Data quality has become an essential concern in recent years not only because of its importance in promoting high standards of patient care but also because of its impact on government financial plans for the maintenance of health services [1]. According to the World Health Organisation [2], accurate, complete and timely healthcare data play a very pivotal role in the development, maintenance and planning of health care services. Data are said to be of high quality if, they are fit for their intended uses in operations, decision making and planning [2]. This high-quality healthcare data offers potential value for optimizing care delivery, but it is still perceived as a by-product of healthcare delivery, rather than a central asset source for competitive advantages [3]. Quality data, particularly concerning timeliness, completeness and accuracy are needed for a variety of purposes including health sector reviews, planning, programme monitoring, quality improvement and reporting [2] [4]. For this reason, it is critical to have high-quality data on performance in the health sector available routinely [2]. Sound decisions are based on sound data; therefore, it is essential to ensure that the data are of good quality. Health-facility data constitute a primary data source for assessing the performance of the health sector; however, it is characterized by inadequate data completeness, timeliness and quality [5].

In most developing countries including Ghana, the issue of the quality of data generated from the community level or the peripheral level of the health care system and forwarded to the district level to be entered into the electronic systems especially the District Health Information System (DHIMS 2) is a serious problem [11]. This is because the completeness, accuracy and timeliness of data have always been compromised. Even though a data audit team had been established at the various levels especially at the district level which had always put in much effort to assess and improve upon the quality of data at the district level, their efforts had not seen the light of day in recent time [6].

Despite the introduction of several interventions such as Public Health Information System, Electronic Health Records in the healthcare systems to ensure that the data generated at the facility level are of high quality to produce valid and reliable information for scientific-based decision making, data generated at the facility level do not meet the required data quality standards [7].

Additionally, the Health Management Information System (HMIS) procedure manuals and the HMIS data management curriculum developed by the Ministry of Health are to ensure proper data management at the various facilities in Ghana. It is also to provide sufficient data quality and must be used at all levels and at all times for capacity building [6]. All these mechanisms are developed to ensure that the integrity of the data collected is not compromised. Community Health Nurses at the various health facilities still submit inaccurate, incomplete and late data to the health directorates.

At the various district health directorates in Ghana, a monthly return monitoring chart is used to monitor the timeliness of forms submitted manually at the district level. Furthermore, every district does a routine data validation and verification at the first week of the preceding month to check the accuracy and completeness of forms submitted by the in-charges of the various health facilities [6]. Community Health Nurses in primary healthcare facilities such as community-based health planning services (CHPS) compounds and health centres collect and report data for monitoring and evaluation of diseases and services in the municipality. These data when generated at the facility level by the nurse are collected and reported using the various data reporting formats. These reports are received at the district level, audited and validated by the data audit team and supervisors. The validated data is entered onto the nationwide database, DHIMS 2. The Data audit team is established at the district level to ensure sound and reliable data quality assessment which is vital to obtain the high data quality which enhances users’ confidence in public health authorities and their performance [7].

Few studies have been conducted in Ghana on assessing the knowledge and practices of community health nurses on data quality, so it is, therefore, necessary that this study is conducted to give insight into the level of knowledge and what they do to ensure accuracy, completeness and timeliness of data in the Ho municipality.

To attain achievable improvements in the public health sector, good data are core [1]. Therefore, to have accurate, complete and timely data in the healthcare system, healthcare providers who collect and manage the data should have good knowledge on data quality. This study was therefore conducted to assess the level of knowledge and practices of Community Health Nurses on data quality in the Ho Municipality, Ghana.

Out of the 77 Community Health Nurses studied, the majority 49 (63.64%) had good knowledge on data accuracy (Figure 1). This corresponds with results from a similar study conducted in Sierra Leone which revealed improvements in data accuracy [9]. This could be due to regular in-service training for community health nurses on data accuracy on how to obtain accurate data during compilation from the registers by tallying and validation.

Also, the study revealed that; out of the 77 respondents, 51 (66.23%) surprisingly had poor knowledge on data completeness (Figure 2). These results however confirm the assertion by [10] in a study conducted in Ghana on assessment of data quality on the expanded programme on immunization that; 50% of health facilities had incomplete tally books. This may be because of the poor level of knowledge on data completeness as revealed in the study which may translate to poor practices such as incomplete data and hence compromising the quality of the data. This is because a good knowledge of data completeness may yield practical steps in ensuring data and data reports are complete before submission.

There were statistically significant relationships between the age/work experience and the level of knowledge on data completeness (poor, satisfactory and good) (P > |z| = 0.018/ P > |z| = 0.017). This implies as the person grows old, and also gains more working experience, thus working longer in the field, his/her level of knowledge on data completeness increases. However, as the community health nurses (CHN) work experience increase, the CHN no longer pay attention to data quality after some time and they see it as routine and business as usual and responsibility of the junior and inexperience staff. Additionally, the study found that community health nurses who were taught in school on data quality are 3 times more likely to have had good knowledge on data completeness than those who were not taught. This is because they would be knowledgeable in that particular dimension of data quality.

Furthermore, on the level of knowledge on data timeliness, it was found that, a total of 64 (83.12%) out of the 77 respondents had poor level knowledge on data timeliness (Figure 3). This agrees with findings from similar studies conducted in Northern Ghana and Madagascar [11] [12]. The reason for these results might be because, most of the respondents only see it as mandatory to submit report forms at the end of each month but might not have knowledge on issues of data timeliness such as the currency of the data being reported on, report submission at the stipulated time to the health directorate, and availability of the reports forms at the time they are needed. These could be some of the attributable reasons for the poor level of knowledge on data timeliness by Community Health Nurses.

It is expected that training, work experience as well as type of certification (certificate, diploma) of Community Health Nurses would have a significant association with the level of knowledge on data quality; however, this study revealed no statistically significant relationship with the type of certification and the general level of knowledge on data quality. This could be because Community Health Nurses were only trained on how to record and extract data from the various registers and tally books to write monthly reports rather than training them on the various dimensions of data quality such accuracy, completeness and timeliness.

Importantly also, the study found that 16 (20.78%) of the Community Health Nurses said they did not have a designated staff responsible for reviewing data quality before the report forms are submitted to the next level. This is evidence of the assertion by [13], that, weaker supervisory mechanisms could result in the generation of inaccurate data. Furthermore, the study found that 33 (42.86%) out of the 77 Community Health Nurses studied revealed that, no feedback was given on the data submitted to the health directorate. This finding supports the assertion made by [14] in a study using forty-one low-income countries that one of the shortcomings in most information systems is lack of feedback relative to data recording and reporting performance. For instance, this study demonstrated that half of the copies of previous monthly reports at the 16 health facilities studied had missing values comparable to the finding of a cross-sectional study by [13], in South Africa which recorded 75% of the reports filled by community-based health workers had missing entries. Additionally, the study found that 2 (12.50%) out of the 16 facilities do not have contacts of reporting officers. This finding however contradicts the Ghana Health Service guidelines for ensuring data quality.

Additionally, out of the 16 health facilities studied, most 13 (81.25%) of the 16 facilities had no data quality audit team. This finding could be attributable to reasons why half 8 (50.00%) out of the 16 health facilities studied had missing values on their copies of the previous month’s reporting forms submitted. Poor supportive supervision, lack of feedback and poor knowledge on data completeness might be some of the reasons for such practices by the Community Health Nurses at the facility level.

On data quality practice at the facility level, it was commendable that all 16 (100%) of the 16 facilities had copies of reports of the previous month. This finding aligns with [15] who established that all health facilities had copies of monthly data in the clinic after submission. That notwithstanding, all those copies of the previous monthly reports had signatures of the reporting officers. The study also found that 14 (87.50%) of the 16 facilities, had contacts (mobile numbers) of reporting officers on their previous month’s reporting forms. This was a laudable practice because it conforms with the Ghana Health Service guidelines to ensuring data quality at facility levels and also by the Standard Operating Procedure on Health Information of the Ghana Health Services [16].

It was however disappointing to know that, most receiving officers’ names and signatures were not on the copies of the previous months’ reports. The reason was that officers at the health directorate found it unnecessary since those forms are to be kept at the facility level and hence no need for authentication with their names and signatures. More so, most 10 (62.50%) of the 16 facilities studied had no reminders (monthly data submission itineraries) for report submission. This is against the Ghana Health Service guidelines for data management practices at the facility levels. The reason could be that Community Health Nurses claimed they already knew the time range (before 5^th of the preceding month) for monthly data submission in each month and hence there was no need for the itineraries. This could also be contributing factor to the untimely report submitted by some of the facilities at the health directorate.

There should be more investments in pre-service training by the Ghana Health Service and also the development of training curricula on data quality and database management for community health nurses to improve data quality practices at the facility level.

The community health nurses should be trained on data quality and its dimensions, validation, and best practices by the Ghana Health Service/Ministry of Health to help improve the level of knowledge and practices on data quality. Also, data validation teams should be institutionalized and strengthened at the facility level to review the data forms before submitting them. The Ho Municipal Health Directorate should undertake data validation and strict supervision of community health nurses and institutionalize feedback mechanisms to those who generate and report the data. These are crucial in minimizing errors and missing values in reporting forms system and increasing data quality. Further, more studies should be conducted on the accuracy and overall data quality of primary health care data reported by Community Health Nurses.

The study targeted 94 community health nurses in the Ho Municipality. However, only 77 were reached out of 94. Because they were on annual leave and maternity leave at the time of the study, thus, could not be reached for the interview.

Most Community Health Nurses had a good level of knowledge on data accuracy; nevertheless, they had a significantly poor level of knowledge on both data completeness and timeliness implying that they had inadequate data quality practices. With data quality practices by Community Health Nurses, the issue of missing values, unsigned reporting forms, lack of contacts of reporting officers and non-availability of the itinerary for report submission were due to lack of supervision and feedback from the municipal health directorate as well as inadequate incentives to Community Health Nurses. The lack of designated technical staff for data quality review and validation at the facility level is still a major problem that needs serious attention. This requires improvement in the level of knowledge and practices of Community Health Nurses on data quality since they compile, manage and transfer data from the facility level to the district, regional, and national level to be analyzed for decision making.

The researchers declare no competing conflict of interest.

The researchers were the sole source of funding for the study.

Zumah, F., Niyi, J.L., Eweh, P.F., Adjei, B.N., Ajuik, M.A., Amaglo, E., Takramah, W.K. and Asem, L. (2022) Assessment of Knowledge and Practices of Community Health Nurses on Data Quality in the Ho Municipality of Ghana. Open Journal of Nursing, 12, 428-443. https://doi.org/10.4236/ojn.2022.126029