HEALTH MANAGEMENT

INFORMATION SYSTEMS (HMIS)

By
Dr. J. O. S. Osero
Department of community health
Kenyatta University
 Objectives
Learner should be able to:
 Define the concepts of HMIS
 Describe the role and function of HMIS in the context of
health system strengthening
 Discuss the contribution of HMIS policies and legal
frameworks in systems strengthening
 Discuss the role of HMIS in knowledge management in the
context of health systems strengthening
 Describe the process of evaluating and improving HMIS
 Describe the role of ICT in HMIS strengthening
Definition of information systems
 Set of information elements or components that
 collect (input)
 manipulate (process)
 disseminate (output) data and information
 store (save) data for future reference; and
 provide a feedback mechanism to meet an organisational objective
and mandate
Definition of information systems…
 Inputs
 The capture or collection of raw data from within the
organisation or from its external environment for processing in
an information system

 Outputs
 Useful information, usually in the form of documents and/or
reports
 Feedback
 Output that is used to make changes to input or processing
activities
 Definitions: data and information
 Data: data are input raw materials from which information is
produced. These are facts obtained by reading, observation,
counting, measuring, weighing, which are then recorded

 Data Sources: health facilities, community, other government

agencies (e.g. Registration of births and deaths, National Bureaus
of Statistics)

 Information: data that have been analysed, interpreted, presented

and understood by the recipient of the communication
 Definition of HMIS
 Health Management Information System: A comprehensive
and integrated structure that collects, collates, analyses,
evaluates, stores, disseminates, health and health-related data
and information for use by all stakeholders

 Typically HMIS is made of two broad parts

 Facility/institution based
 Population based
 Broad parts of HMIS
Resource
Censuses
Records

Civil Service
Registration Records

Population Individual
Surveys Records

Population-based Institution-based
 Sub-systems of HMIS
 Human Resources Information System (HRIS): an
information system used to capture data, manipulate, analyse,
store, retrieve, and disseminate information regarding an
organisation’s human resources
 Financial Information System (FIS): an information system
used to capture data, manipulate, analyse, store, retrieve, and
disseminate information regarding an organisation’s financial
management
 Logistic and Supplies Management Information System
(LMIS): an information system used to capture data,
manipulate, analyse, store, retrieve, and disseminate
information regarding an organisation’s commodity supply
chain management
 The elements and components of the
HMIS system
 Resources: Legislative, personnel, financial, logistical, ICT
 Indicators: Related targets
 Data sources: Population based/institution based
 Data management: Collection, analysis, storage, compilation
at timely intervals
 Information products: To turn data into relevant information
 Dissemination & use: Information is shared and used to
inform decision-making
 HMIS: system elements and
components
 System Elements
 Systems have three principal elements:
 Inputs: Data from different sources – including facility and
community)
 Processing mechanisms (analysis): Processing or
manipulation can include performing calculations, making
comparisons, selecting alternative actions, or merely storing
data for future use.
 Outputs: Output is defined as the product produced from
information system processes
 Feedback provided by the system influences future inputs
 HMIS: system elements and
components …
 Feedback
 It is important that every information system has a
feedback process
 Feedback can take the form of assessing outputs of system
processes and determining whether or not adjustments or
changes to input or processing activities are required
 Feedback is used to influence future inputs into the system
Determinants of effectiveness of HMIS
 Three key information domains determine the effectiveness
of HMIS in a country
 Health determinants
 Health systems performance
 Health status
 Data driven management
 Information systems support a range of management
decisions and actions:
 Planning programmes & obtaining resources
 Enhancing population’s access to services
 Quality measurement & improvement
 Productivity/efficiency
 Benchmark to national or global standards
 Accounting for resources
 Financial as well as physical resources (e.g. drugs,
supplies)
 Evolution of HMIS
Data Repository & Data Repository & Data Repository & Data Repository &
Statistical offices Statistical offices Statistical offices Statistical offices

• Collation and • Routine inclusion • Increase • Increased need for

archiving of of records of investments in analysis across
information systems (e.g.
service delivery births and health by various
presentation of Human
data & Hospital deaths. funding agencies
resource vacancy rates by
administrative • Emergence of and governments different epidemiologic
statistics offices of vital called for improved profiles).
statistics and reporting systems • Development &
demographic for accountability integration of the
Community based
information System
(CBHIS)
 Implications of evolution
 Increased need for quality and timely data
 Increase in the complexity of operational, policy and strategic
information requirements
 Changes in the roles and responsibilities of health records
information officers
 Need to re-tool this cadre of health workers
 Need to revise the training curriculum in tertiary institutions.
 Increased need to employ use of ICT for automation and
integration
 Exposure of gaps in policy and legislation around information
management in health
ROLES AND FUNCTIONS OF HMIS
 Role of HMIS in policy and decision
making
 Management of routine information
 Link between plans and implementation
 Link between strategy, approach, intervention and outcomes,
impact
 Operational research
 Programme evaluation
 Rapid surveys
 Trend and time series analysis
 Surveillance systems
 Role of HMIS in Health Systems
Strengthening (HSS)
 Support of effective health sector planning
 Support of effective health sector performance monitoring
 Management information system for
 financing
 HRM
 logistics and supplies
 infrastructure
 Support for correlational analytics
 Establishment of institutional memory
 Health impact
 HMIS is the sole tool for monitoring trends of impact
indicators at population level.
 These are commonly measured through population surveys:
 Improved health outcomes: Mortality rates
 Equity: Fairness in the output and outcome indicators
 Social and financial risk protection: Cushioning individuals
and families from impoverishment from ill health and costs
of seeking health services
 Responsiveness: Meeting the felt and expressed health needs
of communities, families and individuals
Resource mobilisation and allocation
 HMIS is key in producing the information to guide
resource mobilisation and allocation by:

 Equity analysis

 Efficiency ratios
POLICIES, LEGAL FRAMEWORKS AND
ETHICAL ISSUES IN HSS
 Need for HMIS policy & legal
framework
 Address the country institutional HMIS framework
 Need to streamline the functions of HMIS
 Guarantee availability and accessibility of quality data as a public
good for decision making
 Need to establish and maintain a simple, coherent, scientifically
sound, easily understandable and compatible information system
 Need for a robust system to track achievements of the health
sector objectives at all levels, taking into account the national
values of universal coverage, equity, quality and social justice
 Need for ethical considerations guiding information sharing
 Gaps in policy and legislation
 Reporting obligation by all service providers
 public vs. private actors
 government vs. development partners in health
 implementing partners

 Data structure standards

 Data exchange standards
 Data confidentiality and privacy
 Public access to health information
 Direct financing of HMIS activities as % of THE and GEH
 Process of policy formulation
Problem
Identification
Policy
Evaluation
Prioritisation

Implementation Policy
Formulation

Adoption
 Objectives of HMIS policies
Promote:
 unified and integrated HMIS used by all actors
 incentivised data demand and information use
 functional linkage among all statistical constituencies
 continual improvement in data quality
 individual and institutional learning
 knowledge creation and management
 public access to health information in user friendly formats
INFORMATION AND KNOWLEDGE
MANAGEMENT
 Knowledge Management
 Is knowledge an object OR a process?

Knowledge=Object Knowledge=Process
(Invest in IT) (Invest in people)
Knowledge is:
• A process
• Dynamic
• Personal/organisational
• Different from data
• Different from Information.

Knowledge = A Capacity to Act

 Knowledge Management: Fact or
Myth?
• KM is the same thing as learning
No, learning is a means to an end – KM must have a business
focus
• KM is a series of procedures which are to be implemented
No, KM is a fundamental shift in strategic paradigm
• KM is to capture knowledge kept in the heads of people
No, KM concerns how to create environments for people to
create, leverage and share knowledge
• KM is a question of ensuring information is sent to everyone
No, central push tends to fail. Catering for demand is much more
effective
 Knowledge Management: Fact or
Myth?
• KM is a simple add-on to business as usual
No, KM requires deep rooted behavioural and strategic change
• KM is a function to be delegated to HR or IT
No, KM requires top management involvement; it is a
fundamental shift in strategic perspective
• KM is just a matter of investing in IT
No, IT is a tool for information exchange, but can never drive
change
 Cycle of information management

Values to Navigation
Collection Organization

Repositories Active Knowledge transfer

- Best practices - Expert knowledge base
- Reports Organizational - Contact links
- Documents learning - Expert assistance as needed
- Presentation slides - Communities of practice index
- Tips Decision making tools
-Profiles for customization
-pushed reports and news Communication
- Collaboration tools
Codification
 Identification of information needs
of the user
 Information system managers must answer questions such as:
 What information is needed at what level?
 How much of it is needed?
 How, when, and by whom will it be used?
 In what form is it needed?
 Output requirements
 Management must begin with an examination of the output
requirement e.g. by classifying information based on the level
(strategic, tactical and operational) in the organisation at which it
will be used
Identification of information needs
of the user …
 Data gathering and information processing
 The purpose is to improve the overall quality of
information
Components:
 Evaluation – determining how much confidence can be
based in a particular piece of information. The credibility of
the source and reliability and validity of the data must be
determined
 Data collection and information
processing

 Abstraction – involves editing and reducing incoming

information in order to provide managers with only the
information that is relevant to their particular tasks

 Indexing – classifying information for storage and retrieval

purposes

 Storage – provide for storage of information to permit its use

again in needed
 Information dissemination and use
 Dissemination:
 Getting the right information to right manager at the right time.
This is the overriding purpose of an HMIS

 Information use depends on:

 Quality (accuracy)
 Form – how it is presented
 Timeliness
 Relevance

 Major goal of HMIS:

 Provide the right information to the right decision- maker at the
right time
 Aspects of data quality
 Data must be:
 Complete
 Accurate
 Standardised
 Timely
 Verifiable
 Accessible
 Secure
 Components for design
Data sources Integrated information system
Censuses Resource
Records Health Information
system Actors using
Civil Service Evidence for decision-
Extract
Registration Records and Integrated making
integrate data -Seniour county Officer
Population Individual Data repository Reports -National public Health
Surveys Records Queries Officer
Events -international M&E
Population Institution- and Officer
-based based Alerts -District Health Manager
-seniour County officer
-Facility Health Officer
- ETC
Standard - Compliant
Data collection activities

Policies, Resources and Processes

 Components for design
 Define the data elements needed from each data source

 Design standard data capture tools

 Build the capacity of the health care workers on data capture

 Make electronic formats of the tools

 Design a IT interactive interface and a robust database

 Components for design…
 Determine essential dataset needed from each data source

 Design IT interface to mine data from priority databases

 Develop an integrated data repository relevant to the organisational

specific needs
 Components for design…
 Build capacity for data analysis and data presentation
 Determine the appropriate decision support tools required
 Dashboards
 Messaging services
 Flash alerts
 Adopt appropriate technology to support the data
presentation requirements
 Components for design…
 Effectively profile the end-user data and information needs
 Determine their preferred presentation format and
platform/media
 Determine their preferred frequencies of dissemination
 Adopt appropriate technology to meet dissemination
requirements
 Adopt appropriate technology to archive the data and
information
ROLE OF ICT IN HMIS
STRENGTHENING
 Data transformation
Data Data Storage & Data Reporting &
Capture Transmission processing Exploration dissemination

Getting “Data” Giving “information”

Priorities for information technology
investment
 Fundamental question: Is infrastructure to support IT
available?
 If not, focus on staff training, detailed procedures, team
building, regular audits
 Focus IT investment on activities where it can provide
greatest benefits
 Many first line facilities can use paper records
 IT is most powerful for communicating and aggregating
data, doing complex analyses
Infrastructure requirements to support
information technology
 Staff trained to use computers and software
 Maintenance for computers and software
 Data backup capability
 In case of computer loss or failure
 Physical security
 To prevent theft or damage to hardware
 Data security
 To prevent unauthorised access
Information technology selection
and implementation criteria
 Software: standardisation, ease of use, stability,
upgradeability
 Open source software is free but requires
knowledgeable staff to install and maintain

 Hardware: reliability, support from vendor

 Network: reliability, cost
 Staff: ability to retain staff with critical IT skills
 Glossary of terms
 Archiving – Archiving is a process for backing up data that may not be routinely
accessed, but to which an organisation wants to retain the ability to access should the
need arise. By archiving data, database queries become faster and more efficient,
translating into faster, more responsive experiences for the end users

 Data dictionary – A data dictionary, or metadata repository, as defined in the IBM

Dictionary of Computing, is a "centralised repository of information about data such
as meaning, relationships to other data, origin, usage, and format." In other words, a
data dictionary helps describe the data in the system, and help translate the data of
one system into terms acceptable in another system

 Data dissemination – Once data has been integrated into the national HIS, stored
in the data warehouse, sent to the various data marts for data mining and
visualisation, the “results” should be accessible by the decision makers. The method
of dissemination depends on what the results look like and who needs them;
however, data dissemination could occur by web page, email, RSS, SMS text
message, paper report, voice phone call, a briefing, or another method
 Glossary of terms…
 Data governance – Data governance embodies a convergence of data quality, data
management, data policies, business process management, and risk management
surrounding the handling of data in an organisation. Through data governance,
organisations are looking to exercise positive control over the processes and
methods used by their data stewards and data custodians to handle data

 Data mart – A data mart (DM) is the access layer of the data warehouse (DW)
environment that is used to get data out to the users. The DM is a subset of the DW,
usually oriented to a specific business line or team. There can be multiple data marts
inside a single HIS system; each one relevant to one or more business units for
which it was designed

 Data mining – Data mining is the process of extracting patterns from large data
sets by combining methods from statistics and artificial intelligence with database
management. Data mining is a process of inspecting, cleaning, transforming, and
modeling data with the goal of highlighting useful information, suggesting
conclusions, and supporting decision making
 Glossary of terms …
 Data Services layer (DSL) – The DSL provides a layer for data access that
is independent of the physical schema. The purpose is to provide a consistent
interface for accessing data, independent of the structure of the databases
attempting to make the connection

 Data warehouse – A data warehouse is a subset of the overall data

available in a system, collected over large periods of time, and needed to
process a relatively small number of very large data requests. It is an interim
database that lies somewhere between the source databases and the reporting
platform. Data warehousing is used for archiving, data mining, and analytics
or some combination of all three. A data warehouse maintains its functions in
three layers: staging, integration, and access. Staging is used to store raw data
for use by developers (analysis and support). The integration layer is used to
integrate data and to have a level of abstraction from users. The access layer is
for getting data out for users