Factors influencing PRN medication use in nursing homes

Objective: To identify determinants of PRN ( as needed) drug use in nursing homes. Decisions about the use of these medications are made expressly by nursing home staff when general medical practitioners (GPs) prescribe medications for PRN use. Method: Cross-sectional drug use data were collected during a 7-day window from 13 Australian nursing homes. Information was collected on the size, staffing-mix, number of visiting GPs, number of medication rounds, and mortality rates in each nursing home. Resident specific measures collected included age, gender, length of stay, recent hospitalisation and care needs. Main outcome measures: The number of PRN orders prescribed per resident and the number of PRN doses given per week averaged over the number of PRN medications given at all in the seven-day period. Results: Approximately 35% of medications were prescribed for PRN use. Higher PRN use was found for residents with the lower care needs, recent hospitalisation and more frequent doses of regularly scheduled medications. With increasing length of stay, PRN medication orders initially increased then declined but the number of doses given declined from admission. While some resident-specific characteristics did influence PRN drug use, the key determinant for PRN medication orders was the specific nursing home in which a resident lived. Resident age and gender were not determinants of PRN drug use. Conclusion: The determinants of PRN drug use suggest that interventions to optimize PRN medications should target the care of individual residents, prescribing and the nursing home processes and policies that govern PRN drug use.

Medication management reviews for people from the former Yugoslavia now resident in Australia

Aim: The objective of this prospective study was to conduct medication management reviews (MMR) in people from a non-English speaking background (NESB) (Bosnian/Serbian/ Croatian, from former Yugoslavia, currently residing in Australia) in their native language in order to identify medication-related problems (needs analysis) and implement appropriate therapeutic interventions, in collaboration with their general practitioners (GPs). Methods: Twenty-five participants entered the study. Each was interviewed and medication-related issues were identified by the health care team. Results: Various interventions (over 150 for the whole group, an average of 6 per participant), based on actual and potentia medication-related problems, were designed to improve the use of medicines. The MMRs introduced effective changes into the participants' health care. Psychological (e.g., feeling depressed) and sociological factors (e.g., costs of medicines, not understanding labels written in English) were identified having significant impacts on medication management. Conclusions: These data confirmed there are avoidable medication-related problems in people from a NESB. GPs and pharmacists working in health care teams with a trained interpreter could greatly improve medication use through regular review and a team approach to problem identification and solving.

Medication management at home: medication-related risk factors associated with poor health outcomes

Background: some patients may have medication-related risk factors only identified by home visits, but the extent to which those risk factors are associated with poor health outcomes remains unclear. Objective: to determine the association between medication-related risk factors and poor patient health outcomes from observations in the patients' homes. Design: cross-sectional study. Setting: patients' homes. Subjects: 204 general practice patients living in their own homes and at risk of medication-related poor health outcomes. Methods: medications and medication-related risk factors were identified in the patients' homes by community pharmacists and general practitioners (GPs). The medication-related risk factors were examined as determinants of patients' self-reported health related quality of life (SF-36) and their medication use, as well as physicians' impression of patient adverse drug events and health status. Results: key medication-related risk factors associated with poor health outcomes included: Lack of any medication administration routine, therapeutic duplication, hoarding, confusion between generic and trade names, multiple prescribers, discontinued medication repeats retained and multiple storage locations. Older age and female gender were associated with some poorer health outcomes. In addition, expired medication and poor adherence were also associated with poor health outcomes, however, not independently. Conclusion: the findings support the theory that polypharmacy and medication-related risk factors as a result of polypharmacy are correlated to poor health outcomes.

Resting energy expenditure is lower than predicted in people taking atypical antipsychotic medication

Resting energy expenditure (REE) is lower than predicted in persons taking atypical antipsychotic medication, and weight management is a significant clinical challenge for some of them. However, to date there have been no published guidelines to assist clinicians in choosing appropriate prediction equations to estimate energy expenditure in persons taking atypical antipsychotic medications. The objectives of this study were to measure REE in a group of men taking the atypical antipsychotic clozapine and to determine whether REE can be accurately predicted for this population using previously published regression equations. REE was measured using indirect calorimetry via a ventilated hood on eight men who had completed at least 6 months of treatment with clozapine. Comparisons between measured REE and predicted REE using five different equations were undertaken. The commonly-used Harris-Benedict and Schofield equations systematically overestimated REE. Predictions of REE from other equations were too variable for clinical use. When estimating energy requirements as part of a weight-management program in men who have been taking clozapine for 6 months, predictions of REE from the equations of Harris-Benedict and Schofield should be reduced by 280 kcal/day.

Smoking and schizophrenia: is symptom profile related to smoking and which antipsychotic medication is of benefit in reducing cigarette use?

Smoking rate is disproportionately high among patients with schizophrenia, resulting in significant morbidity and mortality. However, cigarette smoking has been reported to have beneficial effects on negative symptoms, extrapyramidal symptoms, cognitive functioning and mood symptoms. Therefore, smoking cessation may worsen disability in schizophrenia. The association between smoking and these key clinical parameters was examined. Additionally, severity of smoking across four different antipsychotic treatment groups was explored. One hundred and forty-six patients with schizophrenia were assessed for smoking using expired carbon monoxide and smoking history. They were administered the Positive and Negative Symptom Scale, The Extrapyramidal Symptom Rating Scale, the Barnes Akathisia Rating Scale, Reitans Trail-making Test (A and B) and General Health Questionnaire-28. There was no difference in the chlorpromazine equivalent dose of any of the medications studied. Atypical agents were associated with significantly lower levels of smoking when compared with typical medications. There was no difference in smoking severity between the individual atypical medications examined. Similarly, there were no significant differences between smoking and non-smoking groups with regard to Positive and Negative Symptom Scale, Extrapyramidal Symptom Rating Scale, Trail-making Test and General Health Questionnaire-28. However, there was a significant difference between these groups with the smoking group demonstrating less akathisia. Smoking is not associated with positive, negative cognitive and mood symptoms in schizophrenia. Smoking is associated with lower levels of antipsychotic induced akathisia. Clinicians should not be discouraged from helping patients stop smoking for fear of worsening symptoms. However, akathisia may emerge upon cessation of smoking. Switching patients from typical to atypical antipsychotics may assist patients with schizophrenia to give up smoking.

Medication management at home: medication risk factor prevalence and inter-relationships

Background and objective: Patients can have medication-related risk factors associated with poor health outcomes that become evident through visiting them in their homes. These medication-related risk factors may not be apparent in pharmacy and general practitioner (GP) records. The aim was to determine the prevalence and inter-relationships of medication-related risk factors for poor patient health outcomes identifiable through 'in-home' observations. Methods: The design was a cross-sectional study of 204 general practice patients living in their own homes and at risk of medication-related poor health outcomes. Medication-related risk factors were identified in the patients' homes by community pharmacists and GPs. Results and discussion: The prevalence of risk factors varied from 8.3% (multiple medication storage locations) to 55.9% (confused by generic and trade names). There were many relationships observed between the medication-related risk factors, with expired medication having the most relationships with other risk factors followed by therapeutic duplication and poor adherence (9, 6 and 6 relationships respectively). Conclusion: Visiting patients' homes may identify medication-related risk factors not otherwise apparent through patient visits to the health practitioner when medications may be brought for review (i.e. 'brown bag' reviews).

Combined acamprosate and naltrexone, with cognitive behavioural therapy is superior to either medication alone for alcohol abstinence: A single centres' experience with pharmacotherapy

Aims: To compare treatment outcomes amongst patients offered pharmacotherapy with either naltrexone or acamprosate used singly or in combination, in a 12-week outpatient cognitive behavioural therapy (CBT) programme for alcohol dependence. Methods: We matched 236 patients across gender, age group, prior alcohol detoxification, and dependence severity and conducted a cohort comparison study of three medication groups (CBT+acamprosate, CBT+naltrexone, CBT+combined medication) which included 59 patients per group. Outcome measures included programme attendance, programme abstinence and for those who relapsed, cumulative abstinence duration (CAD) and days to first breach (DFB). Secondary analyses compared the remaining matched 59 subjects who declined medication with the pharmacotherapy groups. Results: Across medication groups, CBT+ combined medication produced the greatest improvement across all outcome measures. Although a trend favoured the CBT+ combined group, differences did not reach statistical significance. Programme attendance: CBT + Acamprosate group (66.1%), CBT + Naltrexone group (79.7%), and in the CBT + Combined group (83.1%). Abstinence rates were 50.8, 66.1, and 67.8%, respectively. For those that did not complete the programme abstinent, the average number of days abstinent (CAD) were 45.07, 49.95, and 53.58 days, respectively. The average numbers of days to first breach (DFB) was 26.79, 26.7, and 37.32 days. When the focal group (CBT + combined) was compared with patients who declined medication (CBT-alone), significant differences were observed across all outcome indices. Withdrawal due to adverse medication effects was minimal. Conclusions: The addition of both medications (naltrexone and acamprosate) resulted in measurable benefit and was well tolerated. In this patient population naltrexone with CBT is as effective as combined medication with CBT, but the trend favours combination medication.