This document outlines the objectives and structure of a training on Monitoring and Evaluation (M&E) skills and expertise for researchers. The training aims to build M&E capacity among researchers to strengthen development evaluation. It will cover M&E framework and tool development, as well as program and project evaluation. The training is expected to equip researchers with M&E skills and expertise to become M&E specialists or professional research consultants.
The Basics of Monitoring, Evaluation and Supervision of Health Services in NepalDeepak Karki
This presentation has made to health workers who have more than two decades of experience of managing/implementing public health programs in Nepal, especially at district level and below.
Chapter 5 Program Evaluation and Research TechniquesCharlene R. .docxchristinemaritza
Chapter 5 Program Evaluation and Research Techniques
Charlene R. Weir
Evaluation of health information technology (health IT) programs and projects can range from simple user satisfaction for a new menu or full-scale analysis of usage, cost, compliance, patient outcomes, and observation of usage to data about patient's rate of improvement.
Objectives
At the completion of this chapter the reader will be prepared to:
1.Identify the main components of program evaluation
2.Discuss the differences between formative and summative evaluation
3.Apply the three levels of theory relevant to program evaluation
4.Discriminate program evaluation from program planning and research
5.Synthesize the core components of program evaluation with the unique characteristics of informatics interventions
Key Terms
Evaluation, 72
Formative evaluation, 73
Logic model, 79
Program evaluation, 73
Summative evaluation, 73
Abstract
Evaluation is an essential component in the life cycle of all health IT applications and the key to successful translation of these applications into clinical settings. In planning an evaluation the central questions regarding purpose, scope, and focus of the system must be asked. This chapter focuses on the larger principles of program evaluation with the goal of informing health IT evaluations in clinical settings. The reader is expected to gain sufficient background in health IT evaluation to lead or participate in program evaluation for applications or systems.
Formative evaluation and summative evaluation are discussed. Three levels of theory are presented, including scientific theory, implementation models, and program theory (logic models). Specific scientific theories include social cognitive theories, diffusion of innovation, cognitive engineering theories, and information theory. Four implementation models are reviewed: PRECEDE-PROCEED, PARiHS, RE-AIM, and quality improvement. Program theory models are discussed, with an emphasis on logic models.
A review of methods and tools is presented. Relevant research designs are presented for health IT evaluations, including time series, multiple baseline, and regression discontinuity. Methods of data collection specific to health IT evaluations, including ethnographic observation, interviews, and surveys, are then reviewed.
Introduction
The outcome of evaluation is information that is both useful at the program level and generalizable enough to contribute to the building of science. In the applied sciences, such as informatics, evaluation is critical to the growth of both the specialty and the science. In this chapter program evaluation is defined as the “systematic collection of information about the activities, characteristics, and results of programs to make judgments about the program, improve or further develop program effectiveness, inform decisions about future programming, and/or increase understanding.”1 Health IT interventions are nearly always embedded in ...
The Basics of Monitoring, Evaluation and Supervision of Health Services in NepalDeepak Karki
This presentation has made to health workers who have more than two decades of experience of managing/implementing public health programs in Nepal, especially at district level and below.
Chapter 5 Program Evaluation and Research TechniquesCharlene R. .docxchristinemaritza
Chapter 5 Program Evaluation and Research Techniques
Charlene R. Weir
Evaluation of health information technology (health IT) programs and projects can range from simple user satisfaction for a new menu or full-scale analysis of usage, cost, compliance, patient outcomes, and observation of usage to data about patient's rate of improvement.
Objectives
At the completion of this chapter the reader will be prepared to:
1.Identify the main components of program evaluation
2.Discuss the differences between formative and summative evaluation
3.Apply the three levels of theory relevant to program evaluation
4.Discriminate program evaluation from program planning and research
5.Synthesize the core components of program evaluation with the unique characteristics of informatics interventions
Key Terms
Evaluation, 72
Formative evaluation, 73
Logic model, 79
Program evaluation, 73
Summative evaluation, 73
Abstract
Evaluation is an essential component in the life cycle of all health IT applications and the key to successful translation of these applications into clinical settings. In planning an evaluation the central questions regarding purpose, scope, and focus of the system must be asked. This chapter focuses on the larger principles of program evaluation with the goal of informing health IT evaluations in clinical settings. The reader is expected to gain sufficient background in health IT evaluation to lead or participate in program evaluation for applications or systems.
Formative evaluation and summative evaluation are discussed. Three levels of theory are presented, including scientific theory, implementation models, and program theory (logic models). Specific scientific theories include social cognitive theories, diffusion of innovation, cognitive engineering theories, and information theory. Four implementation models are reviewed: PRECEDE-PROCEED, PARiHS, RE-AIM, and quality improvement. Program theory models are discussed, with an emphasis on logic models.
A review of methods and tools is presented. Relevant research designs are presented for health IT evaluations, including time series, multiple baseline, and regression discontinuity. Methods of data collection specific to health IT evaluations, including ethnographic observation, interviews, and surveys, are then reviewed.
Introduction
The outcome of evaluation is information that is both useful at the program level and generalizable enough to contribute to the building of science. In the applied sciences, such as informatics, evaluation is critical to the growth of both the specialty and the science. In this chapter program evaluation is defined as the “systematic collection of information about the activities, characteristics, and results of programs to make judgments about the program, improve or further develop program effectiveness, inform decisions about future programming, and/or increase understanding.”1 Health IT interventions are nearly always embedded in ...
Identifying the basic purposes and scope of M&E. Describing the functions of an M&E plan. Identifying and understanding the main components of an M&E plan
Lessons from the US Perfromance Management System by Donald MoynihanOECD Governance
Presentation by Donald Moynihan at the 10th annual meeting of the Senior Budget Officials Performance and Results Network held on 24-25 November 2014. Find more information at http://www.oecd.org/gov/budgeting
192020 Capella University Scoring Guide Toolhttpsscor.docxaulasnilda
1/9/2020 Capella University Scoring Guide Tool
https://scoringguide.capella.edu/grading-web/gradingdetails 1/7
MHA-FP5064
u03a1 - Health Information System Implementation
Learner: Monna , Joseph
OVERALL COMMENTS
Mona
This paper is not very clear and specific. You have very genialized explanations of data and are not discussing
data requirements from meaningful use and merit-based incentives. Also you are not supporting the data needs
with CURRENT academic sources. You only have 2 references both from well over 10 years ago. You need
research current trends and best practices from recent sources.
See the rubric below for more specifics.
RUBRICS
1/9/2020 Capella University Scoring Guide Tool
https://scoringguide.capella.edu/grading-web/gradingdetails 2/7
CRITERIA 1
Outline a plan for collecting and analyzing data.
COMPETENCY
Incorporate project management principles into health care administration management and leadership.
NON_PERFORMANCE: Does not outline a plan for collecting and analyzing data.
BASIC:
Outlines a plan for collecting and analyzing data that is impracticable or unlikely to yield limited data for
analysis.
PROFICIENT: Outlines a plan for collecting and analyzing data.
DISTINGUISHED:
Outlines a plan for collecting and analyzing data. Provides a concise and well-articulated outline that
identifies specific data needs and a clear approach to analysis.
Comments:
I am not see a plan that alignes with current trends in health care. Plan needs to address specific data that
would common in an EHR and meet current legislative requirments.
(20%)
1/9/2020 Capella University Scoring Guide Tool
https://scoringguide.capella.edu/grading-web/gradingdetails 3/7
CRITERIA 2
Propose criteria for evaluating organizational needs.
COMPETENCY
Incorporate project management principles into health care administration management and leadership.
NON_PERFORMANCE: Does not propose criteria for evaluating organizational needs.
BASIC:
Proposes criteria for evaluating organizational needs that may lead to erroneous conclusions.
PROFICIENT: Proposes criteria for evaluating organizational needs.
DISTINGUISHED:
Proposes criteria for evaluating organizational needs, and provides relevant, credible evidence that
clearly validates the proposed criteria.
Comments:
Very unclear and is not alinging with best practices from AHIMA, HIMSS or Health IT,gov. Research
current oversight organizations
(16%)
1/9/2020 Capella University Scoring Guide Tool
https://scoringguide.capella.edu/grading-web/gradingdetails 4/7
CRITERIA 3
Outline a plan for generating reports.
COMPETENCY
Incorporate project management principles into health care administration management and leadership.
NON_PERFORMANCE: Does not outline a plan for generating reports.
BASIC:
Outlines a plan for generating reports that is impracticable or unlikely to provide all of the information
necessary to support sound decision making.
PROFICIENT: Outlines a ...
QI Plan Part One28QI Plan Part OneDavis .docxmakdul
QI Plan Part One
28
QI Plan Part One
Davis Healthcare Improvement
Davis Healthcare is a dedicated team of professionals to providing efficient services and patient care delivering. However, each healthcare service requires improvements in one or more sectors to improve the quality of services rendered to the patients. Therefore, focusing on each aspect of development within the healthcare service, Davis Healthcare must make amendments and specific improvements to particular sections of its organization.
Among the required sectors of development include productivity management. This section entails activities that ensure service delivery to various patients and proper coordination with staff to coordinate patient care. Different data collection tools and analyses techniques and instruments must be used to have the appropriate data required for analysis in this section, (Panesar, Carson-Stevens, Salvilla, & Sheikh, 2014). Nice, but what is the topic you will be talking about – HAC, HAI, handwashing, pt identification, med errors? etc
Data Collection
Data collection is aimed at obtaining appropriate data and information required to ensure that correct information is managed within the organization's settings for proper analysis and fact evaluation. The kind of data needed to monitor improvements include data on specific statistics regarding delivery of services, feedback from patients, recovery rates, as well as patient care response.
Some of the tools that can be used in data collection include surveys, questionnaires, and interviews. These collection devices are used in gathering data from the field and various respondents appropriately before indulging in analysis and improvement process of the healthcare delivery sector (Blischke, Karim, & Murthy, 2011).
Surveys are short questions issued to various persons with specific answer sets and defined sets of questions. These studies are aimed at targeted forms of responses within the community and organization. The surveys are given out to respondents across the field area, to achieve issue objectively where the respondents can respond to the questions categorically.
· Surveys are easily formed as they are simple problems and can be sent through emails or other forums to the various respondents across the field of study.
· Informational content on the improvement of productivity management is categorized into obvious questions that can easily be understood by the different respondents within the responses.
· The response fields have areas that can be expounded upon to give more detailed information about a particular service or area of study. According to surveys, information available on specific areas of study and the challenges that each department undertakes in productivity management can be recorded in the survey answers.
· Some of the cons of using surveys include problems in understanding questions asked to the various departments. Moreover, categorizing each study ...
Evaluating the quality of quality improvement training in healthcareDaniel McLinden
Quality Improvement (QI)in healthcare is an increasingly important approach to improving health outcomes, improving system performance and improving safety for patients. Effectively implementing QI methods requires knowledge of methods for the design and execution of QI projects. Given that this capability is not yet widespread in healthcare, training programs have emerged to develop these skills in the healthcare workforce. In spite of the growth of training programs, limited evidence exists about the merit and worth of these programs. We report here on a multi-year, multi-method evaluation of a QI training program at a large Midwestern academic medical center. Our methodology will demonstrate an approach to organizing a large scale training evaluation. Our results will provide best available evidence for features of the intervention, outcomes and the contextual features that enhance or limit efficacy.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...Amil Baba Dawood bangali
Contact with Dawood Bhai Just call on +92322-6382012 and we'll help you. We'll solve all your problems within 12 to 24 hours and with 101% guarantee and with astrology systematic. If you want to take any personal or professional advice then also you can call us on +92322-6382012 , ONLINE LOVE PROBLEM & Other all types of Daily Life Problem's.Then CALL or WHATSAPP us on +92322-6382012 and Get all these problems solutions here by Amil Baba DAWOOD BANGALI
#vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore#blackmagicformarriage #aamilbaba #kalajadu #kalailam #taweez #wazifaexpert #jadumantar #vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore #blackmagicforlove #blackmagicformarriage #aamilbaba #kalajadu #kalailam #taweez #wazifaexpert #jadumantar #vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore #Amilbabainuk #amilbabainspain #amilbabaindubai #Amilbabainnorway #amilbabainkrachi #amilbabainlahore #amilbabaingujranwalan #amilbabainislamabad
Identifying the basic purposes and scope of M&E. Describing the functions of an M&E plan. Identifying and understanding the main components of an M&E plan
Lessons from the US Perfromance Management System by Donald MoynihanOECD Governance
Presentation by Donald Moynihan at the 10th annual meeting of the Senior Budget Officials Performance and Results Network held on 24-25 November 2014. Find more information at http://www.oecd.org/gov/budgeting
192020 Capella University Scoring Guide Toolhttpsscor.docxaulasnilda
1/9/2020 Capella University Scoring Guide Tool
https://scoringguide.capella.edu/grading-web/gradingdetails 1/7
MHA-FP5064
u03a1 - Health Information System Implementation
Learner: Monna , Joseph
OVERALL COMMENTS
Mona
This paper is not very clear and specific. You have very genialized explanations of data and are not discussing
data requirements from meaningful use and merit-based incentives. Also you are not supporting the data needs
with CURRENT academic sources. You only have 2 references both from well over 10 years ago. You need
research current trends and best practices from recent sources.
See the rubric below for more specifics.
RUBRICS
1/9/2020 Capella University Scoring Guide Tool
https://scoringguide.capella.edu/grading-web/gradingdetails 2/7
CRITERIA 1
Outline a plan for collecting and analyzing data.
COMPETENCY
Incorporate project management principles into health care administration management and leadership.
NON_PERFORMANCE: Does not outline a plan for collecting and analyzing data.
BASIC:
Outlines a plan for collecting and analyzing data that is impracticable or unlikely to yield limited data for
analysis.
PROFICIENT: Outlines a plan for collecting and analyzing data.
DISTINGUISHED:
Outlines a plan for collecting and analyzing data. Provides a concise and well-articulated outline that
identifies specific data needs and a clear approach to analysis.
Comments:
I am not see a plan that alignes with current trends in health care. Plan needs to address specific data that
would common in an EHR and meet current legislative requirments.
(20%)
1/9/2020 Capella University Scoring Guide Tool
https://scoringguide.capella.edu/grading-web/gradingdetails 3/7
CRITERIA 2
Propose criteria for evaluating organizational needs.
COMPETENCY
Incorporate project management principles into health care administration management and leadership.
NON_PERFORMANCE: Does not propose criteria for evaluating organizational needs.
BASIC:
Proposes criteria for evaluating organizational needs that may lead to erroneous conclusions.
PROFICIENT: Proposes criteria for evaluating organizational needs.
DISTINGUISHED:
Proposes criteria for evaluating organizational needs, and provides relevant, credible evidence that
clearly validates the proposed criteria.
Comments:
Very unclear and is not alinging with best practices from AHIMA, HIMSS or Health IT,gov. Research
current oversight organizations
(16%)
1/9/2020 Capella University Scoring Guide Tool
https://scoringguide.capella.edu/grading-web/gradingdetails 4/7
CRITERIA 3
Outline a plan for generating reports.
COMPETENCY
Incorporate project management principles into health care administration management and leadership.
NON_PERFORMANCE: Does not outline a plan for generating reports.
BASIC:
Outlines a plan for generating reports that is impracticable or unlikely to provide all of the information
necessary to support sound decision making.
PROFICIENT: Outlines a ...
QI Plan Part One28QI Plan Part OneDavis .docxmakdul
QI Plan Part One
28
QI Plan Part One
Davis Healthcare Improvement
Davis Healthcare is a dedicated team of professionals to providing efficient services and patient care delivering. However, each healthcare service requires improvements in one or more sectors to improve the quality of services rendered to the patients. Therefore, focusing on each aspect of development within the healthcare service, Davis Healthcare must make amendments and specific improvements to particular sections of its organization.
Among the required sectors of development include productivity management. This section entails activities that ensure service delivery to various patients and proper coordination with staff to coordinate patient care. Different data collection tools and analyses techniques and instruments must be used to have the appropriate data required for analysis in this section, (Panesar, Carson-Stevens, Salvilla, & Sheikh, 2014). Nice, but what is the topic you will be talking about – HAC, HAI, handwashing, pt identification, med errors? etc
Data Collection
Data collection is aimed at obtaining appropriate data and information required to ensure that correct information is managed within the organization's settings for proper analysis and fact evaluation. The kind of data needed to monitor improvements include data on specific statistics regarding delivery of services, feedback from patients, recovery rates, as well as patient care response.
Some of the tools that can be used in data collection include surveys, questionnaires, and interviews. These collection devices are used in gathering data from the field and various respondents appropriately before indulging in analysis and improvement process of the healthcare delivery sector (Blischke, Karim, & Murthy, 2011).
Surveys are short questions issued to various persons with specific answer sets and defined sets of questions. These studies are aimed at targeted forms of responses within the community and organization. The surveys are given out to respondents across the field area, to achieve issue objectively where the respondents can respond to the questions categorically.
· Surveys are easily formed as they are simple problems and can be sent through emails or other forums to the various respondents across the field of study.
· Informational content on the improvement of productivity management is categorized into obvious questions that can easily be understood by the different respondents within the responses.
· The response fields have areas that can be expounded upon to give more detailed information about a particular service or area of study. According to surveys, information available on specific areas of study and the challenges that each department undertakes in productivity management can be recorded in the survey answers.
· Some of the cons of using surveys include problems in understanding questions asked to the various departments. Moreover, categorizing each study ...
Evaluating the quality of quality improvement training in healthcareDaniel McLinden
Quality Improvement (QI)in healthcare is an increasingly important approach to improving health outcomes, improving system performance and improving safety for patients. Effectively implementing QI methods requires knowledge of methods for the design and execution of QI projects. Given that this capability is not yet widespread in healthcare, training programs have emerged to develop these skills in the healthcare workforce. In spite of the growth of training programs, limited evidence exists about the merit and worth of these programs. We report here on a multi-year, multi-method evaluation of a QI training program at a large Midwestern academic medical center. Our methodology will demonstrate an approach to organizing a large scale training evaluation. Our results will provide best available evidence for features of the intervention, outcomes and the contextual features that enhance or limit efficacy.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...Amil Baba Dawood bangali
Contact with Dawood Bhai Just call on +92322-6382012 and we'll help you. We'll solve all your problems within 12 to 24 hours and with 101% guarantee and with astrology systematic. If you want to take any personal or professional advice then also you can call us on +92322-6382012 , ONLINE LOVE PROBLEM & Other all types of Daily Life Problem's.Then CALL or WHATSAPP us on +92322-6382012 and Get all these problems solutions here by Amil Baba DAWOOD BANGALI
#vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore#blackmagicformarriage #aamilbaba #kalajadu #kalailam #taweez #wazifaexpert #jadumantar #vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore #blackmagicforlove #blackmagicformarriage #aamilbaba #kalajadu #kalailam #taweez #wazifaexpert #jadumantar #vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore #Amilbabainuk #amilbabainspain #amilbabaindubai #Amilbabainnorway #amilbabainkrachi #amilbabainlahore #amilbabaingujranwalan #amilbabainislamabad
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.
Vaccine management system project report documentation..pdf
first-batch-me-training.pptx
1. KEM LEY | Principal investigator
NHIM DALEN |Consultant
BORAY BORALIN | Data Analyst
UMAKANT SINGH | Advisor
Professional Training
2. To intensify the M&E skills and expertise of researchers and
improve the impact on general public and development.
Main
Objective
Specific
Objectives
Expected
Results
Impact
1. Building the capacity and skills of researchers on M&E system and
development evaluation
2. Strengthening the capacity of researchers to be able to develop M&E
framework and tools
3. Strengthening the capacity of researchers to be able to conduct program and
project evaluation
4. Equipping researchers with M&E skills and expertise
1. Become familiar with concepts and practices of M&E
2. Be able to develop M&E framework and Tools
3. Be able to conduct program/project evaluation
4. Equipped with M&E Skills and expertise
1. M&E Specialist
2. Professional Research Consultant
3. M&E Framework andTools Development
Module 1: M&E Rapid Assessment
Module 2: M&E framework development
Module 3: Monitoring tools development
Module 4: M&ETools Pilot and Review
Module 5: Finalized M&E Framework andTools
Module 6: Roll-out Plan and M&E Costed Capacity Plan
Development Evaluation
Module 1: Objectives of Evaluation
Module 2: Focus and Scope
Module 3: Select Indicators
Module 4: Chose Study Design
Module 5: Data collection Plan
Module 6: Data Enumerators Train
Module 7: Data Collection/Field Work
Module 8: Data processing and analysis
Module 9: Data organization and interpretation
Module 10: Evaluation ReportWriting
7. Community action and results for health and
non health
Activities/services for
communities
Systems
develop & manage
that they use to deliver
Commune
Committee for
Women and
Children
Community &
Health Actors
Outputs
Health outcomes Other outcomes
Impacts on
health and
reduction of
vulnerability of
OVC
Resulting in:
which in turn contribute to
that lead to
8. % of current school
attendance among
double orphans and
non orphans aged 10-
14
% of double orphans
who received
education assistance
and scholarship;
# of OVC and
community people
involved in parental
association and
education for all
committee
# of school offering
breakfast
% of double orphans
whose households
received economic
support
# of OVC whose HH
received economic
and food support
10. Type of
Framework
Brief Description Program
Management
Basis for Monitoring
and Evaluation
Conceptual Interaction of
various factors
Determine which
factors the program
will influence
No. Can help to explain
results
Results Logically linked
program objectives
Shows the causal
relationship between
program objectives
Yes – at the objective
level
Logic model Logically links
inputs, processes,
outputs, and
outcomes,
Shows the causal
relationship between
inputs and the
objectives
Yes – at all stages of
the program from
inputs to process to
outputs to outcomes/
objectives
11. Strategy1:
Objectives Activity
Domain
Core
Indicators
Baseline Target Data
Collection
Methods
Responsible
Institution
Reference
Indicator
Strategy2:
Goal: Strengthen the coordination, systems, coverage and quality, of services needed to mitigate the impact of HIV on
the lives and futures of Cambodian children, while also addressing the underlying issues to vulnerable children.
Impact Indicators: % of Birth Registration, Proportion of Current School attendance , stunt, underweight and wasted
12. Select indicator standard
Reporting Format
Instruction Guide
Data Flow and Management
M&E Data Collectors Train
Piloting and updating
Roll out plan
Data Base System
Data Use Plan
13. A good Indicator should meet the following six
standard;
The indicator is needed and useful
The indicator has technical merit
The indicator is fully defined
Its feasible to measure the indicator
The indicator has been field tested or used
operationally.
The indicator set is coherence and balanced (
relevant to indicator sets only)
14. STANDARD 1: THE INDICATOR IS NEEDED AND
USEFUL
Question 1: Is there evidence that this indicator is needed at the
appropriate level?
Question 2: Which stakeholders need and would use the
information collected by this indicator?
Question 3: How would information from this indicator be used?
Question 4: What effect would this information have on planning
and decision-making?
Question 5: Is this information available from other indicators
and/or other sources?
Question 6: Is this indicator harmonized with other indicators?
15. STANDARD 2: THE INDICATOR HAS
TECHNICAL MERIT
Question 1: Does the indicator have
substantive merit or technically sound and significant or
measure something significant and important within particular field
Question 2: Is the indicator reliable and
valid?
Question 3: Has the indicator been peer
reviewed?
16. STANDARD 3: THE INDICATOR IS FULLY DEFINED
Title and definition
Purpose and rationale
Method of measurement
Data collection methodology
Data collection frequency
Data disaggregation
Guidelines to interpret ad use data
Strengths and weaknesses
Challenges
Relevant sources of additional information
17. STANDARD 4: IT IS FEASIBLE TO COLLECT AND ANALYSE DATA
FOR THIS INDICATOR
Question 1: How well are they systems, tools and
mechanisms that are required to collect, interpret and use
data for this indicator functioning?
Question 2: How would this indicator be integrated into a
national M&E framework and system?
Question 3: How what extend are the financial and
human resources needed to measure this indicator
available?
Question 4: What evidence exists that measuring this
indicator is worth the cost?
18. STANDARD 5: THE INDICATOR HAS BEEN FIEL-
TESTED OR USED OPERATIONALLY
Question 1: To what extend has the
indicator been field-tested or used
operationally?
Question 2: Is this indicator part of a
system to review its performance in
ongoing use?
19. STANDARD 6: THE INDICATOR SET IS COHERENCE
AND BALANCED (Relevant to indicator sets only)
Question 1: Does the indicator set give and overall
picture of the adequacy or otherwise of the response
being measured?
Question 2: Does the indicator set have an appropriate
balance of indicators across elements of the response?
Question 3: Does the indicator set over different M&E
levels appropriately?
Question 4: Does the set contain an appropriate number
of indicators?
20. Consistency or dependability of data and
evaluation judgments, with reference to quality of
the instruments, procedures and analysis used to
collect and interpret evaluation data
Indication defines clearly what we should be
measured. It defines the variables that help
measure change within a given situation as well
as describe the progress and impact.
The extent to which something is reliable and
actually measures up to or make a correct claim.
The process of cross-checking to ensure that the
data obtained from one monitoring method are
confirmed by the data obtained from a different
method
INDICATOR PROTOCOLS
INDICATOR PROTOCOLS
REQUIRES
• Definition
• Measurement
• Strengths
• Limitations
• Reliability
• Precision
• Validity
• Objective
• Owned
• Accessible
• Useful
21. M&E FRAMEWORK &
TOOLS
DEVELOPMENT
M&E Rapid
Assessment
M&E Framework
Development
Monitoring Tools
Development
M&E Tools Pilot
and Review
Roll-out Plan and
M&E Costed
Capacity Plan
Finalize M&E
Framework and
Tools
22. What is instruction guide?
Instruction guide is a reference tool formulated tends to provide clear
explanation on how to accurately complete the reporting format.
How to develop instruction guide?
Identify purpose of the instruction guide
State purpose of the reporting form
Data sources
Who prepare the report
Frequency of reporting
Reporting period
Name of agency completing the report
District
Province
Indicators
23. Indicators:
For example: Total number of OVC whose households received economic support (income
generation activities, livelihood support, regular cash transfer)
Write the total number of OVC whose households received economic support during the
reporting period.
Definition: Economic support (IGAs and livelihood) has been defined as:
Home gardening
Animal husbandry
Provision of agricultural seeds
Small business development
Money management training
Emergency cash support
Regular cash transfers
Access to loan/microfinance
Other
Disaggregation:
This data is disaggregated by gender. Write the total number of male OVC in the “Male”
column and the total number of female OVC in the “Female” column. Then write the total
number of OVC (male + female) in the “Total” column.
24. When mapping the flow of data, please consider
the following issues:
Who will be responsible for data collection?
Who will provide the data?
Who will be responsible for supervision of data
collection?
Who will be responsible for compiling and aggregating
data?
How often are data collected, compiled, reported, and
analyzed?
How are data sent from one level to the next?
How is feedback on reported data provided?
25. Ministry of Social Affairs, Veterans and Youth
Rehabilitation (MoSVY)
(Child Welfare Department)
Youth Rehabilitation /
Drug Rehabilitation
Alternative
Care Centers
Provincial Department of Social Affairs, Veterans and
Youth Rehabilitation (PoSVY)
DoSVY
Commune Council (via
CDB)
Quarterly
Quarterly
Quarterly
Quarterly PoSVY
Report on OVC
Provincial Department of Planning
Ministry of Planning
CCWC
POVCTF
Service
Providers
(NGOs)
Data flow
Feedback
Supportive Supervision
NOVCTF
Village Council (via
CBD)
Annual
Annual
Annual
Annual
Law
Enforcement
(police,
prison, courts
)
PHD
MoH
26. When developing role and responsibility of all key players
involve in data collection, some important point that you
should consider:
What type indicator they need to collect and report?
How many indicator they need to collect and report?
How they collect those data (source of data –
registration book)?
Which reporting form they use?
How frequency that they should report – when?
Who they should report to?
27. Transposition—An example is when 39 is entered as 93.
Transposition errors are usually caused by typing mistakes.
Copying errors—One example is when 1 is entered as 7; another
is when the number 0 is entered as the letter O.
Coding errors—Putting in the wrong code. For example, an
interview subject circled 1 = Yes, but the coder copied 2 (which =
No) during coding.
Routing errors—Routing errors result when a person filling out a
form places the number in the wrong part or wrong order.
Consistency errors—Consistency errors occur when two or more
responses on the same questionnaire are contradictory. For
example, if the birth date and age are inconsistent.
Range errors—Range errors occur when a number lies outside the
range of probable or possible values.
28. First, determine the source of the error.
If the error arises from a data coding or entry
error
If the entry is unclear, missing, or otherwise
suspicious
Once the source of the error is identified,
the data should be corrected if
appropriate.
29. Feedback should be constructive and not punitive
Feedback should be useful to data collectors and help
them improve their work
Errors should be pointed out and corrected
The M&E supervisor should talk to the data collector to
find out the cause of the error so it can be prevented in
the future
The M&E supervisor should discuss how data quality
and reports can be improved in the future
30. Provide both positive and negative feedback (e.g. you
do X very well but can improve Y)
Provide feedback in a timely manner
Help data collectors understand the problem so they
know how to correct it in the future
Be helpful and collaborative
31. Builds relationship between data collectors and users at all levels
Important element of management and supervision
Leads to greater appreciation of data
Improves data quality
Improves information use
Improves service delivery and benefits the target population and the
community
Improve program reporting- data collectors understand trends in
data and understand reasons behind numbers
Incentivizes and motivates data collectors
32. Set criteria for selecting pilot province
Provide training on M&E reporting tools to
all data collectors
Provide on the job training to all data
collectors
33. Objective:
Aim to take an in-dept look at the quality of the
data that was collected during the pilot period
and to assess the systemic factors that affect
M&E performance and to gather direct input
on the M&E tools and system.
34. Step in conducting the review:
Develop assessment tools
▪ Data transmission, accuracy, processing and analysis
▪ Data transmission
▪ Data accuracy
▪ Data processing and analysis
▪ Data use
▪ Some qualitative questions added
Provide training to assessment team
Conduct assessment
Conduct consultation meeting on the findings
35. Key point affecting the finalization of M&E
framework and mechanics
Indicators
▪ Does these indicators are feasible to collect?
▪ Does these indicators are feasible to analyze and use?
▪ Is there any evidence that financial and human
resources are available to allow an indicator to be
measured and that the benefits of measuring the
indicator are worth the costs?
A good indicator needs to be one that is feasible to measure with
reasonable levels of resources and capacity.
36. The situation may change meaning that an indicator needs to be
changed, discarded or added.
M&E system mechanics
Does the data collection tools are applicable?
Does the reporting formats are applicable?
Does the instruction guide (guideline) is user friendly?
Data management process
How well functioning of the data flow of the system?
Does existing human resource have an appropriate capacity to
manage the data flow?
How clear the roles and responsibility of department or person
involved in M&E system?
Does the frequency of data collection and reporting are
appropriate at each level?
37. Revise M&E framework, with revised
indicator, M&E mechanics, and data
management process
Conduct consultative meeting among M&E
team and relevant stakeholders to finalize
M&E framework and system
Get approval from top level of management
(decision makers, policy makers).
40. Royal
Government
of Cambodia
Development
Partners and Civil
Society
Threatened
Communities
• Unfair
Compensation and
worsen living
condition
• Loss of job
• High Service cost
for relocated site
• There is no
available legal,
social and health
services
Positive Impact of
development
• Beautification
• Development
• Employment
• GDP Growth
• Economic Growth
• Survive people from
Slum
Negative impact of development
• Human Rights Violation
• Inadequate housing rights
• Unfair Compensation
• Unfair development
• Inequality of profits distribution
41.
42.
43. Objectives
Focus & Scope
Select Indicators
Chose Study design
Data Collection Plan
Data collection/Field Work
Data Cleaning & Verification
Data Processing & Aggregation
Data Analysing & Organization
Data Interpretation & Report
1
2
3
4
5
7
8
9
10
Data Enumerators Train
Data Use and Data Translation
11
12
6
44. The overall objective of the program
evaluation of HRTF is to assess the
social economic impact of Cambodia
Forced eviction in urban areas of
Phnom Penh Municipality.
The specific objectives of the program
evaluation is to know the status of
economic, education, health, employment,
food security and environment of
threatened and relocated communities.
46. Selected Indicators Relocated
Households
Threatened
Households
1. Percentage of Children drop out of school
2. Percentage of households whose income below poverty line
3. Percentage of households consumption
4. Percentage of households with debt
5. Percentage of household access to registered MFI
6. Percentage of households with food shortage
7. Percentage of house members whose access to health
services in the past three months
8. Percentage of households have experienced physical attack
9. Percentage of household have experienced stigma and
discrimination
10. Percentage of respondents have lost job due to forced
eviction
47. Qualitative and quantitative study design (Cross
Sectional Study)
Household Survey (Cluster Sampling-Lot division)
Key Informant Interview(KII)-Relevant Stakeholders
Focus Group Discussion (FGD)-RS and TS HH
Desk Study and Literature Review
▪ Cambodia Legal Frameworks
▪ National and International Research Findings
▪ NSDP and JMI 2009-2013, MoP
▪ Pro-Poor Policy and National Safety Net Strategy, CoM
▪ HRTF Baseline Survey 2010
▪ HRTF Program and strategy documents
▪ HRTF Strategic Plan 2011-2015
▪ CCHR Survey on land and housing Issues 2011
▪ Draft of National Housing Policy 2011
▪ Country Report _Special reporters 2009, 2010, 2011
▪ Others
49. Confidence Level: The standard confidence level is
95%. This means you want to be 95% certain that your
sample results are an accurate estimate of the
population as a whole.
Precision: This is sometimes called sampling error or
margin of error. We often see this when results from
polls are reported.
Confidence Interval: We can say that we are 95%
certain (this is the confidence level) that the true
population's average salary is between 1,800 and 2,200
(this is the confidence interval).
52. N
n= ----------
1+(N(e)2
n: Sample Size
N: Population Study
e: Level of precision
Yamane (1960) formula assumes a degree
of variability (i.e. proportion) of 0.5 and a
confidence level of 95%.
SDV Z Z2 p q e e2 n
99% 2.58 6.6564 0.5 0.5 0.01 0.0001 16641
98% 2.33 5.4289 0.5 0.5 0.02 0.0004 3393
95% 1.96 3.8416 0.5 0.5 0.05 0.0025 384
90% 1.64 2.6896 0.5 0.5 0.10 0.01 67
85% 1.44 2.0736 0.5 0.5 0.15 0.0225 23
80% 1.28 1.6384 0.5 0.5 0.20 0.04 10
53. 2
2
e
q
p
z
n
SDV Z Z2 p q e e2 n
99% 2.58 6.6564 0.5 0.5 0.01 0.0001 16641
98% 2.33 5.4289 0.5 0.5 0.02 0.0004 3393
95% 1.96 3.8416 0.5 0.5 0.05 0.0025 384
90% 1.64 2.6896 0.5 0.5 0.10 0.01 67
85% 1.44 2.0736 0.5 0.5 0.15 0.0225 23
80% 1.28 1.6384 0.5 0.5 0.20 0.04 10
n= sample size
p = the approximate proportion you expect to find in the population
q = 1-p
e = the level of precision you can tolerate (plus or minus 10%, etc.)
z = the z-value from a table for the level of confidence you want
54. LQAS
LOT5= 19
LOT1= 19
LOT2= 19
LOT5= 19
LOT3= 19
LOT4= 19
1.
• Can be used locally
• Can provide an accurate measure of coverage (
benchmark)
• Can be used for quality assurance
• is a simple, low cost random sampling
methodology
• Small sample
• Meet the quality standards
• Statistically determined sample size
LQAS = Lot Quality Assurance Sampling
• Developed in the 1920’s
• In 1980’s, method was adapted to measure health program coverage:
• Immunization
• Malaria
• Neonatal tetanus elimination
• Leprosy elimination
• Family planning,
• HIV/AIDS prevention
• In Cambodia World Vision , CONCERN , ADRA, and other
55. Sample size for LQAS
where
n= sample size
p = the approximate proportion you expect to find in the population
q = 1-p
e = the level of precision you can tolerate (plus or minus 10%, etc.)
z = the z-value from a table for the level of confidence you want
n = (1.96)
2
(0.5 x 0.5) / (0.1) 2
n = (3.84) (0.25)/(0.01)
n = 96
2
2
e
q
p
z
n
58. Commune 1: Pres Klang (Control Area)
Name of ADP
Number of Samples Seleced
Name of village Population
Cumulative
population
Sampling
Interval
Random
Number (0-5 month) (15-45yrs)
Mor Seth 914 914 169 105
5 5
274
443
612
781
Okleng Por 769 1683 950
5 5
1119
1288
1457
1626
Sromouve 643 2326 1795
4 4
1964
2133
2302
Krang Doung 357 2683 2471
2 2
2640
Anlong Svay 631 3214 2809
3 3
2978
3147
Total 19 19
59. Methods Source Advantage Disadvantage
1. Desk Study & Literature Review
2. Population Base Survey
3. Qualitative Data Collection
3.1. Key Informant Interview-KII
3.2. Focus group discussion-FGD
3.3. Case Study
3.4. Best Practice
3.5. Observation
3.6. Self-administered questionnaires
3.7. Exit Interview
4. Routine Program Monitoring
62. Male Female Total
Age n 131 91 222
5-9 13.0% 9.9% 11.7%
10-14 72.5% 69.2% 71.2%
15-18 14.5% 20.9% 17.1%
Current school attendant 76.7% 67.4% 72.9%
Level of education n 133 102 223
Never attend school 29.5% 23.1% 26.9%
Primary school 65.2% 67.0% 65.9%
Secondary school 4.5% 9.9% 6.7%
High school 0.8% 0.0% 0.4%
Type of education attended n 129 89 210
Formal education 43.4% 48.3% 45.4%
Non-formal education 11.6% 10.1% 11.0%
Both formal and non-formal education 39.5% 40.4% 39.9%
Current living status n 132 93 225
Residential care 18.9% 17.2% 18.2%
Non-residential care 81.1% 82.8% 81.8%
Status of children n 133 93 226
Orphan 26.9% 32.3% 29.1%
Street children 58.5% 55.9% 57.4%
Children in conflict with the law 6.2% 2.2% 4.5%
Chronically ill parent/caregiver during month of the last 12
months 23.1% 22.6% 22.9%
Abused and exploited children 1.5% 2.2% 1.8%
Children addicted to drugs 0.8% 0.0% 0.4%
Children with physical disabilities 0.0% 1.1% 0.4%
Children infected by HIV 0.0% 0.0% 0.0%
Children living with poor HH 44.6% 38.7% 42.2%
Title does not say:
what, when, where
A mistake of using
row and column
Footnote is
needed
Interpretation
63. Status of orphans and vulnerable in Kamreing and Battambang Province,
Cambodia, 2010
Ref. Definition, MoSVY 2010, An orphan is a child who has lost one or both parents.
A maternal orphan is a child whose mother has died. A paternal orphan is a child whose father
has died. A double orphan is a child who has lost both parents.
Note: Types and Definition of
OVC, MoSVY 2010
Male Female Total
Type of orphan n 35 30 65
Maternal orphan 17% 17% 17%
Paternal orphan 46% 60% 52%
Double orphan 37% 23% 31%
Total 100% 100% 100%
Male Female Total
Overlap risk of children n 133 93 226
Once 45% 48% 47%
Double 50% 51% 50%
Triple 5% 1% 3%
Total 100% 100% 100%
64. 87.5%
77.4% 76.0%
92.0%
Orphan Non-Orphan Orphan Non-Orphan
MPK 2010 CDHS 2005
Percentage of children aged 10-14 who currently attending school
Title does not say: what, when, where
Reference
Footnote is
needed
Interpretation
65. 87.5%
77.4% 76.0%
92.0%
Orphan Non-Orphan Orphan Non-Orphan
MPK 2010 CDHS 2005
%
of
respondent
Type of study
MPK 2010 Orphan
MPK 2010 Non-Orphan
CDHS 2005 Orphan
CDHS 2005 Non-Orphan
Comparison of school attendant among orphan and non-orphan
aged 10-14 between MPK 2010 and CDHS 2005
MPK: Meatho Phum Kohma
CDHS: Cambodia Demographic and Health Survey
Ref. End of project evaluation of MPK in 2010 in Battambang Province
with two district (Battambang and Kamrieng).
CDHS 2005, the nationwide study.
66. Poverty/work
67%
To by my own
16%
Mother/father coming
here
11%
Orphan
2%
DV, abuse and
exploitation
1% Other
3%
Main reason of being away from home
68. KEM LEY | Principal investigator
NHIM DALEN |Consultant
BORAY BORALIN | Data Analyst
UMAKANT SINGH | Advisor
Employment
Rate
Poverty
Line
Income
per capital
• 25% or 1/3 are under poverty
line ( RKR, PVH and ST >40%
(MoP 2010)
• 12% food insecurity to 20% or
2,8 millions (CDRI 2008)
• School drop out rate from 13%
to 22%
• Underweight:28%
• Stunt : 40%
• Wasted : 11%
Source: CAS 2008 and CDHS 2010
• 23% or 3.5 m of young population
• 72 of 100 people aged 15-24 are job
seekers
• 30,000 to 30,000 have entered job
market but 67,000 new job created or
27%
• Reason: Skill mismatch
Source: ILO and CAMFEBA
• Income per capita 285 in
1997 to 593US$ in 2007
• More than 80% are farmers
and 91% are living in rural
areas and account for 48% of
total poor
• Benefits have not been
equitably distributed
• Gaps between rich and poor
(the difference in share of consumption
between the richest 20% of
Cambodians and the poorest 25 &
reveals a dramatic and widening gap in
wealth)
Data Interpretation
Fragility of
Cambodia Development
69. Employment
Rate
Agriculture
Sector
Industrial
Sectors
Service
Sector
• Income: 70% from self
employment income, 27%
from wage and salary, 2%
from transfer received and 1%
from other,
• Labor Forces or working age
(15-64) is 84% or 7.5 millions
• Child under 18 is 41% and
child labor (5-14) is 45%
• Expenditure: 49%, food, 19%
(House, water, electricity, 10%
health and others
CSES 2009, MoP
30-40,000 seek job
but absorption is
67,000 Job/27% or
70. Cambodia Population
13,395, 682 or
young population
Working Age
Population (15-64 )
84% or 7.5 millions
Adult working
Population (64%)
including Old Age
Working Population
Old AgeWorking
Population(…)
Young Population(15-24)
23% or 3.5 Million of 200
per village (14 ,073) or 2000
per c/s )1621 C/S)
23% ofWorking
population
Children (5-17): 4.3
Millions or 35%
1.5 millions (5-14)
were working
children or 45%
Sources: ILO, 2009
CCA 2009
CDB, MoP 2009
CSES 2009
Good Governance and Social
Accountability,TAF 2011, 8 Provinces
Average INCOME: 120 US$ per
month per family
Average Expenditure: 150 US$ per
month per family
71. Increased employment
Young Population
Agriculture Sector
Self-Employment
Access to credit
Farming System
market integration
Reformed School
Curriculum
VocationalTrainings
Minimum Wage Policy
for Workers
( Labor Law)
Industrial Sector
Service Sector
Domestic Workers
Retired and Old Age
Population
Management
Early Retired
Population
Reduced Child Labor
D&D –Practicing Decentralization
EmploymentYoung Population
with CC,Village Councils and other
lines offices of Ministries
USA, Singapore, Thailand
Employment and minimum wage
policy and policy enforcement
108 NGO study: 40, 0000 or equal to all
factory workers
NGO Sector-CARE, Plan Int..
Good Governance
72.
73. Total employment workers (15-64) is 7.5 millions but
Paid employee : 22.8%
Self employed: 51.7%
Unpaid family workers: 25.1%
Employer: 0.3%
75. • Radio : 42.5%
• TV :59.6%
• Video tape/recorders/Players : 28.7%
• Stereo : 13.5%
• Cell phone : 43.8%
• Satellite Dish :1%
• Bicycle : 67.7%
• Motorcycle :49%
• Car : 3.8%
• Jep/Van :1%
• PC : 3.4%
CSES 2009, MoP, RGC
76. Household, Capita-
US$
Cambodia 94 21
Phnom Penh 307 65
Urban 134 54
Rural 79 18
8% are negative income among formers
________________________________________
______
• Self employment income :70%
• Wage and Salary :27%
• Transfer received : 2%
77. Description Cambodia Urban RR
• Food 30$ or 49% 38$ 45.% 27$ or 52%
• Housing/Water/Ele 12$ or 19% 19$ or 23% 8$ or 15%
• Health 5$ or 7% 5$ or 5% 5$ or 9%
• Education 2$ or 2% 2$ or 3% 1$ or 1%
• Other 23% 24% 24%
Total 62$ 85$ 51$
CSES 2009, MoP, RGC
78. Average Monthly
Income
(Rural Area)
18 US$
Expenditure
Average monthly
expenditure per
capita
In Rural Area
51 US$
Average Monthly
Saving per capita
-33 US$ Debt
Landless
Migrants
Child Labor
School Drop Out
SexWorkers
Fragile Population
Others
Poverty
Social
Insecurity