Managing Technologies in Healthcare Operations: Levels of Integration and Extent of Implementation

1. Asoke Dey Ph.D. Candidate Operations and Management Science Department Managing Technologies in Healthcare Operations: Levels of Integration and Extent of Implementation August 12, 2006 OM Division PhD Consortium Annual Meeting of AoM, Atlanta

2. Dissertation Overview • Dissertation Topic: Empirical Studies in healthcare operations on (a) Technology Integration and its impact on hospital performance (b) Impact of organization and Users on technology implementation • Research Questions • How do healthcare organizations select the appropriate level of technology integration? • What are the key drivers of the levels of technology integration? • What are the performance implications of organizations for their level of technology integration? • How organizational proactiveness and physician involvement influences the extent of technology implementation in healthcare operations? • Primary Research Methodology: Cross-sectional survey (longitudinal) • Unit of Observation: Acute care hospital

3. Dissertation • Practical Contribution: Better understanding of the decision making process in technology selection and evaluate organizational performance • Academic Contribution: • Conceptualize different levels of technology integration • Account for self-selection of hospitals into levels of technology integration • Empirically investigate technology implementation - multiple technology, many firms, longitudinal • Dissertation Committee: • Kingshuk K. Sinha (Advisor, OMS) • Roger Schroeder (OMS) • Debasish Mallick (OMS) • Dennis Cook (Statistics) • Stephen Parente (Finance - Healthcare) • Stage: Will defend proposal on November 2006

4. Technology Integration in Healthcare Operations: Self-Selection and Performance Implications

5. Providers must consider multiple functions and hundreds of applications offered by numerous vendors • Technology Investments in healthcare increased three-fold, from $ 6.5 billion in 1990 to $ 21.8 billion in 2002 (Dorenfest 2002) Health Care Motivation The General Problem “As the landscape becomes more complex, so does the technology that enables it. The marketplace is flooded with products, and new technologies are emerging….….. Companies need not only decide whether to implement or upgrade but which products among a dizzying array will best suit their needs.” (Susan Happek and John Oliver, ASCET, May 15, 2002)

6. Motivation The performance impact of technology is mixed • “Never has so much technology and brainpower been applied to improving supply chain performance …. Nonetheless, the performance of many supply chains has never been worse (Fisher, 1997) • 44,000 to 98,000 deaths due to medical errors and the cost of nonfatal medical errors is about $17 to $19 billion each year (Khatri et al. 2006, Institute of Medicine 2000) • “Research is needed to better understand what types of technology applications are most useful for improving care in different settings and what circumstances are necessary to ensure successful implementation” (Report to the Congress: New Approaches in Medicare, June 2004)

7. Motivation • Key to successful implementation is integration of technology applications (Meyer and Ferdows 1985, Venkataraman 1994, Raghupathy and Tan 2002) • An Electronic Medical Record (EMR) environment involves integration of various technologies and used within a care delivery organization • to provide reminder, alerts, linkages to knowledge sources for decision support document (Brailer 2003, Institute of Medicine, 1997) • to provide data for outcome research and improved healthcare management • core functions of EMR are recording and accessing information, order entry, decision support, unique patient identification, sharing of information and interoperability (Waegemann 2002, Bates et al, 2003)

8. Research Questions How do healthcare organizations select the appropriate level of technology integration? What are the key drivers of the levels of technology integration? What are the performance implications of organizations for their level of technology integration? Motivation

9. Conceptual Foundation Level of Integration Clinical Technologies*in each level 1 Radiology, Pharmacy and Laboratory – All Not Installed 2 Radiology, Pharmacy and Laboratory – All Installed 3 CDR, CDSS, MRI and all level two applications 4 Clinical Documentation, PACS and all level three applications 5 CPOE and all level four applications Higher Level of Integration = Increase in Technology Capability Legends: CDR: Clinical Data Repository MRI: Medical Records Imaging CDSS: Clinical Decision Support Systems PACS: Picture Archiving Communications System CPOE: Computerized Physician Order Entry * Source: Garets and Davis 2006, Institute of Medicine 2004

10. Conceptual Foundation Research Hypothesis Ceteris paribus, performance for hospitals that select higher level of technology integration will be greater than that for hospitals that select lower level of technology integration

11. Conceptual Foundation • In health care settings, firms self-select themselves into different levels of integration that is optimal given their attributes Examples • Costs of investments vs. expected benefits – financial and operational • Patient / Employee satisfaction

12. Conceptual Foundation Self Selection* • Managers make choices to generate competitive advantage and, hence, performance • Strategy choice is endogenous and self-selected (Shaver 1998) • Firms choose strategies based on their attributes and industry conditions (Unless we can assume firms regularly make errors in selecting their strategy) • Example of self selection: make versus buy • In operations literature – focused factory – where operations strategy is aligned with business strategy (Skinner 1974) * Masten 1993, Maddala 1983, Heckman 1979

13. Research Design Self-Selection Corrected Econometric Procedure: Two Steps Step 1. Selection Model • The choice of a firm to opt for the level of technology integration is modeled • Dependent variables: Five levels of technology integration • Independent variables: scale, scope, structure, network learning, competition, turbulence We model the selection process as a discrete choice model that is driven by healthcare provider specific variables indicating of their inclinations to adopt a level of technology integration

14. Research Design Self-Selection Corrected Econometric Procedure: Two Steps Step 2. Performance Model • The normative effects of levels of technology integration on performance are assessed • Dependent variables: Full time equivalent’s per adjusted hospital bed, Average daily census acute days, Operating Expenses per discharge, Operating Revenue per discharge, Medicare revenue per day • Independent variables: scope, structure, network learning, competition Performance assessment: Traditional regression analysis is inappropriate as it assumes firms are randomly assigned to “treatments” (levels of technology integration)  biased estimates

15. Research Design

16. Research Design

17. Empirical Analysis • Sample and Data Collection • Financial and Operational performance and hospital characteristics data is used from Cost Reports from the Center for Medicare and Medicaid Services (CMS) • Data for the levels of integration used for this research is collected in 2003 as part of the Sixth Dorenfest Complete IHDS+ Survey under the aegis of The Healthcare Information and Management Information Society (HIMSS) • Sample of 1444 integrated healthcare delivery systems (IHDS) and around 28575 facilities • Five facility settings represented in the study sample: • Acute Care [4005] – 12 specialties • Sub-Acute Care [3380] – 10 specialties • Ambulatory Care [18251] – 48 specialties • Owned Payor Components [213] – 8 types • Affiliated Physician Organizations [773] – 5 types

18. Empirical Analysis (n = 2786; Contains all acute care facilities with 2003 data on all variables ) Acute Care Facility Breakup Level of Clinical Technologies Count Integration • Not Radiology, Pharmacy, Laboratory 317 • Radiology, Pharmacy, Laboratory 314 • Level 2 and CDR, CDSS and MRI 304 • Level 3 and PACS and Clinical Doc. 1090 • Level 4 and CPOE 761 CDR: Clinical data Repository; CDSS: Clinical Decision Support Systems; MRI: Medical records Imaging; PACS: Picture Archiving Communications System; CPOE: Computerized Physician Order Entry

19. Potential Contributions • Develop a conceptual understanding of different levels of technology integration • Account for self-selection i.e. the process of decision making in selection of the appropriate level of technology integration • Evaluate relationship between the levels of technology integration and hospital performance • From a technology vendor perspective, a guidance about different levels in a health care facility and variables that influence technology procurement decision