43 tricks to master

8/9/2019 43 tricks to master

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Research Paper & Strategic Brief

Health Information Systems

in Developing Countries

May 2009

A Landscape Analysis


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Vital Wave Consulting HIS © 2009Page 1 • Contents

Contents

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Vital Wave Consulting HIS © 2009Page 2 • Acknowledgements

[09$/9 ((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((( V)

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Acknowledgements

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In India

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In Zambia

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In Brazil

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Vital Wave Consulting HIS © 2009Page 5 • Executive Summary

Executive Summary

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Research methods

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Health Care Trends shaping national health information systems today

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‘First generation’ HIS

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‘First generation’ HIS havedemonstrated significant impactin improving patient healthoutcomes and increasing theefficiency of health systems.Improvements have beendocumented in:

! Increased follow-up rates onanti-retroviral drug campaigns

!

Sharp reduction in emergencyevacuation times and costs

! Dramatic shortening in TBdiagnose time

! Improved clinical efficiencyand laboratory revenues

Note: Citations for these studies arein main text of the re ort


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Movement toward a ‘second generation’ HIS in developing countries

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Stage 1 Stage 2 Stage 3 Stage 4 Stage 5

Peru

Kenya

Vietnam

Bangladesh

Haiti

Mozambique

Ghana

India

Indonesia

Rwanda

Ethiopia

Zambia

Sierra Leone

South Africa

Uganda

Sao Paulo

Belize

Low Income

Lower Middle Income

Upper Middle Income

China

Mexico

Ethiopia


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Case studies illustrate different approaches for different goals

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Case Study Region Income Level Scale Scope

India Asia Lower middleNational,

rural focusCore health and

disease indicators

Brazil(Sao Paulo)

Latin America Upper middleCitywide,

urbanResource allocation,

EMR-based

ZambiaSub-Saharan

AfricaLow

National,urban and rural

EMR-based

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India

Featured HIS Initiative:Health ManagementInformation System for theNational Rural Health Mission(NRHM)

Sponsors/Partners: NRHM,National Informatics Centre,

National Health SystemsResource Centre, stategovernments

Key System Attributes:Web-based system thatcollects health indicators formonitoring and evaluation ofNRHM programs

Scale: Initial focus on 18poor, rural states followed bynationwide deployment

Scope: Reproductive andchild health and infectiousdiseases, in line withMillennium DevelopmentGoals (MDGs) 4, 5, and 6

Sao Paulo, Brazil

Featured HIS Initiative:SIGA Saúde

Sponsors/Partners: SaoPaulo City Department ofHealth

Key System Attributes:

Enterprise Resource Planning-like system with electronicmedical records to manageresource allocation andpatient flow

Scale: Regional, managing20 million health encountersper year at 702 healthfacilities

Scope: Comprehensiveresource management andrecording essential healthencounter data

Zambia

Featured HIS Initiative:SmartCare Electronic HealthRecord System

Sponsors/Partners:Ministry of Health of Zambia,US President’s EmergencyPlan for AIDS Relief

(PEPFAR), US Centers forDisease Control andPrevention (CDC)

Key System Attributes:Distributed database systemproviding a portable patienthealth record to each patient

Scale: 400 health facilities,with 250,000 patientsregistered

Scope: Health records forante-natal care and HIVtreatment modules, withfamily planning, outpatient,lab, pharmacy and under age5 modules added in 2009

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Looking forward

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Next Steps:

! Drive consensus adoption of a minimum set of essential indicators

! Determine the common, essential information needs across countries

Additional Recommendations:

! Enhance HIS success rates by supporting initiatives that have high-levelsponsorship and occur in the context of wider health-system reform

! Support in setting clear priorities for reform

! Define HIS needs and goals

! Streamline data collection

! Develop HIS to support user decision-making

!

Plan for project operations and maintenance at project outset

! Invest in adapted technology

! Develop commercial markets

! Increase project accountability by changing the structure of provider contracts

! Invest in increasing the attractiveness of the HIS technology and services market


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Vital Wave Consulting HIS © 2009Page 11 • Introduction

Introduction

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A multi-faceted research approachwas used to create this report,starting with a comprehensivereview of secondary literature onHIS and health-related ITinitiatives in developing countries,followed by extensive interviewswith experts in the healthinformatics field and rounded outwith in-country research – inthree extremely diversedeveloping countries: India,Brazil and Zambia.


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Research Methods

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Case Study Region Income Level Scale Scope

India Asia Lower middleNational,

rural focusCore health and

disease indicators

Brazil(Sao Paulo)

Latin America Upper middleCitywide,

urbanResource allocation,

EMR-based

ZambiaSub-Saharan

AfricaLow

National,urban and rural

EMR-based

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Vital Wave Consulting HIS © 2009Page 15 • Landscape Overview

Landscape Overview

Decentralization and the Importance of Health InformationSystems

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Picture 1: The dozen-plus registries that nurse midwives in India maintain


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Impact of ‘first generation’ HIS on patient

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The need for a new concept of HIS

B?& D:#16'& 9$/ %?& '?#:%+#16$0' #H +5::&$% ';'%&1' :96'& %?& Y5&'%6#$ #H -?9% 9 '5++&''H5. I=8160?% .##, .6,&( ^?6.& %?&:& 9:& 9 $51T&: #H 79:69%6#$'a %?&:& 6' 9 +.&9: D9%%&:$ %# 19$; #H %?&'&+#$+&D%6#$'a 6..5'%:9%&/ 6$ %?& H#..#-6$0 /690:91(

First generation HIS havedemonstrated significant impactin improving patient healthoutcomes and increasing theefficiency of health systems.Improvements have beendocumented in:

! Increased follow-up rates onanti-retroviral drug campaigns

!

Sharp reduction in emergencyevacuation times and costs

! Dramatic shortening in TBdiagnose time

! Improved clinical efficiencyand laboratory revenues

The same first generation HIS

systems also share a number ofcommon traits or constraints:

! Anchored in the public sector

! Significant fragmentation andduplication in data collection

! Not generally used by thoseproviding or managing healthservices at the local level

! Data collection is a significantburden on those collecting the

data

!

Independent systems areseldom integrated


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Figure 2 – Typical Vision of HIS

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Population

PopulationSurvey

Vital

Registration

HealthInsuranceRecords

FacilityServiceRecords

Supply ChainInventory

Data

DataRepository

Hospitals &Clinics

NationalHealth

Insurance

MOH

NationalProgramDirector

DistrictHealthOfficer

FacilityManager

DonorProgramOfficer

PublicHealth

Researcher

Analysis &Reports


24/120


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Movement Toward a National HIS in Developing Countries

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D a t a F l o w

a n

d C o l l e c t i o n

Stage 1 Stage 2 Stage 3 Stage 4 Stage 5

! Data collection isbased on manualtallies from activityregisters

! Multiple redundantforms

!

Data collection isexternal to routineoperations, timeconsuming

! Data collection isbased on manualtallies from activityregisters

! Focus on using existingsystems to collect an

optimized and smallerset of data with a viewto increasing dataquality, relevance.

! Collection burdenreduced, more rapidavailability possible

! Data collection isbased on manual talliesfrom activity registers

! District data collectionconverted to electronicstorage and reporting

!

No change to basicprocess of compiledreports passed upinstitutional chain.

! Data captured incourse of routinetransactions ratherthan collected. Nomanual tabulationfrom registers. Heavyreliance on electronic

data storage (somepaper-based datacollection may remain)

!

Operational systems(e.g., patientscheduling, labmanagement,pharmaceuticalmodules) as datasource

! Data capturedelectronically fromroutine business ops(clinical andadministrative)

!

Integration of data

from multipleinformation systems atall levels of healthsystem

! Data collectionprovides decisionsupport for clinicians

D a t a U t i l i z a t i o n a n d I n t e g r a t i o n

!

Disorganized andineffective districtreporting

! Data quality poor, longdelays in reporting

!

No integration ofseparate informationsystems

! Peer data from otherfacilities orgeographies rarelyavailable

!

District data collectionnormalized, simplified

!

More rapid dataavailability

! Improved management

decisions possible withquality data

! No integration withother informationsystems

!

Formal electroniccommunication,storage andautomated reporting ofcollected data

! Increased analytics

! Aggregated data nottied to individualelectronic medicalrecords

!

Data from otherfacilities andgeographies can beobtained for peercomparison

!

Enabled individual IDs,EMR, appointment,scheduling andreminders, facilityoperations capabilities(lab, pharmacy, etc.)

!

Systematic businessprocess analysisrequired

!

Access to informationfrom all levels ofservice deliverynetwork possible andencouraged

! Public health data notintegrated

! Complex reporting

!

Full Personal HealthRecord for allindividuals

! Complex reporting

! Evidence-based

decision making anddata-drivenmanagement

! Integrates allsignificant health-related data from allcomponent systems

!

Explicit nationalpolicies on datastandards andinteroperability

R e s o u r c e s a n d C a p a c i t y

!

Little or no computerliteracy at local level

!

Capacity for data

analysis limited,confined to centralMoH

!

Little or no computerliteracy at local level

!

Basic capacity for data

analysis at local levels

!

M&E capacity atcentral level

!

Limited computerliteracy required fordata entry at locallevel

! Increased analyticalcapabilities

!

Moderate to significantcomputer literacyrequired for largernumber of users

! Substantial technicalskills required onongoing basis

! Often local push fornational adoption, butno sustained nationalcommitment or funding

!

Managers at all levelsstrongly inclined tousing data to supportdecision making

! Strong culture of data-driven management

! Strong consistentleadership andsupport. Nationalcommitment toongoing funding

S c o p e

Scope: Modest -captures only districtindicators

Same as Stage 1 Same as Stage 1 Greatly expanded withinclusion of patient-level data from healthsystem transactions(EMR), and resourcedata (personnel,medical supplies)

Maximized, with Stage4 data integrated withpublic health data

S c a l e

Can be country-widedepending oncompliance and follow-through (which is oftenspotty)

Same as Stage 1 Projects often beginwith one or twodistricts, but aim fornationwide deployment

Sub-national becauseof increased resourceand capabilityrequirements

National, entirepopulation included

Table 1 - National HIS Efforts in Developing Countries


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29/120


Cross-cutting ‘Second Generation’ Trends

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