초록 ▼

Systems and methods are provided for look-alike sound-alike medication error messaging. Prescription data relating to a prescription is parsed to identify a submitted drug product and a submitted daily dosage. An absolute dose screening process may be executed to determine whether the submitted dail

Systems and methods are provided for look-alike sound-alike medication error messaging. Prescription data relating to a prescription is parsed to identify a submitted drug product and a submitted daily dosage. An absolute dose screening process may be executed to determine whether the submitted daily dosage meets absolute dosing criteria for the submitted drug product. A typical dose screening process may be executed to determine whether the submitted daily dosage meets statistically derived typical dosing criteria for the submitted drug product and any look-alike sound-alike alternative drug products. If it is determined that the prescription should be rejected based on typical dosing criteria or absolute dosing criteria, a reject message may be built for presentation to the pharmacist.

대표청구항 ▼

We claim: 1. A method for look-alike sound-alike medication error messaging, comprising: receiving, at a host server, a prescription transaction from a pharmacy POS device, wherein the prescription transaction received at the host server specifies a submitted drug product and a submitted daily dosa

We claim: 1. A method for look-alike sound-alike medication error messaging, comprising: receiving, at a host server, a prescription transaction from a pharmacy POS device, wherein the prescription transaction received at the host server specifies a submitted drug product and a submitted daily dosage for the submitted drug product; determining, by the host server, that the submitted drug product specified by the prescription transaction is associated with at least one look-alike sound-alike (LASA) alternative drug product by comparing the submitted drug product specified by the prescription transaction to LASA drug pair data identifying similarities between drug products; determining, by the host server, that the submitted daily dosage specified by the prescription transaction is not within a typical dosage range for the submitted drug product specified by the prescription transaction, wherein the determination is based on a comparison of the submitted daily dosage specified by the prescription transaction to the typical dosage range for the submitted drug product specified by the prescription transaction; determining, by the host server, that the submitted daily dosage specified by the prescription transaction is within a typical dosage range for the at least one LASA alternative drug product identified in the LASA drug pair data, wherein the determination is based on a comparison of the submitted daily dosage specified by the prescription transaction to the typical dosage range for the at least one LASA alternative drug product identified in the LASA drug pair data; accessing at least one likelihood indicator value that represents a relative probability of whether the submitted drug product specified by the prescription transaction is submitted in error and instead should be one of the at least one LASA alternative drug products identified in the LASA drug pair data, wherein the at least one likelihood indicator value is based, at least in part, on a comparison of prescribing frequency of the submitted drug product specified by the prescription transaction to a prescribing frequency of the at least one LASA alternative drug product identified in the LASA drug pair data; determining, based on the at least one likelihood indicator value, that the prescribing frequency of the submitted drug product specified by the prescription transaction compared to the prescribing frequency of the at least one LASA alternative drug product identified in the LASA drug pair indicates an increased probability that the submitted drug product specified by the prescription transaction is submitted in error; determining that the prescription transaction should be rejected based, at least in part, on the determinations that: (a) the submitted drug product specified by the prescription transaction is associated with the at least one LASA alternative drug product identified in the LASA drug pair data; (b) the submitted daily dosage specified by the prescription transaction is within the typical dosage range for the at least one LASA alternative drug product identified in the LASA drug pair data and not within the typical dosage range for the submitted drug product specified by the prescription transaction; and (c) that the prescribing frequency of the submitted drug product specified by the prescription transaction compared to the prescribing frequency of the at least one LASA alternative drug product identified in the LASA drug pair indicates an increased probability that the submitted drug product specified by the prescription transaction is submitted in error; generating a reject message at the host server, wherein the reject message indicates a potential prescription error has been detected; and transmitting the reject message from the host server to the pharmacy POS device. 2. The method of claim 1, wherein determining that the prescription transaction should be rejected includes determining a clinical significance associated with the submitted drug product specified by the prescription transaction and the at least one LASA alternative drug products identified in the LASA drug pair data, the clinical significance being a value used to quantify the consequences of dispensing the submitted drug product specified by the prescription transaction instead of the at least one LASA alternative drug products identified in the LASA drug pair data. 3. The method of claim 1, wherein determining that the prescription transaction should be rejected includes determining whether the prescription transaction relates to a new prescription or a refill. 4. The method of claim 1, wherein the typical dosage ranges are specific to at least one of the group consisting of: patient demographic group, treatment type, illness type and physician specialty. 5. The method of claim 1, wherein the reject message identifies the at least one LASA alternative drug product. 6. The method of claim 1, wherein the at least one likelihood indicator value is also based on additional factors including: a degree of similarity between drug names of the submitted drug product specified by the prescription transaction and the at least one LASA alternative drug product identified in the LASA drug pair data, and whether the submitted drug product and the at least one LASA alternative drug product are available in similar strengths. 7. The method of claim 1, wherein the prescribing frequencies of the submitted drug product specified by the prescription transaction and the at least one LASA alternative drug product identified in the LASA drug pair data are categorized as being either high, medium or low; and wherein a low-low, high-low, or low-high combination of prescribing frequencies indicates an increased probability that the submitted drug product specified by the prescription transaction is submitted in error. 8. The method of claim 1, wherein determining that the prescription transaction should be rejected includes determining whether the submitted daily dosage specified by the prescription transaction meets absolute dosing criteria for the submitted drug product specified by the prescription transaction. 9. The method of claim 8, wherein the submitted daily dosage specified by the prescription transaction is determined to not meet the absolute dosing criteria for the submitted drug product specified by the prescription transaction because the submitted daily dosage is lower than an absolute minimum daily dosage for the submitted drug product. 10. The method of claim 8, wherein the submitted daily dosage specified by the prescription transaction is determined to not meet the absolute dosing criteria for the submitted drug product specified by the prescription transaction because the submitted daily dosage exceeds an absolute maximum daily dosage for the submitted drug product. 11. The method of claim 8, wherein the absolute dosing criteria is specific to at least one of the group consisting of: patient demographic group, treatment type and illness type. 12. A system for look-alike sound-alike medication error messaging, comprising: a network interface; at least one database, wherein the at least one database includes: look-alike sound-alike (LASA) drug pair data identifying similarities between drug products; typical dosage ranges for drug products included in the LASA drug pair data; and a plurality of likelihood indicator values that each represents a relative probability of whether a first drug product is confused with a second drug product identified in the LASA drug pair data, wherein at least one of the plurality of likelihood indicator values is based, at least in part, on comparing a prescribing frequency of the first drug product to a prescribing frequency of the second drug product identified in the LASA drug pair data; and a processor, located at a host server, in communication with the network interface and the at least one database, wherein the processor is configured for executing computer-executable instructions to: receive, via the network interface, a prescription transaction from a pharmacy POS device, wherein the prescription transaction specifies a submitted drug product and a submitted daily dosage for the submitted drug product; determine that the submitted drug product specified by the prescription transaction is associated with at least one LASA alternative drug product identified in the LASA drug pair data by comparing the submitted drug product specified by the prescription transaction to the LASA drug pair data; determine that the submitted daily dosage specified by the prescription transaction is not within a typical dosage range for the submitted drug product specified by the prescription transaction, wherein the determination is based on a comparison of the submitted daily dosage specified by the prescription transaction to the typical dosage range for the submitted drug product specified by the prescription transaction; determine that the submitted daily dosage specified by the prescription transaction is within a typical dosage range for the at least one LASA alternative drug product identified in the LASA drug pair data, wherein the determination is based on a comparison of the submitted daily dosage specified by the prescription transaction to the typical dosage range for the at least one LASA alternative drug product stored in the database identified in the LASA drug pair data; determine, based on the at least one likelihood indicator value associated with the submitted drug product specified by the prescription transaction and the at least one LASA alternative drug product identified in the LASA drug pair, that the prescribing frequency of the submitted drug product compared to the prescribing frequency of the at least one LASA alternative drug product indicates an increased probability that the submitted drug product specified by the prescription transaction is submitted in error; determine that the prescription transaction should be rejected based, at least in part, on the determinations that: (a) the submitted drug product specified by the prescription transaction is associated with the at least one LASA alternative drug product identified in the LASA drug pair data; (b) the submitted daily dosage specified by the prescription transaction is within the typical dosage range for the at least one LASA alternative drug product identified in the LASA drug pair data and not within the typical dosage range for the submitted drug product specified by the prescription transaction; and (c) that the prescribing frequency of the submitted drug product specified by the prescription transaction compared to the prescribing frequency of the at least one LASA alternative drug product identified in the LASA drug pair indicates an increased probability that the submitted drug product specified by the prescription transaction is submitted in error; generate a reject message, wherein the reject message indicates a potential prescription error has been detected; and transmit the reject message from the host server to the pharmacy POS device. 13. The system of claim 12, wherein the computer-executable instructions to determine that the prescription transaction should be rejected include computer-executable instructions to determine a clinical significance associated with the submitted drug product specified by the prescription transaction and the at least one LASA alternative drug products identified in the LASA drug pair data, the clinical significance being a value used to quantify the consequences of dispensing the submitted drug product specified by the prescription transaction instead of the at least one LASA alternative drug products identified in the LASA drug pair data. 14. The system of claim 12, wherein the computer-executable instructions to determine that the prescription transaction should be rejected include computer-executable instructions to determine whether the prescription transaction relates to a new prescription or a refill. 15. The system of claim 12, wherein the typical dosage ranges are specific to at least one of the group consisting of: patient demographic group, treatment type, illness type and physician specialty. 16. The system of claim 12, wherein the reject message identifies the at least one LASA alternative drug product. 17. The system of claim 12, wherein the at least one likelihood indicator value is also based on additional factors including: a degree of similarity between drug names of the submitted drug product specified by the prescription transaction and the at least one LASA alternative drug product identified in the LASA drug pair data, and whether the submitted drug product and the at least one LASA alternative drug product are available in similar strengths. 18. The system of claim 12, wherein the prescribing frequencies of the submitted drug product specified by the prescription transaction and the at least one LASA alternative drug product identified in the LASA drug pair data are categorized as being either high, medium or low; and wherein a low-low, high-low, or low-high combination of prescribing frequencies indicates an increased probability that the submitted drug product specified by the prescription transaction is submitted in error. 19. The system of claim 12, wherein the computer-executable instructions to determine that the prescription transaction should be rejected include computer-executable instructions to determine whether the submitted daily dosage specified by the prescription transaction meets absolute dosing criteria for the submitted drug product specified by the prescription transaction. 20. The system of claim 19, wherein the submitted daily dosage specified by the prescription transaction is determined to not meet the absolute dosing criteria for the submitted drug product specified by the prescription transaction because the submitted daily dosage is lower than an absolute minimum daily dosage for the submitted drug product. 21. The system of claim 19, wherein the submitted daily dosage specified by the prescription transaction is determined to not meet the absolute dosing criteria for the submitted drug product specified by the prescription transaction because the submitted daily dosage exceeds an absolute maximum daily dosage for the submitted drug product. 22. The system of claim 19, wherein the absolute dosing criteria is specific to at least one of the group consisting of: patient demographic group, treatment type and illness type. 23. A method for look-alike sound-alike medication error messaging, comprising: receiving, at a host server, a prescription transaction from a pharmacy POS device, wherein the prescription transaction received at the host server specifies a submitted drug product and a submitted daily dosage for the submitted drug product; determining, by the host server, that the submitted drug product specified by the prescription transaction is associated with at least one look-alike sound-alike (LASA) alternative drug product by comparing the submitted drug product specified by the prescription transaction to LASA drug pair data identifying similarities between drug products; determining, by the host server, that the submitted daily dosage specified by the prescription transaction is not within a typical dosage range for the submitted drug product specified by the prescription transaction, wherein the determination is based on a comparison of the submitted daily dosage specified by the prescription transaction to the typical dosage range for the submitted drug product specified by the prescription transaction; determining, by the host server, that the submitted daily dosage specified by the prescription transaction is within a typical dosage range for the at least one LASA alternative drug product identified in the LASA drug pair data, wherein the determination is based on a comparison of the submitted daily dosage specified by the prescription transaction to the typical dosage range for the at least one LASA alternative drug product identified in the LASA drug pair data; determining, based on a comparison of a prescribing frequency of the submitted drug product specified by the prescription transaction to a prescribing frequency of the at least one LASA alternative drug product identified in the LASA drug pair, there is an increased probability that the submitted drug product specified by the prescription transaction is submitted in error; determining that the prescription transaction should be rejected based, at least in part, on the determinations that: (a) the submitted drug product specified by the prescription transaction is associated with the at least one LASA alternative drug product identified in the LASA drug pair data; (b) the submitted daily dosage specified by the prescription transaction is within the typical dosage range for the at least one LASA alternative drug product identified in the LASA drug pair data and not within the typical dosage range for the submitted drug product specified by the prescription transaction; and (c) that the prescribing frequency of the submitted drug product specified by the prescription transaction compared to the prescribing frequency of the at least one LASA alternative drug product identified in the LASA drug pair indicates an increased probability that the submitted drug product specified by the prescription transaction is submitted in error; generating a reject message at the host server, wherein the reject message indicates a potential prescription error has been detected; and transmitting the reject message from the host server to the pharmacy POS device. 24. The method of claim 1, wherein the prescribing frequencies of the submitted drug product specified by the prescription transaction and the at least one LASA alternative drug product identified in the LASA drug pair data are based on an analysis of historical prescription transactions. 25. The system of claim 12, wherein the prescribing frequencies of the submitted drug product specified by the prescription transaction and the at least one LASA alternative drug product identified in the LASA drug pair data are based on an analysis of historical prescription transactions. 26. The method of claim 23, wherein relative difference between the prescribing frequency of the submitted drug product specified by the prescription transaction and the prescribing frequency of the at least one LASA alternative drug product identified in the LASA drug pair exceeds a pre-established threshold value.