3 Indicator definitions

These are as extracted from the definitions as agreed for the proof of concept

3.1 Anti-microbial resistance

Percentage of bloodstream infections due to selected antimicrobial-resistant organisms (MRSA, Escherichia coli resistant to 3rd-generation cephalosporin (e.g., ESBL- E. coli))

3.1.1 Staphylococcus aureus

title	denominator	numerator	metric	notes
Percentage of bloodstream infections due to selected antimicrobial-resistant organisms: MRSA	Total No. of patients with growth of S. aureus in tested blood samples	No. of patients with growth of methicillin-resistant S. aureus in tested blood samples	Proportion

3.1.2 Escherichia coli

title	denominator	numerator	metric	notes
Percentage of bloodstream infections due to selected antimicrobial-resistant organisms: E.coli	Total No. of patients with growth of E. coli in tested blood samples	No. of patients with growth of E.coli resistant to 3rd generation cephalosporins in tested blood samples	Proportion	Resistance to ceftazidine, cefotaxine

3.2 Smoking

Current cigarette smoking among women aged 18-44 years

title	denominator	numerator	metric	notes
PCurrent cigarette smoking among women aged 18-44 years	Women aged 18-44 years who information about cigarette smoking (excluding unknowns and refusals).	Women aged 18-44 years who reported that they smoked ≥100 cigarettes in their lifetime and currently smoke every day or some days.	Rate with 95% confidence intervals	Data provided is attendances at smoking clinics rather than survey based smoking prevalence

3.3 Injury

Nonfatal hospitalizations for all injuries

title	denominator	numerator	metric	notes
Nonfatal hospitalizations for all injuries	Midyear population for the calendar year under surveillance obtained from the KSA Census or suitable alternative.	Nonfatal hospitalizations with any of the following ICD-10-CM diagnostic codes in the principal diagnosis field	Rate (age standardised) with 95% confidence intervals	Data provided is attendances at smoking clinics rather than survey based smoking prevalence

3.4 Flu vaccination coverage

3.4.1 Paediatric

title	denominator	numerator	metric	notes
Population vaccination coverage - Flu (pediatric group 6 months - 18 years old))	The total number of children eligible for influenza vaccination	The total number of children in the respective eligible age cohort that have received at least one dose of influenza vaccine from 1 Oct in school, pharmacy, and general practice.	Proportion with 95% confidence intervals	Data provided is attendances at smoking clinics rather than survey based smoking prevalence

3.4.2 At-risk groups

The dataset required for calculating coverage for at-risk groups is much more complex than for age-specific coverage rates because it needs details of underlying diseases e.g. asthma, COPD.

3.4.3 65+

title	denominator	numerator	metric	notes
Population vaccination coverage - Flu (65+))	The total number of adults 65+ eligible for influenza vaccination	The total number of children in the respective eligible age cohort	Proportion with 95% confidence intervals	Data provided is attendances at smoking clinics rather than survey based smoking prevalence

--- title: "Indicator definitions" format: html: fig-height: 10 fig-width: 8 toc: true toc-location: right code-fold: true code-tools: true execute: freeze: false echo: false --- ```{r} #| label: setup #| include: false needs(tidyverse, flextable, gt) indicators <- read_csv("data/indicators.csv") ``` These are as extracted from the definitions as agreed for the proof of concept ## Anti-microbial resistance Percentage of bloodstream infections due to selected antimicrobial-resistant organisms (MRSA, Escherichia coli resistant to 3rd-generation cephalosporin (e.g., ESBL- E. coli)) ### Staphylococcus aureus ```{r} #| label: staph areus amr_def_sa <- data.frame( title = "Percentage of bloodstream infections due to selected antimicrobial-resistant organisms: MRSA", denominator = "Total No. of patients with growth of S. aureus in tested blood samples", numerator = "No. of patients with growth of methicillin-resistant S. aureus in tested blood samples", metric = "Proportion", notes = "" ) amr_def_sa |> flextable(cwidth = 6) ``` ### Escherichia coli ```{r} #| label: e coli amr_def_ec <- data.frame( title = "Percentage of bloodstream infections due to selected antimicrobial-resistant organisms: E.coli", denominator = "Total No. of patients with growth of E. coli in tested blood samples", numerator = "No. of patients with growth of E.coli resistant to 3rd generation cephalosporins in tested blood samples", metric = "Proportion", notes = "Resistance to ceftazidine, cefotaxine" ) amr_def_ec |> flextable(cwidth = 6) ``` ## Smoking Current cigarette smoking among women aged 18-44 years ```{r} #| label: smoking smok_def <- data.frame( title = "PCurrent cigarette smoking among women aged 18-44 years", denominator = "Women aged 18-44 years who information about cigarette smoking (excluding unknowns and refusals).", numerator = "Women aged 18-44 years who reported that they smoked ≥100 cigarettes in their lifetime and currently smoke every day or some days.", metric = "Rate with 95% confidence intervals", notes = "Data provided is attendances at smoking clinics rather than survey based smoking prevalence" ) smok_def |> flextable(cwidth = 6) ``` ## Injury Nonfatal hospitalizations for all injuries ```{r} #| label: injury inj_def <- data.frame( title = "Nonfatal hospitalizations for all injuries", denominator = "Midyear population for the calendar year under surveillance obtained from the KSA Census or suitable alternative.", numerator = "Nonfatal hospitalizations with any of the following ICD-10-CM diagnostic codes in the principal diagnosis field", metric = "Rate (age standardised) with 95% confidence intervals", notes = "Data provided is attendances at smoking clinics rather than survey based smoking prevalence" ) inj_def |> flextable(cwidth = 6) ``` ## Flu vaccination coverage ### Paediatric ```{r} #| label: flu paediatric flu_def <- data.frame( title = "Population vaccination coverage - Flu (pediatric group 6 months - 18 years old))", denominator = "The total number of children eligible for influenza vaccination", numerator = "The total number of children in the respective eligible age cohort that have received at least one dose of influenza vaccine from 1 Oct in school, pharmacy, and general practice.", metric = "Proportion with 95% confidence intervals", notes = "Data provided is attendances at smoking clinics rather than survey based smoking prevalence" ) flu_def |> flextable(cwidth = 6) ``` ### At-risk groups The dataset required for calculating coverage for at-risk groups is much more complex than for age-specific coverage rates because it needs details of underlying diseases e.g. asthma, COPD. ### 65+ ```{r} #| label: flu 65 and over flu_def_65 <- data.frame( title = "Population vaccination coverage - Flu (65+))", denominator = "The total number of adults 65+ eligible for influenza vaccination", numerator = "The total number of children in the respective eligible age cohort", metric = "Proportion with 95% confidence intervals", notes = "Data provided is attendances at smoking clinics rather than survey based smoking prevalence" ) flu_def_65 |> flextable(cwidth = 6) ```