Key result
Implementation of clinical decision support tools in primary care practices significantly increased screening for albuminuria by a median absolute change of 30% over 24 months.
Why the study?
Does the implementation of EHR-based clinical decision support tools improve adherence to clinical quality measures for the identification and management of chronic kidney disease in primary care?
Observational
Yes
Does the implementation of EHR-based clinical decision support tools improve adherence to clinical quality measures for the identification and management of chronic kidney disease in primary care?
Effect estimate: Absolute increase 30.0%
Absolute Event Rate: 59% vs 21.5%
p-value: p=<0.0005
The implementation of EHR-based clinical decision support tools in primary care significantly improves process measures for CKD identification and monitoring, particularly for albuminuria screening.
May support CDS integration to boost albuminuria screening in primary care; leaves open confirmation via RCTs and outcome benefits.
BACKGROUND: Early detection of chronic kidney disease (CKD) can lead to interventions to prevent renal failure and reduce risk for cardiovascular disease, yet adherence to treatment goals is suboptimal in the primary care setting. The purpose of this study was to assess whether clinical decision support (CDS) can be used to improve the identification and management of CKD. METHODS: This 2 year demonstration study was conducted in 11 primary care PPRNet practices. CDS included a risk assessment tool, health maintenance protocols, flow chart and a patient registry. Practices received performance reports and hosted annual half day on-site visits. RESULTS: There were statistically significant increases in screening for albuminuria (median 24 month change 30%, p < 0.0005) and monitoring albuminuria (median 24 month change 25%, p < 0.0005). An absolute 23.5% improvement in appropriate use of ACE-inhibitor or angiotensin receptor blocker and an absolute 7.0% improvement in hemoglobin measurement were not statistically significant. There were no clinical or statistically significant differences in other CKD CQMs. Facilitators to CDS use included practices' prioritization of improving CKD and staff use of standing orders. Barriers included incorporating use into existing workflow and variable use among providers. CONCLUSIONS: Use of CDS to improve CKD identification and management in primary care practices shows promise. However, other barriers must be addressed to effectively achieve improvements in CKD outcomes.
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Litvin et al. (2016) conducted an observational in Chronic Kidney Disease (CKD). Clinical decision support (CDS) tools vs. Baseline (pre-intervention) was evaluated on Screening for albuminuria in patients with diabetes and/or hypertension (Absolute increase 30.0%, p=<0.0005). Implementation of clinical decision support tools in primary care practices significantly increased screening for albuminuria by a median absolute change of 30% over 24 months.
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