Influence of Health and Vital Statistics in Control of Epidemic

Influence of Health and Vital Statistics in Control of Epidemic

Chapter One

Objective of the Study

The general objective of this study is to assess the influence of health and vital statistics in the control of epidemics in the University of Benin Teaching Hospital.

The specific objectives include:

To Determine if Health Information Managers at the University of Benin Teaching Hospital have a good knowledge of Health and Vital statistics in the control of epidemic
To Determine if Health and Vital statistics have been collected following the required procedure and using the correct tools in the University of Benin Teaching Hospital
To Assess the effectiveness of health and vital statistics in the control of the epidemic in UBTH
To Examine the challenges associated with the collection of health and vital statistics in the study area.

CHAPTER TWO

LITERATURE REVIEW

DETERMINANTS OF PRACTICE AND UTILIZATION OF DATA AND HEALTH AND VITAL STATISTICS SYSTEM

Various authors in available literature have posited regular training and human resource development of health personnel on HMIS as the major factor in updating their (health personnel) knowledge and thus improving and sustaining their practice and utilisation of the HMIS.^54-56 Other identified factors are the level of education of health personnel and health personnel’ duration on the job,^{59, 60} awareness of their job description, provision of incentives and remunerations for the additional work of HMIS,^{66, 68} cumbersome nature of entering data into the HMIS registers manually as well as electronically into the software,^59,60,68 lack of feedback on data collected, availability of supervision, fear of repercussions for poor entry of data,^68,69 inappropriate (multiple existing tools) data collection instruments and software, lack or poor health infrastructure to support the HMIS and lack of specific budget for HMIS.^73-79

TRAINING

Training was the most common determinant identified in most studies as key in affecting the knowledge, developing a corresponding attitude and sustaining the corresponding practice and utilisation of the health information system at the Primary Health Care facilities. The lack of training and its subsequent negative effects was as observed in an in-depth interview survey conducted in Pakistan in 2004 to explore the perceptions of thirty health managers regarding HMIS which revealed that the last refresher course was held almost ten years previously and was a major factor identified by respondents for the poor knowledge and practice of HMIS.⁵⁴

Knowledge and practice were improved when training was regular and updated in line with changes in the system, whether in terms of health personnel or software for maintaining the health information system, this was observed in a 2008 cross-sectional study in Pakistan to study the existing HMIS being practiced in the Basic Health Units of Tehsil Taxila, where training was regular and ongoing. In this study, 76% of the persons got regular training on HMIS data entry while 24% never had any kind of formal training. Eighty percent of the cases had on-the-job training while 20% had never been involved in training activities. It was also found that there was no schedule for the training of the staffs that were involved in HMIS data entry. Training was key to the 68% practice of filling OPD registers and 96% satisfaction with the reporting HMIS forms among workers.⁵⁵

In a survey done in 2012 to evaluate the Indian Health And Vital Statistics system, findings revealed that, different levels of staff involved in the HMIS had inadequacies as far as training and man power development efforts were concerned. This also applied to key functionaries at district and state level and ultimately affected practice of data entry since they had poor understanding of the registers.⁵⁸ This was not the case in a 2011 rapid assessment study done in Bihar, India among 17,900 respondents to assess the effect of training on knowledge of the minimum data sets and HMIS, which revealed that 97.5% of the auxiliary nurses and midwives (ANMs) and 89% of data entry operators (DEO), block health managers (BHM) and data processing managers (DPM) had undergone trainings.⁵⁹

Almost all the categories of the respondents perceived these trainings as useful. On further probing on the specific aspects of the usefulness of training, about half of the ANMs reported that it enhanced their understanding of various data elements and cleared doubts in filling revised HMIS reporting format. About half of the BHM reported that timeliness has improved due to the training while one third of them opined that the training helped them in clearing many doubts on various data elements.⁵⁹ These were similar findings to another Indian study conducted in 2009 utilizing, in-depth interviews on 26 respondents to evaluate the effectiveness of a computerised HMIS in rural India. This study revealed that the current health staff had been trained in data collection, computerised HMIS and their utilization at the time of its installation. It improved their knowledge, practice and efficiency during service delivery and a training manual was developed for periodic training on data and computerised HMIS.⁶⁰ The selection technique for the various categories of respondents was not stated in this study.

In the African continent, similar findings were observed as in other developing countries of the world, as seen in a study conducted in 2009 to assess the utilization of health information systems at district level in southwest Ethiopia among 332 heads of district health facilities where 170 (51.2%) reported that there was lack of training and technical support on HMIS and 91 (27.4%) complained of lack of computer skills. Twenty nine percent of those who had poor understanding of data collection and the HMIS forms complained that this was because they did not have any training support.⁶⁶

CHAPTER THREE

RESEARCH METHODOLOGY

STUDY DESIGN

A cross-sectional analytical study design was utilized for this study. A cross-sectional analytical study design was utilized in presenting study findings. It went beyond the basic proportions of expressing the ‘who’, ‘where’ and ‘when’ and investigated the association between the possible risk factors (‘how’ and ‘why’) for the outcome and the outcome itself. It investigated the relationship between predictor variables (working experience of respondents) and outcome variables (their knowledge of HMIS). It is useful in identifying these associations which can then be further studied with cohort study and randomised controlled trials.^91,95

STUDY POPULATION

The study population consisted of:

Health care personnel who handled health data and participated in the facility-based survey and the focus group discussion sessions. These included: Nursing Officers (and midwives), Community Health Officers, Community Health Extension Workers (senior and junior), Pharmacy and Laboratory Technicians and Monitoring and Evaluation Officers (health records/disease surveillance notification officers) involved in the day-to-day facility activities and handling of data and HMIS tools in PHC facilities in Edo State.

Stakeholders which included, Primary Health Care Coordinators and Medical Officers in Primary Health Care facilities in Edo State (In-Depth Interview sessions), and policy makers; a representative (an Assistant Director) of the Head of HMIS unit of Department of Health Planning, Research and Statistics, Edo State Ministry Of Health (Key Informant).
Primary Health Care facilities. These were solely Government owned PHC facilities.

CHAPTER FOUR

RESULTS

A total of 432 respondents (comprising 390 health personnel who participated in the facility based survey and 42 FGD participants); 6 Medical Officers of Health/Primary Health Care coordinators and 1 Key informant were interviewed for the purpose of the study. Also, 35 and 12 Primary Health Care facilities were assessed using an observational checklist and a data quality assessment tool respectively.

CHAPTER FIVE

CONCLUSION AND RECOMMENDATION

CONCLUSION

Majority of the studied health personnel in the Primary Health Care facilities had a poor knowledge of the National Health And Vital Statistics System and slightly above five percent had good knowledge. Most of the health personnel had positive attitude and less than one-tenth had negative attitude.

Most of the health personnel handling health data had poor practice of the National Health And Vital Statistics System and only about one-twentieth had good practice. The major determinants of good practice and utilization of the National Health And Vital Statistics System at the health facilities was type of community and practice of the NHMIS respectively.

A few of the health centres surveyed were capable of operating the National Health And Vital Statistics System activities. None of the health centres had internet connectivity and budget specific for NHMIS, one-twentieth had stand by generating set and about three-quarters of the health centres had focal persons handling data.

In terms of the overall data accuracy, Pentavalent3 vaccination data had major data quality issues, antenatal care data had minor data quality issues and institutional birth data had major data quality issues.

RECOMMENDATIONS

Based on the findings from the study, the following recommendations are made with the hope that they will go a long way in control epidemic in health facilities in Edo State.

GOVERNMENT

Specific trainings with specific interests on target cadres and categories of health personnel like the older health personnel and the heads of health facilities be organized by the HMIS unit of the State Ministry of Health. This should change the orientation of these sub-groups of health personnel, improve their interpersonal communication skills and confidence-building which overtime will enhance the provider’s performance, participation, ownership of the HMIS and production of quality HMIS data.
The National Primary Health Care Development Agency’s robust training manual and curricula, designed to strengthen the skills of the PHC health workers in NHMIS data handling, could be used to help providers deal with their own beliefs and biases by introducing these training manuals into the undergraduate training curricular of the various health related specialties including medical students, School of Health Information, School of Health Technology and the Nursing and Midwifery School. The manuals should also be made available at every point of development of the PHC health worker, either at school, during training and at the PHCs; this will encourage self development on the NHMIS.
Trainings and updates on NHMIS should be decentralized and structured according to job specifications. Zealous and dutiful health personnel should be chosen on the basis of merit and a written and oral interview to determine focal persons of HMIS at the health facilities. These focal persons should be regularly trained and updated in training of trainers’ session, so they can regularly cascade these training at their health facilities.
The trainings and updates organized by the focal persons should be given supportive supervision by the LGA HMIS unit to ensure correctness of information delivered by the focal persons to all other health workers at the health facilities. The benefits of quality data and its utilization by all health personnel to make informed health decisions should be emphasized and reiterated during training sessions.
It should be made statutory that all health facilities should analyze the health data they collect and display same on the walls of their health facility and appropriate feedback sent to the next reporting level. These analyzed data should be discussed during facility meetings and ways to improve on them proffered. Defaulting health facilities should get more supportive supervision and encouraged/reoriented to see data collection/HMIS as an integral part of the daily PHC activity. Health facilities who utilize their health data should be encouraged/rewarded financially and in kind with health facility/HMIS equipment that they may lack and will require to improve upon their work (so long as the data they have collected and utilized is verifiably reliable). Also, recognition of health personnel for hard work in form of awards of excellence will be beneficial.
The SMOH should initiate collaborations with the private sector to improve upon the HMIS infrastructure. By taking advantage of their need to fulfill their corporate social responsibilities, multinational organizations such as the Global System of Mobile Communications companies like MTN, Airtel, Globacom and Etisalat, should be collaborated with to provide reliable, dependable broadband internet connectivity at the three senatorial districts especially in hard to reach health facilities and communities. Sustainable power supply and basic HMIS and IT stationeries can also be donated by these organizations.
The determined verification factor should be utilized to correct the data produced in order to ensure and improve on the current data quality.
Strong political will on the part of government at all levels is a prerequisite to achieving anything relating to the HMIS implementation at all levels. The orientation of the Government needs to change as regards the relevance and indispensability of quality health data for health and economic planning. The HMIS Unit of the State Ministry of Health should organise collaborations with related government agencies and departments like the department of Economic Planning to educate and reorient their knowledge and understanding on the relevance of quality health data.

HEALTH PERSONNEL

The heads of facilities and all other health workers should be given targeted and structured reorientation trainings that will emphasize on benefits derivable from the information generated by the HMIS. It could help them re-orient their service by adopting a more empathetic client-centred approach, adjusting their attitude and introducing a convivial ambiance at health service outlets based on the feedback of their clients and the data they have collected.
The health worker handling data should be encouraged to involve themselves in self development educational programmes that will improve upon their service delivery skills, their ability to summarize and analyze health data with the use of statistical methods and develop/improve upon their emotional intelligence in order to improve their general communication skill and interpersonal relationships. These can be achieved by organizing short conferences/updates that will develop their management and leadership skills. Also an avenue for them to easily access health information in form of small in-house libraries (stocked with NHMIS manuals and IT publications) or e-libraries via provision of reliable IT-infrastructure will go a long way in their self improvement.

REFERENCES

AbouZahr C and Boerma T. Health Information Systems: The Foundation of Public Health. Bulletin of World Health Organisation. 2005; 83(8): 578-83. < http://www.who.int/bulletin/volumes/83/8/578.pdf. Accessed 12th March, 2013.
Onwujekwe O. Inequities in healthcare seeking in treatment of communicable endemic diseases in Southeast Nigeria. Social Science & Medicine. 2005; 61(2), 455-463.
Idowu B, Adagunodo R and Adedoyin R. Information technology infusion model for health sector in developing country: Nigeria as a case. Technology and Health Care. 2006; 14(2), 69-77.
Ayodele C. Health Information Systems in Nigeria: A review of literature. Journal of Global Healthcare Systems. 2011; 1(3), 1- 26.
World Health Organisation. Everybody‘s business: strengthening health systems to improve health outcomes. WHO’s Framework for Action. Geneva, World Health Organization. WHO, 2007.
Ebonyi state University/World Health Organization. Health Policy and Systems Research Project Policy Briefs on Health Systems Building Blocks. Strengthening the Generation/Strategic Use of Health Information and Evidence for Health Systems Operations and Policymaking in Nigeria. http://www.who.int/alliance hpsr/projects/alliancehpsr_snppolbriefshssnigeria.pdf. WHO, 2010. Accessed 28th August, 2013.
Vriesendorp S, Lourdes de la Peza, Cary Peabody P, Seltzer B, O´Neil M, Reimann S, Merlini Gaul N, Clark M, Barraclough A, LeMay N, Buxbaum A. Management Sciences for Health. Health Systems in Action: An eHandbook for Leaders and Managers. Cambridge, MA: Management Sciences for Health, 2010. Available online at http://www.msh.org/resource-center/health-systems-in-cfm. Accessed 22nd June, 2013.
Fendall N. Declaration of Alma-Ata. 1978; 2:1308-1314.

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