prescribing workload and error rate over time.

Methods
The cross-section study was performed between September, 2015 and November, 2015. Prescribing errors were intercepted by pharmacists using a prescription reviewing system under which prescriptions with errors were transferred to a specific computer and recorded by another pharmacist and the incidence of total prescribing errors and severe errors was then calculated. A subgroup analysis was conducted in accordance to the number of drug orders, the age group of patients, the seniority of physicians, the specialty of physicians, the working day when prescriptions were issued, and the prescribing workload of physicians. A time-series analysis was employed to analyze the trend of prescribing workload and error rate, and the correlation between them.

Results
Totally, 65,407 patients were included in this study and 150,611 prescriptions with 294,564 drug orders (including 584 different drugs) were reviewed for identification of errors. A total of 534 prescribing errors (an error rate of 0.34%) were identified. Severe errors accounted for 13.62% of total errors. The subgroup analysis showed prescriptions of multiple drug orders, for pediatric patients aged 29 days to 12 years, from physicians specializing in ophthalmology and otorhinolaryngology, or prescribing on weekdays were more susceptible to errors. A time-series analysis demonstrated no correlation between prescribing workload and error rate which increased at the end of each working shift while prescribing workload decreased.

Conclusion
Less than 1% of the studied prescriptions came with errors among which one in seven were severe ones. But prescribing errors were in no relation to workloads. What’s more, further studies are needed to investigate pharmacist-led intervention to reduce prescribing errors.
Patients’ perception of communication at the interface between primary and secondary care: a cross-sectional survey in 34 countries
Authors: Scaioli Giacomo , Schäfer Willemijn L. A. , Boerma Wienke G. W. , Spreeuwenberg Peter , van den Berg Michael , Schellevis François G. , Groenewegen Peter P. 
Published: December 2019

Abstract
Background
Poor communication between general practitioners (GPs) and medical specialists can lead to poorer quality, and continuity, of care. Our study aims to assess patients’ perceptions of communication at the interface between primary and secondary care in 34 countries. It will analyse, too, whether this communication is associated with the organisation of primary care within a country, and with the characteristics of GPs and their patients.

Methods
We conducted a cross-sectional survey among patients in 34 countries. Following a GP consultation, patients were asked two questions. Did they take to understand that their GP had informed medical specialists about their illness upon referral? And, secondly, did their GP know the results of the treatment by a medical specialist? We used multi-response logistic multilevel models to investigate the association of factors related to primary care, the GP, and the patient, with the patients’ perceptions of communication at the interface between primary and secondary care.

Results
In total, 61,931 patients completed the questionnaire. We found large differences between countries, in both the patients’ perceptions of information shared by GPs with medical specialists, and the patients’ perceptions of the GPs’ awareness of the results of treatment by medical specialists. Patients whose GPs stated that they ‘seldom or never’ send referral letters, also less frequently perceived that their GP communicated with their medical specialists about their illness. Patients with GPs indicating they ‘seldom or never’ receive feedback from medical specialists, indicated less frequently that their GP would know the results of treatment by a medical specialist. Moreover, patients with a personal doctor perceived higher rates of communication in both directions at the interface between primary and secondary care.

Conclusion
Generally, patients perceive there to be high rates of communication at the interface between primary and secondary care, but there are large differences between countries. Policies aimed at stimulating personal doctor arrangements could, potentially, enhance the continuity of care between primary and secondary care.
Factors associated with health care provider knowledge on abortion care in Ethiopia, a further analysis on emergency obstetric and newborn care assessment 2016 data
Authors: Taddele Tefera , Getachew Theodros , Taye Girum , Getnet Misrak , Defar Atkure , Teklie Habtamu , Gonfa Geremew , Humnessa Sheleme , Teshome Aster , Akale Zenebe , Mormu Kasahun , Bekele Abebe 
Published: December 2019

Abstract
Background
Abortion is one of the major direct causes of maternal death, accounting for 7.9% globally. In Africa, 5.5 million women have unsafe abortions annually. Although maternal deaths due to complications of abortion have declined in Ethiopia, women still die from complications. Few studies have focused on providers’ clinical knowledge. This study investigates the level of health workers’ knowledge of comprehensive abortion care and its determinants in Ethiopia.

Methods
Data from the national emergency obstetric and newborn care (EmONC) assessment was used. A total of 3804 facilities that provided institutional deliveries in the 12 months before the assessment were included. Provider knowledge was assessed by interviewing a single provider from each facility. Criteria for selection included: having attended the largest number of deliveries in the last one or two months. A summary knowledge score was generated based on the responses to three knowledge questions related to immediate complications of unsafe abortion, how a woman should be clinically managed and what the counselling content should contain. The score was classified into two categories (< 50% and > =50%). Logistic regression was used to determine individual and facility-level factors associated with the summary knowledge score.

Result
A total of 3800 providers participated and the majority were midwives, nurses and health officers. On average, providers identified approximately half or fewer of the expected responses. The multivariate model showed that midwives and nurses (compared to health officers), being female, and absence of training or practice of manual vacuum aspiration were associated with lower knowledge levels. Important facility level factors protective against low knowledge levels included employment in Addis Ababa, being male and having internet access in the facility.

Conclusion
To increase knowledge levels among providers, pre- and in-service training efforts should be particularly sensitive to female providers who scored lower, ensure that more midlevel providers are capable of performing manual vacuum aspiration as well as provide special attention to providers in the Gambella.
A survey of knowledge and use of telehealth among veterinarians
Authors: Watson Kylie , Wells Julia , Sharma Manoj , Robertson Stanley , Dascanio John , Johnson Jason W. , Davis Robert E. , Nahar Vinayak K. 
Published: December 2019

Abstract
Background
As usage of digital information and communication technologies continues to grow, the incorporation of telehealth and telemedicine has become a topic of interest in the veterinary industry. Veterinary telemedicine presents the opportunity to expand veterinary medicine by increasing access to healthcare services for clients and patients and improving medical quality. The objective of this study was to assess veterinarians’ knowledge and utilization of telehealth and telemedicine.

Results
Seventy-six veterinarians participated in the study and both qualitative and quantitative analyses were performed on the data collected. Several key themes emerged from the qualitative analysis of open-ended questions, including telecommunication, Doctor of Veterinary Medicine (DVM)-patient services, and remote interaction, among others. Through coding and qualitative analysis, researchers identified a lack of knowledge of the American Veterinary Medical Association (AVMA) definitions of telehealth and telemedicine. Specifically, a notable amount of participants were unaware of the distinction between the two practices per AVMA guidelines. Quantitative analyses revealed that the largest group of respondents reported sometimes utilizing telehealth and telemedicine in practice, with no distinct difference in utilization among the different age demographics of participants.

Conclusions
These observations indicate a need for interventions both in veterinary school and continuing education programs with the purpose of increasing both knowledge and utilization of telehealth and telemedicine among veterinarians. While these recommendations serve as a starting point, future studies are needed to further enhance the understanding of veterinary telehealth and telemedicine in practice.