M d li  R f l N t k  Modeling Referral Networks to Avert Maternal Death in Ethiopia

Caleb ParkerGIS AnalystBehavioral and Social SciencesFHI

Presentation Overview

• Referral backgroundReferral background• Setting: Ethiopia• Network AnalysisNetwork Analysis

– Objectives, data and methods– Defining referral networksDefining referral networks– Model building and preliminary results

• Next steps in EthiopiaNext steps in Ethiopia

REFERRAL BACKGROUND

What and why referral?

• Defined: upward movement in the seeking of care within p gthe health system.– Emergency Referral

f l i k i h fi ld f l d b• Referral is key in the field of maternal and newborn health– “under‐documented, under‐researched and under‐o , u de e e c ed d u de

theorized.”

• Referral utilizes current resources through linkages in a tsystem

– Cheaper– Short to medium‐term solutions

Time between the beginning of a complication and death

Complication Hours DaysH h  Hemorrhage 

Postpartum  2

Antepartum 12

Ruptured uterus 1

Eclampsia 2

Obstructed labor 3Infection 6

The 3 Delays Model3 y

Referral has the potential to reduce all 3 delays

DELAY #1 DELAY #2 DELAY #3Recei ing

Referral has the potential to reduce all 3 delays

Deciding to seek care

Reaching a facility

Receiving adequate

care

Onset of Recovery or deathComplication

Pyramidal structure & bypassing

Regional Hospital Receiver

District Hospital

Transport

Health center/post

p

/dispensary

Sender

Adapted from Jahn & De Brouwere, 2001Community

Requisites of a functioning referral systemq gCommunication

F ti iTransport

Functioning referral center

Protocols for senders &receiversreceivers

S M SF P SC M t it f l t i d l i t i C t k l d d f t hSource: Murray SF, Pearson SC. Maternity referral systems in developing countries: Current knowledge and future research needs. Soc Sci & Med 62, 2006.

SETTING: ETHIOPIASETTING: ETHIOPIA

Setting: Ethiopia

• Population: 73 millionp 73

• Area: 1.1 million km2

Twice the size of Texas– Twice the size of Texas

Regions of Ethiopia

hAmhara

Tigray and Amhara – Key Indicators

Tigray Amhara NationalTigray Amhara  National

Population (2007 Census) 4,400,000 17,200,000 73,900,000

Number of hospitals 14 18 112Number of hospitals  14 18 112

Percent minimum recommended (CEmOC) 55% 18% 39%

Institutional delivery rate 9% 5% 7%Institutional delivery rate  9% 5% 7%

Cesarean delivery rate 0.7% 0.2% 0.6%

Percent of health centers with desired staffing 45% 2% naPercent of health centers with desired staffing 45% 2% na

OVERVIEW OF DATA AND OVERVIEW OF DATA AND METHODS

Background for this activity

• Ethiopia Needs Assessment for EmONC conductedp

– 797 Healthcare facilities

Geocoded– Geocoded

• Staff saw potential GIS use

• Emergency Referral Network Analysis

– Strengthening referral systems could save lives in short and medium term, even as longer term strategies are implemented 

Objectives:

1. Model current referral system y

2. Identify facilities 2+ hours from closest receiving facility

3. Model short and medium term solutions to reduce travel time

Data

1. Ethiopia EmONC Assessmentp2. Population Data – 2007 Census projected to 20083. Digital Elevation Model3 g4. Road Network Data

Ethiopia Elevation

Ethiopia Road Network

Road Network Discrepancies

Road Network Discrepancies

Methods

1 Define Sender and Referral Facilities1. Define Sender and Referral Facilities

2. Model Current Referral Network

3. Model Referral Scenarios

B ild f ilit   t h t   – Build facility catchment areas 

Defining facilities

• Tier A (Receivers)– conducted cesarean delivery in 3 months prior to the assessment

• Tier B (Senders)– all other facilities

• Identified referral networks based on • Identified referral networks based on shortest travel time to a Tier A facility

Model Current Referral Network

Key Variable: Travel Timel l d di l i f h iCalculated direct travel time for each Tier B 

facility based on:Di t     d  t kDistance on road networkRoad surfaceSeason

Calculated adjusted travel time based on:Motorized transportation available on siteCommunication (if no transportation)

Key Variable – Travel Time

Factors Tier B Facility #1 Tier B Facility #2Factors Tier B Facility #1 Tier B Facility #2Direct travel time (min) to closest Tier A

48  118

‐ Road Surface (in GIS) (in GIS)

‐ Season Dry Dry

Transportation on site No (48x2=96) Yes (118x1=118)Communication No (96+30=126) N/AAdj t d t l ti   6 8Adjusted travel time (min)

126 118

Percentage of facilities within 60 and 120 minutes to closest Tier A facilityminutes to closest Tier A facility

C l i i Cl CCumulative Minutes to Closest Tier A Facility

Count Percentage

Under 60 77 35.8%Under 60 77 35.8%61 to 120 64 29.8%More than 120 74 34.4%3

Model building

• Build Catchment AreasM d l 0  St t  Q• Model 0: Status Quo

• Model 1: All facilities have motorized transportation  and communicationand communication

• Model 2: Upgrading strategic Tier B facilities to Tier A facilitiesfacilities

• Model 3: Improved road surfaces• Optimal model: what is the best outcome with the • Optimal model: what is the best outcome with the 

lowest input (additional phones/vehicles)

Creating Catchment Areas

• An area that “should” be served by a facilityAn area that  should  be served by a facility• Cost Distance Raster in ArcGIS

– SlopeSlope– Rivers/terrain

• Once created, calculated populationOnce created, calculated population

Facility Catchment Areas with Road Network

Referral Networks with Facility Catchment Areas

Referral Networks

Population Density by Catchment Area

Population Density (sq km)

Model building

• Build Catchment Areas• Model 0: Status Quo• Model 1: All facilities have motorized transportation 

and communication• Model 2: Upgrading strategic Tier B facilities to Tier A 

facilities

M d l 0 STATUS QUO

Facility Catchment Areas Beyond 2-hour Travel Time

Model 0: STATUS QUO Total Population   

Population  Currentlywith Access

10,019,395 5,626,099 56.2%

Model building

• Build Catchment AreasBuild Catchment Areas• Model 0: Status Quo• Model 1: All facilities have motorized transportation Model 1: All facilities have motorized transportation 

/communication• Model 2: Upgrading strategic Tier B facilities to Tier A Model 2: Upgrading strategic Tier B facilities to Tier A 

facilities

M d l 0 STATUS QUO

Facility Catchment Areas Beyond 2-hour Travel Time

Model 0: STATUS QUO Total Population   

Population  Currentlywith Access

10,019,395 5,626,099 56.2%

Facility Catchment Areas Beyond 2-hour Travel Time

Model 1: Increase in population served by ensuring that every Tier B facility has a motorized vehicle 

Total  Population Currently  Population with  Overall Increase in Referral Network Population with Access* Access in Model 1 Population Access

1412 – Pawe 1,338,664  646,721  48.3% 646,721  48.3% ‐ 0.0%

1505 – Debre Tabor 2 723 313 2 182 465 80 1% 2 447 996 89 9% 265 531 9 8%1505  Debre Tabor  2,723,313  2,182,465  80.1% 2,447,996  89.9% 265,531  9.8%

1543 – Felege Hiwot 2,156,109  1,151,324  53.4% 1,994,981  92.5% 843,657  39.1%

1623 – Debre Markos 3,801,309  1,645,589  43.3% 2,660,041  70.0% 1,014,452  26.7%

TOTAL 10,019,395 5,626,099 56.2% 7,749,739 77.3% +2,123,640  21.2%

*Only for persons at the Tier B facility

Facility institutional delivery rates

Institutional delivery rate

M d l 0 STATUS QUO

Facility Catchment Areas Beyond 2-hour Travel Time

Model 0: STATUS QUO

Facility Catchment Areas Beyond 2-hour Travel Time

Model 2: Increase in population served by upgrading Fenote Selam District Hospital to a Tier A 

Total Tier B Facilities in New Tier A 

Referral Network

Total Population in New Referral Network 

Population with Access to their Current Tier A

Population with Access to New Tier A

Overall Increase in Population with 

Access

16 1 945 023 293 895 15 1% 781 640 40 2% 487 745 25 1%16 1,945,023  293,895  15.1% 781,640  40.2% +487,745  25.1%

Next Steps in Ethiopia

Further modelingg• Combinations of models (ex. Motorized vehicles plus upgrading)• Improved road surfaces• Optimal model: what is the best outcome with the lowest input • Optimal model: what is the best outcome with the lowest input 

(additional phones/vehicles)• Costing

Federal MoHWorking Group on Referral• Site selection for new ambulancesSite selection for new ambulances• Testing new management models• Transfer of methods and validation of assumptions