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Traditional Chinese medicine (TCM) prescriptions have always relied on the experience of TCM doctors, and machine learning(ML) provides a technical means for learning these experiences and intelligently assists in prescribing. However, in TCM prescription, there are the main (Jun) herb and the auxiliary (Chen, Zuo and Shi) herb collocations. In a prescription, the types of auxiliary herbs are often more than the main herb and the auxiliary herbs often appear in other prescriptions. This leads to different frequencies of different herbs in prescriptions, namely, imbalanced labels (herbs). As a result, the existing ML algorithms are biased, and it is difficult to predict the main herb with less frequency in the actual prediction and poor performance. In order to solve the impact of this problem, this paper proposes a framework for multi-label traditional Chinese medicine (ML-TCM) based on multi-label resampling.

In this work, a multi-label learning framework is proposed that adopts and compares the multi-label random resampling (MLROS), multi-label synthesized resampling (MLSMOTE) and multi-label synthesized resampling based on local label imbalance (MLSOL), three multi-label oversampling techniques to rebalance the TCM data.

The experimental results show that after resampling, the less frequent but important herbs can be predicted more accurately. The MLSOL method is shown to be the best with over 10% improvements on average because it balances the data by considering both features and labels when resampling.

The authors first systematically analyzed the label imbalance problem of different sampling methods in the field of TCM and provide a solution. And through the experimental results analysis, the authors proved the feasibility of this method, which can improve the performance by 10%−30% compared with the state-of-the-art methods.

This study examined how youth would mitigate non-medical use of prescription medication among their peers.

The National Monitoring of Adolescent Prescription Stimulants Study (N-MAPSS) was conducted as an interview comprising 11,048 youth of 10–18 years of age between 2008 and 2011 from entertainment venues of 10 US urban, suburban, and rural areas. Using a mixed-methods approach, participants completed a survey culminating in open-ended questions asking: (1) How should kids your age be informed about prescription drugs and their effects? (2) If you ran the world, how would you stop kids from taking other people’s prescription medicines? (3) Why do people use prescription stimulants without a prescription? Responses from a random sample of 900 children were analyzed using qualitative thematic analyses.

The random sample of 900 youth (52 percent female, 40 percent white, with a mean age of 15.1 years) believed they should be educated about prescription drugs and their negative effects at schools, at home by parents, through the media, and health professionals. Youth would stop kids from using other people’s prescription drugs through more stringent laws that restricted use, and providing education about negative consequences of use. Peer pressure was the most common reason the youth gave for using other’s pills, though some reported taking them out of curiosity.

The importance of considering youth’s opinions on non-medical use of prescription medications is often overlooked. This evidence, from a peer perspective, could end the illicit use of prescription drugs among today’s youth.

In 2017, the opioid epidemic was declared a public health emergency in the United States. The federal and state governments are still struggling to contain the crisis through various legislations and to stem the tide of overdoses and deaths. This paper looks specifically at the issue of high prescriptions of opioids disbursed to patients by physicians.

This paper evaluates this evolving policy issue through a critical review and synthesis of academic literature, government policy documents (at states and national levels) and articles in the popular press.

Over-prescription is a legal problem because it inevitably leads to diversion of these substances for non-medical usage. The Prescription Drug Monitoring Program (PDMP) laws have been passed by all 50 states and the main policy responses are covered. However, there are hindrances to their effectiveness, which have to be addressed. Two state level policy alternatives are discussed as potential solutions — PDMP mandates and Pain Management Clinic Laws (PMCLs). After a comparative evaluation, it is recommended that all states should pass the mandatory PDMP review and usage laws urgently.

This is the first detailed policy evaluation on the specific and time-sensitive aspect of physician over-prescribing, within the larger opioid abuse problem. Moreover, critique on the public health leadership issue is raised.

The purpose of this study is to understand how Amazon’s threat may impact the Pharmacy Industry as a whole and whether traditional drugstore chains such as consumer value stores (CVS) Pharmacy will need to re-think their business strategy, especially in the digital space, to account for potential disruption.

This is a hypothetical case study used as a teaching exercise to guide the learner through a decision-making process. The case starts by presenting a disruption in the retail pharmacy business that the main character must navigate by using real-world data and insights, provided in the case, to formulate a recommendation.

In an extremely competitive and consolidated pharmacy market, Amazon has the potential to change the business entirely. CVS Health will potentially face strong headwinds from Amazon’s PillPack and a downward trend in prescription sales. Regardless of the new competition, CVS Health continues to be innovative in the space. Instead of being a one-trick pony, CVS has encompassed the mentality of becoming a one-stop-shop by expanding into areas such as specialty pharmacy, health clinics, pharmacy benefits management and innovative digital capabilities.

This paper provides the reader with existing and known information about the evolving retail pharmacy business and allows the reader to interpret the new information to make their own decision on how a digital business strategy team can account for potential disruption.

The study aimed to evaluate the effectiveness of using large data sets for new diabetes patient prescriptions.

This study consisted of 101,766 individuals, who had applied to the hospital with a diabetes diagnosis and were hospitalized for 1–14 days and subjected to laboratory tests and medication.

With the help of Mahout and Scala, data mining methods of random forest and multilayer perceptron were used. Accuracy rates of these methods were found to be 0.879 and 0.849 for Mahout and 0.849 and 0.870 for Scala.

The mahout random forest method provided a better prediction of new prescription requirements than the other methods according to accuracy criteria.

Routine general practice (GP) care is rarely comprehensively described in clinical trials. This paper examines routine GP care within the lifestyle approach to managing panic (LAMP) study. The aim of this paper is to describe/discuss routine GP care for panic disorder (PD) patients within both study arms in the LAMP study. An unblinded pragmatic randomised controlled trial in 15 East of England GP practices (2 primary care trusts). Participants met Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria for PD with/without agoraphobia. Follow-up measures recorded at 20 weeks/10 months following randomisation. Control arm, unrestricted routine GP care (practice appointments, referrals and prescriptions). Trial arm, occupational therapy-led lifestyle treatment comprising lifestyle review of fluid intake, diet pattern, exercise, caffeine, alcohol and nicotine. Primary outcome measure: beck anxiety inventory. At baseline, participants attended 2-3 times more GP appointments than population average, reducing at 10 months to 1.6 times population average for routine GP care and 0.97 population average for lifestyle arm. At 10 months, 33% fewer referrals (6 referrals; 0 mental health) than at baseline (9 referrals; 2 mental health) were made for lifestyle arm patients compared with 42% increase (from 12 referrals; 8 mental health at baseline to 17 referrals; 7 mental health) in GP care arm. Selective serotonin reuptake inhibitors were prescribed most often. Benzodiazepines and beta-blockers were prescribed more often than tricyclic against current clinical guidelines. In conclusion, we found that PD patients at baseline were high healthcare resource users. Treatment in both study arms reduced resource use. Routine GP care requires further review for this patient group.

The involvement of politicians in the introduction and use of financial management techniques in the public sector deserves more attention. This paper analyses the influence of members of Parliament (MPs) on the development of financial management regulations for Dutch central government executive agencies.

This paper uses desk research and analyses formal evaluation reports, as well as minutes of meetings of Parliament to analyse the influence of MPs on the changes in financial management regulations.

MPs' influence on the change of prescriptions seems to have been small. The authors observe that modifications were most often already formulated in general evaluation reports by the Ministry of Finance, in advance of parliamentary debates. The analysis also reveals that the criteria to be met by the executive agencies became more detailed in the initial years of the agency model and became more global in recent years.

This paper aims to contribute to the literature on the influence of politicians on financial management regulations.

The paper shows that the influence of MPs on the prescriptions is quite small in daily practice and therefore, their role in the legislative process, as far as financial management techniques are concerned, is limited.

The results show that politicians are both in charge of, as well as subject to NPM-inspired financial management regulations, whereas their influence on the rules is small. The authors advise to further analyse this, as well as to explore how their role can be enlarged.

The interplay between politicians and financial management techniques in general, and the influence of MPs on the legislative process in specific, is an underresearched area. This paper aims to contribute to this literature and shows that the influence of MPs on the development of financial management regulations is limited. Several changes were made in these prescriptions in a period of more than 25 years, whereas discussions in the Parliament hardly played a role in these modifications.

The purpose of this study is to evaluate the prescribing pattern of proton pump inhibitors (PPIs) in patients visiting the outpatient general medical clinic in a Tertiary Care Teaching Hospital.

A hospital-based cross-sectional study was conducted in 419 patients aged ≥18 years, visiting the outpatient general medicine clinic of a tertiary hospital and prescribed with at least one PPI, from July to September 2016 using a purposive sampling technique. Descriptive statistics were performed using IBM-SPSS 20.0 (IBM Corporation, Armonk, NY, USA).

Patients were mostly less than 30 years (30.78%) and female (58.95%). Pantoprazole was the most frequently prescribed PPIs (57.04%). The majority of PPIs were prescribed for acid peptic disorder (APD) (33.65%), followed by non-steroidal anti-inflammatory drugs (NSAIDs) prophylaxis (30.79%). Most of the PPIs were prescribed for twice-daily administration (68.26%). Nearly one-fourth (21.72%) of the patients presented with at least one additional medical condition, and almost all (99%) patients were receiving at least one additional drug along with PPIs.

The study suggests that PPIs are frequently prescribed and their use has been extended to other conditions that in fact do not require acid anti-secretory therapy. Result has highlighted the need for an interdisciplinary collaboration between pharmacists and medical professionals for the rational use of PPIs and promotion of PPIs prescription from the National List of Essential Medicines.