Abstract
Background
Older patients are commonly prescribed multiple medications therefore; medication misadventures are common and expected among older patients. The use of potentially inappropriate medicines (PIMs) further contributes to this risk. Therefore, this study aimed to examine PIMs use among older patients using the 2015 Beers criteria.
Methods
A cross-sectional retrospective study using electronic medical records data from a large tertiary hospital in Saudi Arabia was conducted. Older adult patient’s (age ≥ 65 years) who were treated in the ambulatory care setting were included. PIMs use was defined using the 2015 Beers criteria. Descriptive statistics and logistic regression were used to describe and identify potential predictors of PIMs use. All statistical analyses were carried out using the Statistical Analysis Software version 9.2 (SAS® 9.2).
Results
This study included 4073 older adults with a mean age of 72.6 (± 6.2) years. The majority of the study population was female (56.8%). The Prevalence of PIMs to be avoided among older adults was 57.6% where 39.9% of the older adults population were prescribed one PIMs, 14.5% two PIMs, and 3.3% were on three or more PIMs. The most commonly prescribed PIMs were gastrointestinal agents (35.6%) and endocrine agents (34.3%). The prevalence of PIMs to be used with caution was 37.5%. Polypharmacy and existence of certain chronic comorbidities were associated with high risk of PIMs use among older patients.
Conclusions
Given high prevalence of PIMs occurrence among this population, future research on strategies and interventions rationing PIMs use in the geriatric population are warranted.
Keywords: Elderly, Ageing, Beers criteria, Inappropriate prescribing
Background
The United Nation estimated that the population of older adults defined as those age 65 or older will almost double in Saudi Arabia from 3% in 2000 to 6% or more by the year 2025 [1]. As older adults population is growing, the prevalence of chronic comorbid health conditions secondary to the inevitable nature of ageing expected to increase. This, therefore, is potentially associated with an increase in the use of multiple drugs (polypharmacy) to well manage these comorbidities or to prevent associated complications [2].
Polypharmacy among older adults is common and consequently older patients are at higher risk of potentially inappropriate medications (PIMs) use [3]. PIMs are defined as “medications that should be avoided due to their risk which outweighs their benefit and when there are equally or more effective but lower risk alternatives are available” [4]. PIMs are considered one of the commonly encountered medication-related problems among the older population. The use of PIMs is commonly evaluated using different scales and criteria such as the Beers criteria, which are a set of explicit criteria to identify PIMs. It was first developed in 1991 and consequently updated with the latest update in 2015 [5].
It is well known that PIMs use among older patients is associated with negative health consequences and can impact patients’ quality of life. PIMs use increases the risk of hospitalization, drug-related problems and other adverse health outcomes by two to three folds [6, 7]. For example, drug-related problems secondary to the inappropriate use of sedative and hypnotic among older adults are found highly associated with risk of falls, delirium, and hallucination [8, 9]. Moreover, PIMs use is also associated with an increased cost burden on healthcare system which requires further research to rationalize the use of such medications [10].
The estimated prevalence of PIMs among older patients is high and more than one-third of the older population found to be prescribed at least one PIMs or been exposed to a PIM [11–13]. In the Middle East, the prevalence of PIMs is very high where two studies conducted in Qatar and Lebanon found that 38.3 and 45.2% of older patients were prescribed PIMs respectively [14, 15]. In Saudi Arabia, the prevalence of PIMs use among older adults was assessed by two studies. The first study had identified the PIMs that should be avoided in older patients using 2003 Beers criteria [16]. This study reported that 43% of the older adults used at least one PIM, 18% have used two PIMs and 38.4% have used three or more PIMs. The second study was carried among older patients who visited family medicine clinics and patients who received home health care program [17]. This study found that more than half of the study cohort used one or more of PIMs and majority of these inappropriate medications were avoidable.
Factors associated with inappropriate medications use are variable. Females, older age, polypharmacy, having multiple prescribers physicians, and having poor health status are more likely to be associated with PIMs use [18, 19]. Moreover, certain chronic conditions such as diabetes, hypertension, depression, osteoporosis, and dementia have also been associated with a higher risk of PIMs use compared with older adults who don’t have these chronic conditions [14, 15].
Although many studies have examined the PIMs use among older adults using Beers criteria globally, still few studies has examined factors associated with PIMs use among older adults in Saudi Arabia using the American Geriatric Society (AGS) Beers criteria. While one study was conducted in a Military hospital [16] and another was limited to family medicine [17] ward, both studies were purely descriptive and have used 2003 Beers Criteria. The unique of his study is that it has included all patients admitted to a large tertiary hospital and covers all elderly from all the hospital wards using the electronic medical records which allowed us to get a large sample size to do both descriptive and inferential analysis. Therefore, the main objectives of this study are to assess the prevalence of PIMs use among older adults’ patients in the ambulatory care setting, and to explore factors associated with increased risk of PIMs use among this population.
Methods
Study design
A cross-sectional retrospective study conducted using 12-month (1st Jan 2016 to 30th Dec 2016) data extracted from the Electronic Health Record (EHR) database.
Study population and setting
This study had included older patients aged 65 years and older who visited the ambulatory care clinics in a tertiary teaching hospital in Riyadh, Saudi Arabia.
Data source and data extraction
This study had used 12-month data retrieved from the EHR database. The study was approved by the Institutional Review Board (IRB) of King Saud University (reference number E-17-2580). All the participants provided written informed consent. Data collected included patient’s demographic profile, clinical data, and medication related data. The demographics file contained information about patients’ date of birth, gender, marital status, nationality. Clinical data provides information about documented medical diagnoses. Physicians reported clinical diagnosis using the International Classifications of Diseases – 9th edition, Clinical Modification (ICD-9-CM) codes or the Systematized Nomenclature of Medicine (SNOMED) diagnosis codes. (Appendix). Medication data contained information about patients prescribed medications as ambulatory care patients such as medication group, date of dispensing, and quantity dispensed.
Data handling
After obtaining the approval from the study site IRB, data were extracted by trained health informatics pharmacists. The confidentiality of the data used was maintained throughout the research process. Data extracted on Microsoft excel file was stored on a secure, password-protected, and limited accessed computer. Patients’ records were coded to protect patient confidentiality.
Measures
Dependent variable: Potentially Inappropriate Medications (PIMs)
The main outcome of interest in this study was to estimate the prevalence of PIMs in older adults. The PIMs were identified according to American Geriatric Society (AGS) 2015 updated Beers criteria by applying two categories: (1) medications to avoid for most older adults, and (2) medications to be used with caution [5]. The prevalence of PIMs use was classified into (one PIM, two PIMs, and three or more PIMs). Then PIMs use was classified into two categories: 1) PIMs use (i.e., use of one or more PIMs) and 2) Non-PIMs use (i.e., no PIMs use).
Independent variables
Independent variables included demographics (age in years, gender, nationality “Saudi, non-Saudi” and marital status “married, unmarried”). Independent variables also included chronic conditions which were categorized into: cardiovascular diseases (hypertension, diabetes, dyslipidemia, heart failure (HF), ischemic heart disease (IHD)); respiratory diseases (asthma and chronic obstructive pulmonary disease (COPD)); musculoskeletal diseases (osteoarthritis and osteoporosis); mental health conditions (depression, anxiety and dementia); chronic kidney disease (CKD) and cancer. Polypharmacy use defined as the use of five medications and more was included.
Statistical analysis
Data were entered into a custom-designed Microsoft Excel database and analyzed using the Statistical Analysis Software version 9.2 (SAS® 9.2). Descriptive statistics were used to describe the study population. Descriptive statistics were expressed as the mean and standard deviation (±SD) for continuous variables and frequencies and percentages for categorical variables. Bivariate analyses using the Student’s t-test, Pearson’s chi-squared test were used to assess the difference in demographics and disease characteristics between patients with and without PIMs. A two-tailed probability value of < 0.05 was considered to be statistically significant for all analyses. Logistic regression was used to examine the associations between PIMs use and the patient’s age, gender, polypharmacy and different chronic conditions. All statistical tests were performed at a significance level of α = 0.05 and a 95% confidence interval (CI).
Results
Description of the study population
In this study, 4073 older adults (age ≥ 65 year) who visited ambulatory care clinics in a tertiary hospital during a 1 year period were identified and included. The mean age was (72.6 ± 6.2) years and the majority of the study population were females. The majority of the study population had two or more chronic conditions (77.9%) and 80.5% were using polypharmacy. Characteristics of the study population are presented in (Table 1).
Table 1.
Characteristics of the Study Populationa
| Characteristics | N | % |
|---|---|---|
| Total | 4073 | 100.0 |
| Age mean (±SD) | 72.6 (±6.2) | |
| Marital Status | ||
| Single | 157 | 4.3 |
| Married | 3488 | 95.7 |
| Gender | ||
| Male | 1759 | 43.2 |
| Female | 2314 | 56.8 |
| Nationality | ||
| Saudi | 3737 | 91.9 |
| Non-Saudi | 331 | 8.1 |
| Comorbidities Hypertension | ||
| Yes | 3007 | 73.8 |
| Diabetes | ||
| Yes | 2309 | 56.7 |
| Dyslipidemia | ||
| Yes | 2209 | 54.2 |
| Heart failure | ||
| Yes | 51 | 1.3 |
| Ischemic Heart disease | ||
| Yes | 254 | 6.2 |
| Chronic kidney disease | ||
| Yes | 119 | 2.9 |
| Cancer | ||
| Yes | 123 | 3.0 |
| Asthma | ||
| Yes | 403 | 9.9 |
| COPD | ||
| Yes | 17 | 0.4 |
| Osteoarthritis | ||
| Yes | 373 | 9.2 |
| Osteoporosis | ||
| Yes | 344 | 8.4 |
| Anxiety | ||
| Yes | 376 | 9.2 |
| Depression | ||
| Yes | 60 | 1.5 |
| Dementia | ||
| Yes | 25 | 0.6 |
| No. of chronic conditions | ||
| No chronic | 234 | 5.7 |
| one chronic condition | 665 | 16.3 |
| ≥ two chronic conditions | 3174 | 77.9 |
| Polypharmacy | ||
| 0 to 4 drugs | 794 | 19.5 |
| ≥ 5 | 3279 | 80.5 |
aNote: Study Population Comprised of 4073 (age ≥ 65 year) who visited ambulatory care clinics from tertiary hospital
Prevalence of PIMs
The prevalence of PIMs to be avoided among older adults was (57.6%) (Table 2, Table 3). The most commonly prescribed PIMs to be avoided for older adults were gastrointestinal and endocrine agents. The prevalence of PIMs to be used with caution was 37.5%. The most commonly prescribed PIMs to be used with caution were diuretics followed by antidepressants.
Table 2.
Prevalence of Potentially Inappropriate Medications Using Updated Peers Criteria among Older Patientsa
| Number | Percent | |
|---|---|---|
| PIMs “That Should Be Avoided” | ||
| Yes | 2346 | 57.5 |
| No | 1727 | 42.4 |
| Numbers of PIMs Use That Should Be Avoided | ||
| One PIM | 1625 | 39.9 |
| Two PIMs | 588 | 14.4 |
| Three or more PIMs | 133 | 3.3 |
| PIMs “That Should Be Used With Caution” | ||
| Yes | 1529 | 37.5 |
| NO | 2544 | 62.5 |
| Numbers of PIMs Use With Caution | ||
| One PIM with caution | 1341 | 32.9 |
| Two PIMs with caution | 174 | 4.3 |
| Three or more PIMs with caution | 14 | 0.3 |
aNote: Study population comprised of 4187 (age > 65 year) who visited ambulatory care Clinics from tertiary hospital
Table 3.
Potentially Inappropriate Medications to Be Avoided For Most Older Adults According to Medication Groups
| Medication Groups | N | (%) |
|---|---|---|
| Gastrointestinal Agents | 1450 | 35.6 |
| Endocrine Agents | 1397 | 34.3 |
| NSAID Agents | 278 | 6.8 |
| Antidepressant Agents | 19 | 0.5 |
| Antispasmodic Agents | 20 | 0.5 |
| Antipsychotic Agents | 8 | 0.2 |
| Anti-infective Agents | 7 | 0.2 |
| Genitourinary medications | 4 | 0.1 |
| Central Alpha Blocker Agents | 1 | 0.02 |
| Peripheral Alpha-1 Blocker Agents | 1 | 0.02 |
| Potentially Inappropriate Medications to Be Used With Caution in Older Adults | ||
| Diuretics | 1354 | 33.2 |
| Antidepressant SSRI | 200 | 4.9 |
| Anticoagulant Agents | 54 | 1.3 |
| Vasodilators | 54 | 1.3 |
| Anticonvulsant Agents | 27 | 0.6 |
| Antidepressant Alpha-2 Antagonist Agents | 19 | 0.5 |
| Anti-neoplastic alkylating Agents | 13 | 0.3 |
| Anti-neoplastic Agent, Antimicrotubule | 9 | 0.2 |
Factors associated with PIMs use on bivariate analysis
On bivariate analysis older adults who had chronic conditions compared to those without chronic conditions including hypertension, diabetes, dyslipidemia, HF, IHD, CKD, cancer, COPD, osteoarthritis, osteoporosis and anxiety were all associated with PIMs use. For example, the rate of PIMs use was higher among older adults with hypertension (59.9%, P-value < 0.001) as compared to those without hypertension, PIMs use was higher among patients with diabetes (66%, P-value < 0.001) as compared to those without diabetes. Moreover, PIMs use was higher among older patients with polypharmacy (66.7%, P- value < 0.001) as compared to those without polypharmacy use. Other factors were not associated with PIMs use among older patients (Table 4).
Table 4.
Number and Raw Percentage of Characteristics by PIM Use* Adjusted Odds Ratios and 95% Confidence Intervals From Logistic Regression on PIM Use among Older Patients
| PIM Use | No PIM Use | PIM Use | |||||||
|---|---|---|---|---|---|---|---|---|---|
| N | % | N | % | P value | Sig. | OR | 95% CI | Sig. | |
| Total | 2346 | 57.5 | 1727 | 42.4 | |||||
| Age Mean | 72.8 | 72.3 | 0.23 | ||||||
| Marital Status | 0.77 | ||||||||
| Single | 88 | 56.1 | 69 | 43.9 | |||||
| Married | 1995 | 57.2 | 1493 | 42.8 | |||||
| Gender | 0.36 | ||||||||
| Male | 999 | 56.8 | 760 | 43.2 | |||||
| Female | 1347 | 58.2 | 967 | 41.8 | |||||
| Nationality | 0.25 | ||||||||
| Saudi | 2165 | 57.9 | 1572 | 42.1 | |||||
| Non-Saudi | 181 | 54.7 | 150 | 45.3 | |||||
| Hypertension | 0.00 | *** | |||||||
| Yes | 1802 | 59.9 | 1205 | 40.1 | 0.95 | [0.79, 1.13] | |||
| Diabetes | 0.00 | *** | *** | ||||||
| Yes | 1523 | 66.0 | 786 | 34.0 | 2.03 | [1.76, 2.34] | |||
| Dyslipidemia | 0.00 | ** | |||||||
| Yes | 1320 | 59.8 | 889 | 40.2 | 0.98 | [0.84, 1.13] | |||
| Heart failure | 0.00 | *** | *** | ||||||
| Yes | 48 | 94.1 | 13 | 5.9 | 8.19 | [2.36, 28.38] | |||
| Ischemic Heart disease | 0.00 | *** | *** | ||||||
| Yes | 207 | 81.5 | 47 | 18.5 | 2.74 | [1.93, 3.88] | |||
| Chronic kidney disease | 0.00 | *** | *** | ||||||
| Yes | 97 | 81.5 | 22 | 18.5 | 2.34 | [1.41, 3.87] | |||
| Cancer | 0.00 | *** | *** | ||||||
| Yes | 97 | 78.9 | 26 | 21.1 | 2.71 | [1.65, 4.44] | |||
| Asthma | 0.46 | ||||||||
| Yes | 239 | 59.3 | 164 | 40.7 | |||||
| COPD | 0.03 | * | |||||||
| Yes | 14 | 82.4 | 31 | 17.6 | 0.72 | [0.17, 3.01] | |||
| Osteoarthritis | 0.00 | ** | *** | ||||||
| Yes | 191 | 51.2 | 182 | 48.8 | 0.61 | [0.48, 0.76] | |||
| Osteoporosis | 0.00 | ** | *** | ||||||
| Yes | 172 | 50.0 | 172 | 50.0 | 0.63 | [0.49, 0.79] | |||
| Anxiety | 0.00 | *** | ** | ||||||
| Yes | 262 | 69.7 | 114 | 30.3 | 1.5 | [1.15, 1.96] | |||
| Depression | 0.68 | ||||||||
| Yes | 33 | 55.0 | 27 | 45.0 | |||||
| Dementia | 0.51 | ||||||||
| Yes | 16 | 64.0 | 19 | 36.0 | |||||
| Polypharmacy | 0.00 | *** | *** | ||||||
| > =5 | 2188 | 66.7 | 1091 | 33.3 | 7.79 | [6.36, 9.54] | |||
| 0 to 4 drugs | 158 | 19.9 | 636 | 80.1 | |||||
Note: Study population comprised of 4187 (age > 65 year) who visited ambulatory care from tertiary hospital
The reference category for all chronic conditions was “No”
T-test was used to assess the association between age and PIM use
CI Confidence Interval, OR Odds Ratio, Ref Reference Group
Asterisks (*) represent significant differences in polypharmacy
***P < .001; **.001 ≤ p < .01; *.01 ≤ p < .05
Factors associated with PIMs use in regression analysis
All factors associated with PIMs use in the bivariate analysis were included in the regression analysis. PIMs use was more likely among older adults with diabetes, HF, IHD, CKD, cancer, osteoarthritis, osteoporosis, and anxiety. The adjusted odds ratios (AOR) and 95% confidence intervals (CI) for factors associated with PIMs use are displayed in (Table 4). Older patients with polypharmacy use were seven folds more likely to have PIMs use compared to older adults with no polypharmacy use (Table 4).
Discussion
This study aimed to estimate the prevalence of PIMs use among older patients using the latest updated of Beers criteria “the 2015 American Geriatrics Society Criteria”. The prevalence was assessed by using two categories of 2015 Beers criteria; the prevalence of PIMs to be avoided for older adults which was 57.6%, and the prevalence of PIMs that’s should be used with caution was 37.5%. The prevalence of PIMs was relatively high; however, this rate is within the range comparable to the results of previous studies where the prevalence of PIMs ranged between 21 to 58% [20–23]. This variation between studies may be due to using a different setting, study design or different version of Beers criteria. For instance, a study showed a difference in the prevalence of PIMs when they used two versions of beers criteria 2003 and 2012 on the same population (48% versus 59% respectively) [24].
The most likely factor associated with PIMs use in this study was polypharmacy. We found that 80% of this study population used more than five medications. The higher rate of polypharmacy use in our study population can be attributed to the higher rate of multiple chronic conditions (i.e., two or more chronic conditions), in which they may need to take many medications to control their chronic conditions or to prevent complications associated with certain chronic conditions. Several studies have reported an increased risk of PIMs with polypharmacy where one study showed that PIMs use was two times higher among older patients with polypharmacy, while another study reported that PIMs use was three times as likely with polypharmacy use [25, 26, 21, 22].
In this study, the presence of certain chronic conditions in older patients predicted the increased chance of PIMs use including diabetes, IHD, HF, CKD, cancer, osteoarthritis, osteoporosis, and anxiety. Multiple studies have demonstrated a significant association between PIMs use and cardiovascular diseases, diabetes, osteoporosis and increase number of chronic diseases [27]. The association between PIMs use and different predictors such as the presence of certain chronic conditions and polypharmacy use, although this is not a novel finding, however, this could be an indicator of inappropriate medication management for these conditions in such vulnerable population [28, 29]. This finding can also help to understand the factors associated with PIMs use, as having this knowledge makes it possible to assess health care provided to the older population and the prompt need for future services directed towards older patients. The role of health care providers should expand in order to take the necessary precautions when managing older patient’s conditions to avoid inappropriate medications prescribing, adverse events and other misadventures associated with older patients. Additionally, pharmacists can play a major role in improving the appropriateness of medications use by the recommendation for either medication discontinuation, medication review, the clinical application of tools to assess PIMs such as Peers criteria, or other tools to identify older patients at risk of unnecessary use of PIMs [30].
The study has some limitations. Firstly, this study did not apply other categories of 2015 Beers criteria and only PIMs to be avoided and PIMs to be used with caution were included in the study and this was due to the nature of this study design as a retrospective study and required patient’s data to identify other category of PIMs was not recorded in EHR database. Secondly, findings of this study cannot be generalized to all older adults across Saudi Arabia or the older population entirely as this study included only older patients who visited ambulatory care clinics of one tertiary hospital. Thirdly, the impact of other factors such as the socio-demographic predictors, variation between clinical settings in the region, comorbidity index or recent hospitalization were not evaluated in this study requiring future studies to comprehensively assess such factors and PIM use among older patients. Further, we were not able to capture the use and failure of other drugs prior to the prescribing of PIMS given the nature of the study design.
However, this study still can be considered novel as the study was designed using the latest Beers criteria which also considered one of the most utilized criteria for identifying PIMs among older adults in clinical setting and the latest two update of Beers criteria were supported by American Geriatric Society which improved the quality of the criteria by application of an evidence-based approach [31]. Moreover, to our knowledge, this is the first study to explore PIMs use among older patients and evaluate predicating factors associated with PIMs use in Saudi Arabia. Therefore, this study shed light more on what is needed to understand how to reduce harms associated with the unnecessary use of PIMs and provide better health care for older adults to minimize medications risk and economic burden. Consequently, findings of this study address important information to policymakers about a serious need for effective implantation of pharmacy services such as medication therapy management and continuous medication review regularly to reduce the use of PIMs. Also, elderly patients may benefit from a multidisciplinary collaborative care model that involves pharmacist follow up for the patients to assess the medication use and minimize inappropriate medications. Furthermore, the policymaker would benefit from conducting continuous educational activities for healthcare providers to help them understand the guidelines and criteria on proper prescribing of medications for the elderly population.
Conclusions
This study showed a high prevalence of PIMs that should be avoided or used with caution among older patients. Polypharmacy and chronic conditions were predictors for increased use of PIMs among older patients. With the anticipated growth of the older population, future studies to explore the adverse health outcome associated with PIMs use and strategies to rationalize the use of unnecessary or high-risk medications among this population are warranted.
Acknowledgments
This study was financially supported by the Vice Deanship of Research Chairs, King Saud University, Riyadh, Saudi Arabia.
Abbreviations
- AGS
American Geriatric Society
- AOR
Adjusted Odds Ratios
- CI
Confidence Intervals
- CKD
Chronic Kidney Disease
- COPD
Chronic Obstructive Pulmonary Disease
- EHR
Electronic Health Record
- HF
Heart Failure
- IHD
Ischemic Heart Disease
- IRB
Institutional Review Board
- PIMs
Potentially Inappropriate Medicines
Appendix
Table 5.
International Classifications of Diseases – 9th edition, Clinical Modification (ICD-9-CM) codes or the Systematized Nomenclature of Medicine (SNOMED) diagnosis codes
| Type of Chronic Conditions | ICD-9-CM Codes | SNOMED Codes |
|---|---|---|
| Cardiovascular Conditions | ||
| Hypertension | 401.9 | 64,176,011, 2,164,904,016 |
| Diabetes | 250, 250.00 | 121,589,010, 502,372,015 |
| Ischemic heart disease | 2,534,671,011, 2,537,479,013, 397,667,016, 2,534,663,012 | |
| Vascular heart disease | 1,705,016 | |
| Stroke | 2,644,233,012, 2,476,091,017, 345,636,015, 345,682,011 | |
| Heart failure | 428.0, 428.1 | 1,234,906,013, 143,156,018, 251,680,018, 94,251,011, 2,645,367,010, 18,472,010, 139,475,013, 2,816,764,017, 493,289,014, 70,653,017, 80,720,010 |
| Dyslipidemia | 92,826,017, 1,209,706,018 | |
| Musculoskeletal Conditions | ||
| osteoarthritis | 1,776,248,011, 359,420,013, 359,421,012, 1,785,522,017 | |
| Osteoporosis | 453,855,011, 107,806,013 | |
| Respiratory Conditions | ||
| Asthma | 493, 493.90 | 301,485,011, 301,480,018 |
| COPD | 23,290,013, 23,287,019, 475,431,013, 475,427,019 | |
| Mental Health Conditions | ||
| Dementia | 87,274,019 | |
| Depression | 311 | 486,186,018, 486,187,010, 110,183,011, 346,973,011, 346,979,010, 55,208,011, 454,082,014, 486,187,010, 124,707,013, 1,208,903,011, 490,537,016, 346,980,013, 1,228,731,019, 486,184,015 |
| Anxiety | 346,980,013, 369,987,018, 303,689,015, 481,155,011, 81,133,019 | |
| Other chronic diseases | ||
| Chronic kidney disease | 2,771,041,011, 2,767,385,013, 150,315,015 | |
| Cancera | 153.9, 202.80,202.8 | 1,217,470,011, 379,663,018, 379,662,011, 1,786,810,016, 1,228,536,014, 1,228,535,013, 1,228,484,019, 157,732,017, 1,783,096,018, 198,367,013, 1,220,412,013, 198,006,010, 414,270,011, 2,663,377,018, 414,271,010, 675,125,016, 195,620,018, 1,783,096,018, 413,121,012, 1,778,963,014, 2,663,475,013, 1,220,409,010, 1,228,486,017, 1,228,547,019, 1,479,600,014, 1,786,665,019, 1,229,105,017 |
aCancer included anal, brain, breast, bladder, colon, endometrial, esophageal, gastric, leukemia, liver, lung, lymphoma, ovary, rectal, thyroid, pancreatic, prostate, and uterus cancer
Authors’ contributions
TA: Developing design, literature search, manuscript writing. WA: developing design, literature search, manuscript writing. MA: Developing design, literature search, manuscript writing, and analysis of results. All authors read and approved the final manuscript.
Availability of data and materials
The EHR dataset used during and/or analyzed during the current study are not publicly available due to our IRB policy but are available from the corresponding author upon reasonable request.
Ethics approval and consent to participate
The study was approved by the Institutional Review Board (IRB) of King Saud University (reference number E-17-2580). All the participants provided written informed consent.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Ageing WP. Saudi Arabia. 1950. pp. 402–403. [Google Scholar]
- 2.Jiron M, Pate V, Hanson LC, Lund JL, Jonsson Funk M, Strümer T. Trends in prevalence and determinants of potentially inappropriate prescribing in the United States: 2007 to 2012. J Am Geriatr Soc. 2016;64(4):788–797. doi: 10.1111/jgs.14077. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Suehs BT, et al. Effect of potentially inappropriate use of antimuscarinic medications on healthcare use and cost in individuals with overactive bladder. J Am Geriatr Soc. 2016;64(4):779–787. doi: 10.1111/jgs.14030. [DOI] [PubMed] [Google Scholar]
- 4.Page RL, II SA, Bryant LL, Ruscin JM. “Inappropriate prescribing in the hospitalized elderly patient : defining the problem , evaluation tools , and possible solutions”. 75–87, 2010. [DOI] [PMC free article] [PubMed]
- 5.Panel, A.G.S.B.C.U.E et al. American Geriatrics Society 2015 updated beers criteria for potentially inappropriate medication use in older adults. J Am Geriatr Soc. 2015;63(11):2227–2246. doi: 10.1111/jgs.13702. [DOI] [PubMed] [Google Scholar]
- 6.Lu WH, Wen YW, Chen LK, Hsiao FY. Effect of polypharmacy, potentially inappropriate medications and anticholinergic burden on clinical outcomes: a retrospective cohort study. CMAJ. 2015;187(4):E130–E137. doi: 10.1503/cmaj.141219. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Fick DM, Mion LC, Beers MH, L. Waller J. Health outcomes associated with potentially inappropriate medication use in older adults. Res Nurs Health. 2008;31(1):42–51. doi: 10.1002/nur.20232. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Stockl K, Le L, Zhang S, Harada A. Clinical and economic outcomes associated with potentially inappropriate prescribing in the elderly. Am J Manag Care. 2010;16(1):e1–10. [PubMed] [Google Scholar]
- 9.Perri M, et al. Adverse outcomes associated with inappropriate drug use in nursing homes. Ann Pharmacother. 2005;39(3):405–411. doi: 10.1345/aph.1E230. [DOI] [PubMed] [Google Scholar]
- 10.Fick D, et al. Potentially inappropriate medication use in a Medicare managed care population: association with higher costs and utilization. J Manag Care Pharm. 2001;7(5):407–413. [Google Scholar]
- 11.Hudhra K, García-Caballos M, Jucja B, Casado-Fernández E, Espigares-Rodriguez E, Bueno-Cavanillas A. Frequency of potentially inappropriate prescriptions in older people at discharge according to Beers and STOPP criteria. Int J Clin Pharm. 2014;36(3):596–603. doi: 10.1007/s11096-014-9943-8. [DOI] [PubMed] [Google Scholar]
- 12.Maio V, Yuen EJ, Novielli K, Smith KD, Louis DZ. Potentially inappropriate medication prescribing for elderly outpatients in Emilia Romagna, Italy. Drugs Aging. 2006;23(11):915–924. doi: 10.2165/00002512-200623110-00006. [DOI] [PubMed] [Google Scholar]
- 13.Miller G. Edward, Sarpong Eric M., Davidoff Amy J., Yang Eunice Y., Brandt Nicole J., Fick Donna M. Determinants of Potentially Inappropriate Medication Use among Community-Dwelling Older Adults. Health Services Research. 2016;52(4):1534–1549. doi: 10.1111/1475-6773.12562. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Alhmoud E, Khalifa S, Bahi AA. Prevalence and predictors of potentially inappropriate medications among home care elderly patients in Qatar. Int J Clin Pharm. 2015;37(5):815–821. doi: 10.1007/s11096-015-0125-0. [DOI] [PubMed] [Google Scholar]
- 15.Zeenny R, Wakim S, Kuyumjian Y-M. Potentially inappropriate medications use in community-based aged patients: a cross-sectional study using 2012 Beers criteria. Clin Interv Aging. 2017;12:65–73. doi: 10.2147/CIA.S87564. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Al-Omar HA, Al-Sultan MS, Abu-Auda HS. Prescribing of potentially inappropriate medications among the elderly population in an ambulatory care setting in a Saudi military hospital: trend and cost. Geriatr Gerontol Int. 2013;13(3):616–621. doi: 10.1111/j.1447-0594.2012.00951.x. [DOI] [PubMed] [Google Scholar]
- 17.Al Odhayani A, Tourkmani A, Alshehri M, Alqahtani H, Mishriky A. Potentially inappropriate medications prescribed for elderly patients through family physicians. Saudi J Biol Sci. 2016;24(1):200–207. doi: 10.1016/j.sjbs.2016.05.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Lim YJ, et al. Potentially inappropriate medications by beers criteria in older outpatients: prevalence and risk factors. Korean J Fam Med. 2016;37(6):329–333. doi: 10.4082/kjfm.2016.37.6.329. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Shade Marcia Y., Berger Ann M., Chaperon Claudia, Haynatzki Gleb, Sobeski Linda, Yates Bernice. Factors Associated With Potentially Inappropriate Medication Use in Rural, Community-Dwelling Older Adults. Journal of Gerontological Nursing. 2017;43(9):21–30. doi: 10.3928/00989134-20170406-01. [DOI] [PubMed] [Google Scholar]
- 20.Curtis LH, et al. Inappropriate prescribing for elderly Americans in a large outpatient population. Arch Intern Med. 2013;164:1621–1625. doi: 10.1001/archinte.164.15.1621. [DOI] [PubMed] [Google Scholar]
- 21.Bahat G, Bay I, Tufan A, Tufan F, Kilic C, Karan MA. Prevalence of potentially inappropriate prescribing among older adults: a comparison of the Beers 2012 and screening tool of older Person’s prescriptions criteria version 2. Geriatr Gerontol Int. 2017;17(9):1245–1251. doi: 10.1111/ggi.12850. [DOI] [PubMed] [Google Scholar]
- 22.Zhang X, et al. Potentially inappropriate medications in hospitalized older patients: a cross-sectional study using the Beers 2015 criteria versus the 2012 criteria. Clin Interv Aging. 2017;12:1697–1703. doi: 10.2147/CIA.S146009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Endres Heinz G., Kaufmann-Kolle Petra, Steeb Valerie, Bauer Erik, Böttner Caroline, Thürmann Petra. Association between Potentially Inappropriate Medication (PIM) Use and Risk of Hospitalization in Older Adults: An Observational Study Based on Routine Data Comparing PIM Use with Use of PIM Alternatives. PLOS ONE. 2016;11(2):e0146811. doi: 10.1371/journal.pone.0146811. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Baldoni ADO, Ayres LR, Martinez EZ, Dewulf NDLS, Dos Santos V, Pereira LRL. Factors associated with potentially inappropriate medications use by the elderly according to Beers criteria 2003 and 2012. Int J Clin Pharm. 2014;36(2):316–324. doi: 10.1007/s11096-013-9880-y. [DOI] [PubMed] [Google Scholar]
- 25.Napolitano F, Izzo MT, Di Giuseppe G, Angelillo IF. Frequency of inappropriate medication prescription in hospitalized elderly patients in Italy. PLoS One. 2013;8(12):8–14. doi: 10.1371/journal.pone.0082359. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Reich O, Rosemann T, Rapold R, Blozik E, Senn O. Potentially inappropriate medication use in older patients in swiss managed care plans: prevalence, determinants and association with hospitalization. PLoS One. 2014;9(8):23–25. doi: 10.1371/journal.pone.0105425. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Vieira de Lima TJ, Garbin CAS, Garbin AJÍ, Sumida DH, Saliba O. Potentially inappropriate medications used by the elderly: prevalence and risk factors in Brazilian care homes. BMC Geriatr. 2013;13(1):52. doi: 10.1186/1471-2318-13-52. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Hamano J, Tokuda Y. Inappropriate prescribing among elderly home care patients in Japan. J Prim Care Community Health. 2014;5(2):90–96. doi: 10.1177/2150131913518346. [DOI] [PubMed] [Google Scholar]
- 29.Wawruch M, et al. Factors influencing the use of potentially inappropriate medication in older patients in Slovakia. J Clin Pharm Ther. 2008;33(4):381–392. doi: 10.1111/j.1365-2710.2008.00929.x. [DOI] [PubMed] [Google Scholar]
- 30.Spinewine A, Fialová D, Byrne S. The role of the pharmacist in optimizing pharmacotherapy in older people. Drugs Aging. 2012;29(6):495–510. doi: 10.2165/11631720-000000000-00000. [DOI] [PubMed] [Google Scholar]
- 31.Fick DM, Semla TP. 2012 American Geriatrics Society beers criteria: new year, new criteria, new perspective. J Am Geriatr Soc. 2012;60(4):614–615. doi: 10.1111/j.1532-5415.2012.03922.x. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The EHR dataset used during and/or analyzed during the current study are not publicly available due to our IRB policy but are available from the corresponding author upon reasonable request.