<p>Validation Of Cancer Diagnoses In Electronic Health Records: Results From The Information System For Research In Primary Care (SIDIAP) In Northeast Spain</p>

Abstract

BackgroundElectronic health records are becoming an increasingly valuable resource for epidemiology but their data quality needs to be quantified. We aimed to validate twenty-five types of incident cancer cases in the Information System for Research in Primary Care (SIDIAP) in Catalonia with the population-based cancer registries of Girona and Tarragona as the gold-standard.MethodsWe calculated the sensitivity, positive predictive values (PPV), and the time-difference between the date of diagnosis entered into the SIDIAP and into the registries. We added hospital discharge cancer diagnoses to the SIDIAP to assess sensitivity changes.ResultsWe identified 27,046 incident cancer diagnoses in the SIDIAP from 2009–2015 among the 949,841 residents of Girona and Tarragona. The cancer types with the highest sensitivity were breast (89%, 95% CI: 88–90%), colorectal (81%, 95% CI: 80–82%), and prostate (81%, 95% CI: 80–83%). Trachea, bronchus and lung cancers had the highest PPV (76%, 95% CI: 74%-78%) followed by stomach (72%, 95% CI: 68–75%) and pancreas (71%, 95% CI: 67–75%). Most cancer diagnoses were reported with less than three months of difference between the SIDIAP and the registries. More cases were registered first in the registries than in the SIDIAP. By adding cancer diagnoses based on hospital discharge data, sensitivity increased for all cancers, especially for gallbladder and biliary tract for which the sensitivity increased by 21%.ConclusionThe SIDIAP includes 76% of the cancer diagnoses in the cancer registries but includes a considerable number of cases that are not in the registries. The SIDIAP reports most of the cancer diagnoses within a three-month period difference from the date of diagnosis in the cancer registries. Our results support the use of the SIDIAP cancer diagnoses for epidemiological research when cancer is the outcome of interest. We recommend adding hospital discharge data to the SIDIAP to increase data quality, particularly for less frequent cancer types.

Filling the gaps in the characterization of the clinical management of COVID-19: 30-day hospital admission and fatality rates in a cohort of 118 150 cases diagnosed in outpatient settings in Spain

“…The use of routinely collected data allowed a large sample size. SIDIAP is a well-validated data source 9 that has been used in many previous studies. 24 By using primary-care records linked to comprehensive region-wide hospital, mortality and testing registers obtained from a universal tax-funded healthcare system, we were able to completely characterize the natural history of COVID-19 infection from symptom onset, while avoiding the recall bias and loss to follow-up typical of cohort studies.…”

“…It includes high-quality, validated diagnoses [International Classification for Diseases, 10th revision, Clinical Modification (ICD-10-CM)], medicine prescriptions, laboratory tests, and lifestyle and socio-demographic information. 8 , 9 For this study, SIDIAP was also linked to the region-wide population-based hospital and outpatient emergency register, 10 the bespoke central database of RT-PCR COVID-19 tests and the regional mortality registry.…”

Hospitalization and 30-day fatality in 121,263 COVID-19 outpatient cases

“…SIDIAP contains anonymized primary care electronic health records for over six million people, covering a representative >80% of the Catalan population, since 2006. SIDIAP includes high-quality and validated diagnoses (International Classification for Diseases, 10th revision, Clinical Modification [ICD-10-CM]), medicine prescriptions, laboratory tests, and lifestyle and socio-demographics 8,9 . For this particular study, SIDIAP was further linked to the region-wide population-based hospital and outpatient emergency register 10 , to the bespoke central database of RT-PCR COVID-19 tests, and to the regional mortality registry.…”

Excess cases of influenza and the coronavirus epidemic in Catalonia: a time-series analysis of primary-care electronic medical records covering over 6 million people

“…Our study also has strengths. The data used were good quality, as demonstrated in many previous publications, [24][25][26][27][28][29][30] were obtained directly from primary-care records,and have been validated against gold-standard sentinel systems. This existing database covers over 85% of the population of Catalonia, which allowed us to rapidly detect excess influenza cases across the whole population and in different age groups.…”