scholarly journals Identifying Prenatal Opioid Exposure in Health Administrative Data for Public Health Surveillance and Epidemiologic Research

2020 ◽  
Vol 5 (5) ◽  
Author(s):  
Andi Camden ◽  
Teresa To ◽  
Joel G Ray ◽  
Tara Gomes ◽  
Li Bai ◽  
...  
Keyword(s):  
Prescription Drug ◽  
Administrative Data ◽  
Population Based ◽  
Emergency Department Visits ◽  
Prescription Data ◽  
Opioid Use ◽  
Health Administrative Data ◽  
Maternal Characteristics ◽  
Data Source ◽  
The Impact

IntroductionAccurate estimation of prenatal opioid exposure (POE) is needed for population-based surveillance & research but can be challenging with health administrative data due to varying definitions & methods. Prior research has relied primarily on infant records with a diagnosis of neonatal abstinence syndrome (NAS). Objectives and Approach1) Evaluate the impact of using different definitions of maternal opioid use in the estimation of POE; 2) Investigate whether maternal characteristics vary by the type of definition used. Population-based cross-sectional study of all hospital births (N= 454,746) from 2014-2017 in Ontario, Canada. Multiple linked population-based health administrative databases were used to identify opioid-related pre- & perinatal Emergency Department visits & hospitalizations & opioid prescriptions. We examined how pre-conception & in-pregnancy maternal characteristics varied by using different approaches to ascertain POE. ResultsThere were 9624 live/still births with POE. Ascertainment of POE was highest using maternal prescription drug data (79%) & infant hospital records with NAS (45%). Maternal characteristics varied by data source used for POE ascertainment. Opioid-related health care during pregnancy identified a high-risk phenotype, contrasted with those ascertained through prescription data, with respective rates of 64% vs. 54% for social assistance, 37% vs. 12% for polydrug use, 23% vs. 6% for alcohol use, 26% vs. 19% for 3+ live births, 13% vs. 5% for victim of violence, 12% vs. 6% for involvement in criminal justice system & 64% vs. 17% for mental health & addictions hospital care. Conclusion / ImplicationsPOE ascertainment differs by health administrative data source & ability to link both across maternal records and with infant. Prescription drug data identified the highest number of opioid-exposed births and, with linked healthcare records, is useful to identify illicit opioid use & additional risk factors. Clinically meaningful differences in maternal characteristics of opioid users exist by POE ascertainment method.

scholarly journals Increasing Incidence and Prevalence of Pathologic Hemoglobinopathies Among Children in Ontario, Canada from 1991-2013

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 4698-4698
Author(s):  
Ewurabena Simpson ◽  
Robert J Klaassen ◽  
Pranesh Chakraborty ◽  
Beth Potter ◽  
Melanie Ann Kirby-Allen ◽  
...  
Keyword(s):  
Health Services ◽  
Chronic Diseases ◽  
Administrative Data ◽  
Research Funding ◽  
Population Based ◽  
Advisory Board ◽  
Crude Incidence ◽  
Health Administrative Data ◽  
The Impact ◽  
Reference Cohort

Abstract Background: In Ontario, Canada's largest province, population-based health administrative data represents an accessible and useful tool for population surveillance of people with chronic diseases. While hemoglobinopathies can be identified using data from universal hemoglobinopathy screening, which was implemented in November 2006, these data would not contain information on affected immigrants (21.9% of the population). We validated algorithms using provincial health administrative data and newborn screening data to identify children with hemoglobinopathies whether or not they were born in Ontario, thereby creating a population-based surveillance cohort. Objectives: (1) Validate algorithms to identify children with sickle cell disease, thalassemia and other hemoglobinopathies from within health administrative data; and (2) Determine incidence and prevalence of hemoglobinopathies in Ontario children. Methods: For the validation study, a positive reference cohort was established using lists of known hemoglobinopathy patients who were followed at five pediatric hemoglobinopathy treatment sites in Ontario and born between November 24, 2006 and March 31, 2013. Health card numbers of these patients were linked deterministically to unique identification numbers in administrative data, which included data on hospitalizations, physician claims, sociodemographic characteristics, immigration records and cause of death. The negative reference cohort included all children residing in Ontario cities who had never been seen at a hemoglobinopathy centre, and therefore assumed not to have disease. Various combinations of administrative data codes were tested for their ability to identify children <18 years of age with hemoglobinopathies from within the databases, and we selected the algorithms with the highest positive predictive value, while maintaining sensitivity >80%. Using two validated algorithms, we identified all children with hemoglobinopathies born between April 1, 1991 and March 31, 2013. We described the crude incidence and prevalence per 100,000 patient-years (PYs). Results: Two algorithms functioned best to identify incident and prevalent hemoglobinopathy cases (see Table). Among children born between April 1, 1991 to March 31, 2013, 1526 incident hemoglobinopathy patients were identified using Algorithm 1 (crude incidence of 4.85 per 100,000 PYs) and 1660 new hemoglobinopathy patients were identified using Algorithm 2 (crude incidence 5.28 per 100,000 PYs, 95% CI 3.51 to 3.92). In 2013, the overall prevalence of children <18 years living with hemoglobinopathies was 1215-1325 cases. Conclusion: Through an innovative approach using provincial health administrative, immigration and demographic data, this study identified a rising incidence and prevalence of hemoglobinopathies among Ontario children <18 years of age between April 1, 1991 and March 31, 2013, potentially due to increased immigration rates. These findings could be used to inform health services distribution. This surveillance cohort will be used to understand the impact of immigration status on health care inequality for hemoglobinopathy-related health services delivery, as well as to assess outcomes in this important group of chronic diseases. Disclosures Klaassen: Amgen Inc.: Membership on an entity's Board of Directors or advisory committees; Octapharma AG: Consultancy, Honoraria; Agios Pharmaceuticals Inc.: Consultancy; Novartis: Research Funding; Hoffman-La Roche: Consultancy; Shire: Consultancy; Cangene: Research Funding. Jardine:Pfizer: Other: Advisory board; Bayer: Other: Advisory board; Baxalta: Other: Advisory board.

The validity of algorithms using health administrative data in identifying cancer-related events in adolescents and young adults: A population-based study using the IMPACT cohort.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e18168-e18168
Author(s):  
Jason D Pole ◽  
Paul C. Nathan ◽  
Nancy N. Baxter ◽  
Cindy Lau ◽  
Corinne Daly ◽  
...  
Keyword(s):  
Young Adults ◽  
Administrative Data ◽  
Population Based ◽  
Adolescents And Young Adults ◽  
Administrative Databases ◽  
Time Interval ◽  
Cancer Outcomes ◽  
Health Administrative Data ◽  
Chart Abstraction ◽  
The Impact

e18168 Background: Despite the importance of estimating population level cancer outcomes, most registries do not collect critical events such as relapse and progression. Attempts to use health administrative data to identify these events have focused on older adults and have been mostly unsuccessful. We developed and tested administrative data-based algorithms in a population-based cohort of adolescents and young adults (AYA) with cancer. Methods: We identified all Ontario AYA 15-21 years of age diagnosed with leukemia, lymphoma, sarcoma, or testicular cancer between 1992 and 2012. Chart abstraction was used to determine the end of initial treatment (EOIT) date and subsequent cancer-related events (progression, relapse, second cancer). Linkage to population-based administrative databases identified fee and procedure codes indicating cancer treatment or palliative care. Algorithms that determined EOIT based a time interval free of treatment-associated codes, and new cancer-related events based on billing codes, were compared to chart abstracted data. Results: The cohort comprised 1,404 patients. Time periods free of treatment-associated codes did not validly identify EOIT dates; using subsequent codes to identify new cancer events was thus associated with low sensitivity (56.2%). However, using administrative data codes that occurred after the EOIT date based on chart abstraction, the first cancer-related event was identified with excellent validity (sensitivity 87.0%, specificity 93.3%, PPV 81.5%, negative predictive value 95.5%). Conclusions: While administrative data alone did not validly identify cancer-related events, using administrative data in combination with chart collected EOIT dates was associated with excellent validity. The collection of EOIT dates by cancer registries would significantly expand the potential of administrative data linkage to assess cancer outcomes.

Estimating the incidence of first-episode psychosis using population-based health administrative data to inform early psychosis intervention services

2018 ◽  
Vol 49 (12) ◽  
pp. 2091-2099 ◽  
Author(s):  
Kelly K. Anderson ◽  
Ross Norman ◽  
Arlene G. MacDougall ◽  
Jordan Edwards ◽  
Lena Palaniyappan ◽  
...  
Keyword(s):  
Psychotic Disorder ◽  
Administrative Data ◽  
Catchment Area ◽  
Population Based ◽  
First Episode Psychosis ◽  
Case Definition ◽  
First Episode ◽  
Affective Psychosis ◽  
Health Administrative Data ◽  
Episode Psychosis

AbstractBackgroundDiscrepancies between population-based estimates of the incidence of psychotic disorder and the treated incidence reported by early psychosis intervention (EPI) programs suggest additional cases may be receiving services elsewhere in the health system. Our objective was to estimate the incidence of non-affective psychotic disorder in the catchment area of an EPI program, and compare this to EPI-treated incidence estimates.MethodsWe constructed a retrospective cohort (1997–2015) of incident cases of non-affective psychosis aged 16–50 years in an EPI program catchment using population-based linked health administrative data. Cases were identified by either one hospitalization or two outpatient physician billings within a 12-month period with a diagnosis of non-affective psychosis. We estimated the cumulative incidence and EPI-treated incidence of non-affective psychosis using denominator data from the census. We also estimated the incidence of first-episode psychosis (people who would meet the case definition for an EPI program) using a novel approach.ResultsOur case definition identified 3245 cases of incident non-affective psychosis over the 17-year period. We estimate that the incidence of first-episode non-affective psychosis in the program catchment area is 33.3 per 100 000 per year (95% CI 31.4–35.1), which is more than twice as high as the EPI-treated incidence of 18.8 per 100 000 per year (95% CI 17.4–20.3).ConclusionsCase ascertainment strategies limited to specialized psychiatric services may substantially underestimate the incidence of non-affective psychotic disorders, relative to population-based estimates. Accurate information on the epidemiology of first-episode psychosis will enable us to more effectively resource EPI services and evaluate their coverage.

scholarly journals Repeat emergency department visits by nursing home residents: a cohort study using health administrative data

2018 ◽  
Vol 18 (1) ◽  
Author(s):  
Andrea Gruneir ◽  
Candemir Cigsar ◽  
Xuesong Wang ◽  
Alice Newman ◽  
Susan E. Bronskill ◽  
...  
Keyword(s):  
Emergency Department ◽  
Cohort Study ◽  
Nursing Home ◽  
Administrative Data ◽  
Nursing Home Residents ◽  
Emergency Department Visits ◽  
Health Administrative Data

scholarly journals Prediction of in-hospital mortality after pancreatic resection in pancreatic cancer patients: A boosting approach via a population-based study using health administrative data

PLoS ONE ◽  
2017 ◽  
Vol 12 (6) ◽  
pp. e0178757 ◽  
Author(s):  
Jose F. Velez-Serrano ◽  
Daniel Velez-Serrano ◽  
Valentin Hernandez-Barrera ◽  
Rodrigo Jimenez-Garcia ◽  
Ana Lopez de Andres ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Hospital Mortality ◽  
Cancer Patients ◽  
Administrative Data ◽  
Pancreatic Resection ◽  
Population Based ◽  
Population Based Study ◽  
Health Administrative Data

scholarly journals The impact of COVID-19 on hospital admissions and emergency department visits: A population-based study

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252441
Author(s):  
Elissa Rennert-May ◽  
Jenine Leal ◽  
Nguyen Xuan Thanh ◽  
Eddy Lang ◽  
Shawn Dowling ◽  
...  
Keyword(s):  
Public Health ◽  
Emergency Department ◽  
Hospital Admissions ◽  
Population Based ◽  
Emergency Department Visits ◽  
System Capacity ◽  
Population Based Study ◽  
Health Measures ◽  
Ed Visits ◽  
The Impact

Background As a result of the novel coronavirus disease 2019 (COVID-19), there have been widespread changes in healthcare access. We conducted a retrospective population-based study in Alberta, Canada (population 4.4 million), where there have been approximately 1550 hospital admissions for COVID-19, to determine the impact of COVID-19 on hospital admissions and emergency department (ED visits), following initiation of a public health emergency act on March 15, 2020. Methods We used multivariable negative binomial regression models to compare daily numbers of medical/surgical hospital admissions via the ED between March 16-September 23, 2019 (pre COVID-19) and March 16-September 23, 2020 (post COVID-19 public health measures). We compared the most frequent diagnoses for hospital admissions pre/post COVID-19 public health measures. A similar analysis was completed for numbers of daily ED visits for any reason with a particular focus on ambulatory care sensitive conditions (ACSC). Findings There was a significant reduction in both daily medical (incident rate ratio (IRR) 0.86, p<0.001) and surgical (IRR 0.82, p<0.001) admissions through the ED in Alberta post COVID-19 public health measures. There was a significant decline in daily ED visits (IRR 0.65, p<0.001) including ACSC (IRR 0.75, p<0.001). The most common medical/surgical diagnoses for hospital admissions did not vary substantially pre and post COVID-19 public health measures, though there was a significant reduction in admissions for chronic obstructive pulmonary disease and a significant increase in admissions for mental and behavioral disorders due to use of alcohol. Conclusions Despite a relatively low volume of COVID-19 hospital admissions in Alberta, there was an extensive impact on our healthcare system with fewer admissions to hospital and ED visits. This work generates hypotheses around causes for reduced hospital admissions and ED visits which warrant further investigation. As most publicly funded health systems struggle with health-system capacity routinely, understanding how these reductions can be safely sustained will be critical.

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