| Literature DB >> 31960272 |
Keiko Fujie1, Risa Kamei2, Risa Araki3, Koichi Hashimoto3.
Abstract
Background In recent years, rapid increase of elderly population has become a major social problem in developed countries. They tend to receive an increasing number of prescibed drugs due to multiple illnesses, which might include inappropriate medications, in turn leading to health hazards and rising healthcare cost. Objective To evaluate the current status of potentially inappropriate medications prescribed for elderly outpatients and filled by dispensing pharmacies using the recent Japanese Guidelines, and to determine factors that are related to prescribing potentially inappropriate medications. Setting A cross-sectional study of older patients (≥ 75 years) who visited dispensing pharmacies in the Ibaraki Prefecture, Japan. Method We identified patients prescribed potentially inappropriate medications using the "List of Medications that Require Particularly Careful Administration" in the Guidelines (Guideline List). We explored patient's factors related to polypharmacy (≥ 5 medications) and prescription of inappropriate medications through multivariate analysis, and a cutoff value for predicting potentially inappropriate medications through receiver operating characteristic curve analysis. Main outcome measure Prevalence of polypharmacy and potentially inappropriate medications, and patient's factors associated with them. Results Of 8080 patients (39,252 medications) who visited pharmacies during the study period, 43.1% (3481) were prescribed ≥ 5 medications. In total, 2157 patients (26.7%) were prescribed at least one potentially inappropriate medication. The most prescribed inappropriate medication class was (benzodiazepine) sedatives and hypnotics. Potentially inappropriate medications were 7.11 times (95% CI 6.29-8.03) and 1.51 times (1.34-1.71) more likely to be prescribed for patients with ≥ 5 medications and those prescribed by multiple physicians, respectively. A cutoff value for potentially inappropriate medications was found to be five for the total number of medications and four for the number of chronic medications with a systemic effect. Conclusion Prescription of potentially inappropriate medications was increased among patients with ≥ 5 medications and those chronically prescribed ≥ 4 medications with a systemic effect. The Guideline List should be actively used to screen such patients, and to carefully examine prescriptions. Particular care should be exercised when patients are visiting multiple physicians.Entities:
Keywords: Dispensing pharmacy; Guideline; Japan; Outpatient; Polypharmacy; Potentially inappropriate medication
Year: 2020 PMID: 31960272 PMCID: PMC7192879 DOI: 10.1007/s11096-020-00967-9
Source DB: PubMed Journal: Int J Clin Pharm
Drug classes from the “List of Medications that Require Particularly Careful Administration (STOPP-J)” that were screened in this study
| Category | Drug class | Recommended use |
|---|---|---|
| Sleeping drugs | Benzodiazepine-based sleeping drugs and anti-anxiety drugs | Do not use long-lasting effect type and triazolam Use the other benzodiazepines as little as possible |
| Anti-depressants | Tricyclic anti-depressants | Use as little as possible |
| Sulpiride | Sulpiride | Use as little as possible |
| Anti-Parkinson drugs | anti-Parkinson drugs | Use as little as possible |
| Alpha blockers | Receptor subtype non-selective α1 receptor blockers | Use as little as possible |
| First generation H1 blockers | First generation H1 blockers | Use as little as possible |
| H2 blockers | H2 blockers | Use as little as possible |
| Antiemetics | antiemetics | Use as little as possible |
| Anti-diabetes drugs | Sulfonylurea | Do not use when possible |
| Biguanide | Do not use when possible | |
| SGLT2 inhibitors | Use as little as possible | |
| Insulin | Sliding scale insulin | Use as little as possible |
| Overactive bladder drugs | Oxybutynin | Use as little as possible |
SGLT2 sodium-glucose co-transporter 2
Patient background characteristics and total number of medications
| Total no. of patients | |
|---|---|
| Sex, n (%) | |
| Male | 3668 (45.4) |
| Female | 4412 (54.6) |
| Age, n (%), years | |
| 75–84 | 6009 (74.4) |
| 85 and above | 2071 (25.6) |
| No. of prescribing physicians per patient, n (%) | |
| 1 | 6251 (77.4) |
| 2 | 1365 (16.9) |
| 3 | 361 (4.5) |
| 4 | 77 (1.0) |
| 5 | 20 (0.2) |
| 6 | 6 (0.1) |
| Departments, n (%)a | |
| Neurosurgery | 1795 (17.1) |
| General internal medicine | 1715 (16.3) |
| Orthopedic surgery | 1358 (12.9) |
| Ophthalmology | 1322 (12.6) |
| Cardiovascular medicine | 883 (8.4) |
| Others | 3435 (32.7) |
| Bed no. of medical facilities, n (%)a | |
| 300 and more | 3518 (33.5) |
| 100–299 | 2075 (19.7) |
| 99 and less | 4915 (46.8) |
| No. of prescribed drugs per patient, median (IQR), [max] | |
| Overall | 4 (2–7) [ |
| Chronic-phase systemic drugs | 3 (1–6) [ |
IQR interquartile range
an = 10,508 was the total number of prescriptions, including multiple prescriptions per patient
Analysis of factors related to polypharmacy
| Univariate analysis | Multivariate analysis | ||||
|---|---|---|---|---|---|
| Non-polypharmacy (< 5 medications) | Polypharmacy (≥ 5 medications) | Adjusted ORb (95% CI) | |||
| Sex, female, n (%) | 2484 (54.0) | 1928 (55.4) | 0.219 | 1.02 (0.92–1.12) | 0.739 |
| Age, ≥ 85, n (%) | 1065 (23.2) | 1006 (28.9) | <0.001 | 1.37 (1.23–1.53) | < 0.001 |
| No. of prescribing physicians per patient, ≥ 2, n (%) | 385 (8.4) | 1444 (41.5) | <0.001 | 5.73 (5.11–6.42)d | < 0.001 |
Adjusted confounding variables in the multivariate logistic regression analysis; sex, age and the number of physicians per patient
OR odds ratio, CI confidence interval
aP value according to Chi square test
bOdds ratio adjusted for sex, age, number of prescribing physicians per patient
cP value according to the logistic regression analysis
dNumber of prescribing physicians per patient was treated as a continuous variable at multivariate analysis
Results of PIMs screening based on the STOPP-J
| Category of PIMs | Medications qualified as PIMs, n (%) | Prescriptions including PIMs, n (%) | Patients prescribed PIMs, n (%) |
|---|---|---|---|
| Sleeping drugs | 1460 (50.3) | 1276 (48.5) | 1251 (48.2) |
| Antidepressants | 27 (0.9) | 27 (1.0) | 27 (0.3) |
| Sulpiride | 21 (0.7) | 21 (0.8) | 20 (1.0) |
| Anti-Parkinson drugs | 6 (0.2) | 6 (0.2) | 6 (0.2) |
| Alpha blockers | 221 (7.6) | 217 (8.3) | 216 (8.3) |
| First-generation H1 blockers | 17 (0.6) | 17 (0.6) | 16 (0.6) |
| H2 blockers | 632 (21.8) | 632 (24.0) | 628 (24.2) |
| Antiemetics | 35 (1.2) | 35 (1.3) | 35 (1.3) |
| Diabetes drugs | 316 (10.9) | 261 (9.9) | 260 (10.0) |
| Insulin | 160 (5.5) | 128 (4.9) | 127 (4.9) |
| Overactive bladder drugs | 10 (0.3) | 10 (0.4) | 10 (0.4) |
| Total | 2905 | 2630a (2273)b | 2596a (2157)b |
PIM potentially inappropriate medication, STOPP-J list of medications that require particularly careful administration
aSum of each category
bActual number after eliminating overlaps
Analysis of factors related to PIMs
| Univariate analysis | Multivariate analysis | ||||
|---|---|---|---|---|---|
| PIMs = No | PIMs = Yes | Adjusted ORb (95% CI) | |||
| Sex, female, n (%) | 3192 (53.9) | 1220 (56.6) | 0.033 | 1.10 (0.99–1.23) | 0.084 |
| Age, ≥ 85, n (%) | 1485 (25.1) | 586 (27.2) | 0.056 | 0.96 (0.85–1.08) | 0.486 |
| No. of prescribing physicians per patient, ≥ 2, n (%) | 989 (16.7) | 840 (38.9) | < 0.001 | 1.51 (1.34–1.71) | < 0.001 |
| Polypharmacy | 1800 (30.4) | 1681 (77.9) | < 0.001 | 7.11 (6.29–8.03) | < 0.001 |
| No. of drugs, median (IQR) | |||||
| Overall | 3 (2–5) | 7 (5–10) | < 0.001d | ||
| Chronic-phase systemic drugs | 2 (1–4) | 6 (4–9) | < 0.001d | ||
Adjusted confounding variables in the multivariate logistic regression analysis; sex, age, the number of physicians per patient and polypharmacy
PIM potentially inappropriate medication, OR odds ratio, CI confidence interval, IQR interquartile range
aP value according to Chi square test
bOdds ratio adjusted for sex, age, number of prescribing physicians per patient, and polypharmacy
cP value according to logistic regression analysis
dP value according to Mann–Whitney U test
Fig. 1ROC curves for no. of drugs and PIMs. a Overall no. of drugs. b No. of chronic-phase systemic drugs. AUC, area under the curve; CI, confidence interval; ROC, receiver operating characteristics curve; PIM, potentially inappropriate medication