Performance improvement in Ethiopia through use of aggregate data Tsigereda Gadisa MD,MPH M&E Director, ICAP-Ethiopia July, 2010.

Performance improvement in Ethiopia through use of

aggregate data

Tsigereda Gadisa MD,MPH M&E Director, ICAP-Ethiopia

July, 2010

Progress of Site level data use Supported ICAP-Ethiopia

September 2005 – June 2010

Management commitment Key to Build Results Oriented

Culture• Use Data routinely; Started slow; non-judgmental way• Leadership committed for program improvement;

through data use• Involved all concerned; support the team to arrange

mentoring and ask input from all

• Stimulate positive action and encourage innovation

• Take responsibility; no blaming; focus on what can done

• Encourage learning; review & learn from success & failure

• Reward and reinforce; use rewards & recognition timely

M&E Status ICAP-E Supported Sites September 2005– Number of Facilities Providing Services were 6

(1st and second cohort Hospitals)

– Number of patients under care 12652 (1202 when we start)

– Patient information capturing was performed using unstructured plain hospital cards

– Patients are registered (if they are) using plain unstructured logbooks

– National standard forms were under development

– No M&E Training

Data use Started slowly

Early Phase Data use Activities; Helping the M&E System to

Keck off – Printing and Distribution of M&E form– Recruitment of data clerks- Training of care providers and data clerks on M&E

forms

- Furnishing the record room- Improving paper based record keeping- Cleaning of back log data - Transcription of Cards intake and follow up register report

NB :Data was primarily compiled for reporting purpose : M&E was every body's’ job and there was one M&E advisor

Improving Paper Based Medical RecordsEg Hiwot Fana Hospital

Assisted sites to move from unstructured to structured data capturing

Improving Paper Based Medical Record Keeping

Data u

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ervice & P

rog

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oin

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& E

, Tr

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M & E, Data use and data analysis Training and Mentorship, DQA & Feedback

M&E STAFFING: 2005 01 June 2010 = 13

Addis officeM&E Director

4 M&E Officers2 DB Managers

1 Program Evaluation Officer

Eastern 2Regional M&E Officers

(40 facilities)

South-West1Regional M&E Officer

(11 facilities)

Southern1Regional M&E Officer

(09 facilities)

Dil Chora H.Hiwot Fana H.Bisidimo H.

Chiro H.Karamara H.

Misrak. Arb. H.

AiraGimbi

Jimma H.Nekempt H.Metu Karl H.

Dembi Dolo H.

AbomsaAssela H.Goba H.

HageremariamNegelle H.

Shashemene H.

Central 1 Regional M&E Officer

(9 facilities)

Adama H.Ambo H.

Bishoftu H.Fitche H.

Wonji

Current ICAP-E M & E Activity & Support Level

Regional Support• Development of analysis template for achievement assessment• Compilation of data to be used for regional planning• Development & Role out of Patient level database

Site Level Support 65 (43 hospital & 22 HC• Over 87,500 Patients Capability Building/TA• Training & mentorship• Strengthen documentation• Site level data use• Renovate furnish, & equip data room

Internal M&E support Compile and submit Funder report Compile and share data regularly Plot performance graph in key areas & share Developed & Implemented database to organize report, training , SOCS and CSSCL information

Site Census: service provided and site GIS coordinated & is currently used as an input for goggle map of URS-NY in site map preparation

Current ICAP–E Site level data use Supports

• Training & Mentoring of providers and data clerks on nationally standardized M&E Tools

• Development data analysis and data use providers support tools

• Training and mentoring of clinical care providers and program managers on Data Analysis and Data use

• Conducting Regular data quality check; immediate feed back & follow up DQA issues identified

Capacity Building: Human Resources (Training and Mentoring)

Target achievement self Assessment form

Mes-01 Tik-01 Hidar-01 Tah-01 Tire-01 Yek-01 Meg-01 Miaz-01 Gin-01 Sene-01 Hamle-01 Nehase-01

PRE-ART Target 110 220 330 440 550 660 770 880 990 1100 1205 1310

PRE-ART Ach 105 220 311 407 500 593 697 769 869 956 1047 1161

ART Target 37 74 111 148 185 222 259 296 333 370 421 472

ART Ach 154 351 489 635 738 881 1081 1235 1392 1538 1630 1732

100

300

500

700

900

1100

1300

1500

1700

1900

110

220

330

440

550

660

770

880

990

1100

1205

1310

105

220311

407500

593

697769

869956

1047

1161

37 74 111 148 185 222 259 296 333 370421

472

154

351

489

635

738

881

1081

1235

1392

15381630

1732

Bishoftu Hospital Target Achievement in Care and RX between Meskem-01- Nehase-01

Quarters

# o

f p

ers

on

s

Follow up card completeness trends,

ART clinic Bishoftu Hospital; 2009-2010

Follow

up

date

Weig

ht

Pregn

ancy

Funct

ional

stat

us

WHO s

tage

TB scr

eenin

gOIs

Cotrim

oxaz

ole

ARV dru

g

Next v

isit d

ate

0%

20%

40%

60%

80%

100%

120%

100%

95%

60%

95%

100% 100% 100%

74%

90%

100%100% 100% 100% 100%

95%

100% 100%

93%

100% 100%

Bishoftu Hospital Feb -09

Bishoftu Hospital Apr-10

Key follow up variables

Per

cen

tag

e o

f co

mp

letn

ess

Regional Level Data Use

• Supported the development & rollout of Facility based ART Monitoring SystemBased on the two basic data capturing forms (intake

& follow up form)

Easy data processing and report compilation

Facilitate defaulter tracing

Facilitate continuous service and data quality improvement through data use

Regional Level Data Use-2 Developed a Regional Data Analysis template (Target

achievement self assessment form )

Training of regional HIV coordinators and data managers on data analysis and data use

Supported the development and implementation of Patient level database

Support in data aggregation for evidence based actionFacilitate timely feed back during supervisors Evidence based planningAcknowledging best performing sites

Facility Based ART Monitoring System

Examples of data Analysis Job Aid

Evidence Based Regional Review & Planning Meeting

Evidence Based Recognition of Best Performing Sites

ICAP –Ethiopia Internal data use for CQI

Developed & Implemented database to timely organize the different aggregate data,

- DSS, TrainSoft, SOCS and CSSCL Databases– DSS: Organize service delivery performance aggregate data; produce

report and graph

– TrainSoft: Organize training data by all technical areas

– SOCS: Organize data from SOC exercise & facilitate immediate feedback and see trends in the SOC indicators

– CSSCL: Organize data from CSSCL exercise & facilitate immediate feedback and see trends in the SOC indicators

ICAP –Ethiopia Internal data use for CQI

Selected and developed key performance indicators with the clinical units

Regularly analyze aggregate data and prepare graph on the key indicators for performance review meeting

Regularly meet to review performance design actions

Share results and action points with clinical unit & RO to guide mentorship

Decision Support System (DSS)

TrainSoft

Standard of Care Database (SOC

DB)

 Comprehensive Check List database

(CSCLBD)

TB Screening among newly enrolled in care, Ginbot,01 (May-09) and Ginbot,02 (May-10)

Central East South SW all ICAP0

200

400

600

800

1,000

1,200

1,400

1,600

1,800

596

327367

294

1,584

535(90%)

288(88%) 306 (83%)247 (84%)

1376 (87%)

380

263 289

208

1,140

346(91%)252 (96%) 279(97%)

195(94%)

1,072 (94%)

Newly Enrolled Ginbot,01 Screened for TB Ginbot,01 Newly Enrolled Ginbot,02 Screened for TB Ginbot,02

ICAP Centeral East South SW0

1000

2000

3000

4000

5000

6000

7000

8000

5885

1380 12511042

2212

4708(80%)

1200(87%) 900(72%)802(77%)

1858(84%)

7129

1238

2097

1067

2727

5988(84%)

1102 (89%)

1598 (76%)

939(88%)

2349(86%)

MIPD Unknown status Tir 2001 MIPD tested Tir 2001 MIPD Unknown status Tir 2002 MIPD tested Tir 2002

Medical IPD testingPerformance , Ginbot,01

(May-09) and Ginbot,02 (May-10)

Transition from SdNVP to multiple ARV prophylaxis:

April-07- March-10 ; All ICAP supported sites

April June July- Sept-07

Oct- Dece-07

Jan- March-08

April June-08

July- Sept-08

Oct- Dece-08

Jan- March-09

April-June-09

July- Sept-09

Oct- Dece-09

Jan- March-10

0%

20%

40%

60%

80%

100%

120%

100% 100%

81%

22%

15%

4% 3% 2% 2% 0% 1% 0%

0% 0%

19%

78%

85%

96% 97% 98% 98% 100% 99% 100%

sdNVP% NVP+AZT+3TC%

Comparison of site Pediatrics IPD PICHT performing 3rd and 4th quarter; COP 09

Remark: 8 sites reported 75- 94% PIPD testing rate;

1CRO,1 ERO, 4 SRO & 2 SW sites.

RO Name of facility

% Tested 3rd Q

% Tested 4th Q

Possible reason

Recommendation

CRO Adama 454/621 (73%)

457/490 (93%)

ERO Hiwot Fana 202/202 (98%)

147/197 (91%)

SRO

Abomsa 39/60 (65%) 48/57(84%)

Goba 153/176 (87%)

112/119(94%)

Bullehura 211/232 (91%)

149/198(75%)

Negelle 129/145 (89%)

72/93(77%)

SW Gimbi 120/133 (90%)

208/252(83%)

Jimma 497/507(98%) 265/297(89%)

Lesson learned

• Training of site & RHB staffs on data analysis and use provided opportunity to look at the data , beyond individual patient care in terms of

Service quality (linkage, prophylaxis), Treatment outcome (lost, death, on treatment cure rate) Target setting & target achievement monitoring

• Site staff will be more concerned for the quality of data when they know how to analyze, interpreted and use

• Training, Mentoring and regular DQA with feedback, coupled with data analysis and interpretation enhance data quality and data use

Challenges

• Building result oriented culture on fragile system

• Overburdened & de-motivated site staffs vs huge demand on complete documentation and use of data remained an overarching challenge?

Next Steps

– Especial focus will be made to support the rollout of HMIS and smooth Integration of HIV information

– Support DQA with the new HMIS tools and HMIS and NGI indicators,

– Enhance the use of data collected though HMIS for CQI at a point of generation

Thank You

ICAP-E Family May 2009