ObjectiveImplementation of a surgical checklist depends on many organisational factors and on socio-cultural patterns. The objective of this study was to identify barriers to effective implementation of a surgical checklist and to develop a best use strategy.Setting18 cancer centres in France.DesignThe authors first assessed use compliance and completeness rates of the surgical checklist on a random sample of 80 surgical procedures performed under general or loco-regional anaesthesia in each of the 18 centres. They then developed a typology of the organisational and cultural barriers to effective checklist implementation and defined each barrier's contents using data from collective and semi-structured individual interviews of key staff, the results of an email questionnaire sent to the 18 centres, and direct observations over 20 h in two centres.ResultsThe study consisted of 1440 surgical procedures, 1299 checklists, and 28 578 items. The mean compliance rate was 90.2% (0, 100). The mean completion rate was 61% (0, 84). 11 barriers to effective checklist implementation were identified. Their incidence varied widely across centres. The main barriers were duplication of items within existing checklists (16/18 centres), poor communication between surgeon and anaesthetist (10/18), time spent completing the checklist for no perceived benefit, and lack of understanding and timing of item checks (9/18), ambiguity (8/18), unaccounted risks (7/18) and a time-honoured hierarchy (6/18).ConclusionsSeveral of the barriers to the successful implementation of the surgical checklist depended on organisational and cultural factors within each centre. The authors propose a strategy for change for checklist design, use and assessment, which could be used to construct a feedback loop for local team organisation and national initiatives.

On a country level, for health systems striving for newly implementing QIS it is recommended to start where routine data is available, add qualitative methodologies once the QIS is getting more complex, report performance data back to service providers and be patient centred. On the inter-country level exchange of information between agencies commissioned with implementing national QIS is very much needed for.

BackgroundOur objective was to limit the burden of data collection for Quality Indicators (QIs) based on medical records.MethodsThe study was supervised by the COMPAQH project. Four QIs based on medical records were tested: medical record conformity; traceability of pain assessment; screening for nutritional disorders; time elapsed before sending copy of discharge letter to the general practitioner. Data were collected by 6 Clinical Research Assistants (CRAs) in a panel of 36 volunteer hospitals and analyzed by COMPAQH. To limit the burden of data collection, we used the same sample of medical records for all 4 QIs, limited sample size to 80 medical records, and built a composite score of only 10 items to assess medical record completeness. We assessed QI feasibility by completing a grid of 19 potential problems and evaluating time spent. We assessed reliability (κ coefficient) as well as internal consistency (Cronbach α coefficient) in an inter-observer study, and discriminatory power by analysing QI variability among hospitals.ResultsOverall, 23 115 data items were collected for the 4 QIs and analyzed. The average time spent on data collection was 8.5 days per hospital. The most common feasibility problem was misunderstanding of the item by hospital staff. QI reliability was good (κ: 0.59–0.97 according to QI). The hospitals differed widely in their ability to meet the quality criteria (mean value: 19–85%).ConclusionThese 4 QIs based on medical records can be used to compare the quality of record keeping among hospitals while limiting the burden of data collection, and can therefore be used for benchmarking purposes. The French National Health Directorate has included them in the new 2009 version of the accreditation procedure for healthcare organizations.

BackgroundResults of associations between process and mortality indicators, both used for the external assessment of hospital care quality or public reporting, differ strongly across studies. However, most of those studies were conducted in North America or United Kingdom. Providing new evidence based on French data could fuel the international debate on quality of care indicators and help inform French policy-makers. The objective of our study was to explore whether optimal care delivery in French hospitals as assessed by their Hospital Process Indicators (HPIs) is associated with low Hospital Standardized Mortality Ratios (HSMRs).MethodsThe French National Authority for Health (HAS) routinely collects for each hospital located in France, a set of mandatory HPIs. Five HPIs were selected among the process indicators collected by the HAS in 2009. They were measured using random samples of 60 to 80 medical records from inpatients admitted between January 1st, 2009 and December 31, 2009 in respect with some selection criteria. HSMRs were estimated at 30, 60 and 90 days post-admission (dpa) using administrative health data extracted from the national health insurance information system (SNIIR-AM) which covers 77% of the French population. Associations between HPIs and HSMRs were assessed by Poisson regression models corrected for measurement errors with a simulation-extrapolation (SIMEX) method.ResultsMost associations studied were not statistically significant. Only two process indicators were found associated with HSMRs. Completeness and quality of anesthetic records was negatively associated with 30 dpa HSMR (0.72 [0.52–0.99]). Early detection of nutritional disorders was negatively associated with all HSMRs: 30 dpa HSMR (0.71 [0.54–0.95]), 60 dpa HSMR (0.51 [0.39–0.67]) and 90 dpa HSMR (0.52 [0.40–0.68]).ConclusionIn absence of gold standard of quality of care measurement, the limited number of associations suggested to drive in-depth improvements in order to better determine associations between process and mortality indicators. A smart utilization of both process and outcomes indicators is mandatory to capture aspects of the hospital quality of care complexity.Electronic supplementary materialThe online version of this article (doi:10.1186/s12913-017-2534-3) contains supplementary material, which is available to authorized users.

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