Calculating maximum morphine equivalent daily dose from prescription directions for use in the electronic health record: a case report.
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ABSTRACT:
SUBMITTER: Goud A
PROVIDER: S-EPMC6824516 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveTo describe current state-level policies in the United States, January 1, 2007-June 1, 2017, limiting high morphine equivalent daily dose (MEDD) prescribing.MethodsState-level MEDD threshold policies were reviewed using LexisNexis and Westlaw Next for legislative acts and using Google for nonlegislative state-level policies. The websites of each state's Medicaid agency, health department, prescription drug monitoring program, workers' compensation board, medical board, and pharmacy board were reviewed to identify additional policies. The final policy list was checked against existing policy compilations and academic literature and through contact with state health agency representatives. Policies were independently double-coded on the categories: state, agency/organization, policy type, effective date, threshold level, and policy exceptions.ResultsCurrently, 22 states have at least one type of MEDD policy, most commonly guidelines (14 states), followed by prior authorizations (four states), rules/regulations (four states), legislative acts (three states), claim denials (two states), and alert systems/automatic patient reports (two states). Thresholds range widely (30-300 mg MEDD), with higher thresholds generally corresponding to more restrictive policies (e.g., claim denial) and lower thresholds corresponding to less restrictive policies (e.g., guidelines). The majority of policies exclude some groups of opioid users, most commonly patients with terminal illnesses or acute pain.ConclusionsMEDD policies have gained popularity in recent years, but considerable variation in threshold levels and policy structure point to a lack of consensus. This work provides a foundation for future evaluation of MEDD policies and may inform states considering adopting such policies.
| S-EPMC8607298 | biostudies-literature
Project description:BackgroundPrescription opioid mortality doubled 2002-2016 in the United States. Given the association between high-dose opioid prescribing and opioid mortality, several states have enacted morphine equivalent daily dose (MEDD) policies to limit high-dose prescribing. The study objective is to evaluate the impact of state-level MEDD policies on opioid prescribing among the privately insured.MethodsClaims data, 2010-2015 from 9 policy states and 2 control states and a comparative interrupted time series design were utilized. Primary outcomes were any monthly opioid use and average monthly MEDD. Stratified analyses evaluated theorized weaker policies (guidelines) and theorized stronger policies (passive alert systems, legislative acts, and rules/regulations) separately. Patient groups explicitly excluded from policies (eg, individuals with cancer diagnoses or receiving hospice care) were also examined separately. Analyses adjusted for covariates, state fixed effects, and time trends.ResultsBoth guideline and strong policy implementation were both associated with 15% lower odds of any opioid use, relative to control states. However, there was no statistically significant change in the use of high-dose opioids in policy states relative to control states. There was also no difference in direction and significance of the relationship among targeted patient groups.ConclusionsMEDD policies were associated with decreased use of any opioids relative to control states, but no change in high-dose prescribing was observed. While the overall policy environment in treatment states may have discouraged opioid prescribing, there was no evidence of MEDD policy impact, specifically. Further research is needed to understand the mechanisms through which MEDD policies may influence prescribing behavior.
| S-EPMC8384656 | biostudies-literature
Project description:Morphine is the opioid most commonly used for neonatal pain management. In intravenous form, it is administered as continuous infusions and intermittent injections, mostly based on empirically established protocols. Inadequate pain control in neonates can cause long-term adverse consequences; however, providing appropriate individualized morphine dosing is particularly challenging due to the interplay of rapid natural physiological changes and multiple life-sustaining procedures in patients who cannot describe their symptoms. At most institutions, morphine dosing in neonates is largely carried out as an iterative process using a wide range of starting doses and then titrating to effect based on clinical response and side effects using pain scores and levels of sedation. Our background data show that neonates exhibit large variability in morphine clearance resulting in a wide range of exposures, which are poorly predicted by dose alone. Here, we describe the development and implementation of an electronic health record-integrated, model-informed decision support platform for the precision dosing of morphine in the management of neonatal pain. The platform supports pharmacokinetic model-informed dosing guidance and has functionality to incorporate real-time drug concentration information. The feedback is inserted directly into prescribers' workflows so that they can make data-informed decisions. The expected outcomes are better clinical efficacy and safety with fewer side effects in the neonatal population.
| S-EPMC7378965 | biostudies-literature
Project description:OBJECTIVE:Phenotyping patients using electronic health record (EHR) data conventionally requires labeled cases and controls. Assigning labels requires manual medical chart review and therefore is labor intensive. For some phenotypes, identifying gold-standard controls is prohibitive. We developed an accurate EHR phenotyping approach that does not require labeled controls. MATERIALS AND METHODS:Our framework relies on a random subset of cases, which can be specified using an anchor variable that has excellent positive predictive value and sensitivity independent of predictors. We proposed a maximum likelihood approach that efficiently leverages data from the specified cases and unlabeled patients to develop logistic regression phenotyping models, and compare model performance with existing algorithms. RESULTS:Our method outperformed the existing algorithms on predictive accuracy in Monte Carlo simulation studies, application to identify hypertension patients with hypokalemia requiring oral supplementation using a simulated anchor, and application to identify primary aldosteronism patients using real-world cases and anchor variables. Our method additionally generated consistent estimates of 2 important parameters, phenotype prevalence and the proportion of true cases that are labeled. DISCUSSION:Upon identification of an anchor variable that is scalable and transferable to different practices, our approach should facilitate development of scalable, transferable, and practice-specific phenotyping models. CONCLUSIONS:Our proposed approach enables accurate semiautomated EHR phenotyping with minimal manual labeling and therefore should greatly facilitate EHR clinical decision support and research.
| S-EPMC6913222 | biostudies-literature
Project description:AimsTo estimate prevalence of excess intake of paracetamol and investigate seasonal variations therein.MethodsBetween 2011 and 2016, 14?481 US adults who used paracetamol in the preceding 30 days were sampled from national online panels and completed a detailed online daily diary of paracetamol medication use for 7 days. Respondents were not told that the study concerned paracetamol. Cold/flu season (CFS), identified using Google Trends data, was contrasted to off-season in symptoms, use of paracetamol medications, and consumption exceeding 4 g (the recommended daily maximum).ResultsOverall, 6.3% [95% confidence interval: 5.9-6.7%] of users exceeded 4 g on at least one day; 3.7% [3.5-3.8%] of usage days exceeded 4 g. Cold/flu symptoms were more likely to be experienced and treated with paracetamol in CFS than off-season. Paracetamol users were more likely to exceed 4 g during CFS (6.5% vs. 5.3%; odds ratio = 1.24, 1.04-1.48); days exceeding 4 g also increased (3.9% vs. 2.8%; odds ratio = 1.37, 1.11-1.69). This was not due to differences in characteristics of individuals using paracetamol in CFS, but primarily to increased use of over-the-counter combination medications designed to treat upper respiratory cold/flu symptoms (33.2% of usage days in CFS vs. 24.8% in off-season; odds ratio = 1.58, 1.46-1.72). When such medications were omitted, there was no statistically significant seasonal variation in exceeding 4 g.ConclusionsParacetamol use and over-dosing increases in CFS, primarily due to increased use of over-the-counter combinations treating upper respiratory cold/flu symptoms. Pharmacists should warn users to follow labelled dosing directions, especially during CFS.
| S-EPMC5980528 | biostudies-literature
Project description:Background Only 50% of eligible atrial fibrillation ( AF ) patients receive anticoagulation ( AC ). Feasibility and effectiveness of electronic medical record (EMR)-based interventions to profile and raise provider AC percentage is poorly understood. The SUPPORT-AF (Supporting Use of AC Through Provider Profiling of Oral AC Therapy for AF) study aims to improve rates of adherence to AC guidelines by developing and delivering supportive tools based on the EMR to providers treating patients with AF. Methods and Results We emailed cardiologists and community-based primary care providers affiliated with our institution reports of their AC percentage relative to peers. We also sent an electronic medical record-based message to these providers the day before an appointment with an atrial fibrillation patient who was eligible but not receiving AC . The electronic medical record message asked the provider to discuss AC with the patient if he or she deemed it appropriate. To assess feasibility, we tracked provider review of our correspondence. We also tracked the change in AC for intervention providers relative to alternate primary care providers not receiving our intervention. We identified 3786, 1054, and 566 patients cared for by 49 cardiology providers, 90 community-based primary care providers, and 88 control providers, respectively. At baseline, the percentage of AC was 71.3%, 63.5%, and 58.3% for these 3 respective groups. Intervention providers reviewed our e-mails and electronic medical record messages 45% and 96% of the time, respectively. For providers responding, patient refusal was the most common reason for patients not being on AC (21%) followed by high bleeding risk (19%). At follow-up 10 weeks later, change in AC was no different for either cardiology or community-based primary care providers relative to controls (0.2% lower and 0.01% higher, respectively). Conclusions Our intervention profiling AC was feasible, but not sufficient to increase AC in our population.
| S-EPMC6201433 | biostudies-literature
Project description:Canine acute diarrhoea is frequently observed in first opinion practice, though little is known about commonly used diagnostic or therapeutic management plans, including use of antimicrobials. This retrospective observational study utilised electronic health records augmented with practitioner-completed questionnaires from 3,189 cases (3,159 dogs) collected from 179 volunteer veterinary practices between April 2014 and January 2017. We used multivariable analysis to explore factors potentially associated with pharmaceutical agent prescription, and resolution of clinical signs by 10 days post-initial presentation. Use of bacteriological and/or parasitological diagnostic tests were uncommon (3.2% of cases, 95% confidence interval, CI, 2.4-4.0), though systemic antimicrobials were the most commonly prescribed pharmaceutical agents (49.7% of cases, 95% CI 46.1-53.2). Such prescription was associated with haemorrhagic diarrhoea (odds ratio, OR, 4.1; 95% CI 3.4-5.0), body temperature in excess of 39.0°C, or moderate/severe cases (OR 1.3, 95% CI 1.1-1.7). Gastrointestinal agents (e.g., antacids) were prescribed to 37.7% of cases (95% CI 35.4-39.9), and were most frequently prescribed to vomiting dogs regardless of presence (OR 46.4, 95% CI 19.4-110.8) or absence of blood (OR 17.1, 95% CI 13.4-21.9). Endoparasiticides/endectocides were prescribed to 7.8% of cases (95% CI 6.8-9.0), such prescription being less frequent for moderate/severe cases (OR 0.5, 95% CI 0.4-0.7), though more frequent when weight loss was recorded (OR 3.4, 95% CI 1.3-9.0). Gastrointestinal nutraceuticals (e.g., probiotics) were dispensed to 60.8% of cases (95% CI 57.1-64.6), these cases less frequently presenting with moderate/severe clinical signs (OR 0.6, 95% CI 0.5-0.8). Nearly a quarter of cases were judged lost to follow-up (n=754). Insured (OR 0.7, 95% CI 0.5-0.9); neutered (OR 0.4, 95% CI 0.3-0.5), or vaccinated dogs (OR 0.3, 95% CI 0.3-0.4) were less commonly lost to follow-up. Of remaining dogs, clinical signs were deemed resolved in 95.4% of cases (95% CI 94.6-96.2). Provision of dietary modification advice and gastrointestinal nutraceuticals alone were positively associated with resolution (OR 2.8, 95% CI 1.3-6.1); no such associations were found for pharmaceutical agents, including antimicrobials. Hence, this study supports the view that antimicrobials are largely unnecessary for acute diarrhoea cases; this being of particular importance when considering the global threat posed by antimicrobial resistance.
| S-EPMC6615257 | biostudies-literature
Project description:Background and study aims
The Federal Ministry of Education and Research (BMBF) has funded the development of a patient controlled “Personal Electronic Health Record” (PEPA) as part of their current INFOPAT project. PEPA allows for the exchange of medical data between all interested groups, including the patients thenselves. A PEPA contains medical reports and findings including, for example, x-rays, CT scans and MRIs. The patients can safeguard their information and access all content. The aim of this study is to test the PEPA-prototype for cancer patients being treated at the National Center for Tumor Diseases (NCT) in Heidelberg.
Who can participate?
Adult colorectal cancer patients being treated at the National Center for Tumor Diseases (NCT) in Heidelberg.
What does the study involve?
There are two part to this study. The first part involves focus groups, in which a group of people are asked their opinion and attitudes towards, for example, an idea, product or service. Here, focus groups are set up that involve the patients, doctors and other health professionals to discuss current problems with the coordination of care offered to cancer patients, as well as discuss what people want to get from using PEPA (i.e. user requirements). The PEPA-prototype is then developed taking into account the conclusions from the focus groups. In the second part of the study, patients are encouraged to use the PEPA-prototype to prepare and follow up meetings with their physicians.
| 2424890 | ecrin-mdr-crc
Project description:BackgroundMedication-wide association studies (MWAS) have been applied to assess the risk of individual prescription use and a wide range of health outcomes, including cancer, acute myocardial infarction, acute liver failure, acute renal failure, and upper gastrointestinal ulcers. Current literature on the use of preconception and periconception medication and its association with the risk of multiple gestation pregnancies (eg, monozygotic and dizygotic) is largely based on assisted reproductive technology (ART) cohorts. However, among non-ART pregnancies, it is unknown whether other medications increase the risk of multifetal pregnancies.ObjectiveThis study aimed to investigate the risk of multiple gestational births (eg, twins and triplets) following preconception and periconception exposure to prescription medications in patients who delivered at Penn Medicine.MethodsWe used electronic health record data between 2010 and 2017 on patients who delivered babies at Penn Medicine, a health care system in the Greater Philadelphia area. We explored 3 logistic regression models: model 1 (no adjustment); model 2 (adjustment for maternal age); and model 3-our final logistic regression model (adjustment for maternal age, ART use, and infertility diagnosis). In all models, multiple births (MBs) were our outcome of interest (binary outcome), and each medication was assessed separately as a binary variable. To assess our MWAS model performance, we defined ART medications as our gold standard, given that these medications are known to increase the risk of MB.ResultsOf the 63,334 distinct deliveries in our cohort, only 1877 pregnancies (2.96%) were prescribed any medication during the preconception and first trimester period. Of the 123 medications prescribed, we found 26 (21.1%) medications associated with MB (using nominal P values) and 10 (8.1%) medications associated with MB (using Bonferroni adjustment) in fully adjusted model 3. We found that our model 3 algorithm had an accuracy of 85% (using nominal P values) and 89% (using Bonferroni-adjusted P values).ConclusionsOur work demonstrates the opportunities in applying the MWAS approach with electronic health record data to explore associations between preconception and periconception medication exposure and the risk of MB while identifying novel candidate medications for further study. Overall, we found 3 novel medications linked with MB that could be explored in further work; this demonstrates the potential of our method to be used for hypothesis generation.
| S-EPMC9214620 | biostudies-literature
Project description:Background and Purpose: Non-motor symptoms of Parkinson disease (PD) have a strong negative impact on the health-related quality of life (QoL) of patients with PD. Sleep disturbance is an important non-motor symptom because of its high prevalence. However, previous studies investigating the determinants of sleep quality in patients with PD have revealed inconsistent results. Our study evaluated the correlations between sleep quality in patients with PD and disease-related variables, medications used depression, anxiety, and QoL and identified the determinants of sleep disturbance in people with PD in Taiwan. Methods: A total of 134 patients with PD were recruited from the outpatient clinic. We examined the correlations between the Parkinson disease sleep scale-2 (PDSS-2) scores and different variables, namely the Unified Parkinson Disease Rating Scale, Parkinson disease questionnaire, Beck Depression Inventory, and Beck Anxiety Inventory (BAI). Logistic regression analysis was used to assess the potential predictive variables for sleep quality in patients with PD. Results: Among our participants, 47.8% were classified as poor sleepers (PDSS-2 = 15-60). Correlation analysis demonstrated that poor sleepers exhibited longer disease durations, higher levodopa equivalent daily doses (LEDDs), higher PD severity, more depression and anxiety symptoms, poorer QoL, more frequent unemployed status, higher hypnotics use, higher dependency for activities of daily living, more motor impairments, and more therapy-related complications. Logistic regression revealed that the LEDD was a significant predictive factor of sleep quality. Conclusion: Poor sleepers constituted approximately half of our patients with PD. The participants experienced more favorable sleep if they were currently working. Increased PD duration, severity, depression or anxiety symptoms, and doses of dopaminergic therapy were significantly associated with poor sleep quality. Continued working, attempts to treat comorbid anxiety or depression, and avoidance of overdosage of dopaminergic treatments may improve sleep quality in patients with PD.
| S-EPMC6476952 | biostudies-literature