scholarly journals Routine Health Information System in the Health Facilities in Yaoundé-Cameroon: Assessing the Gaps for Strengthening

2020 ◽  
Author(s):  
Brian Bongwong Tamfon ◽  
Chanceline Bilounga Ndongo ◽  
Serge Marcial Bataliack ◽  
Marie Nicole Ngoufack ◽  
Georges Nguefack-Tsague
Keyword(s):  
Decision Making ◽  
Information System ◽  
Health Information ◽  
Information Dissemination ◽  
Health Sector ◽  
Health Information System ◽  
Health Facilities ◽  
World Health ◽  
Quality Data ◽  
Health Related

Abstract Background: Management of health data and its use for informed decision making is a challenging health sector aspect in developing countries. Monitoring and evaluation of health interventions for meeting health-related Sustainable Development Goals (SDGs), and Cameroon Health Sector Strategy (HSS) targets is facilitated through evidence-based decision-making and public health action. Thus, a Routine Health Information System (RHIS) producing quality data is imperative. The objective of this study was to assess the RHIS in the health facilities (HFs) in Yaoundé in order to identify gaps and weaknesses and to propose measures for strengthening. Methods: A health facility-based cross-sectional descriptive study was carried out in the six health districts (HDs) of Yaoundé; followed by a qualitative aspect consisting of in-depth interviews of key informants at the Regional Health Office. HFs were selected using a stratified sampling method with probability proportional to the size of each HD. Data were collected (one respondent per HF) using the World Health Organization (WHO) and MEASURE Evaluation RHIS rapid assessment tool. Data were entered into Microsoft Excel 2013 and analyzed with IBM-SPSS version 20. Results: A total of 111 HFs were selected for the study. Respondents aged 24-60 years with an average of 38.3±9.3 years; 58 (52.3%) male and 53(47.7%) female. Heads of HFs and persons in charge of statistics/data management were most represented with 45.0% and 21.6% respectively. All the twelve subdomains of the RHIS were adequately functioning at between 7% and 30%. These included Human Resources (7%), Data Analysis (10%), Information and Communication Technology (11%), Standards and System Design (15%), Policies and Planning (15%), Information Dissemination (16%), Data Demand and Use (16%), Management (18%), Data Needs (18%), Data Quality Assurance (20%), Collection and Management of Individual Client Data (26%), Collection, Management, and Reporting of Aggregated Facility Data (30%). Conclusions: The level of functioning of subdomains of the RHIS in Yaoundé was low; thus, immediate and district-specific strengthening actions should be implemented if health-related SDGs and HSS targets are to be met. A nation-wide assessment should be carried out in order to understand the determinants of these poor performances and to strengthen the RHIS.

scholarly journals Routine health information system in the health facilities in Yaoundé–Cameroon: assessing the gaps for strengthening

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Brian Bongwong Tamfon ◽  
Chanceline Bilounga Ndongo ◽  
Serge Marcial Bataliack ◽  
Marie Nicole Ngoufack ◽  
Georges Nguefack-Tsague
Keyword(s):  
Decision Making ◽  
Information System ◽  
Health Information ◽  
Information Dissemination ◽  
Health Sector ◽  
Health Information System ◽  
Health Facilities ◽  
World Health ◽  
Quality Data ◽  
Health Related

Abstract Background Management of health data and its use for informed-decision making is a challenging health sector aspect in developing countries. Monitoring and evaluation of health interventions for meeting health-related Sustainable Development Goals (SDGs), and Cameroon Health Sector Strategy (HSS) targets is facilitated through evidence-based decision-making and public health action. Thus, a routine health information system (RHIS) producing quality data is imperative. The objective of this study was to assess the RHIS in the health facilities (HFs) in Yaoundé in order to identify gaps and weaknesses and to propose measures for strengthening. Methods A health facility-based cross-sectional descriptive study was carried out in the six health districts (HDs) of Yaoundé; followed by a qualitative aspect consisting of in-depth interviews of key informants at the Regional Health Office. HFs were selected using a stratified sampling method with probability proportional to the size of each HD. Data were collected (one respondent per HF) using the World Health Organization and MEASURE Evaluation RHIS rapid assessment tool. Data were entered into Microsoft Excel 2013 and analyzed with IBM-SPSS version 20. Results A total of 111 HFs were selected for the study. Respondents aged 24–60 years with an average of 38.3 ± 9.3 years; 58 (52.3%) male and 53(47.7%) female. Heads of HFs and persons in charge of statistics/data management were most represented with 45.0% and 21.6% respectively. All the twelve subdomains of the RHIS were adequately functioning at between 7 and 30%. These included Human Resources (7%), Data Analysis (10%), Information and Communication Technology (11%), Standards and System Design (15%), Policies and Planning (15%), Information Dissemination (16%), Data Demand and Use (16%), Management (18%), Data Needs (18%), Data Quality Assurance (20%), Collection and Management of Individual Client Data (26%), Collection, Management, and Reporting of Aggregated Facility Data (30%). Conclusions The level of functioning of subdomains of the RHIS in Yaoundé was low; thus, immediate and district-specific strengthening actions should be implemented if health-related SDGs and HSS targets are to be met. A nation-wide assessment should be carried out in order to understand the determinants of these poor performances and to strengthen the RHIS.

scholarly journals Routine Health Information System in the Health Facilities in Yaoundé-Cameroon: Assessing the Gaps for Strengthening

2020 ◽  
Author(s):  
Brian Bongwong Tamfon ◽  
Chanceline Bilounga Ndongo ◽  
Serge Marcial Bataliack ◽  
Marie Nicole Ngoufack ◽  
Georges Nguefack-Tsague
Keyword(s):  
Decision Making ◽  
Information System ◽  
Health Information ◽  
Information Dissemination ◽  
Health Sector ◽  
Health Information System ◽  
Health Facilities ◽  
World Health ◽  
Quality Data ◽  
Health Related

Abstract Background Management of health data and its use for informed decision making is a challenging health sector aspect in developing countries. Monitoring and evaluation of health interventions for meeting health-related Sustainable Development Goals (SDGs), and Cameroon Health Sector Strategy (HSS) targets is facilitated through evidence-based decision-making and public health action. Thus, a Routine Health Information System (RHIS) producing quality data is imperative. The objective of this study was to assess the RHIS in the health facilities (HFs) in Yaoundé in order to identify gaps and weaknesses and to propose measures for strengthening. Methods A health facility-based cross-sectional descriptive study was carried out in the six health districts (HDs) of Yaoundé; followed by a qualitative aspect consisting of in-depth interviews of key informants at the Regional Health Office. HFs were selected using a stratified sampling method with probability proportional to the size of each HD. Data were collected (one respondent per HF) using the World Health Organization (WHO) and MEASURE Evaluation RHIS rapid assessment tool. Data were entered into Microsoft Excel 2013 and analyzed with IBM-SPSS version 20. Results A total of 111 HFs were selected for the study. Respondents aged 24-60 years with an average of 38.3±9.3 years; 58 (52.3%) male and 53(47.7%) female. Heads of HFs and persons in charge of statistics/data management were most represented with 45.0% and 21.6% respectively. All the twelve subdomains of the RHIS were adequately functioning at between 7% and 30%. These included Human Resources (7%), Data Analysis (10%), Information and Communication Technology (11%), Standards and System Design (15%), Policies and Planning (15%), Information Dissemination (16%), Data Demand and Use (16%), Management (18%), Data Needs (18%), Data Quality Assurance (20%), Collection and Management of Individual Client Data (26%), Collection, Management, and Reporting of Aggregated Facility Data (30%). Conclusions The level of functioning of subdomains of the RHIS in Yaoundé was low; thus, immediate and district-specific strengthening actions should be implemented if health-related SDGs and HSS targets are to be met. A nation-wide assessment should be carried out in order to understand the determinants of these poor performances and to strengthen the RHIS.

scholarly journals Routine Health Information System in the Health Facilities in Yaoundé-Cameroon: Assessing the Gaps for Strengthening

2020 ◽  
Author(s):  
Brian Bongwong Tamfon ◽  
Chanceline Bilounga Ndongo ◽  
Serge Marcial Bataliack ◽  
Marie Nicole Ngoufack ◽  
Georges Nguefack-Tsague
Keyword(s):  
Decision Making ◽  
Information System ◽  
Health Information ◽  
Information Dissemination ◽  
Health Sector ◽  
Health Information System ◽  
Health Facilities ◽  
World Health ◽  
Quality Data ◽  
Health Related

Abstract Background: Management of health data and its use for informed-decision making is a challenging health sector aspect in developing countries. Monitoring and evaluation of health interventions for meeting health-related Sustainable Development Goals (SDGs), and Cameroon Health Sector Strategy (HSS) targets is facilitated through evidence-based decision-making and public health action. Thus, a Routine Health Information System (RHIS) producing quality data is imperative. The objective of this study was to assess the RHIS in the health facilities (HFs) in Yaoundé in order to identify gaps and weaknesses and to propose measures for strengthening. Methods: A health facility-based cross-sectional descriptive study was carried out in the six health districts (HDs) of Yaoundé; followed by a qualitative aspect consisting of in-depth interviews of key informants at the Regional Health Office. HFs were selected using a stratified sampling method with probability proportional to the size of each HD. Data were collected (one respondent per HF) using the World Health Organization (WHO) and MEASURE Evaluation RHIS rapid assessment tool. Data were entered into Microsoft Excel 2013 and analyzed with IBM-SPSS version 20. Results: A total of 111 HFs were selected for the study. Respondents aged 24-60 years with an average of 38.3±9.3 years; 58 (52.3%) male and 53(47.7%) female. Heads of HFs and persons in charge of statistics/data management were most represented with 45.0% and 21.6% respectively. All the twelve subdomains of the RHIS were adequately functioning at between 7% and 30%. These included Human Resources (7%), Data Analysis (10%), Information and Communication Technology (11%), Standards and System Design (15%), Policies and Planning (15%), Information Dissemination (16%), Data Demand and Use (16%), Management (18%), Data Needs (18%), Data Quality Assurance (20%), Collection and Management of Individual Client Data (26%), Collection, Management, and Reporting of Aggregated Facility Data (30%). Conclusions: The level of functioning of subdomains of the RHIS in Yaoundé was low; thus, immediate and district-specific strengthening actions should be implemented if health-related SDGs and HSS targets are to be met. A nation-wide assessment should be carried out in order to understand the determinants of these poor performances and to strengthen the RHIS.

Quality of Routine Health Information System Data and Associated Factors Among Departments in Public Health Facilities of Harari Region, Ethiopia

2021 ◽  
Author(s):  
Adisu Tafari Shama ◽  
Hirbo Shore Roba ◽  
Admas Abera ◽  
Negga Baraki
Keyword(s):  
Public Health ◽  
Information System ◽  
Data Quality ◽  
Health Information ◽  
Health Information System ◽  
Health Facilities ◽  
Quality Data ◽  
Public Health Facilities ◽  
System Data

Abstract Background: Despite the improvements in the knowledge and understanding of the role of health information in the global health system, the quality of data generated by a routine health information system is still very poor in low and middle-income countries. There is a paucity of studies as to what determines data quality in health facilities in the study area. Therefore, this study was aimed to assess the quality of routine health information system data and associated factors in public health facilities of Harari region, Ethiopia.Methods: A cross-sectional study was conducted in all public health facilities in Harari region of Ethiopia. The department-level data were collected from respective department heads through document reviews, interviews, and observation check-lists. Descriptive statistics were used to data quality and multivariate logistic regression was run to identify factors influencing data quality. The level of significance was declared at P-value <0.05. Result: The study found a good quality data in 51.35% (95% CI, 44.6-58.1) of the departments in public health facilities in Harari Region. Departments found in the health centers were 2.5 times more likely to have good quality data as compared to departments found in the health posts. The presence of trained staffs able to fill reporting formats (AOR=2.474; 95%CI: 1.124-5.445) and provision of feedback (AOR=3.083; 95%CI: 1.549-6.135) were also significantly associated with data quality. Conclusion: The level of good data quality in the public health facilities was less than the expected national level. Training should be provided to increase the knowledge and skills of the health workers.

scholarly journals Measles Data Reporting in the District Health Information System: A Case Study of Gombe State

2019 ◽  
Vol 11 (11) ◽  
pp. 109
Author(s):  
Nnamdi Usifoh ◽  
Toby Yak ◽  
Ivy Dooga ◽  
Raymond Dankoli ◽  
Olufemi Ajumobi ◽  
...  
Keyword(s):  
Information System ◽  
Health Information ◽  
Health Facility ◽  
Health Information System ◽  
Data Entry ◽  
Health Facilities ◽  
World Health ◽  
District Health ◽  
Targeted Interventions ◽  
Data Entry Error

BACKGROUND: The District Health Information System (DHIS2) is a modular, cloud-based data management system designed for use in integrated health information systems. In Nigeria, it serves as the repository for routine health data, including measles. A first dose of measles is given routinely in most countries, however, for a country to include a second dose of measles in the routine immunization schedule, it must meet certain criteria set by the World Health Organization (WHO). Unfortunately, Nigeria falls into the category of countries that haven&rsquo;t met the criteria. Despite this, MCV2 data can be seen on the DHIS2 platform. Data from DHIS2 also shows that Gombe State has the highest number of health facilities that reported MCV2 data at least once from 2015 to 2017. The aim of the study was to determine the reasons for the MCV2 reporting on DHIS2 platform for Gombe State. METHOD: We conducted a cross-sectional study among health workers in selected health facilities and LGA RI Officers at the LGA level in Gombe State. Health facility registers were reviewed, and data consistency was ascertained. We reviewed and conducted secondary data analysis of MCV2 data for Gombe State from January 2015 to December 2017. RESULTS: Of the 22 health facilities assessed, 14 health facilities (12 public and 2 private) reported offering MCV2 during the health facility-level interviews. At the LGA level, 5 LGAs out of the 11 LGAs reported during the LGA-level interviews that a second dose of measles is part of the RI schedule in their respective LGAs. For the 6 LGAs that reported not offering a second dose of measles as part of the RI schedule, 3 LGAs identified data entry error as the possible reason for having MCV2 data in the DHSI2 platform while the remaining 3 LGAs reported that the MCV2 data in the DHIS2 platform can be attributed to recording children who didn&rsquo;t receive a first dose of measles at 9 months but received at 18&ndash;23 months as second dose of measles. CONCLUSION: Data entry error and knowledge gap on how to record measles data were identified factors responsible for MCV2 data on the DHIS2 platform. There is a need for targeted interventions towards improving the quality of RI data in Nigeria.

scholarly journals Assessment of quality of routine health information system data and associated factors among departments in public health facilities of Harari region, Ethiopia

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Adisu Tafari Shama ◽  
Hirbo Shore Roba ◽  
Admas Abera Abaerei ◽  
Teferi Gebru Gebremeskel ◽  
Negga Baraki
Keyword(s):  
Public Health ◽  
Information System ◽  
Data Quality ◽  
Health Information ◽  
Health Information System ◽  
Health Facilities ◽  
Quality Data ◽  
Public Health Facilities ◽  
System Data

Abstract Background Despite the improvements in the knowledge and understanding of the role of health information in the global health system, the quality of data generated by a routine health information system is still very poor in low and middle-income countries. There is a paucity of studies as to what determines data quality in health facilities in the study area. Therefore, this study was aimed to assess the quality of routine health information system data and associated factors in public health facilities of Harari region, Ethiopia. Methods A cross-sectional study was conducted in all public health facilities in the Harari region of Ethiopia. The department-level data were collected from respective department heads through document reviews, interviews, and observation checklists. Descriptive statistics were used to data quality and multivariate logistic regression was run to identify factors influencing data quality. The level of significance was declared at P value < 0.05. Result The study found good quality data in 51.35% (95% CI 44.6–58.1) of the departments in public health facilities in the Harari Region. Departments found in the health centers were 2.5 times more likely to have good quality data as compared to those found in the health posts. The presence of trained staffs able to fill reporting formats (AOR = 2.474; 95% CI 1.124–5.445) and provisions of feedbacks (AOR = 3.083; 95% CI 1.549–6.135) were also significantly associated with data quality. Conclusion The level of good data quality in the public health facilities was less than the expected national level. Lack of trained personnel able to fill the reporting format and feedback were the factors that are found to be affecting data quality. Therefore, training should be provided to increase the knowledge and skills of the health workers. Regular supportive supervision and feedback should also be maintained.

scholarly journals A Strategy That Improves the Culture of Information Use at Primary Health Care Units in Ethiopia

2021 ◽  
Author(s):  
Wondwosen Shiferaw Abera ◽  
Brook Abate Halallo ◽  
Ismael Ali Beshir ◽  
Binyam Fekadu Desta ◽  
Mesele Damte Argaw
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Information System ◽  
Primary Health Care ◽  
Health Information ◽  
Health Information System ◽  
Information Use ◽  
Assessment Tools ◽  
Quality Data ◽  
Primary Health

Abstract Background: Health systems require high-quality data production for health service delivery and program improvement. Ethiopia’s health sector was challenged with lack of quality data from its routine health information system which is an essential element of evidence-based decision making. To overcome this, the Ethiopian Ministry of Health introduced a health information system (HIS) performance monitoring tool named the connected woreda strategy (CWS). This study aims to assess the effectiveness of the CWS to improve culture of information use at primary health care entities. Methods: The study employed a repeated cross-sectional study design through pre and post testing of district health offices using connected woreda assessment tools. A total of 78 districts were enrolled in this study to assess their performance on the implementation of the CWS. The CWS assessment checklist is comprised of 54 questions, all of which were assigned numeric number response types and categorized into HIS capacity (30%), data quality (30%), and administrative data use (40%) and further categorized as districts that meet the highest standards, (>90% of common set of criteria) i.e. ‘model woredas’, districts that meet medium standards, (between 65% to 90% score of common set criteria) i.e. ‘candidate woredas’ and districts that meet lowest standards (<65 of common set of criteria) i.e. ‘emerging woredas’. Finally, the data were analyzed using the SPSS-version 25 software. Results: A total of 78 districts were employed and described and a paired sample t-test was used to measure the performance of districts on CWS implementation. Due to CWS implementation, 10% of districts were ‘models’ in HIS performance; ‘candidate’ districts increased from 40% to 73%; and ‘emerging’ districts decreased from 60% to 17%. Finally, overall CWS scores showed significant improvements after the intervention with 73.4 ± 10.48 SD compared to before intervention 60.4±13.69 SD, with t (77) =-7.18 and p=0.001. Conclusions: This study has revealed that the CWS implementation has a positive effect towards cultural transformation of use of data for decision making at primary health care entities. Thus, scaling up the connected woreda implementation is recommended at the national level to improve the performance of primary health care entities.

Effectivness of Health Information System Applications: Clinical Information and Diagnosis-Treatment Systems in Turkey

2017 ◽  
Vol 5 (1) ◽  
pp. 122
Author(s):  
Assist. Prof. Dr. Demokaan DEMİREL
Keyword(s):  
Decision Making ◽  
Information System ◽  
Information Systems ◽  
Management Information System ◽  
Health Sector ◽  
Health Information System ◽  
Clinical Information ◽  
Clinical Decision ◽  
Clinical Information Systems ◽  
Management Information

The distinctive quality of the new social structure is that information becomes the only factor of production. In today's organizations, public administrators are directly responsible for applying information to administrative processes. In addition to his managerial responsibilities, a knowledge based organization requires every employee to take responsibility for achieving efficiency. This has increased the importance of information systems in the decision-making process. Information systems consist of computer and communication technology, data base management and model management and include activity processing system, management information system, decision support systems, senior management information system, expert systems and office automation systems. Information systems in the health sector aim at the management and provision of preventive and curative health services. The use of information systems in healthcare has the benefits of increasing service quality, shortening treatment processes, maximizing efficiency of the time, labour and medical devices. The use of information systems for clinical decision making and reducing medical errors in the healthcare industry dates back to the 1960s. Clinical information systems involve processing, storing and re-accessing information that supports patient care in a hospital. Clinical information systems are systems that are directly or indirectly related to patient care. These systems include electronic health/patient records, clinical decision support systems, nurse information systems, patient tracking systems, tele-medicine, case mix and smart card applications. Diagnosis-treatment systems are information-based systems used in the diagnosis and treatment of diseases. It consists of laboratory information systems, picture archiving and communication system, pharmacy information system, radiology information system, nuclear medicine information system. This study aims to evaluate the effectiveness of health information system applications in Turkey. The first part of the study focuses on the concept of information systems and the types of information systems in organization structures. In the second part, clinical information systems and applications for diagnosis-treatment systems in Turkey are examined. Finally, the study evaluates applications in the health sector qualitatively from the new organizational structure, which is formed by information systems.

scholarly journals THE ROLE OF HEALTH INFORMATION SYSTEM IN MATERNAL AND CHILD HEALTHCARE SERVICES

2017 ◽  
Vol 10 (6) ◽  
pp. 29
Author(s):  
Rakhi Chowdhury ◽  
Leena Kumari ◽  
Subhamay Panda
Keyword(s):  
Health Care ◽  
Information System ◽  
Child Health ◽  
Health Information ◽  
Maternal And Child Health ◽  
Health Information System ◽  
Health Care Sector ◽  
Related Information ◽  
Health Related ◽  
And Child Health

Health information system deals with any system that helps in capturing, storing, transmitting, and managing health-related information of an individual or to demonstrate the activities or organizations working within health-care sector. In the developing countries, maternal and child health is gaining concern due to increasing cases of morbidity and mortality. The disparities among the maternal, infant, and child health are a growing concern in India and are governed by various determinants such as socioeconomic status, literacy, quality of health care, discrimination, and biological and genetic factors. Accurate and reliable health information and data are the basis for decision-making across the health-care sector and are crucial for the development and implementation of health system policy by the policy-makers. Strict monitoring and evaluation of the present program design and its implementation is required at the microlevel to effectively utilize the resources for the improvement of maternal and child health. Our present article focuses on evaluating the coverage gap at the different levels for the provision of health-care facilities to maternal, neonatal, and child health, immunization, and treatment of poor children. Big data plays a major role in providing sound and reliable health-related information and also help in managing and recording structured and unstructured data. More concrete plans are required further to reduce the inequalities in health-care interventions for providing better maternal and child health-care services in our nation.

scholarly journals Routine Health Information System Utilization for Evidence-Based Decision Making in Amhara National Regional State, Northwest Ethiopia: a multi-level analysis.

2020 ◽  
Author(s):  
Moges Asressie Chanyalew ◽  
Mezgebu Yitayal ◽  
Asmamaw Atnafu ◽  
Binyam Tilahun
Keyword(s):  
Decision Making ◽  
Information System ◽  
Health Information ◽  
Performance Monitoring ◽  
Health Information System ◽  
Evidence Based ◽  
Department Heads ◽  
Target Setting ◽  
Work Location ◽  
And Performance

Abstract Background: Health Information System (HIS) is the key to making evidence-based decisions. Ethiopia has been implementing the Health Management Information System (HMIS) since 2008 to collect routine health data and revised it in 2017. However, the evidence is meager on the use of routine health information for decision making among department heads in the health facilities. The study aimed to assess the proportion of routine health information systems utilization for evidence-based decisions and factors associated with it. Method: A cross-sectional study was carried out among 386 department heads from 83 health facilities in ten selected districts in the Amhara region Northwest of Ethiopia from April to May 2019. The study participants were selected using a simple random sampling technique. Descriptive statistics mean and percentage were calculated. The study employed a generalized linear mixed-effect model. Adjusted Odds Ratio (AOR) and the 95% CI were calculated. Variables with p-value <0.05 were considered as predictors of routine health information system use. Result: Proportion of information use among department heads for decision making was estimated at 46%. Displaying demographic (AOR= 12.42, 95% CI: [5.52, 27.98]) and performance (AOR= 1.68; 95% CI: [1.33, 2.11]) data for monitoring, and providing feedback to HMIS unit (AOR= 2.29; 95% CI: [1.05, 5.00]) were individual (level-1) predictors. Maintaining performance monitoring team minute (AOR= 3.53; 95% CI: [1.61, 7.75]), receiving senior management directives (AOR= 3.56; 95% CI: [1.76, 7.19]), supervision (AOR= 2.84; 95% CI: [1.33, 6.07]), using HMIS data for target setting (AOR= 3.43; 95% CI: [1.66, 7.09]), and work location (AOR= 0.16; 95% CI: [0.07, 0.39]) were organizational (level-2) explanatory variables. Conclusion: The proportion of routine health information utilization for decision making was low. Displaying demographic and performance data, providing feedback to HMIS unit, maintaining performance monitoring team minute, conducting supervision, using HMIS data for target setting, and work location were factors associated with the use of routine health information for decision making. Therefore, strengthening the capacity of department heads on data displaying, supervision, feedback mechanisms, and engagement of senior management are highly recommended.

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