Case Study: A Real-time Bed Management and...

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

A Real-time Bed Management and Census Control Dashboard (Rosow) Page 2

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.”


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:


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.


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.


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


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;


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.


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.


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.


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.


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.


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.


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…


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.


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.


mailto:[email protected]

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.


mailto:[email protected]

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