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 Table of Contents  
Year : 2021  |  Volume : 30  |  Issue : 5  |  Page : 573-580

The effect of training and provision of logistic support on disease surveillance and notification system in private health facilities in Enugu State, Nigeria

1 Department of Community Medicine, College of Medicine, University of Nigeria, Enugu State, Nigeria
2 Department of Community Medicine, Federal Teaching Hospital, Abakaliki, Ebonyi State, Nigeria

Date of Submission04-Feb-2021
Date of Decision26-Feb-2021
Date of Acceptance30-Jul-2021
Date of Web Publication11-Oct-2021

Correspondence Address:
Dr. Elias Chikee Aniwada
Department of Community Medicine, University of Nigeria, Enugu Campus, Enugu state
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/NJM.NJM_226_20

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Introduction: Rapid notification of infectious diseases is essential for prompt public health actions and monitoring disease trends at local, state and national levels. Disease surveillance is the backbone of Health Management Information system (HMIS). The study assessed the effect of training and provision of IDSR forms on disease surveillance and response in selected private hospitals in Enugu state. Methodology: The study was a quasi-experimental study that compared the study and control groups “before and after” an intervention (training and provision of IDSR forms). The intervention group received training and supplies if IDSR forms while the control group did not. A multistage sampling technique was used to select 400 participants from one hundred and four private hospitals in eight selected LGAs in Enugu East and Enugu North Senatorial Districts. Baseline data were collected followed by intervention. After six months waiting period post-intervention data were collected. A Questionnaire and observational checklist were used. Pearson and McNemar chi-square tests were employed. The level of statistical significance was set at p < 0.005. Result: At baseline, most knowledge and practice variables were poor (< 50%). The mean score of knowledge and practice between the groups at baseline was not significant (knowledge p=0.203 and practice p= 0.138). However, six months post-intervention there were significant increases in proportion for both knowledge and practice for study (McNemarχ2 p < 0.001) but not so control group. There was no statistically significant association of knowledge and practice with socio-demographic characteristics for both groups. Conclusion: Training of HCWs and provision of IDSR forms caused significant improvement in both knowledge and practice of disease notification and reporting in the private healthcare sector.

Keywords: Integrated disease surveillance and response forms, knowledge, notification, practice, surveillance, training

How to cite this article:
Ibiok NC, Aniwada EC, Ossai EN, Nwobi EA, Uzochukwu BS. The effect of training and provision of logistic support on disease surveillance and notification system in private health facilities in Enugu State, Nigeria. Niger J Med 2021;30:573-80

How to cite this URL:
Ibiok NC, Aniwada EC, Ossai EN, Nwobi EA, Uzochukwu BS. The effect of training and provision of logistic support on disease surveillance and notification system in private health facilities in Enugu State, Nigeria. Niger J Med [serial online] 2021 [cited 2021 Dec 8];30:573-80. Available from: http://www.njmonline.org/text.asp?2021/30/5/573/327958

  Introduction Top

Nigerian health-care system has been and remains besieged by numerous communicable disease epidemics. Therefore, there remains an enormous necessity to confront these problems by having a well-organized approach.[1],[2],[3] In Nigeria, surveillance and notification of diseases are considered epidemic-prone such as cholera and measles, targets for eradication or elimination such as poliomyelitis and dracunculiasis, and other diseases of public health importance such as malaria, tuberculosis, and HIV/AIDS.[3]

Disease surveillance and notification were launched in Nigeria in 1988. This was consequent on a severe epidemic of yellow fever in 1986/1987 which recorded high mortality and affected major parts of the country.[4] This was partly due to no or poor harmonized structure of disease reporting and surveillance in the country. As at that time, several states report weekly, some annually and others do not report at all. This practice resulted in a dearth of health information required for apt response to disease outbreaks.[4]

Despite the Federal Ministry of Health in Nigeria recognition of the necessity for the establishment of an Integrated Disease Surveillance and Response (IDSR) system, the vision has not been translated at the implementation level (state and local government). There is a need for functional IDSR to include workforce, materials, and other resources that can be utilized more efficiently and proficiently.[5] Little or no training on IDSR is received by health-care workers (HCWs) in both public and private sectors and when there is, training it is grossly inadequate leading to ineffective planning, implementation, and monitoring of the program.[6] Furthermore, there abound national and regional epidemics such as Ebola virus disease, Lassa fever as well as numerous epidemic-prone diseases that call for urgent reporting of cases and ultimately public health actions.

Private medical practitioners can play a vital role in disease surveillance as they are the first contact point for the greater part of the populace. Private hospitals are widely distributed in all geographical areas, unlike government hospitals that are mostly urban and cluster-based. Nevertheless, underreporting, particularly among the private sector, continues to be a threat to the health information system in most countries.[7] This was equally collaborated by the WHO. This gap needs to be bridged and this could be done by the active involvement of private medical practitioners in the mainstream of IDSR through regular training and provision of Integrated Disease Surveillance and Response (IDSR) forms and other incentives to motivate them.

Moreover, outside of the official training of public health workers on National Health Management Information System (NHMIS) and IDSR, there have been very few studies, conducted among health workers in the private health sector on NHMIS and IDSR reporting in the state. This study is expected to produce an objective assessment of the performance of IDSR by private health sector workers and help inform policies for the improvement of the IDSR system in Enugu.

  Methodology Top

Study area

The study was carried out in selected private hospitals in eight of the 17 local government areas (LGAs) in Enugu State. Enugu State is located in the South-east geopolitical zone of Nigeria with a total population of 4,881,500 persons occupying an area of 7618 sq. km.[8] The people are of Igbo ethnicity and are predominantly Christians. The state is divided into seven health districts with each made up of at least two LGAs for health-care delivery. There are 1090 health facilities which include 440 primary health care centers, 40, cottage hospitals and 378 registered private and mission hospitals.

Study participants

This comprised of all cadre of HCWs; doctors, nurses, midwives, laboratory technicians and scientists, Community Health Officers, record officers and community health extension workers in the private health facilities eligible for the study who gave consent.

Study design

A Quasi-study that compared the intervention and control groups “before and after” an intervention was used. The study was in three stages: preintervention, intervention, and postintervention stages. There was a 6-month waiting period after the intervention to allow for the changes to occur in the reporting of disease notification. The intervention included training and provision of IDSR forms to the intervention group.

Sample size

The minimum sample size was calculated using the formula for two proportions of equal size in a population <10,000.[9] n = (2[Zα+Zβ]2 π[1−π])/Δ2 using Zα (confidence level) of 95% which is 1.96; Zβ (power of the study) of 80% which is 0.84; π as the proportion that had the knowledge and practiced IDSR from a previous study (35.6%)[10] and Δ = margin of error of 0.10. Using the Yates formula, a minimum sample size of 196 each for the study and control group was gotten. However, 200 HCWs each were studied.

Sampling technique

A multistage sampling technique was used. Stage 1 involved the selection of two senatorial zones out of the three zones in the state; Enugu East senatorial zone was selected as the intervention group while Enugu North senatorial zone was used for the control group. Stage 2 involved the selection of 2 LGAs each from each of the selected senatorial zones. Stage 3 involved the selection of health facilities from the LGAs selected. Proportionately, 59 private health facilities were selected from Enugu East senatorial district (study group) and 45 private health facilities were selected from Enugu North senatorial district (control group). Stage 4 involved the selection of participants. Each selection was done using simple random sampling by balloting.

Study instrument

A pretested, semi-structured, interviewer-administered questionnaire consisting of three sections including sociodemographic variables, knowledge, and practice of IDSR by HCWs was used. Furthermore, a checklist was used to ascertain the completeness and timeliness of returned forms, proportion of health facilities that completed and sent Disease Surveillance and Notification (DSN) 003 form by the first week of the preceding month at baseline and 6 months after intervention for both groups

Data collection

This was done at baseline and 6 months after the intervention. The pre-intervention stage involved the baseline assessment of knowledge and practices on IDSR among health workers in private health facilities using questionnaires among both groups. The intervention stage involved training of selected HCWs in the intervention group on DSN. Postintervention stage involved the comparative assessment of both groups to determine the residual gain in disease notification and reporting related knowledge and practice using the same questionnaire. It was carried out 6 months after the intervention to allow for the changes to occur in the reporting of disease notification. During these 6 months, monthly supervisory visits were done with the aid of the checklist.

Data analysis

Data were analyzed using the Statistical Packages for the Social Sciences (SPSS) software version 23 (IBM SPSS Statistics for Windows, Version 23.0. Armonk, NY: IBM Corp. released 2015). Data were summarized using means, standard deviation, and proportions. The knowledge and practice of the respondents were compared at baseline and 6 months after the intervention between the groups using the Pearson Chi-square test. Knowledge and practice scores of the study and control group were also compared at baseline and after intervention using the McNemar Chi-square test. The level of statistical significance was at P ≤ 0.05.

Ethical consideration

Ethical consent for the study was obtained from the Health Research and Ethics Committee of the University of Nigeria Teaching Hospital, Ituku-Ozalla, Enugu. Approval for the study was gotten from the heads of various private health facilities. Written informed consent was gotten from all participants. Confidentiality and voluntary participation were ensured.

  Results Top

[Table 1] shows that no sociodemographic variables of the respondents showed a statistically significant difference between the HCWs in groups (P > 0.05). The mean age of the HCWs was 27.9 ± 12.8 and 28.7 ± 12.7 for the study and control groups, respectively. A higher proportion of the study (71.0%) and control (68.0%) groups was females. Majority were aged 21–30 years in both groups.
Table 1: Socio demographic characteristics of respondents

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[Table 2] shows that at baseline there were no statistically significant differences between the two groups in all of the variables. Majority of HCWs (92.0% in the study group and 93.5% in the control group) reported diseases (χ2 = 2.200; P = 0.138). Thirty-two (16.0%) of dedicated HCWs reported in the study group and 47 (23.5%) reported in the control group. Thirty-two (16.0%) and 33 (16.5%) in the study and control groups had standard case definition book and had used it (χ2 = 0.140; P = 0.708). Twenty-nine (14.5%) and 34 (17.0%) received feedback, respectively, for study and control groups.
Table 2: Baseline knowledge and practice of Disease Notification

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Furthermore, there were no statistically significant differences between the two groups for the practice of Disease Surveillance and Notification at baseline. Low proportions of health workers; 32 (16.0%) in study and 34 (17.0%) in control groups had attended training in IDSR. About 20 (62.5%) in the study group and 19 (56.0%) in control group of those who attended IDSR training was between 1 and 3 years ago (χ2 = 1.943; P = 0.163). The majority of 165 of the study 165 (83.5%) of study and 168 (84.0%) of the control groups reported frequent stock-out of IDSR forms. Major factors responsible for regular reporting were supervision; 8 (42.9%) among study group and 8 (53.3%) among control group. The reason given for nonregular reporting was lack of training; 6 (54.5%) for study and 6 (66.7%) control groups.

[Table 3] shows that postintervention, the majority of both study (95.0%) and control (93.5%) groups had good knowledge of diseases requiring reporting (P = 0.392). Furthermore, 66.8% in the study and 40.6% in the control groups knew where to send their DSN forms. Only (16.0%) study and (16.5%) control groups had standard case definition book and had used it (P = 0.708). Of those that reported, 35 (9.5%) in the study group and 18 (52.9%) in the control group reported appropriately. Thirty-four (17.0%) in the study group and 29 (14.5%) in the control group received feedback.
Table 3: Post-intervention comparison of knowledge and practice of Disease Notification in both groups

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Ninety-six (48.0%) HCWs in the study group and 34 (17.0%) in the control group had attended training on IDSR. The majority 154 (77.0%) HCWs in the study group and 166 (83.0%) in control group reported frequent stock-out of IDSR forms. Major factors responsible for regular reporting among control group were supervision; 12 (48.0%) and training received; 8 (32.0%) for intervention group, supervision; 8 (22.2%) and motivation/incentives received; 7 (19.7%) were key. The main factors responsible for nonregular reporting among the control group were lack of forms – 6 (66.7%) and lack of motivation – 2 (22.2%). For the intervention group, the main factors responsible for nonregular reporting were lack of training; 9 (47.4%) and lack of motivation/incentives; 7 (36.8%).

[Table 4] shows that there were statistically significant differences in HCWs knowledge in the study group at baseline and postintervention for those who had heard about IDSR. (McN P < 0.001), where to report the diseases (McN P < 0.001), and availability of IDSR forms currently at the facility (McN = P < 0.001). In the control group, there were no statistically significant differences.
Table 4: Comparison of the healthcare workers knowledge of IDSR at baseline between study and control at six months post-interventions period

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[Table 5] shows that the sociodemographic variables were significantly associated with knowledge on DSN on male sex (P = 0.010) and years of practice ≤20 years in the study (P = 0.014), while in the control group, only the years of practice ≤20 years (P = 0.003) was significant.
Table 5: Associations between socio-demographic variables of health care workers and mean knowledge score of IDSR in both groups

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[Table 6] shows that most of the sociodemographic variables did not show any significant association with the practice of IDSR in the study group, whereas for the control group, male sex (P = 0.013) and years of practice in ≤20 years respondents (P = 0.022) in the control group were significant.
Table 6: Associations between socio-demographic variables of health care and mean practice score of IDSR in both groups

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  Discussion Top

This study shows that the baseline knowledge of diseases that require notification was high in both groups with no statistically significant difference. This was similar to another study which showed that 89.9% of the HCWs knew about DSN system.[11] In another study in Ilorin, Nigeria, about two-thirds (67.6%) of HCWs knew about NHMIS.[12] Furthermore, in India, a very high proportion (80.0%) of private medical practitioners were aware of notification of disease.[13] On the contrary, in a study in North East, Nigeria, about 38.2% of the respondents were aware of the DSN.[14] Following the intervention there was an increase among the study but no change in the control. This is good as poor knowledge could result in under-reporting and undermine the success of prevention and control programmes for communicable diseases.[15]

There was also poor knowledge at baseline on the diseases that were to be reported with the forms at baseline in both groups. After the training, there was an appreciable increase among the study group. This improvement can be attributed to the training received. However, the findings conform to other studies which showed poor knowledge of forms used for IDSR.[16],[17] Poor understanding of reporting necessities is the main issue affecting DSN with negative consequence that these HCWs were not capable of detecting and notifying the occurrence of diseases that have high case fatality rates and are of public health-care importance.

The knowledge of who should be doing the reporting at the facility level was poor at baseline and postintervention for both groups. The reason for this could be due to the misconception especially in the private health sector practice that it is only the doctors that can report disease outbreaks. Furthermore, many doctors are not even aware of disease notification and reporting, while some believe that it is a waste of time reporting cases. Comparable kind of issues was observed in the United States where poor awareness of the legal requirement to report, lack of knowledge of which diseases are reportable, poor understanding of how or to whom to report, and an assumption that someone else will report the case were reported.[18] In this study, there was a statistically significant improvement in HCW's knowledge of disease surveillance and reporting following interventions. It is, therefore, expected that the desired knowledge of DSN by the HCWs would be achieved if similar interventional programs are promoted among them at regular intervals.

A low proportion of both groups had IDSR 003 forms for monthly reporting. Similarly, a study in Yobe State, Nigeria, reported that only 8.0% of the health facilities had IDSR forms.[14] Furthermore, a study on the effect of absurdity on the worth of health information systems found that health-care facilities do not have an adequate supply of IDSR forms.[10] The consequence of this is that diseases that should be reported with these forms will not be reported thereby compounding existing poor disease notification and reporting.

The possession and usage of a standard case definition book in the private health facilities in both groups were very poor as only a few of the private health facilities had standard case definition books, but case definition in form of fliers was seen displayed on the wall of some facilities, especially for diseases such as poliomyelitis, cholera, and measles. These were usually not complete for most other diseases that require notification. The presence of a simple and standard case definition book has been highlighted by numerous researchers as a requirement for an efficient surveillance system.[19] The possible reason for this study is that it was not provided to the facilities as part of the intervention logistics and the facilities made no effort to get one. The implication of this would be that appropriate classification of cases would be missed and this would affect the quality of data they would provide.

There was no significant difference among those that have received feedback following reporting in the intervention and control group. Feedback and remunerations were often considered being primary factors in IDSR.[20] The finding is reinforced by a study done in Northern Nigeria, where they found that only 21.8% of the respondents have ever received feedback on the reports they forwarded to higher authorities.[13] However, in a study in Germany, a higher proportion of respondents, 59.3% denied not to have gotten any feedback on infectious disease surveillance.[21] This may act as a form of disincentive to HCWs in regularly sending data to the appropriate authority.

The proportion of HCWs who have been trained in IDSR, in both groups was very low and no significant difference between the groups at baseline. At post-intervention there was an appreciable increase from 16.0% to 48.0% in the proportion of HCWs in the study group and vice versa for the control group. The implies that the collection of health information is hampered by a shortage of trained workforce at all levels,[22] and this is worse in private health facilities where there are no designated members of staff whose work is solely to collect data. A similar study in Northern Nigeria[22] supports the finding but differs from one done in South-west Nigeria.[23]

The reasons identified to be responsible for regular reporting among the HCWs in both groups included supervision, training received, and motivation in the form of incentives. However, although public HCWs send their reports because they believe that their salaries and wages may be tied to these reports, this is not the case with private HCWs. It has been observed by researchers that health workers receive little or no training on data collection leading to a lack of skill that would enable them gather the best possible data, analyze and draw inferences relevant to service provision.[24]

HCWs in both groups had generally good knowledge at baseline for some of the factors that can influence the practice of IDSR; the results showed that there was a significant improvement in health-care workers' knowledge due to interventions but not with control. Several studies have dwelled on these factors,[25],[26] and all noted that these factors usually affect the practice of IDSR. Training has been documented to positively impact disease notification as reported in an interventional study carried out in Northern Nigeria.[13] As shown in this study, all the respondents (Disease Surveillance and Notification Officers and disease control officers) have relevant training on DSN, this is in contrast to a similar study in which only a small proportion was found to have received training.[13]

There were significant associations between HCW's mean knowledge score and practice score on IDSR with sociodemographic variables in both the study and control groups. Previous studies showed association with sex,[27],[28] length of practice, specialty,[29] motivation, and training in IDSR.[30] However, this contrasts findings in the study done in Iran where they found no significant association between the participants' self-reported practices and knowledge question scores.[25]

  Conclusion Top

The baseline knowledge and practice on disease surveillance and notification were poor but interventions led to a statistically significant improvement. This demonstrates that regular training of the health-care workers is likely to improve significantly knowledge and practice of disease notification and reporting among the health-care workers. This will in turn help in the reduction of morbidity and mortality from these diseases. If Nigeria is to make progress in DSN, private facilities should be fully engaged.

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Conflicts of interest

There are no conflicts of interest.

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  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]


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