Waiting for child developmental and rehabilitation services

See related article on page 815 The paper by Miller et al. in this issue reviews an important issue of concern to all those working in this field: waiting for assessment and treatment. The authors have attempted an overview of the current state of thinking, knowledge, and practice with children waiting for child developmental and rehabilitation (CDR) services, and have pointed to the key ingredients to help the field move forward. There is a helpful literature review, both informal and systematic. Using a systematic review approach, Miller and colleagues find little data specific to CDR services on waiting times. Alternative methodologies might obtain significant and useful unpublished material – e.g. data on waiting times may have been collected locally – and therefore potentially available by a survey of professionals in the field. The authors therefore discuss the general literature on waiting times. I particularly appreciated their drawing out questions of whether improvements in accessibility occur at the cost of effectiveness, the risk that measuring waiting times in isolation can produce a distorted picture of quality of care, the need to understand assessment/decision-making processes in a complex field (are cases allocated to the correct waiting list?), and the value of delivering alternative interventions rather than just increasing resources. Views of participants in the (Canadian) national workshop on the topic convened by the authors are summarized on the clinical significance of waiting for CDR services, confirming the lack of evidence or even consensus, the risk that attention to waiting times could distract from situations with no service at all, and discussing issues of data collection in a complex field. Miller and colleagues have illustrated the discussion with three specific successful interventions (two unpublished) for reducing waiting times. Although the authors are clear later in the paper that interventions that reduce waiting times should also assess comparability of effectiveness (and they suggest appropriate outcomes to study), they do not critique the interventions they report in this way (perhaps prevented by limited data?). They then offer a proposed approach to addressing waiting times, beautifully supported by the previous discussion of the literature and the themes identified by workshop participants, involving clarity and consensus in definition and measurement, with comprehensive and effective patient registration and data management. They are clear that progress in this area should go hand in hand with developments in the evidence-base of effective interventions, using pragmatic trials and/or geographical controls in areas where randomized controlled trials are difficult to organize. The suggestions of further research on families’ experience of waiting, how to improve this, and how to assess risk during waiting, are interesting. They affirm the impact of collaborative networks, and report the state of emerging networks in Canada. In my experience if clinicians are able to agree the parameters for gathering and reporting data, they are in a very powerful position to engage with managers and commissioners to address inequalities and gaps in service. The concluding discussion is of obstacles to action, especially complexity, which they argue can be dealt with by focusing on ‘sentinel’ components of pathways and standardization via consensus-building. Overall this is a helpful discussion of a complex field of high significance to many of our readers. In my view the key tension in their approach is between complexity and clarity. The case for clarity is immediately apparent, with great strength in the approach proposed. Effective networks are a key tool in this process, and we each have a duty to contribute to their development, being willing to modify our own systems of data collection to contribute to a coherent whole where possible. However, focusing on a limited number of ‘sentinel’ components and areas where there is already a significant evidence-base risks neglecting the most underfunded, poorly-evidenced, or complex services. Practitioners who contribute effectively to the multi-agency care of children with life-trajectories of developmental, mental health, and social difficulty in a complex social and cultural background may resist excessive simplification of their multifactorial assessments to contribute to these pathways and networks. Approaches of life course or developmental trajectory modelling,1 currently being developed from longitudinal epidemiological studies, may offer very convincing ways to select key factors to be treated and measured in future. More pragmatically, in the UK there are examples where the National Health Service has responded to evidence that a practice is in widespread use by funding research to assess its effectiveness. Monitoring what services are being waited for regardless of the evidence available to date may be of value to argue for testing their effectiveness. Examples of methods that have been used to build consensus, with their pros and cons, would add significantly to this developing field. What aspects of such a process might protect from distortion and oversimplification?

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.