Restoration Constitutionalism in the South Pacific

The dilemmas confronting societies which move from a period of authoritarian rule to liberal democracy have increasingly engaged the attention of academic experts and policy-makers alike. One issue which has received comparatively less notice, however, is the phenomenon of “restoration constitutionalism,” i.e. the process by which the transitional society is sought to be returned to the constitutional order that predated the authoritarian rule. Recent events in Fiji offer a good example of how this process works in practice. This article looks at the relationship between constitutionalism and transitional regimes, and argues that, where the “rupture” in a constitutional order is relatively short-lived, restoration constitutionalism provides a smoother and quicker return to liberal politics than any other modality of transition

Courts and Constitutional Usurpers Some Lessons from Fiji

Much concern and disappointment has been expressed by jurists and human rights campaigners over the inaction ofnational judiciaries in reversing the effects of coups d\u27etat and other acts which result in the unconstitutional overthrow of democratically constituted governments Against this backdrop, the decisive steps taken b) the superior courts of Fiji to nullify the attempted destabilisation of that country\u27s elected government in May 2000 was a trail-blazing development The author analyses the jurisprudence in this area and explains the implications of the Fijian judgments

DIAGNOSE: Avoiding Out-of-distribution Data using Submodular Information Measures

Avoiding out-of-distribution (OOD) data is critical for training supervised machine learning models in the medical imaging domain. Furthermore, obtaining labeled medical data is difficult and expensive since it requires expert annotators like doctors, radiologists, etc. Active learning (AL) is a well-known method to mitigate labeling costs by selecting the most diverse or uncertain samples. However, current AL methods do not work well in the medical imaging domain with OOD data. We propose Diagnose (avoiDing out-of-dIstribution dAta usinG submodular iNfOrmation meaSurEs), a novel active learning framework that can jointly model similarity and dissimilarity, which is crucial in mining in-distribution data and avoiding OOD data at the same time. Particularly, we use a small number of data points as exemplars that represent a query set of in-distribution data points and a private set of OOD data points. We illustrate the generalizability of our framework by evaluating it on a wide variety of real-world OOD scenarios. Our experiments verify the superiority of Diagnose over the state-of-the-art AL methods across multiple domains of medical imaging.Comment: Accepted to MICCAI 2022 MILLanD Worksho

CLINICAL: Targeted Active Learning for Imbalanced Medical Image Classification

Training deep learning models on medical datasets that perform well for all classes is a challenging task. It is often the case that a suboptimal performance is obtained on some classes due to the natural class imbalance issue that comes with medical data. An effective way to tackle this problem is by using targeted active learning, where we iteratively add data points to the training data that belong to the rare classes. However, existing active learning methods are ineffective in targeting rare classes in medical datasets. In this work, we propose Clinical (targeted aCtive Learning for ImbalaNced medICal imAge cLassification) a framework that uses submodular mutual information functions as acquisition functions to mine critical data points from rare classes. We apply our framework to a wide-array of medical imaging datasets on a variety of real-world class imbalance scenarios - namely, binary imbalance and long-tail imbalance. We show that Clinical outperforms the state-of-the-art active learning methods by acquiring a diverse set of data points that belong to the rare classes.Comment: Accepted to MICCAI 2022 MILLanD Worksho

How to build a robust provider improvement partnership program to enhance patient experience – A case study

Patient experience is emerging as a key differentiating factor in patients’ choice of healthcare system. Many healthcare organizations are attempting to improve their patient experience by data-driven, patient-centered initiatives. This involves engaging all staff along all the contact points of a patient’s journey in healthcare. Perhaps, the physicians or care providers are most important link in this chain but also the most challenging to engage in improvement efforts. Most healthcare organizations have some training or workshops to educate providers on communication skills and other tools to enhance patient experience. However, there seems to a paucity of a standardized approach or a roadmap to put together a robust physician or care provider coaching or improvement partnership program with patient experience (PX) staff. There seems to be several gaps in this process. The current article attempts to develop broad guidelines and suggest a roadmap to address these gaps. The article also suggests general templates for PX staff to use in conducting these improvement work with providers and suggestions for developing a standard physician observation or shadowing template for consistency. The article has woven several commonly used tools like motivational interviewing, change management (ADKAR model), and several communication tools to suggest a detailed blue print for provider patient experience improvement partnership

Achieving Surgical, Obstetric, Trauma, and Anesthesia (SOTA) care for all in South Asia

South Asia is a demographically crucial, economically aspiring, and socio-culturally diverse region in the world. The region contributes to a large burden of surgically-treatable disease conditions. A large number of people in South Asia cannot access safe and affordable surgical, obstetric, trauma, and anesthesia (SOTA) care when in need. Yet, attention to the region in Global Surgery and Global Health is limited. Here, we assess the status of SOTA care in South Asia. We summarize the evidence on SOTA care indicators and planning. Region-wide, as well as country-specific challenges are highlighted. We also discuss potential directions—initiatives and innovations—toward addressing these challenges. Local partnerships, sustained research and advocacy efforts, and politics can be aligned with evidence-based policymaking and health planning to achieve equitable SOTA care access in the South Asian region under the South Asian Association for Regional Cooperation (SAARC)

The Changing Landscape for Stroke\ua0Prevention in AF: Findings From the GLORIA-AF Registry Phase 2

Background GLORIA-AF (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients with Atrial Fibrillation) is a prospective, global registry program describing antithrombotic treatment patterns in patients with newly diagnosed nonvalvular atrial fibrillation at risk of stroke. Phase 2 began when dabigatran, the first non\u2013vitamin K antagonist oral anticoagulant (NOAC), became available. Objectives This study sought to describe phase 2 baseline data and compare these with the pre-NOAC era collected during phase 1. Methods During phase 2, 15,641 consenting patients were enrolled (November 2011 to December 2014); 15,092 were eligible. This pre-specified cross-sectional analysis describes eligible patients\u2019 baseline characteristics. Atrial fibrillation disease characteristics, medical outcomes, and concomitant diseases and medications were collected. Data were analyzed using descriptive statistics. Results Of the total patients, 45.5% were female; median age was 71 (interquartile range: 64, 78) years. Patients were from Europe (47.1%), North America (22.5%), Asia (20.3%), Latin America (6.0%), and the Middle East/Africa (4.0%). Most had high stroke risk (CHA2DS2-VASc [Congestive heart failure, Hypertension, Age  6575 years, Diabetes mellitus, previous Stroke, Vascular disease, Age 65 to 74 years, Sex category] score  652; 86.1%); 13.9% had moderate risk (CHA2DS2-VASc = 1). Overall, 79.9% received oral anticoagulants, of whom 47.6% received NOAC and 32.3% vitamin K antagonists (VKA); 12.1% received antiplatelet agents; 7.8% received no antithrombotic treatment. For comparison, the proportion of phase 1 patients (of N = 1,063 all eligible) prescribed VKA was 32.8%, acetylsalicylic acid 41.7%, and no therapy 20.2%. In Europe in phase 2, treatment with NOAC was more common than VKA (52.3% and 37.8%, respectively); 6.0% of patients received antiplatelet treatment; and 3.8% received no antithrombotic treatment. In North America, 52.1%, 26.2%, and 14.0% of patients received NOAC, VKA, and antiplatelet drugs, respectively; 7.5% received no antithrombotic treatment. NOAC use was less common in Asia (27.7%), where 27.5% of patients received VKA, 25.0% antiplatelet drugs, and 19.8% no antithrombotic treatment. Conclusions The baseline data from GLORIA-AF phase 2 demonstrate that in newly diagnosed nonvalvular atrial fibrillation patients, NOAC have been highly adopted into practice, becoming more frequently prescribed than VKA in Europe and North America. Worldwide, however, a large proportion of patients remain undertreated, particularly in Asia and North America. (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients With Atrial Fibrillation [GLORIA-AF]; NCT01468701

Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017

A double burden of malnutrition occurs when individuals, household members or communities experience both undernutrition and overweight. Here, we show geospatial estimates of overweight and wasting prevalence among children under 5 years of age in 105 low- and middle-income countries (LMICs) from 2000 to 2017 and aggregate these to policy-relevant administrative units. Wasting decreased overall across LMICs between 2000 and 2017, from 8.4% (62.3 (55.1–70.8) million) to 6.4% (58.3 (47.6–70.7) million), but is predicted to remain above the World Health Organization’s Global Nutrition Target of <5% in over half of LMICs by 2025. Prevalence of overweight increased from 5.2% (30 (22.8–38.5) million) in 2000 to 6.0% (55.5 (44.8–67.9) million) children aged under 5 years in 2017. Areas most affected by double burden of malnutrition were located in Indonesia, Thailand, southeastern China, Botswana, Cameroon and central Nigeria. Our estimates provide a new perspective to researchers, policy makers and public health agencies in their efforts to address this global childhood syndemic