Quantitative Service Delivery Survey in Health 2000
Uganda, 2000
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Reference ID
UGA_2000_QSDS_v01_M
Producer(s)
World Bank, Makerere Institute for Social Research, Uganda, Ministry of Health, Uganda, Ministry of Finance, Planning and Economic Development, Uganda
Collection(s)
Created on
Dec 06, 2011
Last modified
Sep 26, 2013
Page views
190816
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13375
chloroquine ending date (t7b3)
Data file: facilitydatasheets_cleaned_data
Overview
Valid:
84
Invalid:
66
Minimum:
0
Maximum:
57000
Type:
Discrete
Decimal:
0
Start:
2551
End:
2555
Width:
5
Range:
0 - 57000
Format:
Numeric
Questions and instructions
Question pretext
Table 7: Drug use from stock cards (ALL FACILITIES)
From the stock cards identify two dates spanning roughly one month, preferably during the period April-June, 2000).
Ensure that the starting date is before the ending date and that it is some time in between them (preferably around 1 month).
Start at a time when a new supply is received (or shortly afterwards), and ensure that no new supplies were received in the period and that there were no stockouts over the period. It is also important that the stock moved during the identified period; that is, the sum of "amount removed" and "stock after removal" at starting date minus the sum of "amount removed" and "stock after removal" at end date should be a positive number.
If the starting date is the same as the supply date, ensure that the stock is at least as large as the supply.
Record the starting date, the amount removed ('Quantity Out'), and the stock after the removal ('Balance in hand') of drugs on that date.
Record the ending date (roughly one month later), the amount removed ('Quantity Out'), and the stock after the removal ('Balance on hand').
Use 'NA' only if no records are available. There should be NO EMPTY CELLS.
From the stock cards identify two dates spanning roughly one month, preferably during the period April-June, 2000).
Ensure that the starting date is before the ending date and that it is some time in between them (preferably around 1 month).
Start at a time when a new supply is received (or shortly afterwards), and ensure that no new supplies were received in the period and that there were no stockouts over the period. It is also important that the stock moved during the identified period; that is, the sum of "amount removed" and "stock after removal" at starting date minus the sum of "amount removed" and "stock after removal" at end date should be a positive number.
If the starting date is the same as the supply date, ensure that the stock is at least as large as the supply.
Record the starting date, the amount removed ('Quantity Out'), and the stock after the removal ('Balance in hand') of drugs on that date.
Record the ending date (roughly one month later), the amount removed ('Quantity Out'), and the stock after the removal ('Balance on hand').
Use 'NA' only if no records are available. There should be NO EMPTY CELLS.
Literal question
Chloroquine tablets
Ending date
Stock after removal
Ending date
Stock after removal
Categories
| Value | Category | Cases | |
|---|---|---|---|
| 0 | 1 |
1.2%
|
|
| 5 | 1 |
1.2%
|
|
| 504 | 1 |
1.2%
|
|
| 600 | 1 |
1.2%
|
|
| 700 | 1 |
1.2%
|
|
| 750 | 1 |
1.2%
|
|
| 925 | 1 |
1.2%
|
|
| 930 | 1 |
1.2%
|
|
| 1000 | 2 |
2.4%
|
|
| 1200 | 1 |
1.2%
|
|
| 1918 | 1 |
1.2%
|
|
| 2000 | 1 |
1.2%
|
|
| 2300 | 1 |
1.2%
|
|
| 2317 | 1 |
1.2%
|
|
| 2360 | 1 |
1.2%
|
|
| 2927 | 1 |
1.2%
|
|
| 3000 | 5 |
6%
|
|
| 3500 | 2 |
2.4%
|
|
| 4000 | 8 |
9.5%
|
|
| 4115 | 1 |
1.2%
|
|
| 4400 | 1 |
1.2%
|
|
| 4800 | 1 |
1.2%
|
|
| 4900 | 1 |
1.2%
|
|
| 5000 | 4 |
4.8%
|
|
| 5261 | 1 |
1.2%
|
|
| 6000 | 2 |
2.4%
|
|
| 6202 | 1 |
1.2%
|
|
| 6500 | 1 |
1.2%
|
|
| 7000 | 2 |
2.4%
|
|
| 7600 | 1 |
1.2%
|
|
| 8000 | 1 |
1.2%
|
|
| 8300 | 2 |
2.4%
|
|
| 8542 | 1 |
1.2%
|
|
| 8949 | 1 |
1.2%
|
|
| 9000 | 2 |
2.4%
|
|
| 9400 | 2 |
2.4%
|
|
| 9598 | 1 |
1.2%
|
|
| 10000 | 2 |
2.4%
|
|
| 10495 | 1 |
1.2%
|
|
| 10898 | 1 |
1.2%
|
|
| 11784 | 1 |
1.2%
|
|
| 12000 | 1 |
1.2%
|
|
| 12940 | 1 |
1.2%
|
|
| 14046 | 1 |
1.2%
|
|
| 14460 | 1 |
1.2%
|
|
| 15226 | 1 |
1.2%
|
|
| 16789 | 1 |
1.2%
|
|
| 17000 | 1 |
1.2%
|
|
| 18005 | 1 |
1.2%
|
|
| 20000 | 1 |
1.2%
|
|
| 21000 | 1 |
1.2%
|
|
| 21120 | 1 |
1.2%
|
|
| 21820 | 1 |
1.2%
|
|
| 22406 | 1 |
1.2%
|
|
| 24000 | 1 |
1.2%
|
|
| 26709 | 1 |
1.2%
|
|
| 26970 | 1 |
1.2%
|
|
| 27000 | 1 |
1.2%
|
|
| 32000 | 1 |
1.2%
|
|
| 34225 | 1 |
1.2%
|
|
| 36000 | 1 |
1.2%
|
|
| 57000 | 1 |
1.2%
|
|
| Sysmiss | 66 |
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.