38]. Drawing and building on sociotechnical approaches to technology implementation employed in previous work [25,26], has allowed a theoretically informed basis for sampling and analysis. For the period of time we spent in the field we have, we believe, reached saturation as we continued data collection until no new themes emerged. Nevertheless, there are also some limitations including a lack of insight into system developers’ perspectives due to commercial sensitivities and our initial focus on interviewing academic GPs, which was based on pragmatic considerations, may have biased our focus towards issues that are not immediately visible to non- academic practicing clinicians (e.g. they might have attached greater value to the benefits associated with the secondary uses of data for research purposes). Our exploratory focus in an area that lacked empirical insights meant that interviews were appropriate in the context of our study. However, exploring how best to integrate different systems within complex individual user work- flows and derive maximum benefits for all concerned, warrants the need for some more targeted in-depth observational work in individual settings. Considering our Findings in the Light of the Existing Literature We have investigated the often neglected perspectives of clinical coders and considered potential trade-offs between clinical coding by healthcare professionals during the clinical encounter and retrospectively by clinical coders. Although there is an interna- tional drive to increase clinical coding at the point of care to improve data quality [5], our results suggest that this may in practice reduce data quality by increasing inconsistencies in clinical coding. The intuitive assumption that clinical coding at the point of care is preferable should therefore be questioned. Our results confirm the potential value of coded clinical data for managerial and research purposes, but direct patient care benefits are currently lacking as existing systems (e.g. ICD) are often designed primarily for reimbursement [3,39]. This is despite most clinical coding efforts being invested by healthcare professionals, associated risks such as a perceived reduction in the quality of patient contact due to increased administrative activity, and concerns regarding the implications of coding patient diagnoses of often stigmatizing mental health conditions. Other systems, using clinical vocabularies (e.g. Systematized Nomenclature of Medi- cine-Clinical Terms, SNOMED-CT) to document,[19,37] can be more valuable for clinical users as the clinical codes are often captured by the system as a largely background activity, later drawn upon by clinical coding professionals for other purposes. The question is therefore, whether and how clinical coding activity can be optimized by giving different sets of professionals the right tool for their respective purposes. Different mental disorders may have diverse and overlapping biological and experiential causes [8,16]. Despite an increasing recognition that classification and clinical coding systems need to take this complexity into account, existing systems are often viewed as inadequate resulting in inaccurate and/or unrepresen- tative clinical coding [3,7,8,15–17,40–42]. These tensions illustrate the need to balance classification systems without masking the unique complexity of mood disorders. These discussions are particularly relevant in the primary care setting as diagnostic decisions more contestable at the less severe end of the depressive spectrum. Tailoring systems to individual needs, be it countries, care settings, organizations, or individual users, has frequently been proposed in the literature as a way to facilitate adoption [6,8,43]. This may entail giving users and/or organizations the authority to ‘‘There Are Too Many, but Never Enough’’ priorities categories in line with perceived need and increased involvement in the development of clinical codes [4,43]. Our findings highlight the need to achieve a balance between tailoring of systems to promote clinical utility and a degree of standard- ization to allow meaningful analysis of data on a larger scale. One solution may be the combination of coded clinical data entry with free text, which has been found to improve categorization rates amongst users [44]. We have further illustrated the importance of financial incentives in promoting clinical coding activity across care settings [45,46]. In the literature, there is some evidence that linking healthcare professional performance to payment can improve the quality of care [47–49], but there remains a need to explore alternative incentives, such as feedback on user performance – otherwise conditions not included in payment schemes may suffer [47–49]. Tensions between the need to standardize systems whilst maintaining clinical utility were also illustrated by debates surrounding the number of categories in existing mental disorders coding and classification systems. Participants felt that subcatego- ries were becoming increasingly specific as this was desirable for research and management purposes. However, this meant that clinical users were faced with rising numbers of terms, which they often found time-consuming to browse and difficult to remember. Consequently, and in line with our work, existing studies have found that many diagnostic categories in psychiatric settings are not used at all and there is a high incidence of unspecified diagnoses [6,7,50]. A potential solution, frequently mentioned in the literature and also by our participants, could be to reduce the number of diagnostic categories [7,35,38,51,52], which may be achieved by grouping these together around meaningful clusters [7,14,41]. However, the ultimate decision will not only depend on clinical utility, but will also need to be decided on the basis of, amongst other issues, public health utility, which generally requires more granularity [8,41]. Potential Ways Forward Based on our work, we have a range of recommendations, which policy makers may wish to consider when deliberating strategic directions in relation to clinical coding of information in the UK mental health setting and beyond (Table 5). In terms of overall strategy, there is a need to agree centrally determined clinical coding standards and align systems between care settings to facilitate information exchange. This will require some degree of tailoring of systems to local needs to allow effective integration within work practices. National and international quality improvement initiatives have an important potential role to play to ensure clinical coding in line with evidence-based practice. The option of free text information capture in mental health settings is likely to be of continuing importance, but there may be value in considering a balance of coded clinical data entry and free text based on severity and type of diagnoses. For instance, whilst mild depression may need an increased amount of free text as life circumstances are often important, severe depression may be more amenable to clinical coding as patients are most likely to benefit from standardized treatments. Systems which facilitate coding of symptoms initially, followed by coding of diagnoses, would help to address the evolving nature of mental health conditions. Finally, organizations themselves may wish to consider drawing more explicitly on the expertise of local clinical coding teams, who can advise on how best to derive clinical value from systems. Throughout, recognition of professional differences in clinical coding practices is necessary as some professions and their PLOS ONE | www.plosone.org 8 August 2012 | Volume 7 | Issue 8 | e43831