Differential Effects of the Two Types of Information Systems: A HospitalBased Study

Journal of Management Information Systems Summer 2009, Vol 26, No 1, pp 297–316 © 2009 M E Sharpe, Inc 0742–1222 2009 9 50 + 0 00 DOI 10 2753MIS0742 1222260111 Differential Effects of the Two Ty.Nirup M. MeNoN is an associate professor of Information Systems at george Mason university and a Visiting professor at the Instituto de Empresa Business School, Madrid, Spain. He has previously held teaching appointments at the university of Texas at Dallas and Texas Tech university. His research interests include economics of information systems, business value of information technology, enterprise systems, information privacy, and information security. Dr. Menon has published in several leading information systems journals, including Management Science, Information Systems Research, and Journal of Management Information Sy

Journal of Management Information Systems / Summer 2009, Vol 26, No 1, pp 297–316

© 2009 M.E Sharpe, Inc 0742–1222 / 2009 $9.50 + 0.00 DOI 10.2753/MIS0742-1222260111

Information Systems: A Hospital-Based Study

NIrup M MENON, ulku YaYlacIcEgI, aND aSuNur cEzar

Nirup M MeNoN is an associate professor of Information Systems at george Mason university and a Visiting professor at the Instituto de Empresa Business School, Madrid, Spain He has previously held teaching appointments at the university of Texas at Dallas and Texas Tech university His research interests include economics

of information systems, business value of information technology, enterprise systems, information privacy, and information security Dr Menon has published in several

leading information systems journals, including Management Science, Information Systems Research, and Journal of Management Information Systems

ulku YaYlacicegi is an assistant professor of Information Systems at cameron ness School, university of North carolina at Wilmington She obtained her ph.D from the university of Texas at Dallas Her research interests span information communica-tions technologies, telecommunications policy, information security, IT productivity, health-care IT, quality management, and innovative education Her research has ap-

Busi-peared in, or is forthcoming in, Technology in Society, Industrial Management and Data Systems, Journal of Information Systems Applied Research, and International Journal of Innovation and Learning

asuNur cezar is a ph.D candidate in the School of Management at the university

of Texas at Dallas She has received degrees in computer engineering, financial gineering, and supply-chain management Her research focuses on the economics of privacy and security, and economics of information systems Having more than eight years of experience in IT industry, she has participated in the design, development, and launch of leading-edge technology solutions

en-abstract: a new empirical model for the production function of the hospital rating two types of information systems (IS) is developed One type of IS is represen-tative of information technology (IT) used in primary, clinical, value-chain activities, and the other is representative of the IT used in support (administrative) value-chain activities The model innovation is that it accommodates up to a seven-year lag for each type of IS The output variables for the production function are hospital output and medical labor productivity using data spanning from 1979 to 2006 from several hospitals, it was found that clinical IS improve hospital output in the short run (of two years) administrative IS were found to be negatively associated with organizational performance in the short run, but positively associated with these performance measures over the long run (over four years) These results highlight the importance of timing

incorpo-IT investments and the sequencing chosen for the implementation of IS presenting various value-chain activities, and the resulting pattern of business value over time

Differential lag length of the types of IS is to be considered in estimating the rate of return of new IT projects.

keY words aNd phrases: health-care informatics, IT productivity, value-chain model

despite the dowNturN iN the iNforMatioN techNologY (IT) industry since the late 1990s, investments in IT have not decreased [28] IT adoption in health care has been increasing rapidly u.S health-care costs, as a percentage of gross domestic product (gDp), continue to grow, but hospitals have been laggard in adopting IT [22] The rate of growth of expenditures in IT by health-care organizations is gradually catching

up with the rate of growth of health-care costs [44] Industry analysts report that IT spending at hospitals was $15.4 billion out of the $23.6 billion that the u.S economy spent on health-care IT in 2003 [18, 33] current forecasts indicate that health-care

IT spending will surpass $39.5 billion by 2010 [40]

The benefits of IT in hospitals are manifold Hospitals and Health Networks’ 2005 Most Wired Survey and Benchmarking Study reported significantly lower mortal-ity rates for the most wired hospitals (i.e., those with the highest rate of investment

in IT) [46] preventable medical errors rank as the sixth leading cause of death in america [51] The mortality rank of medical errors is ahead of those for diabetes, liver disease, and pneumonia The lower mortality rate in the most wired hospitals

is said to be due to the greater adoption of computerized physician order entry, more accurate medication order and delivery, and better decision support (e.g., information

is maintained on duplicate orders, drug–drug interaction, dose checking, and allergy alerts) Hospitals classified as the most wired environments not only excel in lowering the mortality rates but also generate 5.4 percent more net patient revenues per full-time employee compared to the u.S hospital average of 2.9 percent [46] The most wired hospitals also recorded a 3.8 percent decrease in paid staff hours per hospital discharge, compared to the u.S hospital average decrease of 1.8 percent

Despite the potential benefits of IT, it is not clear whether hospitals are investing

in the appropriate IT, how different types of IT are timed and sequenced, and what returns are obtained over time as a result [5, 23] One reason for the lack of clarity

is that hospitals possess a dichotomous structure whereby administrators and cal staff form two “branches,” contending for resources, working under different constraints, and aiming for different objectives [26] There is some evidence that the use of different ITs affects contemporary hospital performance [5, 7, 17] The performance of hospitals with specific administrative IT applications (accounts pay-able and receivable, payroll, personnel administration) has been found to be different from those with specific clinical IT (e.g., electronic health records, electronic lab results, electronic clinical notes systems, electronic images throughout the hospital,

medi-electronic lab orders, medi-electronic reminders for guideline-based interventions, and e-prescribing) [23].

The value-chain model is often used to determine the business value of activities in

an organization [43] One estimate puts the contribution of primary activities tory, production, sales, marketing, customer service) to value-added at 65.2 percent and the contribution of support activities (firm infrastructure, human resources, technology, research and development) at 34.8 percent [1, p 22] from an IT per-spective, it is instructive to ascertain the business value of information systems (IS) following this nomenclature of activities administrative IS in this paper represent

(inven-IT in support value-chain activities, and clinical IS are representative of the (inven-IT in primary value-chain activities in a hospital It is argued that information transac-tions generated by primary activities possess higher value because of their revenue potential [32] IT for value-chain activities integrates product and customer data across various departments and sites, thereby affecting output directly, and has also

been termed information technology for core competence [19, 39, 48, 58] although

competitive advantage is not the focus of this paper, productivity enhancements over time are considered necessary for competitiveness [4, 15, 45] primary activities are dependent not only on other primary activities but also on many support activities This type of interdependence of processes in an organization must guide the timing and sequence of acquisition and upgrading of IT Support activity IT is also useful for generating long-term benefits because, for example, post hoc (after-sales) analy-sis of accounting data can provide unique insights for future value-chain activities long-term value of IT comes from the long-term value of information Once created, databases such as customer records provide value even when transported from an old system to a new one [32] as a result, the maturation rate—that is, the pattern of business value of IS over time—of different types of IS will differ One way to find this pattern is to measure the effect of costs of different types of IS on performance over several years [10, 55]

an elaborate model of hospital production function is presented, which helps to unravel patterns in the business value of types of IS Evaluating differential effects of types of IS has implications for IS project management and IS policy in accounting, among others With respect to IS project management, the empirical evidence that different types of IT applications have varying patterns in how returns on investment surface is enlightening

The long-term association between the costs for two major types of IT, and hospital output and labor productivity measures is estimated for a sample of hospitals span-ning from 1979 to 2006 The extensive panel data analysis, because it encompasses many generations of technology, enables more generality in interpreting the results, for a broader understanding of the impact of IT investment in the health-care indus-try current and lagged (past years) capital depreciation amounts on two types of

IT served as independent variables that approximate the long-term capabilities of each type of technology The two kinds of IT were found to exhibit different effects

on the dependent variables over time lags of clinical IS boosted hospital output

administrative IS were related to an initial drop in organizational performance but improved performance in the long term.

Hospital IT and Business Value

the electroNic health record, a clinical IT application, contains information ing a patient’s medical history—illnesses, digital radiology images, a list of allergies, billing records, and so on Electronic medical records have numerous advantages over paper records, including increased accuracy; decreased medical errors and mortality rates; improved efficiency; lowered costs; and better, safer, and more equitable care [2, 3] Electronic records also allow improved privacy and thus better compliance with privacy regulation [13] policymakers call for the universal adoption of electronic health records by 2014, but the industry is unlikely to meet this deadline given its current adoption rates [30, 36]

regard-In a study by Jorgenson and colleagues [30], health care’s weighted average tribution to the annual u.S productivity growth rate between 1997 and 2000 ranked within the bottom two, with a –10 percent growth rate, compared to a 15 percent growth rate in the field of computers and office equipment The Healthcare Informa-tion and Management Systems Society’s 2002 leadership survey listed the barriers

con-to implementing IT in health care as limited vendor ability and end-user acceptance, difficulty in providing return on investment, lack of IT strategy, and insufficient financial and management support [50] productivity lags in labor-intensive service industries, such as health care [6]

The health-care IT literature has sought to determine the value of IT in this conscious industry (Table 1) Teplensky et al [49] focused on technology adoption Teplensky et al investigated hospitals’ reasons for investing in new technology (in their study, magnetic resonance imaging technology), and found that technology adoption was associated with the strategic orientation of health-care organizations unlike the single technology focus of Teplensky et al., Burke and Menachemi [11] and Menachemi et al [38] looked at overall technology diffusion in hospitals Burke

cost-et al [12] associated IT adoption diffusion with various characteristics of hospitals, such as size and competition They also found that hospitals with high technology diffusion adopted strategic IT more readily, whereas hospitals with less technology diffusion were mostly limited to adoption of administrative IT Menachemi [37] found that hospitals with high technology diffusion also excelled in quality In a cover story,

BusinessWeek reported on a hospital that, after spending over $72 million in IT projects over six years, entered electronically only 10 percent of its tests and orders [41] Other studies looked at postadoption effect of technology for example, Burke et al [12] observed operational financial improvements following health-care IT investments Walker et al [52] pointed out the financial value enhancement effects of standard-ized health-care systems Some studies such as Devaraj and kohli [17] focused on postadoption effects of a single technology Devaraj and kohli found that a decision support system had a positive effect on performance in health-care settings with a three-month lag, using a data set of eight hospitals over three years kramer et al

Table 1 Hospital Information

The studies are limited to one type of technology adoption or a single hospital.

as more time elapses after implementation

Only impact of electronic medical records adoption is in

The study is limited to one type of IT

Financial gain associated with health-care IT

Count of applications used as measure of IT

[31] examined one psychiatric hospital and reported significant positive performance consequences of investment in electronic medical record technology Mekhjian et al [36] observed efficiency improvements along with reduced medical errors in an aca-demic medical center after the implementation of physician order entry and electronic medical administration record systems Wang et al [53] studied the financial impact

of electronic medical record systems

Two works that looked at how the presence of types of IT affects performance are Bhattacherjee et al [5] and Borzekowski [7] The independent variable is the count of the number of applications of each type of IT—administrative, clinical, and strategic Borzekowski [7] used hospital costs as the performance variable, whereas Bhat-tacherjee et al [5] used a performance score variable collected from an accreditation organization for hospitals Both found support for a positive association between an index for clinical IT and performance, but not for other types of IT Both studies did not analyze the pattern of costs of different IS and the resulting pattern of returns obtained from these IS

The reasons the costs and values of administrative and clinical IS differ over time stem from differences in types of value-chain activities, acquisition pattern, and us-age pattern usage and adoption of administrative IT is likely to be high, because administration’s tasks for communicating, coordinating, controlling, and planning are enhanced through IT [24] physicians possess considerable influence in the clinical side, and have resisted adopting clinical ITs [7, 24] To date, no study has compared the patterns of costs and value of the two types of IS over time

Data Overview

The annual cost accounting data for each hospital are available at the subunit level

in each hospital costs comprise salaries, capital depreciation, supplies, purchased services, rental and lease expenses, and miscellaneous expenses for each hospital, the data contain inpatient and outpatient revenues, inpatient days, outpatient visits, and number of beds To homogenize the hospital population, we included only gen-eral medical and surgical hospitals in the sample.1 Because the data spanned several years, during which the u.S economy and the medical environment underwent sev-eral changes, we deflated all monetary variables to remove macroeconomic and time effects across observations: (1) salaries, employee benefits, and professional fees in all accounts for each hospital were deflated by the employment cost index for health-care services, obtained from the Web site of the Bureau of labor Statistics [42];

(2) other expenses—depreciation, rental and lease, supplies, purchased services, and miscellaneous expenses—were deflated by the producer price Index for hospitals; (3) revenues—inpatient and outpatient—were deflated by the consumer price Index for health-care services.

The hospitals followed the same reporting format2 so that the department name and definition provided by WaDoH were useful in classifying the major capital deprecia-tion Examples of departments in a hospital are data processing, admitting, patient records, hospital administration, accounting, and personnel

Independent Variables: Two Types of IT

capital depreciation in departments identified as clinical or administrative was proximated as a measure of the department’s IT capability The variance in capital depreciation across hospitals and over time is a proxy for IT infrastructure variance across hospitals and time IT infrastructure is defined as “the base foundation of the information technology portfolio, which is shared throughout the firm in the form of reliable services” [1, p 258] Thus, even without application-level data, we expected that the capital depreciation of infrastructure would provide a reasonable proxy for IT acquisition pattern, and perhaps to some degree, the adoption and usage patterns ag-gregating capital over several departments has the advantage over a finer grain for IT in that the latter would require an inventory of all hardware and software technologies in all hospitals The quantity of data (the number of hospitals and years) prevented such

ap-a detap-ailed ap-anap-alysis It is useful to meap-asure IT in terms of cap-apitap-al depreciap-ation (rap-ather than presence or absence of application), because more costly applications require better quality infrastructure Some have argued that superior infrastructure has direct organizational benefits [8, 31, 39, 48], whereas others have regarded infrastructure as

a competitive necessity [1]

Departments in which capital is primarily clinical IT are patient accounts, patient records, admitting, and pharmacy [29].3 again, the underlying assumption is that this is the infrastructure that most affects clinical applications an objective of these departments is to reduce errors in treatment by better maintaining the medical his-tory of patients, helping to reduce the confusion that can be caused when patient care

is provided by multiple entities, including the hospital and physicians proper use

of clinical IT avoids redundant tests, which lowers operating costs [17] clinical IT helps maintain records of billings and payments to physicians and other health-care providers for administrative IT, we summed the capital depreciation from utilization management, management engineering, hospital administration, nursing administra-tion, data processing, personnel, purchasing, accounting, and communications

Dependent Variables

Most hospitals in the state of Washington are not-for-profit organizations and strive

to reduce costs Hospital output and labor productivity are important outcomes in the health-care industry Hospital output is measured by the number of adjusted patient

Table 2 Descriptive Statistics and correlations

correlation matrix

Note: all pearson correlation coefficients significant at < 0.0001

days of patient care The adjusted patient days measure was the sum of inpatient days and outpatient “days” (i.e., visits converted into a days measure according to the proportion of inpatient revenues and outpatient revenues).4 labor productivity was calculated in two ways: (1) hospital charges divided by total salaries, and (2) adjusted patient days divided by total number of employees The former measure can be thought

of as a price-weighted average of the latter measure accordingly, the former measure accounts, to some degree, for the differences in the types of cases a hospital faces, as well as the skill levels of employees

Descriptive statistics (mean, standard deviation, and the correlation matrix) of the log-transformed dependent variable and the main independent variables are provided

in Table 2 all pearson correlation coefficients are significant

control Variables

We used variables to control production-specific effects, hospital-specific fixed effects, and time-specific effects in the model for testing hypotheses To control production-specific effects, we added other input factors used by a hospital to produce services to the model These were medical capital Medical capital explains both hospital output and medical labor productivity lags of medical capital were used following the logic that non-IT capital affect productivity in a lagged manner [10, 27] Hospital-specific effects could occur as a result of differences in production processes and organizational incentives [16, 20] These effects were captured by government status, profit status, teaching status, and urban status [57] The government status of hospitals was a binary indicator, coded 1 for government hospitals profit status was also a binary indicator, with for-profit hospitals coded as 1 The teaching status of hospitals also contributed

to hospital-specific differences.5 another aspect that contributed to hospital-specific production process and to the levels of capital was urban status [9].6 In addition, the