Health Managers Modules for Immunization

Transcription

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2 Information management in Immunization Health Managers Modules for Immunization Module compiled by UNOPS-NIPI and NCHRC-NIHFW, Delhi Prepared for Block Junior Child Health Managers

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4 Module 5: Addressing demand side issues in Immunization 3 Foreword The Universal Immunization Program, launched in 1985 for reducing deaths and disabilities due to vaccine preventable diseases in the country, has received a special impetus through the National Rural Health Mission (NRHM). The strengthening support provided by NRHM includes funds, resources, strategic guidelines and contractual manpower for program management. Since 2005, when the NRHM came into effect, there has been an increasing trend in Immunization coverage and quality. Child Health managers introduced to manage and oversee child health and immunization in select districts of low performing states, as well as other health managers from non-medical background introduced through the NRHM, was found to have an increasing role in the Immunization Program. However they often came with no prior knowledge, experience or skills related to management of the Immunization program. Their roles and therefore their requirement in the program were identified as being a mixture of technical, supervisory and managerial. This set of modules covers many of these aspects, and have been developed for self as well as collective learning by program managers and supervisors. The modules have been compiled from existing literature related to the Immunization program and health management available in India with the Ministry of Health and Family Welfare as well as with UNICEF, WHO, USAID and PATH. The materials have been adapted to meet the requirements at the primary levels of health program management in the country, particularly at the sector, block and district levels. The National Child Health Resource Center (NCHRC) at the National institute of Health and Family Welfare (NIHFW) has worked closely with national trainers in Immunization at the NIHFW and the Immunization officer of United Nations Office for Project Services, Norway India Partnership Initiative (UNOPS-NIPI) in developing these modules. The pilot testing of these modules has been conducted in Orissa, Bihar and Rajasthan involving the district, block and sub block level managers and supervisors along with select state level trainers, and their feedback has been incorporated. UNOPS-NIPI has been instrumental in identifying the need for improving program management at implementation levels as an important step to achieve enhanced program coverage and quality, and have also provided the required support for the development of these modules. We hope that this set of module will prove to be useful in enhancing the capacity of managers and supervisors at implementation levels for improving quality and coverage of lmmunization. Dr. Kaliprasad Pappu Director, UNOPS-NIPI LFA New Delhi Prof. Jayant K. Das Director, National Institute of Health and Family welfare New Delhi

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6 Module 5: Addressing demand side issues in Immunization 5 Table of Contents Abbreviation...7 I. Introduction: key concepts in data management II. Overview of data flow processes III. Basic recording tools in Immunization IV. External data in Immunization: monitoring data, evaluation surveys V. Analysis and use of data for action Final Assessment References Facilitators Guide... 47

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8 Module 5: Addressing demand side issues in Immunization 7 Abbreviations Abbreviation ADS AEFI ANC ANM ASHA AVD AWW CES CHC DH DHQ DLHS DIO DPMU DPT DT GoI HMIS ILR JE MCH MCHN MCP MCV M& E NFHS NRHM OPV ORS PCM PHC PNC Extended form Auto disable syringes Adverse Effects Following Immunization Antenatal checkup Auxiliary Nurse Midwife Accredited Social Health Activist Alternate Vaccine Delivery Anganwadi worker Coverage Evaluation Survey Community Health Center District Hospital District headquarter District Level Household Survey District Immunization Officers District Program Management Unit Diphtheria Pertussis Tetanus Vaccine Diphtheria Tetanus Government of India Health Management Information System Ice-Lined Refrigerator Japanese Encephalitis Maternal and Child Health Maternal and Child Health and Nutrition Mother and Child Protection Measles containing Vaccine Monitoring and Evaluation National Family Health Survey National Rural Health Mission Oral Polio Vaccine Oral Rehydration Solution Paracetamol Primary Health Center Postnatal checkup

9 8 Health managers modules on Immunization Abbreviation RI SC SC/ST SDH TT VHND VPD VVM WHO UIP VVM Extended form Routine Immunization Sub center Scheduled Caste/Tribe Sub divisional Hospital Tetanus Toxoid Vaccine Village Health and Nutrition Day Vaccine preventable disease Vaccine Vial Monitor World Health Organization Universal Immunization Programme Vaccine Vial Monitor

10 Health managers modules for Immunization Module 6: Information management in Immunization Module 5: Addressing demand side issues in Immunization 9 Objectives By the end of the module, the health managers will be able to Understand key concepts in data management systems Have a overview of data collection, compilation, reporting, flow and use Know of the available tools and systems for reporting and recording immunization and VHND activities Use data for action at implementation levels for program improvement Contents: I. Introduction: key concepts in data management II. Overview of data flow processes III. Basic recording tools in Immunization IV. External data in Immunization: monitoring data, evaluation surveys V. Analysis and use of data for action

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12 I. Introduction: key concepts in Module 5: Addressing demand side issues in Immunization 11 data management Do you find data as a whole lot of numbers and facts that come to you as monthly reports and you are happy to forward it with least effort and joy as possible? Data and information can be the manager s best tools and friends if used appropriately. With a little effort and interest, good data will be able to keep you at the top of events and make you an effective manager. In this section we are going to learn how data and information can be interesting as well as rewarding for a good manager. Every day data: What are the instances where you inter act with data in your day to day life? Do you enjoy the data...are they meaningful to you? Let us look at the following examples of every day data that we enjoy or use: 1. ICC Cricket World Cup 2011 / Scorecard India v Sri Lanka India won by 6 wickets (with 10 balls remaining) ODI no /11 season Played at Wankhede Stadium, Mumbai 2 April day/night (50-over match) Sri Lanka innings (50 overs maximum) R M B 4s 6s SR WU Tharanga c Sehwag b Khan TM Dilshan b Harbhajan Singh KC Sangakkara* c Dhoni b Yuvraj Singh DPMD Jayawardene not out TT Samaraweera lbw b Yuvraj Singh CK Kapugedera c Raina b Khan KMDN Kulasekara run out ( Dhoni) NLTC Perera not out Extras (b 1, lb 3, w 6, nb 2) 12 Total (6 wickets; 50 overs; 246 mins) 274 (5.48 runs per over) Fall of wickets1-17 (Tharanga, 6.1 ov), 2-60 (Dilshan, 16.3 ov), (Sangakkara, 27.5 ov), (Samaraweera, 38.1 ov), (Kapugedera, 39.5 ov), (Kulasekara, 47.6 ov)

13 12 Health managers modules on Immunization Bowling O M R W Econ Z Khan (1w) S Sreesanth (2nb) MM Patel (1w) Harbhajan Singh (1w) Yuvraj Singh SR Tendulkar (3w) V Kohli India innings (target: 275 runs from 50 overs) R M B 4s 6s SR V Sehwag lbw b Malinga SR Tendulkar c Sangakkara b Malinga G Gambhir b Perera V Kohli c & b Dilshan MS Dhoni* not out Yuvraj Singh not out KMDN Kulasekara run out ( Dhoni) NLTC Perera not out Extras (b 1, lb 6, w 8) 15 Total (4 wickets; 48.2 overs; 230 mins) 277 (5.73 runs per over) Fall of wickets1-0 (Sehwag, 0.2 ov), 2-31 (Tendulkar, 6.1 ov), (Kohli, 21.4 ov), (Gambhir, 41.2 ov) Bowling O M R W Econ SL Malinga (2w) KMDN Kulasekara NLTC Perera (2w) S Randiv TM Dilshan (1w) M Muralitharan (1w) Toss Sri Lanka, who chose to bat Series India won the 2010/11 ICC Cricket World Cup Player of the match MS Dhoni (India) Player of the series Yuvraj Singh (India)

14 Module 5: Addressing demand side issues in Immunization 13 Did you follow up with the 2011 World Cup Cricket? Did you check out the scores every moment during the finals? Were you computing data like run-rate, strike rate, bowling average while enjoying the match? Were you happy when India won the world cup? Did Dhoni deserve the player of the match and why? Did you enjoy the cricket data? Can you also think of other instances where data becomes more important to you than a game? Think of these two data sets: 1. The half yearly and yearly report cards of a child in your family. What would be the importance of a good or poor report? Would the family do something about the child s education if the report cards show poor performance? 2. The election results in your state and country. Would the government elected and it s performance have a bearing on your future and civic amenities available to you? Do you follow up the electoral reports of your state during election time? How do you interpret the results? Remember correct and reliable data of activities pertaining to your work and life are important to you. You should have the ability to understand and use relevant data effectively. However, for data to be effective, it needs to have several qualities like accuracy, reliability, completeness, timeliness and integrity. You would need to know about these before you can use data effectively: 1. Data Quality Accurate data have minimal errors and bias. Accuracy is also known as validity. For example, accuracy can be compromised through transcription errors that can occur if data are inaccurately entered into the system. These are usually accidental mistakes and can occur if someone records information inaccurately or enters the information into a computer database incorrectly. Accuracy can also be affected by data that are not complete, timely and precise. Accuracy may also be directly affected by manipulation for other reasons. In case you doubt the correctness of the data, it may be a good idea to verify it, before relying on it for decision making.

15 14 Health managers modules on Immunization 2. Reliability Data are reliable when they are measured and collected consistently over time. The reliability of data depends on having an information system with consistent protocols and procedures. Reliable data require standardized, written instructions for data collection. A program s data collection procedures should not change according to who is using them, which site is using them, when they are used, or how often they are used. In addition, procedures to correct data errors or deal with missing or incomplete data must be consistent across different sites and time periods. 3. Completeness Completeness means that an information system captures all of the eligible persons, services, sites, or other units that it is supposed to measure. The resulting data should represent the complete list of persons, services, sites and other units and not just a fraction of the list. Completeness is affected by: The extent to which source documents include all relevant and needed information for reporting, The extent to which all sites have reported information to higher aggregation levels, Timeliness of reports to higher aggregation levels. For example, a program site s data will be incomplete if it does not include information about all of the clients served, all of the services provided to the client, or all of the activities undertaken. A program s aggregate data will not be complete if data from only 90 of 100 sites are included. 4. Timeliness Data are timely when they are reported to the next level in time to meet reporting deadlines. On time implies that the data reported were able to be used in the summary report prepared by the next highest reporting level. For example, reports from service sites are due to the intermediate level on the 15th day of the month for the previous month, and the report from the intermediate level is due to the M&E Unit on the 20th day of the month, and the M&E Unit prepares its report by the last day of the month. Each of these deadlines must be met for the data to be timely. Timeliness is affected by: The rate at which the program s information system is updated The rate of change of actual program activities When the information is actually used or required

16 Module 5: Addressing demand side issues in Immunization 15 Data should become available on a frequent enough basis so that program managers, regional managers, and national or international managers can use the information to make management decisions. 5. Integrity Data have integrity when the information system is protected from deliberate bias or manipulation for political or personal reasons. An independent review of the data can help determine whether the integrity of the data has been compromised. Knowing that the data will be subject to an independent review may deter deliberate manipulations of the data. Another way is by frequently validating the data during field visits. Similar concepts: The concepts of data, information, and knowledge are often used interchangeably though they are not synonymous. Often collecting more data is regarded as creating more knowledge, which is a wrong assumption. Data: It is the raw material in the form of numbers or characters and it is without context. Information: It is a meaningful collection of facts/data with reference to a context. Knowledge: When information is analyzed, communicated, and acted-upon it becomes knowledge. Figure below illustrates these concepts with example. Data: No. of pregnant women in an area who received skilled birth assistance Information: % of pregnant women who received skilled birth assistance & % of pregnant women who were left out Knowledge: Why are some pregnant women able to receive skilled birth assistance? Why some pregnant women were left out? Who were left out? What are the issues related to access to service? A. Data Element A data element refers to the name of a particular event or factor that must be counted or measured. In context of HMIS, a data element is a record of health event or health related event. Example During a particular month: 1. Number of pregnant women who received an antenatal check-up. 2. Number of children below five years who were affected with measles. 3. Number of female children born The first example is a record of a service delivered, second is a health event, and third is health related event. All these three are data elements that are recorded in a register by the service provider. Later, similar events for the month are aggregated and reported in specified reporting formats.

17 16 Health managers modules on Immunization B. Indicator An indicator converts raw data into information that can be interpreted and used for decision-making. Raw data generally does not make much sense unless one data element is seen in relation to other data element. In simple words, an indicator is derived from data elements so that it becomes information that can be used for programme monitoring, management, and action. Indicators facilitate Comparison of performance among areas/groups. Track progress made towards a target. Converting data elements into indicators To derive an indicator, identify a data element as the numerator, divide it by another data element which represents the context and multiply it by a factor (which is usually but not always 100). Thus, an indicator is also a relationship between two data elements. Example Data element: Total number of children in month age group who have been given Measles Vaccine = 360 Numerator: Total number of children given measles=360 Denominator: Total number of children in the age group 12 to 23 months=450 Multiplying factor: 100 Indicator: Percentage of children in month age group given Measles vaccine=80%.

18 Module 5: Addressing demand side issues in Immunization 17 II: Overview of data flow processes Data for immunization is generated at the implementation and primary management levels. For example; beneficiaries vaccinated would be derived at implementation level and vaccine stocks available would be derived from the ILR point. A set of periodic data flows from Health sub-center, PHC and CHC upwards towards the district, state and National levels, such as the HMIS reports. However data is also connected along time, representing the events that occur along a continuum. It is therefore important to identify individual beneficiaries and follow them up in time. For example, tracking the antenatal care received by a pregnant woman, the details of her delivery and birth of the child. This is followed by periodic vaccination of a child till he/she achieve full immunization status and also receives booster doses. This is essentially also captured in data capturing systems like the parent/mother-child-tracking-systems (PCTS). An identification number which is unique to a beneficiary is often helpful in tracking him/her from the beginning of services received till its logical conclusion. This number is usually generated at the point of first contact of the health worker with the beneficiary. This number is used as a reference every time the beneficiary avails a service.

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20 Module 5: Addressing demand side issues in Immunization 19 III: Basic recording tools in Immunization The Routine Immunization program has a system of recording immunization data. To ensure systematic reporting and recording, a variety of tools such as formats and registers are used in Immunization. Each level of reporting has a set of important formats and registers. Level Persons concerned Type of record/report Beneficiary Pregnant women, young children Maternal and child protection card* Immunization card* Village level ASHA / Aganwadi worker Tracking / immunization register* Due list * Counterfoil of Immunization card* Session site level ANM Comprehensive (MCH) Register* Tally sheet * Blank Immunization cards* HMIS subcenter report* PHC level SD Hospital/ Sadar Hospital/ Urban Hospital/ dispensary/ NGO or Private clinic Report compiler / data operator Comprehensive (MCH) Register * HMIS report* Vaccine stock register# Injection stock register# Equipment stock register# Temperature record register# District level RI report compiler / data operator HMIS report# Part C accounts register# Vaccine stock register# Injection stock register# Equipment stock register# Temperature record register# *these reporting/recording tools are dealt with in this module # these reporting/ recording tools are dealt in other modules Records: Are usually in forms of registers and are maintained at a certain location or with a certain person or functionary. These are not sent forward. Reports: These are compiled on a periodic basis and sent to the next higher level for review and action. 1. Maternal and child protection MCP card This is a five or six fold card which is issued to pregnant women when she first registers her pregnancy with a health worker. The identity details and registration number (A) is given during the first visit when this MCP card is handed to the pregnant woman is given to her. Following this the pregnant woman is to bring this card during all her subsequent visits with the health worker.

21 20 Health managers modules on Immunization When explained well the woman will be able to follow up with each health intervention provided during her pregnancy, child birth and motherhood with the use of this card. Following every visit she should also be told what services were provided and when to come for the next visit. A B C D E Each part of the card and its use is described here: (A) The identity details including registration number are given in this section. Sometimes a unique identity number based on mother child tracking system or the mother child register may also be given. This would help in tracking the mother and child through the software or register for subsequent services received. (B) Care given during antenatal visits. (C) Precautions and danger signs in pregnancy (D) Care to be given to infants (E) Care for children 1-3 years (F) Immunization schedule and status (G) Growth monitoring of child using new WHO standards.

22 Module 5: Addressing demand side issues in Immunization Immunization card The Immunization card contains the immunization history and status of pregnant women and the child born following the particular pregnancy. This may still be used in places where the mother child protection card has not been introduced.

23 22 Health managers modules on Immunization The immunization card is important for many reasons It serves as a reminder for parents to return to the clinic for the next dose. It helps the health worker determine a mother and child s immunization status Enables the health worker to monitor an individual pregnant and child s progress towards full immunization It also tells about the ante natal care received by the pregnant women and the vitamin A and Pulse Polio drops received by the child It is useful to derive information during coverage surveys The immunization card is also sometimes called the mother and child health card (MCH card) or mother and child health and nutrition card (MCHN card). The card can be separated (torn off) into two parts: the main card and the counterfoil (Adh katti). While the main card is retained by the beneficiary, the counterfoil is retained by the health worker or the community link worker (ASHA). Tickler boxes or tracking bags can be used to make effective use of the counterfoils. The counterfoils can be arranged month-wise or village-wise and serves as a reminder to the health worker of the beneficiaries who have doses due in a forthcoming session. Tracking Bag A cloth tracking bag, comprising of fourteen pockets, is a simple, easy-to-use tool for follow up of beneficiaries by filing counterfoils of Immunization cards. It provides the basis of preparing a session-wise name-based list of due beneficiaries for sharing with the AWW/ ASHA/Mobilizer and helps estimate the logistics required. Provide one tracking bag for every SC/ village/urban area. The first twelve pockets indicate each of the twelve months of the year. Counterfoils are filled in the pocket indicating the month when the next vaccine is due. For example, if a child receives DPT1 in January, DPT2 is due in February. Therefore, the counterfoil is updated and placed in the pocket for February. When the DPT2 dose is given in February, the counterfoil is updated and moved to the pocket for March, when DPT3 is due. The thirteenth pocket is meant for placing counterfoils of beneficiaries who have left the HW s catchment area or have died. The fourteenth pocket is for filling counteroils of fully immunized children. At the end of each month, cards remaining in the pocket for that month represent dropouts who need to be followed up or moved in the next month s pocket. In the absence of a tracking bag, counterfoils for each month can be tied with rubber bands and labelled.

24 Module 5: Addressing demand side issues in Immunization Tally Sheet While recording individual vaccine doses administered is an important practice, this is not often followed in most places/ session sites. Why do you think tally marking after each vaccine dose administered is important? In your area, how do vaccinators count the number of vaccines administered during an outreach session? As a manager doing spot-checks how can you verify whether the reports given are consistent with the vaccines actually administered? Varieties of tally sheet: While some tally sheets contain very basic information like a tally mark for every type of vaccine dose administered, other tally sheets have more detailed information. The one below shows several other information available such as details about session held, utilization of syringes and vaccine vials, any Vaccine preventable disease (VPD) or Adverse effects following immunization (AEFI) detected during the session. In some places name based tally sheets are also used. In these the names of the beneficiaries are recorded along with the vaccine doses and other services (ANC, PNC) they have received. These are later entered into a computer or data base and used to track services given to each beneficiary as well as detect drop outs.

25 24 Health managers modules on Immunization 4. The tracking / immunization register This register goes by different names in different places (maternal and child register, service delivery register, tracking register, immunization register) but the essential function remains the same. In this register, each row (sometimes an entire page) is dedicated to a single beneficiary with services to be given marked in columns (or cells). As the beneficiary receives the service/ or vaccine dose, the date is entered at the corresponding place. This goes on until the entire range of services and due vaccine doses are given to the beneficiary over a period of time. In some registers the first entries are the identification details an eligible couple and thereafter, services given to them are chronologically traced through pregnancies, deliveries, infant growth, post natal services, childhood services, use of family planning methods and finally to adolescent care. Other registers tend to focus more on the pregnant woman and the infant. This tracking register is usually maintained by the health worker at village/outreach or sub center level. However, some community mobilizers involved mobilizing beneficiaries for outreach services also maintain similar registers to help them determine which beneficiaries to mobilize on what date. Examine the tracking register of your area and comment on the different services which are recorded in it. Can you enlist the beneficiaries due for the next outreach session from a register of a health worker in your area? How many drop-out beneficiaries (who have missed more than 1 opportunity in the past to avail any available service) can you identify from a register filled by one of the health workers in your areas?

26 Module 5: Addressing demand side issues in Immunization 25 The unique identification number of a beneficiary receiving Reproductive and child health services is usually generated by the local health worker and noted in this tracking register. This same number is continued along with each service provided to the beneficiary. This number is also used in the mother and child protection card and its counterfoil. This number will help in going back to the same page in the register/ entry sheet in the computer data so that continuity is maintained in entering the data of a single person in a single row/line list. 5. Due-list This is a simple compilation or a list of beneficiaries who are due for services or vaccines in the next outreach session. This can be compiled with the help of the tracking register, the counterfoils of cards or even computer generated for the line-list data set (as envisaged in mother and child/ parent and child tracking systems). In usual practice, this due list should be compiled at the end of a given outreach session for the next session to follow at the same site (which is usually 1 month after). It should be drawn up together by the health worker and the mobilizer. The due list for immunization should include the following: 1. The subsequent dose of any vaccine to be given in series e.g. for TT1 administered that day, the due list should have TT2 for the same beneficiary on the next visit. Also DPT2 and 3, OPV2 and 3 following DPT1 and 2, OPV 1 and 2 respectively. 2. The vaccine for which the beneficiary is due as per the age achievable by the next session date, e.g. Measles as the infant will have completed 9 months by next session date, DPT booster as the child will have completed 16 or 60 months by next session day 3. The mobilizer would also be responsible to add during the course of the month (between two session days in the locality) to this due list any newborn child, any newly detected pregnant woman and any visitor to the village who by the next visit would be eligible for a vaccine dose.

27 26 Health managers modules on Immunization 6. HMIS reports The entire series of health services delivered at various levels such as outreach, facility and home should be captured in the form of relevant data at the end of each month. The health management information systems has identified these relevant data sets for each activity so that information which can lead to appropriate review and action is available at each decision making level. The health manager at different levels should ensure regularity; completeness and reliability of data collected from field and facility and entered at block and district levels. They should also be able to verify and retrieve data for analysis on a periodic basis. The following table shows the lists of forms in the HMIS and their levels and periodicity of reporting. MoHFW has revised the forms and reporting the forms and reporting procedures for HMIS S. No. A Form No. Periodicity Submission Date Submission Channel Reporting forms from State & UTs to GOI (These forms are to be send to GOI) 1 NRHM/GOI/1/A Annual Consolidated 30th April 2 NRHM/GOI/2/Q Quarterly Consolidated 20th of Month following respective quarter State Govt. to GOI 3 NRHM/GOI/3/M Monthly Consolidated 20th of following month B Reporting forms within State Govt. (These forms are NOT to be sent to GOI) 4 NRHM/SGI/1/A Annual 15th April Internal for 5 NRHM/SGI/2/Q Quarterly 20th of Month following respective quarter State Govt. C Reporting forms within Districts (These forms are to be sent to State Govt.) 6 NRHM/DHQ/1/A Annual 5th April District to 7 NRHM/DHQ/2/Q Quarterly 10th of Month following respective quarter State Govt. 8 NRHM/DHQ/3/M Monthly 10th of following month Remarks

28 Module 5: Addressing demand side issues in Immunization 27 S. No. D Form No. Periodicity Submission Date Submission Channel Facility reporting forms within Districts (These forms are to be sent to District HQ) 9 NRHM/DH-SDH- CHC/3/M Monthly 5th of following month District Hospital to District HQ 10 NRHM/PHC/3/M Monthly 5th of following month PHC to District HQ 11 NRHM/HSC/3/M Monthly 5th of following month Health subcentre to District HQ Remarks The forms are the same for DH, SDH, CHC and can be used inter changeably While HMIS is a comprehensive data set which provides for data regarding a large range of health information (services, infrastructure and even outcomes), the section on immunization is presented here for the health managers knowledge and as an example of the HMIS data. M6 Child Immunization 22 Number of Infants 0 ti 11 months old who received the following 22.1 BCG 22.2 DPT DPT DPT OPV0 (Birth Dose) 22.6 OPV OPV OPV Hepatitis-B Hepatitis-B Hepatitis-B Measles Total number of children aged between 9 and 11 months who have been Fully immunized (BCG+DPT123+Measles) during the month (a) Male (b) Female Total{(a) to (b)} 23 Number of children more than 16 months who received the following 23.1 DPT Booster 23.2 OPV Booster 23.3 Measles Mumps, Rubella (MMR) Vaccine 24 Immunization Status 24.1 Total number of children aged between 12 and 23 months who have been Fully immunized (BCG+DPT123+Measles) during the month (a) Male (b) Female Total{(a) to (b)}

29 28 Health managers modules on Immunization M6 Child Immunization 24.2 Children more than 5 years given DT Children more than 10 years given TT Children more than 16 years given TT Adverse Event Following Immunization (AEFI) (a) (b) Abscess Death (c) Others Total{(a) to (c)} 25 Number of Immunization sessions during the month 25.1 Sessions planned 25.2 Sessions held 25.3 Number of sessions where ASHAs were present M7 Number of Vitamin A Doses 27 Administered between 9 months and 5 years 27.1 Dose Dose Dose 9 M8 Number of cases of Childhood Diseases reported during the month (0-5 years) 28 Measles 29 Diarrhoea and dehydration 30 Malaria 7. Collecting and compiling reports HMIS reports collected from Health sub centres on a monthly basis (or sometimes session wise reports collected from outreach session sites on outreach days) need to be compiled at Block/ PHC/ ILR point level (e.g. Urban Hospital/ DIO office which manages Urban Immunization) before making the final report of the entire area. A simple checklist can be used to note timeliness and completeness of reports. Late reports should not be rejected or ignored instead they can be submitted as a supplementary report with an explanatory note. Timeliness and completeness of HMIS reports from Health sub centres Name of Health Block: XYZ PHC:ABC Year:2011 sub centre April May June July August Sept Oct Nov Dec A B x C x D L E Timely (by 5th of next month) Complete : Timely x: report not received L: report received late

30 Module 5: Addressing demand side issues in 29 IV: External data in Immunization: monitoring data, evaluation surveys It is possible to get data from several sources to oversee any health program. No particular data set can be wholly complete, accurate and reliable, as such when a number of data sets are available for the same program, triangulation of data from different sources but related closely in time and place can give a closer picture of field realities. While administrative coverage reports are the mainstay of information for the Immunization program too, two more sets of data can be made available to review the program periodically. The two sets of data other than administrative data (UPI reports/ RIMS or HMIS reports) for the Immunization program in India are: 1. Reports from monitoring and supervision visits 2. Reports from evaluation surveys 1. Data from monitoring and supervisory visits: The current monitoring system recommended by Government of India for Routine Immunization helps in generating data about the quality of session sites, particularly outreach sites and completeness of coverage for various vaccines through a convenience household visit of beneficiaries. At session site some of the key indicators generated are: Sessions where ANM/vaccinator was present as per microplan (%) Reason for Session not held Utilization of AVD Sessions with available Vaccines (BCG,DPT,OPV, MCV,DT,TT, Hep B, JE) Diluents (for BCG, MCV, JE) Syringes (AD: >0.1ml & 0.5ml, Disposable). Unusable vaccines Sessions with logistics available(%) Vit A, PCM, ORS Hub cutter, RI cards, R&B bags Sessions where DPT being given on outer mid-thigh. Mobilisation of beneficiaries by ASHA / AWW / others Use of vaccine carrier & ice packs Vaccine safety (frozen, unusable VVM, expired vaccine etc.) Injection safety (AD syrg.; site of inj) Use of Hub Cutter after every injections

31 30 Health managers modules on Immunization Proper delivery of vitamin A Four key messages conveyed to parents of beneficiaries ANM touching part of needle while injecting vaccine Sessions where for child vaccinated (%): Tally sheet filled up RI card provided/updated From the household visits the following indicators can be derived: No of Children in months fully immunized (%) Children receiving age specific antigens Reasons for not getting the due vaccine Drop out and left out rate Reasons for drop out & Left out Areas where RI sessions are not held in last 3 months However since the supervision and monitoring is done through convenience sampling and no scientific methodology, the data must be interpreted in relationship to both the numbers and the prevalent style of monitoring. Reasons for drop-out can be elicited through the monitoring data as shown below. Drop-out: Elicited Reason Source : H-t-H Monitoring, Pilot: March-2009 Below are some select indicators from supervision and monitoring formats which can be used monthly to review immunization progress across sectors. Immunization Sector1 Sector2 Sector3 Sector4 Number of ILR points monitored by all managerial personnel combined Number of ILR points found with above buffer levels of all vaccine/diluents/syringes throughout the month Number of ILR points found with proper disposal of Immunization wastes

32 Module 5: Addressing demand side issues in Immunization 31 Immunization Sector1 Sector2 Sector3 Sector4 Number of ILR points found with any expired vaccine/frozen T series or Hep B/ VVM unusable stage Number of session sites monitored for which monitoring formats has been submitted Number of session sites found held as per micro plan Number of sites found where ASHA is mobilizing beneficiaries Number of session sites with all other logistics Number of parents given 4 key messages following vaccination Number of 0-23 month children verified Number of 0-23 month children verified who received all due vaccines Percentage of cancelled sessions for Immunization reorganized during the month Percentage of blocks with dropout monitoring chart updated for the month Achievements this month for immunization A table such as the one above can be compiled sector-wise or supervisor wise at a block level each month. The same can be used at higher levels such as districts / divisions/ states to monitor performance of the next lower unit. When data related to each indicator is collected and analysed over several months, a trend showing improvement / no change or worsening of the program may become evident. Some graphs like the one below may be generated. Month wise all Vaccine (BCG, DPT, OPV, Measles & TT) availability at the site

33 32 Health managers modules on Immunization 2. Data from Evaluation surveys: Evaluation surveys to assess the coverage and quality of Immunization services are carried out on a periodic basis. National level surveys such as NFHS, CES and DLHS all provide information about coverage through various vaccines. While NFHS and CES usually provide data for state level coverage, DLHS gives coverage at district levels too. Smaller surveys are also undertaken by states, districts and research agencies. Some of the more commonly followed methodologies while undertaking such surveys are the cluster sampling methods (e.g. 30 cluster sampling) and lot quality assurance methods. However, real time data is difficult to derive from survey figures primarily because the children surveyed for immunization status are of the age group months which is reflective of the immunization program one year before the period of the survey. Large scale surveys also take time in data compilation and dissemination. However surveys like DLHS, NFHS and CES follow the rigours of scientific research and methodology and their results are generally well accepted. Moreover as these surveys are conducted over a periodic basis the trend in coverage also gives an indication of the progress of the immunization program over the years. Below is a comparative table of Immunization coverage observed during surveys of several states: Trend of Evaluated Full Immunization coverage in several states of India

34 V: Analysis and use of data for action Module 5: Addressing demand side issues in Immunization 33 Indicators An indicator is a data element placed in a given context so that it becomes information that can be acted upon and can be used for programme monitoring and management In order to manage health services well and for attainment of optimum health of beneficiaries and users, Health Programme Managers at various levels need to know. Who gets sick? What illnesses are most common? Where do these people live? They also need to know: What health services are provided? Who uses these services? What is the quality of these services? How much do these services cost? Health indicators can help answer these questions. Indicators also help to track and monitor progress towards a target/objective and reflect changes over time. Indicators are used to alert Managers to potential problems, possible causes for these problems, and additional questions that can be asked. While indicators are useful tools for measuring change, they also have some limitations such as: Indicators rarely indicate specific cause of the problem and possible solution. An isolated indicator by itself does not mean much. It needs comparison over time and across facilities and Districts to show trends in order to be useful. Thus, an indicator can be defined as a data element placed in a given context so that it becomes information that can be acted upon and can be used for programme monitoring and management. Indicators can be classified into following groups: a. Input indicators: indicate resources invested in the system, e.g., number of doctors per 100,000 people. b. Process indicators: indicate activities of the health system, e.g., percentage of doctors trained in safe delivery skills. c. Output indicators: indicate achievements made in specific health strategies e.g. percentage of women who received 3 ANCs. d. Outcome indicators: indicate achievements of a health programme or health system. e.g institutional delivery rate, breastfeeding in one hour rate etc. e. Impact indicators: indicate achievements in health status of particular group of people e.g. Maternal Mortality Ratio, Infant Mortality Rate, Total Fertility Rate etc. There are no rigid boundaries between these classifications and sometimes an indicator can fit in more than one classification/category depending on how it is viewed. These indicators can be used on monthly, quarterly and annual basis by Programme Managers for monitoring/ management of health services.

35 34 Health managers modules on Immunization Immunization Coverage Indicators Indicator Definitions Numerator Denominator Multiplying factor Full immunization coverage rate BCG Coverage rate DPT3 Coverge rate OPV3 Coverge rate Measles Coverge rate Actions to Consider % of children aged between 9 and 11 months who have been fully immunized (Child given one dose of BCG i.e. DPT1,2.3; three dosages of polio i.e. OPV 1,2.3 and a dosage of Measles) The percentage of live births that received BCG within one year The percentage of children who received their 3 doses of DPT The percentage of children under 1 immunized with 3 doses of OPV The percentage of children who received their measles dose (normally at 9 months) Total Number of children aged between 9 and 11 months who have been fully immunized BCG dose under 1 year DPT3 dose under 1 year OPV3 dose under 1 year Measles dose under 1 year Estimated children below 1 year Estimated children below 1 year Estimated children below 1 year Estimated children below 1 year Estimated children below 1 year Suggested level of use 100 National, State, District and Block 100 National, State, District and Block 100 National, State, District and Block 100 National, State, District and Block 100 National, State, District and Block Every district and sub-district management team should monitor these indicators annually or semiannually and look for trends and consistencies. Identify areas with low coverage and ensure supplies and promotion activities. Monitor associated indicators such as immunization drop-out rates. Periodically of indicator Annual, semiannual Annual, semiannual Annual, semiannual Annual, semiannual Annual, semiannual Immunization Drop-outs Rate Indicator Definitions Numerator Denominator Multiplying factor BCG - Measles dropout rate DPT3 - Measles dropout rate % of children who dropped out of immunization schedule between BCG dose measles dose The percentage of children who dropped out of the immunization schedule between the third dose of DPT (normally at 14 weeks and the measles dose normally at 9 months) Total number of children (0-11 months), given BCG immunization - number of children given measles Number of children given DPT3 - number of children given measles Number of children given BCG Number of children given DPT3 Suggested level of use 100 State and District 100 State and District Periodically of indicator Annual Annual

36 Module 5: Addressing demand side issues in Immunization 35 Immunization Drop-outs Rate Indicator Definitions Numerator Denominator Multiplying factor Rationale Action to consider A dashboard Suggested level of use Periodically of indicator A high drop out rate means that either quality of immunization services is very poor or mothers have poor access to immunization services. A negative dop out rate can occur if there is a stock out of the early vaccines and good supply of the late vaccines Ensure best possibly quality of immunization Ensure child tracking with immunization card BCC to mothers on importance of finishing immunization course Ensure constant availability of vaccine All people who drive cars understand the importance of a dashboard. A few selected indicators like speed, miles covered, fuel status and temperature are good enough to understand the car s performance. Likewise, if some indicators related to the immunization program are selected well and placed on a wall- chart or computer program, it would help in understanding the progress of the program. As a program manager what are the key indicators you would select to monitor the progress of the immunization program in your area? What would the sources of your data be? At what frequency would you monitor the progress? How would you be able to identify weak performing sub-centers? Compiling coverage data In order to analyze data, it is necessary to compile data properly by area. The table below provides a simple way of compiling and analyzing data. 1. List each geographic area or community that you serve (column a). 2. List the target population numbers for infants <1 year (column b). 3. Enter the number of doses of vaccine administered to the target age group during the preceding 12-month period, for example for DTP1, DTP3, measles (columns c to e).

37 36 Health managers modules on Immunization Area Name Compile population, immunization coverage data in the previous 12 months Target <1 year Doses of vaccine administered Immunization coverage (%) Unimmunized (No.) DPT1 DPT3 Measles DPT1 DPT3 Measles DPT3 Measles DPT1- DPT3 Analyze problem Drop-out rate (%) Identify problem a (see Table 7.4 ) Categorize problem according to Table 7.4 b DPT1 Access Utilization Categoty 1,2,3 or 4 a b c d e f g h i j k l m n o p Prioritize area Priority 1,2,3... Calculate Immunization coverage 4. Calculate immunization coverage in the preceding 12-month period, for example for DTP1, DTP3, measles, (columns f to h). You can also add coverage for other vaccines administered including TT1, TT2+, HepB1, HepB3 etc. However, for the sake of simplicity, the table above uses DTP and measles only. 5. To calculate immunization coverage, divide the total number of immunizations given over the preceding 12-month period by the target population. Use the formula below: Annual coverage for childhood immunizations (BCG, DPT3, OPV3, Measles, HepB3, Yellow fever, Hib3) and Vitamin A 6. Calculate the number of unimmunized infants for a specific vaccine or pregnant women for TT 2+, for example: number of infants who have not received measles vaccine (column j). Unimmunized infants with measles vaccine (j) : target population (b) minus infants who received measles vaccines (e) Calculate dropout rate 7. Calculate annual dropout rates, for example: DTP1 DTP3, DTP1 measles (columns k, l), or for any other combination of vaccines you have selected.

38 Module 5: Addressing demand side issues in Immunization 37 Identify and categorize problem for each area you serve (columns m, n,o) 8. Specify in column m the quality of access (good or poor) depending on the DTP1 coverage ( good is defined in this exercise as DTP1 coverage > 80% in the target age group, and poor corresponds to a DTP1 coverage in the target age group of< 80% ; however, you may decide to use lower or higher cutoff coverage rates). 9. Specify in column n the quality of utilization (good or poor) depending on the dropout rates Good is defined in this exercise as a dropout rate in the target age group < 10%, and poor corresponds to a dropout rate in the target age group > 10%; however, you may decide to use lower or higher cut-off dropout rates. 10. Refer to the first table which shows how to determine problem category 1, 2, 3, 4. Write the number of the problem category (1, 2, 3 or 4) in column o. Use your data to prioritize areas (column p) Assign the highest priority to the area that has the most number of unimmunized infants, and not necessarily the lowest coverage in terms of percentage. Figure 7I gives an example. The number of unimmunized infants by area is shown in columns i and j of the Table. Once you have compiled data and have assigned priorities to the different areas you serve. In the next section you would need to plan corrective action based on these priorities. Can you take the previous year s data of your sectors and compile a prioritization table?

39 38 Health managers modules on Immunization Immunization data case study/exercise Purpose: This will enable the block manager to identify problems and prioritize action in consultation with other stake holders. Please read step carefully and complete the task as per given steps. Exercise: Steps: 1. In your district, collect basic information from your blocks Tabulate the information received as follows: Name of sector/hsc DPT1 coverage in doses in and (%) DPT3 coverage in doses in and (%) Compute the drop-out rates and drop out beneficiaries of the sectors using the following formula: Number of DPT1 to DPT3 drop out beneficiaries= DPT1 coverage in doses-dpt3 coverage in doses Then prioritize the sectors on basis of drop-out rates and numbers. The higher rates and numbers will have higher priority: Sector DPT1-DPT3 drop-out rate DPT1-DPT3 drop out number Priority The sector with the highest priority (number 1) is to be selected for the remaining tasks. 2. Discuss and enlist the internal and external causes of the high drop out. Prioritize the problems Causes of high drop-out rate / number in selected sector It is important not to attempt to make a LONG list of problems, but instead, focus on identifying those problems that have higher implication to drop-out rates. For each problem indicate their relative implication to drop-out rates (e.g. low, medium, high). After this, the group should identify problems with priority from 1-5 from the entire list below. PROBLEM DOMAIN HEALTH SERVICES PROBLEMS Problems having origins in service delivery and related to health manpower, infrastructure, capacity, practices and resources/ supplies. COMMUNITY PROBLEMS Problems having origins in community perceptions, knowledge, attitude, practices, demand and involvement. Possible problem reasons. Relative implication (low/ med/high) Priority (1, 2, 3 )