In our interventions at EMC, we sought to 1) examine how IT-enabled information can support a hospital’s revenue cycle and 2) explore how Polycentricity Theory can inform our understanding of information management in complex organizations. To achieve these objectives, we investigated information exchanges related to the revenue cycle within EMC and with its external partners. Importantly, we considered the challenges in these information exchanges. This data became the basis of designing IT-enabled interventions to improve specific information exchanges and overall information management at EMC. With a set of ten interventions (grouped into four cases) that focused on improving EMC’s revenue cycle, we sought to develop and illustrate our theory (that is, Information Polycentricity Framework, IPF) with empirical observations (Eisenhardt 1989; Orlikowski 1992). Overall, our goal was to develop IPF to offer faithful explanations of the challenges of IT-enabled information management at EMC.
Data collection for the study started in March 2008, when we held the initial workshop with revenue cycle stakeholders at EMC. In April 2008, EMC’s chief financial officer invited us to visit the hospital. During the visit, we conducted interviews with the chief financial officer, the director of the business office, the director of coding and documentation, the billing supervisor, a nurse manager, and the IT manager. These early interactions with EMC resulted in a deeper engagement with the hospital. After initial communication of our diagnosis of EMC’s problem situation (see Table 7.3-1), we began a formal engagement that lasted over the next two years. Both researchers visited EMC about once every month for full day sessions, in which we reviewed progress of various interventions with the steering committee, interviewed other stakeholders, and planned for subsequent interventions. In addition, I visited EMC almost every
Singh | Dissertation | DATA COLLECTION AND ANALYSIS 101 other week and at times stayed overnight in the city19 to continue data collection the next day. Besides collecting data, the purpose of these visits was to design and implement interventions, provide training to revenue cycle staff about specific interventions, and coordinate any technical issues with EMC’s IT team. After each meeting, the research team held a de-briefing session to discuss our observations. In June 2011, we made a final follow-up visit.
In all, we conducted over 125 semi-structured in-person interviews at EMC. We transcribed most interviews and all workshops. Following Yin (2003) and Miles and Huberman (1994), we collected evidence from multiple sources to enhance data quality and facilitate research. We conducted direct observations of how different revenue cycle stakeholders conducted their day- to-day work, what technologies they used, how they consumed and produced information, what challenges they faced, and which opportunities for improvement they saw. Fortunately, with support from the chief financial officer, we could interview any member of the revenue cycle any number of times, and we made full use of this opportunity. For example, if we had any follow-up questions about billing-related activities, we could interview the billing supervisor or a billing clerk as needed. Apart from face-to-face interviews and direct observations, we also interacted through e-mail and phone to clarify issues raised in interviews and to collect additional documents. In particular, I requested and received weekly data updates for key interventions. I also had remote access to the Exception Management System that we implemented at EMC. This allowed me to re-configure the system remotely based on feedback (such as, requests for new categories of registration-related exceptions). We reviewed usage statistics regularly and ascertained need for training to various users.
The research team prepared a protocol to structure the interview process and to collect appropriate information. We tailored the protocol for specific interviewees. For example, the protocol for the IT specialist included information about EMC’s IT infrastructure, an overview of IT applications supporting the revenue cycle, current and planned projects, security risks, and other technical challenges. Typically, each interview lasted between 30 minutes and two hours, and both researchers took separate notes. We recorded all interviews, except those that discussed specific patient cases, or when requested by an interviewee. Whenever we discussed a particularly “sensitive” issue (such as the resistance of nurses to adopt EMR-facilitated clinical
Singh | Dissertation | DATA COLLECTION AND ANALYSIS 102 documentation), we asked multiple interviewees to reflect on the same issue. These multiple perspectives improved our understanding of the involved complexities.
The research team also reviewed secondary data sources such as technical specifications of the EMR system (which allowed us to create many custom reports), consultant reports, internal presentations, minutes of staff meetings, e-mails, and other written materials. A summary of information about these data sources is included in Table 8.1-1.
Table 8.1-1 Primary and Secondary Data Sources at EMC
Primary data sources Secondary data sources
Workshops (6)
Steering committee meetings (20)
Clinical and non-clinical staff meetings (8) Semi-structured interviews (125) with EMC’s
• Chief financial officer
• Business office manager and staff
• Billing supervisor and staff
• Quality manager
• Utilization review manager
• Documentation and coding manager
• IT manager and staff
• Nursing managers
• Registration supervisor and staff
• EMR system consultant
Field observations (50), including • Patient registration
• Clinical documentation
• Coding
• Billing
• Follow up of delinquent accounts
• Interaction with insurance payers
Internal documents (150), including • EMR system reports
• Presentations
• Meeting notes
• E-mails
• Clinical documentation
• Consultant’s audit reports
• Personal communications
• IT resources questionnaire
External documents (5) • Public data (www.cms.gov;
www.jcaho.org)
CMS—Centers for Medicare and Medicaid Services; JCAHO—Joint Commission on Accreditation of Healthcare Organizations
Singh | Dissertation | DATA COLLECTION AND ANALYSIS 103 The research team also collected as many facts as possible from secondary sources and triangulated between the different empirical materials, perspectives, and observers (Denzin and Lincoln 2005; Miles and Huberman 1994; Yin 2003). This triangulation allowed us an in-depth understanding of the phenomenon in question, provided validation, and added rigor, breadth, complexity, richness, and depth (Flick 2002, p229). In summary, the action research engagement at EMC involved multiple workshops, interviews, and presentations. We used these sources to generate and collect data, and to diagnose the problem, plan and take actions, evaluate interventions, and specify learning.