Analysis of Access to Prescription Data Management Programs Data for Research.
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ABSTRACT:
SUBMITTER: Lee VA
PROVIDER: S-EPMC9218843 | biostudies-literature | 2022 Jun
REPOSITORIES: biostudies-literature
Publications
Analysis of Access to Prescription Data Management Programs Data for Research.
Lee Vivian A VA Compton Wilson M WM Pollock Jonathan D JD
JAMA network open 20220601 6
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Project description:Building on achievements and experience gained through the EU project DAMOCLES and international data management during the International Polar Year, ACCESS, data management was implemented using the same platform as used for DAMOCLES. A metadata-driven approach through which all datasets are properly described with discovery and use metadata was chosen in order to simplify data management and data usage. The system provides automated submission and checking of datasets, search and download as well as visualisation and transformation on user demand and metadata export. Long-term management of ACCESS climate datasets is done within the context of the Arctic Data Centre. This ensures visibility of ACCESS datasets in the context of WMO and GEOSS catalogues. Challenges with ACCESS data management have mainly been cultural with the consequence that the system has been underutilised within the duration of the project duration.
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Project description:To address the opioid epidemic, some states mandate that prescribers review a state-run prescription drug monitoring program (PDMP) database before prescribing opioids. We used Medicare Part D prescriber data from 2013 (baseline) to 2019 to examine the association between state mandatory-access PDMPs, with and without a cancer exemption, and changes in the percent of oncologists' patients with any opioid fill per year, stratified by oncologists' baseline prescribing volume. Among 9746 medical or hematologic oncologists, the proportion of patients prescribed opioids declined after states implemented mandatory-access PDMPs without a cancer exemption overall (-0.49 percentage point, 95% confidence interval = -0.78 to -0.20 percentage point) and among those with above-median baseline prescribing, but not in states with a cancer exemption (-0.16 percentage point, 95% confidence interval = -0.50 to 0.18 percentage point) or with below-median baseline prescribing. Carefully designed mandatory-access PDMPs with cancer exemptions minimize unnecessary reductions in prescription opioid treatments among oncology patients in need of pain management.
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Project description:One of the most common terms that is used to describe entities responsible for sharing genomic data for research purposes is 'genomic research consortium'. However, there is a lack of clarity around the language used by consortia to describe their data sharing arrangements. Calls have been made for more uniform terminology. This article reports on a review of the genomic research consortium literature illustrating a wide diversity in the language that has been used over time to describe the access arrangements of these entities. The second component of this research involved an examination of publicly available information from a dataset of 98 consortia. This analysis further illustrates the wide diversity in the access arrangements adopted by genomic research consortia. A total of 12 different access arrangements were identified, including four simple forms (open, consortium, managed and registered access) and eight more complex tiered forms (for example, a combination of consortium, managed and open access). The majority of consortia utilised some form of tiered access, often following the policy requirements of funders like the US National Institutes of Health and the UK Wellcome Trust. It was not always easy to precisely identify the access arrangements of individual consortia. Greater consistency, clarity and transparency is likely to be of benefit to donors, depositors and accessors alike. More work needs to be done to achieve this end.
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Project description:Background: Having low-income limits one's ability to purchase foods that are high in nutritional value (e.g. vegetables and fruits (V/F)). Higher V/F intake is associated with less diet-related chronic disease. Food pharmacy programs are potential solutions to providing V/F to low-income populations with or at-risk for chronic disease. Aim: This systematic review aimed to determine the effect of food pharmacy programs, including interventions targeting populations at-risk for chronic disease. Methods: We searched Pubmed and Google Scholar databases for studies reporting on food pharmacy interventions and outcomes (hemoglobin A1c, body mass index (BMI), V/F intake, and blood pressure). We calculated pooled mean differences using a random-effects model. Seventeen studies met our inclusion criteria; 13 studies used a pre/post study design, three used a randomized controlled trial, and one was a post-survey only. Results: We found that the pooled mean daily servings of V/F (0.77; 95% CI: 0.30 to 1.24) was higher and BMI (-0.40; 95% CI: -0.50 to -0.31) was lower with food pharmacy interventions We did not find any differences in the pooled mean differences for hemoglobin A1c or systolic blood pressure. Conclusion: Findings posit that food pharmacy programs delivered to primarily low-income individuals with comorbidities may be a promising solution to improving V/F intake and possibly overall diet in these populations.
| S-EPMC10150796 | biostudies-literature
Project description:ObjectiveTo develop a legal research protocol for identifying various measures of prescription drug monitoring program (PDMP) start dates, apply the protocol to create a useable PDMP database, and test whether the different legal databases that are meant to contain the same information produce divergent results when used in an illustrative empirical exercise.Data sourcesOriginal research from state statutes, regulations, policy statements, and interviews; alternative PDMP data from the National Alliance for Model State Drug Laws and Prescription Drug Abuse Policy System; claims from a 40 percent random sample of Medicare beneficiaries, 2006-2014.Study designCollaborative research effort among a group of lawyers to develop protocol. Legal research to produce an original database of dates state PDMP laws: (a) were enacted, (b) became operational, and (c) required query before prescribing controlled substances. Descriptive analyses characterize differences in dates of enactment, operation, and must query requirements. Regression analyses estimating, for each beneficiary annually any opioid prescription received in a calendar year, among other measures. Estimates conducted on under age 65 and full Medicare population.Data collection/extraction methodsPDMP legal databases were linked to annual Medicare claims.Principal findingsAn original database differs from commonly used, publicly available data. Outcomes tested depend on the measure of PDMP date used and differ by data source. Must-query laws show the largest effects among all the laws tested.ConclusionsData choices likely have had large consequences for study results and may explain contradictory outcomes in prior research. Researchers must understand and report protocol for dates used in PDMP research to ensure that results are internally consistent and verifiable.
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Project description:BACKGROUND:Translational researchers need robust IT solutions to access a range of data types, varying from public data sets to pseudonymised patient information with restricted access, provided on a case by case basis. The reason for this complication is that managing access policies to sensitive human data must consider issues of data confidentiality, identifiability, extent of consent, and data usage agreements. All these ethical, social and legal aspects must be incorporated into a differential management of restricted access to sensitive data. METHODS:In this paper we present a pilot system that uses several common open source software components in a novel combination to coordinate access to heterogeneous biomedical data repositories containing open data (open access) as well as sensitive data (restricted access) in the domain of biobanking and biosample research. Our approach is based on a digital identity federation and software to manage resource access entitlements. RESULTS:Open source software components were assembled and configured in such a way that they allow for different ways of restricted access according to the protection needs of the data. We have tested the resulting pilot infrastructure and assessed its performance, feasibility and reproducibility. CONCLUSIONS:Common open source software components are sufficient to allow for the creation of a secure system for differential access to sensitive data. The implementation of this system is exemplary for researchers facing similar requirements for restricted access data. Here we report experience and lessons learnt of our pilot implementation, which may be useful for similar use cases. Furthermore, we discuss possible extensions for more complex scenarios.
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Project description:The 1000 Genomes Project was launched as one of the largest distributed data collection and analysis projects ever undertaken in biology. In addition to the primary scientific goals of creating both a deep catalog of human genetic variation and extensive methods to accurately discover and characterize variation using new sequencing technologies, the project makes all of its data publicly available. Members of the project data coordination center have developed and deployed several tools to enable widespread data access.
| S-EPMC3340611 | biostudies-literature
Project description:BackgroundWhile the mandate to check patients' prescription history in Prescription Drug Monitoring Program (PDMP) database before prescribing/dispensing controlled drugs has been shown to be an important tool to curb opioid abuse, less is known about whether the mandate can reduce the misuse of other commonly abused prescription drugs. We examined whether PDMP use mandates were associated with changes in prescription stimulant and depressant quantities.MethodsUsing data from Automated Reports and Consolidate Ordering System (ARCOS), we employed difference-in-differences design to estimate the association between PDMP use mandates and prescription stimulant and depressant quantities in 50 U.S. states and the District of Columbia from 2006 to 2020. Limited PDMP use mandate was specific only to opioids or benzodiazepines. Expansive PDMP use mandate was non-specific to opioid or benzodiazepine and required prescribers/dispensers to check PDMP when prescribing/dispensing targeted controlled substances in Schedule II-V. The main outcomes were population-adjusted prescription stimulant (amphetamine, methylphenidate, lisdexamfetamine) and depressant (amobarbital, butalbital, pentobarbital, secobarbital) quantities in grams.ResultsThere was no evidence that limited PDMP use mandate was associated with a reduction in the prescription stimulant and depressant quantities. However, expansive PDMP use mandate that was non-specific to opioid or benzodiazepine and required prescribers/dispensers to check PDMP when prescribing/dispensing targeted controlled substances in Schedule II-V was associated with 6.2% (95% CI: -10.06%, -2.08%) decline in prescription amphetamine quantity.ConclusionExpansive PDMP use mandate was associated with a decline in prescription amphetamine quantity. Limited PDMP use mandate did not appear to change prescription stimulant and depressant quantities.
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Project description: Not available
| S-EPMC4465450 | biostudies-literature
Project description:Prescription drug monitoring programs (PDMPs) are a crucial component of federal and state governments' response to the opioid epidemic. Evidence about the effectiveness of PDMPs in reducing prescription opioid-related adverse outcomes is mixed. We conducted a systematic review to examine whether PDMP implementation within the United States is associated with changes in 4 prescription opioid-related outcome domains: opioid prescribing behaviors, opioid diversion and supply, opioid-related morbidity and substance-use disorders, and opioid-related deaths. We searched for eligible publications in Embase, Google Scholar, MEDLINE, and Web of Science. A total of 29 studies, published between 2009 and 2019, met the inclusion criteria. Of the 16 studies examining PDMPs and prescribing behaviors, 11 found that implementing PDMPs reduced prescribing behaviors. All 3 studies on opioid diversion and supply reported reductions in the examined outcomes. In the opioid-related morbidity and substance-use disorders domain, 7 of 8 studies found associations with prescription opioid-related outcomes. Four of 8 studies in the opioid-related deaths domain reported reduced mortality rates. Despite the mixed findings, emerging evidence supports that the implementation of state PDMPs reduces opioid prescriptions, opioid diversion and supply, and opioid-related morbidity and substance-use disorder outcomes. When PDMP characteristics were examined, mandatory access provisions were associated with reductions in prescribing behaviors, diversion outcomes, hospital admissions, substance-use disorders, and mortality rates. Inconsistencies in the evidence base across outcome domains are due to analytical approaches across studies and, to some extent, heterogeneities in PDMP policies implemented across states and over time.
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