Benefits of Healthcare Information Technology

Introduction

Changes in the healthcare industry have necessitated healthcare facilities to implement cost-cutting measures by improving the efficiency of their operations. Declining reimbursements is one of the major factors that have led to the changes. Failure to implement cost-cutting measures poses a significant threat to the financial viability of healthcare organizations. Most healthcare organizations rely on information technology to improve the efficiency of their operations. IT also improves the competitiveness of the healthcare organizations. However, IT is a significant financial investment. Therefore, failure of IT to improve the performance of a healthcare organization may increase the rate of its decline. Due to the above factors, it is vital to determine the payoff of healthcare information technology. There is a raging debate on the payoff of the healthcare information technology. The debate is referred to as the ‘IT productivity paradox.’ It is vital for research to measure to the impact of IT on organizational performance. The success of IT implementation is dependent on the environmental factors within an organization. These include quality indicators and financial indicators. This research would strive to determine the impact of IT on the performance of a healthcare organization using the nature and extent of the process redesign initiatives. The research would strive to analyze literature on effectiveness of IT and process redesign (Boutros & Purdie, 2013).

During the 1970s, productivity declined compared to the previous two decades. This is despite the fact that the decline occurred when organizations started making significant investments in IT. There was a similar pattern of decline in productivity during the 1980s and early 1990s. During this period the output of workers declined by more than 10%. This trend discouraged organizations from deploying IT within their processes. However, there are studies that show that investment in IT actually increase the productivity of organizations. Investment in IT is one of the major factors that fuels GDP growth of modern economies.

At the firm level, investment in IT improves the productivity. It helps in improving the efficiency of the organization. This reduces wastage within the organization. Ultimately, it helps in improving the profitability of the organizations. This makes contemporary organizations be eager to implement IT in its processes. Business process reengineering also helps in improving the productivity and efficiency of organizations. It helps in determining processes that have wastage. Therefore, it is vital for organizations to combine business process reengineering with IT investment. IT investment should support the business process investment. Combining investment in IT and business process reengineering leads to a significant improvement in the efficiency and financial viability of organizations. This is regardless of the industry of operation of the organizations (Boutros & Purdie, 2013).

The research hypothesizes that organizations, which have environments where there is significant investment in technology and business process reengineering initiatives have improved performance. Therefore, the null hypothesis is that significant investment in technology and business process reengineering do not improve the performance of an organization. The research would test the fit between technology and business process reengineering using various variables for technology and business process reengineering.

Research Design

The research collected data of 4 hospitals that are in the health system for a period of 36 months that had implemented a decision support system (DDS) to help in evaluating their contracts. DDS helps in estimating the costs of expected services in comparison to the results of the services. It also helps in identifying areas that a hospital should cut costs and the operational improvements that a hospital should undertake to improve its financial viability. Time series data from a cross-sectional set of hospital would help in determining the impact of IT on profitability and quality.

Decision Support Systems (DDS)

Decision support system (DDS) is a computer system whose major function is to improve the productivity and effectiveness of managers. It has models that can help in evaluating the policies and alternatives of an organization. Therefore, it enables hospital managers to gain insights into the operations of the hospital and consider alternatives. This helps the managers in the development of business strategies. DDS is critical in operational decision making, managerial decision making, and strategic decision making. Operation decision making involves resource allocation and decisions that strive to improve operations at the patient care level of the hospital. On the other hand, managerial decision making involves cost containment, profitability of the department, and integration of the services of the department with those of other departments within the hospital. Finally strategic decision making involves contracting decisions, decision on whether the hospital should merge or acquire other hospitals, and pricing decisions (Sauter, 2011).

Hospital that took part in the study relied heavily on DDS in analysis of data and identification of areas for business process reengineering. DDS of the hospitals is designed to store financial, clinical, quality outcomes of all patients admitted in the hospital. It was also designed to store the duration of stay of the patients. DDS analyzes the data to determine best practices. It enables the hospital to measure its performance in comparison to the performance of other healthcare organizations (Sauter, 2011).

Data Analysis

Dependent Variables

Measures of profitability and quality

The research used revenues as a measure of the profitability of the hospitals that took part in the study. This is despite the fact that traditional measures of profitability deduct costs from the revenues. However, in a healthcare setting this is difficult due to various reasons. This includes the fact that most healthcare organizations do not have accurate cost accounting systems. The healthcare organizations mainly use a constant ratio of costs to charges (RCC) to find out the costs of services they offer. In addition, in a healthcare setting costs are affected by the different contractual agreements between hospitals and other parties. Hospitals may offer discounts to healthcare insurance providers or offer free charity care (Berger, 2008).

To prevent bias due to the varying length of stay of patients, the research used net revenue per day and the net revenue per admission as the measures of revenue of the hospitals. The revenues of the hospitals were multiplied by a certain constant to protect the confidentiality of the financial information of the healthcare facilities.

Customer satisfaction and mortality rates were the major measures of quality of the hospitals. Customer satisfaction was measured by determining the percentage of customers who tick the top box, which signified they were highly satisfied with the services, during the period duration of the research. On the other hand, mortality rates refer to the number of people who dies within 30 days of undergoing an operative procedure within the hospital divided by the number of operative procedures that the hospitals conducted during the period of the study.

Independent Variables

Technology Investment

The researchers collected monthly costs related to IT capital, labor and support for all the hospitals that were part of the study. In the research IT labor included all the costs associated with salaries, wages and other expenses involved in the management and supervision of DDS. IT support referred to consulting fees, programming of the DDS, software support, and maintenance of the DDS. IT capital referred to the costs of procuring DDS software and its associated modules.

Statistical Analysis

A chi square test of independence was used to analyze the data from the research. Chi square test is generally used to determine whether certain data sets follow certain patterns. The chi square test of independence is the most common chi square test. It classifies the variables into a two-way contingency table. The table contains the variables in a combination of row and column categories for easy analysis. The chi square test determines if there is a relationship (dependence) between the variable in the columns and rows (Geher & Hall, 2014). Below is the data of the study arranged in a two way contingency table:

H1 H2 H3 H4 Total
revenue per day 500 750 900 950 3100
revenue per admission 6 8 10 12 36
customer satisfaction 30 50 80 100 260
mortality rates 10 8 5 3 26
IT capital 10 20 30 40 100
IT labor 10 15 20 28 73
IT support 6 8 10 12 36

For the purpose of conducting a chi test of independence only the revenue per day and IT capital were considered. Therefore, the results of the study are listed below:

H1 H2 H3 H4 Total
Revenue per day 500 (494.06) 750 (745.94) 900 (900.94) 950 (959.06) 3100
IT capital 10 (15.94) 20 (24.06) 30 (29.06) 40 (30.94) 100
Total 510 770 930 990 3200

The Chi square of the above table would be

((500-494.06)2/494.06) + ((750-745.94)2/745.94) +……..((40-30.94)2/30.94) = 5.76

The value of chi square is small. Therefore, there is no major difference between observed and expected results. From the above table, the degree of freedom is (number of rows -1) (number of columns -1). Therefore, in this case degree of freedom is:

(4-1) x (6-1) = 3 x 5 = 15

The degree of freedom is 15

From the table testing the alpha level of 0.05 makes the critical chi square would be less than the calculated chi square. Therefore, we reject the null hypothesis of the study.

Results and Discussion

Below are the results of the study.

H1 H2 H3 H4 Total
revenue per day 500 750 900 950 3100
revenue per admission 6 8 10 12 36
customer satisfaction 30 50 80 100 260
mortality rates 10 8 5 3 26
IT capital 10 20 30 40 100
IT labor 10 15 20 28 73
IT support 6 8 10 12 36

From the above results, it is clear that technology investment had a significant effect on the quality and profitability of hospitals. Increased investment in technology reduced the mortality rates of the hospitals. Hospital 4 (H4) had the highest technology investment. In addition, the labor investment of the hospitals had a significant effect on the revenue per day of the hospitals. Investment in IT capital had an effect on the patient revenue per day and the revenue per patient of the hospitals that took part in the study. However, there IT support activities did not affect the profitability of the hospitals.

IT labor investment had a significant on the mortality rates of the hospitals. However, IT support investments did not have a significant effect on the mortality of patients. From the research, business process reengineering had a significant effect on the patient mortality and patient satisfaction. Business process reengineering had a significant effect on the financial performance of the hospitals.

Significance of investing in IT

The results of the study show that investing in IT has a significance effect on the profitability of organizations. It improved the financial viability of organizations. The study showed that investment in IT does not improve the financial performance of organizations immediately after its implementation. Organizations started seeing the benefits of investing in IT after 3 or more months. The research determined that the link between IT and profitability is stronger when one considers the customer or patient’s profitability. However, the research found varying support for investment in IT and support services. IT investment in consulting and other relevant support services did not have a significant effect on the profitability of the hospitals. IT investment had a significant effect on the quality within organizations. Therefore, the research proved the hypothesis as true.

Significance of business process reengineering

Business process reengineering initiatives attract heated discussions and controversy within organizations. The research showed that business process reengineering initiatives reduced mortality and increased patient satisfaction within the hospitals. However, organization cannot experience the benefits of business process reengineering immediately. Organizations experience the benefits a few months after undertaking business process reengineering. However, business process reengineering alone does not improve the financial viability of an organization (Boutros & Purdie, 2013).

Significance of business process reengineering with IT investment

Business process reengineering leads to significant changes in the processes of an organization. Modifications in the processes may make it face stiff resistance from the employees of an organization. This is due to the fact that it leads to significant changes in the roles of employees of an organization. Therefore, it is vital for business process reengineering to have management support. The combined effect of business process reengineering and IT investment improves the profitability of organizations. In fact, IT support and business process reengineering have the strongest impact on the profitability of organizations. However, business process reengineering and IT labor investment do not have a significant effect on the profitability of organizations. IT capital and business process reengineering affect the profitability of organizations especially if IT is used as an enabler of the business process reengineering of the organization. This is due to the fact that they improve the efficiency of the patient care.

Conclusion

The research highlighted the importance of IT investment in the profitability of organizations. IT investment and business process reengineering improve the efficiency of organizations. Improved efficiency reduces the operational costs and wastage, which in turn lead to an increase in the financial viability of organizations. The research proved the hypothesis was true. Testing the alpha level of 0.005 showed that the critical chi square was less than the calculated chi square. Therefore, the research rejected the null hypothesis.

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