Microsoft word - technical report final jan 2011.doc
Joint Evaluation of Avian Influenza Socialization For Primary Health Care Workers In Central Java and West Java November 30th – December 1st 2010 Sub Directorate of Zoonosis, Directorate of VBDC Directorate General CDC & EH, MOH RI I. Background Avian Influenza (AI) Situation In Indonesia Indonesia has been considered as the country with highest number of confirmed AI cases in human. As per WHO report since the first appearance of this disease in 2005 until December 9th 2010, the country has reported 171 confirmed human cases with 141 fatalities. Graph 1. Total human AI confirmed cases in Indonesia 2005-2010
As shown in the graph 1 above, the peak was occurred in 2006 and gradually declined over the time. In 2010, the total cases found are just one sixth of the total cases found in the 2006. This trend may indirectly be seen as a good progress that has been achieved by the country in AI control program even though many factors may also contribute to the decrease such as the underreporting or undetected cases that may occur. From the distribution mapping, all of the AI cases were identified from Sumatera, Java, Bali and Sulawesi Island with the dense concentration in western part of Java (DKI Jakarta, Banten and West Java Province). In opposite of the declining trend, Indonesia is still rank as one of countries with the highest case fatality rate (CFR) with the overall CFR is 82,46%. This roughly meaning that 8 out of 10 AI patients will ends with fatal outcome. If we look to the trend of CFR over the time as shown in Graph 2 below, it can be seen that the CFR still remins high. This means that the prevention activities to reduce the exposure to H5N1 Avian Influenza virus may result quite significant decline in reducing morbidity ,however the case management is still a major challenge for Indonesia.
Graph 2. CFR of human AI confirmed cases in Indonesia 2005-2010
Based on the analysis done to the data provided by MOH RI, it is shown that out of the total 171 cases, 169 (98,8%) were presented to the health facilities and 2 cases (1,2%) were found during the contact tracing and never presented to the health care facilities. In terms of first presentation to health care facilities after the onset, only 162 cases have the data while 7 cases were unknown. Among the 162 cases, majority of cases (n=115, 80%) first presented to a health care facility in the first 2 days of illness. The majority of cases first presented to private clinics/doctors (38%), midwives’ (17%), private hospitals (14%) and government health care centers (14%). Only 6 cases (4%) that first presented to the AI referral hospital. This is strongly indicated that the role of the private health sectors and health centers are the key factor in the AI case management chain which may define the outcomes. B. Avian Influenza Situation in Central Java and West Java According to the latest release by the MOH on H5N1 cumulative confirmed human cases there were 12 cases recorded from Central Java Province with 11 of them were fatal (CFR 91,6%) while for West Java there were 41 cases with 34 cases were fatal (CFR 82,9%). Based on the same report, West Java is considered as the second rank for province with the highest number after DKI Jakarta with 48 cases while the third is Banten with 31 cases and Central Java as the fourth. This situation has raised much concern particularly to these four highest rank provinces as they are densely populated provinces, and the emerging of H5N1 may put millions of people in the high risk situation from getting contracted with the disease. C. Roll Out of AI Socialization
To deal with the abovementioned problems, MOH with the support of various stakeholders and donor agencies has been implementing the national strategy of AI control programme since the first case emerged in 2005. One of the prominent projects
is INSPAI which is funded by EU through WHO country office for Indonesia. One of the strategies in this project is to strengthen health care providers at the first line level to increase the sensitivity to the disease as well as to improve the skill on case management. The main objective of AI socialization is to improve the knowledge and skills of primary health care workers in the AI case management with the special emphasize on: (1) Case detection, (2) Case Management, (3) Case Referral, (4) Case Reporting, (5) Case Response. At the end it is expected that the morbidity and mortality due to AI can be decreased. The AI socialization in Central and West Java Province was the second phase of the AI socialization activity supported by the INSPAI. The first phase was done in Riau Province. The AI socialization in Central Java and West Java was done in August 2009 till December 2009 to improve the awareness and capacity of public and private primary health care workers on AI case management and control.
II. Evaluation Activity Rationale As part on the national AI control strategy, the AI socializations for primary health care workers have been done in several pilot provinces with the high cases recorded and high risk. These socialization activities were done targeting primary health care workers in public and private facilities with emphasizing on the early detection, case management, referral, reporting and responding to the case finding. In 2008 the socialization was done in Riau province which covered 735 health care workers and in 2009 was done in Central Java which covered 3180 health care workers and West Java with 2693 health care workers. The activity in Riau had been evaluated and the results are showing that there are many improvements achieved in terms of capability of health staffs in detecting cases, treatment, referral and reporting.
In order to see the achievements in Central and West Java, MOH plan to conduct joint evaluation with WHO. This activity is planned to look for the input, process and output components of this activity. By having the result of this evaluation, it is expected that best practices can be documented and gaps can be indentified for the improvement of further activities. Objectives General Objective To evaluate the implementation of AI socialization for primary health care workers and AI control program as general and to provide recommendations for future AI control program activities. Specific Objective
To evaluate the input, process and output of the AI socialization activities
To evaluate the outcome of implementation of AI socialization for primary
health care workers on particular components below:
Scope of evaluation
Scope of the evaluation are but not limited to all activities related the
implementation of AI socialization for primary health care workers activity in Central Java and West Java province covering the input, process and output.
o Provincial AI control team o District AI control team o Sub District AI control team o Puskesmas staffs (Doctor, nurse, surveillance staffs) o Private Clinic staffs (Doctor, nurse)
o Document review o Secondary data collection o Interview o Observation o Report
o The selection of sites is using criteria as shown below:
There are positive cases on animals/poultries and human suspect
There are positive cases on animals/poultries and human
o 4 districts have been selected, 2 in Central Java (Sukoharjo and
Wonogiri) and 2 in West Java (Bandung and Garut) and 1 PHC per district was selected.
o Respondents were selected for province, district and health center level.
Respondents are those who have attended TOT or socialization activity.
o Tools consisted of data collection form and questionnaire o Tools are jointly developed with WHO technical assistance
The data collection form used in this evaluation is the same as the form used in Riau evaluation. The questionnaire was developed but due to the limited time the pre testing was not able to be done. There are 2 type of questionnaire based on the target respondent, (1) For TOT participants (province and district facilitators) and (2) Socialization participants. The observation check list was not able to be developed due to the limited preparation time.
Time November 30th – December 1st 2010 Evaluation team Due to the limited time available, it is decided that two teams were formed to cover Central and West Java in parallel. The core team consisted of 2 staffs from Sub Directorate of Zoonosis and 1 WHO officer for each of province. Initially MOH planned to also involved Sub Directorate of Outbreak and Sub Directorate of Emergency & Evacuation, Dit. Basic Medical Services to join the evaluation as these two sub directorates have a close relationships with the AI programming, but due to the tight schedule in the year end periods they couldn’t join the activity. During the evaluation, the core team also being facilitated by the provincial team and district team during the visit to the health centers. Expected Output
Achievement of the implementation of AI socialization to primary health care
workers impact to AI control program can be identified and properly documented.
Concrete recommendations are provided for the improvement of programs based
III. Results and Discussion The joint evaluation activity has managed to collect some essential data from the two provinces. The data on AI suspect and confirmed cases represents the outcome on the early detection, case management, referral and response aspects while the data from interview reflecting more on the knowledge and practice of the health staffs. The document review mainly looked at the reporting and response for AI suspected/confirmed cases. The observation was used to confirm the findings. The main challenge during the data collection was the incomplete data set of suspected and confirmed AI cases provided by the province and district level. Many of important variables were missing in the form thus creating difficulties in analyzing the outcome and this is a very unfortunate condition that may heavily influences the evaluation outcome. For the qualitative data, team interviewed 12 respondents in Central Java and 6 respondents in West Java. The problem with the low participations in West Java was that many of the respondents attended the socializations were not available for interview. A. Input, process and output of the TOT and AI socialization activities
A.1. Input The analysis will be more focusing on the 5 Ms to look for the sufficiency and appropriateness of the input as the precondition of the socialization activity that may influence the output of the activity. Man power This AI socialization roll out involved 24 provincial facilitators and 35 district facilitators were involved in the roll out in Central Java, while 34 provincial facilitators and 26 district facilitators in West Java. Mostly districts represent by 1 staff from communicable disease control (CDC) unit. All of these 119 facilitators had attended 2 days TOT conducted by the central MOH prior to the assignment. In every batch of the AI socialization, there were 2 provincial and 2 district facilitators assigned to teach 30 participants. This equal to 1 for 7.5 participants where based on the respondent’s interview results was manageable. There was a miss match during the implementation of the AI socialization, where two district facilitators were required during the socialization for each batch while in fact only 1 district facilitator was trained in the TOT. To cope with this insufficiency, district team assigned one staff from the CDC unit to become facilitator in the socialization. Taking the example from Sukoharjo district health office (DHO), they decided to assign the head of CDC unit in to facilitated topics on AI control program policy and other general topics as she has been attending other trainings on AI. Even though this is not the ideal situation and supposes to be a lesson learned but the steps taken by the DHO might be rational and understandable. For the future similar activity, district respondents suggested that at least 2 facilitators from district shall be trained in the TOT. Methods The method of implementation concept for this AI socialization is by optimizing the local resources. The philosophy used in this approach is by improving the capacity of local
staffs it will assure the sustainability of skilled personnel in the province and districts. Coordination was done among central MOH and PHO followed by TOT to train provincial and district facilitators which was organized by central MOH. After the TOT completed, roll out activities were conducted according to the time plan. 106 batches in 35 districts were scheduled in parallel and the PHO organized the provincial facilitators to move parallel in pairs. In the district level, 2 district facilitators also involved and facilitated the process. During the implementation of roll out, 2 times review with the central MOH were done to assure that the activities are on track and technical problems could be resolved. Evaluation meeting was done at the end of activity to evaluate the achievements and challenges. After the socialization roll out, it was expected that participants attended the socialization could share their knowledge to their peers through conducting small group discussion or during the regular activity meeting done in the facilities. From the interview with the participants it was found that some of participants didn’t do the proper sharing with their peers. According to them, this was caused by lack of funding available in the facility to support this activity. The other problem revealed during the interview was the fact that some of participants didn’t have enough self confident to share their knowledge to their peers. This was very unfortunate situation since the concept of information sharing is not merely done through formal meeting, it can be done through informal discussion or through already existing regular meeting in the facility, such as in primary health center (PHC) it is a regular monthly meeting called PHC mini workshop where many problems will be discussed and also there is a session on information sharing. Materials Materials of this socialization are standardized materials developed by central MOH. Reference book for all participants, additional facilitator’s handbook for the facilitators and IEC materials were printed by WHO and distributed to PHO and DHOs by the MOH. Based on the interview with the provincial and district organizers, there was no significant problem with the materials in terms of quantity and the delivery arrangements. Based on the interview with the roll out participants, aside of the written materials, they expect that the training also provides PPE for practices to ensure that participants can identify and use proper PPE during contact with AI suspected patients. Machines This component refers to the equipments or technologies used for the TOT and roll out. The TOT or roll out mostly consists of class room teaching, interactive group discussions and microteaching practice. The provincial and district organizers have no difficulties in preparing the equipments (Computers, LCDs, Flip Charts, room setting, etc). Participants also considered that the equipments used in the training were sufficient. Money The fund for this activity was provided by European Union channeled through WHO Indonesia under the Implementing National Strategy Programme on Avian Influenza (INSPAI) project. For the TOT activity, the fund was transferred from WHO to MOH while for the roll out activities, the funds were directly transferred from WHO to PHO account in several installments. According to the interview with the MOH, PHO and DHO person in charge, the system is acceptable and no particular problems found regarding to the financial arrangement. Based on the interview, participants considered that the amount of per diem provided was sufficient and acceptable.
A.2. Process The analysis of the process will be focusing on the implementation of TOT and implementation of the socialization roll out. It is focused on the three components to look the appropriateness and gaps to be fulfilled. Materials This component is focusing on the quality and appropriateness of the contents. The standardized modules were prepared by the national team which involved several directorates within the MOH. The curricula for the TOT are divided into two days where first day was for the AI socialization contents and the second day was for the facilitation skills. The curriculum for the first day is constructed exactly similar to the curriculum of the one day socialization activity. Based on the confirmation to the MOH, this is designed to familiarize the facilitators with the actual situation that they will find during the socialization roll out. According to the interview with seven provincial and district facilitators attended the TOT, five respondents considered that the materials are good and meet their expectations; three respondents considered the materials are good but need some adjustments such as refining the difficult wordings, reduction of pandemic presentations and addition for the organizational arrangement at PHC level if cases are found; one respondent considered the materials are too much and caused facilitators couldn’t focus on delivering all the materials in very limited time during the one day socialization activity. Two respondents considered that the material for pandemic preparedness was too much and needs to be reducing to avoid confusion for the primary health workers. One respondent also said that they found problem in implementing the socialization. Overall we can consider that the quality of the materials are fine with minor adjustments are needed for improvement. The curricula for the AI socialization activity are fitted for one full day starting from 08.00 – 16.00 with the available materials. From the interview results with respondents attended the socialization activity; four of them considered the quantity and quality of the materials are fine and meeting their expectation, three respondents considered the materials are enough but need some improvement such as the materials need to be more practical, case management must reflect the existing SOPs, materials on recording and reporting must be more detailed and forms must be properly explained. Two respondents considered the materials are too much and caused the facilitators looked in rush and skipped several important slides, this created confusion amongst participants. Respondents Methods For the TOT, the first day of the training was set up exactly the same with one day socialization activity to familiarize facilitators with the setting. In this session, combined methods were used to deliver the materials such as: (1) Meta card session to probe the participant’s knowledge on the topics and to identify area of improvement, (2) Interactive Group discussions and group works to ensure active participation and knowledge sharing among participants, (3) Serial case studies to guide participants through step-by- step quizzes covering case detection, management, referral, recording and reporting and also response to AI suspect cases; (4) class room presentation on particular topic such as policy, epidemiology, pandemic and other formal topics. The second day of TOT consisted of facilitation skill topics which were delivered through class room
teaching and individual microteaching practices. The methods of AI socialization activity are actually similar to the curricula for first day TOT. Most of the respondents considered the combination of teaching methods were very effective especially the case series discussion which stimulated respondents to actively involved in the discussions. Aside of the positive response, there was also concern where in the group discussion where the members are from various education background, medical doctors usually dominating the forum while nurses or surveillance officer usually more passive. This condition was also due to facilitators didn’t actively engage within the groups and stimulate discussions among all members of the group. Time For the TOT, 2 days training was sufficient according to the provincial and district respondents. Aside of the curricula, perhaps this was caused by the fact that many of the respondents have had previous AI training experiences by MOH or other agencies thus they already familiarized with the issues. For the AI socialization, 6 out of 8 respondents (75%) attending the socialization mentioned that one day was not enough for the current curricula and materials. They expected additional time into 2 days or reduction of unnecessary materials to fit with the current timing. This also might be due to many of participants never or less attending AI training before. This results also confirmed by the results of interview with the provincial and district facilitators. A.3. Output
The socialization in Central Java Province covered 3,180 primary healthcare workers in public and private health care facilities in 35 districts/municipalities in 106 batches. The composition of primary health care workers attended the socialization based on the profession were nurses 1,320 (41,5%), medical doctors 1,161 (36,5%), midwives 468 (14,7%) and others 231 (7,3%). For the knowledge improvement, it was found that there was an increase post test average 87,60 from the pre test 77,60 or 12.8% increase. The results of high pre-test mark may indicate that participants already have previous knowledge on AI and the increase of post test could indicate that there was an improvement on the participant’s knowledge. The AI socialization in West Java was done in August 2009 till December 2009. This activity covered 2,639 primary healthcare workers in 93 batches out of 31,287 primary healthcare workers (8.6 %) in the province and 602 health centers out of total 1029 health centers (58%). From the report document review, there were results provided showing the increase of post test against pre test with various results. For the private involvement, there were participants from 126 private clinics attended this activity.
B. Outcome of AI socialization for the primary health care workers
Evaluation of the AI socialization for the primary health care workers outcomes is concentrated to five components (disebutin komponennya). Data for the outcomes were derived from the provincial report which was assumed as the representation of province- wide data on AI suspected and confirmed cases. As mentioned earlier, data provided by both Central and West java are not properly completed. Many of the data were missing
and untraceable. This creates problems and makes the analysis of the results becoming less comprehensive. This incomplete data set could be considered as one of significant findings during the evaluation and need to be improved by both district and provincial health offices under the supervision of MOH. Period of data collection is January 2009 until November 2010 where data from 1 January 2009 is considered as “Pre-Intervention” and data from 1 January 2010 – 30 November 2010 as “Post-Intervention”. Both of data then compared to see the achievements of the intervention. In order to see the achievement for comparation purposes, the analysis of several data from Central Java and Central Java will be done separately. Central Java i) AI Early Case Detection
Cases profile1st January 2009 until 30th November 2010, 36 suspected cases were reported in Central Java. In terms of the geographical distribution, in 2009 10 AI suspect cases were reported from 8 districts. The number was increasing in 2010 with 26 cases were reported from 12 districts (see Graph 1). In the graph also shows that in 2010 after the socialization, there were suspect cases found in 7 districts that didn’t report any cases in 2009. This shows that the increasing number of suspect cases and number of areas that reported cases could indicate the the improvement of knowledge on AI early detection, increase of awareness and confidence of health care workers to establish AI suspect case diagnosis. Graph 1. Distribution of AI suspect case based on districts
In terms of sensitivity, among 36 suspect cases, 2 cases (5.5%) were confirmed as H5N1 (see Graph 2). 1 confirmed case was found in 2009 in Pemalang district and 1 confirmed cases in 2010 in Sukoharjo district. Even though the sensitivity of the case diagnosis is quite low, but it is still worth full considering to the potential impact and the very high CFR of AI cases. Graph 2. Distribution of AI suspect and confirmed case based on year
For to the case distribution regarding to age, most of the cases were occurred on children less than 15 years old (see Graph 3). The mean of age is 21 years old with the youngest is 9 months old and the oldest is 60 years. A significant peak of cases in children under five years old also identified but no sufficient information is available for further analysis, but this is a note that must be considered. In terms of distribution of cases based on sex, male is dominating with 27 cases (75%) compared to female (9 cases, 25%). Graph 3. Distribution of AI suspect case based on Age and Sex
From the data provided by Central Java Province, among 36 cases reported only 20 cases have complete data on date of onset and date of first contact with health care providers (55.5%). Data from 10 cases in 2009 and 6 cases in 2010 were missing. From the 20 cases in 2010, 15 cases (75%) cases presented to health care provider before 2 days after onset, 4 cases (20%) presented within 2-4 days, and 1 case (10%) presented 7 days after the onset (see Graph 4).
Number of Day from onset to first contact
Graph 4. Number of days from onset to the first contact with health care provider
For the type of health care providers for the first contact with AI suspect cases, we found that most of cases (16 cases, 47%) were firstly presented to the primary health centers (PHC) both in 2009 and 2010 periods (see Graph 5). But further analysis found that in 2009, cases firstly presented to referral hospital, private hospital and PHC while in 2010 cases firstly presented to more variety of primary health care providers such as private GPs, midwives, nurses, private clinics and village health post. At this level, usually cases presented were still unspecific and may lead to different diagnosis. Based on the interview results with respondents one of respondents who had experience in diagnosing an AI suspect, she mentioned that primary health care workers usually feel uncomfortable in establishing diagnosis for AI suspect considering to the consequences and refusal from the patient’s family. An experience from Sukoharjo district where the general practitioner was able to establish diagnosis of AI suspect after series of consultations were made to the head of primary health center (Puskesmas), district health office CDC unit, and AI team in Moewardi Hospital. This situation shows that primary health care provider’s role both public and private is important in the screening and early detection of AI cases. Graph 5. Distribution of AI suspect cases based on the type of health care provider for the first contact For the number of days between the onset of disease and the time of suspect diagnosis was established, only 11 out of 35 cases (31.4%) have the complete information to support the analysis. All cases are from year 2010. Out of the 11 cases, only 3 cases (27.2%) were diagnosed as AI suspect before 2 days after the onset while 8 cases (72.8%) were diagnosed more than 2 days after the onset (see Graph 6). 6. Number of days from onset to the time of suspect diagnosis established Case management of AI cases
For the case management aspect of AI disease, this evaluation will look to the two components of outcomes which are % of laboratory testing for AI suspect case and Tamiflu® administration. The laboratory testing is very important as the definitive diagnosis can only be made if the result of laboratory testing is available. For the laboratory testing, all of 10 suspect cases found in 2009 were underwent for PCR examination and resulted as 1 confirmed case (10%). For 2010, among 22 cases underwent PCR examination, 1 case came up as confirmed AI (4.5%) while data for 4 cases in 2010 were missing (see Graph 7). One concern raised by respondents during the interview session is in regards with the delay of PCR results provided by NIHRD as the only authority to officially release the result of PCR testing. In the PHC level this created problems where they need to take immediate action to response or to contain the area if it is confirmed as AI while the result from NIHR often being informed to PHC more than 2 weeks after the case finding. One case in Wonogiri district where one suspect patient died while the final laboratory results from NIHRD has not been informed, they have to face denial and resistance from the family members especially in the funeral arrangements, but when the negative results came after the funeral, the PHC staffs felt that they did a mistake by not allowing the family of the deceased patients to do funeral treatment as a mandatory by moslem religion. Graph 7. Laboratory PCR examination on AI suspect cases
Tamiflu® is the essential part of AI case management. Tamiflu® found to be the most effective anti viral to date for AI cases and the earlier administration will lead to a better outcome if it is given within 2 x 24 hours since the onset of the disease. All of 10 data on the status of Tamiflu® administration during 2009 were missing while in 2010, data on 18 cases out of 26 (69.2%) were available. Out of 18 cases, 13 cases were given with Tamiflu® (72.2%) while 5 cases (27.8%) were not given with Tamiflu®. It is very difficult to tell that there is an improvement in this component as data from 2009 was not available. The available data in 2010 still shows that not all AI suspect cases were given with Tamiflu®. One respondent from private hospital suggested that it is also important to provide Tamiflu® stocks in private hospitals to enable immediate preliminary treatment to AI suspects found in the facilities. During the interview, several respondents forgot the exact dosing of Tamiflu®.
Graph 8. Tamiflu® administration to AI suspect cases Referral of AI cases
As explained earlier that cases mostly had the first contact with the primary health care providers both public and private facilities and then referred to the higher facilities. As per data provided on 20 cases in 2010 with complete data, after the first contact, patients with persistent/worsening symptoms referred or self visited to the non AI referral hospitals (75%) while the rest (25%) had contacted with AI referral hospitals (see Graph 9). This could be at the beginning; the patients were diagnosed as other respiratory of infectious diseases so primary health care providers referred them to non AI referral hospitals. Based on the interview with respondents, all of them can explain the AI referral facilities in their area and also the referral procedures. An issue raised by one respondent form private hospital is in regards with the referral and reporting cases from private hospitals to primary health centers or district health office. Private hospitals need a clear guideline or SOP on the arrangement of referral and reporting. He also indicated that more socialization need for private hospital staffs to increase awareness and enable proper treatment and referral. No sufficient data is available to find out number of AI suspect cases that finally reached the AI referral hospitals. Graph 9. Type of first referral facility Reporting of AI cases
From the interview, respondents from Central Java PHO and DHO in Wonogiri and Sukoharjo districts all mentioned that there are significant improvements in the reporting of AI cases. The improvements consist of:
a) Timing: After the socialization, PHO and DHO received the report of AI suspect
cases from health facilities within 24 hours since the cases were identified. The report firstly made by sms or by phone.
b) Quality of report: After the socialization, reporting health facilities provided better
and more complete preliminary data as needed for clarification by DHO or PHO.
c) Coordination: Improved coordination among DHO and PHCs and other primary
health care providers. Focal person for each of facilities have been established and network has been developed with DHO as the lead. Fast reporting system through sms and phone to designated phone numbers of District Surveillance Officers (DSOs).
Response of AI cases Response to AI suspect case is an epidemiological investigation which is an important step to find comprehensive data to locate the source of infection, the course and possibility of other infections occurred in the surrounding area. This effort involves many stakeholders in various sectors. Results of this response will be used as a based of further public health measures to be applied. Based on the interview with respondents from PHO and DHO, they indicated that after the socialization activity, the response provided is getting better. PHCs are able to conduct initial response to provide basic information to the district response team and become more actively involve in the epidemiological investigation with the DHO and PHO. Within the PHO and DHO themselves, they found that after AI socialization, CDC unit and DSO involved more units such as environmental health, health promotion and medical team to join the epidemiological investigation. From confirmation with the respondents from PHCs and private practitioners interviewed, all of them considered that responses provided by the PHO and DHO are sufficient. West Java i) AI Early Case Detection
Cases profile1st January 2009 until 30th November 2010, 27 cases were reported in West Java. In terms of the geographical distribution, in 2009 20 AI suspect cases were reported from 10 districts the number was increasing in 2010 with 7 cases were reported from 6 districts (see Graph 10). Graph 10. Distribution of AI suspect case based on districts
In terms of sensitivity, among 27 suspect cases, 8 cases (29.6%) were confirmed as H5N1 (see Graph 11). 6 confirmed case was found in 2009 and 2 confirmed cases in 2010 or overall the confirmed cases were one third of the suspect cases diagnosed. Graph 11. Distribution of AI suspect and confirmed case based on year
For the case distribution regarding to age, most of the cases were almost equally distributed in the age group (see Graph 12). The mean of age is 25 years old with the youngest is 9 months old and the oldest is 56 years. In terms of distribution of cases based on sex, female is dominating with 15 cases (55.5%) compared to male (11 cases, 42.3% while 1 case is missing (2.2%). Graph 12. Distribution of AI suspect case based on Age and Sex
From the data provided by West Java Province, among 27 cases reported only 11 cases have complete data on date of onset and date of first contact with health care providers
(42.3%). Data from 2009 shows only 4 cases out of 20 cases (20%) have available data where 2 cases were presented to the health providers less than 2 days after onset and 2 cases were presented between 2-4 days after the onset. Data on16 cases in 2009 were missing. From the 7 cases in 2010, 4 cases (57.1%) cases presented to health care provider before 2 days after onset, 2 cases (28.5%) presented within 2-4 days, and 1 case (14.4%) presented 7 days after the onset (see Graph 13).
Number of days from onset to the first contact with health care provider
Graph 13. Number of days from onset to the first contact with health care provider
For the type of health care providers for the first contact with AI suspect cases, we found that only 7 cases out of 27 cases (25.9%) were having data available for analysis as shown in the graph 14. The 7 cases distributed evenly in several types of health providers.
Graph 14. Distribution of AI suspect cases based on the type of health care provider for the first contact Case management of AI cases
Among 27 cases recorded in 2009-2010, only 8 cases have available for the PCR testing and all resulted as confirmed. Other 19 data on PCR were missing and could not be analyze. For the Tamiflu® administration, among those 27 cases, only 4 cases have complete data while others were missing. For the Tamiflu® administration, during the interview, one respondent from PHC in Garut informed that at the time when they got the AI suspected case, no Tamiflu® stocks were available at PHC as the drugs were stored in DHO Garut. iii) Referral of AI cases
As shown in the Graph 15, only 9 cases (33.3%) are available for the analysis of first referral while data on 18 cases (66.7%) were missing. 2 suspect cases in 2009 were referred to private hospital while 18 cases were missing. For 2010, 5 out of 7 cases (71.4%) were firstly referred to AI referral hospital as expected while 1 case (14.3%) was referred to non referral public hospital and 1 case (14.3%) was referred to private hospital. The high percentage of cases referred to the AI referral hospital in 2010 may indicate an improvement in case referral even though is not conclusive due to the incomplete data. Graph 15. Type of first referral facility Reporting of AI cases
For the reporting, the interview results found that after AI socialization, the case reporting from health facilities became faster. The DHO has established direct reporting system through sms or by phone similarly to that applied in Central Java. v) Response of AI cases
From the interview, respondents from PHO and DHO mentioned that after AI socialization activity the responses provided to the AI suspect cases is improving. The response is getting better, faster and involving more stakeholders. The primary health
care providers interviewed also informed that the responses provided by DHO and PHO are sufficient and also involved community participations. C. Best Practices
During the evaluation, team found that there are several best practices identified as follows:
1. Utilization of local district budget (APBD) for the expansion of socialization activity
to cover more primary health care workers such as in Demak district with 2 batches (60 nurses and midwives) and in Wonogiri 5 batches (170 midwives, nurses, health promotion and CDC staffs).
2. Adoption of socialization methods in this activity for health trainings/socialization
with other subjects such as Dengue and Malaria to primary health
3. Integration of AI early detection socialization to puskesmas meeting/ cadre
4. Establishment of case reporting network through designation of focal person
amongst PHO, DHO, Health Facilities and every villages with high risk of AI
During the evaluation, team found that there are several challenges found as follows:
1. The materials provided are too much for one day socialization, according to
respondents, the quantity of some materials such as pandemic preparedness is need to be reduced and more focus on case detection and management.
2. The number of District facilitators trained (1 person/district) found to be
3. Lack of monitoring from central MOH during the implementation of activities 4. Lack of support for participants attended the socialization to conduct further
socialization to their peers/colleagues in the health facility (mainly lack of financial support from their facilities)
5. Several primary health care workers interviewed could not explain in detail about
few subjects asked mainly on the case management (Tamiflu® course and dosing, infection prevention and control, etc)
6. Limited data available in the activity report documents reviewed to enable
analysis of the private health care providers involvement
7. Incomplete data available in provincial health office and District Health Office on
8. Inconsistency of data such as in Wonogiri, until 30 November 2010, 2 suspect
cases were reported for 2010, while in the PHO Central Java reported only 1 case for 2010.
IV. Conclusion and Recommendation
1. TOT and AI socialization for primary health care provider activities in Central
Java and West Java Province have been concluded timely as planned in August to December 2009 covering all districts in both provinces.
2. In the input, all of the components evaluated showing good achievements in the
practice except of in the human resource where the number of district facilitator was lacking.
3. In the output; (1) for the attendance rate, Central Java achieved 100% while
West Java achieved 94.6% attendance rate. Participants invited to the socialization were consist of medical doctors, nurses, midwifes and epidemiologist from public and private health care facilities. The post test results showing improvement against the pre test results.
4. There are several achievement for the outcomes as shown below:
i. Early Case Detection: (1) Improved awareness and confident among primary
health care workers on conducting screening for cases with the suspicion of AI, (2) In Central Java more districts were reporting cases while in West Java there was reduction of districts reporting cases in 2010, (3) Missing data made the analysis of the number of days between onset and diagnosis of suspect established was not possible to be done in both provinces.
ii. Case Management: (1) For the PCR testing, missing of data made the
analysis to see the improvement made was not possible (2) For the Tamiflu® administration, it is found that there were still AI suspect cases that not given with Tamiflu® in Central Java during period of 2010. From the further interviews, several of respondents couldn’t explain the case management in details particularly in the course and dosing of Tamiflu®.
iii. Referral: For Central Java, after the first contact with health facility, most of
the patients identified in 2010 were referred to non AI referral hospitals while in West Java most of the patients identified in 2010 were referred to AI referral hospital. Based on the interviews with respondents, it is caused by the general symptoms appeared at the initial phase which lead to other respiratory diseases.
iv. Reporting: In Central and West Java, improvement of reporting system has
been reported by respondents in terms of timing, quality of reports and better coordination among stakeholders. However the documentation and recording of data should be improved.v. Response: In Central and West Java, improvement of case response has
been reported by respondents. More active involvement of primary health care workers in the epidemiological investigation also being noted. More
stakeholders are involved in the epidemiological investigation compared to prior of the socialization.
1. Reduce the materials for socialization and rearrangement to fit with one day
2. Increase the number of district facilitators trained with minimum 2 facilitators and
reduce the proportion of provincial facilitators and interchange the district facilitators to cover other districts.
3. Improve monitoring from central MOH during the implementation of activities to
ensure quality process and result of socialization.
4. Monitor the follow up actions of AI socialization in each province to ensure the
multiplier effects of the activity for responding to AI.
5. Support advocacy to Provincial and district government to support the expansion
AI early detection socialization using local budget especially to support socialization done by participants to their colleagues in their facilities
6. Conduct refresher socialization to refresh and update the participants on the
subjects focusing mainly in the case detection and case management
7. Improve data collection and data management for suspected and confirmed cases
at the district and provincial level focusing on completeness of all important variables for further analysis
8. Synchronization of data among district and province level to avoid inconsistency 9. Conduct Independent external evaluation to measure the outcome and impact of AI
socialization and deliver feed back/ input to provinces to improve their performance in following up the result of the socialization.
This is a summary of benefits for your Pharmacy Plan. The document will be used to reflect how your Pharmacy plan will be loaded (Pharmacy plan deductibles, out-of-pocket maximums, copays and annual maximums do not integrate with the employer medical program unless elected as part of the CIGNA Choice Fund product) CIGNA Healthcare Pharmacy Customer Worksheet Tektronix, Inc. CIGNA
Guide Specification SECTION 08 71 00 - DOOR HARDWARE PART 1 - GENERAL NOTE: All door hardware for public rest rooms shall be stainless steel. SUBMITTALS Product Data: Submit product data including installation details, material descriptions, dimensions of individual components and profiles, and finishes. Samples: Submit samples of exposed door hardware for each type indicat