Dataset Information

Defect-free care trends in the Paul Coverdell National Acute Stroke Program, 2008-2018.

ABSTRACT:

Background

In an effort to improve stroke quality of care and patient outcomes, quality of care metrics are monitored to assess utilization of evidence-based stroke care processes as part of the Paul Coverdell National Acute Stroke Program (PCNASP). We aimed to assess temporal trends in defect-free care (DFC) received by stroke patients in the PCNASP between 2008 and 2018.

Methods

Quality of care data for 10 performance measures were available for 849,793 patients aged ≥18 years who were admitted to a participating hospital with a clinical diagnosis of stroke between 2008 and 2018. A patient who receives care according to all performance measures for which they are eligible, receives "defect-free care" (DFC) (eg, appropriate medications, assessments, and education). Generalized estimating equations were used to examine the factors associated with receipt of DFC.

Results

DFC among ischemic stroke patients increased from 38.0% in 2008 to 80.8% in 2018 (P < .0001), with the largest improvement seen in receipt of stroke education (relative percent change, RPC = 64%). Similarly, DFC for hemorrhagic stroke and transient ischemic attack patients increased from 46.7% to 82.6% (RPC = 76.9%) and 39.9% to 85.0% (RPC = 113.0%) (P < .001), respectively. Among ischemic stroke patients, the adjusted odds for receiving DFC were lower for women, patients aged 18 to 54 years, Medicaid or Medicare participants, and patients with atrial fibrillation (P < .05).

Conclusions

From 2008 to 2018, receipt of DFC by ischemic stroke patients significantly increased in the PCNASP; however certain subgroups were less likely to receive this level of care. Targeted quality improvement initiatives could result in even further improvements among all stroke patients and help reduce disparities in care.

SUBMITTER: Overwyk KJ

PROVIDER: S-EPMC8114176 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe Paul Coverdell National Acute Stroke Registry (PCNASR) is a U.S. based national registry designed to monitor and improve the quality of acute stroke care delivered by hospitals. The registry monitors care through specific performance measures, the accuracy of which depends in part on the reliability of the individual data elements used to construct them. This study describes the inter-rater reliability of data elements collected in Michigan's state-based prototype of the PCNASR.MethodsOver a 6-month period, 15 hospitals participating in the Michigan PCNASR prototype submitted data on 2566 acute stroke admissions. Trained hospital staff prospectively identified acute stroke admissions, abstracted chart information, and submitted data to the registry. At each hospital 8 randomly selected cases were re-abstracted by an experienced research nurse. Inter-rater reliability was estimated by the kappa statistic for nominal variables, and intraclass correlation coefficient (ICC) for ordinal and continuous variables. Factors that can negatively impact the kappa statistic (i.e., trait prevalence and rater bias) were also evaluated.ResultsA total of 104 charts were available for re-abstraction. Excellent reliability (kappa or ICC > 0.75) was observed for many registry variables including age, gender, black race, hemorrhagic stroke, discharge medications, and modified Rankin Score. Agreement was at least moderate (i.e., 0.75 > kappa >/=; 0.40) for ischemic stroke, TIA, white race, non-ambulance arrival, hospital transfer and direct admit. However, several variables had poor reliability (kappa < 0.40) including stroke onset time, stroke team consultation, time of initial brain imaging, and discharge destination. There were marked systematic differences between hospital abstractors and the audit abstractor (i.e., rater bias) for many of the data elements recorded in the emergency department.ConclusionThe excellent reliability of many of the data elements supports the use of the PCNASR to monitor and improve care. However, the poor reliability for several variables, particularly time-related events in the emergency department, indicates the need for concerted efforts to improve the quality of data collection. Specific recommendations include improvements to data definitions, abstractor training, and the development of ED-based real-time data collection systems.