Knowledge of preconception care among healthcare providers working in public health institutions in Hawassa, Ethiopia

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Study Justification:
– Preconception care (PCC) is an evidence-based health promotion intervention to prevent adverse pregnancy outcomes.
– Despite the WHO’s recommendation, most developing countries, including Ethiopia, have not yet implemented preconception care.
– This study aims to determine the knowledge level of healthcare providers about PCC and identify predictors of effective knowledge of preconception care.
Highlights:
– Only 31% of healthcare providers demonstrated a good level of knowledge on preconception care.
– Factors associated with good PCC knowledge include working in hospitals, using smartphones to access clinical resources, reading PCC guidelines from organizations outside of Ethiopia, practicing PCC, and earning a higher salary.
Recommendations:
– Enhance the knowledge of healthcare providers about preconception care.
– Provide training and resources on preconception care to healthcare providers.
– Promote the use of smartphones and other technology for accessing clinical resources.
– Disseminate PCC guidelines from reputable organizations outside of Ethiopia.
– Encourage healthcare providers to practice preconception care.
– Consider salary incentives to motivate healthcare providers to improve their knowledge of preconception care.
Key Role Players:
– Ministry of Health: Responsible for implementing policies and guidelines related to preconception care.
– Public Health Institutions: Provide training and resources to healthcare providers.
– Professional Associations: Support the dissemination of PCC guidelines and provide training opportunities.
– Healthcare Providers: Actively engage in learning and practicing preconception care.
Cost Items for Planning Recommendations:
– Training Programs: Budget for organizing training sessions for healthcare providers on preconception care.
– Educational Materials: Allocate funds for developing and distributing educational materials on preconception care.
– Technology Infrastructure: Invest in smartphones or other devices for healthcare providers to access clinical resources.
– Guideline Dissemination: Allocate resources for translating and disseminating PCC guidelines from reputable organizations.
– Salary Incentives: Consider budgeting for salary incentives to motivate healthcare providers to improve their knowledge of preconception care.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is based on a cross-sectional study conducted among healthcare providers in public health institutions in Hawassa, Ethiopia. The study used a self-administered survey tool to collect data from 634 healthcare providers. The data analysis included descriptive statistics, bivariate and multivariate logistic regression models. The study found that only 31% of healthcare providers demonstrated a good level of knowledge on preconception care. The study also identified several predictors of good knowledge, such as working in hospitals, using smartphones to access clinical resources, reading PCC guidelines from organizations outside of Ethiopia, practicing PCC, and earning a higher salary. The study concludes that there is a low level of knowledge about PCC among healthcare providers in public health facilities in Ethiopia. The evidence in the abstract is based on a quantitative study with a large sample size and statistical analysis. However, the abstract does not provide information on the representativeness of the sample or the response rate, which could affect the generalizability of the findings. Additionally, the abstract does not mention any limitations of the study or potential biases. To improve the evidence, future studies could consider using a more representative sample and addressing potential biases. It would also be helpful to include information on the limitations of the study and any recommendations for further research.

Background Preconception care (PCC) is an evidence-based health promotion intervention to prevent adverse pregnancy outcomes. Nevertheless, it is one of the missing elements within the continuum of maternal and child healthcare. Despite the WHO’s recommendation, most of the developing countries have not yet started implementing preconception care. Objective To determine the knowledge level of healthcare providers about PCCand to identify predictors of effective knowledge of preconception care. Method This is a cross-sectional study conducted among 634 healthcare providers (HCP) working in public health institutions of Hawassa. A pilot-tested and validated self-administered survey tool was used to collect data from individual healthcare providers who were selected randomly using a multistage sampling technique. The data entry and analysis were conducted using SPSS version 20 software. Frequency, proportions, means and standard deviations were used to describe the data. Bivariate and multivariate logistic regression models were implemented to determine the predictors of HCP’s PCC knowledge. Results Only a few (31%) of the healthcare providers demonstrated a good level of knowledge on preconception care. The odds of having good PCC knowledge was high among HCPs working in hospitals (AOR = 1.8, 95% C.I. 1.3-2.6), HCPs using their smart phone to access clinical resources (AOR = 1.4, 95% C.I. 1.1-2.0), among those HCPs ever have read PCC guideline prepared by organization outside of Ethiopia (AOR = 1.9, 95% C.I. 1.4-2.7), among those who claimed practicing PCC (AOR = 3.4, 95% C.I. 2.0-5.9), and among those who earn salary of ≥ 146.0 $(AOR = 1.5, 95% C.I. 1.1-2.1). Conclusion There is an unacceptably low level of knowledge about PCC among most of the healthcare providers in public health facilities in Ethiopia. The predictors identified in this study can be used to enhance the knowledge of healthcare providers about preconception care.

The study was a cross-sectional quantitative study conducted from May to June 2017 among healthcare providers working in public health institutions (PHI) within the jurisdiction of Hawassa, 275km south of the capital (Addis Ababa) of Ethiopia. The public health institutions consist of nine healthcentres and two hospitals of which one was a secondary level public hospital and the other a tertiary level comprehensive specialized hospital. Under the public health centres are seventeen health posts where the health extension workers are working. During the study period, healthcare workers consisted of 106 doctors, 826 nurses, 60 health officers, 95 midwifes, and 142 health extension workers who were employed in the institutions and formed the target population for the study. The health extension workers are primarily nurses, specifically trained to provide community health service in line with the country’s primary healthcare package. The maternal healthcare includes antenatal care, postnatal care and institutional delivery services. These services are provided in every health facility by all healthcare providers but mainly by midwives and gynaecologists. Preconception care is not a specified area of care in any of these facilities. The authors of this study purposively selected Hawassa City Administration as the study area. Selection of the study area considered the goals of the study, feasibility issues, and the availability of all healthcare providers working at all levels of the referral system located at both rural and urban areas. The study sample of healthcare providers in public health institutions in Hawassa was randomly selected by using the employers register as a sampling frame. The sampled healthcare professionals were all taken proportional to their profession, their number, and the type of health facility where they are working. Healthcare workers who were employed for less than six months were excluded from the study. Multistage sampling technique was applied to draw a total of 647 HCPs. The minimum sample size required for the study was determined by using a single population proportion formula. While computing the minimum sample size, the following parameters were considered: a 0.05 margin of error (α), a 95% Confidence Interval (CI), a 50% estimated proportion of healthcare providers’ knowledge about preconception care, 10% non-response rate and a design effect of 2. The design effect (DEEF) was calculated with the formula DEEF = 1+ δ (n-1). The “δ” or the interclass correlation coefficient (ICC) was calculated from the cluster data by using SPSS and it was found 0.169. Since the average size of clusters (n) was 11/2 = 5.5, the final DEEF was determinedas 1.79 ≈ 2. Given that the total number of HCPs working in PHIs of the study area was 1239, a population correction factor was considered. Due to the absence of a similar study or comparative study in the country we preferred taking a 50% proportion which is a proportion to yield adequate sample size. Concerning sampling procedure, first, five PHIs out of the 11 PHIs found within the city administration were randomly selected. By using simple random sampling technique, 3 out of the 9 health centres were included in the study. Since the remaining two public hospitals were quite different in their level and type, both were selected. The study population was also stratified in terms of profession. In the second stage, HCPs were selected by the systematic random sampling method using employer’s employee registry document as a sampling frame. The study participants were all taken from each strata using probability proportional to size method. All HCPs were selected and consented to participate in the study without any coercion. A data collection tool, namely ‘Andarg-Ethio PCC-KAP-Questionnaire for HCP’, based on literature and evidence-based guidelines on PCC was developed and validated by the principal investigator to conduct this research project. The instrument was tested for content and face-validity by a panel of experts and was scored with a content validity index (CVI) of 92.4%. The reliability of the instrument was checked for its internal consistency with a Cronbach’s α test and demonstrated a score of 0.945[19]. The questionnaire which was originally prepared in English was translated to local language Amharic and then translated back to English. The survey was administered using the Amharic version. The instrument was designed to assess socio-demographic characteristics of HCPs, their knowledge on PCC, their attitude towards PCC, their practice on PCC,issues on training of PCC,and in-service training opportunities on PCC. The HCPs’ knowledge of PCC was measured through 18 questions, each containing only one correct answer. A further 36 items measured various elements of PCC practice, including reproductive life planning,screening practices, access to resources to practice PCC. The attitude of healthcare workers on PCC was assessed by using 10 items each with five-point Likert scale responses. The calculated single knowledge factor was then categorized into three ordinal categories. Respondents who scored less than the 50th percentile or below the mean score were categorized as HCPs with ‘poor/low PCC knowledge’. Whereas, HCPs who scored ≥ 50th percentile to 75th percentile and those who scored > 75th percentile were categorized as HCPs with ‘medium’ and ‘high’ PCC knowledge respectively. For analytical purpose, those HCPs who scored ‘high’ and ‘medium’ PCC knowledge were merged all together into another category called ‘HCPs with good PCC knowledge’. The instrument was piloted on 65 (10% of the minimum sample) healthcare practitioners in a different town as Hawassa, after which minor revision to improve on the clarity of questions were done. The questionnaire was administered by two nurses, one health officer, one 2nd year Master of public health student, and one pharmacist after being trained by the primary investigator. There were two field supervisors. The principal investigator was the main supervisor throughout the study. The data collected was entered to the SPSS version 20 software by an experienced statistician. The analysis used descriptive statistics such as frequency, proportion, standard deviation, mean, mode and range to describe the variables of the study. In addition, the inferential statistics applied a binary and multiple logistic regression analytical models to determine the crude (COR) and adjusted odds ratios (AOR) respectively. The analysis was all made fixing CI at 95%. The variables with their P-Value of less than 0.20 were all considered in the second or multivariate logistic regression model. The second analytical step used a stepwise backward model to determine factors associated with ‘HCP’s good PCC knowledge’. The goodness of fit of the models was tested by using the Hosmer-Lemeshow test. Thus, the model which was found to be greater than the significance level (P-value = 0.05) was accepted. The project proposal of the study was approved by IRBs of Hawassa University and the University of South Africa. Ethical principles such as confidentiality, beneficence, respect and human rights were maintained throughout the study.

Based on the provided information, here are some potential recommendations for innovations to improve access to maternal health:

1. Develop and implement a comprehensive preconception care (PCC) program: Based on the study findings, there is a low level of knowledge about PCC among healthcare providers. Developing a comprehensive PCC program that includes training modules, guidelines, and resources can help improve healthcare providers’ knowledge and understanding of PCC.

2. Mobile health (mHealth) interventions: The study found that healthcare providers who use their smartphones to access clinical resources had higher odds of having good PCC knowledge. Leveraging mHealth interventions, such as mobile applications or text message reminders, can provide healthcare providers with easy access to up-to-date information and resources on PCC.

3. Collaboration with international organizations: Healthcare providers who have read PCC guidelines prepared by organizations outside of Ethiopia had higher odds of having good PCC knowledge. Strengthening collaborations with international organizations that specialize in maternal health can help provide healthcare providers with access to evidence-based guidelines and best practices in PCC.

4. Training and capacity building: Implementing regular training and capacity building programs on PCC can help improve healthcare providers’ knowledge and skills in providing preconception care. These programs can be tailored to different levels of healthcare providers, including doctors, nurses, health officers, midwives, and health extension workers.

5. Financial incentives: The study found that healthcare providers who earn a higher salary had higher odds of having good PCC knowledge. Providing financial incentives or bonuses for healthcare providers who demonstrate good knowledge and practice in PCC can help motivate and reward them for their efforts.

6. Integration of PCC into existing maternal healthcare services: Since preconception care is not currently a specified area of care in the public health facilities in Ethiopia, integrating PCC into existing maternal healthcare services can help ensure that women receive comprehensive care throughout their reproductive journey. This can include incorporating PCC components into antenatal care, postnatal care, and institutional delivery services.

These recommendations aim to address the identified gaps in knowledge and practice of preconception care among healthcare providers in Ethiopia and improve access to maternal health services.
AI Innovations Description
The study titled “Knowledge of preconception care among healthcare providers working in public health institutions in Hawassa, Ethiopia” aimed to determine the knowledge level of healthcare providers about preconception care (PCC) and identify predictors of effective knowledge of PCC. The study was conducted from May to June 2017 among healthcare providers working in public health institutions in Hawassa, Ethiopia.

The study found that only 31% of healthcare providers demonstrated a good level of knowledge on preconception care. Several predictors of good PCC knowledge were identified, including working in hospitals, using smartphones to access clinical resources, reading PCC guidelines prepared by organizations outside of Ethiopia, practicing PCC, and earning a salary of at least $146.0.

The study sample consisted of 634 healthcare providers working in public health institutions, including doctors, nurses, health officers, midwives, and health extension workers. The healthcare providers were selected randomly using a multistage sampling technique. Data was collected using a self-administered survey tool and analyzed using SPSS version 20 software.

The study highlights the low level of knowledge about preconception care among healthcare providers in public health facilities in Ethiopia. The identified predictors can be used to enhance the knowledge of healthcare providers about preconception care. This can ultimately contribute to improving access to maternal health by ensuring that healthcare providers have the necessary knowledge and skills to provide preconception care services.
AI Innovations Methodology
Based on the provided information, here are some potential recommendations to improve access to maternal health:

1. Increase awareness and knowledge of preconception care (PCC) among healthcare providers: Develop and implement training programs and workshops to educate healthcare providers about the importance of PCC and its role in preventing adverse pregnancy outcomes. This can include providing information on best practices, guidelines, and resources related to PCC.

2. Improve access to clinical resources: Ensure that healthcare providers have access to up-to-date clinical resources, such as guidelines and research articles, through the use of smartphones or other digital platforms. This can help them stay informed about the latest developments in PCC and provide evidence-based care to pregnant women.

3. Collaborate with international organizations: Encourage healthcare providers to read PCC guidelines prepared by organizations outside of Ethiopia. This can help them gain insights from global best practices and adapt them to the local context.

4. Promote the practice of PCC: Encourage healthcare providers to actively practice PCC by integrating it into their routine care for pregnant women. This can include conducting preconception counseling, providing information on reproductive life planning, and offering screening tests and interventions to optimize maternal health before pregnancy.

5. Improve financial incentives: Consider providing financial incentives, such as higher salaries, to healthcare providers who demonstrate good knowledge and practice of PCC. This can help motivate them to prioritize and invest in improving their knowledge and skills in this area.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could be developed as follows:

1. Define the indicators: Identify key indicators that reflect access to maternal health, such as the number of women receiving preconception counseling, the percentage of women with adequate knowledge of PCC, and the rate of adverse pregnancy outcomes.

2. Collect baseline data: Gather baseline data on the selected indicators before implementing the recommendations. This can be done through surveys, interviews, or analysis of existing data sources.

3. Implement the recommendations: Roll out the recommended interventions, such as training programs, access to clinical resources, and financial incentives, to healthcare providers in public health institutions in Hawassa.

4. Monitor and evaluate: Continuously monitor the implementation of the recommendations and collect data on the selected indicators. This can be done through regular surveys, interviews, or data collection from health facilities.

5. Analyze the data: Analyze the collected data to assess the impact of the recommendations on the selected indicators. This can involve comparing the baseline data with the post-implementation data to identify any changes or improvements.

6. Interpret the findings: Interpret the findings of the data analysis to determine the effectiveness of the recommendations in improving access to maternal health. This can involve identifying any trends, patterns, or correlations between the implemented interventions and the selected indicators.

7. Adjust and refine: Based on the findings, make any necessary adjustments or refinements to the recommendations to further enhance their impact on improving access to maternal health.

8. Repeat the process: Continuously repeat the monitoring, evaluation, and adjustment process to ensure ongoing improvement in access to maternal health.

By following this methodology, it will be possible to simulate the impact of the recommendations on improving access to maternal health and make evidence-based decisions for further interventions.

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