Thailand Intervention : online data entry. ProblemHow to manage 1.Data assistants enter incorrect data (due to human error and wrong data sent from malaria.

Slides:



Advertisements
Similar presentations
Giving Feedback. The right and the wrong. >> giving feedback
Advertisements

Unit 7: Course Summary – Putting It All Together.
Supervision Training: some lessons from Kenya Dr Pamela Lynam / Nancy Koskei JHPIEGO-Johns Hopkins University Chris Rakuom – DSRS-Ministry of Health.
Health Management Information System (HMIS) KAPIL GHAI State Coordinator RMNCH+A.
What happens after submission? Sadeghi Ramin, MD Nuclear Medicine Research Center, Mashhad University of Medical Sciences.
1 Receipt Acknowledgment Letter (RAL) for Form 471.
Enquiry Progress Give your vendor code In case of incorrect vendor code / no id registered with us, you will get this error message In case of correct.
LEVERAGING TECHNOLOGY TO IMPROVE QUALITY PSI\TANZANIA Authors: Anya Fedorova, PSI; Niza Sikana, PSI; Dr. Joseph Mashafi, PSI, Dr. Edgar Lusaya, PSI, Dr.
Indicators, Data Sources, and Data Quality for TB M&E
Country/Network Admin
Overview of Cambodia Laboratory System & Organizational work flow Structure Dr. Lek Dysoley CNM 8-12 April, 2013.
RHEA Phase 1 Storyboard. Purpose This provides a high level overview of the solution, in a simple story format.
Complex Care Management In Practice Dunblane Tuesday 6 th November 2007.
Copyright 2010, The World Bank Group. All Rights Reserved. Training and Procedural Manuals Section A 1.
1 CPMKL: 2010, Q3 GSTS Action Planning Responsiveness of Staff in Fulfilling Request (Front Office) Key PrioritiesRoot CausesActionsAction By Target Completion.
Additional Structure Exercise 2 ANSWERS NB. As not whole case study was given some of these answers may not be within the text.
Introduction to AFRS Toolbox
Getting Hired The Hidden Components of a Successful Job Search:
1 Module ON-SITE SUPERVISION OVERVIEW. 2 Content Overview What is on-site supervision? Advantages and disadvantages of on-site supervision Organization.
Schedules Students should go directly to Advisory Tuesday morning Student will receive their schedule (on blue paper) in Advisory Please make sure to follow.
Report of Collections Class
Copyright © 2007 Pearson Education Canada 1 Chapter 13: Audit of the Sales and Collection Cycle: Tests of Controls.
Baltimore Update: SSuN, Challenges in implementation Clinic-based dataset: – Existing clinic data system (Insight™) – Minimal barriers to electronic.
Monitoring, supervision and quality control IDSP training module for state and district surveillance officers Module 11.
@ 2012, Cengage Learning Analyzing Transactions LO 4b – Discovery and Correction of Errors.
Chapter 7 Quiz on next Tuesday Nov 3.  Let’s review how trial balance is made: 1. Journal entry is made in journal. Debit amount and Credit amount must.
P1 External Quality Assessment (EQA) Proficiency Testing.
Posting from a Cash Payments Journal to an Accounts Payable Ledger
Objectives for today’s lesson Recap from last weeks lesson - journals Recap from last weeks lesson - journals Understand different types of errors: Understand.
Assuring Safety for Clinical Techniques and Procedures MODULE 5 Facilitative Supervision for Quality Improvement Curriculum 2008.
Head Start of Greater Dallas Accident Prevention Training Objective Loss Trends Accident Prevention Processes Accident Reporting Accident Investigations.
ICT Infrastructure Used By Organisations Additional Exercise ANSWERS.
©SHRM 2007SHRM Weekly Online Survey: June 6, Inappropriate Use of Technology in the Workplace Sample comprised of 398 randomly selected HR professionals.
Quality Child Care What to look for. Staff The staff is well trained and caring Good ratio of staff to children Serious about their job.
CENTURY 21 ACCOUNTING © 2009 South-Western, Cengage Learning LESSON 6-4 Finding and Correcting Errors on the Work Sheet  Finding and correcting errors.
Strengthening SME system for national programmes moving from transmission reduction to elimination phase Cambodia.
Minnesota Department of Health Assisted Living Home Care Provider Licensing Surveys Surveys Conducted May – October 2005 © Care Providers of Minnesota.
Accident recording and reporting. JD September 2011.
SOP for Malaria Cambodia. SOP for case-based Malaria surveillance PCDACD - To confirm all suspected malaria cases from Community Based, Public Health.
Data Verification and Validation
Exercise 1: Improve the organization of supervisory visits Purpose: Answer questions about supervision and plan how to improve organization of supervision.
SOP for malaria case surveillance
Conducting supervisory visits and feedback
CH. 6 SELF CHECK QUIZ ARE YOU PREPARED FOR THE TEST?
Review POSTING Refer to link: Note%20-%20Posting.html Note%20-%20Posting.html.
Module Three: Identifying your Patient in SIS. Introduction – Search for 1 st T Specimen The Search for 1 st T Specimen screen is used to access your.
INTRODUCTION TO INFORMATION SYSTEMS FOR IMMUNIZATION SERVICES IPV Global Workshop March 2014.
3/16/20161 Education Service Center Region 10 Professional T & E Instruction Presentation
Review POSTING Refer to link: Note%20-%20Posting.html Note%20-%20Posting.html.
Performance Appraisal Presented by: Nur Hasanah, SE, MSc.
Session 6: Data Flow, Data Management, and Data Quality.
Our paperless pickup and delivery system Visit our Website
The Visiting Supervisor Model What’s the evidence?
BSHS 375 GENIUS Peer Educator/ bshs375genius.com FOR MORE CLASSES VISIT
 Many different parties rely on the information produced by accounting systems  There needs to be a high degree of accuracy  Any errors must be discovered.
M – Health ( CommCare App ) Pilot Project American Refugee Committee RAI - Malaria Program.
CENTURY 21 ACCOUNTING © 2009 South-Western, Cengage Learning LESSON 6-4 Finding and Correcting Errors on the Work Sheet.
BUS 210 Week 8 Individual Developing Good Business Sense Check this A+ tutorial guideline at 210/BUS-210-Week-8-Individual-Developing-
Overview of Quality Assurance
11 ii. Develop a plan for aDSM
IFSP Aligned with the Early Intervention Data System
RHEA Phase 1 Storyboard.
Surveillance. Public Health Approach Surveillance What is the Problem ? Problem Risk Factor Identification : What Is the Cause ? Intervention Evaluation.
Pharmacy Use Case.
First Year Experience – Software Support Tools
DepEd e-FORMS Automated Form Templates in Excel for Elementary and High School Alfonso C. Corpuz, Physics Teacher September 10, :00 pm.
Review POSTING Refer to link:
Streamline, Simplify, Organize, Automate
RECRUITING Staff and Student
Baseline Household Survey (CAPI) High-frequency Data Collection (CATI)
Presentation transcript:

Thailand Intervention : online data entry

ProblemHow to manage 1.Data assistants enter incorrect data (due to human error and wrong data sent from malaria post) - Data assistants should check and verify paper –base report before entering. - Data assistants should report to his/her supervisor about poorly filled reports. -Data manager send immediately feedback for any error occurred. 2.Data assistants enter wrong data due to frequently changed report format -Surveillance unit should inform ( Through sending revised SOP for minor changes) or retrain ( for major changes ) for data assistant

Exercise 1: Improve the organization of supervisory visits problem: Data assistants enter incorrect data (due to human error and wrong data sent from malaria post) WhereWhat and who to be supervised Supervisory methods When: Frequency Who will conduct sup. visits Other interventions that could be supervised at the same time Malaria post -How to record the data in paper-based blood record form - Head of Health centre and Head of VBDU - On the job visit -Whenever error detected or twice monthly as routine work -Head of health centre -Head of VBDU - Supervise case management by MP

WhereWhat and who to be supervised Supervisory methods When: Frequency Who will conduct sup. visits Other interventions that could be supervised at the same time VBDU- Head of Health center and Head of VBDU On the job visit Problem: Data assistants enter incorrect data (due to human error and wrong data sent from malaria post)