Can we simplify the hospital accreditation process? Predicting accreditation decisions from a reduced dataset of focus priority standards and quality indicators: results of predictive modelling

Abstract

ObjectivesAccreditation in France relies on a mandatory 4-year cycle of self-assessment and a peer review of 82 standards, among which 14 focus priority standards (FPS). Hospitals are also required to measure yearly quality indicators (QIs—5 in 2010). On advice given by the accreditation committee of HAS (Haute Autorité en Santé), based on surveyors proposals and relying mostly on compliance to standards, accreditation decisions are taken by the board of HAS. Accreditation is still perceived by hospitals as a burdensome process and a simplification would be welcomed. The hypothesis was that a more limited number of criteria might give sufficient amount of information on hospitals overall quality level, appraised today by accreditation decisions.DesignThe accuracy of predictions of accreditation decisions given by a model, Partial Least Square-2 Discriminant Analysis (PLS2-DA), using only the results of FPS and QIs was measured. Accreditation decisions (full accreditation (A), recommendations or reservation (B), remit decision or non-accreditation (C)), results of FPS and QIs were considered qualitative variables. Stability was assessed by leave one out cross validation (LOOCV).Setting and participantsAll French 489 acute care organisations (ACO) accredited between June 2010 and January 2012 were considered, 304 of them having a rehabilitation care sector (RCS).ResultsAccuracy of prediction of accreditation decisions was good (89% of ACOs and 91% of ACO-RCS well classified). Stability of results appeared satisfactory when using LOOCV (87% of ACOs and 89% of ACO-RCS well classified). Identification of worse hospitals was correct (90% of ACOs and 97% of ACO-RCS predicted C were actually C).ConclusionsUsing PLS2-DA with a limited number of criteria (QIs and FPS) provides an accurate prediction of accreditation decisions, especially for underperforming hospitals. This could support accreditation committees which give advices on accreditation decisions, and allow fast-track handling of ‘safe’ reports.

The impact of Saudi hospital accreditation on quality of care: a mixed methods study

“…For instance, the clinical indicator programme of the Australia Council on Healthcare Standards (ACHS) programme was established to increase the clinical components and indicators in its new accreditation programme (Guérin et al . ). More than half of Australian hospitals are monitoring the indicators and reporting clinical data twice yearly to the ACHS (Collopy ).…”

“…Several accreditation programmes have taken steps to incorporate objective, validated measures of service quality and outcomes into their accreditation standards process. For instance, the clinical indicator programme of the Australia Council on Healthcare Standards (ACHS) programme was established to increase the clinical components and indicators in its new accreditation programme (Guérin et al 2013). More than half of Australian hospitals are monitoring the indicators and reporting clinical data twice yearly to the ACHS (Collopy 2000).…”

Counting the costs of accreditation in acute care: an activity-based costing approach

“…Recommendations for policymakers to reduce higher costs for smaller hospitals could be focused on the way the surveys are conducted. Suggestions include: short notice surveys to maintain a ‘survey ready’ approach rather than reacting to accreditation timetables; 41 improved provision for data collection to reduce the reporting burden; increased online reporting; providing technology platforms for accreditation tools; developing indicators to reduce survey requirements; 42 and reducing duplication with State and Federal reporting requirements. This research provides a baseline of accreditation costs to compare the impact of the new accreditation programme.…”

The Impact of Applying Quality Management Practices on Patient Centeredness in Jordanian Public Hospitals: Results of Predictive Modeling

“…Based on the limited evidence, we also assumed that administrators hold a different view from clinicians and that nurses are more aware about the needs, circumstances, and preferences of the patients receiving care than other health care professionals. This assumption is supported by several studies, 24,[27][28][29][30][31] wherein the perceptions of nurses were targeted as an information source for determining the impact of QI and accreditation on the delivery of health care services. According to these studies, the role of the nursing staff is considered to contribute toward improvement in the quality of care and achievement of a better understanding of what is important to the patient.…”