Quality improvement demands quality measurement

Draycott, Timothy; Sibanda, Thabani; Laxton, C.; Winter, Catherine; Mahmood, Tahir; Fox, Robert

doi:10.1111/j.1471-0528.2010.02734.x

Cited by 37 publications

(24 citation statements)

References 9 publications

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“…As Fox et al 24 already stated, it is not easy to test the effect of simulation-based team training on patient outcomes, but the use of a validated questionnaire measuring quality of care as perceived by patients is one of the suggested possibilities. 25 To measure quality of care as perceived by patients who have recently given birth, the Pregnancy and Childbirth Questionnaire (PCQ) 9 was administered at 6 to 10 weeks postpartum. The PCQ has been developed after focus group interviews and has been validated using exploratory and confirmatory factor analyses in 2 separate samples of approximately 300 women who recently gave birth.…”

Section: Methodsmentioning

confidence: 99%

The Effect of Multiprofessional Simulation-Based Obstetric Team Training on Patient-Reported Quality of Care

Truijens

Banga

Fransen

et al. 2015

Simulation in Healthcare: The Journal of the Society for Simulation in Healthcare

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Despite the methodological restrictions of a pilot study, the preliminary results indicate that multiprofessional simulation-based obstetric team training seems to improve patient-reported quality of care. The possibility that this improvement relates to the training is supported by the fact that the items with the largest increase are about the principles of crew resource management, used in the training.

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Section: Methodsmentioning

confidence: 99%

The Effect of Multiprofessional Simulation-Based Obstetric Team Training on Patient-Reported Quality of Care

Truijens

Banga

Fransen

et al. 2015

Simulation in Healthcare: The Journal of the Society for Simulation in Healthcare

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show abstract

“…3,4 Also, there is often an implicit assumption that those hospitals that perform best on process measures will have the best outcomes as well. 5 Yet this assumption has not been proven in obstetrics.…”

mentioning

confidence: 99%

Can differences in obstetric outcomes be explained by differences in the care provided? The MFMU Network APEX study

Grobman

Bailit

Rice

et al. 2014

American Journal of Obstetrics and Gynecology

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Objective To determine whether hospital differences in the frequency of adverse obstetric outcomes are related to differences in care. Study Design The Assessment of Perinatal EXcellence (APEX) cohort of 115,502 women and their neonates born in 25 hospitals in the United States between March 2008 and February 2011. Hierarchical logistic regression was used to quantify the amount of variation in postpartum hemorrhage, peripartum infection, severe perineal laceration, and a composite adverse neonatal outcome among hospitals that is explained by differences in patient characteristics, hospital characteristics, and the obstetric care provided. Results 115,502 women were included in the study. For most outcomes, between 20 and 40% of hospital differences in outcomes were related to differences in patient populations. After controlling for patient-, provider- and hospital-level factors, multiple care processes were associated with the predefined adverse outcomes, but these care processes did not explain significant variation in the frequency of adverse outcomes among hospitals. Ultimately, between 50 and 100% of the inter-hospital variation in outcomes was unexplained. Conclusion Hospital differences in the frequency of adverse obstetric outcomes could not be explained by differences in frequency of types of care provided.

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“…1–3 Yet, because outcomes may be dependent upon pre-existing patient characteristics, simply measuring health outcomes may not provide insight into quality of care or allow valid comparisons among institutions. To overcome this limitation, risk adjustment has been widely employed in clinical disciplines such as cardiothoracic surgery to assess outcomes for procedures such as lung resection or coronary artery bypass grafting (CABG).…”

mentioning

confidence: 99%

Risk-adjusted models for adverse obstetric outcomes and variation in risk-adjusted outcomes across hospitals

Bailit

Grobman

Rice

et al. 2013

American Journal of Obstetrics and Gynecology

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Objective Regulatory bodies and insurers evaluate hospital quality using obstetrical outcomes, however meaningful comparisons should take pre-existing patient characteristics into account. Furthermore, if risk-adjusted outcomes are consistent within a hospital, fewer measures and resources would be needed to assess obstetrical quality. Our objective was to establish risk-adjusted models for five obstetric outcomes and assess hospital performance across these outcomes. Study Design A cohort study of 115,502 women and their neonates born in 25 hospitals in the United States between March 2008 and February 2011. Hospitals were ranked according to their unadjusted and risk-adjusted frequency of venous thromboembolism, postpartum hemorrhage, peripartum infection, severe perineal laceration, and a composite neonatal adverse outcome. Correlations between hospital risk-adjusted outcome frequencies were assessed. Results Venous thromboembolism occurred too infrequently (0.03%, 95% CI 0.02% – 0.04%) for meaningful assessment. Other outcomes occurred frequently enough for assessment (postpartum hemorrhage 2.29% (95% CI 2.20–2.38), peripartum infection 5.06% (95% CI 4.93–5.19), severe perineal laceration at spontaneous vaginal delivery 2.16% (95% CI 2.06–2.27), neonatal composite 2.73% (95% CI 2.63–2.84)). Although there was high concordance between unadjusted and adjusted hospital rankings, several individual hospitals had an adjusted rank that was substantially different (as much as 12 rank tiers) than their unadjusted rank. None of the correlations between hospital adjusted outcome frequencies was significant. For example, the hospital with the lowest adjusted frequency of peripartum infection had the highest adjusted frequency of severe perineal laceration. Conclusions Evaluations based on a single risk-adjusted outcome cannot be generalized to overall hospital obstetric performance.

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Quality improvement demands quality measurement

Abstract: Please cite this paper as: Draycott T, Sibanda T, Laxton C, Winter C, Mahmood T, Fox R. Quality improvement demands quality measurement. BJOG 2010;117:1571–1574.

Cited by 37 publications

References 9 publications

The Effect of Multiprofessional Simulation-Based Obstetric Team Training on Patient-Reported Quality of Care

The Effect of Multiprofessional Simulation-Based Obstetric Team Training on Patient-Reported Quality of Care

Can differences in obstetric outcomes be explained by differences in the care provided? The MFMU Network APEX study

Risk-adjusted models for adverse obstetric outcomes and variation in risk-adjusted outcomes across hospitals

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