Part of a series on |
Algocracy |
---|
Examples |
In the United States, prescription monitoring programs (PMPs) or prescription drug monitoring programs (PDMPs) are state-run programs which collect and distribute data about the prescription and dispensation of federally controlled substances and, depending on state requirements, other potentially abusable prescription drugs. PMPs are meant to help prevent adverse drug-related events such as opioid overdoses, drug diversion, and substance abuse by decreasing the amount and/or frequency of opioid prescribing, and by identifying those patients who are obtaining prescriptions from multiple providers (i.e., "doctor shopping") or those physicians overprescribing opioids.[1][2]
Most US health care workers support the idea of PMPs, which intend to assist physicians, physician assistants, nurse practitioners, dentists and other prescribers, the pharmacists, chemists and support staff of dispensing establishments. The database, whose use is required by State law, typically requires prescribers and pharmacies dispensing controlled substances to register with their respective state PMPs and (for pharmacies and providers who dispense from their offices) to report the dispensation of such prescriptions to an electronic online database. The majority of PMPs are authorized to notify law enforcement agencies or licensing boards or physicians when a prescriber, or patients receiving prescriptions, exceed thresholds established by the state or prescription recipient exceeds thresholds established by the State.[3] All states have implemented PDMPs, although evidence for the effectiveness of these programs is mixed.[4][5] While prescription of opioids has decreased with PMP use, overdose deaths in many states have actually increased, with those states sharing data with neighboring jurisdictions or requiring reporting of more drugs experiencing highest increases in deaths.[6] This may be because those declined opioid prescriptions turn to street drugs, whose potency and contaminants carry greater overdose risk.[6]
History
Prescription drug monitoring programs, or PDMPs, are an example of one initiative proposed to alleviate effects of the opioid crisis.[1] The programs are designed to restrict prescription drug abuse by limiting a patient's ability to obtain similar prescriptions from multiple providers (i.e. “doctor shopping”) and reducing diversion of controlled substances. This is meant to reduce risk of fatal overdose caused by high doses of opioids or interactions between opioids and benzodiazepenes, and to enable better decision making on the part of healthcare providers who may be unaware of a patient's prescription drug use, history or other prescriptions.[7][8]
PDMPs have been implemented in state legislations since 1939 in California, a time before electronic medical records, though implementation increased with s awareness of overprescribing of opioids and overdose.[9][3] A later New York state program was struck down by the U.S. Supreme Court in Whalen v. Roe.[10] But, by 2019, 49 states, the District of Columbia, and Guam had enacted PDMP legislation.[11] In 2021 Missouri, the last State to not use a PMP, adopted legislation to create one.[12][13]
PMPs are constantly being updated to increase speed of data collection, sharing of data across States, and ease of interpretation. This is being done by integrating PDMP reports with other health information technologies such as health information exchanges (HIE), electronic health record (EHR) systems, and/ or pharmacy dispensing software systems.[14] One program that has been implemented in nine states is called the PDMP Electronic Health Records Integration and Interoperability Expansion, also known as PEHRIIE. Another software, marketed by Bamboo Health and integrated with PMPs in 43 states, uses an algorithm to track factors thought to increase risk of diversion, abuse or overdose, and assigns patients a three digit score based on presumed indicators of risk.[15] While some studies have suggested that PDMP-HIT integration and sharing of interstate data brings benefits such as reduced opioid-related inpatient morbidity,[16] others have found no or negative impact on mortality compared to states without PMP data sharing.[6] Patient and media reports suggest need for testing and evaluation of algorithmic software used to score risk, with some patients reporting denial of prescriptions without c explanation or clarity of data.[15]
Goals
Most health care workers support PMPs[17] which intend to assist physicians, physician assistants, nurse practitioners, dentists and other prescribers, the pharmacists, chemists and support staff of dispensing establishments, as well as law-enforcement agencies. The collaboration supports the legitimate medical use of controlled substances while limiting their abuse and diversion. Pharmacies dispensing controlled substances and prescribers typically must register with their respective state PMPs and (for pharmacies and providers who dispense controlled substances from their offices) report the dispensation to an electronic online database. Some pharmacy software can submit these reports automatically to multiple states.[18]
Usage
List of programs by state
State Name | State Code | Format | Method | Reporting Agency | Schedules Monitored | Documentation | State Frequency | Data Retention |
---|---|---|---|---|---|---|---|---|
Alaska | AK | ASAP 2009 v4.1 | sFTP | Appriss:855-525-4767 | 2 - 5 | Source | Monthly | 2 Source |
Alabama | AL | ASAP 2007 v4.0 | sFTP | Health Information Design Phone: 334.502.3262 | 2 - 5 | Source | Daily | ? |
Arkansas | AR | ASAP 2011 v4.2 | sFTP | Health Information Design Phone: 334.502.3262 | ? | ? | Weekly | ? |
Arizona | AZ | ASAP 2011 v4.2 | sFTP | Health Information Design Phone: 334.502.3262 | 2 - 4 + Carisoprodol | Source | Daily | Adult 6 / Minor 3 Source |
California | CA | ASAP 2009 v4.1 | sFTP | Atlantic Associates, Inc Phone: 800.539.3370 | 2 - 4 | Source | Weekly | 3 Source |
Colorado | CO | ASAP 2012 v4.2 | sFTP | Health Information Design Phone: 334.502.3262 | 2 - 5 | Source | Bi-Weekly | ? |
Connecticut | CT | ASAP 4.2 | FTPs | Appriss:855-525-4767 | 2 - 5 | Source | Bi-Weekly | ? |
District of Columbia | DC | ASAP 4.2 | ? | ? | ? | ? | ? | ? |
Delaware | DE | ASAP 2011 v4.2 | sFTP | Health Information Design Phone 334.502.3262 | 2 - 5 | Source | Daily | ? |
Florida | FL | ASAP 2009 v4.2 | sFTP | Health Information Design Phone: 334.502.3262 | 2 - 4 | Source | Weekly | ? |
Georgia | GA | ASAP 2011 V4.2 | ? | Appriss:855-525-4767 | ? | ? | ? | 1 Source |
Hawaii | HI | ASAP 2009 v4.2 | Web Portal | Appriss:855-525-4767 | 2 - 5 + Carisoprodol | Source | Weekly | https://hipdmpreporting.hidinc.com/ |
Idaho | ID | ASAP 2009 v4.1 | sFTP | Appriss:855-525-4767 | 2 - 5 | Source | Weekly | ? |
Illinois | IL | ASAP 2007 v4.0 | sFTP | Atlantic Associates, Inc Phone: 800.539.3370 | 2 - 5 | Source | Weekly | 2 Source |
Indiana | IN | ASAP 2007 v4.2 | FTPs | INSPECT Phone: 317.234.4458 Phone:866.683.2476 | 2 - 5 + Carisoprodol (SOMA) | [1] | Daily | ? |
Iowa | IA | ASAP v4.1 | FTPs | Optimum Technology, Inc Phone: 866.683.2476 | 2 - 4 | Source | Bi-Weekly | 4 Source |
Kansas | KS | ASAP 2009 v4.1 | sFTP | Appriss:855-525-4767 | 2 - 4 + Drugs of Concern | Source | Daily | ? |
Kentucky | KY | ASAP 2009 v4.1 | sFTP | Health Information Design Phone: 334.502.3262 | 2 - 5 + Carisoprodol, Tramadol | Source | Daily | 5 Source |
Louisiana | LA | ASAP 4.2 | sFTP | Appriss:855-525-4767 | 2 - 5 + Tramadol, Butalibtal, Carisoprodol, Ephedrine, Pseudoephedrine, PPA | Source | Weekly | ? |
Massachusetts | MA | ASAP 2009 v4.1 | sFTP | Appriss:855-525-4767 | 2 - 5 | Source | Weekly | ? |
Maryland | MD | ASAP 2011 V4.2 | sFTP | Health Information Design Phone: 334.502.3262 | 2 - 4 | Source | Weekly | ? |
Maine | ME | ASAP 2009 v4.1 | sFTP | Appriss:855-525-4767 | 2 - 4 | Source | Bi-Weekly | 6 Source |
Michigan | MI | ASAP 2009 v4.1 | Web Portal | Michigan Automated Prescription System (MAPS) Source | 2 - 5 | Source | Bi-Weekly | ? |
Minnesota | MN | ASAP 2007 v4.0 | sFTP | Health Information Design Phone: 334.502.3262 | 2 - 4 + Codeine containing cough syrups that are schedule 5 federally are schedule 3 in MN; Human growth hormones are schedule 3 in MN. | Source | Daily | 1 Source |
Missouri | MO | ASAP 4.2 | ? | ? | ? | ? | ? | 3 Source |
Mississippi | MS | ASAP 2005 v3.0 | sFTP | Appriss:855-525-4767 | 2 - 5 + Butalbital, Carisoprodol, Soma, Tramadol Powder, Ultracet, Ultram ER, Ryzolt ER. | [2] | Weekly | ? |
Montana | MT | ASAP 4.2 | sFTP | Montana Prescription Drug Registry [3] | ? | ? | Weekly | ? |
North Carolina | NC | ASAP 4.2 | sFTP | Health Information Design Phone: 334.502.3262 | 2 - 5 | Source | Weekly | 6 Source |
North Dakota | ND | ASAP 2009 v4.1 | sFTP | Health Information Design Phone: 334.502.3262 | 2 - 5 + Tramadol, Carisoprodol | Source | Daily | ? |
Nebraska | NE | ASAP 4.2 | ? | ? | ? | ? | ? | ? |
New Hampshire | NH | ASAP 4.2 | sFTP | Appriss:855-525-4767 | 2 - 5 + Tramadol, Carisoprodol | nhpdmpreporting.hidinc.com | Daily | ? |
New Jersey | NJ | ASAP 2009 v4.1 | sFTP | Appriss:855-525-4767 | 2 - 5 and HCG | [4] | Weekly | ? |
New Mexico | NM | ASAP 2009 v4.1 | Web Portal | Appriss:855-525-4767 | 2 - 4 + Butalbital (Fioricet), Carisoprodol (Soma), Dezocine (Dalgan), Flunitrazepam (Rohypnol), Nalbuphine (Nubain), Pseudoephedrine (Sudafed) | Source | Weekly | ? |
Nevada | NV | ASAP 2005 v3.0 | sFTP | Appriss:855-525-4767 | 2 - 4 + Carisoprodol | Source | Weekly | ? |
New York | NY | ASAP 2007 v4.0 | Web Portal | New York (DOH & BNDD) Phone: 866.811.7957 | 2 - 5 + Chorionic Gonadotropin, HCG | Source | Daily | 5 Source |
Ohio | OH | ASAP 2009 v4.1 | sFTP | Ohio Automated Rx Reporting System (OARRS) Phone: 614.466.4143 | 2 - 5 + Carisoprodol, Tramadol | Source | Daily | 2 Source |
Oklahoma | OK | ASAP 2019 v4.2b | Web Service | Appriss:855-525-4767 | 2 - 5 + Tramadol | Source | Within 5 Minutes | ? |
Oregon | OR | ASAP 2009 v4.1 | sFTP | Health Information Design Phone: 334.502.3262 | 2 - 4 | ? | Weekly | 3 Source |
Pennsylvania | PA | ASAP 2007 v4.0 | FTPs | Appriss:855-525-4767 | 2 + ephedrine, pseudoephedrine, phenylpropanolamine, PSE | ? | Monthly | ? |
Rhode Island | RI | ASAP 4.2 | Web Portal | Prescription Monitoring Program (PMP) Phone: 401.222.2840 | 2 - 3 | Source | Monthly | ? |
South Carolina | SC | ASAP 4.2 | sFTP | Appriss:855-525-4767 | 2 - 4 | Source | Monthly | ? |
South Dakota | SD | ASAP 2009 v4.1 | sFTP | Appriss:855-525-4767 | 2 - 4 | ? | Weekly | ? |
Tennessee | TN | ASAP 2009 v4.1 | FTPs | Optimum Technology, Inc Phone: 866.683.2476 | 2 - 5 | Source | Bi-Weekly | ? |
Texas | TX | ASAP 2009 v4.1 | FTPs | Appriss:855-525-4767 | 2 - 5 + Carisoprodol | Source | Bi-Weekly | 1 Source |
Utah | UT | ASAP 4.2 | Web Portal | Utah Controlled Substance Database Program Phone: 801.530.6232 | 2 - 5 + butalbital w/acetaminophen | Source | Daily | UCA 58-37f |
Virginia | VA | ASAP 2009 v4.1 | FTPs | Appriss:855-525-4767 | 2 - 4 | Source | Bi-Weekly | ? |
Vermont | VT | ASAP 2005 v3.0 | sFTP | Appriss:855-525-4767 | 2 - 4 | ? | Weekly | 6 Source |
Washington | WA | ASAP 2011 v4.2 | sFTP | Health Information Design Phone: 334.502.3262 | 2 - 5 | Source | Weekly | ? |
Wisconsin | WI | ASAP 2011 v4.2 | ? | ? | 2-5 + Tramadol | ? | ? | ? |
West Virginia | WV | ASAP 4.2 | Web Portal | West Virginia Board of Pharmacy | 2 -4 | Source | ? | ? |
Wyoming | WY | ASAP 4.2 | sFTP | Atlantic Associates, Inc. Phone: 800.539.3370 | 2 - 4 + Tramadol, Carisoprodol | Source | Weekly | ? |
Software systems
NarxCare is a prescription drug monitoring program (PDMP) run by Bamboo Health.[19][20] Bamboo Health was formerly known as Appriss.[19] It is widely used across the United States by pharmacies including Rite Aid as well as those at Walmart and Sam’s Club. The NarxCare software allows doctors to view data about a patient, combining data from the prescription registries of various U.S. states to make the registries interoperable nationally. It also uses machine learning to generate an "Overdose Risk Score" that potentially includes EMS and criminal justice data; these scores have been criticized by researchers and patient advocates for the lack of transparency in the process as well as the potential for disparate treatment of women and minority groups.[20]
Advertised as an "analytics tool and care management platform", the NarxCare software allows doctors to view data about a patient including how many pharmacies they have visited and the combinations of medication they are prescribed.[21] It combines data from the prescription registries of various U.S. states, making the registries interoperable nationally.[22][23] It additionally uses machine learning to generate various three-digit "risk scores" and an overall "Overdose Risk Score", collectively referred to as Narx Scores,[24] in a process that potentially includes EMS and criminal justice data[21] as well as court records.[25]
Controversy
Many doctors and researchers support the idea of PDMPs as a tool in combatting the opioid epidemic. Opioid prescribing, opioid diversion and supply, opioid misuse, and opioid-related morbidity and mortality are common elements in data entered into PDMPs.[9] Prescription Monitoring Programs are purported to offer economic benefits for the states who implement them by decreasing overall health care costs, lost productivity, and investigation times.[11]
However, there are many studies that conclude the impact of PDMPs is unclear.[9] While use of PMPs has been accompanied by decrease in opioid prescribing, few analyses consider corresponding use of street opioids, extramedical use, or diversion, which might provide a more holistic method for evaluation of PMP intent and efficacy. Evidence for PDMP impact on fatal overdoses is decidedly mixed, with multiple studies finding increased overdose rates in some states, decreases in others, or no clear impact.[5][6] Interestingly, an increase in heroin overdoses after PDMP implementation has been commonly reported, presumably as denial of prescription opioids sends patients in search of street drugs.[26]
Narx Scores have been criticized by researchers and patient advocates for the lack of transparency in the generation process as well as the potential for disparate treatment of women and minority groups.[21] Writing in Duke Law Journal, Jennifer Oliva stated that "black-box algorithms" are used to generate the scores.[24]
References
- ^ a b Islam, M Mofizul; McRae, Ian S (2014). "An inevitable wave of prescription drug monitoring programs in the context of prescription opioids: pros, cons and tensions". BMC Pharmacol Toxicol. 15 (46): 46. doi:10.1186/2050-6511-15-46. PMC 4138942. PMID 25127880.
- ^ Sacco, Lisa N.; Duff, Johnathan H.; Sarata, Amanda K. (May 24, 2018). Prescription Drug Monitoring Programs (PDF). Washington, DC: Congressional Research Service. Retrieved 5 June 2018.
- ^ a b Substance Use and Mental Health Services Administration (2017). "Prescription Drug Monitoring Programs: A Guide For Health Professionals" (PDF). SAMSHA in Brief. 10 (1): 2.
- ^ Rutkow, Lainie; Smith, Katherine C.; Lai, Alden Yuanhong; Vernick, Jon S.; Davis, Corey S.; Alexander, G. Caleb (2017). "Prescription drug monitoring program design and function: A qualitative analysis". Drug and Alcohol Dependence. 180: 395–400. doi:10.1016/j.drugalcdep.2017.08.040. PMID 28978492.
- ^ a b Ponnapalli, Aditya; Grando, Adela; Murcko, Anita; Wertheim, Pete (2018-12-05). "Systematic Literature Review of Prescription Drug Monitoring Programs". AMIA Annual Symposium Proceedings. 2018: 1478–1487. ISSN 1942-597X. PMC 6371270. PMID 30815193.
- ^ a b c d Martins, Silvia S.; Ponicki, William; Smith, Nathan; Rivera-Aguirre, Ariadne; Davis, Corey S.; Fink, David S.; Castillo-Carniglia, Alvaro; Henry, Stephen G.; Marshall, Brandon D. L.; Gruenewald, Paul; Cerdá, Magdalena (December 2019). "Prescription drug monitoring programs operational characteristics and fatal heroin poisoning". The International Journal on Drug Policy. 74: 174–180. doi:10.1016/j.drugpo.2019.10.001. ISSN 1873-4758. PMC 6897357. PMID 31627159.
- ^ Department of Health. (n.d.). Retrieved from https://www.health.ny.gov/community/opioid_epidemic
- ^ Baehren, David F.; Marco, Catherine A.; Droz, Danna E.; Sinha, Sameer; Callan, E. Megan; Akpunonu, Peter (July 2010). "A statewide prescription monitoring program affects emergency department prescribing behaviors". Annals of Emergency Medicine. 56 (1): 19–23.e1–3. doi:10.1016/j.annemergmed.2009.12.011. ISSN 1097-6760. PMID 20045578.
- ^ a b c Finley, Erin P.; Garcia, Ashley; Rosen, Kristen; McGeary, Don; Pugh, Mary Jo; Potter, Jennifer Sharpe (20 June 2017). "Evaluating the impact of prescription drug monitoring program implementation: a scoping review". BMC Health Services Research. 17 (1): 420. doi:10.1186/s12913-017-2354-5. PMC 5477729. PMID 28633638.
- ^ Whalen v. Roe, 429 U.S. 589 (1977). This article incorporates public domain material from this U.S government document.
- ^ a b Briefing on PDMP Effectiveness. (2014). In Prescription Drug Monitoring Program Center of Excellence At Brandeis (p. 13). Brandeis University .
- ^ Thielking, M., Ross, C., Branswell, H., Hogan, A., & Associated Press. (2017, March 7). Missouri is the only state not tracking prescription drug use. Here’s why. Retrieved January 24, 2019, from https://www.statnews.com/2017/03/07/missouri-prescription-drug-database/
- ^ "Governor Parson Signs SB 63: Creating Statewide Prescription Drug Monitoring Program in Missouri | Governor Michael L. Parson". governor.mo.gov. Retrieved 2022-01-20.
- ^ "Integrating & Expanding Prescription Drug Monitoring Program Data: Lessons from Nine States" (PDF). National Center for Injury Prevention and Control. February 2017.
- ^ a b Szalavitz, Maia. "A Drug Addiction Risk Algorithm and Its Grim Toll on Chronic Pain Sufferers". Wired. ISSN 1059-1028. Retrieved 2022-01-20.
- ^ Wang, Lucy Xiaolu (27 May 2021). "The complementarity of drug monitoring programs and health IT for reducing opioid-related mortality and morbidity". Health Economics. 30 (9): 2026–2046. doi:10.1002/hec.4360. PMID 34046967. S2CID 235233087.
- ^ Hwang, Catherine S.; Turner, Lydia W.; Kruszewski, Stefan P.; Kolodny, Andrew; Alexander, G. Caleb (2016). "Primary Care Physicians' Knowledge And Attitudes Regarding Prescription Opioid Abuse and Diversion". The Clinical Journal of Pain. 32 (4): 279–284. doi:10.1097/ajp.0000000000000268. PMID 26102320. S2CID 6019620.
- ^ Pharmacist's Manual. (n.d.). Retrieved from https://www.deadiversion.usdoj.gov/pubs/manuals/pharm2/pharm_content.htm Archived 2019-10-17 at the Wayback Machine
- ^ a b Siegel, Zachary (June 2022). "In a World of Stigma and Bias, Can a Computer Algorithm Really Predict Overdose Risk?". Annals of Emergency Medicine. 79 (6): A16–A19. doi:10.1016/j.annemergmed.2022.04.006. S2CID 248789032.
- ^ a b Beaulieu et al. 2021, p. 5.
- ^ a b c Szalavitz 2021, p. 41.
- ^ Szalavitz 2021, p. 40.
- ^ Romo, Vanessa (2018-05-08). "Walmart Will Implement New Opioid Prescription Limits By End Of Summer". NPR. Retrieved 2021-10-06.
- ^ a b Oliva 2020, p. 847.
- ^ Oliva 2020, p. 848.
- ^ Fink, David S.; Schleimer, Julia P.; Sarvet, Aaron; Grover, Kiran K.; Delcher, Chris; Castillo-Carniglia, Alvaro; Kim, June H.; Rivera-Aguirre, Ariadne E.; Henry, Stephen G.; Martins, Silvia S.; Cerdá, Magdalena (8 May 2018). "Association Between Prescription Drug Monitoring Programs and Nonfatal and Fatal Drug Overdoses". Annals of Internal Medicine. 168 (11): 783–790. doi:10.7326/M17-3074. PMC 6015770. PMID 29801093.
Further reading
- Moyo, Patience; Simoni-Wastila, Linda; Griffin, Beth Ann; Onukwugha, Eberechukwu; Harrington, Donna; Alexander, G. Caleb; Palumbo, Francis (October 2017). "Impact of prescription drug monitoring programs (PDMPs) on opioid utilization among Medicare beneficiaries in 10 US States". Addiction. 112 (10): 1784–1796. doi:10.1111/add.13860. PMID 28498498. S2CID 2699009.
- Beaulieu, Tara; Knight, Rod; Nolan, Seonaid; Quick, Oliver; Ti, Lianping (2021-01-02). "Artificial intelligence interventions focused on opioid use disorders: A review of the gray literature". The American Journal of Drug and Alcohol Abuse. 47 (1): 26–42. doi:10.1080/00952990.2020.1817466. ISSN 0095-2990. PMID 33006905. S2CID 222159315.
- Szalavitz, Maia (October 2021). "The Pain Algorithm". WIRED. pp. 36–47. ISSN 1059-1028.
- Oliva, Jennifer (2020-01-08). "Prescription-Drug Policing: The Right To Health Information Privacy Pre- and Post-Carpenter". Duke Law Journal. 69 (4): 775–853. ISSN 0012-7086.