Foodborne Trematodiasis: Paragonimiasis
- Comorbidity correction (COMO)
- Age sex splitting
- Meta-analysis of mild, moderate, severe
- Out of DisMod crosswalks
- DisMod-MR 2.1
- Severity splits
Fungal Skin Diseases
- Adjustment from primary code to all code based on Claims data
- Comorbidity correction (COMO)
- Dismod-MR 2.1
- Age-sex splitting
Gallbladder and biliary diseases
- Adjustment from primary code to all code based on Claims data
- Comorbidity correction (COMO)
- Computing excess mortality from available incidence & CSMR data
- DisMod-MR 2.1
- Age-sex splitting
- Subtract prevalence of symptomatic episodes from prevalence of chronic gallbladder and biliary disease
- Meta-analysis of % mild\mod\severe gallbladder disease
- Severity splits
Gastritis and duodenitis
- 1. Nonfatal health outcome estimation
- Calculate 3 correction factors
- Convert claims to cases, Apply age and sex restrictions, Aggregate
- Convert inpatient encounters to prevalent cases using correction factors, Apply age and sex restrictions, Aggregate
- DisMod-MR 2.1
- Format codes, Map to modeling causes
- 3. Severity and anemia split
- 2. Anemia estimation
- Anemia causal attribution
Gastroesophageal reflux disease (GERD)
- Comorbidity correction (COMO)
- DisMod-MR 2.1
- Meta-analysis of symptom frequency
- Meta-analysis of symptom severity
Genital prolapse
- Comorbidity correction (COMO)
- Adjustment from primary code to all code based on Claims data
- Meta-analysis of % mild, moderate, severe prolapse
- Dismod-MR 2.1
- Severity splits
Glaucoma
- Comorbidity correction (COMO)
- Crosswalk data points that span multiple vision loss categories
- Split into moderate and severe vision loss
- Squeeze into severity-specific vision loss envelope
- Dismod-MR 2.1
Gout
- Comorbidity correction (COMO)
- DisMod-MR 2.1
- Age-sex splitting
- Average of two studies reporting average duration
- Lognormal fit to distribution of ## attacks per year
- Severity splits
Guillain-Barre syndrome (GBS)
- Comorbidity correction (COMO)
- Adjustment for case fatality rate via meta-analysis
- Identify and outlier extreme hospital data
- Age splitting
- Meta-analysis of % GBS underlying etiologies
- Dismod-MR 2.1
- Etiology splits
Guinea Worm
- Dismod-MR 2.1 to generate age trend
- Estimate uncertainty for vetted case data
- Estimate incidence from Poisson model
- Apply sex split
- Apply Dismod Age
- Assign sequelea
HAT
- Comorbidity correction (COMO)
- Age-splitting
- Incident cases
- Prevalence estimation
- Splitting sleeping disorder\disfig
Headaches
- Comorbidity correction (COMO)
- Age-sex splitting and age splitting
- Nonfatal Database
- Squeeze definite and probable migraine to the total
- Apply proportion of time episodic by probable/definite
- Meta-analysis proportion time symptomatic
- Meta-analysis for proportion of medication overuse headache due to migraine and tension-type headache
- Dismod-MR 2.1
Hearing Impairment
- Comorbidity correction (COMO)
- Adjust for hearing aid use
- Apply hearing aid coverage distribution by severity
- By severity, estimate proportion of people experiencing tinnitus
- Calculate congenital hearing loss as birth prevalence
- Crosswalk data points that span multiple hearing loss categories
- Multiple hearing loss by proportion of hearing loss due to age-relate and othre
- Proportionally split according to distribution of hearing loss envelope prevalences
- Proportionally split into mild\moderate via meta-analysis
- Proportionally squeeze causes to fit within each severity envelope
- Proportionally squeeze to 35+ envelope
- Proportionally squeeze to population
- Split into prevalence with\without tinnitus
- Dismod-MR 2.1
Heart failure
- Adjustment from primary code to all code based on Claims data
- Comorbidity correction (COMO)
- Age-sex splitting
- Meta-analysis of % mild, moderate, severe heart failure due to Chagas
- Multiply suqeezed proportions by overall prevalence of heart failure not including Chagas
- Proportion splits
- Apply correction factor using U.S. proportions only
- Generate correction factor using U.S. proportions only
- Subtract prevalence of heart failure due to Chagas from overall envelope
- Cause of Death\Claims data proportions
- Disability weights for each sequela
- Dismod-MR 2.1
- Meta-analysis of % mild, moderate, severe heart failure
- Regression of % mild, moderate, severe heart failure
- Severity splits
Hemoglobinopathies and hemolytic anemias
- Comorbidity correction (COMO)
- DisMod Incidence = 0, remission = 0
- DisMod-MR 2.1
- Adjustment from primary code to all code based on Claims data
- Anemia and heart failure envelope attribution
- Hardy-Weinberg equilibrium calculation on birth prevalence
- Meta-analysis of % with symptoms
- Severity splits
