case study: a real-time bed management and...
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Case Study: A Real-time Bed Management and Census Control Dashboard
Eric Rosow, M.S. Director of Biomedical Engineering Hartford Hospital Co-founder, Premise Development Corporation Hartford, CT Joseph Adam, M.S. Chief Operating Officer and Co-founder Premise Development Corporation Hartford, CT Kathleen Coulombe, MS, RN Admissions Coordinator Hartford Hospital Hartford, CT
INTRODUCTION
In April 2001, Hartford Hospital, an 819 bed tertiary care, Level I Trauma center located in Hartford, Connecticut
completed a multiyear re-engineering initiative. A major objective of this re-engineering program was the re-
establishment of a centralized Bed Management system to streamline patient flow throughout the institution.
Specifically, this initiative, which was sponsored by Hartford Hospital’s President and CEO, was designed to meet
the needs of all inpatient services within Hartford Hospital and include technology-based solutions to increase the
flexibility and efficiency of accepting patients into the hospital and moving patients between care areas, including
the ED, ICUs, OR and PACU.
Following a review of available third-party products and systems on the market, it was decided to retain Premise
Development Corporation, a local information technology firm, to work with Hartford Hospital to collaboratively
design and build an enterprise bed management system. Hartford Hospital elected to pursue this strategy because
the existing products on the market were either “department centric” (i.e., Operating Room or Emergency
Department) or addressed only patient transport or housekeeping needs. As part of the re-engineered bed
management process, Hartford Hospital required an enterprise wide and scalable solution that focused on the clinical
aspects of the patient (i.e., requires patient monitor, near the nursing station, requires negative pressure, requires a
sitter/security risk, etc.) rather than the physical aspects of the bed (i.e., clean or dirty).
After more than one year of extensive research and analysis, a new enterprise-wide bed management department
was introduced at Hartford Hospital. Underlying the new system was the development of a software product called
the Bed Management Dashboard (the “BMD”). This case study will highlight how a collaborative team of
physicians, nurses, administrators, software engineers and support staff designed, developed, tested and deployed an
enterprise wide software application, the BMD, to support the goals of centralized bed management and the ability
to make timely, data-driven decisions.
OBJECTIVES AND GOALS
The Bed Management Problem: Most healthcare institutions today manage patient flow via paper, whiteboards
and phone calls. As a result, hospitals often lack precise and timely information to match bed availability with
patient clinical needs. This causes inefficient use of beds, resources and provider time, leading ultimately to:
reduced throughput, ED overcrowding, lost admissions, OR delays, unhappy physicians, staff, and patients, and
decreased revenue and higher expenses.
Industry Trends: Concerns over patient access to hospital care has become one of the largest, most urgent
healthcare issues on the public’s agenda. Many hospitals are struggling to cope with surprising increases in the
number of patients. Nationwide, hospitals report unprecedented inpatient and outpatient volumes, while average
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occupancy levels approaching 100 percent are not uncommon. These problems are compounded by two nationwide
trends in hospitals: 1) an increase in the number of patients, and 2) a decrease in the number of beds.
For example, some hospitals are being forced to turn away ambulances and cancel or delay elective surgeries due to
a shortage of hospital beds. At other hospitals, emergency room patients wait hours or even days for rooms.
Administration often has minimal information to be able to proactively match the demand for patients with the
appropriate level of nurse staffing. In addition, aging baby boomers are more likely to experience serious illness or
injury, and medical advances are helping doctors treat conditions that patients might have simply accepted in the
past. These challenges are further exacerbated by the overall staff shortage of hospital workers—especially amongst
nurses. With no sign of apparent slowdown in these trends, these problems in hospital care appear set to escalate for
the foreseeable future.
Bed Management at Hartford Hospital - A Historical Profile: Until the early 1990s, Hartford Hospital relied
upon a centralized, non-clinical Admitting Department that performed all booking and scheduling and patient
placements from all access points of the hospital. Clinicians’ growing dissatisfaction with the more generalized
populations of patients on units and the Admitting Department’s inability to clinically assess patient needs, level of
care and acuity drove the development of decentralized, service-specific admitting and patient placement processes.
However, this decentralized approach also soon failed for a number of reasons. Specifically, patient care unit
closures of the mid and later 1990s resulted in higher unit occupancies and their loss of abilities to hold beds.
Admission delays from Admitting, ED and PACU became hours long while they searched for available beds.
Physician and patient satisfaction with the patient placement systems dropped. In addition, increasing patient acuity
and more complicated and acute surgical and life sustaining procedures resulted in greater demands for ICU beds.
Reengineering Admissions and Patient Placement: A Reengineering Initiative undertaken in 1999 assessed the
aforementioned problems and deemed them to be critical barriers to general system improvements within the entire
hospital. The reengineering teams also recognized the benefits of clinical knowledge incorporated into patient
placement decisions. The hospital’s President and CEO sponsored the re-establishment of a centralized Bed
Management system with the following charge:
“Establish a centralized admissions coordination process that will meet the needs of all inpatient
services within Hartford Hospital and include solutions to increase the flexibility and efficiency of
accepting patients into the hospital and moving patients between care areas, including the ICUs,
PACU and ED.”
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Guiding Principles of the project included:
• Facilitate entry of patients into the system;
• Maximize utilization of beds while preserving population competencies of each patient care unit;
• Reduce staff nurse time devoted to phone calls and communication regarding admissions/placements;
• Avoid the surgical delays and/or cancellations and diversions;
• Clearly define role accountability, authority and decision making processes; and
• Leverage established clinical protocols, algorithms, measurement systems and information technology.
CHALLENGES
Technology Development / The Bed Management Department: The need for technological support under a
centralized bed management approach was immediately evident as all interactions between hospital personnel were
being performed via telephone and data collection and record keeping was manually performed with various hard-
copy forms. Such a system proved highly inefficient and labor intensive. Without some kind of technological
support, the Bed Management Department was going to have to double in number of personnel to achieve its daily
mission.
The challenge for Hartford Hospital and its information technology partner was to develop a software application
that provided real-time status of beds by unit, predictability of bed status, and match bed attributes with the clinical
needs of the patient. At the same time, the dashboard allowed centralized booking of patients and automated
communications to various departments and users. Also important was the preservation of the clinical decision-
making and triage while making communication of those decisions highly efficient, even seamless for Bed
Managers and for receiving patient care unit staff.
IMPLEMENTATION STRATEGY The design and development of a centralized bed management process incorporated proven project management
techniques and Six Sigma design methodologies. Six Sigma is a measure of quality that strives for near perfection.
The Six Sigma process uses data and rigorous statistical analysis to identify “defects” in a process or product, reduce
variability, and achieve as close to zero defects as possible. Six Sigma is all about measurements—that is, if you
can measure how many “defects” you have in a process, you can systematically figure out how to eliminate them
and get as close to “zero defects” as possible. An integral part of a Six Sigma Quality Initiative is a DMADV
methodology. DMADV is a data-driven quality strategy for designing products and processes. DMADV consists of
five interconnected phases: Define, Measure, Analyze, Design, and Verify. Each of these phases is illustrated in the
following figure:
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Figure 1: The DMADV Process
The timeline for the design, development and deployment of the Bed Management Dashboard using the DMADV methodology is illustrated below in Figure 2.
Figure 2: Timeline for planning, development and deployment of the Bed Management Dashboard.
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Voice of the Customer (VOC): The bed management Project Team met with numerous stakeholders throughout
the organization, to obtain “voice of the customer” or VOC data. As a result of these interviews, the following
insights were made:
• Protocols for primary unit location work well for planned admissions when the unit is not full;
• Staffing and quality of care considerations must be accommodated when particular services/units are
stressed;
• Bed management function must be closely linked to the registration and admitting processes;
• New systems must specifically address all patient types including the following: planned, emergent,
direct/urgent, outside transfers and internal transfers, including ambulatory surgery;
• Information systems must be available throughout the institution to provide relevant bed management data
while at the same time have the appropriate levels of security to protect patient confidentiality; and
• Information must be available in real-time and must be aggregated in the form of an easy-to-use interface
or “dashboard” that: a) improves communication processes and b) facilitates decision support.
CURRENT STATUS Bed Management Today at Hartford Hospital - A Re-Engineered System: A key assumption with respect to the
development of the Bed Management role in a centralized environment was that a clinical background was essential
to the Bed Manager in understanding the urgency of a situation and the acuity of the patient. The Bed Manager
probes for additional care needs that can affect patient placement. These assumptions have been demonstrated to be
true over the course of the two years since the Department’s inception. Sometimes the Bed Manager can match
what on the surface appears to be a mismatched population into a placement solution. A non-clinician cannot do
this. As nurses, the Bed Managers understand population-specific nursing competencies, care protocols and
placement algorithms. They are able to interact with staff on patient care units to assess acuity and to match patient
placements to units whose resources can best manage them.
The bed management process at Hartford Hospital is now centralized under the Bed Management Department and is
facilitated by the use of the BMD software. The BMD currently has over 900 users and has been deployed to over
3,500 workstations throughout the continuum of care at Hartford Hospital. The BMD is a real-time process
improvement and decision support software tool used by the hospital’s administrators, clinicians and managers on a
7x24 hour basis and has proven its ability to efficiently and cost-effectively manage patient flow and allocate
resources.
The Bed Management Dashboard: The BMD, as shown in Figure 3, is an enterprise-wide software solution that
directly and indirectly interacts with all departments throughout the continuum of care.
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Figure 3: The BMD is an enterprise-wide system that interacts with all departments throughout the continuum of care (e.g., admitting, ED, OR, ICU, administration, etc.)
The BMD is a real-time process improvement and decision support product used by hospital administrators,
clinicians and managers on a 7x24 hour basis.
Process Improvement: The BMD enables more efficient patient placement by: reducing/eliminating phone
calls and paper processes, and automatically matching patient requirements to available resources.
Specifically, the system assists with the clinical and business decision processes that occur when a patient needs
to be assigned to a specific bed location. Via continual, “real-time” updates across the hospital’s network, BMD
users are assured that they have accurate data available to them when and where they need it.
Current ADT systems are admissions and billing systems geared towards financials. The BMD complements
these systems with clinical requirements and was designed to improve operational efficiencies on a unit and/or
hospital wide. Intuitive modules are used to display and provide alerts on quantitative results in real-time
providing an easy way for personnel to know which beds are available and ready for immediate use, which beds
have been requested by other units, or which beds have patients with special requirements, etc.
Decision Support: The BMD is an easy-to-use business intelligence application. It has been designed to allow
administrators, clinicians, and managers to easily access, analyze and display real-time patient and bed
availability information from ancillary information systems, databases, and spreadsheets. The dashboard
provides on-demand historical, real-time and predictive reports, alerts and recommendations. Decision-makers
can easily move from big-picture analyses to transaction-level details while at the same time, safely share this
information throughout the enterprise to derive knowledge and make timely, data-driven decisions.
OUTCOMES
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Outcomes and benefits of a centralized Bed Management process that maintained clinical input and incorporated
technological support:
Process Improvement: Streamlines the process of admitting, transferring, and discharging patients by:
Optimizing patient placement processes (for direct admissions, Emergency Room “upgrades”, and all
scheduled pre-admissions, transfers and discharges);
Increasing staff efficiency - Reduce administrative expenses by eliminating paperwork and phone volume;
Improving utilization of beds - Reduce inappropriate usage of inpatient beds without payer authorization
(e.g. 23+ hour observation outpatients) by automatic alerts;
Optimizing utilization of material resources (e.g., monitored beds and negative pressure rooms);
Managing patient flow in the event of Admissions/Discharge/Transfer (ADT) system or network failure
(Disaster recovery);
Enabling Real-time & Predictive Capacity Management; and
Providing clinical attributes to supplement ADT data (e.g., telemetry, near nursing station, negative
pressure room required, etc.).
This results in:
Reduced Emergency Room overcrowding;
Reduced Operating Room delays;
Increased MD, Staff and Patient Satisfaction;
Improved patient flow;
Time savings;
Better treatment of patients and improved customer satisfaction;
Reduced diversions and lost admissions;
Increased revenues & decreased expenses; and
Reduced staff.
Decision Support: The bed management system helps administrators, clinicians, and managers to easily access,
analyze and display real-time patient and bed availability information. It provides:
On-demand historical, real-time and predictive reports;
Alerts, warnings and recommendations;
Ability to share information throughout the enterprise;
Provides point-in-time predicted bed availability; and
Ability for decision-makers to easily move from “big-picture” analyses to transaction details.
This results in:
Timely data-driven decisions;
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Improved decisions regarding staffing levels;
Reduce reliance on third party staffing companies to supplement in-house staff;
Improved crisis management during rapidly fluctuating census levels; and
Improved ability to negotiate contracts with payers.
An Air Traffic Control Tower for Beds: In many ways, the BMD is similar to an Air Traffic Control Tower. Like
a real Air Traffic Control Tower, this application is real-time and mission critical. It must handle both scheduled
and emergency events. The system assists with the clinical and business decision processes that occur when a
patient needs to be assigned to a specific bed location. Collectively, this system provides organizations with an array
of enabling technologies to:
Schedule/Reserve/Request patient bed assignments;
Assign/Transfer patients from the emergency department and/or other clinical areas such as Intensive Care
Units, Medical/Surgical Units, Operating Rooms, Post-Anesthesia Care Unit, etc;
Reduce/Eliminate dependency on phone calls to communicate patient and bed requirements;
Reduce/Eliminate paper processes to manage varying census levels;
Apply Statistical Process Control (SPC) and “Six Sigma” methodologies to manage occupancy and patient
diversion; and
Provide administrators, managers and caregivers with accurate and on-demand reports and automatic alerts
via pagers, e-mail, phone and intelligent software agents.
How it works: The BMD was designed to interface with any healthcare information system providing an Health
Level Seven (HL7) data feed, including: ADT systems; clinical information systems (CIS); enterprise scheduling
systems; patient monitoring networks; paging systems; and hospital nurse call systems.
The BMD is currently accessible via a client application and is in the process of porting to a browser environment.
The supporting architecture of the BMD system is a standard N-tier server based system, which depending on the
customer’s needs, consists of one or more of the following: an application server, a database server and an ADT
interface server. In addition, the BMD is comprised of multiple “modules” which can be selected based on the
specific needs of the customer.
The system typically receives up to 12,000 transaction messages a day from the ADT system. These messages are
then parsed into appropriate data elements by an HL7 parser and are stored in a database management system
(DBMS). In this way, the dashboard’s DBMS is always kept “in synch” with the ADT system. Figure 4 illustrates
the flow of information from the ADT system to the user’s desktop and the various modules in the BMD.
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Figure 4: Bed Management Dashboard System Diagram.
Reporting and Data Mining: The BMD’s integrated data mining and report module consists of a number of
standard reports that take advantage of the data warehouse nature of the BMD. These reports include, but are not
limited to: historical census report, real-time census report, bed manager report, physician discharge report, and
discharge compliance report. In addition, access to the data by industry-standard report writers, such as Crystal
Reports and Microsoft Access or SQL Server give technical users the ability to create complicated or special reports
as desired. For example, the BMD offers extensive ad hoc reporting capabilities ranging from length of stay (LOS)
and “Care Day” metrics to asset management analyses (on beds and patient monitor utilization), to biosurveillance
reports which have been requested by State and Federal organizations such as Department of Public Health and the
Centers for Disease Control.
Configuration Tools: The utility and configuration module gives system operators the ability to administer BMD
users (e.g., add new users, modify new or existing user security settings, etc.); administer service, unit, rooms and
beds (e.g., add or modify clinical services, units, rooms and beds and their inter-relationships); define automated
alert thresholds; and configure unit floor plan diagrams.
Emergency Backup and Disaster Recovery: The embedded backup utility module consists of a local version of
the bed management database that is constantly updated. Access to this database gives users a self-contained and
mobile version of the system that can be used in the event of catastrophic failure of the system hardware or network
hardware or in the event of a crisis that removes the users from direct access to the hospital network.
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User-defined Processes, Data Visualization and Presentation: One of the most important features of the BMD is
that it reformats information from the ADT system and presents it to the clinical user in a more “user-friendly” and
process-oriented manner. Dynamic and interactive graphical presentations of data are used extensively. All patients
and/or beds can be displayed and selected from a dynamically sortable “smart tables.”
Hospital beds are classified as having pre-defined “attributes”, such as being “monitored” or being assigned to the
“Surgery” service. The needs of patients are similarly described with attributes, such as “monitor required” or
“scheduled for surgery”. The BMD helps users find those available beds in the hospital that meet the specific needs
of a patient by guiding the clinical staff through a set of process screens that perform the match. Once a patient is
selected, this “Bed Finder” screen is used to locate a specific bed or unit for the patient. The user first enters various
criteria about the type of bed that is needed (i.e., patient gender, monitor required, negative pressure room required,
etc.). The system then displays all of the available beds that meet the specified criteria. Finally, the user selects a
particular bed or unit for the previously specified patient.
Decisions for patient placement can be centralized or de-centralized. The dashboard allows proper communication
between the appropriate parties. Status of decisions is automatically tracked, and a monitoring process can detect
and notify key stakeholders of any process delays. Admitting or Emergency Departments can automatically be
notified of decisions, if appropriate. Reporting of information is provided by on-line screen views of data tailored to
the needs of a particular class of system user. Unit personnel can view both detailed information as well as
summary roll-ups of their patients. Figure 5 illustrates how patient information can be viewed in a dynamic and
interactive floor plan mode.
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Figure 5 – Unit Details (Floor Plan View): This screen provides a graphical view of a surgical care unit. Each bed is presented as a square using a simplified floor plan view. Colors are used to indicate the selected attribute of the patient or bed. For example, the above screen indicates male and female beds in blue and pink respectively. Unoccupied beds are indicated in gray (and closed beds would be indicated in black). Numeric indicators show how long a patient has been in outpatient status or how many hours until the patient is expected until transfer or discharge. Flashing beds are used to indicate that a user-defined threshold (i.e., outpatient status >23 hours, telemetry use >48 hours, etc.) has been exceeded. Additional details such as the bed characteristics (i.e., telemetry bed, negative pressure room, etc.) and patient information can also be viewed by “scrolling over” any bed or by selecting a bed and clicking on the bed or patient information buttons. An example of a summary report is shown in Figure 6.
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Figure 6– Hospital Summary: This screen is primarily used by administrators who need to see a global view of the hospital status. Table and pareto charts profile the various units and the current status summaries of each unit. These patients can also be rolled up into Services, or grouped by Physician. In addition, patients can be aggregated in many other ways such as: time of admission, length of stay, and admitting diagnosis.
A key feature of this system is its capability to use “Intelligent Agents.” These online agents, as shown in Figure 7,
can constantly monitor and analyze patient and census information, and they have the ability to detect key system
situations, such as high census in a unit (i.e., no available beds), excessive ED placement time for a particular
patient, delays in responses to placement requests or patient who exceed a user-defined threshold, for example <23
hours in outpatient status or <48 hours on a medical telemetry monitor.
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Figure 7 –Intelligent Agents: The BMD can also employ on-line “intelligent agents“ to provide assistance and alert the user of important alarm conditions that may have otherwise gone unnoticed. Messages can be in the form of an onscreen agent (such as Microsoft’s Agent Technology, in this case, Merlin the Wizard) or also via e-mail, pager, fax and/or telephone.
The BMD at Hartford Hospital on 9/11/01: The dashboard played a critical role at Hartford Hospital on that
terrible day of 9/11/01. When the news came in from New York (just 100 miles away), Hartford Hospital told to
expect hundreds of injured patients. At that time, the hospital only had 7 opens beds—only 2 of which were ICU
beds. The BMD played an important role with respect to providing real-time occupancy information, predictive
capacity management and biosurveillance reporting.
Specifically, the dashboard helped in the following ways:
1. It improved efficiency by eliminating the need for whiteboards and many, many phone calls;
2. It allowed for predictive occupancy reports to help free up 150 beds in a timely and orderly fashion; and
3. It provided an efficient way to collect and report biosurveillance data that was required by the State
Department of Public Health.
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The key factors in this success story were that the dashboard was directly linked to the hospital census database so
that accurate data was constantly available to the Command Center. The dashboard displays were easily, rapidly,
and repeatedly revised to facilitate iterative decision-making.
Demonstrated Return on Investment (ROI): Since its installation in April 2001 at Hartford Hospital, the system
has more than paid for itself through achievement of the following:
$200,000 annual expense avoidance by reducing the number of Bed Manager FTE’s needed
50% decrease in the number of phone calls per bed assignment/patient placement
75-90% decrease in the overall time needed for the patient placement process
50% decrease in the number of paper forms used
25% increase in throughput by alerting bed managers to discharges sooner of those that are reported to bed
managers
40 minute decrease in the length of the end-of-shift admission coordinator reports
The hospital expects to save “thousands of dollars per day” by implementing the BMD Outpatient alert
system. (The specific dollars saved are still to be determined.)
Supports corporate compliance initiatives and governmental requirements (i.e., appropriate level-of-
care assignment, placement, billing and documentation)
*Note: Statistics are based on actual observations from Hartford Hospital, since its installation in April 2001.
FACTORS FOR SUCCESS
Feedback throughout Hartford Hospital regarding the Bed Management Department and the Bed Management
Dashboard has been very favorable. The following are some of the key factors to Hartford Hospital’s success:
Executive sponsorship by the President and CEO factored significantly into buy-in by hospital
administration, physicians and staff.
Proven project management methodologies (i.e., Six Sigma)
Establishing systems for direct feedback for concerns and decision-making regarding patient placements.
Centralized, prioritized and consistent patient placement based on clinical needs
Standardization of bed placement and communication processes throughout the organization.
Cooperation and communication among all stakeholders (especially IT resources for testing, training, deploying and supporting the application)
Constant Solicitation of Customer Feedback (voice of the customer), and most importantly,
Commitment to Success…
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FUTURE DIRECTION
The future “road map” for the Bed Management Dashboard includes additional interfaces including: clinical
information systems, patient monitoring networks, staff scheduling/time and attendance, nurse call, patient and asset
location systems and housekeeping systems. In addition, other hospitals within a healthcare system can also be
interfaced into the dashboard, thereby providing end-users with a multi-dimensional “Executive Dashboard.”
Bed Management and/or Executive Dashboards like the ones described in this paper can play an important role in
emergency preparedness and homeland security. In his budget for 2003, President George Bush proposed $518
million for the nation’s hospitals to better prepare for a bioterrorist attack. A major concern is what experts call
“surge capacity”, the ability of hospitals to accommodate a sudden increase of patients. Tommy G. Thompson, the
Secretary of the Department for Health and Human Services has stated that he wants each state to develop regional
plans that would enable hospitals to handle an extra 500 patients on any given day this year, and 1,500 patients on
any given day next year.
Using core components of the BMD technology, it is possible to collect and organize data needed to detect
outbreaks of disease and to coordinate resources when responding to mass casualty events. Given that the BMD can
interface with any hospital ADT system, hospitals throughout a region can be networked to provide state and federal
agencies with real-time bed availability status, as well as epidemiological surveillance information.
CONCLUSION
This case study discussed how Hartford Hospital conceived and developed a “user-defined” solution to meet specific
requirements related to patient placement and bed management. Through a collaborative process involving
physicians, nurses, administrators, hospital staff and software engineers, a “dashboard” was developed to support
process improvements and data-driven decisions. This Bed Management Dashboard was designed to complement
the existing ADT system and support the efficient placement of patients via enhanced communication and by
leveraging clinical protocols. The BMD supports general operations, helps Hartford Hospital manage fluctuating
patient census and bed availability, and empowers clinicians, administrators and researchers with tools to acquire,
analyze and display clinical and operational information from disparate sources. Decision makers can easily move
from big-picture analyses to transaction-level details while at the same time, safely share this information
throughout the enterprise to derive knowledge and make timely, data-driven decisions. Collectively, the dashboard
has been shown to directly benefit healthcare providers, payers, and most importantly, patients.
ACKNOWLEDGEMENTS Special thanks are extended to Domonique Mettler, Management Engineer at Baylor Health Care System for her
time and effort to provide valuable feedback, recommendations and edits for this paper and presentation.
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REFERENCES
1. AHA Statistics 2001, American Hospital Association ; The Clinical Advisory Board, Capacity Command Center-Best
Practices for Managing a Full House, 2001. 2. Carey, Raymond G., Lloyd, Robert C. Measuring Quality Improvement in Healthcare: A Guide to Statistical
Process Control Applications, ISBN: 0527762938, 1995
3. Clinical Advisory Board, Capacity Command Center-Best Practices for Managing a Full House, 2001.
4. Gieras I, Rosow E., Adam J, Roth C. “Decision Support Applications using Statistical Process Control (SPC)
and Virtual Instrumentation” presented at the Association for the Advancement of Medical Instrumentation
(AAMI), Boston, MA, June 7, 1999.
5. Montgomery, Douglas C., Introduction to Statistical Quality Control, John Wiley and Sons, 2nd Edition,
1992.
6. Rosow, E., Adam, J. and Satlow, M., “Real-time Executive Dashboards and Virtual Instrumentation:
Solutions for Healthcare Systems”, presented at the 2002 Annual Health Information Systems Society
(HIMSS) Conference and Exhibition, Georgia World Congress Center, Atlanta, GA, January 28, 2002.
7. Rosow, E., Adam, J. “Virtual Instrumentation Tools for Real-Time Performance Indicators,” Biomedical
Instrumentation and Technology: Association for the Advancement of Medical Instrumentation,” Volume 34,
Number 2 (March/April 2000), pp. 99 –104.
8. Rosow, E. and Olansen, J., Virtual Bio-Instrumentation: Biomedical, Clinical, and Healthcare Applications
in LabVIEW, Prentice-Hall, 2001.
9. Tufte, E. R., Visual Explanations, Graphics Press, 1997.
10. Tufte, E. R., Envisioning Information, Graphics Press, 1990.
11. Tufte, E. R., The Visual Display of Quantitative Information, Graphics Press, 1983.
12. Wheeler, Donald J. and Chambers, Davis S., Understanding Statistical Process Control, SPC Press, 2nd
Edition, 1992.
AUTHOR BIOGRAPHIES
Eric Rosow, M.S. — Eric Rosow ([email protected]) is Director of Biomedical Engineering at Hartford
Hospital where he introduced virtual instrumentation into the hospital environment. Mr. Rosow is also a co-founder
of Premise Development Corporation, a software company for the biomedical and healthcare industries. Most
recently, Eric co-authored a book called Virtual Bio-Instrumentation: Biomedical, Clinical, and Healthcare
Applications in LabVIEW.
Joseph Adam, M.S. — Joseph Adam ([email protected]) is Chief Operating Officer and co-founder of
Premise Development Corporation, a software company which creates award-winning, software-based tools for the
biomedical and healthcare industries, and has co-developed numerous virtual instrument solutions for leading
healthcare institutions and companies throughout the world.
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Kathleen Coulombe, MS, RN — Kathleen Coulombe ([email protected]) was Project Coordinator for the
Bed Management Implementation Project and is now the Admissions Coordinator at Hartford Hospital. As
Admissions Coordinator, she has played a key role in the design and development of the BMD. Prior to her role as
Admissions Coordinator, Kathleen has held positions as Director of General Surgery at Hartford Hospital and
Manager in Critical Care at Johnson Memorial Hospital, Stafford Springs, CT.
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