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Review Date: March 2014
Republic of South Sudan
DHIS INTERMEDIATE TRAINING MANUAL
Final Draft
Directorate General of Policy, Planning, Budgeting and
Research
2
Acknowledgements
The achievements in the DHIS and HMIS implementation continue to grow in
South Sudan, under the leadership of the Honourable Dr Riek Gai Kok, Minister
for Health and Dr Makur Kariom, Undersecretary, Ministry of Health.
The DHIS Intermediate Training Manual is an example of the increased ability,
skills and knowledge in South Sudan as we work towards developing effective
and efficient health care system.
The Ministry of Health thanks the Ministry of Health Directorates, State
Ministries of Health and County Health Departments for their input and
participation, as well as the supporting partners. The Ministry also gives thanks
to health workers working at the facility/community levels collecting the data.
Dr Richard Lako
Director General of Policy, Planning, Budgeting and Research
Ministry of Health, Republic of South Sudan
3
Table of Contents
Advanced Data Entry/ Edit
6
Producing Reports
8
Data Quality
14
Importing
25
Advanced Set-up Functions
29
Updating the Org Hierarchy
33
Pivot Tables
44
Top Tips and Quiz Answers
59
4
Introduction to the course
Welcome the DHIS Intermediate Training Course!
The aim of the course is to improve the skills and knowledge, supplementary to the Foundation
Training Course. The course is practical with examples, exercises and quiz questions
throughout. The answers to the quiz questions can be found at the end of the manual.
By the end of the course, participants will be able to:
1.
Change the location or period of the data already entered
2.
Produce useful standard reports
3.
Identify common data quality issues
4.
Ensure consistent importing of data
5.
Update the organisational hierarchy
6.
Use pivot tables to analyse data
If participants want to do some revision, we’d recommend reading the DHIS Foundation
Training Manual.
If participants want to gain more knowledge, look out for the Data Quality Manual, which will be
released later in 2014.
5
Learning Log
Session
What did I learn in this session? What will I do differently in
my work?
6
For basics see Chapter 3
Foundation DHIS South
Sudan Manual
ADVANCED DATA ENTRY/ EDIT
The session covers:
• Moving the data to correct facility/month
7
If data is captured in the incorrect month or facility you can move
the data easily using Options and Data Correction
1. Select Options
2. Select Data
Correction
You can move
data to another
OrgUnit
or another Data
Period
8
PRODUCING REPORTS
The session covers:
• Revision on producing standard reports
• Producing completeness reports
9
Revision on producing standard reports
1
2
3
4
5
Select “Standard Reports” on the Control Centre
1. Select Routine Raw Data Reports
2. Select a Data set you want
3. Select the Org Unit level. Facility/county/state
4. Select the “from” and “to” dates
5. Select whether you want a word document or an excel document
The report is not saved, a new document opens on your taskbar that you can
look at. Save this as a useful name! E.g. “Akoka Jan-Jun 2011”
10
Producing completeness reports, an important monitoring
tool
1
2
4
3
Select “Data Quality” on the Control Centre
1. Select Data Completeness Report
2. Select a Data set you want
3. Select the Org Unit level. Facility/county/state
4. Select the “from” and “to” dates
5. Run Analysis
You can also select whether you want a word document or an excel document
4
5
11
Producing completeness reports (continued)
12
Exercise 1: Producing a standard report
Create a Routine Raw Data Report for one state
• Time Period:
January to June 2013
• Save the file as:
Raw Data Report_[State Name]_Jan_Jun_2013
13
Exercise 2: Data completeness
Create a data completeness report for your state
Jan-June 2013
Save the file
Completeness_[State Name]_Jan_Jun_2013
Make a list of 10 facilities that are the worst in reporting
14
DATA QUALITY
The session covers:
• Data Quality Rules
• Tips for looking out for errors
• Data validation rule set up
Data Quality Guide January 2012 (Modified March 2014)
Guidelines for Good Data Quality and Data Capture
This is a guideline on how to ensure that the data provided in the routine monthly report is of good quality and
provides some tips of what good data quality looks like. It also gives suggestions on when to provide a comment
to explain why the data does not look like it would be expected to be.
10 Common Data Quality Issues with a Monthly Report
•
Rule 1: Comparing diarrhea treated with ORS and Diarrhea all under 5
Children with diarrhea treated with ORS must be less than or the same as all children with
diarrhoea. If all children with diarrhoea are given ORT (ORS or any homemade fluid) as in the South
Sudan protocol for rehydration, the 2 values should be similar. This is an absolute rule.
Diarrhoea treated with ORS under 5 years
Diarrhoea all under 5 years
58
61
However if the use of ORS is low and the children with diarrhoea are not given ORS, this should be
explained.
•
Rule 2: Children with malaria must be less than children seen
It is accepted that more children can be seen with malaria, diarrhoea and pneumonia than children
who were seen, as a child may have more than 1 diagnosis. An example would be the child has both
malaria and diarrhoea.
However there cannot be more children with malaria than children seen. This is an absolute rule.
There should also be a relationship between children seen and malaria, diarrhoea and pneumonia.
See Statistical rules
Children with diarrhea, malaria and pneumonia should generally be less than all children seen
Consultation curative under 5 male
Consultation curative under 5 female
Malaria clinically diagnosed
Malaria confirmed
Malaria severe
39
31
49
22
16
Add up the children with malaria: 87. All children seen add up to 70. This is wrong data.
•
Rule 3: Pneumonia presumed should be small numbers
Pneumonia presumed under 5 years is defined as cough or difficult and fast breathing. The
definition of fast breathing depends on the age of the child:
Age
Breaths per minute
1 week up to 2 months
60 breaths per minute or more = fast breathing
2 months up to 12 months
50 breaths per minute or more
12 months up to 5 years
40 breaths per minute or more
Generally very few children are seen with ‘real’ pneumonia. Most children have upper respiratory
tract infection, which are NOT reported. This is a statistical rule.
Data Quality Guide January 2012 (Modified March 2014)
•
Rule 4: Comparing children with malaria, diarrhea, pneumonia with total children seen
The total number of cases for malaria, diarrhea and pneumonia for under 5 years, should correlate
the total consultations under 5 male and female. The total cases should be less than or slightly
greater than the total consultations under 5.
Children with diarrhoea, malaria and pneumonia should generally be less than all children seen.
This is because the health facility will see other cases that are recorded in the register but not
recorded in the monthly form, for example, other communicable diseases/eye diseases. Several
children may show signs of multiple health issues, hence the total could end up slightly higher than
the total consultations.
The below is example fulfils the rule. 101 Consultations Under 5, 96 cases of malaria, diarrhea,
pneumonia.
48
53
21
Curative consultation under 5 male
Curative consultation under 5 female
Malaria uncomplicated clinically diagnosed under 5 years
Malaria uncomplicated confirmed under 5 years
Malaria severe under 5 years
Pneumonia presumed under 5 years
Diarrhea treated with ORS under 5 years
Diarrhea all under 5 years
7
3
32
33
No RDTs
•
Rule 5: Comparing ANC visits
Antenatal client 4th or more visit should be a small number as very few women come for more than
1 or 2 antenatal visits. This is a statistical rule.
•
Rule 6: Comparing live births and Deliveries in facility
Live births in facility should be similar to deliveries in facility (delivery by skilled staff and unskilled
staff). If there were multiple births, the live births may be more than the deliveries, if there were
still births, the figure may be slightly smaller than deliveries.
NB: “Delivery in community” should not be included in the “Live births in facility”.
Delivery in facility by Skilled Birth Attendant
Delivery in facility by TBA, MCHW, Community Health
Worker, Community Midwife or Village Midwife
Delivery in community
Delivery referred
Live birth in facility
4
12
4
0
16
Data Quality Guide January 2012 (Modified March 2014)
•
Rule 7: Deliveries in community
Deliveries done in community and written into the Delivery Register are NOT counted as deliveries
in the facility nor are these births included as live births in facility.
•
Rule 8: All deaths in the facility are reported
Deaths that occur in the community are NOT included
Deaths under 5 years and maternal deaths that occur in the facility are included in the sum of all deaths.
This is an absolute rule.
Death in facility all
Death in facility under 5 years
Death in facility maternal
5
2
0
The following data is wrong:
Death in facility all
Death in facility under 5 years
Death in facility maternal
2
4
1
This states that there were only 2 deaths in the facility, but 4 children died and there was 1 maternal death
in the facility. There should be at least 5 deaths reported.
•
Rule 9: VCT client seen and Client tested for HIV
All VCT clients must be seen which implies counselling, before being tested. Therefore clients tested for HIV
cannot be more than clients seen for VCT. This is an absolute rule.
VCT client seen
VCT client tested for HIV - new
5
2
• Rule 10: DPT 3rd dose VS DPT 1st dose
Usually DPT 3 doses are slightly lower than DPT 1 as there are some drop outs
Data Quality Guide January 2012 (Modified March 2014)
General tips when “eyeballing” data
Use these Guidelines for Good Quality Data to identify potential errors
Look out for duplicate data; is the data the same as the previous month?
DataElement
Consultation curative under 5 years male
Consultation curative under 5 years female
Curative consultation 5 years and older male
Curative consultation 5 years and older female
Antenatal client 1st visit
Antenatal client 4th or more visit
10-Nov 10-Dec
61
125
82
148
43
33
30
36
17
13
11
6
11-Jan
51
70
21
34
15
7
11-Feb
51
70
21
34
15
7
January and February have the same data…..
Look out for made up data; (for example round numbers like 1000, 1010, 900)
Very high numbers compared to the previous months
Very low numbers compared to the previous months
Have unusual numbers been explained in the comments?
Data Quality Guide January 2012 (Modified March 2014)
Tips for Data Capturing in the Form
Three Top Tips to pass onto the health facility
•
Tip 1: Use of Zero and blanks when capturing data
If your facility does NOT render a specific service, then leave the column blank – if you put in a zero ‘0’ this
means that the facility was ready, equipped, stocked, trained and capable of rendering the service but no
one came. For example: HIV Services if this facility does not render any HIV services then leave the section
on HIV blank. Another example is Caesarean section done: if the service is not provided, leave it blank; if
normally provided and none were done this month, put “0”
•
Tip 2: The facility did not function in a month
Should a facility NOT function in a specific month(s), then open the Data Entry/Edit form and at Consultation
Curative under 5r years male – put in a zero ‘0’ and in the Comment column select the following remark
from the drop down list ‘No activity this month’.
•
Tip 3: Use the comments box
A comment is given to explain why data does not look like you expect it to look.
The comment provided could be ‘influx of cattle herders’. This explains why the figure is much higher than
normal in January 2011. Another example could be to explain why so little ORS was given to children with
diarrhea.
Diarrhoea treated with ORS under 5 years
3 Stock out of ORS
Diarrhoea all under 5 years
61
If the facility has accidently put “0” but you know they do not provide the service, please leave the data
element blank, when you do data entry.
20
Data Quality Rules: Answer True or False…
Diarrhoea treated with ORS under 5 years
Diarrhoea all under 5 years
Consultation curative under 5 male
Consultation curative under 5 female
Malaria clinically diagnosed
Malaria confirmed
Malaria severe
Delivery in facility by Skilled Birth Attendant
Delivery in facility by TBA, MCHW,
Community Health Worker, Community
Midwife or Village Midwife
Delivery in community
Delivery referred
Live birth in facility
58
61
39
70
49
123
16
13
26
0
12
Diarrhoea
treated with
ORS is equal to
or less than
Diarrhoea all
under 5
Children with
malaria must be
less than children
seen
Comparing live
births and
Deliveries in
facility
21
What is your opinion?
22
What is your opinion?
1. Numbers should be explained, not ignored
23
Real Example
• Can you find the errors?
24
Remember…Data must link together; does the make
sense?
25
IMPORTING DATA
The session covers:
• Tips on making the right choices
• Description of key symbols
26
Importing data relies on making the right choices and
checks
1
For basics see Chapter 11
Foundation DHIS South
Sudan Manual
2
1. Don’t forget to check the New Records and the Updates!
2. You have four actions to make with the choices: choose carefully what
action you want to take. Think before you click!
27
Tips for selecting the correct actions
Use “remove selected” or “remove all”
• The county sends you new or updated data elements
• There are facilities that cannot be matched, has no data
Use “match new to existing”?
• There are duplicate facilities
Use “Add and Update”?
• Right at the end of the process, when you are completely
sure you have completed everything
28
When importing, what do the symbols mean?
Please REVIEW
New Record
Records
Updates
No Records
29
ADVANCED SET-UP FUNCTIONS
The session covers:
1. Over-writing the data file
NB: Please take care of when doing this and only conduct
this function if you have been instructed to.
30
Over-writing your data file e.g. if updated by MoH RSS or
SMoH
3
1
Open the DHIS
1. Switch data file
2. Refresh List
3. Select DHIS_#00.mdb
4. Select OK
4
3
31
Over-writing your data file (continued)
Open Local Disk (C:) and Dhis14
1. Rename the South Sudan file as
shown above BE CAREFUL!
2. Copy the new data file to the
Dhis14 folder
32
Over-writing your data file (continued)
• Why do we change the name of the old file?
• Why do we keep the new file name as
DHIS_#SS_SOUTH_SUDAN ?
33
UPDATING THE
ORGANISATIONAL HIERARCHY
The session covers:
1. Deleting facilities
2. Eliminating duplicates
3. Editing names of the organisational units
4. Adding a new facility
34
Select Maintenance on the Control Centre and you will
be able to see the Organisational Units Menu
To view, add or make changes to Org Units
use the OrgUnit Hierarchies function
35
1. Deleting a health facility, e.g. if no data after 2 years.
1
4
3
2
Tip:
You cannot delete a
health facility when it
has data! You have
to log on as admin
Click here to find
out how to close a
facility
1.
2.
3.
4.
Select OrgUnit Hierarchies
Find a Payam
Select a facility (do not double click)
Select Delete
36
2. Eliminate duplicates: When you have 2 facilities that
should be the same
1
3
2
4
1.
2.
3.
4.
Select OrgUnit Hierarchies
Select a Payam
Double click on a facility
New window will open, select “Eliminate Duplicate”
37
2. Eliminate duplicates (continued)
6
7
5
5. Find Duplicate facility
6. Select the facility you want to keep
7. Press the Blue Button (Remove duplicate and move data to destination
OrgUnit)
38
3. Edit names e.g. of a payam
1
4
3
2
1. Select OrgUnit Hierarchies
2. Find the name of the County (as we are editing the payam)
3. The list will appear and choose the payam
4. Click on “Edit Payam”
Steps 1-3 are the similar to “Deleting facilities”
39
3. Edit names (continued)
ForWhat
the “Name”
two aspects
there must
is theyou
state
remember
prefix when editing
names?
The Name and Short name must match!
40
4. Adding a new facility, when officially stated by the MoH
or SMoH
1
3
2
1. Select OrgUnit Hierarchies
2. Select the Payam for the new facility
3. Select “New Facility”
41
4. Adding a new facility: an empty OrgUnit window will
open for you to populate
1
1
X
2
For a new facility:
1. “Short name” and “name” must match. If facility name is the same name in
another state insert county name in ()
2. You must complete the 2 compulsory groups
X. For closing a facility, you can change the date also remember untick
“submits data” circled above
42
4. New Facilities.. don’t forget...to allocate the Org Unit
3
2
1
4
1.
2.
3.
4.
Select Data sets
Click once on the data set you want to add the facility
Click on Allocate to Org Unit
Find the facility and click. BE CAREFUL!
Tip:
Check that all
payams have been
“ticked” in your
state/county
43
5. If the facility has closed, you can close it without
deleting the data..
X
For closing a facility, you can change the
date also remember untick “Submits
data” circled above
X. To get here, as explained in previous examples:
• Select OrgUnit Hierarchies
• Select a Payam
• Double click on a facility and the above box will appear
44
PIVOT TABLES
The session covers:
1. Importance of pivot tables
2. The report filter, column fields, row fields and values
3. Creating a basic pivot table
4. Selecting a data element for analysis
5. Analysing several data elements
45
1. Why are pivot tables important?
• Pivot tables are one of the most powerful tools in
Microsoft Excel
• They allow large amounts of data to be analysed and
summarised in just a few clicks of a mouse!
46
The DHIS is made of 3 parts, the Data file captures data, the
Datamart does the hard work and the Pivot Table shows the
results
Captured Data file
DHIS_#SS_SOUTH_SUDAN.mdb
Datamart
DHIS_xSS_SOUTH_SUDAN.mdb
Pivot Table
DHIS_$SS_SOUTH_SUDAN.xls
47
2. There are four components to the pivot table
Report Filters
Column Fields
Values
Row Fields
All four components can
also be viewed here
A pivot table allows us to make a table of any of the fields available in the rows, columns
and report filters!
48
3. Creating a basic pivot table Step 1: Export to Datamart
See Chapter 13 Foundation DHIS
South Sudan Manual
Tip:
Export to Data mart
when you have
entered new data
49
3. Creating a basic pivot table Step 1: Export to Datamart
1
Tip:
Do not export from
(e.g. from 2008) as
it will take a long
time! Choose a
relevant time
period
2
3
1. Select Export to Data Mart
Do not change the Filename
2. Select the time period you would like export
3. (Optional) Include Outstanding Input Form
4. Select the export button
After it has finished, press close on the next screen
4
50
3. Creating a basic pivot table Step 2: Control + P
1
5
See Top Tips!
2
3
4
1.
2.
3.
4.
5.
Press the buttons “Ctrl” and “P” on your keyboard and the screen will change
Select Routine Raw Data OU5 and include chart
You can change the graph type
Select the year required (cutting down the file size)
Create!
51
Is this the pivot table?
1. The excel worksheet shows all the data available in a chart.. Too much
information to analyse!
52
Check which worksheet you are viewing, now you have a
pivot table!
Go to Worksheet: Routine Raw OU 5
53
4. Analysing 1 data element.. E.g. ANC
1
2
3
1.
2.
3.
4.
4
Look for “Sort Order” and select using the drop down arrow
De-select all
Select number 9, for ANC 1
Now look at the first worksheet (Routine Raw OU5 Chart)
54
5. Analysing ANC and ANC 4
See Top Tips..
1. Look for “Sort Order” and select
the drop down arrow
2. Scroll down
3. Select number 10, for ANC 4
1
2
3
4
55
You can switch the rows and columns
2
3
1
56
The screen will change to the below results!
57
Exercise (and tips)
• You would like to analyse the number of ANC 1 and ANC
4 for all facilities…
Tip
Keep to a simple set-up:
1 field in row label
1 field in column label
58
Exercise 2
• Create a chart for the consultations under 5 per county,
for 2012
• Copy the chart into a PowerPoint slide
Exercise 3
• Continue with the county level information
• Create a chart comparing ANC 1 and ANC 4 per county
59
TOP TIPS AND QUIZ ANSWERS
60
Top Tips on DHIS functions
What the symbols have in common?
All of these symbols show that
there are options to select. No
need to manually write anything!
61
Control Centre Buttons
Good practice to save reports to the reports folder
Further training materials can be found here
Always save import-export files to the transfer folder
Select Advanced Import Module
62
Organisation Hierarchy
See Pivot Tables
Country
OU 2: State
OU 3: County
OU 4: Payam
OU 5: Facility
It’s useful to know the meaning of the Organisation Units (OU) especially for
creating pivot tables!
63
Top Tip!! Taking a picture of your screen..
1.
2.
3.
4.
5.
When you want to send error message, hold the buttons
Buttons are in different places on keyboards (check!)
Open a word document
Right Click & Select “Paste”
Send the document error message as email attachment
64
Whenever you get stuck in a pivot table..
Press the buttons below on your keyboard and the last
action will be un-done!
65
Quiz Answers
Advance set up
Q:Why do we change the name of the old file?
A: So that if we make a mistake, we still have our previous data
Q:Why do we keep the new file name as DHIS_#SS_SOUTH_SUDAN?
A: The DHIS is made of a series of linked files, hence the DHIS only
recognises South Sudan information using this filename
Updating the Org Hierarchy
Q: What two aspects must you remember when editing names?
A: For the “Name” there is the state prefix
A: The Name and Short name must matc
66
So this is the end of the course…..
Notes