The automated anesthetic record will not automatically solve problems in record keeping

1990 ◽  
Vol 6 (4) ◽  
pp. 334-337 ◽  
Author(s):  
Reynolds J. Saunders
Keyword(s):  
Anesthetic Record ◽  
Record Keeping

Automated Anesthetic Record Keeping

1985 ◽  
pp. 147-161 ◽  
Author(s):  
N. Ty Smith
Keyword(s):  
Anesthetic Record ◽  
Record Keeping

Automated Documentation Error Detection and Notification Improves Anesthesia Billing Performance

2007 ◽  
Vol 106 (1) ◽  
pp. 157-163 ◽  
Author(s):  
Stephen F. Spring ◽  
Warren S. Sandberg ◽  
Shaji Anupama ◽  
John L. Walsh ◽  
William D. Driscoll ◽  
...  
Keyword(s):  
Median Time ◽  
Error Detection ◽  
Computer Software ◽  
Information Management System ◽  
Timely Manner ◽  
Anesthetic Record ◽  
Record Keeping ◽  
Before And After ◽  
Order Of Magnitude ◽  
E Mail

Background Documentation of key times and events is required to obtain reimbursement for anesthesia services. The authors installed an information management system to improve record keeping and billing performance but found that a significant number of their records still could not be billed in a timely manner, and some records were never billed at all because they contained documentation errors. Methods Computer software was developed that automatically examines electronic anesthetic records and alerts clinicians to documentation errors by alphanumeric page and e-mail. The software's efficacy was determined retrospectively by comparing billing performance before and after its implementation. Staff satisfaction with the software was assessed by survey. Results After implementation of this software, the percentage of anesthetic records that could never be billed declined from 1.31% to 0.04%, and the median time to correct documentation errors decreased from 33 days to 3 days. The average time to release an anesthetic record to the billing service decreased from 3.0+/-0.1 days to 1.1+/-0.2 days. More than 90% of staff found the system to be helpful and easier to use than the previous manual process for error detection and notification. Conclusion This system allowed the authors to reduce the median time to correct documentation errors and the number of anesthetic records that were never billed by at least an order of magnitude. The authors estimate that these improvements increased their department's revenue by approximately $400,000 per year.

Financial record-keeping simulation in the dental auxiliary utilization clinic

1975 ◽  
Vol 39 (9) ◽  
pp. 613-616 ◽  
Author(s):  
EG Barron ◽  
RR Waller
Keyword(s):  
Record Keeping

Problems in record-keeping. A new approach toward the preservation of continuity

1977 ◽  
Vol 137 (4) ◽  
pp. 436-436
Author(s):  
M. L. Levin
Keyword(s):  
New Approach ◽  
Record Keeping

Record Keeping Guidelines.

2007 ◽  
Vol 62 (9) ◽  
pp. 993-1004 ◽  
Author(s):  
Keyword(s):  
Record Keeping

Ethics Rounds: Record-keeping under the new Ethics Code

2005 ◽  
Author(s):  
Stephen Behnke
Keyword(s):  
Record Keeping ◽  
Ethics Rounds ◽  
Ethics Code

Record keeping for practitioners

2012 ◽  
Author(s):  
Cynthia Sturm
Keyword(s):  
Record Keeping

Record Keeping Guidelines

2007 ◽  
Keyword(s):  
Record Keeping

Record Keeping Guidelines

2007 ◽  
Keyword(s):  
Record Keeping

A Generic Model of Clinical Practice

2003 ◽  
Vol 42 (03) ◽  
pp. 203-211 ◽  
Author(s):  
J. L. G. Dietz ◽  
A. Hasman ◽  
P. F. de Vries Robbé ◽  
H. J. Tange
Keyword(s):  
Clinical Practice ◽  
Theoretical Model ◽  
Action Theory ◽  
Human Subjects ◽  
Shared Care ◽  
Patient Record ◽  
Generic Model ◽  
Problem Solver ◽  
Record Keeping ◽  
Process View

Summary Objectives: Many shared-care projects feel the need for electronic patient-record (EPR) systems. In absence of practical experiences from paper record keeping, a theoretical model is the only reference for the design of these systems. In this article, we review existing models of individual clinical practice and integrate their useful elements. We then present a generic model of clinical practice that is applicable to both individual and collaborative clinical practice. Methods: We followed the principles of the conversation-for-action theory and the DEMO method. According to these principles, information can only be generated by a conversation between two actors. An actor is a role that can be played by one or more human subjects, so the model does not distinguish between inter-individual and intra-individual conversations. Results: Clinical practice has been divided into four actors: service provider, problem solver, coordinator, and worker. Each actor represents a level of clinical responsibility. Any information in the patient record is the result of a conversation between two of these actors. Connecting different conversations to one another can create a process view with meta-information about the rationale of clinical practice. Such process view can be implemented as an extension to the EPR. Conclusions: The model has the potential to cover all professional activities, but needs to be further validated. The model can serve as a theoretical basis for the design of EPR-systems for shared care, but a successful EPR-system needs more than just a theoretical model.

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