The importance of developmental field trials in the revision of psychiatric classifications

"I was very sad, but not depressed": phenomenological differences between adjustment disorder and a major depressive episode

Introduction

Adjustment disorder (AD) is a diagnosis that must be differentiated from major depressive episode (MDE) because of the therapeutic implications. The aim of this study is to understand the experience of patients who in their lifetime have been diagnosed with AD as well as MDE to establish the characteristics of each disorder.

Methods

A descriptive phenomenological approach was used with in-depth interviews to four patients and the method proposed by Colaizzi to understand the experiences and reach the description of both disorders.

Results

Three women and one man, with advanced schooling were interviewed. The participants emphasized the existence of differences that were grouped in: the attribution made by the individual, the theme of cognitions, the variability in the course, the possibility of mood modulation, the syndrome severity, the presence of hopelessness and the perceived course.

Conclusion

Phenomenological differences were found in the subjective experience of MDE and AD. The MDE would be described as an intense state of generalized shutdown of the subject's own life, with little response to events, and the AD, as a dynamic reaction attributed to a stressful event, with high variability in the course of symptoms due to the dependence on such event, with the preserved hope that it will end.

The operational paradigm in psychiatry: How valid is it?

BACKGROUND

One of the criticisms of the operational/diagnostic criteria, generalised since DSM-III, has been that they were shaped solely to achieve the best inter-peer reliability with no considerations for validity. This does not fully reflect reality since throughout the development of the criteria, there was an effort to define and fulfil some validity requirements. However, despite several attempts to create alternative diagnostic systems, there is still a widespread misunderstanding of the epistemological foundations that support this paradigm.

METHODS

In this article, we intend to analyse the epistemological context in which the operational criteria (OC) emerged and some of the validation processes they have undergone since their conception.

RESULTS

On the epistemological basis of these operational criteria (OC) the influence of Hempel has been widely discussed. However, the group from St. Louis and, also the DSM-III editors, never openly acknowledged his role and his contribution and revealed other influences such as other medical specialties (that used and validated several OC in the diagnosis of their diseases). On the other hand, contrary to what has often been mentioned there has been a continuous attempt to validate the OC since their conception. In the implementation and development of the operational paradigm, a more instrumental trend was followed, focused on utility, but with successive attempts to achieve realistic validity by searching for biological or psychological causality. The methodologies were initially expert-driven and gradually more data-driven and included some variables external to the construct itself, such as familial aggregation, diagnostic consistency over time, prognostic and other psychometric measures.

Network biomarkers in recovered psychosis patients who discontinued antipsychotics

There are no studies investigating topological properties of resting-state fMRI (rs-fMRI) in patients who have recovered from psychosis and discontinued medication (hereafter, recovered patients [RP]). This study aimed to explore topological organization of the functional brain connectome in the RP using graph theory approach. We recruited 30 RP and 50 age and sex-matched healthy controls (HC). The RP were further divided into the subjects who were relapsed after discontinuation of antipsychotics (RP-R) and who maintained recovered state without relapse (RP-M). Using graph-based network analysis of rs-fMRI signals, global and local metrics and hub information were obtained. The robustness of the network was tested with random failure and targeted attack. As an ancillary analysis, Network-Based Statistic (NBS) was performed. Association of significant findings with psychopathology and cognitive functioning was also explored. The RP showed intact network properties in terms of global and local metrics. However, higher global functional connectivity strength and hyperconnectivity in the interconnected component were observed in the RP compared to HC. In the subgroup analysis, the RP-R were found to have lower global efficiency, longer characteristic path length and lower robustness whereas no such abnormalities were identified in the RP-M. Associations of the degree centrality of some hubs with cognitive functioning were identified in the RP-M. Even though network properties of the RP were intact, subgroup analysis revealed more altered topological organizations in the RP-R. The findings in the RP-R and RP-M may serve as network biomarkers for predicting relapse or maintained recovery after the discontinuation of antipsychotics.

An ecological study of objective rest-activity markers of lithium response in bipolar-I-disorder

BACKGROUND

Despite its pivotal role in prophylaxis for bipolar-I-disorders (BD-I), variability in lithium (Li) response is poorly understood and only a third of patients show a good outcome. Converging research strands indicate that rest-activity rhythms can help characterize BD-I and might differentiate good responders (GR) and non-responders (NR).

METHODS

Seventy outpatients with BD-I receiving Li prophylaxis were categorized as GR or NR according to the ratings on the retrospective assessment of response to lithium scale (Alda scale). Participants undertook 21 consecutive days of actigraphy monitoring of sleep quantity (SQ), sleep variability (SV) and circadian rhythmicity (CR).

RESULTS

Twenty-five individuals were categorized as GR (36%). After correcting statistical analysis to minimize false discoveries, four variables (intra-daily variability; median activity level; amplitude; and relative amplitude of activity) significantly differentiated GR from NR. The odds of being classified as a GR case were greatest for individuals showing more regular/stable CR (1.41; 95% confidence interval (CI) 1.08, 2.05; p < 0.04). Also, there was a trend for lower SV to be associated with GR (odds ratio: 0.56; 95% CI 0.31, 1.01; p < 0.06).

CONCLUSIONS

To our knowledge, this is the largest actigraphy study of rest-activity rhythms and Li response. Circadian markers associated with fragmentation, variability, amount and/or amplitude of day and night-time activity best-identified GR. However, associations were modest and future research must determine whether these objectively measured parameters, singly or together, represent robust treatment response biomarkers. Actigraphy may offer an adjunct to multi-platform approaches aimed at developing personalized treatments or stratification of individuals with BD-I into treatment-relevant subgroups.

Regulation of sensorimotor gating via Disc1/Huntingtin-mediated Bdnf transport in the cortico-striatal circuit

Sensorimotor information processing underlies normal cognitive and behavioral traits and has classically been evaluated through prepulse inhibition (PPI) of a startle reflex. PPI is a behavioral dimension deregulated in several neurological and psychiatric disorders, yet the mechanisms underlying the cross-diagnostic nature of PPI deficits across these conditions remain to be understood. To identify circuitry mechanisms for PPI, we performed circuitry recording over the prefrontal cortex and striatum, two brain regions previously implicated in PPI, using wild-type (WT) mice compared to Disc1-locus-impairment (LI) mice, a model representing neuropsychiatric conditions. We demonstrated that the corticostriatal projection regulates neurophysiological responses during the PPI testing in WT, whereas these circuitry responses were disrupted in Disc1-LI mice. Because our biochemical analyses revealed attenuated brain-derived neurotrophic factor (Bdnf) transport along the corticostriatal circuit in Disc1-LI mice, we investigated the potential role of Bdnf in this circuitry for regulation of PPI. Virus-mediated delivery of Bdnf into the striatum rescued PPI deficits in Disc1-LI mice. Pharmacologically augmenting Bdnf transport by chronic lithium administration, partly via phosphorylation of Huntingtin (Htt) serine-421 and its integration into the motor machinery, restored striatal Bdnf levels and rescued PPI deficits in Disc1-LI mice. Furthermore, reducing the cortical Bdnf expression negated this rescuing effect of lithium, confirming the key role of Bdnf in lithium-mediated PPI rescuing. Collectively, the data suggest that striatal Bdnf supply, collaboratively regulated by Htt and Disc1 along the corticostriatal circuit, is involved in sensorimotor gating, highlighting the utility of dimensional approach in investigating pathophysiological mechanisms across neuropsychiatric disorders.

Using density of antecedent events and trajectory path analysis to investigate family-correlated patterns of onset of bipolar I disorder: a comparison of cohorts from Europe and USA

BACKGROUND

Major contributors to the global burden of bipolar disorders (BD) are the early age at onset (AAO) and the co-occurrence of non-mood disorders before and after the onset of BD. Using data from two independent cohorts from Europe and the USA, we investigated whether the trajectories of BD-I onset and patterns of psychiatric comorbidities differed in (a) individuals with or without a family history (FH) of BD, or (b) probands and parents who both had BD-I.

METHODS

First, we estimated cumulative probabilities and AAO of comorbid mental disorders in familial and non-familial cases of BD-I (Europe, n = 573), and sex-matched proband-parent pairs of BD-I cases (USA, n = 194). Then we used time to onset analyses to compare overall AAO of BD-I and AAO according to onset polarity. Next, we examined associations between AAO and polarity of onset of BD-I according to individual experiences of comorbidities. This included analysis of the density of antecedent events (defined as the number of antecedent comorbidities per year of exposure to mental illness per individual) and time trend analysis of trajectory paths plotted for the subgroups included in each cohort (using R² goodness of fit analysis).

RESULTS

Earlier AAO of BD-I was found in FH versus non-FH cases (log rank test = 7.63; p = 0.006) and in probands versus parents with BD-I (log rank test = 15.31; p = 0.001). In the European cohort, AAO of BD-I was significantly associated with factors such as: FH of BD (hazard ratio [HR]: 0.60), earlier AAO of first non-mood disorder (HR: 0.93) and greater number of comorbidities (HR: 0.74). In the USA cohort, probands with BD-I had an earlier AAO for depressive and manic episodes and AAO was also associated with e.g., number of comorbidities (HR: 0.65) and year of birth (HR: 2.44). Trajectory path analysis indicated significant differences in density of antecedents between subgroups within each cohort. However, the time trend R² analysis was significantly different for the European cohort only.

CONCLUSIONS

Estimating density of antecedent events and comparing trajectory plots for different BD subgroups are informative adjuncts to established statistical approaches and may offer additional insights that enhance understanding of the evolution of BD-I.

Imbalance Model of Heart Rate Variability and Pulse Wave Velocity in Psychotic and Nonpsychotic Disorders

OBJECTIVES

Patients with psychiatric disorders have an increased risk of cardiovascular pathologies. A bidirectional feedback model between the brain and heart exists widely in both psychotic and nonpsychotic disorders. The aim of this study was to compare heart rate variability (HRV) and pulse wave velocity (PWV) functions between patients with psychotic and nonpsychotic disorders and to investigate whether subgroups defined by HRV and PWV features improve the transdiagnostic psychopathology of psychiatric classification.

METHODS

In total, 3448 consecutive patients who visited psychiatric or psychological health services with psychotic (N = 1839) and nonpsychotic disorders (N = 1609) and were drug-free for at least 2 weeks were selected. HRV and PWV indicators were measured via finger photoplethysmography during a 5-minute period of rest. Canonical variates were generated through HRV and PWV indicators by canonical correlation analysis (CCA).

RESULTS

All HRV indicators but none of the PWV indicators were significantly reduced in the psychotic group relative to those in the nonpsychotic group. After adjusting for age, gender, and body mass index, many indices of HRV were significantly reduced in the psychotic group compared with those in the nonpsychotic group. CCA analysis revealed 2 subgroups defined by distinct and relatively homogeneous patterns along HRV and PWV dimensions and comprising 19.0% (subgroup 1, n = 655) and 80.9% (subgroup 2, n = 2781) of the sample, each with distinctive features of HRV and PWV functions.

CONCLUSIONS

HRV functions are significantly impaired among psychiatric patients, especially in those with psychosis. Our results highlight important subgroups of psychiatric patients that have distinct features of HRV and PWV which transcend current diagnostic boundaries.

Reliability and Clinical Utility of Gender Identity-Related Diagnoses: Comparisons Between the ICD-11, ICD-10, DSM-IV, and DSM-5

Purpose: The World Health Organization general assembly approved the 11th revision of the International Classification of Diseases (ICD) in 2019 which will be implemented in 2022. Gender identity-related diagnoses were substantially reconceptualized and removed from the mental health chapter so that the distress criterion is no longer a prerequisite. The present study examined reliability and clinical utility of gender identity-related diagnoses of the ICD-11 in comparison with the Diagnostic and Statistical Manual of Mental Disorders (DSM)-5, ICD-10, and DSM-IV. Methods: Sixty-four health care providers assessed six videos of two children, two adolescents, and two adults referred for gender incongruence. Each provider rated one pair of videos with three of the four classification systems (ICD-11, DSM-5, ICD-10, and DSM-IV-TR). This resulted in 72 ratings for the adolescent and adult diagnoses and 59 ratings for the children's diagnoses. Results: Interrater agreement rates for each instrument ranged from 65% to 79% for the adolescence/adulthood diagnoses and from 67% to 94% for the childhood diagnoses and were comparable regardless of the system used. Only agreement rates for ICD-11 were significantly better than those for DSM-5 for both age categories. Clinicians evaluated all four systems as convenient and easy to use. Conclusion: In conclusion, both classification systems (DSM and ICD) and both editions (DSM-IV and DSM-5 and ICD-10 and ICD-11) of gender identity-related diagnoses seem reliable and convenient for clinical use.

Building a statistical classification: A new tool for classification development and testing

Statistical classifications are essential for collecting consistent data that can be compared over space and time. However, a publicly-documented body of practice concerning how to undertake the development and testing of a statistical classification is currently lacking. What aspects of the classification should be tested during the development process? How do we judge whether the classification is fit-for-purpose? How should problems and shortcomings be identified so that they can be remedied? To fill this gap, we drew on existing, authoritative sources to develop an analytic structure for use in the development and testing of statistical classifications. It consists of two components: (1) a statistical classification development and testing framework reflecting the required features of a statistical classification; and (2) a 4-tier model representing the main elements that make up a statistical classification, to use as a heuristic structure within which to locate issues identified and consider how they can be addressed. In this paper, we outline the development of the framework and model, and reflect on their application in testing a draft classification of health interventions. We propose this analytic structure as a new tool to support those engaged in the development of statistical classifications.

Can network analysis shed light on predictors of lithium response in bipolar I disorder?

OBJECTIVE

To undertake a large-scale clinical study of predictors of lithium (Li) response in bipolar I disorder (BD-I) and apply contemporary multivariate approaches to account for inter-relationships between putative predictors.

METHODS

We used network analysis to estimate the number and strength of connections between potential predictors of good Li response (measured by a new scoring algorithm for the Retrospective Assessment of Response to Lithium Scale) in 900 individuals with BD-I recruited to the Consortium of Lithium Genetics.

RESULTS

After accounting for co-associations between potential predictors, the most important factors associated with the good Li response phenotype were panic disorder, manic predominant polarity, manic first episode, age at onset between 15-32 years and family history of BD. Factors most strongly linked to poor outcome were comorbid obsessive-compulsive disorder, alcohol and/or substance misuse, and/or psychosis (symptoms or syndromes).

CONCLUSIONS

Network analysis can offer important additional insights to prospective studies of predictors of Li treatment outcomes. It appears to especially help in further clarifying the role of family history of BD (i.e. its direct and indirect associations) and highlighting the positive and negative associations of different subtypes of anxiety disorders with Li response, particularly the little-known negative association between Li response and obsessive-compulsive disorder.

Prospective cohort study of early biosignatures of response to lithium in bipolar-I-disorders: overview of the H2020-funded R-LiNK initiative

Background

Lithium is recommended as a first line treatment for bipolar disorders. However, only 30% of patients show an optimal outcome and variability in lithium response and tolerability is poorly understood. It remains difficult for clinicians to reliably predict which patients will benefit without recourse to a lengthy treatment trial. Greater precision in the early identification of individuals who are likely to respond to lithium is a significant unmet clinical need.

Structure

The H2020-funded Response to Lithium Network (R-LiNK; http://www.r-link.eu.com/) will undertake a prospective cohort study of over 300 individuals with bipolar-I-disorder who have agreed to commence a trial of lithium treatment following a recommendation by their treating clinician. The study aims to examine the early prediction of lithium response, non-response and tolerability by combining systematic clinical syndrome subtyping with examination of multi-modal biomarkers (or biosignatures), including omics, neuroimaging, and actigraphy, etc. Individuals will be followed up for 24 months and an independent panel will assess and classify each participants’ response to lithium according to predefined criteria that consider evidence of relapse, recurrence, remission, changes in illness activity or treatment failure (e.g. stopping lithium; new prescriptions of other mood stabilizers) and exposure to lithium. Novel elements of this study include the recruitment of a large, multinational, clinically representative sample specifically for the purpose of studying candidate biomarkers and biosignatures; the application of lithium-7 magnetic resonance imaging to explore the distribution of lithium in the brain; development of a digital phenotype (using actigraphy and ecological momentary assessment) to monitor daily variability in symptoms; and economic modelling of the cost-effectiveness of introducing biomarker tests for the customisation of lithium treatment into clinical practice. Also, study participants with sub-optimal medication adherence will be offered brief interventions (which can be delivered via a clinician or smartphone app) to enhance treatment engagement and to minimize confounding of lithium non-response with non-adherence.

Conclusions

The paper outlines the rationale, design and methodology of the first study being undertaken by the newly established R-LiNK collaboration and describes how the project may help to refine the clinical response phenotype and could translate into the personalization of lithium treatment.

Electronic supplementary material

The online version of this article (10.1186/s40345-019-0156-x) contains supplementary material, which is available to authorized users.

Transdiagnostic Dimensions towards Personality Pathology and Childhood Traumatic Experience in a Clinical Sample: Subtype Classification by a Cross-sectional Analysis

Psychiatric disorders are highly heterogeneous syndromes often explained by underlying and internalized personality disorder(PD) traits that are affected by externalized childhood trauma experiences(CTE). The present study investigated the differential subtype model by examining the association between PD traits and CTE in a clinical sample with transdiagnostic psychopathology. Outpatients(n = 2090) presenting for psychiatric treatment completed self-reported measures of PD traits(Personality Diagnostic Questionnaire) and the childhood adversity(Child Trauma Questionnaire). Canonical variates were generated by canonical correlation analysis(CCA) and then used for hierarchical cluster analysis to produce subtypes. A support vector machine(SVM) model was used and validated using a linear kernel to assess the utility of the extracted subtypes of outpatients in clinical diagnosis classifications. The CCA determined two linear combinations: emotional abuse related dissociality PD traits(antisocial and paranoid PD) and emotional neglect related sociality PD traits(schizoid, passive-aggressive, depressive, histrionic, and avoidant PD). A cluster analysis revealed three subtypes defined by distinct and relatively homogeneous patterns along two dimensions, and comprising 17.5%(cluster-1, n = 365), 34.8%(cluster-2, n = 727), and 47.8%(cluster-3, n = 998) of the sample, each with distinctive features of PD traits and CTE. These subtypes suggest more distinct PD trait correlates of CTE manifestations than were captured by clinical phenomenological diagnostic definitions. Our results highlight important subtypes of psychiatric patients that highlight PD traits and CTE that transcend current diagnostic boundaries. The three different subtypes reflect significant differences in PD and CTE characteristics and lend support to efforts to develop PD and childhood trauma targeted psychotherapy that extends to clinical diagnosis-based interventions.

Innovations and changes in the ICD-11 classification of mental, behavioural and neurodevelopmental disorders

Following approval of the ICD-11 by the World Health Assembly in May 2019, World Health Organization (WHO) member states will transition from the ICD-10 to the ICD-11, with reporting of health statistics based on the new system to begin on January 1, 2022. The WHO Department of Mental Health and Substance Abuse will publish Clinical Descriptions and Diagnostic Guidelines (CDDG) for ICD-11 Mental, Behavioural and Neurodevelopmental Disorders following ICD-11's approval. The development of the ICD-11 CDDG over the past decade, based on the principles of clinical utility and global applicability, has been the most broadly international, multilingual, multidisciplinary and participative revision process ever implemented for a classification of mental disorders. Innovations in the ICD-11 include the provision of consistent and systematically characterized information, the adoption of a lifespan approach, and culture-related guidance for each disorder. Dimensional approaches have been incorporated into the classification, particularly for personality disorders and primary psychotic disorders, in ways that are consistent with current evidence, are more compatible with recovery-based approaches, eliminate artificial comorbidity, and more effectively capture changes over time. Here we describe major changes to the structure of the ICD-11 classification of mental disorders as compared to the ICD-10, and the development of two new ICD-11 chapters relevant to mental health practice. We illustrate a set of new categories that have been added to the ICD-11 and present the rationale for their inclusion. Finally, we provide a description of the important changes that have been made in each ICD-11 disorder grouping. This information is intended to be useful for both clinicians and researchers in orienting themselves to the ICD-11 and in preparing for implementation in their own professional contexts.

Can an Integrated Science Approach to Precision Medicine Research Improve Lithium Treatment in Bipolar Disorders?

Clinical practice guidelines identify lithium as a first line treatment for mood stabilization and reduction of suicidality in bipolar disorders (BD); however, most individuals show sub-optimal response. Identifying biomarkers for lithium response could enable personalization of treatment and refine criteria for stratification of BD cases into treatment-relevant subgroups. Existing systematic reviews identify potential biomarkers of lithium response, but none directly address the conceptual issues that need to be addressed to enhance translation of research into precision prescribing of lithium. For example, although clinical syndrome subtyping of BD has not led to customized individual treatments, we emphasize the importance of assessing clinical response phenotypes in biomarker research. Also, we highlight the need to give greater consideration to the quality of prospective longitudinal monitoring of illness activity and the differentiation of non-response from partial or non-adherence with medication. It is unlikely that there is a single biomarker for lithium response or tolerability, so this review argues that more research should be directed toward the exploration of biosignatures. Importantly, we emphasize that an integrative science approach may improve the likelihood of discovering the optimal combination of clinical factors and multimodal biomarkers (e.g., blood omics, neuroimaging, and actigraphy derived-markers). This strategy could uncover a valid lithium response phenotype and facilitate development of a composite prediction algorithm. Lastly, this narrative review discusses how these strategies could improve eligibility criteria for lithium treatment in BD, and highlights barriers to translation to clinical practice including the often-overlooked issue of the cost-effectiveness of introducing biomarker tests in psychiatry.

The ICD-11 developmental field study of reliability of diagnoses of high-burden mental disorders: results among adult patients in mental health settings of 13 countries

Reliable, clinically useful, and globally applicable diagnostic classification of mental disorders is an essential foundation for global mental health. The World Health Organization (WHO) is nearing completion of the 11th revision of the International Classification of Diseases and Related Health Problems (ICD-11). The present study assessed inter-diagnostician reliability of mental disorders accounting for the greatest proportion of global disease burden and the highest levels of service utilization - schizophrenia and other primary psychotic disorders, mood disorders, anxiety and fear-related disorders, and disorders specifically associated with stress - among adult patients presenting for treatment at 28 participating centers in 13 countries. A concurrent joint-rater design was used, focusing specifically on whether two clinicians, relying on the same clinical information, agreed on the diagnosis when separately applying the ICD-11 diagnostic guidelines. A total of 1,806 patients were assessed by 339 clinicians in the local language. Intraclass kappa coefficients for diagnoses weighted by site and study prevalence ranged from 0.45 (dysthymic disorder) to 0.88 (social anxiety disorder) and would be considered moderate to almost perfect for all diagnoses. Overall, the reliability of the ICD-11 diagnostic guidelines was superior to that previously reported for equivalent ICD-10 guidelines. These data provide support for the suitability of the ICD-11 diagnostic guidelines for implementation at a global level. The findings will inform further revision of the ICD-11 diagnostic guidelines prior to their publication and the development of programs to support professional training and implementation of the ICD-11 by WHO member states.

Secular trends in the age at onset of bipolar I disorder - Support for birth cohort effects from interational, multi-centre clinical observational studies

OBJECTIVE

To examine any association of birth decade, sex and exposure to alcohol and/or substance use disorders (ASUD) with age at onset (AAO) of bipolar I disorder (BD-I).

METHODS

Using data from a representative clinical sample of 3896 BD-I cases recruited from 14 European countries, we examined AAO distributions in individuals born in consecutive birth decades. Cumulative probabilities with Mantel-Cox log-rank tests, pairwise comparisons and Odds Ratios (OR) with 95% confidence intervals (95% CI) were employed to analyze AAO according to birth decade, sex, and presence or absence of an ASUD.

RESULTS

In the total sample, median AAO of BD-I decreased from about 41 years for those born in the 1930s to about 26 years for those born in the 1960s. In a sub-sample of 1247 individuals (selected to minimize confounding), AAO significantly decreased for males and females born in each consecutive decade between 1930 and 50 (OR: 0.65; 95% CI: 0.51, 0.81), and for cases with an ASUD as compared to without (OR: 0.77, 95% CI: 0.69, 0.87). The best fitting regression model identified an independent effect for each birth decade and an interaction between ASUD status and sex, with a consistently earlier AAO in males with an ASUD (OR: 0.79: 95% CI: 0.70, 0.91).

CONCLUSIONS

In BD-I cases diagnosed according to internationally recognized criteria and recruited to pan-European clinical observational studies, the AAO distributions are compatible with a birth cohort effect. A potentially modifiable risk factor, namely ASUD status, was associated with the observed reduction in AAO, especially in males.

Use of a New International Classification of Health Interventions for Capturing Information on Health Interventions Relevant to People with Disabilities

Development of the World Health Organization’s International Classification of Health Interventions (ICHI) is currently underway. Once finalised, ICHI will provide a standard basis for collecting, aggregating, analysing, and comparing data on health interventions across all sectors of the health system. In this paper, we introduce the classification, describing its underlying tri-axial structure, organisation and content. We then discuss the potential value of ICHI for capturing information on met and unmet need for health interventions relevant to people with a disability, with a particular focus on interventions to support functioning and health promotion interventions. Early experiences of use of the Swedish National Classification of Social Care Interventions and Activities, which is based closely on ICHI, illustrate the value of a standard classification to support practice and collect statistical data. Testing of the ICHI beta version in a wide range of countries and contexts is now needed so that improvements can be made before it is finalised. Input from those with an interest in the health of people with disabilities and health promotion more broadly is welcomed.