| Abstract In the era of severe resident work hour restrictions, residents must work with greater efficiency in order to maximize operative training and clinical education. To accomplish this, we created an automated, computerized system to monitor patient information and assist in clinical duties. We developed a VBA subroutine that allows a microcomputer to act as a hospital mainframe user by simulating keystrokes that would be pressed while looking up patient information. Each screen displayed by the hospital system is copied to a temporary worksheet. The program alters keystrokes based on output just as a human user would, so its operation is completely automated. Relevant data (such as medications and analysis of laboratory, cerebrospinal fluid, and microbiology) of patients on the service are imported into a list that is distributed among the residents. Progress notes are produced using this information. Patients also automatically are added to a long-term database. Over 12 months, the system accessed the hospital computer 873 times, and 16,305 daily progress notes were generated on 3,468 patients. Resident surveys revealed that time spent daily on checking patient information and documentation decreased from two hours for each activity to 15 minutes and 20 minutes, respectively. All residents surveyed reported improvement in work hour compliance, and a majority reported more time for educational activities and OR participation’ Attending physicians also noted improved legibility of documentation and residentsâ improved knowledge and communication of patient information. This system allows a large academic neurosurgery service to run more efficiently, with improved communication and work hour compliance. |
Compliance with recent restrictions on resident work hours translates to the performance of clinical duties in much less time so that a reduction in operative surgical experience is prevented. The requirement that residents sign out early after taking call necessitates multiple transfers every day of patient information from one resident to another. To accomplish these transfers, large amounts of data must be collected several times per day, concisely summarized for many patients, and efficiently communicated among the residents. Legible and thorough documentation must be maintained for all patients on the service even though the process can be tedious and time-consuming. Residents are often faced with the distressing choice of prioritizing clinical duties, work hour compliance, or adequate training.
A survey of on-service junior and senior residents at our program revealed that nearly 25 percent of each resident’s time is spent acquiring, processing, and disseminating patient information (Figure 1). We believe that this is likely to be true of many residency programs. Streamlined information management therefore should prove to be a powerful tool for residents to maximize efficiency. Most hospitals have mainframe computer systems that store much of the information residents need to access. Laboratory data, microbiology results, cerebrospinal fluid analysis, medications, discharge summaries, radiology and pathology reports, operative dictations, medical history, clinic notes, consultation reports, and much more are freely available to any physician with a sign-on code. However, this information is rarely presented in a form that is easy to access and manipulate for our purposes.
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| Figure 1. Click to enlarge |
Materials and Methods
Prior to implementation of this system, maintenance of patient information
required a user to manually log into the hospital mainframe and individually
access patient records, then produce progress notes and sign-out sheets by
hand (Figure 2A). This system automates all these activities using Microsoft
VBA, a simplified programming language bundled with Microsoft Office and accessible
by pressing alt-F11 from any Office application (Figure 2B). We produced a
set of VBA subroutines that allows the desktop computer to act as a hospital
mainframe user, enabling a dynamic exchange of information so that the computer
can look up patient information without the intervention of a human user.
The program uses a list, arranged on a Microsoft Excel spreadsheet, of medical record numbers of patients for whom information is desired. When a user activates the program, it asks for the user name and password, and from there the process is completely automatic. The “Shell” command is used to open the program that is normally used to access the patient data server, then the VBA command “Sendkeys” is used to simulate keystrokes that would be pressed in the process of logging into the server and performing appropriate queries for each patient. Each screen displayed by the server is copied to the Windows clipboard using a screen copy command and is sequentially pasted to a temporary Microsoft Excel worksheet. The “Do…Loop Until” command is used to repeat this process until the last screen of patient data is reached. Since the program is able to read what is pasted, a series of &If…Then” sequences can be used to alter keystrokes based on mainframe output, just like a human user would. Once all data is present, the program extracts the requested information, which will be on a predictable location on each screen. This information is pasted onto another worksheet, the temporary worksheet is cleared, and the process is repeated for the next patient using a “For…Next” loop until the end of the list of patients is reached. If the institution has multiple servers managing patient data, several subroutines can be used to access each server individually to extract information from each one. This paradigm can be used to retrieve any information on a hospital mainframe that would ordinarily be available to an end user, including laboratory values, culture results, current patient location, medications, radiology reports, pathology reports, discharge summaries, operative dictations, and so forth.
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| Figure 2A. Click to enlarge |
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| Figure 2B. Click to enlarge |
Using Microsoft Excel, we developed a single page, self-updating, automated master list that contains information in tabular format about all patients on the service. The list reports every patient’s name, location, medical record number, age, attending physician, dates of admission and surgery, brief assessment of clinical history, current medications, culture results, and recent laboratory values, including cerebrospinal fluid analysis. The list automatically updates all information available from the hospital computer at least once a day (automatically before rounds) or by pressing a button. At typical system speeds, the automated interface is able to process data for approximately 900 patients per hour, which allows complete update of a census of 50 patients in less than five minutes. The list provides a concise, single-page report about the entire service that can be used as a pocket reference and as a basis for transfer of service responsibility, reducing errors of communication at handoff points. Other subroutines allow printing of specialized reports, such as patient summaries that contain only information that is of interest to a specific attending physician.
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| Figure 3. Click to enlarge |
Results
During the first 12 months after implementation, the system accessed the hospital
computer 873 times to ensure that information on the master patient list was
always accurate. Over the same period, 16,305 daily progress notes were automatically
generated on 3,468 patients. A survey of junior and senior residents on the
service revealed that average time spent checking patient information decreased
to 15 minutes from nearly two hours per day, and time spent with documentation
decreased to 20 minutes from over two hours per day (Figure 4). Time spent
on rounds and signing out also decreased, largely because of better organization.
All residents surveyed reported that work hour compliance improved as a direct
result of this system, and a majority felt that operative and educational experience
was enhanced as well (Figure 5). A survey of attending physicians revealed
that all felt communication had improved, and a majority noted an increase
in legibility of documentation and knowledge and communication of patient information
amongthe residents (Figure 6).
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| Figure 4. Click to enlarge |
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| Figure 5. Click to enlarge |
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| Figure 6. Click to enlarge |
Data for thousands of patients has been added to the long-term database, allowing us to search for previous admissions, summarize patient characteristics, and statistically analyze operative caseload, length of stay, patient outcomes, and other information. We have also been able to process very long lists of patients obtained from other databases to screen discharge summaries, operative dictations, clinic notes, and radiology and pathology reports for research purposes. Operative experience for individual residents has been assessed by searching for assistant surgeons in operative dictations. Long-term analysis of patient characteristics has been accomplished by searching for final diagnoses on discharge summaries. All of these functions are managed by the computer with minimal need for manual data entry or manipulation, so there has been significant savings of time and effort.
Discussion
As neurosurgical training practices continue to evolve, residents must work
with ever-increasing efficiency to prevent a tradeoff of education for work
hour compliance. This novel computerized patient management system has been
an effective tool to accomplish that goal at our institution. Accurate patient
data is now readily available and easy to communicate, and every resident on
the service has access to a large amount of timely information without having
to gather it manually. Improved information management has led to better task
organization and has streamlined the process of rounding and signing out. As
a result, compliance with mandated resident work hours has been greatly facilitated.
There has been a significant improvement in the quality of documentation since this system was implemented. Each resident now can write several dozen comprehensive and legible progress notes in a very short period of time, and since all information is centralized and coordinated to the master list, there is minimal risk of error by miscopying or omission. Furthermore, since the note template has been approved by attending physicians and case managers, notes generated by even the most inexperienced residents are more legally sound, facilitate more accurate coding, and are more helpful during emergencies, when the chart particularly is an important source of patient data. Chart review also has become much easier because each patient’s hospital chart now contains reports of daily assessments that are consistently systematic, legible, and thorough.
The ability to integrate mainframe data with local relational databases has proven to be a powerful data gathering tool for other purposes, such as determining the number and types of operations performed and providing a backup for other systems that track operative data. We also have been able to access large numbers of operative reports and discharge summaries going back several years for statistical analysis of patient characteristics and outcomes. This system costs no money to implement and can be integrated with almost any hospital computer interface as long as the information is accessed via keystrokes and displayed on the screen.
Conclusions
We have shown that a series of relatively simple programs written using widely
available software can eliminate the redundancy of data entry, enhance speed
of patient data acquisition, and improve the content and legibility of patient
notes. Properly implemented, this new computerized patient information management
system has the potential to allow a large academic neurosurgical service to
run more efficiently, with improved communication and work hour compliance.
| Jonathan P. Miller, MD, and Steven C. Fulop, MD
University Hospitals of Cleveland-Neurosurgery Cleveland, Ohio Correspondence to: Abbreviations: Received: May 16, 2007 Key Words: resident work hours, electronic medical record, patient data management, information technology |