Automated order entry system and method

• US 7,970,621 B2
• Filed: 10/06/2003
• Issued: 06/28/2011
• Est. Priority Date: 10/18/2002
• Status: Active Grant

• Current Assignee: Cerner Innovation, Inc. (Oracle Corporation)
• Original Assignee: Cerner Innovation, Inc. (Oracle Corporation)
• Inventors: McCallie, David P. Jr., Finn, Christopher S., Crooks, Steven S.
• Primary Examiner(s): Gilligan; Luke
• Assistant Examiner(s): MOLINA, ANITA C
• Application Number:
  US10/679,567
• Publication Number:
  US 20040078366A1
• Time in Patent Office: 2,822 Days
• Field of Search: 707/600, 707/759, 707/706, 705/2, 705/3
• US Class Current: 705/2
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/284 Relational databases
• CPC Class Codes: G16H 40/20 for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms

Abstract

A computer-implemented method for facilitating placement of health care order entry is provided. The method includes receiving input indicative of a desired healthcare order. The order has certain terms therein that are normalized. The method also finds possible order matches for the normalized terms, and calculates a rough score for the possible order matches. The method refines the rough score with a rough score adjustment, and then ranks the found possible order matches from the most-likely to match the desired order to the least-likely based upon the refined rough score. These possible order matches can then be displayed to the user for selection.

Claims

1. A computer-implemented method for facilitating placement of health care order entry, comprising:

receiving, utilizing a first computer process, input indicative of a desired healthcare order having terms therein;

normalizing, utilizing a second computer process, the terms of the healthcare order, wherein the normalizing includes separating number strings within the healthcare order that begin a term into separate terms;

finding possible drug matches for the normalized terms, and calculating a rough score for possible order matches;

refining the rough score with a rough score adjustment; and

ranking the found possible order matches from the most-likely to match the desired healthcare order to the least-likely based upon the refined rough score,

wherein the first and second computer processes are executed utilizing one or more computing devices.

2. The computer-implemented method of claim 1, wherein refining includes adding known synonyms to the terms in the possible drug matches and matching full sentence orders to the possible order matches.

3. The computer-implemented method of claim 2, wherein refining further includes normalizing the full sentence orders, adjusting for exact matches and adjusting for unit matches.

4. The computer-implemented method of claim 1, wherein the rough score calculation includes determining a match distance and ranking the match based on the distance.

5. The computer-implemented method of claim 4, wherein the distance is defined as the number of changes needed in the possible drug matches to obtain an exact match to the terms of the received input.

6. The computer-implemented method of claim 1, wherein the normalizing further comprises:

replacing any abbreviations with known terms corresponding to the respective abbreviations; and

eliminating any terms that are numbers.

7. The computer-implemented method of claim 1, further comprising displaying the found possible order matches in the ranked order.

8. The computer-implemented method of claim 1, wherein normalizing further includes setting an anti-flag for any found, pre-determined anti-terms, and wherein the rough score calculation includes removing any terms for which the anti-flag is set.

9. A computer-implemented method for facilitating placement of health care order entry, comprising:

receiving, utilizing a first computer process, input indicative of a desired healthcare order having terms therein;

normalizing, utilizing a second computer process, the terms of the healthcare order, wherein the normalizing includes;

converting a case of the terms of the healthcare order to match that existing in a database;

replacing any abbreviations with known terms corresponding to the respective abbreviations;

determining whether a number exists at an end of the healthcare order; and

based on a determination that the healthcare order does not end with a number, separating number strings within the healthcare order that begin a term into separate terms;

identifying a plurality of possible order matches; and

ranking the plurality of possible order matches from the most-likely to match the desired healthcare order to the least-likely;

wherein the first and second computer processes are executed utilizing one or more computing devices.