Comparing Prevalence Estimates From Population-Based Surveys to Inform Surveillance Using Electronic Health Records
| Autor: | Sharon E. Perlman, Katharine H. McVeigh, Pui Ying Chan, Elizabeth Lurie-Moroni, Lorna E. Thorpe, Kathleen S. Tatem, Matthew L. Romo |
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| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Population
Population health Health records 03 medical and health sciences 0302 clinical medicine Margin (machine learning) Environmental health Influenza Human Diabetes Mellitus Prevalence Medicine Electronic Health Records Humans 030212 general & internal medicine education Equivalence (measure theory) Original Research education.field_of_study 030505 public health business.industry Depression Health Policy Public Health Environmental and Occupational Health Nutrition Surveys Health indicator Health Surveys 3. Good health Test (assessment) Influenza Vaccines Population Surveillance Community health Hypertension Immunization 0305 other medical science business |
| Zdroj: | Preventing Chronic Disease |
| ISSN: | 1545-1151 |
| Popis: | INTRODUCTION Electronic health record (EHR) systems provide an opportunity to use a novel data source for population health surveillance. Validation studies that compare prevalence estimates from EHRs and surveys most often use difference testing, which can, because of large sample sizes, lead to detection of significant differences that are not meaningful. We explored a novel application of the two one-sided t test (TOST) to assess the equivalence of prevalence estimates in 2 population-based surveys to inform margin selection for validating EHR-based surveillance prevalence estimates derived from large samples. METHODS We compared prevalence estimates of health indicators in the 2013 Community Health Survey (CHS) and the 2013-2014 New York City Health and Nutrition Examination Survey (NYC HANES) by using TOST, a 2-tailed t test, and other goodness-of-fit measures. RESULTS A ±5 percentage-point equivalence margin for a TOST performed well for most health indicators. For health indicators with a prevalence estimate of less than 10% (extreme obesity [CHS, 3.5%; NYC HANES, 5.1%] and serious psychological distress [CHS, 5.2%; NYC HANES, 4.8%]), a ±2.5 percentage-point margin was more consistent with other goodness-of-fit measures than the larger percentage-point margins. CONCLUSION A TOST with a ±5 percentage-point margin was useful in establishing equivalence, but a ±2.5 percentage-point margin may be appropriate for health indicators with a prevalence estimate of less than 10%. Equivalence testing can guide future efforts to validate EHR data. |
| Databáze: | OpenAIRE |
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