A Bayesian Causal Inference Approach for Assessing Fairness in Clinical Decision-Making

Fairness in clinical decision-making is a critical element of health equity, but assessing fairness of clinical decisions from observational data is challenging. Recently, many fairness notions have been proposed to quantify fairness in decision-making, among which causality-based fairness notions have gained increasing attention due to its potential in adjusting for confounding and reasoning about bias. However, causal fairness notions remain under-explored in the context of clinical decision-making with large-scale healthcare data. In this work, we propose a Bayesian causal inference approach for assessing a causal fairness notion called principal fairness in clinical settings. We demonstrate our approach using both simulated data and electronic health records (EHR) data

Making effective use of healthcare data using data-to-text technology

Healthcare organizations are in a continuous effort to improve health outcomes, reduce costs and enhance patient experience of care. Data is essential to measure and help achieving these improvements in healthcare delivery. Consequently, a data influx from various clinical, financial and operational sources is now overtaking healthcare organizations and their patients. The effective use of this data, however, is a major challenge. Clearly, text is an important medium to make data accessible. Financial reports are produced to assess healthcare organizations on some key performance indicators to steer their healthcare delivery. Similarly, at a clinical level, data on patient status is conveyed by means of textual descriptions to facilitate patient review, shift handover and care transitions. Likewise, patients are informed about data on their health status and treatments via text, in the form of reports or via ehealth platforms by their doctors. Unfortunately, such text is the outcome of a highly labour-intensive process if it is done by healthcare professionals. It is also prone to incompleteness, subjectivity and hard to scale up to different domains, wider audiences and varying communication purposes. Data-to-text is a recent breakthrough technology in artificial intelligence which automatically generates natural language in the form of text or speech from data. This chapter provides a survey of data-to-text technology, with a focus on how it can be deployed in a healthcare setting. It will (1) give an up-to-date synthesis of data-to-text approaches, (2) give a categorized overview of use cases in healthcare, (3) seek to make a strong case for evaluating and implementing data-to-text in a healthcare setting, and (4) highlight recent research challenges.Comment: 27 pages, 2 figures, book chapte

CSI-OMIM - Clinical Synopsis Search in OMIM

<p>Abstract</p> <p>Background</p> <p>The OMIM database is a tool used daily by geneticists. Syndrome pages include a Clinical Synopsis section containing a list of known phenotypes comprising a clinical syndrome. The phenotypes are in free text and different phrases are often used to describe the same phenotype, the differences originating in spelling variations or typing errors, varying sentence structures and terminological variants.</p> <p>These variations hinder searching for syndromes or using the large amount of phenotypic information for research purposes. In addition, negation forms also create false positives when searching the textual description of phenotypes and induce noise in text mining applications.</p> <p>Description</p> <p>Our method allows efficient and complete search of OMIM phenotypes as well as improved data-mining of the OMIM phenome. Applying natural language processing, each phrase is tagged with additional semantic information using UMLS and MESH. Using a grammar based method, annotated phrases are clustered into groups denoting similar phenotypes. These groups of synonymous expressions enable precise search, as query terms can be matched with the many variations that appear in OMIM, while avoiding over-matching expressions that include the query term in a negative context. On the basis of these clusters, we computed pair-wise similarity among syndromes in OMIM. Using this new similarity measure, we identified 79,770 new connections between syndromes, an average of 16 new connections per syndrome. Our project is Web-based and available at <url>http://fohs.bgu.ac.il/s2g/csiomim</url></p> <p>Conclusions</p> <p>The resulting enhanced search functionality provides clinicians with an efficient tool for diagnosis. This search application is also used for finding similar syndromes for the candidate gene prioritization tool S2G.</p> <p>The enhanced OMIM database we produced can be further used for bioinformatics purposes such as linking phenotypes and genes based on syndrome similarities and the known genes in Morbidmap.</p

Normalizing acronyms and abbreviations to aid patient understanding of clinical texts: ShARe/CLEF eHealth Challenge 2013, Task 2

Background: The ShARe/CLEF eHealth challenge lab aims to stimulate development of natural language processing and information retrieval technologies to aid patients in understanding their clinical reports. In clinical text, acronyms and abbreviations, also referenced as short forms, can be difficult for patients to understand. For one of three shared tasks in 2013 (Task 2), we generated a reference standard of clinical short forms normalized to the Unified Medical Language System. This reference standard can be used to improve patient understanding by linking to web sources with lay descriptions of annotated short forms or by substituting short forms with a more simplified, lay term. Methods: In this study, we evaluate 1) accuracy of participating systems’ normalizing short forms compared to a majority sense baseline approach, 2) performance of participants’ systems for short forms with variable majority sense distributions, and 3) report the accuracy of participating systems’ normalizing shared normalized concepts between the test set and the Consumer Health Vocabulary, a vocabulary of lay medical terms. Results: The best systems submitted by the five participating teams performed with accuracies ranging from 43 to 72 %. A majority sense baseline approach achieved the second best performance. The performance of participating systems for normalizing short forms with two or more senses with low ambiguity (majority sense greater than 80 %) ranged from 52 to 78 % accuracy, with two or more senses with moderate ambiguity (majority sense between 50 and 80 %) ranged from 23 to 57 % accuracy, and with two or more senses with high ambiguity (majority sense less than 50 %) ranged from 2 to 45 % accuracy. With respect to the ShARe test set, 69 % of short form annotations contained common concept unique identifiers with the Consumer Health Vocabulary. For these 2594 possible annotations, the performance of participating systems ranged from 50 to 75 % accuracy. Conclusion: Short form normalization continues to be a challenging problem. Short form normalization systems perform with moderate to reasonable accuracies. The Consumer Health Vocabulary could enrich its knowledge base with missed concept unique identifiers from the ShARe test set to further support patient understanding of unfamiliar medical terms.</p

Self-reported use of complementary and alternative medicine (CAM) products in topical treatment of diabetic foot disorders by diabetic patients in Jeddah, Western Saudi Arabia

<p>Abstract</p> <p>Background</p> <p>There is little published on current Saudi diabetic patients' practices when they are exposed to foot disorders such as open wound, ulcer, and skin cracks. These factors are usually influenced by local culture and communities beliefs. The aim of the current study was to identify the pattern of patients' use of CAM products in dealing with diabetic foot disorders topically in a group of diabetic patients.</p> <p>Findings</p> <p>A Cross-sectional descriptive study of a representative cohort of diabetic patients living in Jeddah, Saudi Arabia was designed. A pre-designed questionnaire to identify local diabetics' practices in dealing topically with foot disorders including open wound, chronic ulcer, and skin cracks was designed. Questionnaire was administered by a group of trained nutrition female students to diabetics face to face living in their neighborhood. A total of 1634 Saudi diabetics were interviewed. Foot disorders occurred in approximately two thirds of the respondents 1006 (61.6%). Out of the 1006 patients who had foot disorders, 653 reported trying some sort of treatment as 307 patients (47.1%) used conventional topical medical treatment alone, 142 (21.7%) used CAM products alone, and 204 (31.2%) used both treatments. The most commonly used CAM product by the patients was Honey (56.6%) followed by Commiphora Molmol (Myrrh) in (37.4%) and Nigellia Sativa (Black seed) in (35.1%). The least to be used was Lawsonia inermis (Henna) in (12.1%). Ten common natural preparations used topically to treat diabetic foot disorders were also identified.</p> <p>Conclusions</p> <p>The use of CAM products in topical treatment of diabetic foot disorders is fairly common among Saudi diabetic patients. Honey headed the list as a solo topical preparation or in combination with other herbs namely black seeds and myrrh. The efficacy of the most common products needs further research.</p

Association of Circulating Monocyte Chemoattractant Protein-1 Levels With Cardiovascular Mortality A Meta-analysis of Population-Based Studies

Importance Human genetics and studies in experimental models support a key role of monocyte-chemoattractant protein-1 (MCP-1) in atherosclerosis. Yet, the associations of circulating MCP-1 levels with risk of coronary heart disease and cardiovascular death in the general population remain largely unexplored. Objective To explore whether circulating levels of MCP-1 are associated with risk of incident coronary heart disease, myocardial infarction, and cardiovascular mortality in the general population. Data Sources and Selection Population-based cohort studies, identified through a systematic review, that have examined associations of circulating MCP-1 levels with cardiovascular end points. Data Extraction and Synthesis Using a prespecified harmonized analysis plan, study-specific summary data were obtained from Cox regression models after excluding individuals with overt cardiovascular disease at baseline. Derived hazard ratios (HRs) were synthesized using random-effects meta-analyses. Main Outcomes and Measures: Incident coronary heart disease (myocardial infarction, coronary revascularization, and unstable angina), nonfatal myocardial infarction, and cardiovascular death (from cardiac or cerebrovascular causes). Results The meta-analysis included 7 cohort studies involving 21401 individuals (mean [SD] age, 53.7 [10.2] years;10012 men [46.8%]). Mean (SD) follow-up was 15.3 (4.5) years (326392 person-years at risk). In models adjusting for age, sex, and race/ethnicity, higher MCP-1 levels at baseline were associated with increased risk of coronary heart disease (HR per 1-SD increment in MCP-1 levels: 1.06 [95% CI, 1.01-1.11];P = .01), nonfatal myocardial infarction (HR, 1.07 [95% CI, 1.01-1.13];P = .02), and cardiovascular death (HR, 1.12 [95% CI, 1.05-1.20];P < .001). In analyses comparing MCP-1 quartiles, these associations followed dose-response patterns. After additionally adjusting for vascular risk factors, the risk estimates were attenuated, but the associations of MCP-1 levels with cardiovascular death remained statistically significant, as did the association of MCP-1 levels in the upper quartile with coronary heart disease. There was no significant heterogeneity;the results did not change in sensitivity analyses excluding events occurring in the first 5 years after MCP-1 measurement, and the risk estimates were stable after additional adjustments for circulating levels of interleukin-6 and high-sensitivity C-reactive protein. Conclusions and Relevance: Higher circulating MCP-1 levels are associated with higher long-term cardiovascular mortality in community-dwelling individuals free of overt cardiovascular disease. These findings provide further support for a key role of MCP-1-signaling in cardiovascular disease. Question Are circulating monocyte-chemoattractant protein-1 (MCP-1) levels associated with the risk of cardiovascular disease in the general population? Findings In this meta-analysis of 7 population-based studies involving 21401 individuals who were free of overt cardiovascular disease, higher baseline circulating MCP-1 levels were associated with higher risk of cardiovascular mortality over a follow-up extending beyond 20 years. Meaning By complementing evidence from previous genetic and experimental studies, these results provide additional support for a key role of MCP-1 in cardiovascular disease development. This meta-analysis of 7 population-based cohort studies assesses the association between circulating monocyte-chemoattractant protein-1 levels and risk of cardiovascular disease and death

Circulating Monocyte Chemoattractant Protein-1 and Risk of Stroke: A Meta-Analysis of Population-Based Studies Involving 17,180 Individuals.

RATIONALE: Pro-inflammatory cytokines have been identified as potential targets for lowering vascular risk. Experimental evidence and Mendelian randomization suggest a role of monocyte-chemoattractant protein-1 (MCP-1) in atherosclerosis and stroke. However, data from large-scale observational studies are lacking. OBJECTIVE: To determine whether circulating levels of MCP-1 are associated with risk of incident stroke in the general population. METHODS AND RESULTS: We used previously unpublished data on 17,180 stroke-free individuals (mean age 56.7{plus minus}8.1 years; 48.8% males) from six population-based prospective cohort studies and explored associations between baseline circulating MCP-1 levels and risk of any stroke, ischemic stroke, and hemorrhagic stroke over a mean follow-up interval of 16.3 years (280,522 person-years at risk; 1,435 incident stroke events). We applied Cox proportional hazard models and pooled hazard ratios (HR) using random-effects meta-analyses. Following adjustments for age, sex, race, and vascular risk factors, higher MCP-1 levels were associated with increased risk of any stroke (HR per 1 SD increment in ln-transformed MCP-1: 1.07, 95%CI: 1.01-1.14). Focusing on stroke subtypes, we found a significant association between baseline MCP-1 levels and higher risk of ischemic stroke (HR: 1.11, [1.02-1.21]), but not hemorrhagic stroke (HR: 1.02, [0.82-1.29]). The results followed a dose-response pattern with a higher risk of ischemic stroke among individuals in the upper quartiles of MCP-1 levels as compared to the 1st quartile (HRs: 2nd quartile: 1.19 [1.00-1.42]; 3rd quartile: 1.35, [1.14-1.59]; 4th quartile: 1.38, [1.07-1.77]). There was no indication for heterogeneity across studies and in a sub-sample of four studies (12,516 individuals) the risk estimates were stable after additional adjustments for circulating levels of interleukin-6 and high-sensitivity C-reactive protein. CONCLUSIONS: Higher circulating levels of MCP-1 are associated with increased long-term risk of stroke. Our findings along with genetic and experimental evidence suggest that MCP-1-signaling might represent a therapeutic target to lower stroke risk.M. Georgakis is funded by scholarships from the German Academic Exchange Service (DAAD) and Onassis Foundation. The ARIC study has been funded in whole or in part with Federal funds from the National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services, under Contract nos. (HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700005I, HHSN268201700004I). The DHS study was funded by a grant from the Donald W. Reynolds Foundation. The EPIC-Norfolk study is funded by grants from the Medical Research Council UK (G9502233, G0401527) and Cancer Research UK (C864/A8257, C864/A2883). FHS is supported by the National Heart, Lung and Blood Institute’s Framingham Heart Study (Contract No. N01-HC-25195 and No. HHSN268201500001I and 75N92019D00031), received funding by grants from the National Institute of Aging (R01s AG054076, AG049607, AG059421, U01-AG049505, AG058589 and AG052409) and the National Institute of Neurological Disorders and Stroke (R01 NS017950, UH2 NS100605), as well as grants for the MCP-1 measurements by NIH (1RO1 HL64753, R01 HL076784, 1 R01 AG028321). The KORA study was initiated and financed by the Helmholtz Zentrum München – German Research Center for Environmental Health, which is funded by the German Federal Ministry of Education and Research (BMBF) and by the State of Bavaria. Furthermore, KORA research was supported within the Munich Center of Health Sciences (MC-Health), Ludwig-Maximilians-Universität, as part of LMUinnovativ. The MDCS-CV study has been supported with funding from the Swedish Research Council, Swedish Heart and Lung Foundations, and the Swedish Foundation for Strategic Research. This project has received funding from the European Union’s Horizon 2020 research and innovation programme (No 666881), SVDs@target (to M. Dichgans) and No 667375, CoSTREAM (to M. Dichgans); the DFG as part of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy – ID 390857198) and the CRC 1123 (B3) (to M. Dichgans); the Corona Foundation (to M. Dichgans); the Fondation Leducq (Transatlantic Network of Excellence on the Pathogenesis of Small Vessel Disease of the Brain)(to M. Dichgans); the e:Med program (e:AtheroSysMed) (to M. Dichgans) and the FP7/2007-2103 European Union project CVgenes@target (grant agreement number Health-F2-2013-601456) (to M. Dichgans)