Validation of a Low-Burden Quality Metric for the Care of Acute Sickle Cell Pain in the Emergency Department

The emergency department (ED) is an important healthcare delivery site for patients with sickle cell disease (SCD). Because of perceived institutional variability in the quality of SCD care in the ED, a quality metric for emergency care in SCD is needed. The National Heart, Lung, and Blood Institute (NHLBI) in 2014, followed by the American Society of Hematology (ASH) in 2020, released guidelines for the care of SCD-related pain episodes which recommended rapid assessment and administration of analgesia within 1 hour of presentation to the ED. Measuring how often this 60-minute analgesia guideline is followed is problematic because it does not account for institutional and contextual factors that may contribute to delays in care that are unrelated to SCD.

Our study proposes a novel metric: mean door-to-analgesia time for SCD patients, relative to door-to-analgesia time for patients presenting with renal colic (RC), expressed as a ratio. Patients with both conditions suffer from severe pain, often with an abrupt and unpredictable onset, may have several episodes throughout their life, have no visible signs of pain or reliable diagnostic studies to immediately prove pathology, and warrant timely analgesia. We designed our metric to reflect time of ED arrival at triage to time of nursing documentation of initial analgesic administration. A ratio greater than 1 indicates that patients with SCD, on average, wait longer for analgesia than patients with RC, indicating opportunities for quality improvement at the institutional level.

To assess the feasibility of reporting this metric at institutions with varying informatics resources, we used two approaches to create the metric. The first method is a “high-burden” approach where sophisticated informatics techniques were used to extract and clean data from an electronic health record (EHR) data warehouse system but may not be feasible for most institutions due to the informatics expertise required. The second method is a “low-burden” approach where structured data were extracted from the EHR in the standard provider view interface without any data cleaning. We hypothesized that the quality metric calculated using high- and low-burden methods will generate similar data. We aimed to validate our low-burden approach for use across diverse healthcare systems.

We conducted a single-center retrospective cohort study of all adult patients who presented to the ED at The Mount Sinai Hospital with acute pain from SCD and RC between January and December 2021. ED patients with final diagnosis ICD-9 codes for Hb-SS disease with crisis (282.62) or Renal colic (788) and treatment with an analgesic while in the ED were included. During the study period, there were 365 patient visits extracted using the high-burden method and 356 patient visits extracted using the low-burden method for SCD. For patients with renal colic, 31 patient visits were extracted using the high-burden method and 34 patient visits were extracted using the low-burden method. The Pearson correlation coefficient for door-to-analgesia time using the high- and low-burden methods for patients presenting with SCD was 0.929, p<0.001. Similarly, the Pearson correlation coefficient for door-to-analgesia time using the high- and low-burden methods for patients presenting with RC was 0.949, p<0.001. The ratio of mean door-to-analgesia time for SCD to RC calculated using data extracted by the low-burden method was 0.75 (and 0.74 calculated using data extracted by the high-burden method). Over the 12-month study period, the average monthly coefficient of variation was 8.72%.

Therefore, we found that patients who presented to our ED with SCD-related pain episodes experienced a shorter mean waiting time for the administration of an initial analgesia dose compared to patients with renal colic. Furthermore, highly correlated data generated by both high- and low-burden methods validates our low-burden approach, and offers clinicians a simplified process to retrieve and track this metric to improve outcomes for SCD patients across diverse healthcare systems.