Variations in achievement of evidence-based, high-impact quality indicators in general practice: An observational study
- PMID: 28704407
- PMCID: PMC5509104
- DOI: 10.1371/journal.pone.0177949
Variations in achievement of evidence-based, high-impact quality indicators in general practice: An observational study
Abstract
Background: There are widely recognised variations in the delivery and outcomes of healthcare but an incomplete understanding of their causes. There is a growing interest in using routinely collected 'big data' in the evaluation of healthcare. We developed a set of evidence-based 'high impact' quality indicators (QIs) for primary care and examined variations in achievement of these indicators using routinely collected data in the United Kingdom (UK).
Methods: Cross-sectional analysis of routinely collected, electronic primary care data from a sample of general practices in West Yorkshire, UK (n = 89). The QIs covered aspects of care (including processes and intermediate clinical outcomes) in relation to diabetes, hypertension, atrial fibrillation, myocardial infarction, chronic kidney disease (CKD) and 'risky' prescribing combinations. Regression models explored the impact of practice and patient characteristics. Clustering within practice was accounted for by including a random intercept for practice.
Results: Median practice achievement of the QIs ranged from 43.2% (diabetes control) to 72.2% (blood pressure control in CKD). Considerable between-practice variation existed for all indicators: the difference between the highest and lowest performing practices was 26.3 percentage points for risky prescribing and 100 percentage points for anticoagulation in atrial fibrillation. Odds ratios associated with the random effects for practices emphasised this; there was a greater than ten-fold difference in the likelihood of achieving the hypertension indicator between the lowest and highest performing practices. Patient characteristics, in particular age, gender and comorbidity, were consistently but modestly associated with indicator achievement. Statistically significant practice characteristics were identified less frequently in adjusted models.
Conclusions: Despite various policy and improvement initiatives, there are enduring inappropriate variations in the delivery of evidence-based care. Much of this variation is not explained by routinely collected patient or practice variables, and is likely to be attributable to differences in clinical and organisational behaviour.
Conflict of interest statement
Figures
References
-
- Eccles M, Armstrong D, Baker R, Cleary K, Davies H, Davies S, et al. An implementation research agenda. Implement Sci. 2009;4: 18 doi: 10.1186/1748-5908-4-18 - DOI - PMC - PubMed
-
- Hobbs FDR, Bankhead C, Mukhtar T, Stevens S, Perera-Salazar R, Holt T, et al. Clinical workload in UK primary care: a retrospective analysis of 100 million consultations in England, 2007–14. Lancet. 2016;387: 2323–2330. doi: 10.1016/S0140-6736(16)00620-6 - DOI - PMC - PubMed
-
- Wallace E, Salisbury C, Guthrie B, Lewis C, Fahey T, Smith SM. Managing patients with multimorbidity in primary care. BMJ. 2015;350: h176 doi: 10.1136/bmj.h176 - DOI - PubMed
-
- Baird B, Charles A, Honeyman M, Maguire D, Das P. Understanding pressures in general practice. London: The King's Fund; 2016.
Publication types
MeSH terms
Grants and funding
LinkOut - more resources
Full Text Sources
Other Literature Sources
