| Literature DB >> 35650614 |
Christine Li Ling Lau1, Cheah Yen Hor2, Siew Ting Ong3, Muhammad Fadhlullah Roslan4, Xin Yi Beh5, Dashnilatha Permal6, Shamini Rama4.
Abstract
BACKGROUND: Proper home medication management plays a role in improving medication adherence, preserving drug efficacy and ensuring safe medication practices, which is crucial to establish positive treatment outcomes. However, no published studies are available on home medication management among psychiatric patients. The study aimed to identify home medication management problems among psychiatric patients in Malaysia and to examine the associations of inappropriate medication storage and lack of a medication administration schedule with sociodemographic factors, disease insight, number of medications and type of home care pharmacy services (HCPS).Entities:
Keywords: Home care services; Hospitals; Malaysia; Medicine; Pharmacists; Pharmacy; Psychiatry
Mesh:
Year: 2022 PMID: 35650614 PMCID: PMC9157038 DOI: 10.1186/s12913-022-08069-0
Source DB: PubMed Journal: BMC Health Serv Res ISSN: 1472-6963 Impact factor: 2.908
Demographic characteristics of the study patients (N = 205)
| Characteristics ( | Median ( | N | % | |
|---|---|---|---|---|
| Age | 45 (38–56) | – | – | |
| Disease duration | 14 (6–23) | – | – | |
| Number of medications | 3 (2–4) | – | – | |
| Gender | Male | – | 102 | 49.8 |
| Female | – | 103 | 50.2 | |
| Ethnicity | Malay | – | 118 | 57.5 |
| Chinese | – | 60 | 29.3 | |
| Indian | – | 19 | 9.3 | |
| Others | – | 8 | 3.9 | |
| Highest Level of Education | No formal education | – | 29 | 14.2 |
| Primary school | – | 42 | 20.5 | |
| Secondary school | – | 120 | 58.5 | |
| Tertiary education | – | 14 | 6.8 | |
| Marital status | Married | – | 39 | 19.0 |
| Single | – | 127 | 62.0 | |
| Divorced | – | 23 | 11.2 | |
| Widowed | – | 16 | 7.8 | |
| Employment | Employed | – | 50 | 24.4 |
| Unemployed | – | 155 | 75.6 | |
| Household Income | B40 | – | 181 | 88.3 |
| M40 | – | 24 | 11.7 | |
| T20 | – | 0 | 0.0 | |
| Smoking | Yes | – | 72 | 35.1 |
| No | – | 133 | 64.9 | |
| Alcohol intake | Yes | – | 10 | 4.9 |
| No | – | 195 | 95.1 | |
| Substance abuse | Yes | – | 5 | 2.4 |
| No | – | 180 | 87.8 | |
| Has stopped | – | 20 | 9.8 | |
| Psychiatric disease | Schizophrenia | – | 179 | 87.2 |
| Major Depressive Disorder | – | 2 | 1.0 | |
| Bipolar Mood Disorder | – | 12 | 5.9 | |
| Others | – | 12 | 5.9 | |
| Presence of comorbidities | Yes | – | 81 | 39.5 |
| No | – | 124 | 60.5 | |
| Insight | Good | – | 157 | 76.6 |
| Poor | – | 48 | 23.4 | |
Types of home medication management problems identified during home visits, N = 229*
| Types of home medication management problems | n (%) |
|---|---|
| Inappropriate storage of medication | 73 (31.9) |
| Drug hoarding | 41 (17.9) |
| No medication administration schedule | 71 (31.0) |
| Possible medication duplication | 32 (14.0) |
| Sharing of medication | 4 (1.7) |
| Presence of expired medication at home | 8 (3.5) |
*Observation was only performed once for each patient at one visit. A patient may have more than one home medication problem, but the same problem is not repeated (e.g.. in a condition where a patient has several medications, it will be considered as one problem regardless of the number of medications that were inappropriately stored)
Logistic regression of factors associated with inappropriate storage of medications at home (N = 205)
| Variables | Univariate Analysis | Multivariate Analysis | ||||||
|---|---|---|---|---|---|---|---|---|
| Crude OR | 95% CI of OR | Wald’s χ | Adjusted OR | 95% CI of OR | Wald’s χ | |||
| Male | 0.72 | (0.29, 1.77) | 0.50 (1) | 0.478 | ||||
| Female | 1.00 | |||||||
| 1.03 | (0.99, 1.06) | 3.57 (1) | 1.03 | (0.99, 1.06) | 3.32 (1) | 0.068 | ||
| 5.82 (3) | 6.27 (3) | 0.099 | ||||||
| Chinese | 1.33 | (0.56, 3.14) | 0.44 (1) | 0.506 | 1.38 | (0.62, 3.06) | 0.64 (1) | 0.423 |
| Indian | 0.16 | (0.03, 0.86) | 4.54 (1) | 0.16 | (0.03, 0.84) | 4.65 (1) | ||
| Others | 1.34 | (0.21, 8.56) | 0.09 (1) | 0.753 | 1.34 | (0.23, 7.67) | 0.11 (1) | 0.738 |
| Malay | 1.00 | 1.00 | ||||||
| 1.47 (3) | 0.689 | |||||||
| No formal education | 0.96 | (0.20, 4.61) | 0.03 (1) | 0.959 | ||||
| Primary school | 0.51 | (0.11, 2.27) | 0.77 (1) | 0.380 | ||||
| Secondary school | 0.78 | (0.20, 2.94) | 0.13 (1) | 0.718 | ||||
| Tertiary education | 1.00 | |||||||
| 2.66 (3) | 0.446 | 2.51 (3) | 0.473 | |||||
| Single | 1.47 | (0.57, 3.79) | 0.65 (1) | 0.420 | 1.44 | (0.58, 3.59) | 0.63 (1) | 0.427 |
| Divorced | 2.27 | (0.63, 8.07) | 1.60 (1) | 2.37 | (0.68, 8.28) | 1.85 (1) | 0.173 | |
| Widowed | 0.67 | (0.15, 3.03) | 0.25 (1) | 0.611 | 0.78 | (0.19, 3.17) | 0.11 (1) | 0.735 |
| Married | 1.00 | 1.00 | ||||||
| Unemployed | 0.89 | (0.39, 2.05) | 0.06 (1) | 0.793 | ||||
| Employed | 1.00 | |||||||
| B40 | 4.20 | (1.12, 15.74) | 4.53 (1) | 4.34 | (1.17, 15.98) | 4.87 (1) | ||
| M40 | 1.00 | 1.00 | ||||||
| Yes | 1.28 | (0.47, 3.48) | 0.24 (1) | 0.624 | ||||
| No | 1.00 | |||||||
| Yes | 16.55 | (1.90, 143.66) | 6.48 (1) | 14.26 | (1.82, 111.38) | 6.42 (1) | ||
| No | 1.00 | 1.00 | ||||||
| 0.04 (2) | 0.977 | |||||||
| Yes | 1.28 | (0.11, 14.72) | 0.04 (1) | 0.838 | ||||
| Ex-abuser | 1.09 | (0.32, 3.67) | 0.02 (1) | 0.887 | ||||
| No | 1.00 | |||||||
| 1.23 | (0.98, 1.55) | 3.30 (1) | 1.23 | (0.98, 1.54) | 3.40 (1) | 0.065 | ||
| Poor | 2.37 | (1.07, 5.22) | 4.61 (1) | 2.34 | (1.08, 5.06) | 4.72 (1) | ||
| Good | 1.00 | 1.00 | ||||||
| Part-time | 2.46 | (1.07, 5.65) | 4.51 (1) | 2.60 | (1.20, 5.67) | 5.85 (1) | ||
| Full-time | 1.00 | 1.00 | ||||||
* p value below 0.05 is considered statistically significant; CI confidence interval, OR odds ratio
Logistic regression of factors associated with lack of medication administration schedule at home (N = 205)
| Variables | Univariate Analysis | Multivariate Analysis | ||||||
|---|---|---|---|---|---|---|---|---|
| Crude OR | 95% CI of OR | Wald’s χ | Adjusted OR | 95% CI of OR | Wald’s χ | |||
| Male | 1.70 | (0.66, 4.36) | 1.23 (1) | 0.267 | ||||
| Female | 1.00 | |||||||
| 1.01 | (0.97, 1.04) | 0.56 (1) | 0.451 | |||||
| 0.35 (3) | 0.949 | |||||||
| Chinese | 1.28 | (0.50, 3.27) | 0.27 (1) | 0.597 | ||||
| Indian | 1.30 | (0.37, 4.60) | 0.17 (1) | 0.676 | ||||
| Others | 1.15 | (0.17, 7.69) | 0.02 (1) | 0.879 | ||||
| Malay | 1.00 | |||||||
| 4.34 (3) | 4.71 (3) | 0.194 | ||||||
| No formal education | 0.34 | (0.06, 1.76) | 1.62 (1) | 0.33 | (0.07, 1.55) | 1.94 (1) | 0.163 | |
| Primary school | 0.85 | (0.19, 3.79) | 0.04 (1) | 0.836 | 0.85 | (0.21, 3.42) | 0.04 (1) | 0.826 |
| Secondary school | 0.41 | (0.10, 1.59) | 1.64 (1) | 0.42 | (0.11, 1.53) | 1.71 (1) | 0.190 | |
| Tertiary education | 1.00 | 1.00 | ||||||
| 2.52 (3) | 0.472 | |||||||
| Single | 0.85 | (0.31, 2.32) | 0.09 (1) | 0.765 | ||||
| Divorced | 2.01 | (0.53, 7.64) | 1.07 (1) | 0.301 | ||||
| Widowed | 0.67 | (0.13, 3.30) | 0.23 (1) | 0.629 | ||||
| Married | 1.00 | |||||||
| Unemployed | 1.07 | (0.45, 2.51) | 0.02 (1) | 0.871 | ||||
| Employed | 1.00 | |||||||
| B40 | 6.45 | (1.29, 32.18) | 5.16 (1) | 6.90 | (1.46, 32.48) | 5.98 (1) | ||
| M40 | 1.00 | 1.00 | ||||||
| Yes | 1.97 | (0.73, 5.32) | 1.79 (1) | 2.43 | (1.20, 4.92) | 6.12 (1) | ||
| No | 1.00 | 1.00 | ||||||
| Yes | 0.77 | (0.14, 4.11) | 0.09 (1) | 0.763 | ||||
| No | 1.00 | |||||||
| 0.68(2) | 0.711 | |||||||
| Yes | 0.41 | (0.03, 4.94) | 0.48 (1) | 0.485 | ||||
| Ex-abuser | 0.65 | (0.19, 2.21) | 0.46 (1) | 0.496 | ||||
| No | 1.00 | |||||||
| 0.94 | (0.73, 1.21) | 0.17 (1) | 0.676 | |||||
| Poor | 5.61 | (2.50, 12.59) | 17.53 (1) | 5.32 | (2.45, 11.56) | 17.85 (1) | ||
| Good | 1.00 | 1.00 | ||||||
| Part-time | 2.88 | (1.21, 6.83) | 5.79 (1) | 2.96 | (1.42, 6.15) | 8.51 (1) | ||
| Full-time | 1.00 | 1.00 | ||||||
* p value below 0.05 is considered statistically significant; CI confidence interval, OR odds ratio