Attitude and Perception of Patients Towards Health Information Management Service Delivery in General Out Patients Department; Case Study Nnamdi Azikiwe University Teaching Hospital (NAUTH) Nnewi, Anambra State
Chapter One
Purpose of the Study
To investigate the Attitude and perception of patients towards health information managements on service delivery to patients in NAUTH Anambra State, Nigeria.
Research Objectives
The study was guided by the following research objectives:
- To establish how data collection and entry can influence service delivery to patients in NAUTH in Anambra State
- To determine how data analysis influences service delivery to patients in NAUTH in Anambra State
- To establish how warehousing of data can facilitate communication on service delivery to patients in NAUTH in Anambra State
- To find out how data application influences service delivery to patients in NAUTH in Anambra State
CHAPTER TWO
LITERATURE REVIEW
Conceptual Review
The Concept of Health Information Systems
A functional component of a comprehensive healthcare system, a health information system (HIS) aims to enhance both individual and societal health. It is a management information system as a result. Hurtubise (1984) provided a thorough definition of a management information system, which he defined as a system that gives particular information support to the decision-making process at each level of an organization (Lippeveld, 2001).
With a limited amount of resources, the HIS structure should enable the generation of the data required for use in decision-making at each level of the health system. This pertains to the procedures used in a health system for gathering, processing, and disseminating information (Shrestha and Bodart, 2000). The term “Electronic Health Record” (EHR) refers to a comprehensive electronic record of a person’s health-related data that has been created and compiled over time across multiple health care organizations and is managed and consulted by licensed clinicians and staff involved in the person’s health and care (EHR & EMR, 2010).
Information is knowledge that has a purpose for the person receiving it. Data is the term used to describe information that is entered into a computer. Data is a raw input that, after being processed, produces an output known as information. Information is dispersed and stored in numerous types of devices in the modern world in a variety of formats. Accessing the appropriate information at the appropriate moment in a fairly organised way is a crucial demand (WHO, 2003).
The shift to performance-based resource allocation and the considerable gains in health-related resources mobilized in recent years, such as through the Global Fund for HIV/AIDS, TB, and Malaria, are driving up the demand for high-quality health information (GFATM). In the framework of such international initiatives, reporting obligations for nations are being increased, and outputs from short-term programs are routinely monitored (such as improvements in service provision and the number of people using such services) is now necessary as a component of systems that reward performance. Enhanced reporting of health outcomes, such as increases in life expectancy and quality, is also necessary to track progress toward important global objectives like the Millennium Development Goals (MDGs). Unfortunately, the demands for data resulting from such global and disease-specific activities frequently center on specific indicators and do not always translate into the development of systems that address both national and global health information needs. Because not enough money has been spent developing efficient health information systems that can produce data on the whole spectrum of health-related issues, the recent increase in demand for health information cannot now be satisfactorily supplied. (blaya, 2010).
The performance of a company’s healthcare systems can be enhanced by efficient data management. Health care workers can determine where systems are deficient, make necessary corrections, and follow outcomes by gathering, analyzing, interpreting, and acting on data for specified performance measures. This module’s goal is to inform users on how to collect, analyze, interpret, and use data for a particular performance measurement while also assisting them in understanding the connection between quality improvement and data management (duranti,1997).
Implementation of the Health Information Management in Public health institutions
Healthcare information is generated, transmitted, and stored using a variety of networking technologies, clinical databases, electronic health records, and other specialized biomedical, administrative, and financial technologies. An electronic health record is filled out with data from all healthcare providers, including hospitals, clinics, emergency rooms, small offices, and multispecialty groups. Then, through electronic communication, this information is networked to regional and national databases. Then, guidelines for prevention and treatment are used to channel data flows from EHRs and regional registries, which can then be processed further to produce information for decision-making and decision-support. If the management is effective, then data definition and transmission standards are both crucial.
A practical use of a health information system similar to the one described above in cancer information surveillance is covered by Shortliffe and Sondik (2006). In this illustration, EHR data is processed and used in a way that enhances cancer-related decision-making, leading to better cancer patient care. As a result, monitoring, managing, and controlling the cancer care utilizing health information technology. Wootton (2009), Chan and Kaufman (2009), and (2010) have demonstrated that there are a number of impediments and enablers to hospitals adopting electronic records. They include a lack of funding for the acquisition, worries about maintenance expenses, physician reluctance, an ambiguous return on investment, and a shortage of staff with the necessary IT skills. Four of these five issues were less frequently cited as major adoption hurdles in hospitals that had adopted electronic records systems compared to institutions that had not (Ashash et al. 2009). The evidence foundation supporting its practical usage is thin, despite the belief that technology can and does have a positive impact on healthcare (Wootton, 2009). In actuality, many decisions about the acceptance of new medical technology are undertaken without knowledge of the consequences of doing so (Kazanjian & Green, 2002). Decision-makers rarely receive feedback on the results of their decisions, including feedback on the effectiveness, costs, ethical, legal, or societal ramifications of technology, and are frequently ignorant of the knowledge they lack (Wootton, 2009).
The availability of information on the selection of new technologies is frequently unstructured and ambiguous, which is further exacerbated by the growing number of technologies and their growing complexity, in addition to the dearth of study on evidence for making informed selections (Ruder et al 2008, Chan and Kaufman 2010). The costs of hardware and software, the accessibility of broadband and mobile networks, the creation of user interfaces and applications in languages other than English, as well as ongoing maintenance costs, to name a few, are some specific issues with the use of ICT that are generally better understood (Wootton, 2009). As Ruder (2008) has remarked, while thinking about technological advancements in healthcare, a fuller understanding of the social, political, and economic limitations also known as the “soft barriers” is sometimes lacking (Ruder et al 2008). This study looks into how improved health information management can improve health record management in order to fill this obvious knowledge gap.
CHAPTER THREE
RESEARCH METHODOLOGY
Introduction
This chapter looked at the research design, target population, sample size, sampling techniques, data collection instruments and procedures, validity, reliability of the study and data analysis components.
Research Design
The research problem was studied through the use of a descriptive survey research design. According to Kothari (2004), descriptive research is concerned with specific predictions, with narration of facts and characters concerning situation. The descriptive design is preferred since it is carefully structured to ensure complete description of the situation, making sure that there is minimum bias in the collection of data and to reduce errors in interpreting the data collected.
Target Population
The target population of the study was 773 employees of Nnamdi Azikiwe University Teaching Hospital (NAUTH). The target population included people from senior management, health records, audit and accounts and Information and Communication Technology (ICT).
Sample Size and Sampling Procedures
Sampling is the process of choosing a number of individuals for a study in such a way that the individuals selected represents the larger group from which they are selected hence representing the characteristics found in the entire group (Orodho, 2003).
CHAPTER FOUR
DATA ANALYSIS AND PRESENTATION OF FINDINGS
Introduction
This chapter presents the data analysis, presentation, interpretation and discussion of the findings. The study assessed the Attitude and perception of patients towards health information management on service delivery to patients at NAUTH, Anambra State, Nigeria. The chapter is divided into various sections namely; response rate, the demographic information of the participants and the study objectives specifically; investigated how data collection and entry can influence service delivery to patients, determined how data analysis influences service delivery to patients, established how warehousing of data can facilitate communication on service delivery to patients and find out how data application influences service delivery to patients in NAUTH in Anambra State. The chapter starts with the response rate and then demographic information of the participants.
CHAPTER FIVE
SUMMARY OF FINDINGS, CONCLUSION AND RECOMMENDATIONS
Introduction
This chapter summarized the findings, gave conclusions and recommendations. It also suggested areas for further research in the following sub themes
Summary of the study findings
Based on the data and information analysed in chapter four. The findings are summarized in this section.
Demographic characteristics of respondents
The findings indicates that most 149(61.1%) of the respondents were male and majority 88(36.1%) of the respondents were of the ages between 28 to 37 years. In addition, majority 137(56.1%) of the respondents were protestants. Further to that, majority 118(48.4%) of the respondents had tertiary level of education and most 60(24.6%) had University level.
Influence of data collection on service delivery to patients
The study findings suggested that the respondents tended to agree (Mean=3.92) that suitable education and training to those who collect data improved accuracy, hence efficient service delivery. In addition, it emerged from the study that the respondents agreed (Mean=4.01) that development of data collection instrument that explored methods to access needed data ensured efficient service delivery. Similarly, the study findings suggested that the respondents agreed (Mean=4.16) that data definition and data precision impacted from comprehensive data collection improved quality service delivery. Further, the study findings suggested that the respondents agreed (Mean=4.19) that adoption of standardized data collection and integrated/ interfaced systems ensured data consistency hence, improved service delivery. Finally, it emerged from the study that the respondents agreed (Mean=4.05) that pilot of the data collection instrument ensured data relevancy, thus efficient service delivery. For correlation analysis, the findings shows a strong positive relationship (r =.653; p= .000; α = 0.05) between data collection and service delivery to patients.
Influence of data analysis on service delivery to patients
The study findings suggested that the respondents tended to agree (Mean=3.94) that an appropriate use of algorithms, formulas, and translation systems improved service delivery. In addition, it emerged from the study that the respondents agreed (Mean=4.05) that ensuring that all pertinent data impacting the application were analyzed appropriately improved data comprehensiveness hence, efficient service delivery. Similarly, the study findings suggested that the respondents agreed (Mean=4.34) that data analysis under reproducible circumstances by use of standard formulas, scientific equations, variance calculations adopted ensured data consistency, hence efficient service delivery. Further, the study findings suggested that the respondents agreed (Mean=4.13) that data displayed to reflect the purpose for which they were collected ensured clear definitions of data, hence quality service delivery. Finally, it emerged from the study that the respondents agreed (Mean=4.02) that timely data analysis allowed for the initiation of action, thus efficient service delivery. For correlation analysis, the findings indicates a strong positive relationship (r =.672; p= .000; α = 0.05) between data analysis and service delivery to patients.
Influence of data warehousing on service delivery to patients
The study findings suggested that the respondents tended to agree (Mean=3.78) that appropriate edits put in place ensured data accuracy, hence improved service delivery. In addition, it emerged from the study that the respondents tended to agreed (Mean=3.84) that technology and hardware impacted data accessibility, hence enhanced service delivery. Similarly, the study findings suggested that the respondents agreed (Mean=4.29) that management of relationships of data owners, data collectors, and data end-users to ensured awareness of the data availability in the inventory and accessible systems. Further, the study findings suggested that the respondents agreed (Mean=4.18) that warehousing employed edits or conversion tables by coordinating edits and tables to ensure consistency, hence improved service delivery. Finally, it emerged from the study that the respondents agreed (Mean=4.05) that continually updating of systems, tables, and databases ensured data currency, thus efficient service delivery. For correlation analysis, the findings revealed a strong positive relationship (r =.708; p= .000; α = 0.05) between data warehousing and service delivery to patients.
Influence of data application on service delivery to patients
The study findings suggested that the respondents tended to agree (Mean=3.73) that a clearly determined aim for collecting data improved data accuracy, hence quality service delivery. Similarly, it emerged from the study that the respondents tended to agreed (Mean=3.92) that legality of the available data to be collected for application improved data accessibility, hence enhanced service delivery. In addition, the study findings suggested that the respondents agreed (Mean=4.27) that clarification on data usage and identification of end-users, enhances data comprehensiveness, thus efficient service delivery. Further to that, the study findings suggested that the respondents agreed (Mean=4.11) that consideration of the changes in appropriateness or value of an application improved data currency, thus enhanced service delivery. Finally, it emerged from the study that the respondents tended to agree (Mean=3.89) that adequate staffing was ensured through continuous patients‟ census. Correlation analysis, shows a strong positive relationship (r =.678; p= .000; α = 0.05) between data application and service delivery to patients.
Conclusion of the study
From the findings, the study concluded that; health information management through effective data collection, data analysis, data warehousing and data application influences service delivery to patients. Consequently, data collection in terms of suitable education and training to those who collect data, adoption appropriate data collection instruments and comprehensive data collection improves data relevancy, consistency, accuracy and precision hence positively influence service delivery to patients. Similarly, data analysis through appropriate use of algorithms, formulas, and translation systems, use of standard formulas, scientific equations, variance calculations and timely data analysis improves data relevancy, consistency, accuracy and precision hence positively influence service delivery to patients. In addition, data warehousing in terms appropriate edits, technology and hardware adoption, continually updating of systems, tables, and databases improves data relevancy, and consistency, accuracy and precision hence positively influence service delivery to patients. Finally, data application through clearly determined aim for collecting data, legality of the available data, clarification on data usage and identification of end-users and continuous patients‟ census improves data relevancy, and consistency, accuracy and precision hence positively influence service delivery to patients.
Recommendation of the study
In reference to the findings, conclusions and the guidance from the literature review, it was clear that health information management enhances services delivery to patients. Therefore, the hospitals administration, policy makers and other health stakeholders should ensure;
Effective data collection through adequate training and education of data entry clerks, adoption of appropriate data collection instruments.
Appropriate data analysis procedure in terms of usage of suitable algorithms, formulas, and translation systems, use of standard formulas, scientific equations, variance calculations.
Efficient data warehousing through appropriate technology adoption, edits and continuous update of systems, tables and database.
Appropriate data application through clearly determined aim for collecting data, legality of the available data, clarification on data usage.
Suggestions for further studies
The researcher suggests the following further areas of research
- A similar research should be carried out in a different institution to determine if the health information management still influence service delivery to
- A research should be carried on the influence of other elements of health information management on service delivery to
- A research should also be carried on the entire health institution in the country to determine the effects of health information management on service delivery to patients in Nigeria.
- Further research should be done on the mediating effects on the relationship between health information management and service delivery to
- Future studies need to test significant levels of the findings of the hypothesis using chi square
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