Improving the Quality of Health Data and
Weekly Surveillance Reporting Rates in
Mityana District
By Dr.Lwasampijja Fred
District Health Officer
Mityana District Local Government
ACADEMIC MENTOR:
John Kissa (Ministry of Health)
INSTITUTIONAL MENTOR:
Nkata B. James
(Mityana District Local Government)
Grand Dissemination. Golf Course Hotel Kampala, 14/07/2016
July 2016
1
Presentation outline
• Introduction and background
• Problem statement
• Project objectives
• Project implementation & Results
• Challenges experienced and how they were overcome
• Conclusion & Way forward
• Acknowledgement
2
Introduction and background
• Mityana district is located in the central region 74kms West
of Kampala and has 59 health facilities
• HMIS is one of the core functions of the district and serves
as a source of health information
• Health information is used for planning and management of
services hence a need to be credible
• During extraction of data from the registers to reporting tools
errors and omissions occur which affect data quality
Problem identification
• The DHT reviewed a report on the district capacity
assessment survey done by CDC/MOH/MakSPH in 2014
• Among the 8 domains assessed: HMIS, Service delivery,
Human resources and supply chain were performing poorly
and needed urgent attention
• DHT scored on the urgency, feasibility and effect of the above
gaps on service delivery and came up with HMIS
• During brainstorming on HMIS, the issue of poor quality data
and low rates of weekly reporting were considered to be
critical. Hence the project.
4
Baseline Situation
Parameter HMIS Tool Baseline
Completeness
(Financial summary)
105 (Outpatient) 42%
Accuracy
(New clients started on
ART)
106a (HIV/ART
Quarterly)
52.3%
Timeliness 108 (Inpatient) 87%
Health facility Weekly
reporting rate
033b (Weekly
surveillance)
57.3%
5
**Source: July-Sept 2015 District HMIS Report
Root cause analysis
The DHT used a fish bone analysis and identified
the following:
• Health workers not oriented on issues of quality data and
use of data for decisions
• Health workers do not prioritize tools during procurement
planning and ordering
• DHT do not prioritize review and feedback meetings
• DHT do not prioritize supervision and DQA
6
Problem Statement
• Health data collected and reported in Mityana district was of poor quality;
• 58% of HMIS 105 reports were incomplete-Financial
summary section
• 48% inaccuracy in reporting for the selected ART indicator
from 106a was noted.
• 43% Health facilities were not submitting weekly reports as
required.
All the above are below the national standard of 80%
• Timeliness for HMIS 108 of 87% is also below the standard
of 100%
7
Problem Statement...
Identified causes
• Low knowledge and skills
• Attitude of health staffs
• Inadequate support supervision
• Limited financial resources for M&E related activities
Addressing the above would strengthen systems
for generating quality data
8
Objectives
Overall
Objective
To improve the quality of health data generated
and rates of weekly surveillance reported from
the health facilities in Mityana district by June,
2016.
Objective 1 To improve completeness of HMIS 105 reporting
from 42% to 80%
Objective 2 To improve the accuracy of HMIS 106a reporting
from 52.3% to 80%
Objective 3 To improve timely submission of HMIS 108 from
87% to 100%
Objective 4 To improve health facility weekly surveillance
reporting rates from 57.3% to 65% in 22 health
facilities
9
Project Implementation
Activities undertaken
Oriented 158 health staff on the values and dimensions of quality
data, extraction and reporting
Developed data improvement plans
Conducted support supervision and on-job mentorship
Carried out data validation at the health facilities
Conducted monthly and quarterly review and feedback meetings
Supported In-charges and records assistants to develop SOPs for
submission of reports
10
Project Implementation
Activities undertaken…
Provided internet data on 4 modems to ease entry of data and
timely submission
Registered 35 alternative phone numbers (for 22 facilities)
Established a system of reminding the contact persons at facilities
to submit the reports
Used the monitoring tool to track the performance of facilities
regarding submission of reports and recognizing good performers
at joint meetings
11
12
Workshops were conducted to build the
capacity of health staff to use their own
data for management & monitoring health
service delivery indicators
Health workers were engaged in
developing standards procedures for
information flow
Relevance for consistent collection and
documentation of good quality data for
decisions was emphasized
Orientation of the health workers in data use and management
Health workers were making data improvement plans
Health workers draw data flow charts as part of SOPs
Results: Completeness of data from high volume
facilities Oct 2015 to May 2016
0
20
40
60
80
100
120
Oct Nov Dec Jan Feb March April May
Mityana Hospital
Kyantungo HCIV
Ssekanyonyi HCIV
Mwera HCIV
Bulera HCIII
13
%
Reporting
Intervention point
Results: Accuracy of data on new clients started
on ART
14
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
MityanaHospital
SsekanyonyiHC IV
Kyantungo HCIV
Mwera HC IV Bulera HC III
Oct-Dec 2015 Accuracy 90% 100% 100% 100% 93%
Jan-Mar 2016 Accuracy 96% 100% 100% 97% 50%
April- June 2016 Accuracy 100% 100% 100.0% 100.0% 100.0%
Ne
w c
lie
nts
sta
rte
d o
n A
RT
Results: Timely Submission of Inpatient reports
(HMIS 108) in 9 facilities
15
33.3
62.9
66.7
96.3
0
20
40
60
80
100
120
% t
ime
lin
es
Intervention facilities
July - Sept 2015
Jan-Mar 2016
Results: Average reporting for the each sub-
counties before and after interventions
16
0102030405060708090
100
Bbanda
Su
b C
ounty
Bule
ra S
ub
county
Busi
mbi S
ubcounty
Buta
yunja
Subcounty
Kaki
ndu S
ubcounty
Kala
ngaalo
Sub
county
Kik
andw
a S
ubco
un
ty
Maa
nyi
Subcounty
Mala
ngala
Subco
unty
Mitya
na T
ow
n C
ouncil
Nam
ungo
Su
b C
ounty
Sse
kanyo
nyi
Subcounty
48
31
53 62
79
53
72
51
71
33
100
69 73
46
70 71
88
62
86
57
86
54
100
88
Av
era
ge
Re
po
rtin
g R
ate
average surveillance reporting by sub-county Before and After
Average Reporting Before Intervention Average Reporting After Intervention
Before period: 2015w1-2016w3 After period: 2016w4-2016w25
Results: Trend in district reporting rates over the
weeks in 2015 and 2016
17
33.9
45.8
25.4
62.7
57.6
66.1 69.5
83.1 83.1
20
30
40
50
60
70
80
90
100
201
5W
1
201
5W
3
201
5W
5
201
5W
7
201
5W
9
2015…
2015…
2015…
2015…
2015…
2015…
2015…
2015…
2015…
2015…
2015…
2015…
2015…
2015…
2015…
2015…
2015…
2015…
2015…
2015…
2015…
201
6W
1
201
6W
3
201
6W
5
201
6W
7
201
6W
9
2016…
2016…
2016…
2016…
2016…
2016…
2016…
2016…
Re
po
rtin
g R
ate
Mityana: Weekly Surveillance Reporting Rate for 2015w1 to 2016w25
Intervention
point
80%- Minimum Standard
Lessons Learnt
• Having more than one person registered for mTrac at the
facility strengthens team work and reporting.
• Presence of data improvement plans at the health facilities
encourages health workers to improve their recording,
compilation of reports and data use.
• Presence of the Standard Operating Procedure guides the
right flow of data from the facilities
• Review and feedback on performance encourages reporting
• DQA helps health workers to appreciate their weaknesses
18
Challenges and solutions
Challenges Solutions
Lack of funds to support
data management
Inclusion of data activities in Work
plans for funding
High attrition of staff in
private facilities
Support supervision and mentorship
Inadequacy of new updated
HMIS tools in some
facilities
Work with Mildmay and NMS for
provision and in charges to place
orders
Lack of teamwork at
facilities
Orientation, mentorship, supervision
and collective responsibility towards
reporting.
19
Conclusions
• Completeness of 105, accuracy of 106b and timeliness of
108 improved from 42% to 100%, 52.7 to 80% and 87%
to 100% respectively
• Generation of quality health data entails having skilled
and competent health staff who know the importance of
data
• Inclusion of HMIS activities in work plan is key for
collection and submission of quality data
20
Next steps
• Routine support supervision and mentorship
• New staff will be oriented and mentored on HMIS tools and
reporting
• Liaise with Implementing Partners to support DQA, support
supervision, mentorships and supply of tools
• Inclusion of HMIS activities in work plans at district and
facilities
• HMIS reporting to be an assessable area for annual
performance for in-charges and records assistants
21
Recommendations
• Inclusion of data management activities in work plans at
district and facilities
• Sustainable provision of new updated registers and other
HMIS tools
• Regular supervision, mentorship and data quality
assessment
22
Acknowledgement
• CDC
• Ministry of Health
• Makerere University School of Public Health
• Academic and Institutional Mentors
• Fellows in the programme
• Mityana District Leadership
• Implementing Partners
• District Health Team
• The health workers
23