Susan Paulukonis

Population based surveillance in sickle cell disease: Methods, findings and implications from the California registry and surveillance system in hemoglobinopathies project (RuSH)

There are no population‐based surveillance systems to determine prevalence, impact or outcomes in sickle cell disease (SCD). Estimates of the SCD population in California range broadly from 4,500 to 7,000, and little is known about their health status, health care utilization or health outcomes. A surveillance strategy was implemented using diverse data sources to develop a multi‐dimensional, state‐based surveillance system for SCD that includes adults and children and describes utilization, treatment and outcomes.

Defining Sickle Cell Disease Mortality Using a Population-Based Surveillance System, 2004 through 2008:

Objective. Population-based surveillance data from California and Georgia for years 2004 through 2008 were linked to state death record files to determine the all-cause death rate among 12,143 patients identified with sickle cell disease (SCD). Methods. All-cause death rates, by age, among these SCD patients were compared with all-cause death rates among both African Americans and the total population in the two states. All-cause death rates were also compared with death rates for SCD derived from publicly available death records: the compressed mortality files and multiple cause of death files. Results. Of 12,143 patients identified with SCD, 615 patients died. The all-cause mortality rate for the SCD population was lower than the all-cause mortality rate among African Americans and similar to the total population all-cause mortality rates from birth through age 4 years, but the rate was higher among those with SCD than both the African American and total population rates from ages 5 through 74 years. The count of deceased patients identified by using population-based surveillance data (n=5615) was more than twice as high as the count identified in compressed mortality files using SCD as the underlying cause of death alone (n=5297). Conclusion. Accurate assessment of all-cause mortality and age at death requires long-term surveillance via population-based registries of patients with accurately diagnosed SCD.

Emergency department utilization by Californians with sickle cell disease, 2005-2014.

Clinical care for children and adults living with sickle cell disease (SCD) is often provided in the emergency department (ED). Population‐based surveillance data can be used to describe the ED utilization patterns of this patient population.

Chart Card: Feasibility of a Tool for Improving Emergency Department Care in Sickle Cell Disease

BACKGROUND Patients with sickle cell disease (SCD) are concerned with emergency department care, including time to treatment and staff attitudes and knowledge. Providers are concerned about rapid access to patient information and SCD treatment protocols. A software application that stores and retrieves encrypted personal medical information on a plastic credit card-sized Chart Card was designed. OBJECTIVE To determine the applicability and feasibility of the Chart Card on patient satisfaction with emergency department care and provider accessibility to patient information and care protocols. METHODS One-half of 44 adults (aged -18 years) and 50 children with SCD were randomized to either the Chart Card or usual care. Patient satisfaction was surveyed pre and post implementation of the Chart Card program, and emergency department staff was surveyed about familiarity with SCD treatment protocols. CONCLUSION Patient satisfaction with emergency department care and efficacy in health care increased post Chart Card implementation. Providers valued immediate access to patient information and SCD treatment guidelines. The technology has potential for application in the treatment of other illnesses in other settings.

Increased risk of leukemia among sickle cell disease patients in California

To the editor: Due to improvements in treatment and care, the life expectancy of patients with sickle cell disease (SCD) has improved over the last 50 years[1][1] such that many patients now survive to an age where they are at an increased risk for cancer.[2][2] Previously reported small case

Evaluating the Use of Electronic Health Records for Type 2 Diabetes Surveillance in 2 California Counties, 2010-2014

Objectives: Electronic health records (EHRs) and electronic laboratory records (ELRs) are increasingly seen as a rich source of data for performing public health surveillance activities and monitoring community health status. Their potential for surveillance of chronic illness, however, may be underused. Our objectives were to (1) evaluate the use of EHRs and ELRs for diabetes surveillance in 2 California counties and (2) examine disparities in diabetes prevalence by geography, income, and race/ethnicity. Methods: We obtained data on a clinical diagnosis of diabetes and hemoglobin A1c (HbA1c) test results for adult members of Kaiser Permanente Northern California living in Contra Costa County or Solano County at any time during 2010-2014. We evaluated the validity of using HbA1c test results to determine diabetes prevalence, using clinical diagnoses as a gold standard. We estimated disparities in diabetes prevalence by combining HbA1c test results with US Census data on income, race, and ethnicity. Results: When compared with a clinical diagnosis of diabetes, data on a patient’s 5-year maximum HbA1c value ≥6.5% yielded the best combination of sensitivity (87.4%) and specificity (99.2%). The prevalence of 5-year maximum HbA1c ≥6.5% decreased with increasing median family income and increased with greater proportions of residents who were either non-Hispanic black or Hispanic. Conclusions: Timely diabetes surveillance data from ELRs can be used to document disparities, target interventions, and evaluate changes in population health. ELR data may be easier to access than a patient’s entire EHR, but outcome metric validation with diabetes diagnoses would need to be ongoing. Future research should validate ELR and EHR data across multiple providers.