| Literature DB >> 34660435 |
Butoul Alshaish Alanizy1, Nazish Masud2, Aljawaharah Abdulaziz Alabdulkarim1, Ghada Abdulaziz Aldihan1, Reema Abdullah Alwabel1, Shikah Mohammed Alsuwaid1, Ihab Sulaiman3.
Abstract
BACKGROUND: Basic understanding of medical errors and medical complications is essential to ensure patient safety. Our aim in this study was to assess whether patients have sufficient knowledge of medical errors and medical complications and to identify the factors that influence their knowledge.Entities:
Keywords: Medical complications; knowledge; medical errors; patient education; patient safety
Year: 2021 PMID: 34660435 PMCID: PMC8483113 DOI: 10.4103/jfmpc.jfmpc_2031_20
Source DB: PubMed Journal: J Family Med Prim Care ISSN: 2249-4863
Demographic profile of the sample (n=346)
| Variables | Categories | |
|---|---|---|
| Age Categories (years) | 18-27 | 59 (17) |
| 28-37 | 101 (29) | |
| 38-47 | 90 (26) | |
| 48 and above | 96 (28) | |
| Gender | Female | 198 (57) |
| Male | 148 (43) | |
| Education level | Intermediate or less | 45 (13) |
| Secondary | 109 (32) | |
| Higher education | 192 (56) | |
| Employment status | Employed | 156 (45) |
| Unemployed | 190 (55) | |
| Health care background | Yes | 30 (9) |
| Any chronic illness? | Yes | 155 (45) |
| Are you using any medication? | Yes | 216 (62) |
| Do you rely on medical information from social media? | Yes | 113 (33) |
| Experienced medical error? | Yes | 76 (22) |
| Familiarity with the term “medical error” | Know the term | 252 (73) |
| Heard of it | 87 (25) | |
| Never heard of it | 7 (2) | |
| Familiarity with the term “medical complication” | Know the term | 204 (59) |
| Heard of it | 102 (30) | |
| Never heard of it | 40 (12) |
Correct and incorrect responses related to medical complications and medical errors (n=346)
| Incorrect | Correct | |
|---|---|---|
| Medical Complication Items | ||
| Item 1 | 141 (41) | 205 (59) |
| Item 3 | 190 (55) | 156 (45) |
| Item 4 | 121 (35) | 225 (65) |
| Item 7 | 123 (36) | 223 (65) |
| Item 8 | 158 (46) | 188 (54) |
| Item 12 | 115 (33) | 231 (67) |
| Item 14 | 189 (55) | 157 (45) |
| Item 15 | 261 (75) | 85 (25) |
| Item 16 | 122 (35) | 224 (65) |
| Medical Error Items | ||
| Item 2 | 151 (44) | 195 (56) |
| Item 5 | 112 (32) | 234 (68) |
| Item 6 | 139 (40) | 207 (60) |
| Item 9 | 60 (17) | 286 (83) |
| Item 10 | 52 (15) | 294 (85) |
| Item 11 | 60 (17) | 286 (83) |
| Item 13 | 194 (56) | 152 (44) |
| Item 17 | 69 (20) | 277 (80) |
For details about each item’s content, check Table 3
Context of the items
|
|
| Item 1: “Eye drops were prescribed for a patient then she felt burning sensation” |
| Item 3: “A patient complained of blurred vision after surgery that required anesthesia” |
| Item 4: “A patient complained of bruises over the area were the blood was drawn” |
| Item 7: “A patient started to vomit in the recovery room after general anesthesia ” |
| Item 8: “doctor prescribed a drug for hypertension as needed and the patient developed cough during the period of therapy” |
| Item 12: “A doctor prescribed iron supplement, then the patient complained of constipation after taking the supplements ” |
| Item 14: “A patient developed infection after surgery ” |
| Item 15: “A doctor prescribed an aspirin for a patient who has blood clots and he developed internal bleeding ” |
| Item 16: “A doctor prescribed a medication to manage a patient’s acne, but the acne progressed as a normal body reaction” |
|
|
| Item 2: “A patient is taking iron supplements, but his condition didn’t improve because the doctor didn’t warn him to avoid drinking coffee with the supplements ” |
| Item 5: “A patient received a physical therapy after a hand surgery, but the therapist exaggerated the area, which caused the patient to repeat the surgery ” |
| Item 6: “A patient was given a drug orally although he has difficulty in swallowing ” |
| Item 9: “A doctor prescribed a contraindicated drug to a diabetic patient, then the patient developed renal failure after intake” |
| Item 10: “ a drug was prescribed for hypertensive patient without measuring the patient’s blood pressure ” |
| Item 11: “A patient received blood transfusion. Later on, they found that blood donor had HIV” |
| Item 13: “A nurse missed a medication dose that was supposed to be given to a patient, but there was no harm” |
| Item 17: “A doctor prescribed warfarin (a blood thinner) to a patient without asking if the patient is taking other blood thinners” |
Association of demographic characteristics with the level of knowledge
| Variables | Categories | Level of Knowledge of Medical Complications | Level of Knowledge of Medical Errors | ||||
|---|---|---|---|---|---|---|---|
|
|
| ||||||
| Insufficient Knowledge | Sufficient Knowledge |
| Insufficient Knowledge | Sufficient Knowledge |
| ||
| Age Categories (years) | 18-27 | 31 (53%) | 28 (48%) | 26 (44%) | 33 (56%) | ||
| 28-37 | 55 (55%) | 46 (46%) | 32 (32%) | 69 (68%) | |||
| 38-47 | 55 (61%) | 35 (39%) | 41 (46%) | 49 (54%) | |||
| 48 and above | 60 (63%) | 36 (38%) | 28 (29%) | 68 (71%) | |||
| Gender | Female | 113 (57%) | 85 (43%) | 63 (32%) | 135 (68%) | ||
| Male | 88 (60%) | 60 (41%) | 64 (43%) | 84 (57%) | |||
| Education level | Intermediate or less | 29 (64%) | 16 (36%) | 16 (36%) | 29 (64%) | ||
| Secondary | 76 (70%) | 33 (30%) | 60 (55%) | 49 (45%) | |||
| Higher education | 96 (50%) | 96 (50%) | 51 (27%) | 141 (73%) | |||
| Employment status | Employed | 75 (48%) | 81 (52%) | 65 (42%) | 91 (58%) | ||
| Unemployed | 126 (66%) | 64 (34%) | 62 (33%) | 128 (67%) | |||
| Healthcare background | Yes | 12 (40%) | 18 (60%) | 8 (27%) | 22 (73%) | ||
| Chronic illness | Yes | 90 (58%) | 65 (42%) | 53 (34%) | 102 (66%) | ||
| Using any medication | Yes | 124 (57%) | 92 (43%) | 75 (35%) | 141 (65%) | ||
| Relying on social media for health information | Yes | 67 (59%) | 46 (41%) | 48 (43%) | 65 (58%) | ||
| Firsthand medical error experience | Yes | 37 (49%) | 39 (51%) | 23 (30%) | 53 (70%) | ||
*Significant Chi-square values (P≤0.05)
Figure 1Level of knowledge regarding medical complications and medical errors by gender
Predictors of medical complication and medical error knowledge
| Independent Variables | Knowledge of Medical Complications | Knowledge of Medical Errors | ||
|---|---|---|---|---|
|
| ||||
| Odds Ratio [95% CI] |
| Odds Ratio [95% CI] |
| |
| Age† (years) | ||||
| 28-37 | 0.58 [0.28-1.17] | 0.13 | 1.43 [0.69-2.98] | 0.333 |
| 38-47 | 0.47 [0.22-0.99] |
| 0.92 [0.44-1.93] | 0.836 |
| 48 and above | 0.56 [0.26-1.19] | 0.132 | 1.65 [0.76-3.57] | 0.202 |
| Female gender† | 1.47 [0.89-2.43] | 0.133 | 1.33 [0.80-2.21] | 0.277 |
| Education level† | ||||
| Intermediate or less | 0.74 [0.36-1.55] | 0.431 | 0.46 [0.22-0.99] | 0.047 |
| Secondary education | 0.52 [0.30-0.88] |
| 0.28 [0.16-0.49] |
|
| Unemployed† | 0.41 [0.23-0.72] |
| 1.93 [1.08-3.46] |
|
| No health care background‡ | 0.81 [0.35-1.86] | 0.614 | 0.56 [0.22-1.41] | 0.218 |
| Chronic illness¦ | 0.79 [0.47-1.33] | 0.375 | 1.00 [0.59-1.71] | 0.989 |
| No firsthand medical error‡ experience | 0.61 [0.35-1.04] | 0.071 | 0.78 [0.43-1.40] | 0.397 |
*Significant Chi-square values (P ≤0.05). *Significant logistic regression (P ≤0.05). †Reference category is “18-27 years” for age, “male” for gender, “higher education” for education level, and “employed” for employment status, ‡Reference category is “yes”. §Reference category is “no”, CI: Confidence Interval