Explaining heterogeneity of individual treatment causal effects by subgroup discovery: An observational case study in antibiotics treatment of acute rhino-sinusitis.

OBJECTIVES: Individuals may respond differently to the same treatment, and there is a need to understand such heterogeneity of causal individual treatment effects. We propose and evaluate a modelling approach to better understand this heterogeneity from observational studies by identifying patient subgroups with a markedly deviating response to treatment. We illustrate this approach in a primary care case-study of antibiotic (AB) prescription on recovery from acute rhino-sinusitis (ARS). METHODS: Our approach consists of four stages and is applied to a large dataset in primary care dataset of 24,392 patients suspected of suffering from ARS. We first identify pre-treatment variables that either confound the relationship between treatment and outcome or are risk factors of the outcome. Second, based on the pre-treatment variables we create Synthetic Random Forest (SRF) models to compute the potential outcomes and subsequently the causal individual treatment effect (ITE) estimates. Third, we perform subgroup discovery using the ITE estimates as outcomes to identify positive and negative responders. Fourth, we evaluate the predictive performance of the identified subgroups for predicting the outcome in two ways: the likelihood ratio test, and whether the subgroups are selected via the Akaike Information Criterion (AIC) using backward stepwise variable selection. We validate the whole modelling strategy by means of 10-fold-cross-validation. RESULTS: Based on 20 pre-treatment variables, four subgroups (three for positive responders and one for negative responders) were identified. The log likelihood ratio tests showed that the subgroups were significant. Variable selection using the AIC kept two of the four subgroups, one for positive responders and one for negative responders. As for the validation of the whole modelling strategy, all reported measures (the number of pre-treatment variables associated with the outcome, number of subgroups, number of subgroups surviving variable selection and coverage) showed little variation. CONCLUSIONS: With the proposed approach, we identified subgroups of positive and negative responders to treatment that markedly deviate from the mean response. The subgroups showed additive predictive value of the outcome. The modelling approach strategy was shown to be robust on this dataset. Our approach was thus able to discover understandable subgroups from observational data that have predictive value and which may be considered by the clinical users to get insight into who responds positively or negatively to a proposed treatment.

An assessment of the Dutch experience with health insurers acting as healthcare advisors.

INTRODUCTION: With managed competition, selective contracting and the appointing of preferred providers are important instruments for health insurers to improve their bargaining position in the healthcare purchasing market. Insurers can offer enrollees extra services, such as advice about their healthcare, to attract them, ensure that they remain loyal, and to channel them to preferred providers. We investigate which advice services insurers in the Dutch system of managed competition offer enrollees, how they inform them about services, and if enrollees use and appreciate them. MATERIALS AND METHODS: From November to December 2017, two researchers independently analyzed the websites of all health insurers in the Netherlands. We also conducted a questionnaire study among 1,500 members (response 44.5%, N = 668) of the Nivel Dutch Health Care Consumer Panel. RESULTS AND DISCUSSION: All insurers offer one or more services. Most enrollees do not know if their insurer offers advice (67-87% per service). Twelve per cent (N = 76) of the enrollees indicate that they ever made use of a service, mostly regarding the choice of provider (N = 42). Respondents who used healthcare advice were satisfied with it. Of all enrollees, 41% indicate that they would probably/certainly, contact their insurer for advice and 37% would appreciate it if their insurer approached them. Among enrollees, 40% indicated the potential advice has some or a major influence on their choice of insurer. CONCLUSIONS: While all insurers offer at least one service, enrollees generally are unaware of them. Only a minority ever made use of such a service. However, a reasonable proportion do appreciate their insurers' advice services and indicate that they would like to have contact with their insurer if they need care. Insurers do not appear to make the best use of the potential for giving healthcare advice and need to think about ways to increase coverage of those services.

Relations Between the Intelligibility of Speech in Noise and Psychophysical Measures of Hearing Measured in Four Languages Using the Auditory Profile Test Battery.

The aim of the present study was to determine the relations between the intelligibility of speech in noise and measures of auditory resolution, loudness recruitment, and cognitive function. The analyses were based on data published earlier as part of the presentation of the Auditory Profile, a test battery implemented in four languages. Tests of the intelligibility of speech, resolution, loudness recruitment, and lexical decision making were measured using headphones in five centers: in Germany, the Netherlands, Sweden, and the United Kingdom. Correlations and stepwise linear regression models were calculated. In sum, 72 hearing-impaired listeners aged 22 to 91 years with a broad range of hearing losses were included in the study. Several significant correlations were found with the intelligibility of speech in noise. Stepwise linear regression analyses showed that pure-tone average, age, spectral and temporal resolution, and loudness recruitment were significant predictors of the intelligibility of speech in fluctuating noise. Complex interrelationships between auditory factors and the intelligibility of speech in noise were revealed using the Auditory Profile data set in four languages. After taking into account the effects of pure-tone average and age, spectral and temporal resolution and loudness recruitment had an added value in the prediction of variation among listeners with respect to the intelligibility of speech in noise. The results of the lexical decision making test were not related to the intelligibility of speech in noise, in the population studied.

Relations between psychophysical measures of spatial hearing and self-reported spatial-hearing abilities.

OBJECTIVE: The aim of the present study was to investigate how well the virtual psychophysical measures of spatial hearing from the preliminary auditory profile predict self-reported spatial-hearing abilities. DESIGN: Virtual spatial-hearings tests (conducted unaided, via headphones) and a questionnaire were administered in five centres in Germany, the Netherlands, Sweden, and the UK. Correlations and stepwise linear regression models were calculated among a group of hearing-impaired listeners. STUDY SAMPLE: Thirty normal-hearing listeners aged 19-39 years, and 72 hearing-impaired listeners aged 22-91 years with a broad range of hearing losses, including asymmetrical and mixed hearing losses. RESULTS: Several significant correlations (between 0.24 and 0.54) were found between results of virtual psychophysical spatial-hearing tests and self-reported localization abilities. Stepwise linear regression analyses showed that the minimum audible angle (MAA) test was a significant predictor for self-reported localization abilities (5% extra explained variance), and the spatial speech reception threshold (SRT) benefit test for self-reported listening to speech in spatial situations (6% extra explained variance). CONCLUSIONS: The MAA test and spatial SRT benefit test are indicative measures of everyday binaural functioning. The binaural SRT benefit test was not found to predict self-reported spatial-hearing abilities.