Developing an algorithm across integrated healthcare systems to identify a history of cancer using electronic medical records.

OBJECTIVE: Tumor registries in integrated healthcare systems (IHCS) have high precision for identifying incident cancer but often miss recently diagnosed cancers or those diagnosed outside of the IHCS. We developed an algorithm using the electronic medical record (EMR) to identify people with a history of cancer not captured in the tumor registry to identify adults, aged 40-65 years, with no history of cancer. MATERIALS AND METHODS: The algorithm was developed at Kaiser Permanente Colorado, and then applied to 7 other IHCS. We included tumor registry data, diagnosis and procedure codes, chemotherapy files, oncology encounters, and revenue data to develop the algorithm. Each IHCS adapted the algorithm to their EMR data and calculated sensitivity and specificity to evaluate the algorithm's performance after iterative chart review. RESULTS: We included data from over 1.26 million eligible people across 8 IHCS; 55 601 (4.4%) were in a tumor registry, and 44848 (3.5%) had a reported cancer not captured in a registry. The common attributes of the final algorithm at each site were diagnosis and procedure codes. The sensitivity of the algorithm at each IHCS was 90.65%-100%, and the specificity was 87.91%-100%. DISCUSSION: Relying only on tumor registry data would miss nearly half of the identified cancers. Our algorithm was robust and required only minor modifications to adapt to other EMR systems. CONCLUSION: This algorithm can identify cancer cases regardless of when the diagnosis occurred and may be useful for a variety of research applications or quality improvement projects around cancer care.

Risk Factors for Decreased Quality of Life in Thyroid Cancer Survivors: Initial Findings from the North American Thyroid Cancer Survivorship Study.

BACKGROUND: The prevalence of thyroid cancer survivors is rising rapidly due to the combination of an increasing incidence, high survival rates, and a young age at diagnosis. The physical and psychosocial morbidity of thyroid cancer has not been adequately described, and this study therefore sought to improve the understanding of the impact of thyroid cancer on quality of life (QoL) by conducting a large-scale survivorship study. METHODS: Thyroid cancer survivors were recruited from a multicenter collaborative network of clinics, national survivorship groups, and social media. Study participants completed a validated QoL assessment tool that measures four morbidity domains: physical, psychological, social, and spiritual effects. Data were also collected on participant demographics, medical comorbidities, tumor characteristics, and treatment modalities. RESULTS: A total of 1174 participants with thyroid cancer were recruited. Of these, 89.9% were female, with an average age of 48 years, and a mean time from diagnosis of five years. The mean overall QoL was 5.56/10, with 0 being the worst. Scores for each of the sub-domains were 5.83 for physical, 5.03 for psychological, 6.48 for social, and 5.16 for spiritual well-being. QoL scores begin to improve five years after diagnosis. Female sex, young age at diagnosis, and lower educational attainment were highly predictive of decreased QoL. CONCLUSION: Thyroid cancer diagnosis and treatment can result in a decreased QoL. The present findings indicate that better tools to measure and improve thyroid cancer survivor QoL are needed. The authors plan to follow-up on these findings in the near future, as enrollment and data collection are ongoing.