Can internal medicine specialists diagnose functional somatic disorders (FSDs)? Training and comparison with FSD specialists.

BACKGROUND: Functional somatic disorders (FSD) are a common problem across medical settings and remain challenging to diagnose and treat. Many patients with FSD undergo sequential and unnecessary extensive diagnostic work-up, which is costly for society and stressful for patients. Previous studies have shown that the empirically based FSD diagnostic entities are interrater reliable and stable over time. OBJECTIVE: The aim of this study was to investigate whether internists who have received adequate training and with sufficient time per patient could diagnose FSD. DESIGN: This was a prospective diagnostic accuracy study. The study was conducted from May 2020 to April 2022. PARTICIPANTS: The study included 27 consecutive patients referred by their general practitioner to a non-psychiatric diagnostic clinic for assessment of physical symptoms on suspicion of FSD. INTERVENTIONS: The internists received a 30-hour training course in the use of a tailored version of the SCAN interview. MAIN MEASURES: The main outcome measure was the agreement between the diagnoses of the internists and the reference diagnoses made by specialists in FSD on the basis of the full SCAN interview. KEY RESULTS: The interrater agreement between the internists and the FSD experts was substantial for any FSD (kappa = 0.63) as well as multi-organ vs. single-organ FSD (kappa = 0.73), indicating good diagnostic agreement. CONCLUSIONS: Internists with proper training and sufficient time (3-4 hours) per patient can proficiently diagnose FSD employing a tailored version of the SCAN interview for use in a non-psychiatric diagnostic setting.

[Quality improvement in Danish healthcare services - status and recommendations].

In light of a 2018 report by WHO, OECD and World Bank, we provide a set of recommendations for quality improvement in Danish healthcare services, in this review: 1) Easily accessible decision-relevant local quality data should be provided. 2) The legal basis for quality development and research should be clarified. 3) The effort to develop patient-reported outcome measures should be intensified. 4) All clinicians should be involved in quality improvement, and quality improvement methods should be included in all healthcare professionals' training curricula.

Optimisation of quality indicators for lipid-lowering treatment of type 2 diabetes mellitus.

INTRODUCTION: The Danish Adult Diabetes Database (DADD) annually reports a quality indicator for lipid-lowering treatment of type 2 diabetes mellitus (T2DM) patients. This retrospective cohort study aims to A) investigate the reasons for inadequate or lacking lipid-lowering treatment and to B) assess the validity of the DADD indicator as a measure of quality of care. METHODS: A) A pop-up questionnaire enquiring about reasons for lack of treatment was added to the clinicians' data entry tool in the Central Denmark Region. B) The DADD indicator was compared on a per-clinic basis with the achieved median low-density lipoprotein (LDL) cholesterol level and with an internationally widely used indicator of lipid-lowering treatment quality. RESULTS: A) A total of 3,491 patients were registered from 1 January 2013 to 28 February 2015. For 170 (62%) of 309 patients with an LDL level > 2.5 mmol/l who were not receiving lipid-lowering treatment, there was no "good" explanation for lacking treatment. Among 518 patients with an LDL level > 2.5 mmol/l despite lipid-lowering treatment, 259 (50%) did not receive high-intensity treatment. B) The DADD quality indicator was neither associated with the international quality indicator nor with the median per-clinic LDL level for T2DM patients. CONCLUSIONS: A) We found substantial potential for improvement of lipid management among T2DM patients in Denmark by initiating and/or intensifying lipid-lowering treatment. B) The current DADD indicator is not a valid measure of lipid-lowering quality of care. FUNDING: supported by the Rosa and Asta Jensen Foundation. TRIAL REGISTRATION: not relevant.

Selection of quality indicators for hospital-based emergency care in Denmark, informed by a modified-Delphi process.

BACKGROUND: In 2013, Danish policy-makers on a nationwide level decided to set up a national quality of care database for hospital-based emergency care in Denmark including the selection of quality indicators. The aim of the study was to describe the Delphi process that contributed to the selection of quality indicators for a new national database of hospital-based emergency care in Denmark. METHODS: The process comprised a literature review followed by a modified-Delphi survey process, involving a panel of 54 experts (senior clinicians, researchers and administrators from the emergency area and collaborating specialties). Based on the literature review, we identified 43 potential indicators, of which eight were time-critical conditions. We then consulted the Expert panel in two consecutive rounds. The Expert panel was asked to what extent each indicator would be a good measure of hospital-based emergency care in Denmark. In each round, the Expert panel participants scored each indicator on a Likert scale ranging from one (=disagree completely) through to six (=agree completely). Consensus for a quality indicator was reached if the median was greater than or equal to five (=agree). The Delphi process was followed by final selection by the steering group for the new database. RESULTS: Following round two of the Expert panel, consensus was reached on 32 quality indicators, including three time-critical conditions. Subsequently, the database steering group chose a set of nine quality indicators for the initial version of the national database for hospital-based emergency care. CONCLUSIONS: The two-round modified Delphi process contributed to the selection of an initial set of nine quality indicators for a new a national database for hospital-based emergency care in Denmark. Final selection was made by the database steering group informed by the Delphi process.