Improving the Quality of Health Data and Weekly Surveillance Reporting Rates in Mityana District

Transcription

1 1 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

2 2 Presentation outline Introduction and background Problem statement Project objectives Project implementation & Results Challenges experienced and how they were overcome Conclusion & Way forward Acknowledgement

3 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

4 Problem identification The DHT reviewed a report on the district capacity assessment survey done by CDC/MOH/MakSPH in 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.

5 5 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% **Source: July-Sept 2015 District HMIS Report

6 6 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

7 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

8 8 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

9 Objectives 9 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, 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

10 Project Implementation 10 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

11 11 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

12 12 Orientation of the health workers in data use and management Health workers draw data flow charts as part of SOPs Health workers were making data improvement plans 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

13 Results: Completeness of data from high volume facilities Oct 2015 to May Intervention point 80 % Mityana Hospital Kyantungo HCIV Ssekanyonyi HCIV Mwera HCIV Bulera HCIII 20 0 Oct Nov Dec Jan Feb March April May Reporting

14 New clients started on ART Results: Accuracy of data on new clients started on ART % 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Mityana Ssekanyonyi Kyantungo HC Mwera HC IV Bulera HC III Hospital HC IV IV 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%

15 % timelines Results: Timely Submission of Inpatient reports (HMIS 108) in 9 facilities July - Sept 2015 Jan-Mar Intervention facilities

16 Bbanda Sub County Bulera Subcounty Busimbi Subcounty Butayunja Subcounty Kakindu Subcounty Kalangaalo Subcounty Kikandwa Subcounty Maanyi Subcounty Malangala Subcounty Mityana Town Council Namungo Sub County Ssekanyonyi Subcounty Average Reporting Rate Results: Average reporting for the each subcounties before and after interventions 16 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

17 2015W1 2015W3 2015W5 2015W7 2015W9 2016W1 2016W3 2016W5 2016W7 2016W Reporting Rate Results: Trend in district reporting rates over the weeks in 2015 and Mityana: Weekly Surveillance Reporting Rate for 2015w1 to 2016w Intervention point 80 80%- Minimum Standard

18 18 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

19 19 Challenges and solutions Challenges Lack of funds to support data management High attrition of staff in private facilities Inadequacy of new updated HMIS tools in some facilities Lack of teamwork at facilities Solutions Inclusion of data activities in Work plans for funding Support supervision and mentorship Work with Mildmay and NMS for provision and in charges to place orders Orientation, mentorship, supervision and collective responsibility towards reporting.

20 20 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

21 21 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

22 22 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

23 23 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