Information Systems In Organizations

Future Trends in Organizational Information Systems

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INTRODUCTION OF INFORMATION SYSTEMS IN ORGANIZATIONS 

Task 1: Identification and Analysis

The usage and implementation of health information systems in any type of technical or data analysis helps to create and process real data and enhanced logistical values. The report of the topic maintains a space in finding the correct nature of the topic structures. However, the nature of the report study indicates the implementation of advanced health information systems in developed as well as in underdeveloped countries like Africa. The report structure revolves around the data analysis of the health information systems in the healthcare centers of Africa. The process of using and implementing upgraded information systems around the world that takes care of the data values and processes real time data figures as a health information system. Most of the African countries are unable to bear the expenses of a costly or a basic health information system, so the systems are imported from other first world countries. The project definition and the project assessment states the proper usage, meaning and overview of the healthcare information systems in Africa that can give a detailed informative structure for the report structure. The nature of the topic specification gives an annual observation point for the overall topic detail understanding regarding the information systems in different countries.

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Project Definition

The study has performed a secondary data analysis by evaluating various articles to analyze data regarding the implementation of Information systems in the Healthcare sector in Africa and the system can be called a "Health information system' that helps to maintain information related to patients, healthcare facilities, resources, disease as well as maintaining financial data. By using the CATWOE analysis tools the various factors in the case study scenario can easily evaluate the information system factors and identify problems of the system implementation.

CATWOE Service providers Service recipients Policymakers
Customers Patients and families, Insurance, resources Patients and families Nurses, Physicians, Pharmacist, Diagnosis centers, private hospitals
Actors Managers and policymakers, nurses, pharmacists, etc. Implementation of “Patients rights” Ministry of health, service providers, insurance.
Transformation a. Leadership and governance b. Human resource c. Drugs and other technologies d. Financial services e. Information system f. Service providers a. Leadership and governance b. Human resource c. Drugs and other technologies d. Financial services e. Information system f. Service providers a. Leadership and governance b. Human resource c. Drugs and other technologies d. Financial services e. Information system f. Service providers
World View Offering fast and effective health services as well as involving a clear payroll system based on the global standards Offering Promotions as well as maintaining the health of the patients through benchmarking method Maintaining accountability and health, promoting public health, maintaining the health infrastructure based on successful global models
Owner Administrative organizations and employment, medical science related universities Supporting patients rights as well as Organization Ministry of health
Environment Salary rates, Threats regarding Mental health and life Various medical expenses, lack of healthcare facilities and equipment Low budget, lack of equipment and resources and prioritization

Project Assessment

This study thus discusses the various possibilities of implementing the health information system in order to improve the facilities of the existing Healthcare system in developing countries such as African countries. It is also a factor that collecting different pieces of information from the non-harmonized tools makes this system difficult in managing storing data related to various paper-based forms or electronic forms (Al-Azzeh, 2018). The inadequacy and the less reliable data in the generalized HIS it is required to follow various approaches in making the information system included with various data that can be effective for improving the existing health care facilities. The study has identified that the healthcare facilities across the developing countries nowadays still face difficulties in getting accurate and reliable data regarding healthcare support and related information. For this reason, it becomes much more difficult in obtaining effective health results (Walsham, 2020). Therefore, this study is aiming to provide an overview of the factors of the Health Information system in limited resources and settings. Different Design approaches thus can be developed for structuring this Health information system and providing information about various requirements in this project.

The project assessment pointer believes the fact that the upgradation of the different tools for proper healthcare systems have proper belief systems regarding the patient’s health support and environment standards. 

According to the author Kavanagh and Johnson (2020), the healthcare information systems are updated according to the storage and data sharing methods due to which the reasoning collected in the report has similarities for the data research cases. The developmental; philosophy as well as the model are connected with each other in case of the healthcare information system pipeline. The report study for the health improvement is based on the overall developmental design in the healthcare information devices.

Problem Analysis

In this section, the study has given an overview of the health information system that includes various features and factors that the following HIS can include for the effective operation of the system. The various factors the HIS must include to eliminate the problems regarding low data availability and retrieving data related to the health care systems (ChePa et al. 2017). The various processor functions the Information that are included in points as follows: 

  1. Leadership and governance
  2. Delivery of health service
  3. Health-related information (i.e. Electronic medical records)
  4. Health workforce data
  5. Financing
  6. Resources and products

The following section covers some important functional points that are required in analysis and data recovery in the healthcare information systems as per the system availability and resources.

As per the opinions of the author Constantinides et al. (2018), there is a prolonged research case regarding the details of the healthcare based analysis of the information system as the data pointers of the collected pipeline format is not in use but the project requirements gives a clear observational viewpoint regarding the installation and upgradation of the information systems in African healthcare systems. The HIS (Health Information Systems) are a major example for the working process of the healthcare systems and homes to princess and treat patients with proper care and real time data upgradation methods. The processor functions mentioned in this section are added as per the healthcare system maintenance as the cost and time factor is the main thing (Tallon et al. 2019). The resources, financial operations, health workforce and other factors properly contribute to the annual availability of the correct data resources that are very much trustful for the healthcare management. One of the main phases is the system approach selection that uses engineering philosophy implementation.

Task 2: Approach Selection

IS Development Philosophy

The information system philosophy is the approach that is focused on processing information, representation of information and integrating that information with the help of technological means or technological supports. The two approaches or philosophies for developing an Information system are either by following socio-technical approach and engineering approach.

The Socio-technical approach is known as the most effective approach for developing information systems that are much more acceptable on delivering values to the end-user and stakeholders. This approach allows building research based on an independent approach, investigation of the design of the information system, cognitive engineering, "computer-supported work" (Fraua, 2019). The approach has certain characteristic phases that can properly denote the recurring engineering timeline.

On the other hand, the engineering approach of developing information systems follows a systematic approach in order to reach the end goal of the following information system and eliminating the issues (Udekwe and Andre, 2017). This is often known as Method engineering that offers an effective approach to configure various methods related to the development of an Information system. The various phases are analysis, requirements, identifying requirements, object and vision of the project, design of the system, design, development and the implementation of the system (Gesulga, 2017).

Therefore, it is important to create and envisage a particular methodological blueprint that is needed to implement the correct information management systems. For producing database labels and record connections, the produced data set values are deemed to be effective for developing the accurate information floaters by following the rapid reverse engineering channel instead of the socio-technical approach in linearity (Stepanenko and Kashevnik, 2017). For eliminating the remaining issues that are already related with the data loss also includes various related information on diseases and treatment and testing methods for enhancing the correct data filters in a sequential case. The developmental model structure connects down with the proper informational pointers of the philosophy section that can accurately comply in relation with the predefined accurate analysis.

IS Development Model

The study has followed the case report which shows that the existing health care systems in developing countries in Africa require to develop of a Health information management system that can effectively allow managing the data of the patients, disease, physicians, nurses, lab testing results, disease control methods etc and various other types of data that can be collected from the medical databases and websites (Holohan and Mcdonagh, 2017). For this reason, it is essential to follow a particular method within a Software development lifecycle (SDLC) for the development of this Health information system.

The following SDLC regarding the HIS is in the healthcare domain and provides a framework that can be used to improve the existing infrastructure of the healthcare system by managing large amounts of data properly.

The model includes different processes including requirement analysis, planning, designing the system, building the system and testing the system (Sheykhotayefeh et al. 2017).

The socio-engineering approach backfires certain drawback phases according to the different report topic sections that comply with the provision of the upgraded reverse engineering or proper engineering philosophy grounds. The materials that are similar in case of the implementation of the SDLC phase life cycle on the healthcare information systems provide a basic viable life expectancy according to the socio-technical aspects in the report case study. The viability required for correcting and adjusting the required concepts of HIS in treatment and data analysis is presented as per the data planning and design process structure.

As per the evidence of the author Von Krogh (2018), the engineering concepts are very much related with the IS development model assessed here as a small methodological table process. The data modeling is related to the conventional design access that is described properly.

Task 3: Design

Project Requirements

The project requirements of this report case study is applicable in lieu of certain record management of the hardware and system software manuals. The report study assesses the IS development model and its philosophy stage that can be processed as related data cases in separate sections. 

As per the data evidence of the author Duan et al. (2019), the data evaluation and engineering concept in IS developmental model is ratified in terms of the successful data model when it comes to perfectly evaluating and operating the healthcare information systems. In African cities, most of the hospitals depend on the productive welfare systems that are normal in nature and do not depend on man made resources.

But the repaired intervention in the informational checkup for the report case study retains the fact that the health information system management is not at all confined to one boundary but all other countries are bound to use the system for defining and recording correct treatment values according to the sequence. Therefore, producing all the required changes that are required to evolve, generate and produce the final implementation aspects and the approach selection can be fully confirmed in the light of specific health care parameters. One of the main issues regarding the project requirement cases for maintaining certain evaluated pointers is the cost secureness and machinery updation. The project validation is loosely based on the requirement crisis that can only be solved prior or after the health checking terms or record creation processes.

Design 1

The design sections in the section ratifies the correct implementation of the information system flow design that can be used to implement certain casse values and data formations in the recurring flow diagrams.

According to the reports of the author Chanias et al. (2019), there are design diagrams regarding the information flow and data entity design structures which refine the probable usage of the proper management patterns in HIS systems. The software used for creating these diagrams is draw.io that maintains a proper and simple environment variable in technical system based diagram formation. The influx pattern is created in special parameters as per the data availability is imported, extracted, processed and then collected as per the in-process inventory connection of the database records. The design cases are far more effective than the data flow designs in the case structure iterations that makes the overall entry and exit process in flow diagram conclusive as per source allocation (Lenart-Gansiniec, 2019). There is a calculated structure for each of the stirred data and entered record cases inside the healthcare information manual.

Information Systems In Organizations

The data entity design cases in this diagram specializes about the proper working of the healthcare information systems in a systematic database format. The main variables are termed as “patients”, “doctors”, “patient registration”, “medical record”,”health office” and mainly “administration”. The above information flow design states about the design processing stage of the health care data that is stored, processed, and varied in different tuple models (Dubey et al. 2021). The flow processes regarding the information flow design as well as the data entity design states about the working and data processing in the healthcare information systems. In this way, most of the hospitals and medical homes record, observe and provide accurate data results of the patients. The database creation is assessed according to the design format of the information software management that rectifies early stage errors and dysfunctionalities.

Design 2

The second design case shows the ERD design diagram that has also been done with the help of the draw.io software. Basically, this software creates analytical drawing cases that are required for joining and forming ERD or case diagrams as well as UML or class diagram too. 

As per the data structures of the author Baskerville et al. (2018), there are certain primary keys and foreign keys that are corresponding to the previous design diagram that is the data entity design flowchart. The attributes as well as the sub attributes are connected sequentially in reference to the cardinal pointer connection for the database design processing and importation because most of the data attributes have sub normalized data values in required value case boxes.

In contradiction, the author Schultz and Schultz (2020), all the keys are denoted with special schema relation that makes the healthcare system in manual compliance. There is a relational connection between the provided and not provided data structures that retaliate in connection with the provided valid attributes and their case pointers.

Hardware requirements- In order to develop the Health information system to be implemented in the Healthcare sectors in developing countries like African countries where the existing system has various issues related to improper data management, ineffective patient handling techniques, it makes the system time-consuming in providing healthcare service to the patients. The HIS requires different computing devices for displaying the data regarding patients and various clinical processes (Kaldahl and Kostveit, 2020). The system 

also requires developing a network with various devices in the healthcare facilities that may include servers for storing data, Routers, Switches, IP phones for communication.

Software requirements- The system requires various software systems for integrating with the hardware. These include proper Interfaces of the system, database management system, Business information system, Cloud-based services including cloud storage, security measures, etc.

Task 4: Implementation Plan

Actions

The action part is based on the radical working implementation of the HIS systems in poor and underdeveloped countries like Romania, Lithuania and Afriaca. Here, the action plan of the behavioral system design is maintained according to the reportive process that has been amplified as per the data resources.

According to the research cases of the author Kobusinge et al. (2018), the author states that various action strategies are maintained or required according to the phase based calculation or effective healthcare system planning but the African health center infrastructure is kept in mind. At first, the strategic plan of action is implemented and processed as per the detailed information plan process structure stated in the report structure. The implementation plan states about the seven phases that are mentioned as follows:

  • Planning outcomes.
  • Defining ownership outcomes.
  • Action to outcome processing.
  • Budget creation and role measurement.
  • Process accurate data track.
  • Implement project management method structure.

Reviewing final system requirements

The main process plan structure is divided into certain points that are called implementation plan pointers and project process creation. 

As per the data resources of the author Lowry et al. (2017), there are also some certain implementation action processes for the system project initiatives. The correct plan template in reference to the correct data filter is processed on the basis of the accurate project attribute cases in the plan sample structure shown below. 

The project implementation plan and ten stages are shown in a proper sequence because most of the data profile parts of the healthcare information systems are updated on a yearly basis. The system familiarity and the plan implementation in the HIS management requires low to medium and heavy data design cases that are provided as per the implementation timelines. 

After complying with the final data evaluation process in a single stemmed chain, most of the steps shows implemented action plan completion in accordance with the healthcare information system with proper management and termed care.

According to the collected data phases of the author Muhaise and Kareeyo (2017), the overall possible healthcare software is treated with process implementation stages and plan definition that is ideal for data creation. 

The implemented process action plan and project stages implicate that for regularizing the correct and error free system usage, the database design cases are updated for proper recording of the healthcare information systems in African hospitals and health homes. The timescale and data planning of the system projectiles are carefully upgraded in the light of a probable safe and transparent healthcare information device.

Timescale

The probable timescale series is calculated and added as a special chart data for the calculation of the implementation and the usage of the healthcare information systems.

According to the observations of the author Wang et al. (2018), there is a big difference in the schematic data observations of the Gantt chart data as the time periods are largely affected in case of the data planning and execution in separate case places. Most of the data value that is allocated in the project libre software complies with process concatenation with each of the predefined start and finish dates. The healthcare systems are properly connected and defined as per correct data parametric evaluation because all the relative functions required for Gantt process creation are accomplished. Once there is a shortage of the data methods all the other data resources are complied with each processes to form a combined data panel process.

(Source: Project Libre)

The Gantt chart shows the recorded validations in the accuracy measurement are processed, evaluated and then re-declared according to the same value numbers taken for the calculation sequences.

As per the data evaluation of the author Gupta et al. (2020), the data metrics are channeled in an up - right position as per the start and the end date that shows proper data metrics in the database column cases. The gantt data validations are not all collected as the limitations in the maintenance rate of the software system that is collectively known as “Healthcare information systems”. The data collection sequences are not well demonstrated due to which there is certain passage in the remaining data processes (Parker and Grote, 2022). The action implementation is further processed and corrected in correct channel data fields as because most of the channel data is either full or dismembered. Hence, all the data calculations are processed in the similar format to bring the analysis workbrain of the HIS into the normal state.

Conclusion

The conclusion of the topic states the fact that the healthcare information system is based on the philosophical concepts of socio-technical and engineering that are required for a complete and successful interaction process. Most of the database cases are required to follow the evaluation of the functional data cases in separate values. The topic sections are all clearly followed, evaluated and processed with incomplete accurate information as per the topic meaning and its specification. The reasons behind the co-operational information system management is discussed in terms of the proper evaluation sequences as because the data correlation is functional but not hereditary in nature. Most of the data processing is non functional as the information system devices are not updated in proper connection. The sections of the topic report are recorrected according to the requirements needed and then collected in the main data records from where the HIS management is compiled in case of data availability factor. The design cases for the information system inflow produces valid reasons in reference to the correct methods enacted as different implementation plans and stages collectively. All the data pointers are accessed in light of the proper data functioning and methodical planning for rational reasoning state.

References

Journals

Al-Azzeh, J., 2018. Information technologies for supporting administrative activities of large organisations. DESIDOC Journal of Library & Information Technology , 38 (3), p.187.

Baskerville, R., Baiyere, A., Gregor, S., Hevner, A. and Rossi, M., 2018. Design science research contributions: Finding a balance between artifact and theory. Journal of the Association for Information Systems , 19 (5), p.3.

Chanias, S., Myers, M.D. and Hess, T., 2019. Digital transformation strategy making in pre-digital organizations: The case of a financial services provider. The Journal of Strategic Information Systems , 28 (1), pp.17-33.

ChePa, N., Jasin, N.M. and Bakar, N.A.A., 2017, October. How change management can prevent the failure of information systems implementation among Malaysian government hospitals?. In AIP Conference Proceedings (Vol. 1891, No. 1, p. 020037). AIP Publishing LLC.

Constantinides, P., Henfridsson, O. and Parker, G.G., 2018. Introduction—platforms and infrastructures in the digital age. Information Systems Research , 29 (2), pp.381-400.

Duan, Y., Edwards, J.S. and Dwivedi, Y.K., 2019. Artificial intelligence for decision making in the era of Big Data–evolution, challenges and research agenda. International journal of information management , 48 , pp.63-71.

Dubey, R., Gunasekaran, A., Childe, S.J., Fosso Wamba, S., Roubaud, D. and Foropon, C., 2021. Empirical investigation of data analytics capability and organizational flexibility as complements to supply chain resilience. International Journal of Production Research , 59 (1), pp.110-128.

Fraua, L., 2019. Research evolution on implementation and adoption behaviour of Information Systems by Senior Managers in Commercial Organisations over the last 40 years.

Gesulga, J.M., Berjame, A., Moquiala, K.S. and Galido, A., 2017. Barriers to electronic health record system implementation and information systems resources: a structured review. Procedia Computer Science , 124 , pp.544-551.

Grover, V., Chiang, R.H., Liang, T.P. and Zhang, D., 2018. Creating strategic business value from big data analytics: A research framework. Journal of management information systems , 35 (2), pp.388-423.

Gupta, S., Drave, V.A., Dwivedi, Y.K., Baabdullah, A.M. and Ismagilova, E., 2020. Achieving superior organizational performance via big data predictive analytics: A dynamic capability view. Industrial Marketing Management , 90 , pp.581-592.

Holohan, J. and Mcdonagh, J., 2017, June. How information systems managers align business and information systems strategies in public service organisations: A practice-based taxonomy. In 17th European Academy of Management Conference (Vol. 21, pp. 21-24).

Kaldahl, E. and Kostveit, M.H., 2020. Health Information Systems in Developing Countries (Master's thesis, NTNU).

Kavanagh, M.J. and Johnson, R.D. eds., 2020. Human resource information systems . SAGE Publications, Incorporated.

Kobusinge, G., Pessi, K., Koutskouri, D. and Mugwanya, R., 2018. An Implementation Process of Interoperability: A Case-Study of Health Information Systems (HIS).

Lenart-Gansiniec, R., 2019. Organizational learning in industry 4.0. Problemy Zarz?dzania , (2/2019 (82)), pp.96-108.

Lowry, P.B., Dinev, T. and Willison, R., 2017. Why security and privacy research lies at the centre of the information systems (IS) artefact: Proposing a bold research agenda. European Journal of Information Systems , 26 (6), pp.546-563.

Muhaise, H. and Kareeyo, M., 2017. Electronic Health Information Systems Critical Implementation Issues (E-HMIS): District Health Information Software Version. 2 in the Greater Bushenyi, Uganda. American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) , 34 (1), pp.205-212.

Parker, S.K. and Grote, G., 2022. Automation, algorithms, and beyond: Why work design matters more than ever in a digital world. Applied Psychology , 71 (4), pp.1171-1204.

Schultz, D.P. and Schultz, S.E., 2020. Psychology and work today: An introduction to industrial and organizational psychology . Routledge.

Sheykhotayefeh, M., Safdari, R., Ghazisaeedi, M., Mohammadzadeh, N., Khademi, S.H., Torabi, V., Jebraeily, M., Maserat, E. and Farajolah, S.S.S., 2017. Hospital information systems implementation: an evaluation of critical success factors in northeast of Iran. Global Journal of Health Science , 9 (2), pp.91-101.

Stepanenko, V. and Kashevnik, A., 2017, April. Competence management systems in organisations: A literature review. In 2017 20th Conference of Open Innovations Association (FRUCT) (pp. 427-433). IEEE.

Tallon, P.P., Queiroz, M., Coltman, T. and Sharma, R., 2019. Information technology and the search for organizational agility: A systematic review with future research possibilities. The Journal of Strategic Information Systems , 28 (2), pp.218-237.

Udekwe, E. and Andre, C., 2017. The use of human resource information systems in two retail organisations in the Western Cape, South Africa. SA Journal of Human Resource Management , 15 , p.7.

Von Krogh, G., 2018. Artificial intelligence in organizations: New opportunities for phenomenon-based theorizing. Academy of Management Discoveries .

Walsham, G., 2020. Health information systems in developing countries: some reflections on information for action. Information Technology for Development , 26 (1), pp.194-200.

Wang, Y., Kung, L. and Byrd, T.A., 2018. Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological forecasting and social change , 126 , pp.3-13.

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