Bridging the Gap: Towards an Expanded Toolkit for ML-Supported Decision-Making in the Public Sector

Machine Learning (ML) systems are becoming instrumental in the public sector, with applications spanning areas like criminal justice, social welfare, financial fraud detection, and public health. While these systems offer great potential benefits to institutional decision-making processes, such as improved efficiency and reliability, they still face the challenge of aligning intricate and nuanced policy objectives with the precise formalization requirements necessitated by ML models. In this paper, we aim to bridge the gap between ML and public sector decision-making by presenting a comprehensive overview of key technical challenges where disjunctions between policy goals and ML models commonly arise. We concentrate on pivotal points of the ML pipeline that connect the model to its operational environment, delving into the significance of representative training data and highlighting the importance of a model setup that facilitates effective decision-making. Additionally, we link these challenges with emerging methodological advancements, encompassing causal ML, domain adaptation, uncertainty quantification, and multi-objective optimization, illustrating the path forward for harmonizing ML and public sector objectives

Prediction of acute myeloid leukaemia risk in healthy individuals

The incidence of acute myeloid leukaemia (AML) increases with age and mortality exceeds 90% when diagnosed after age 65. Most cases arise without any detectable early symptoms and patients usually present with the acute complications of bone marrow failure(1). The onset of such de novo AML cases is typically preceded by the accumulation of somatic mutations in preleukaemic haematopoietic stem and progenitor cells (HSPCs) that undergo clonal expansion(2,3). However, recurrent AML mutations also accumulate in HSPCs during ageing of healthy individuals who do not develop AML, a phenomenon referred to as age-related clonal haematopoiesis (ARCH)(4-8). Here we use deep sequencing to analyse genes that are recurrently mutated in AML to distinguish between individuals who have a high risk of developing AML and those with benign ARCH. We analysed peripheral blood cells from 95 individuals that were obtained on average 6.3 years before AML diagnosis (pre-AML group), together with 414 unselected age- and gender-matched individuals (control group). Pre-AML cases were distinct from controls and had more mutations per sample, higher variant allele frequencies, indicating greater clonal expansion, and showed enrichment of mutations in specific genes. Genetic parameters were used to derive a model that accurately predicted AML-free survival; this model was validated in an independent cohort of 29 pre-AML cases and 262 controls. Because AML is rare, we also developed an AML predictive model using a large electronic health record database that identified individuals at greater risk. Collectively our findings provide proof-of-concept that it is possible to discriminate ARCH from pre-AML many years before malignant transformation. This could in future enable earlier detection and monitoring, and may help to inform intervention

A first update on mapping the human genetic architecture of COVID-19

peer reviewe

Association of opioid use disorder with healthcare utilization and cost in a public health system.

AIM: To quantify the healthcare costs associated with opioid use disorder among members in a public healthcare system and compare them with healthcare costs in the general population. DESIGN: Retrospective cohort study. Inpatient and outpatient care settings of Israel's largest public healthcare provider (that covers 4.7 million members). Participants included 1173 members who had a diagnosis of opioid use disorder in the years between 2013 and 2018. Each patient was matched with 10 controls based on age and sex. MEASUREMENTS: The main outcome was monthly healthcare costs. FINDINGS: The mean monthly healthcare cost of members with opioid use disorder was $1102 compared with$211 among controls. After excluding members with heroin related diagnoses before the index date (to focus on prescription opioids), this healthcare cost ratio did not substantially change. Members with opioid use disorder under the age of 65 years had a cost difference of 6.1-fold, whereas those 65 years and older experienced cost difference of 3.4-fold, compared with controls. The category with the highest cost for members with opioid use disorder was inpatient services, which was 8.7-fold greater than among controls. CONCLUSIONS: Healthcare costs among individuals with opioid use disorder in Israel's public health system are substantially higher than among controls, at least partially attributable to prescription opioid use disorder. Differences are greater among individuals under 65 years

Myocardial injury in hospitalized patients with COVID-19 infection—Risk factors and outcomes

Myocardial injury in hospitalized patients is associated with poor prognosis. This study aimed to evaluate risk factors for myocardial injury in hospitalized patients with coronavirus disease 2019 (COVID-19) and its prognostic value. We retrieved all consecutive patients who were hospitalized in internal medicine departments in a tertiary medical center from February 9th, 2020 to August 28th with a diagnosis of COVID-19. A total of 559 adult patients were hospitalized in the Sheba Medical Center with a diagnosis of COVID-19, 320 (57.24%) of whom were tested for troponin levels within 24-hours of admission, and 91 (28.44%) had elevated levels. Predictors for elevated troponin levels were age (odds ratio [OR], 1.04; 95% confidence interval [CI], 1.01–1.06), female sex (OR, 3.03; 95% CI 1.54–6.25), low systolic blood pressure (OR, 5.91; 95% CI 2.42–14.44) and increased creatinine level (OR, 2.88; 95% CI 1.44–5.73). The risk for death (hazard ratio [HR] 4.32, 95% CI 2.08–8.99) and a composite outcome of invasive ventilation support and death (HR 1.96, 95% CI 1.15–3.37) was significantly higher among patients who had elevated troponin levels. In conclusion, in hospitalized patients with COVID-19, elevated troponin levels are associated with poor prognosis. Hence, troponin levels may be used as an additional tool for risk stratification and a decision guide in patients hospitalized with COVID-19

A randomised controlled trial to investigate the effects of dehydration on tooth colour.

A recently published, large prospective study showed unexpectedly high prevalence of acute pulmonary embolism (APE) among patients hospitalized for syncope. In such a case, a high incidence of recurrent pulmonary embolism is expected among patients who were discharged without APE workup.To determine the incidence of symptomatic APE among patients hospitalized for a first episode of syncope and discharged without APE workup or anticoagulation.This retrospective cohort study included patients hospitalized at Rambam Health Care Campus between January 2006 and February 2017 with a primary admission diagnosis of syncope, who were not investigated for APE and were not taking anticoagulants. The patients were followed up for up to three years after discharge. The occurrence of venous thromboembolism (VTE) during the follow-up period was documented.The median follow-up duration was 33 months. 1,126 subjects completed a three-year follow-up. During this period, 38 patients (3.38%) developed VTE, 17 (1.51%) of them had APE. The cumulative incidence of VTE and APE was 1.9% (95% CI 1.3%-2.5%) and 0.9% (95% CI 0.4%-1.3%) respectively. Only seven subjects developed APE during the first year of follow-up. The median times from the event of syncope to the development of APE and VTE were 18 and 19 months respectively.The cumulative incidence of VTE during a three-year follow-up period after an episode of syncope is low. In the absence of clinical suspicion, a routine diagnostic workup for APE in patients with syncope cannot be recommended

Study flow chart.

<p>* Some patients were excluded due to more than one criterion. CHS–Clalit Health Services; AC- anticoagulation; VTE- venous thromboembolism; PE- pulmonary embolism; DVT- deep vein thrombosis.</p

Detailed description of 12 of 17 patients who developed APE subsequent to discharge after first syncope episode during a 3-year follow-up period.

<p>Detailed description of 12 of 17 patients who developed APE subsequent to discharge after first syncope episode during a 3-year follow-up period.</p

The incidence of acute pulmonary embolism following syncope in anticoagulant-naïve patients: A retrospective cohort study - Fig 2

<p>Cumulative incidence with 95% confidence interval estimate of venous thromboembolism (Fig 2A) and acute pulmonary embolism (Fig 2B) during 36 months after hospitalization for investigation of syncope.</p