[Physician-patient interactions: a comparison of analysis systems]

Applying a multidimensional approach to understanding clinical conversations: A deprescribing case study in primary care

OBJECTIVE

To describe and evaluate the contribution of multiple coding approaches applied to a clinical conversation on deprescribing in primary care (PC).

METHODS

Seven distinct coding approaches were applied to one audiotaped consultation. Only exchanges related to deprescribing a benzodiazepine (BZD) were coded for: content, interaction, arguments, connectors, transitions, orientation towards deprescribing and concordance with a deprescribing algorithm. A discursive map presents the unfolding of the exchanges.

RESULTS

The deprescribing conversation was broken down into 31 utterances divided into three segments: opening (n = 6), development (n = 16) and closing (n = 9). The family physician dominated the last two segments and most of her utterances were favorable to BZD deprescribing while the patient's utterances were generally unfavorable in the first two segments. The number of distinct codes assigned to utterances varied according to the coding approach. The map illustrates how each utterance can be viewed through different lenses revealing the dynamics and complexity of the deprescribing conversation.

CONCLUSION

This multidimensional methodological approach with its proposed way of presenting results, either quantitatively or qualitatively, and its map offer a comprehensive evaluation of the deprescribing process in this PC setting.

PRACTICE IMPLICATIONS

This novel multidimensional coding approach has potential to be applied to a range of other topics in clinical communications.

[The Verona Medical Interview Classification System/Patient (VR-MICS/P): the tool and its reliability]

OBJECTIVE

To assess the reliability and to describe the categories and the procedure to apply the VR-MICS/P (Verona-Medical Interview Classification System/Patient).

SETTING

The interviews used for the reliability study were audiotaped. Five general practitioners (GPs) working in two general practices in South-Verona recorded their consultations.

SAMPLE

50 interviews selected randomly from 120, 10 for each GP. The selection criterion for the participating patients was a GHQ-12 score of 3 and the consultation for a new illness episode.

MAIN OUTCOME MEASURES

The VR-MICS/P classifies patients' verbal behaviours into 21 categories, 15 of them are defined by form (cue or statement) and content.

PROCEDURE

Two trained raters classified 50 interviews. Before applying the classification system each interview is divided into units which are numbered to define doctor's and patient's sequence of speech.

RESULTS

The reliability of VR-MICS/P was satisfactory (Kappa 0.85). Similarity Index (Dice, 1945) for categories varied between 0.71 and 0.94. Reliability for form and content classification was satisfactory too (Similarity Index between 0.81 and 0.89 and between 0.84 and 0.94, respectively).

CONCLUSIONS

The VR-MICS/P is a reliable measure for describing patients' verbal behaviours during medical interviews. It can be used together with the VR-MICS/D (Verona-Medical Interview Classification System/Doctor; Saltini et al., 1998) to describe the medical interview, the quality of doctor-patient interview and can be used as a measure of patient centredness.

[An instrument for evaluating th medical interview in general practice: VR-MICS/D (Verona-Medical Interview Classification System/Doctor)]

OBJECTIVE

To assess the reliability of the VR-MICS/D (Verona-Medical Interview Classification System/Doctor) and to identify the verbal behaviour by general practitioners in interviews conducted with primary care attenders with medical complaints and emotional distress.

SETTING

Two general practices in South-Verona.

SAMPLE

100 primary care patients attending for a new illness episode with a GHQ-12 score > or = 3. The five participating GPs contributed each with 20 audiotaped interviews of 10 patients judged by GP as emotionally distressed and of 10 judged without emotional distress.

MAIN OUTCOME MEASURES

The VR-MICS/D classifies GPs' verbal behaviour during the medical interview into 16 categories in terms of form (question or statement) and content and allows to assess their interview skills.

PROCEDURE

Two raters classified 30 interviews (15 with patients judged by their GP as emotionally distressed and 15 with patients judged without emotional distress). Having established satisfactory reliability, the overall verbal performance, based on 100 interviews, was assessed and GPs' verbal behaviours with patients judged as emotionally distressed was compared with that adopted with patients judged without emotional distress.

RESULTS

The reliability was satisfactory (Kappa 0.93). Percentage agreements for categories varied between 78.2% and 96.4%. The most frequent verbal behaviours were closed ended questions and information giving (58% of a total of 5522 classified verbal units). Interviews with patients judged as emotional distressed contained a greater number of psychological and psychosocial contents, facilitating comments and clarifications. These differences, however, were small, despite their statistical significance.

CONCLUSIONS

The VR-MICS/D is a reliable measure for describing GPs' verbal behaviour during the interview with emotional distressed patients. The interview style of the GPs in this study was similar to that reported in the literature for GPs without formal training in communication skills and was characterised by a prevalently doctor-centred approach. This approach, particularly with emotional distressed patients, has severe limitations and underlines the necessity of the introduction of communication skills training.