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Rx16 pdmp tues_200_1_o_neill_2carter_3small_armagan
The document discusses new developments in prescription drug monitoring programs (PDMPs) in California, Colorado, and Minnesota. It provides an overview of presentations given on upgrades to the PDMP systems in each state. Key points include: Colorado's PDMP has enhanced data reporting requirements and streamlined data retrieval; Minnesota's PDMP has focused on improving data quality and compliance; and California's upgraded PDMP (CURES 2.0) features automated registration, delegation of authority, patient flagging, peer-to-peer communication on patient safety, and de-identified data sets.
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Rx16 pdmp tues_200_1_o_neill_2carter_3small_armagan
- 1. New Developments inPDMPs: California, Colorado and Minnesota Presenters: • Mark R. O’Neill, RPh, Program Manager, Colorado Prescription Drug Monitoring Program • Barbara A. Carter, PMP Manager, Minnesota Board of Pharmacy, Prescription Monitoring Program • Tina Farales, Department of Justice Administrator, Prescription Drug Monitoring Program, California Department of Justice • Artin Armagan, PhD, Manager, Advanced Analytics Lab, SAS Institute PDMP Track Moderator: John L. Eadie, Coordinator, Public Health and Prescription Drug Monitoring Program Project, National Emerging Threat Initiative, National HIDTA Assistance Center, and Member, Rx and Heroin Summit National Advisory Board
- 2. Disclosures • Barbara A.Carter; Tina Farales; Mark R. O’Neill, RPh; and John L. Eadie have disclosed no relevant, real, or apparent personal or professional financial relationships with proprietary entities that produce healthcare goods and services. • Artin Armagan, PhD – Ownership interest: Walmart (spouse)
- 3. Disclosures • All planners/managershereby state that they or their spouse/life partner do not have any financial relationships or relationships to products or devices with any commercial interest related to the content of this activity of any amount during the past 12 months. • The following planners/managers have the following to disclose: – John J. Dreyzehner, MD, MPH, FACOEM – Ownership interest: Starfish Health (spouse) – Robert DuPont – Employment: Bensinger, DuPont & Associates-Prescription Drug Research Center
- 4. Learning Objectives 1. Expressthe value of PDMPs as healthcare tools. 2. Describe PDMP enhancements that improve data integrity and streamline retrieval and viewing of PDMP searches and reports. 3. Identify the features and benefits of California’s upgraded PDMP, CURES 2.0. 4. Provide accurate and appropriate counsel as part of the treatment team.
- 5. New Developments inPDMPs: Colorado Mark R. O’Neill, RPh Program Manager Colorado Prescription Drug Monitoring Program
- 6. Focus on Value:A map of Colorado’s rising drug- related deaths between 2002 and 2014. Representation of the need for PDMP programs in the United States.
- 7. Colorado Drug OverdoseDeath Rate 2002 “Colorado Drug Death Rate Tops U.S. Average,” Colorado Health Institute, Feb. 2016
- 8. Colorado Drug OverdoseDeath Rate 2014 “Colorado Drug Death Rate Tops U.S. Average,” Colorado Health Institute, Feb. 2016
- 9. Colorado PDMP: Anoverview Began 2007. 6 prescribing Boards / Pharmacy. 2 person staff. 3rd Party vendor. ~ $175,000 / year. Funded by prescriber fees. Colorado Population: 5.5 million Over 2.6 million patient specific queries in 2015
- 10. Enhancements: PDMP asa Healthcare Tool Legislative Update 2014 Mandatory registration (not mandatory use) of all DEA registered prescribers Daily reporting by pharmacies to increase reliability and trust of data Delegated authority for increased use and access for prescribers and pharmacists – up to 3 trained delegates Access granted to Colorado Department of Public Health and Environment
- 11. Prescription Trends 2014- 2015 722,964 601,895 585,587 420,108 521,806 450,984 467,922 402,576 400,676 306,348 358,041 329,191300,000 400,000 500,000 600,000 700,000 Prescriptions Dispensed Patients recieving prescriptions
- 12. Tackling Doctor Shopping- Push Notices Obtaining controlled substances from multiple sources in potentially dangerous quantities. Prescribers and pharmacists can use the PDMP to stop “doctor shopping.” Push Notice letters are sent out to prescribers and pharmacies monthly. Push Notices are often a “reality check” for prescribers and pharmacists
- 14. Streamlined Retrieval ofData Automated Access: Single log-on access to patients’ PDMP files Inclusion of “Rxcheck” Allows for efficient, reliable and secure access. Currently used at two practice sites in Colorado: one major chain pharmacy and one federal facility.
- 15. Streamlined Retrieval ofData Integration of Electronic Health Records through the Harold Rogers PDMP Grant for Practitioner and Research Partnerships 5 major Emergency Departments at Colorado hospitals
- 16. Colorado: Outreach andEducation Outreach to Colorado – Speakers Bureau offers ongoing PDMP information. Consortium for the Prevention of Prescription Drug Abuse: Created as “Task Force” for continued improvement of PDMP. New PDMP dedicated website Training webinars YouTube videos Production of PDMP brochure
- 17. New Developments inPDMPs: Minnesota Barbara A. Carter PMP Manager Minnesota Board of Pharmacy
- 18. Disclosure Statement • BarbaraA. Carter, has disclosed no relevant, real or apparent personal or professional financial relationships with proprietary entities that produce health care good and services.
- 19. Learning Objectives • Expressthe value of PDMPs as healthcare tools. • Describe PDMP enhancements that improve data integrity and streamline retrieval and viewing of PDMP searches and reports. • Identify the features and benefits of California’s upgraded PDMP, CURES 2.0. • Provide accurate and appropriate counsel as part of the treatment team.
- 20. DATA REPORTING &DATA INTEGRITY: THE PATH TO IMPROVEMENT Barbara A Carter, PMP Manager, Minnesota Board of Pharmacy
- 21. Identifying the Issues •Compliance in Reporting – Are all dispensers reporting? – How often are they reporting? • Data Quality – How accurate is the data? – Are there missing records?
- 22. Facts and Figures 2010 •1,700 licensed pharmacies • 6.6M prescription records (CS II-IV) 2015 • 2,000 licensed pharmacies • 8M prescription records (CS II-V)
- 23. Are all dispensersreporting? • Honor System – Unmet Expectations • Unique Pharmacy Identifier – Pharmacy DEA# • Match with MN pharmacy license # • Monthly Compliance – 1st notice – 2nd notice ($10,000 fine) – Phone Call – Complaint filed
- 24. How often arethey reporting? • Daily reporting required – By procedure not statute • Inadequate Reporting – Definition • Less than 20 reports monthly • Identify manageable threshold – 10 reports – 18 reports
- 25. DATA QUALITY • Whouploads the data? – Pharmacy staff – Corporate office – External vendor • How are errors communicated and to whom? – Error reports • Email • Fax – Data uploader
- 26. Errors impacting enduser • Minor – Days supply invalid (>180 days) – Refill code is not a # • Serious – Invalid prescriber DEA# – Invalid NDC # • Fatal – Blank prescriber DEA# – Blank DOB
- 27. Current initiative • Blastcommunication-2 months in advance – Uploader and PIC • Error correction within 7 days receipt of edit report • Establish relationship with data uploader • Auditing Begins – Weekly error summary report • Identify worst offenders – Errors that impact end user • Allow 7 days to pass then audit for error resolution
- 28. Determining Compliance • Errorsresolved within 7 days • Outstanding errors – Phone call to Pharmacist in Charge (PIC) • Secure email with prescription details • Ongoing collaboration with PIC, uploader and PMP vendor – Complaint filed with Board
- 29. Outcomes • Compliance inreporting improved • Frequency of reporting improved • Improvement in data quality • Relationships improved
- 30. Lessons Learned • Communicationis Critical – PMP and Dispenser – Dispenser and their Vendor • Start Out Small • Hidden Issues uncovered • Dedicated Resources • Work in Progress
- 31. Next Steps • Recognize“gold star” performance • Update contact lists • Update error report communication preference • Create tutorials-how to’s for data providers • Increase frequency of communications • Educate, educate, educate
- 32.
- 33. New Developments inPDMPs California’s CURES 2.0
- 34. Mike Small hasdisclosed no relevant, real or apparent personal or professional financial relationships with proprietary entities that produce health care goods and services. Artin Armagan has disclosed that his spouse is employed as a pharmacist by Duke Raleigh Hospital and Walmart Pharmacy.
- 35. New Developments inPDMPs California’s CURES 2.0 Learning Objective: Identify the features and benefits of California’s upgraded PDMP, CURES 2.0.
- 36. California Health andSafety Code section § 11165. (a) To assist health care practitioners in their efforts to ensure appropriate prescribing, ordering, administering, furnishing, and dispensing of controlled substances, law enforcement and regulatory agencies in their efforts to control the diversion and resultant abuse of Schedule II, Schedule III, and Schedule IV controlled substances, and for statistical analysis, education, and research, the Department of Justice shall . . . maintain the Controlled Substance Utilization Review and Evaluation System (CURES)…Review and Evaluation System (CURES)…
- 37. The Iatrogenically AddictedPatient and the Doctor Shopper ~ Information Delivery ~ Support the Public Health Sector ~ The Public Needs to Know ~ Analytics
- 38. Automated Registration California clinicalusers are provided a fully automated registration process. Delegation Authority Prescribers and dispensers can easily assign delegates who can initiate CURES 2.0 patient inquiries on their behalf. Compact Flagging Prescribers can easily notate their patients with treatment exclusivity compacts, forewarning other providers that additional prescribing to these patients can be potentially counter- productive to their existing treatment regimen. CURES 2.0 User Features
- 39. Peer-to-Peer Communication Prescribers anddispensers can instigate alert messages to fellow doctors and pharmacists about mutual patients of concern. Patient Safety Messaging Prescribers are alerted daily with information regarding their patients who reach various prescribing thresholds. CURES 2.0 User Features
- 40. CURES 2.0 systematicallyde-duplicates and de-identifies county and statewide data sets for County Health Officers and researchers. Quarterly and annual de-identified data sets are produced for County Health Officers. This data enables counties to calculate current rates of prescriptions, examine variations within the state, and track the impact of safe prescribing initiatives. De-Duplicated / De-Identified Data
- 41. 1. For EachIndividual Prescriber, a List of That Prescriber's Rx Recipients Who are Currently Prescribed More than 100 Morphine Milligram Equivalency Per Day 2. For Each Individual Prescriber, a List of That Prescriber's Rx Recipients Who Have Obtained Prescriptions from 6 or More Prescribers or 6 or More Pharmacies During Last 6 Months 3. For Each Individual Prescriber, a List of That Prescriber's Rx Recipients Who Are Currently Prescribed More than 40 MMEs Methadone Daily 4. For Each Individual Prescriber, a List of That Prescriber's Rx Recipients Who Are Currently Prescribed Opioids More Than 90 Consecutive Days 5. For Each Individual Prescriber, a List of That Prescriber's Rx Recipients Who Are Currently Prescribed Both Benzodiazepines and Opioids Patient Safety Messaging
- 46. 1 Total Numberof Prescriptions for Opioid Drugs by Month, by State, County and Zip Code 2 Total Number of Prescriptions for Opioid Drugs by Calendar Year, by State, County and Zip Code 3 Total Number of Unique Patients Prescribed Opioids by Month, by State, County and Zip Code 4 Total Number of Unique Patients Prescribed Opioids by Calendar Year, by State, County and Zip Code 5 Number of Opioid Pills Prescribed by Month, by State, County and Zip Code 6 Number of Opioid Pills Prescribed by Calendar Year, by State, County and Zip Code 7 Median Number of Opioid Pills Per Prescription by Month, by State, County and Zip Code Public Reports
- 47. 8 Median Numberof Opioid Pills Per Prescribed by Calendar Year, by State, County and Zip Code 9 Number of Patients Receiving Opioid Prescriptions by Month, by State, County and Zip Code, by Age as Follows: ≤ 14; 15-24; 25-44; 45-64; ≥65 10 Number of Patients Receiving Opioid Prescriptions by Calendar Year, by State, County and Zip Code, by Age as Follows: ≤ 14; 15-24; 25-44; 45-64; ≥65 11 Number of Opioid Pills and Benzodiasepine Pills Prescribed to the Same Patient by Month, by State, County and Zip Code 12 Number of Opioid Pills and Benzodiasepine Pills Prescribed to the Same Patient by Calendar Year, by State, County and Zip Code Public Reports
- 48. 13 Number ofPatients, by Month, Prescribed Both Opioids and Benzodiasepine, by State, County and Zip Code 14 Number of Patients, by Year, Prescribed Both Opioids and Benzodiasepine Within Any 30 Day Window, by State, County and Zip Code 15 Total Morphine Milligram and Morphine Kilogram Equivalents Prescribed by Month, by State, County and Zip Code 16 Total Morphine Milligram and Morphine Kilogram Equivalents Prescribed by Calendar Year, by State, County and Zip Code 17 Morphine Milligram and Morphine Kilogram Equivalents Prescribed by Month, by State, County and Zip Code for: Oxycodone, Hydrocodone, Morphine, Methadone, Hydromorphone, Buprenorphine, Fentanyl, Oxymorphone, Codeine, Levorphanol, and Zohydro Public Reports
- 49. 18 Morphine Milligramand Morphine Kilogram Equivalents Prescribed by Calendar Year, by State, County and Zip Code for: Oxycodone, Hydrocodone, Morphine, Methadone, Hydromorphone, Buprenorphine, Fentanyl, Oxymorphone, Codeine, Levorphanol, and Zohydro 19 Number of Very Frequent Opioid Prescribers (580+ Opioid Rx/Yr), Frequent Prescribers (50-579 Opioid Rx/Yr), Occasional Prescribers (8-49 Opioid Rx/Yr), and Rare Prescribers (1-7 Opioid Rx/Yr), by State, by State, County and Zip Code 20 Number of Very Frequent Schedule II Drug Prescribers (580+ Sked II Rx/Yr), Frequent Prescribers (50-579 Sked II Rx/Yr), Occasional Prescribers (8-49 Sked II Rx/Yr), and Rare Prescribers (1-7 Sked II Rx/Yr), by State, County and Zip Code 21 Total Number of Prescriptions for all Schedule II Drugs by Month, by State, County and Zip Code Public Reports
- 50. 21 Total Numberof Prescriptions for all Schedule II Drugs by Month, by State, County and Zip Code 22 Total Number of Prescriptions for all Schedule II Drugs by Calendar Year, by State, County and Zip Code 23 Total Number of Prescriptions for Schedules II, III, and IV Drugs, by Schedule and Total, by Month, by State, County and Zip Code 24 Total Number of Prescriptions for Schedules II, III, and IV Drugs, by Schedule and Total, by Calendar Year, by State, County and Zip Code 25 Total Number Patients Receiving Schedule II, III and IV Drug Prescriptions, by Month, by State, County and Zip Code 26 Total Number Patients Receiving Schedule II, III and IV Drug Prescriptions, by Calendar Year, by State, County and Zip Code Public Reports
- 51. 27 Median Numberof Pills Per Prescription for Schedules II, III, and IV Drugs by Month, by State, County and Zip Code 28 Median Number of Pills Prescribed for Schedules II, III, and IV Drugs by Calendar Year, by State, County and Zip Code 29 Median Number of Pills Per Prescription for Schedule II Drugs by Month, by State, County and Zip Code 30 Median Number of Pills Prescribed for Schedule II Drugs by Calendar Year, by State, County and Zip Code 31 Median Pills , by Month, Per Schedule II, III, or IV Prescription by Age as follows: ≤ 14; 15-24; 25-44; 45-64; ≥65 32 Median Pills , by Year, Per Schedule II, III, or IV Prescription by Age as follows: ≤ 14; 15-24; 25-44; 45-64; ≥65 Public Reports
- 52. 33 Number ofPrescriber and Dispenser Registrants, by Month, by State, County and Zip Code 34 Number of Prescriber and Dispenser Registrants, by Year, by State, County and Zip Code 35 Number of Patients Who Obtained 4 or More Schedule II, III, or IV Prescriptions from 4 or More Dispensers During Prior 12 months, by State, County and Zip Code 36 Number of Patients Who Obtained 4 or More Schedule II, III, or IV Prescriptions from 4 or More Dispensers During the Calendar Year, by State, County and Zip Code 37 Number of Patients with Same Prescription Drug from 3 or More Prescribers, by Month, by State, County and Zip Code Public Reports
- 53. 38 Number ofPatients with Same Prescription Drug from 3 or More Prescribers, by Calendar Year, by State, County and Zip Code 39 Number of CURES Inquiries by Prescribers, by Month, by State, County, and Zip Code 40 Number of CURES Inquiries by Prescribers, by Year, by State, County, and Zip Code 41 Number of CURES Inquiries by Dispensers, by Month, by State, County, and Zip Code 42 Number of CURES Inquiries by Dispensers, by Year, by State, County, and Zip Code 43 Numbers of Prescribers Prescribing Opioids and Benzodiazepines Concurrently to a Patient, by Month, by State, County, and Zip Code Public Reports
- 54. 44 Numbers ofPrescribers Prescribing Opioids and Benzodiazepines Concurrently to a Patient, by Year, by State, County, and Zip Code 45 Number of Patients Currently Prescribed More than 100 Morphine Milligram Equivalency Per Day, by Month, by State, County, and Zip Code 46 Number of Patients Currently Prescribed More than 100 Morphine Milligram Equivalency Per Day, by Year, by State, County, and Zip Code 47 Number of Patients Who Are Currently Prescribed More than 40 Milligrams Methadone Daily, by Month, by State, County, and Zip Code 48 Number of Patients Who Are Currently Prescribed More than 40 Milligrams Methadone Daily, by Year, by State, County, and Zip Code Public Reports
- 55.
- 56. ENTITY RESOLUTION John Doe 01/01/70 456HARRISON AVE CARY, NC 27513John Doe 01/01/70 123 HARRISON AVE CARY, NC 27513 John Doe 01/01/70 789 HARRISON AVE CARY, NC 27511 Johnnie Doe 01/01/70 123 HARISON AVE CARY, NC 27511 ONE ENTITY
- 57. PATIENT SCENARIOS 1. RxRecipients Who are Currently Prescribed More than 100 Morphine Milligram Equivalency Per Day 2. Rx Recipients Who Have Obtained Prescriptions from 6 or More Prescribers or 6 or More Pharmacies During Last 6 Months 3. Rx Recipients Who Are Currently Prescribed More than 40 MMEs Methadone Daily 4. Rx Recipients Who Are Currently Prescribed Opioids More Than 90 Consecutive Days 5. Rx Recipients Who Are Currently Prescribed Both Benzodiazepines and Opioids
- 58. ENTITY RESOLUTION &SCENARIOS
- 59. TIME 30 MME80 MME110MME110 MME + BENZO OPIOID OPIOID OPIOID BENZO
- 60. ALERTS • Patient Name •Patient DOB • Patient Address • Patient City • Patient Zip Code • # of Anomalous Scenarios • Triggered Scenarios
- 61. DE-IDENTIFIED DATA AnonymizedPatient ID Anonymized Prescriber ID Anonymized Pharmacy ID Patient Birth Year Patient Gender Patient Zip Code Patient County Patient State Prescriber Zip Code Prescriber County Prescriber State Pharmacy Zip Code Pharmacy County Pharmacy State Product Name NDC Drug Form Strength Quantity Days Supply Date Filled Refill Number Payment Code Prescriber Specialty Prescriber Board Certification Indicator • Personally identifying information redacted. • Anonymized patient IDs maintained to be consistent from report to report. • Generated quarterly and annually for each county and the entire state.
- 62.
- 63. New Developments inPDMPs: California, Colorado and Minnesota Presenters: • Mark R. O’Neill, RPh, Program Manager, Colorado Prescription Drug Monitoring Program • Barbara A. Carter, PMP Manager, Minnesota Board of Pharmacy, Prescription Monitoring Program • Tina Farales, Department of Justice Administrator, Prescription Drug Monitoring Program, California Department of Justice • Artin Armagan, PhD, Manager, Advanced Analytics Lab, SAS Institute PDMP Track Moderator: John L. Eadie, Coordinator, Public Health and Prescription Drug Monitoring Program Project, National Emerging Threat Initiative, National HIDTA Assistance Center, and Member, Rx and Heroin Summit National Advisory Board
Editor's Notes
- #21 As you heard from Mark several improvements in CO have been made in the accessibility and use of the data. As we continue to encourage use of PMPs it is critical that A) We get all of the prescription information that we should be getting and B) That the data is accurate. Like many PMPs our program staff get calls from prescribers and pharmacists when there are prescriptions missing from the database, there is no prescriber name in the record, they cant find a patient and so on. Who would have thought that data received would not be perfect?
- #22 Determining compliance in reporting and the integrity of the data reported has been a challenge for some PMPs. In MN we recognized early on that this would be a huge undertaking and knew that we couldn’t deal with it all at once. As with any challenge we needed to first break down the issues. Broken down in to two areas seemed to be much more manageable. We needed to know if all of the dispensers who should be reporting were and how often were they reporting [NEXT] Secondly we needed to know how accurate was the data they were reporting and were there any missing records or files.
- #23 Before I continue I just want to lay the groundwork for what we would be dealing with. In 2010-when the PMP was first implemented there were approximately 1700 MN licensed pharmacies and by the end of that calendar year we had collected close to 6.6 million prescription records. Fast forward to 2015 and now we are dealing with more than 2,000 pharmacies and 8 million prescriptions. From here on out I will use pharmacy and dispenser interchangeably.
- #24 In the beginning, we relied heavily on dispensers, most of which are pharmacies, to comply with the new law based on the honor system. But we quickly learned that it wasn’t quite working as we had planned. Our contracted PMP vendor provided a monthly report showing which dispensers were reporting data, but the number of reporting pharmacies didn’t seem to come close to what we expected. [NEXT} Because pharmacies reported using their DEA registration number and not their MN license number it was very difficult to match those reporting with those not reporting. So the first thing we had to do was request that each and every pharmacy licensed by MN, who was not exempted from reporting, send us their DEA# and then capture it in their pharmacy license record. At that time a very manual and time consuming process, but we did it. Finally in 2011 we began providing our PMP vendor a current monthly data file of all MN licensed pharmacies, which included their DEA# to be used for matching. The reports returned show all who reported on one tab, including the number of data uploads and those who did not report data for the given month on another. [NEXT} Those identified as not reporting are notified by mail of their non-compliance and are required to commence reporting immediately. If necessary a second letter is sent, this time with a stronger message which included the possibility of up to a $10,000 file (imposed by the Board, not the PMP) for non-compliance. Continued failure to comply results in a phone call and if needed a complaint is filed with the Board. Very few complaints are filed as that reference to the $10,000 fine seemed to make an impact.
- #25 But just reporting doesn’t satisfy the requirements. Our expectation is that the pharmacy report either at the end of the business day or the next day. Procedures established by the PMP require daily reporting of prescriptions dispensed. Getting the data is important, but getting it in a timely manner is critical to the PDMP being a valuable healthcare tool. The number of file uploads is included in the monthly compliance reports and is used to identify how often files are being uploaded. Because we are located in the Board of Pharmacy, PMP staff have access to information in the pharmacy license record such as their business days and hours, which has proven to be very useful in determining how many uploads in a month we should be expecting from a specific pharmacy. Therefore setting a more realistic threshold. Taking into account holidays and weekends, we defined inadequate reporting as less than 20 reports from a pharmacy during a given month. We started with the biggest offenders and therefore set our initial threshold a bit lower. Those with less than 10 reports were considered non-compliant and the pharmacy was notified. As a result of our efforts we recently increased the threshold to 18 reports a months. Notification to pharmacies and process for gaining compliance is similar to reporting compliance process in which notifications are sent and if compliance is not met after the second notice, a phone call is made and if no results a complaint is filed with the Board. Again, very few dispensers have been turned over to the board for further consideration.
- #26 The next phase of our initiative was to deal with data quality. In this day and age of technology one might think that reporting is done automatically without human intervention. That is not always the case. Depending on the pharmacy the data uploader might be a pharmacy staff person, such as the pharmacist in charge or a technician or it could be done at the corporate level. There are even pharmacy operations software vendors who might provide the data upload service. When data is submitted to the MN PMP, via our software vendor, the records being submitted, using a set of industry standards, are checked for errors. The MN PMP RxSentry, the application used by MN for ourr data collection and dissemination, automatically generates a report confirming no errors in the batch submitted, or indicating errors. These error reports are sent via email or fax, depending on the data uploaders preference. Since the data uploader can be one of several involved in the prescription records communications are critical to data quality.
- #27 In the MN PMP RxSentry system, errors are assigned one of three levels. Minor, which if not correct have the least impact on the end user. Such as days supply being greater than 180 days or the code for a refill not being a number. [NEXT] Serious , which if not corrected do have an impact on the end user who is using the PMP as part of their patient care. Errors such as an invalid prescriber DEA#, will not list a prescriber’s name since the DEA# is not legitimate or an invalid National Drug Code (NDC) which when viewed in a report will provide an n/a for the medication dispensed. [NEXT] And finally Fatal errors. When a record with a fatal error is submitted, that record will not load into the database, it will be rejected. Two of the most frequent fatal errors are blank prescriber DEA# and Blank date of birth. In addition, a file containing a percentage of both fatal and serious errors greater than the established threshold will reject as well. Thus even more records that will not be in the database if not corrected.
- #28 So how did we start- We began by establishing an error correction timeline and identifying those errors that we deemed most critical to the end user. Blast communications were sent out 2 months in advance to not only those identified within our system as the “data uploaders” but also the pharmacists in charge at all MN licensed pharmacies, regardless of whether or not they were required to report data. We indicated that our expectation is that errors are corrected within 7 days, all errors including minor errors. We also encouraged them to establish a relationship with each other as we knew that in some cases a PIC really had no knowledge of how their data got to us to begin with. This relationship building really became the key to success. Once we were confident that we were ready to proceed we began to receive a weekly error summary report, which contained errors from the week prior. The first report contained 695 total errors from 247 different pharmacies. Of the errors we deemed to impact the end user with the greatest severity, 298 errors were identified from 140 pharmacies. Pretty overwhelming-so we already needed to adjust our process. We identified what we are calling the “worst offenders”, those with the most errors that impacted the end users and picked the top two. The errors we focused on were invalid prescriber DEA# and blank prescriber DEA#. We wait until the end of the allowable 7day correction period, and audit their data to determine compliance in corrections.
- #29 If it is found that the pharmacy has resolved their errors within 7 days without intervention [NEXT] we internally, give them a gold star. We are currently picking the top 2 offenders but we do move down the list until we have identified 2 that have not corrected errors. Currently we estimate it takes on average 1 hour to audit a pharmacy. [NEXT} If it is determined that the errors have not been fixed, we make a phone call. The PIC is called initially and not the uploader as the responsibility ultimately lies with PIC to submit accurate data. After sometimes a fairly lengthy discussion a secure email containing the prescriptions in questions is sent. Generally we find that most PICs need some assistance in fixing records so we do find ourselves communicating with PIC, Uploader and sometimes our PMP vendor to resolve errors. [NEXT] If this all fails, and it appears that the pharmacy is blatantly disregarding correcting errors or keeps making promises week after week that they do not keep-a complaint is filed with the Board.
- #30 Compliance in reporting rates went from about 87% of pharmacies reporting in 2011 to more than 98% reporting in 2015. Because new pharmacies come on board daily we use the total number of pharmacies licensed at the beginning of the calendar year to measure against. [NEXT] Frequency of reporting improved and therefore we were able to tighten the monitoring threshold to look for reporting less than 18 days in a month. We have on average 20 pharmacies that doe not meet the threshold. Down from 80 when we first began. This number has become progressively smaller since the inceptions of inadequate reporting because many pharmacies have responded letting us know they are only open one day a week, or month or that they are closed on the weekends [NEXT] Improved data quality- for example invalid DEAs were removed from the pharmacy’s prescriber dropdown lists so they would not be used again. But most importantly we educated the pharmacies on how the bad data impacts the end user. [NEXT] We continue to educate PICs in the process of data reporting and what they should be expecting of their uploader. Facilitating the communications between PIC and uploader proved to be well worth the time invested. All in all we feel that the communications we initially sent and the ongoing communications with PIC and uploaders does have an impact as when auditing we do find that errors are corrected without intervention.
- #31 As was previously mentioned, communications is critical to improving both compliance in reporting and the quality of the data being reported. Fostering the relationships between PIC and data uploaders is an ongoing effort. [NEXT] The process for auditing is very manual at this time, therefore starting out small is best for ones sanity. [NEXT] We uncovered hidden issues such as pharmacies that were reporting and stopped reporting and didn’t realize they had an internal system issue, the manner in which compounds were being reported was incorrect for all compounds from that pharmacy, and we even found long term care pharmacies dispensing via automated drug distribution systems within the long term care facilities were reporting each time a pill was dispensed out of the machine as a prescription when the law exempted them from reporting that data in the first place. [NEXT] In order to fully engage in a data quality improvement process we will needed additional dedicated resources. We know that it takes approximately 10-15 hours a week to audit and communicate with just a fraction of those pharmacies who are submitting and not correcting their errors without some level of intervention. [NEXT] This initiative continues to be a work in progress as we keep finding the need to modify criteria and thresholds, especially after identifying the hidden issues.
- #32 So what are our next steps? [NEXT} Send a notice of recognition to the pharmacy when we identify them as resolving errors without intervention. [NEXT] Send blast communication to uploaders requesting their current contact info [NEXT] and ask them to update their preference for receiving reports [NEXT]Create a short tutorial on how to revise, remove, or submit a record in the MN PMP so that we can shift our focus to address more errors not being corrected [NEXT] Request space in Board newsletters to provide an update on error resolution and other important PMP information {NEXT} and finally continue to educate not only on data reporting but data corrections and use of the database