Data Infrastructure to Reduce Hospital Management Costs

Background of the Study

Stemming from the difficulty of providing quality and affordable healthcare services, many countries have struggled to remodel their care delivery systems to minimize the effects of rising costs on access and delivery of services. Common cost drivers in current hospital management systems include lack of synergy among departments, fraud, operational inefficiencies, and poor decision-making (Gao, Niu and Shi, 2019). Using information technology (IT) tools to measure and assess data infrastructure is a relatively new area of research in the hospital management field intended to improve the efficiency of service delivery and financial planning activities (Merga, Debela and Alaro, 2019). However, this strategy has not gained traction in most healthcare settings as witnessed in a recent KPMC survey, which showed that only 10% of healthcare systems use data analysis tools to improve their productivity and efficiency (Srikanth, 2020, par. 1). The use of IT tools for better financial management in healthcare systems is supported by a change in data management infrastructure.

The concept of data infrastructure will be progressively used in this study to refer to a virtual network of financial information flow characterized by the adoption of automation tools in hospital management activities. Using Saudi Arabia as a case study, this research proposal seeks to investigate how changes in data infrastructure can lead to cost minimization through the adoption of better measurement and assessment techniques. The research aim, objectives, questions, and hypotheses underlying the investigation are highlighted below.

We'll create an entirely exclusive & plagiarism-free paper for $13.00 $11.05/page 569 certified experts on site View More

Research Aim and Objectives

The aim of this study is to investigate how middle managers and IT professionals could better measure and assess data infrastructure to reduce hospital management costs. It will be guided by three research objectives, which include finding out whether improvements in data measurement and assessment using IT tools can create financial synergy across healthcare departments and describing the potential of using digital infrastructure improvements to minimize fraud. Furthermore, it will be guided by the quest to understand inefficiencies in hospital management systems, and estimate the potential of using IT-enabled data analysis tools to improve financial decision support in the healthcare setting.

Research Questions

Three research questions will be answered in the study. The first one will explain whether improvements in hospital data measurement and assessment using IT tools can create financial synergy across healthcare departments. The second one will highlight the potential of using digital infrastructure improvements to minimize fraud and inefficiencies in hospital management systems and explain the extent that which IT tools can be used to support financial decision-making in the healthcare setting.

Hypotheses

It is hypothesized that improvements in data measurement and assessment using IT tools will create financial synergy across healthcare departments, minimize fraud and inefficiencies in hospital management systems, and support financial decision-making in the hospital setting.

Importance of Study

The findings of this study will be instrumental in enhancing the efficiency of the Saudi Arabian healthcare system by identifying possible areas of service delivery that could be improved to minimize costs. Data generated from the study may also inform key policy areas relating to financial resource management in the healthcare sector. Particularly, they may help policymakers formulate financially prudent policies that would maximize the value of IT tools in management (Ojo and Popoola, 2015). Moreover, the findings of this study will be integral in expanding the literature on effective healthcare management through an IT-focused strategy for augmenting cost management efforts. Overall, advances in the measurement and assessment of medical data, using IT tools, should ideally promote information flow and enhance the efficiency and productivity of healthcare systems globally (Gao, Niu and Shi, 2019). Besides enhancing collaboration and interoperability of healthcare departments, improvements in data infrastructure should also reduce operational costs and serve as a baseline for developing efficient healthcare management systems for long-term use.

Receive an exclusive paper on any topic without plagiarism in only 3 hours View More

Literature Review

Theoretical Framework

The attribution theory will be used as the main theoretical framework for the proposed study. Although not initially conceptualized for use in the healthcare field, its management roots have made it applicable in the sector as a way of reviewing the successes and failures of current healthcare management systems. For example, the attribution theory has been used in research studies that focus on creating a safer environment for workers and patients (Borkowski, 2015). The fundamental premise of applying this theoretical framework in the proposed study is its position that the reduction of hospital management costs could occur through the acknowledgment of errors that can happen in the healthcare management system. In the present study, IT is proposed as a tool for minimizing these errors. Proponents of the attribution theory argue that when these errors occur, they may lead to high healthcare costs and create feelings of cynicism, which affect the performance of the healthcare system (Lee, Ho and Forrest, 2019). By understanding how to minimize these miscalculations, managers can learn how to improve hospital management systems for better service delivery, as opposed to focusing on what they have failed to do correctly. The attribution theory provides a framework for achieving this goal.

Unavoidability of Hospital Management Costs

Most healthcare facilities have to incur specific operating expenses to remain functional. In light of these concerns, there is a need to distinguish diagnosis or treatment expenses from management costs. However, it is not an easy process because most healthcare cost categories overlap and an increase in certain overhead expenses may represent a positive economic performance for an institution (Nicholson et al., 2015). In the United States, more than $1.9 billion annually is wasted on hospital management costs. These expenses are indirectly related to a patient’s medical care. In most cases, these expenses are linked with governance and documentation processes as crucial areas associated with hospital management. Managers often strive to reduce these expenses by minimizing operational costs across various departments. However, Pema, Kiabilua, and Pillay (2018) caution that this approach could be detrimental to the overall success of a hospital’s financial management plan because some expenses have to be incurred for the survival of the healthcare facility. In this regard, managers who successfully reduce their overheads while maintaining vital processes that create additional value for the business are likely to improve their competitiveness in the long term.

Rising Hospital Management Costs

Globally, a turbulent economic environment and supply chain disruptions have contributed to the increase in hospital management costs. Different countries have experienced this problem in varied ways and degrees. The US alone incurs $750 billion in expenses that are indirectly linked to patient care (Health Management, 2020, par. 2). Most of these healthcare expenses vary, depending on the kind of operations undertaken by a hospital but most of the costs have been traced to a rise in administrative expenses (Smith et al., 2019). The US has been singled out as having the highest administrative costs globally as it accounts for about 25% of hospital expenses (Health Management, 2020, par. 3). Comparatively, these costs are lower in countries with a single-payer system, such as Canada or Scotland, because they rely on the government to pay such expenses (Nicholson et al., 2015). Since the operational structures of such hospitals are planned and grants are added as supplementary funds, hospital management costs should be suppressed to about 12% (Health Management, 2020, par. 4). Based on these statistics, it is estimated that a reduction in hospital management costs could save up to $190 billion annually in healthcare costs (Health Management, 2020, par. 1). However, it is unclear how these cost savings will be realized without a re-imagination of the existing data infrastructure.

Using Data Infrastructure to Reduce Hospital Management Costs

One of the most effective ways of reducing hospital management costs is optimizing available information flow systems in different areas of service delivery. This process entails innovating aspects of data management, such as billing procedures and data integration to create improved efficiency levels (Smit, Zemlin and Erasmus, 2015). In the US, it is estimated that 28% of transactions are done manually, thereby constraining the capacity to realize cost savings through data integration and optimization (Health Management, 2020, par. 2). The potential for realizing such savings through automation is enormous because reorganizing the data infrastructure could yield significant savings (Wass, Vimarlund and Ros, 2019). For example, the manual transactions fee is about $5, while the automation model only costs $1.60 (Health Management, 2020, par. 3). Based on differences in pricing models, it is estimated that $7 billion could be saved if health management systems are automated. Doing so could generate financial savings of up to 86% (Health Management, 2020, par. 3). These statistics have been used to affirm the potential for using IT tools to reduce hospital management expenses.

Get your 1st exclusive paper 15% cheaper by using our discount! Use a Discount

Enhancing the efficiency of hospital management processes through comprehensive digitalization is imperative in managing the high cost of healthcare. Particularly, it is projected that such a system could effectively manage the complexity and lack of transparency associated with current healthcare costing models (Schopf et al., 2019). However, there is scanty information regarding how healthcare professionals can use IT tools to better measure and assess data for purposes of reducing hospital management costs.

Summary

Based on the insights outlined in this literature review, much has been said about healthcare cost management in the US and other western countries. However, the information about Saudi Arabia is less known. Nonetheless, the Kingdom provides a unique case of healthcare cost reduction in the Middle East, characterized by rapid reforms aimed at improving access to quality healthcare services for all citizens. Indeed, for a long time, the kingdom has provided its citizens with affordable medical services; however, concerns about quality and high management costs persist. The proposed study will seek to fill this research gap by investigating how data infrastructure can be improved to reduce hospital expenses.

Methodology

Research Approach and Design

Qualitative and quantitative techniques are the main research approaches used in academic studies. The quantitative method is often applicable in investigations that have measurable variables, while researchers who employ the qualitative technique often want to manipulate subjective nuances of study (Patten and Newhart, 2017). The proposed study will use the quantitative research approach because managers can estimate data management and hospital expenses. In other words, healthcare cost is a quantifiable measure of assessment because it can be reviewed using numerical means.

The quantitative research approach will be descriptive and not experimental because it will be focused on evaluating data analytical methods for purposes of reducing hospital management costs. Comparatively, the experimental technique is associated with studies that measure subjects before and after an experiment (Patten and Newhart, 2017). The case study research design will be adopted as the main technique for executing the research strategies highlighted above. Saudi Arabia will be used as a case study because limited research investigations have explored the topic. Particularly, Saudi Arabia will be advanced as a unique case study in the Middle East to understand how data analytics can be used to reduce hospital management costs.

Struggle with a task? Let us write you a plagiarism-free paper tailored to your instructions 569 certified experts on site View More

Data Collection

Data will be collected using surveys as the main information-gathering technique. This data collection method aligns with the quantitative research approach described above because it involves the assessment of quantifiable research variables. Several researchers have used surveys to collect data because of its immense benefits, including high representativeness, low cost, convenience, reliable statistical significance, and little or no observer subjectivity (Bryman, 2016). The researcher will obtain survey responses using questionnaires that respondents will receive via email.

The questionnaire will be divided into two key sections. The first one will contain demographic data relating to the respondents, including their age, gender, education qualification, and work experience. The second part of the questionnaire will be designed to gather pieces of information that will be used to answer the research questions. This section is divided into three parts that represent three research focus areas (objectives) guiding this study – synergy creation, minimization of fraud and inefficiencies, and better financial decision support. These three areas of analysis will outline three thematic areas related to cost minimization in hospital management.

The thematic areas will be later analyzed to understand how they address the research aim, which is to explore the way data infrastructure can be better measured and assessed using IT tools to reduce hospital management costs. The informants will be required to state their views on four questions that are linked to each of the three thematic areas highlighted above. The intensity of their responses will be assessed using the five-point Likert scale, which measures a respondent’s views based on five criteria: “strongly agree,” “agree,” “neither agree nor disagree,” “disagree,” and “strongly disagree.” A comprehensive outlook of the questionnaire is available in the appendix section.

Data Sample

Data will be collected from four healthcare institutions located in the researcher’s city. The questionnaires will be emailed to healthcare practitioners located in the information technology (IT) departments of the above-mentioned institutions. The researcher intends to target 15 respondents from each department to gather 60 responses. There will be no gender bias in the selection of the participants, but they will be required to state their gender in the questionnaire. The researcher will randomly select informants who will give their views in the proposed study from each of the departments overseeing the IT operations of the four healthcare institutions highlighted above. This sampling strategy is selected for the proposed study because it eliminates bias in data collection (Kara, 2015). Therefore, the information generated will be objectively developed.

Data Analysis

The statistical package for social sciences (SPSS) will be used as the main data analysis software for this study. The analysis will involve descriptive tools of assessment, such as mean, frequencies, and standards of deviation to analyze data generated from the surveys. The justification for using this technique in the proposed study is rooted in its successful implementation in quantitative data analysis, as highlighted by Bryman (2016). Therefore, the software will provide a comprehensive analysis of the data.

Ethical Implications

The researcher will seek permission from hospital administrators of the four healthcare institutions before sampling the views of the respondents. All informants will also take part in the study voluntarily. Stated differently, the researcher will not coerce or offer them financial incentives to participate in the study. The researcher will record all information provided by the respondents anonymously to safeguard their privacy and allow them to withdraw from the study, at any point, without any repercussions.

Gantt Chart

The Gantt chart below provides time estimates for the completion of the research tasks

Activity Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 Week 8
Preliminary assessment X
Contacting Respondents X
Sending out Questionnaires X
Data Analysis X X
Writing the Final Report X X X

Reference List

Borkowski, N. (2015) Organizational behavior, theory, and design in health care. 2nd edn. London: Jones and Bartlett Publishers.

Bryman, A. (2016) Social research methods. Oxford: Oxford University Press.

Gao, H., Niu, H. and Shi, J. (2019) ‘Implementation of criteria-based audit to reduce patient’s burdens and improve efficiency in hospital management’, European Journal of Inflammation, 9(2), pp. 11-18.

Health Management. (2020) Identifying, controlling, and reducing overhead costs. Web.

Kara, H. (2015) Creative research methods in the social sciences: a practical guide. New York: Policy Press.

Lee, M., Ho, E. S. and Forrest, C. R. (2019) ‘Pierre Robin sequence: cost-analysis and qualitative assessment of 89 patients at the hospital for sick children’, Plastic Surgery, 27(1), pp. 14-21.

Merga, M., Debela, T. F. and Alaro, T. (2019) ‘Hidden costs of hospital-based delivery among women using public hospitals in Bale Zone, Southeast Ethiopia’, Journal of Primary Care and Community Health, 7(2), pp. 1-10.

Nicholson, K. et al. (2015) ‘Examining the prevalence and patterns of multimorbidity in Canadian primary healthcare: a methodologic protocol using a national electronic medical record database’, Journal of Comorbidity, 6(3), pp. 150-161.

Ojo, A. I. and Popoola, S. O. (2015) ‘Some correlates of electronic health information management system success in Nigerian teaching hospitals’, Biomedical Informatics Insights, 4(1), pp. 1-11.

Patten, M. and Newhart, M. (2017) Understanding research methods: an overview of the essentials. London: Taylor and Francis.

Pema, A. K., Kiabilua, O. and Pillay, T. S. (2018) ‘Demand management by electronic gatekeeping of test requests does not influence requesting behaviour or save costs dramatically’, Annals of Clinical Biochemistry, 55(2), pp. 244-253.

Schopf, T. R. et al. (2019) ‘How well is the electronic health record supporting the clinical tasks of hospital physicians? A survey of physicians at three Norwegian hospitals’, BMC Health Services Research, 19(934), pp. 456-466.

Smit, I., Zemlin, A. E. and Erasmus, R. T. (2015) ‘Demand management: an audit of chemical pathology test rejections by an electronic gate-keeping system at an academic hospital in Cape Town’, Annals of Clinical Biochemistry, 52(4), pp. 481-487.

Smith, M. W. et al. (2019) ‘Test results management and distributed cognition in electronic health record-enabled primary care’, Health Informatics Journal, 25(4), pp. 1549-1562.

Srikanth, B. (2020) Reduce cost of patient care in hospitals with data analytics. Web.

Wass, S., Vimarlund, V. and Ros, A. (2019) ‘Exploring patients’ perceptions of accessing electronic health records: innovation in healthcare’, Health Informatics Journal, 25(1), pp. 203-215.

Appendix

Questionnaire

Dear Sir/Madam,

We appreciate your time to take part in this study. This research is designed to investigate how data infrastructure can be better measured and assessed to reduce hospital management costs in Saudi Arabia. Please, tick (✓) on the appropriate boxes.

Demographic Data

  1. Gender
    • Please state your gender
      • Male
      • Female
  2. Age
    • What is your age?
      • 18-25 years
      • 26-35 years
      • 36-45 years
      • 46-55 years
      • over 55 years
  3. Education Qualification
    • Please state your education qualification
      • High School
      • Diploma
      • Undergraduate
      • Masters
      • Ph.D. and above
  4. Years of Work Experience
    • Please state your work experience
      • Less than 2 years
      • 2-5 years
      • 5-10 years
      • 10-15 years
      • More than 15 years

Part A: Synergy

  1. Data integration among departmental activities would improve financial synergy in the healthcare system
    • (Strongly Agree)
    • (Agree)
    • (Neither Agree nor Disagree)
    • (Disagree)
    • (Strongly Disagree)
  2. Improved measurement of hospital management data using IT would reduce the cost of communication among departments
    • (Strongly Agree)
    • (Agree)
    • (Neither Agree nor Disagree)
    • (Disagree)
    • (Strongly Disagree)
  3. Improved assessment of hospital management data using IT would reduce operational cost inefficiencies
    • (Strongly Agree)
    • (Agree)
    • (Neither Agree nor Disagree)
    • (Disagree)
    • (Strongly Disagree)
  4. Improved synergy among departmental activities using IT would lower administrative expenses
    • (Strongly Agree)
    • (Agree)
    • (Neither Agree nor Disagree)
    • (Disagree)
    • (Strongly Disagree)

Part B: Fraud and Inefficiencies

  1. Enhanced information management systems would minimize fraud and lead to cost savings
    • (Strongly Agree)
    • (Agree)
    • (Neither Agree nor Disagree)
    • (Disagree)
    • (Strongly Disagree)
  2. The adoption of IT tools in data management would increase efficiencies in healthcare management and lead to cost savings
    • (Strongly Agree)
    • (Agree)
    • (Neither Agree nor Disagree)
    • (Disagree)
    • (Strongly Disagree)
  3. Improved information management flow using IT communication tools would reduce management inefficiencies and increase the hospital’s cost-saving record
    • (Strongly Agree)
    • (Agree)
    • (Neither Agree nor Disagree)
    • (Disagree)
    • (Strongly Disagree)
  4. Adopting IT tools in keeping patients’ records would lead to improved cost savings due to efficiencies in data management
    • (Strongly Agree)
    • (Agree)
    • (Neither Agree nor Disagree)
    • (Disagree)
    • (Strongly Disagree)

Part C: Improving Financial Decision Support

  1. Adopting IT management tools would enhance financial planning in the organization
    • (Strongly Agree)
    • (Agree)
    • (Neither Agree nor Disagree)
    • (Disagree)
    • (Strongly Disagree)
  2. Enhanced data management tools would lead to improved cost savings through better resource management
    • (Strongly Agree)
    • (Agree)
    • (Neither Agree nor Disagree)
    • (Disagree)
    • (Strongly Disagree)
  3. Employing IT-supported tools in healthcare management would improve hospital costing systems
    • (Strongly Agree)
    • (Agree)
    • (Neither Agree nor Disagree)
    • (Disagree)
    • (Strongly Disagree)
  4. Integrating IT tools in data management would lead to an increase in the range of financial options available for management to manage hospital expenses
    • (Strongly Agree)
    • (Agree)
    • (Neither Agree nor Disagree)
    • (Disagree)
    • (Strongly Disagree)

Cite this paper

Select a referencing style

Reference

AssignZen. (2022, August 1). Data Infrastructure to Reduce Hospital Management Costs. Retrieved from https://assignzen.com/data-infrastructure-to-reduce-hospital-management-costs/

Work Cited

"Data Infrastructure to Reduce Hospital Management Costs." AssignZen, 1 Aug. 2022, assignzen.com/data-infrastructure-to-reduce-hospital-management-costs/.

1. AssignZen. "Data Infrastructure to Reduce Hospital Management Costs." August 1, 2022. https://assignzen.com/data-infrastructure-to-reduce-hospital-management-costs/.


Bibliography


AssignZen. "Data Infrastructure to Reduce Hospital Management Costs." August 1, 2022. https://assignzen.com/data-infrastructure-to-reduce-hospital-management-costs/.

References

AssignZen. 2022. "Data Infrastructure to Reduce Hospital Management Costs." August 1, 2022. https://assignzen.com/data-infrastructure-to-reduce-hospital-management-costs/.

References

AssignZen. (2022) 'Data Infrastructure to Reduce Hospital Management Costs'. 1 August.

Click to copy

This report on Data Infrastructure to Reduce Hospital Management Costs was written and submitted by your fellow student. You are free to use it for research and reference purposes in order to write your own paper; however, you must cite it accordingly.

Removal Request

If you are the original creator of this paper and no longer wish to have it published on Asignzen, request the removal.