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Lines 60-63 and 80-87, dynamic text for emergency admissions and usch…
There717 ffbd58d
Lines 326-327, filter out year with no data. Lines 336-398, add dynam…
There717 fdb2ae2
AE dynamic text
JosieSteele 46eeead
Addition of free text
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Dynamic text for readmissions
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Dynamic text unscheduled care mh and missing data fixes
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Added dynamic text for emergency admissions age groups and acute bed …
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minor wording and a typo fix
Moohan 95269e7
Update Unscheduled Care/2. Unscheduled Care outputs.R
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Merge branch 'community_care' of github.com:Public-Health-Scotland/li…
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Fixes to filter structure
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Merge branch 'development' into community_care
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Use `percent_change_calc` consistently.
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Apply `word_change_calc` consistently
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Merge branch 'community_care' of github.com:Public-Health-Scotland/li…
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Add `get_article()` to Community Care dynamic text (#111)
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Merge branch 'development' into community_care
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**Summary** | ||
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This section includes acute hospital data, delayed discharge bed days and A&E attendances. For the most recent time period available, `r LOCALITY` had: | ||
**For the most recent time periods available, `r LOCALITY` had:** | ||
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- **`r latest_emergency_adm_loc`** emergency hospital admissions per 100,000 population, compared to `r scot_emergency_adm` in Scotland. | ||
- **`r latest_emergency_adm_loc1`** emergency hospital admissions per 100,000 population, compared to `r scot_emergency_adm1` in Scotland. | ||
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- **`r latest_bed_days_loc`** unscheduled acute specialty bed days per 100,000 population, compared to `r scot_bed_days` in Scotland. | ||
- **`r latest_bed_days_loc1`** unscheduled acute specialty bed days per 100,000 population, compared to `r scot_bed_days1` in Scotland. | ||
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- **`r latest_ae_att_loc`** A&E attendances per 100,000 population, compared to `r scot_ae_att` in Scotland. | ||
- **`r latest_ae_att_loc1`** A&E attendances per 100,000 population, compared to `r scot_ae_att1` in Scotland. | ||
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- **`r latest_dd_loc`** delayed discharge bed days per 100,000 population aged over 65, compared to `r scot_dd` in Scotland. | ||
- **`r latest_dd_loc1`** delayed discharge bed days per 100,000 population aged over 65, compared to `r scot_dd1` in Scotland. | ||
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- **`r latest_falls_loc`** emergency hospital admissions from falls per 100,000 population aged over 65, compared to `r scot_falls` in Scotland. | ||
- **`r latest_falls_loc1`** emergency hospital admissions from falls per 100,000 population aged over 65, compared to `r scot_falls1` in Scotland. | ||
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- **`r latest_read_loc`** emergency readmissions (28 days) per 1,000 discharges, compared to `r scot_read` in Scotland. | ||
- **`r latest_read_loc1`** emergency readmissions (28 day) per 1,000 discharges, compared to `r scot_read` in Scotland. | ||
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- **`r latest_ppa_loc`** potentially preventable hospital admissions per 100,000 population, compared to `r scot_ppa` in Scotland. | ||
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- **`r latest_ppa_loc$data2[2]`** potentially preventable hospital admissions per 100,000 population, compared to `r scot_ppa$data2[2]` in Scotland. | ||
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##### Page break | ||
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### Emergency Admissions | ||
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Figure `r x` presents the emergency admissions rate per 100,000 population in the `r LOCALITY` locality from `r min_year_ea` to `r max_year_ea`. | ||
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As presented Figure `r x`, the emergency admissions rate in the `r LOCALITY` locality for `r max_year_ea` is `r latest_emergency_adm_loc1`, a `r percent_rate_change`% `r word_change_rate` since `r min_year_ea`. The `r HSCP` HSCP rate is `r hscp_emergency_adm1`, a `r hscp_rate_change`% `r word_change_hscp` since `r min_year_ea`. The `r HB` health board rate is `r hscp_emergency_adm1` in `r max_year_ea`, a `r hb_rate_change`% `r word_change_hb` since `r min_year_ea` and the Scotland rate is `r scot_emergency_adm1`, a `r scot_rate_change`% `r word_change_scot` since `r min_year_ea`. | ||
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#### Figure `r x`: Emergency admissions by geographical area | ||
\newline | ||
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@@ -686,6 +689,10 @@ EAs_loc_ts | |
x <- x + 1 | ||
``` | ||
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Figure `r x` presents the emergency admissions rate per 100,000 population in the `r LOCALITY` locality from `r min_ea_age` to `r max_ea_age` by age group. | ||
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As presented in Figure `r x`, the highest emergency admissions rate for the `r LOCALITY` locality in `r max_ea_age` is `r latest_ea_max_age1` per 100,000 population for the `r age_group_max_ea` age group with a percentage `r max_word_change_ea` of `r max_rate_change_ea`% since `r min_ea_age`. The lowest emergency admissions rate for `r LOCALITY` in `r max_ea_age` is `r latest_ea_min_age1` per 100,000 population for the `r age_group_min_ea` age group with a percentage `r min_word_change_ea` of `r min_rate_change_ea`% since `r min_ea_age`. | ||
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#### Figure `r x`: Emergency admissions by age group | ||
\newline | ||
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@@ -699,6 +706,10 @@ x <- x + 1 | |
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### Unscheduled Acute Bed Days | ||
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Figure `r x` presents the unscheduled bed days rate per 100,000 population in the `r LOCALITY` locality from `r min_year_ubd` to `r max_year_ubd`. | ||
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As presented in Figure `r x`, the unscheduled bed days rate in the `r LOCALITY` locality for `r max_year_ubd` is `r latest_bed_days_loc1`, a `r rate_change_ubd`% `r word_change_ubd` since `r min_year_ubd` and the `r HSCP` HSCP rate is `r hscp_bed_days1`, a `r hscp_rate_ubd`% `r hscp_change_ubd` since `r min_year_ubd`. The `r HB` health board rate for `r max_year_ubd` is `r hb_bed_days1`, a `r hb_rate_change_ubd`% `r word_change_hb_ubd` since `r min_year_ubd` and the Scotland rate is `r scot_bed_days1`, a `r scot_rate_ubd`% `r scot_change_ubd` since `r min_year_ubd`. | ||
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#### Figure `r x`: Unscheduled acute bed days by geographical area | ||
\newline | ||
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@@ -708,6 +719,10 @@ BDs_loc_ts | |
x <- x + 1 | ||
``` | ||
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Figure `r x` presents the unscheduled bed days rate per 100,000 population in the `r LOCALITY` locality from `r min_ubd_age` to `r max_ubd_age` by age group. | ||
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As presented in Figure `r x`, the highest unscheduled bed days rate for the `r LOCALITY` locality in `r max_ubd_age` is `r latest_ubd_max_age1` bed days per 100,000 population for the `r age_group_max_ubd` age group with a percentage `r max_word_change_ubd` of `r max_rate_change_ubd`% since `r min_ubd_age`. The lowest unscheduled bed days rate for `r LOCALITY` in `r max_ubd_age` is `r latest_ubd_min_age1` bed days per 100,000 population for the `r age_group_min_ubd` age group with a percentage `r min_word_change_ubd` of `r min_rate_change_ubd`% since `r min_ubd_age`. | ||
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#### Figure `r x`: Unscheduled acute bed days by age group | ||
\newline | ||
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### A&E Attendances | ||
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Figure `r x` presents the A&E attendance rate per 100,000 population in the `r LOCALITY` locality from `r min_year_ae_area` to `r max_year_ae_area`. | ||
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As presented in Figure `r x`, the A&E attendance rate per 100,000 in the `r LOCALITY` locality for `r max_year_ae_area` is `r latest_ae_att_loc1`, a `r percent_rate_change_ae_areas`% `r word_change_rate_ae_areas` since `r min_year_ae_area` and the `r HSCP` HSCP rate is `r hscp_ae_att1`, a `r percent_rate_change_ae_areas_hscp`% `r word_change_rate_ae_areas_hscp` since `r min_year_ae_area`. The `r HB` health board rate for `r max_year_ae_area` is `r hb_ae1`, a `r hb_rate_change_ae`% `r word_change_hb_ae` since `r min_year_ae_area` and the Scotland rate is `r scot_ae_att1`, a `r percent_rate_change_ae_areas_scot`% `r word_change_rate_ae_areas_scot` since `r min_year_ae_area`. | ||
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#### Figure `r x`: A&E attendances by geographical area | ||
\newline | ||
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x <- x + 1 | ||
``` | ||
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Figure `r x` presents the A&E attendance rate per 100,000 population in the `r LOCALITY` locality from `r min_year_ae_area` to `r max_year_ae_area` by age group. | ||
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As presented in Figure `r x`, the highest A&E attendance rate for the `r LOCALITY` locality in `r max_year_ae_age` is `r latest_ae_att_loc1_age` per 100,000 population for the `r age_group_max` age group with a percentage `r word_change_rate_ae_age` of `r percent_rate_change_ae_age`% since `r min_year_ae_age`. The lowest A&E attendance rate for `r LOCALITY` in `r max_year_ae_age` is `r latest_ae_att_loc1_age_min` per 100,000 population for the `r age_group_min` age group with a percentage `r word_change_rate_ae_age2` of `r percent_rate_change_ae_age2`% since `r min_year_ae_age`. | ||
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#### Figure `r x`: A&E attendances by age group | ||
\newline | ||
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### Emergency Readmissions (28 days) | ||
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Figure `r x` presents the emergency readmission (28 days) rate per 1,000 discharges in the `r LOCALITY` locality from `r min_year_re_area` to `r max_year_re_area`. | ||
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As presented in Figure `r x`, the emergency readmission (28 days) rate per 1,000 discharges in the `r LOCALITY` locality for `r max_year_re_area` is `r latest_read_loc1`, a `r percent_rate_change_re_area`% `r word_change_rate_re_area` since `r min_year_re_area` and the `r HSCP` HSCP rate is `r hscp_read`, a `r percent_rate_change_re_area_hscp`% `r word_change_rate_re_area_hscp` since `r min_year_re_area`. The `r HB` health board rate for `r max_year_re_area` is `r hb_read1`, a `r hb_rate_change_read`% `r word_change_hb_read` since `r min_year_re_area` and the Scotland rate is `r scot_read`, a `r percent_rate_change_re_area_scot`% `r word_change_rate_re_area_scot` since `r min_year_re_area`. | ||
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#### Figure `r x`: Emergency readmissions (28 days) by geographical area | ||
\newline | ||
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@@ -754,6 +781,10 @@ Read_loc_ts | |
x <- x + 1 | ||
``` | ||
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Figure `r x` presents the emergency readmission (28 days) rate per 1,000 discharges in the `r LOCALITY` locality from `r min_year_re_age` to `r max_year_re_age` by age group. | ||
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As presented in Figure `r x`, the highest emergency readmission (28 days) rate for the `r LOCALITY` locality in `r max_year_re_age` is `r latest_re_max_age_data` per 1,000 discharges for the `r latest_re_max_age_group` age group with a percentage `r word_change_rate_re_age` of `r percent_rate_change_re_age`% since `r min_year_re_age`. The lowest emergency readmission (28 days) rate for the `r LOCALITY` locality in `r max_year_re_age` is `r latest_re_min_age_data` per 1,000 discharges for the `r latest_re_min_age_group` age group with a percentage `r word_change_rate_re_age_min` of `r percent_rate_change_re_age_min`% since `r min_year_re_age`. | ||
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#### Figure `r x`: Emergency readmissions (28 days) by age group | ||
\newline | ||
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@@ -768,6 +799,10 @@ x <- x + 1 | |
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### Delayed Discharge Bed Days | ||
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Figure `r x` presents the number of delayed discharge bed days per 100,000 population aged over 65+ in the `r LOCALITY` locality from `r min_year_dd` to `r max_year_dd`. | ||
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As presented in Figure `r x`, the number of delayed discharge bed days per 100,000 population aged over 65+ in the `r LOCALITY` locality for `r max_year_dd ` is `r latest_dd_loc1`, a `r percent_rate_change_dd_loc`% `r word_change_rate_dd_loc` since `r min_year_dd` and the `r HSCP` HSCP rate is `r hscp_dd1`, a `r percent_rate_change_dd_hscp`% `r word_change_rate_dd_hscp` since `r min_year_dd`. The `r HB` health board rate for `r max_year_dd` is `r hb_dd1`, a `r hb_rate_change_dd`% `r word_change_hb_dd` since `r min_year_dd` and the Scotland rate is `r scot_dd1`, a `r percent_rate_change_dd_scot`% `r word_change_rate_dd_scot` since `r min_year_dd`. | ||
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#### Figure `r x`: Delayed discharge bed days in the population aged 65+ by geographical area | ||
\newline | ||
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### Emergency admissions from a fall | ||
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Figure `r x` presents the emergency admissions from falls rate per 100,000 population aged over 65+ in the `r LOCALITY` locality from `r min_year_falls` to `r max_year_falls`. | ||
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As presented in Figure `r x`, the emergency admissions from falls rate per 100,000 population aged over 65+ in the `r LOCALITY` locality for `r max_year_falls ` is `r latest_falls_loc1`, a `r percent_rate_change_falls_loc`% `r word_change_rate_falls_loc` since `r min_year_falls` and the `r HSCP` HSCP rate is `r hscp_falls1`, a `r percent_rate_change_falls_hscp`% `r word_change_rate_falls_hscp` since `r min_year_falls`. The `r HB` health board rate for `r max_year_falls` is `r hb_falls1`, a `r hb_rate_change_falls`% `r word_change_hb_falls` since `r min_year_falls` and the Scotland rate is `r scot_falls1`, a `r percent_rate_change_falls_scot`% `r word_change_rate_falls_scot` since `r min_year_falls`. | ||
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#### Figure `r x`: Falls in the population aged 65+ by geographical area | ||
\newline | ||
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Information on the conditions included in PPAs is available in Appendix 3. In `r max_fy`, **`r latest_ppa_65plus`%** of PPAs in `r LOCALITY` were amongst those aged 65 and over, and **`r latest_ppa_under65`%** were amongst those aged under 65. | ||
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Figure `r x` presents the potentially preventable admissions rate per 100,000 population in the `r LOCALITY` locality from `r min_year_ppa_areas` to `r max_year_ppa_areas`. The rate per 100,000 population for potentially preventable admissions in the `r LOCALITY` locality for `r max_year_ppa_areas ` is `r latest_ppa_loc$data2[2]`, a `r ppa_diff`% `r ppa_word_change` since `r latest_ppa_loc$financial_year[1]` and the `r HSCP` HSCP rate is `r hscp_ppa$data[2]`, a `r ppa_diff_hscp`% `r ppa_word_change_hscp` since `r latest_ppa_loc$financial_year[1]`. | ||
The `r HB` health board rate for `r hb_ppa$financial_year[2]` is `r hb_ppa$data2[2]`, a `r diff_hb_ppa`% `r word_change_hb_ppa` since `r hb_ppa$financial_year[]` and the Scotland rate is `r scot_ppa$data2[2]`, a `r diff_scot_ppa`% `r word_change_scot_ppa` since `r hb_ppa$financial_year[1]`. | ||
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#### Figure `r x`: Potentially Preventable Admissions (PPAs) by geographical area | ||
\newline | ||
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This section looks at mental health-related unscheduled care indicators. For the most recent time period available, `r LOCALITY` had: | ||
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- **`r psych_hosp_latest`** psychiatric patient hospitalisations per 100,000, compared to `r scot_psych_hosp` in Scotland^4^. | ||
- **`r latest_bed_days_mh_loc`** unscheduled mental health specialty bed days per 100,000, compared to `r scot_bed_days_mh` in Scotland. | ||
- **`r psych_hosp_latest`** psychiatric patient hospitalisations per 100,000, compared to `r scot_psych_hosp$measure[2]` in Scotland^4^. | ||
- **`r latest_bed_days_mh_loc1`** unscheduled mental health specialty bed days per 100,000, compared to `r scot_bed_days_mh1` in Scotland. | ||
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\newline | ||
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### Psychiatric patient hospitalisations | ||
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Figure `r x` presents the psychiatric patient hospitalisation 3-year aggregate rate per 100,000 population in the `r LOCALITY` locality from `r loc_psych_hosp$period_short[1]` to `r loc_psych_hosp$period_short[2]`. | ||
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As presented in Figure `r x`, the 3-year aggregate psychiatric patient hospitalisation rate per 100,000 population in the `r LOCALITY` locality for `r loc_psych_hosp$period_short[2]` is `r loc_psych_hosp$measure[2]`, a `r diff_loc_psych`% `r word_change_loc_psych` since `r loc_psych_hosp$period_short[1]` and the `r HSCP` HSCP rate is `r hscp_psych_hosp$measure[2]`, a `r diff_hscp_psych`% `r word_change_hscp_psych` since `r loc_psych_hosp$period_short[1]`. The `r HB` health board the 3-year aggregate rate for `r loc_psych_hosp$period_short[2]` is `r hb_psych_hosp$measure[2]`, a `r diff_hb_psych`% `r word_change_hb_psych` since `r loc_psych_hosp$period_short[1]` and the Scotland the 3-year aggregate rate is `r scot_psych_hosp$measure[2]`, a `r diff_scot_psych`% `r word_change_scot_psych` since `r loc_psych_hosp$period_short[1]`. | ||
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#### Figure `r x`: Psychiatric patient hospitalisations by geographical area | ||
\newline | ||
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@@ -838,6 +884,10 @@ x <- x + 1 | |
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### Unscheduled Mental Health Specialty Bed Days | ||
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Figure `r x` presents the unscheduled mental health bed days rate per 100,000 population in the `r LOCALITY` locality from `r min_year_bd_mh_areas` to `r max_year_bd_mh_areas`. | ||
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As presented in Figure `r x`, the unscheduled mental health bed days rate per 100,000 population in the `r LOCALITY` locality for `r max_year_bd_mh_areas ` is `r latest_bed_days_mh_loc1`, a `r loc_rate_change_beds_mh`% `r loc_word_change_beds_mh` since `r min_year_bd_mh_areas` and the `r HSCP` HSCP rate is `r hscp_bed_days_mh1`, a `r hscp_rate_change_beds_mh`% `r hscp_word_change_beds_mh` since `r min_year_bd_mh_areas`. The `r HB` health board rate for `r max_year_bd_mh_areas` is `r hb_mh_beddays1`, a `r hb_rate_change_mh`% `r word_change_hb_mh` since `r min_year_bd_mh_areas` and the Scotland rate is `r scot_bed_days_mh1`, a `r scot_rate_change_beds_mh`% `r scot_word_change_beds_mh` since `r min_year_bd_mh_areas`. | ||
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#### Figure `r x`: Unscheduled mental health specialty bed days by geographical area | ||
\newline | ||
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@@ -847,6 +897,10 @@ BDMH_loc_ts | |
x <- x + 1 | ||
``` | ||
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Figure `r x` presents the unscheduled mental health bed days rate per 100,000 in the `r LOCALITY` locality from `r min_year_bd_mh_age` to `r max_year_bd_mh_age` by age group. | ||
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As presented in Figure `r x`, the highest unscheduled mental health bed days rate for the `r LOCALITY` locality in `r max_year_bd_mh_age` is `r latest_bd_mh_max_age1` per 100,000 population for the `r age_group_max_mh` age group with a percentage `r max_word_change_beds_mh` of `r max_rate_change_beds_mh`% since `r min_year_bd_mh_age`. The lowest unscheduled mental health bed days rate for the `r LOCALITY` locality in `r max_year_bd_mh_age` is `r latest_bd_mh_min_age1` per 100,000 population for the `r age_group_min_mh` age group with a percentage `r min_word_change_beds_mh` of `r min_rate_change_beds_mh`% since `r min_year_bd_mh_age1`. | ||
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#### Figure `r x`: Unscheduled mental health specialty bed days by age group | ||
\newline | ||
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@@ -861,11 +915,11 @@ x <- x + 1 | |
##### Page Break | ||
### Footnotes | ||
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1. Population projections are not currently provided by NRS at the locality level. To explore how the population in `r LOCALITY` is expected to change in the future, the percent changes in population projection to 2025 for `r HSCP` by age group and gender were calculated from the NRS Local Authority Population Projections. These percent changes were then applied to the `r LOCALITY` 2018 mid-year population estimates (also split by age group and gender) to obtain population projection estimates for `r LOCALITY`, based on the projections for the HSCP and the current population structure of the locality. | ||
1. Population projections are not currently provided by NRS at the locality level. To explore how the population in `r LOCALITY` is expected to change in the future, the percent changes in population projection to 2025 for `r HSCP` by age group and gender were calculated using the NRS Local Authority Population Projections. These percent changes were then applied to the `r LOCALITY` 2018 mid-year population estimates (also split by age group and gender) to obtain population projection estimates for `r LOCALITY`, based on the projections for the HSCP and the current population structure of the locality. | ||
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2. Care Home Data included in the Services Map and Table was sourced from the [Care Inspectorate](https://www.careinspectorate.com/images/documents/5713/MDSF_data_31%20May%202020.csv). [GP Practice](https://www.opendata.nhs.scot/dataset/gp-practice-contact-details-and-list-sizes) data from October 2021, and [Hospital](https://www.opendata.nhs.scot/dataset/hospital-codes) and [A&E](https://www.opendata.nhs.scot/dataset/nhs-scotland-accident-emergency-sites) data was sourced from Public Health Scotland Open Data. Only services that are within the physical boundary of the HSCP or Locality are included in the map and table, so there may be services outside `r HSCP` that people may use but are not shown. Information on access deprivation was taken from [ScotPHO](https://scotland.shinyapps.io/ScotPHO_profiles_tool/). | ||
2. Care Home data included in the Services Map and Table was sourced from the [Care Inspectorate](https://www.careinspectorate.com/images/documents/5713/MDSF_data_31%20May%202020.csv). [GP Practice](https://www.opendata.nhs.scot/dataset/gp-practice-contact-details-and-list-sizes) data from October 2021, and [Hospital](https://www.opendata.nhs.scot/dataset/hospital-codes) and [A&E](https://www.opendata.nhs.scot/dataset/nhs-scotland-accident-emergency-sites) data was sourced from Public Health Scotland Open Data. Only services that are within the physical boundary of the HSCP or Locality are included in the map and table, so there may be services outside `r HSCP` that people may use but are not shown. Information on access deprivation was taken from [ScotPHO](https://scotland.shinyapps.io/ScotPHO_profiles_tool/). | ||
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3. Sourced from [ScotPHO](https://scotland.shinyapps.io/ScotPHO_profiles_tool/). There may be more recent data available for the indicators elsewhere. | ||
3. Sourced from [ScotPHO](https://scotland.shinyapps.io/ScotPHO_profiles_tool/). More recent data may be available for the indicators elsewhere. | ||
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4. Data taken from ScotPHO is often reported using the European Age-Sex Standardised Rate per 100,000. This allows for comparisons across different areas to be made. For more information on how these rates are calculated, please refer to [www.isdscotland.org/Products-and-Services/GPD-Support/Population/Standard-Populations/](https://www.isdscotland.org/Products-and-Services/GPD-Support/Population/Standard-Populations/) | ||
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In the USC/USC-testing-markdown, this looks wrong. Can you compare the two docs and 1) make sure they're the same, please.
For this heading I think a level 3 heading
### Summary
is probably correct, rather than just bold**Summary**