STUDY DESIGN: A prospective study using data from the Australian Longitudinal Study on Women's Health. Women aged 77-82 years in 2003, and 91-96 years in 2017 were analysed, linking the Pharmaceutical Benefits Scheme data to participants' survey data.
MAIN OUTCOME MEASURES: The association between frailty and continuous polypharmacy was determined using generalised estimating equations for log binomial regressions, controlling for confounding variables. Descriptive statistics were used to determine the proportion of women with polypharmacy, and medications that contributed to polypharmacy.
RESULTS: The proportion of women with continuous polypharmacy increased over time as they aged. Among participants who were frail (n = 833) in 2017, 35.9 % had continuous polypharmacy and 1.32 % had hyperpolypharmacy. Among those who were non-frail (n = 1966), 28.2 % had continuous polypharmacy, and 1.42 % had hyperpolypharmacy. Analgesics (e.g. paracetamol) and cardiovascular medications (e.g. furosemide and statins) commonly contributed to continuous polypharmacy among frail and non-frail women. Accounting for time and other characteristics, frail women had an 8% increased risk of continuous polypharmacy (RR 1.08; 95 % CI 1.05, 1.11) compared to non-frail women.
CONCLUSIONS: Combined, polypharmacy and frailty are key clinical and public health challenges. Given that one-third of women had continuous polypharmacy, monitoring and review of medication use among older women are important, and particularly among women who are frail.
METHODS: This cross-sectional study was conducted at the University of Jordan Hospital in Amman, Jordan. During the study period, a convenience sample of patients admitted to the internal medicine and surgical wards were approached to take part in this study. Following patients' recruitments, patients were interviewed and their medical files were reviewed to obtain demographic and clinical information regarding their medical conditions and their regular use of medicines. Then, the prevelence of patients with polypharmacy were identified, and factors predicting polypharmacy among them were determined.
RESULTS: Among the 300 participants who agreed to participate in this study, females represented 45.3% of the recruited sample (n = 139), and around 48.0% (n = 144) of the study sample were elderly people (≥65 years old). Most of the recruited patients (n = 248, 82.7%) were found to use polypharmacy (≥ 5 medications). Hypertension was the most frequent medical condition among study participants (n = 240, 80.0%) followed by diabetes (n = 185, 61.7%). Results of logistic regression analysis showed that polypharmacy was only significantly affected by patients' age (OR = 2.149, P-value = .024) and monthly income (OR = 0.336, P-value = .009), while other factors were not associated with polypharmacy. Elderly patients (≥65 years) were found to have polypharmacy more significantly than non-elderly patients. Also, those with lower monthly income (<500 JD) were found to use lower polypharmacy compared with those with higher monthly income (>500 JD).
CONCLUSION: The present study showed that polypharmacy is prevalent among patients in Jordan. While polypharmacy was not affected by smoking status, gender, BMI and educational level, it was significantly affected by monthly income and age. Further plans should be put in place to reduce polypharmacy, starting with effective pharmaceutical care services leading to treatment optimisation and ensuring desired treatment outcomes.
DESIGN: Pragmatic multicenter stepped-wedge cluster randomized controlled trial.
SETTING AND PARTICIPANTS: Residents across 4 nursing homes in Singapore were included if they were aged 65 years and above, and taking 5 or more medications.
METHODS: The intervention involved a 5-step deprescribing intervention, which involved a multidisciplinary team-care medication review with pharmacists, physicians, and nurses (in which pharmacists discussed with other team members the feasibility of deprescribing and implementation using the Beers and STOPP criteria) or to an active waitlist control for the first 3 months.
RESULTS: Two hundred ninety-five residents from 4 nursing homes participated in the study from February 2017 to March 2018. At 6 months, the deprescribing intervention did not reduce falls. Subgroup analysis showed that intervention reduced fall risk scores within the deprescribing-naïve group by 0.18 (P = .04). Intervention was associated with a reduction in mortality [hazard ratio (HR) 0.16, 95% confidence interval 0.07, 0.41; P
METHODS: A systematic search was conducted in four databases from inception until April 30, 2021 as well as search of citation of included articles. Studies that reported patients' and/or their caregivers' attitude towards deprescribing quantitatively were included. All studies were independently screened, reviewed, and data extracted in duplicates. Patients and caregivers willingness to deprescribe their regular medication was pooled using random effects meta-analysis of proportions.
RESULTS: Twenty-nine unique studies involving 11,049 participants were included. All studies focused on the attitude of the patients towards deprescribing, and 7 studies included caregivers' perspective. Overall, 87.6% (95% CI: 83.3 to 91.4%) patients were willing to deprescribe their medication, based upon the doctors' suggestions. This was lower among caregivers, with only 74.8% (49.8% to 93.8%) willing to deprescribe their care recipients' medications. Patients' or caregivers' willingness to deprescribe were not influenced by study location, study population, or the number of medications they took.
DISCUSSION: Most patients and their caregivers were willing to deprescribe their medications, whenever possible and thus should be offered a trial of deprescribing. Nevertheless, as these tools have a poor predictive ability, patients and their caregivers should be engaged during the deprescribing process to ensure that the values and opinions are heard, which would ultimately improve patient safety. In terms of limitation, as not all studies may published the methods and results of measurement they used, this may impact the methodological quality and thus our findings. OPEN SCIENCE FRAMEWORK REGISTRATION: https:// osf.io/fhg94.
METHODS: Medical claims records from February 2019 to February 2020 were extracted from a health insurance claims database. Data cleaning and data analysis were performed using Python 3.7 with the Pandas, NumPy and Matplotlib libraries. The top five most common diagnoses were identified, and for each diagnosis, the most common medication classes and medications prescribed were quantified. Potentially inappropriate prescribing practices were identified by comparing the medications prescribed with relevant clinical guidelines.
KEY FINDINGS: The five most common diagnoses were upper respiratory tract infection (41.5%), diarrhoea (7.7%), musculoskeletal pain (7.6%), headache (6.7%) and gastritis (4.0%). Medications prescribed by general practitioners were largely as expected for symptomatic management of the respective conditions. One area of potentially inappropriate prescribing identified was inappropriate antibiotic choice. Same-class polypharmacy that may lead to an increased risk of adverse events were also identified, primarily involving multiple paracetamol-containing products, non-steroidal anti-inflammatory drugs (NSAIDs), and antihistamines. Other areas of non-adherence to guidelines identified included the potential overuse of oral corticosteroids and oral salbutamol, and inappropriate gastroprotection for patients receiving NSAIDs.
CONCLUSIONS: While prescribing practices are generally appropriate within the private primary care sector, there remain several areas where some potentially inappropriate prescribing occurs. The areas identified should be the focus in continuing efforts to improve prescribing practices to obtain the optimal clinical outcomes while reducing unnecessary risks and healthcare costs.
METHODS: This study was based on the fourth survey of the consortium known as the Research on Asian Psychotropic Prescription Pattern for Antipsychotics. Fifteen Asian countries/territories participated in this survey, including Bangladesh, Mainland China, Hong Kong, India, Indonesia, Japan, Korea, Malaysia, Myanmar, Pakistan, Singapore, Sri Lanka, Taiwan, Thailand, and Vietnam. Basic demographic and clinical characteristics were collected using a standardized data collection form.
RESULTS: Among the 879 older adults with schizophrenia included in the survey, the rate of APP was 40.5%. Multiple logistic regression analysis revealed that higher antipsychotic doses (P < .001, odds ratio [OR] = 1.003, 95% confidence interval [CI]: 1.002-1.003), longer duration of illness (P = .02, OR = 1.845, 95% CI: 1.087-3.132), and the prescription of anticholinergics (P < .001, OR = 1.871, 95% CI: 1.329-2.635), second-generation antipsychotics (P = .001, OR = 2.264, 95% CI: 1.453-3.529), and first-generation antipsychotics (P < .001, OR = 3.344, 95% CI: 2.307-4.847) were significantly associated with APP.
CONCLUSION: Antipsychotic polypharmacy was common in older adult Asian patients with schizophrenia. Compared to the results of previous surveys, the use of APP showed a declining trend over time. Considering the general poor health status of older patients with schizophrenia and their increased risk of drug-induced adverse events, the use of APP in this population needs careful consideration.
AIM: The aim of this study was to determine the characteristics of medication complexity and polypharmacy and determine their relationship with drug-related problems (DRP) and control of iron overload in transfusion-dependent thalassaemia patients.
METHOD: Data were derived from a cross-sectional observational study on characteristics of DRPs conducted at a Malaysian tertiary hospital. The medication regimen complexity index (MRCI) was determined using a validated tool, and polypharmacy was defined as the chronic use of five or more medications. The receiver operating characteristic curve analysis was used to determine the optimal cut-off value for MRCI, and logistic regression analysis was conducted.
RESULTS: The study enrolled 200 adult patients. The MRCI cut-off point was proposed to be 17.5 (Area Under Curve = 0.722; sensitivity of 73.3% and specificity of 62.0%). Approximately 73% and 64.5% of the patients had polypharmacy and high MRCI, respectively. Findings indicated that DRP was a full mediator in the association between MRCI and iron overload.
CONCLUSION: Transfusion-dependent thalassaemia patients have high MRCI and suboptimal control of iron overload conditions in the presence of DRPs. Thus, future interventions should consider MRCI and DRP as factors in serum iron control.