Table 1.
Characteristics of included studies (n = 33)
| Study | Country | Design | Setting | Time period | Source of data | Age (years)£ | Sex (%F)◊ | Number of drugs∆ | Population subgroup | Method used to identify DDIs | Classification of DDIs π | Total N | N ≥ 65 years† | n ≥ 65 years with a DDI† | Prevalence estimate [95% CI] |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Abubakar et al. (2021) | Nigeria | Cross-sectional | Outpatient | Jun–Sep 2016 | Medical records | 71.1 (±6.1) | 50.8 | 5.4 (±2.3) | – | 2015 AGS Beers criteria® | (Potentially) clinically important | 244 | 244 | 79 | 32.4% [26.8–38.5]F |
| Bacic-Vrca et al. (2010) | Croatia | Cohort | Outpatient | Mar 2009 | Patient interview, pharmacist/physician record | 73 (65–95) | 70.6 | 5 (2–12) | Arterial hypertension | Lexi-interact® | (Potentially) clinically important | 265 | 265 | 240 | 90.6% [86.4–93.5]F |
| Bazargan et al. (2018) | USA | Cross-sectional | Community | Nov 2015–Feb 2017 | Patient interview, drug inventory method | 75.2 (±7) | 67 | 7.3 (±3.60) | Hypertension | 2015 AGS Beers criteria® | (Potentially) clinically important | 193 | 193 | NR≈ | – |
| Bogetti-Salazar et al. (2016) | Mexico | Cross-sectional | Outpatient | Jan 2007–Jan 2010 | Data from the QOL-AD study | 80.11 (±8.28) | 68.5 | 5.20 (±3.04) | Dementia | Micromedex® | All | 181 | 181 | 107 | 59.1% [51.8–66.0]F |
| Burato et al. (2021) | Italy | Cohort | Community | Jan–Jun 2018 | LHA administrative healthcare data | 77.0 (±0.9) | 56.9 | 16.1% used ≥ 5 prescription drugs | – | Delphi consensus | (Potentially) clinically important | 835,247 | 835,247 | 220,175 | 26.4% [26.3–26.5]F |
| Chen et al. (2020) | China | Cross-sectional | Outpatient | Oct 2018–Apr 2019 | Questionnaire | 42.92 (18–85) | 34.7 | 22.1% had co-medications¥ | HIV | University of Liverpool HIV Drug Interactions Checker | All | 1804 | 163¥ | 11¥ | 6.7% [3.8–11.8]F |
| Faught et al. (2018) | USA | Cohort | Community | 2008–2010 | Medicare claims data | NR | 61.6 | NR | Epilepsy | MultipleA | All | 36,912 | 36,912 | 14,396 | 39.0% [38.5–39.5]G |
| Guthrie et al. (2015) | Scotland | Cross-sectional | Community | 1995 and 2010 | GP prescribing data | 50.1 | 51.5 | 17.2% dispensed ≥ 10 drugs in 2010 | – | British National Formulary | (Potentially) clinically important | 311,811 | 73,522 | 25,071 | 34.1% [33.8–34.4]H |
| Hanlon et al. (2017) | USA | Cross-sectional | Community | 1997–1998 | Data from the Health ABC study | 73.6 (±2.9) | 51.5 | 1.73 (±2.0) ; 9.2% took ≥ 5 drugs | – | MultipleB | (Potentially) clinically important | 3055 | 3055 | 767 | 25.1% [23.6–26.7]F |
| Harasani et al. (2020) | Albania | Cross-sectional | Community | Mar–May 2019 | Medical records, patient interview | 73.5 (8) | 43.1 | NR* | – | 2019 AGS Beers criteria® | (Potentially) clinically important | 174 | 125¥ | 1¥ | 0.8% [0.1–5.5]F |
| Hermann et al. (2021) | Norway | Cross-sectional | Community | NR | Interview, visual inspection, medication list | 78 (±3) | 54 | 43% used ≥ 5 drugs | – | Micromedex® | (Potentially) clinically important | 233 | 197 | 107 | 54.3% [47.3–61.1]F |
| Jazbar et al. (2018) | Slovenia | Cohort | Outpatient | 2015 | Pharmacy claims data | NR | 56.8 | 7 (4–11) | – | Lexi-interact® | (Potentially) clinically important | 1,179,803 | 346,708 | 105,355 | 30.4 [30.2–30.5]F |
| Kerr et al. (2014) | Australia | Cohort | Community | Mar 2007–Nov 2009∑ | Data from the ‘Ageing in General Practice’ study | NR | 58.7 | 6.1 (±3.0) µ | CYP enzyme inhibitor and substrate drugs | Flockhart list of CYP450 DDIs | (Potentially) clinically important | 1045 | 1045 | 65 | 6.2% [4.9–7.9]H |
| Lopez-Picazo et al. (2010) | Spain | Cross-sectional | Community | Mar 2007 | Electronic medical record data (OMI-AP) | NR | 51 | NR* | – | Medications database (BOT) of the CGCOF in Spain | All | 430,525 | 64,579 | 18,405 | 28.5% [28.2–28.8]I |
| Lopez-Rodriguez et al. (2020) | Spain | Cross-sectional | Community | Dec 2016–Jan 2017 | Interview with patient's GP | 69.7 (±2.7) | 55.8 | 7.4 (±2.4) ; 17.9% prescribed ≥ 10 drugs | – | ChecktheMeds® | All | 593 | 589 | 373 | 63.3% [59.4–67.1]F |
| Matos et al. (2020) | USA | Cohort | Community | 2017 | Pharmacy claims data | 75.5 (±10.4) | 70.7 | NR | BPSD | Proprietary CDSS | (Potentially) clinically important | 1190 | 1071 | 725 | 67.7% [64.8–70.4]G |
| Naples et al. (2016) | USA | Cohort | Community | 1998–1999‡ | Data from the Health ABC study | 74.6 (±2.9) | 51.3 | 3.2 (±2.7) | 20-m gait speed recorded | MultipleC | (Potentially) clinically important | 2402 | 2402 | 251 | 10.4% [9.3–11.7]F |
| Nikolic et al. (2014) | Serbia | Cross-sectional | Outpatient | Nov 2011 | Electronic prescription database | NR | 57.8 | 4.66 (±2.10)¥ | – | Drug Interaction Facts® | (Potentially) clinically important | 4467 | 2022¥ | 755¥ | 37.3% [35.3–39.5]H |
| Novaes et al. (2017) | Brazil | Cross-sectional | Community | Oct 2014–Mar 2015 | Interview, questionnaire | 73.80 (±8.019) | 64.5 | 44.6% used ≥ 5 drugs | – | Medscape Drug Interactions Checker | All | 368 | 328¥ | 240¥ | 73.2% [68.1–77.7]F |
| Patel et al. (2018) | USA | Cross-sectional | Community | Oct–Nov 2015 | Patient interview | NR | 62.1 | 5.7 (±3.3) | – | 2015 AGS Beers criteria® | (Potentially) clinically important | 703 | 703 | 54 | 7.7% [5.9–9.9]F |
| Popović et al. (2014) | Croatia | Cohort | Outpatient | 2010 | Electronic database (Croatian Health Insurance Fund) | 77 | 63.2 | All n = 29,418 used ≥ 5 drugs | – | Mimica Matanović and Vlahović-Palčevskii DDI list | (Potentially) clinically important | 29,418 | 29,418 | NRΩ | – |
| Roughead et al. (2010) | Australia | Cross-sectional | Community | Jun–Nov 2005 | Veterans’ Affairs Pharmacy claims data | 78.1 (±10.8) | 45 | 9 (±6) | – | MultipleD | (Potentially) clinically important | 287,074 | 287,074 | 4211 | 1.5% [1.4–1.5]I |
| Santos et al. (2019) | Brazil | Cross-sectional | Community | Apr 2015–Feb 2016 | Pharmacy records | 70.2 (±7.8) | 61.3 | NR* | – | 2015 AGS Beers criteria®; Dumbreck et al. disease-specific DDI list | (Potentially) clinically important | 408 | 285¥ | 13 (Beers)¥ | 4.6% [2.7–7.7]F |
| 79 (Dumbreck)¥ | 27.7% [22.8–33.2]F | ||||||||||||||
| Secoli et al. (2010) | Brazil | Cross-sectional | Community | 2000 | Data from the SABE survey study | NR | 65.5 | NR* | – | Micromedex® | All | 1035 | 531 | 288 | 54.2% [50.0–58.4]G |
| Sell and Schaefer (2020) | Germany | Cross-sectional | Community | Apr 2015 | Brown bag medication review | 72.0 (±9.1) | 51.9 | 10.7 (±3.7) | – | PI-Doc® classification | Unclear | 1090 | 830 | 447¥ | 53.9% [50.5–57.2]F |
| Skaar et al. (2011) | USA | Cohort | Community | 2006 | Medicare Current Beneficiary Survey data | NR | 57 | 8.2 | Medicare beneficiaries with a dental visit | Malone et al., 2004 DDI list | (Potentially) clinically important | 14,361,198 | 14,361,198 | 490,874 | 3.4% [3.4–3.4]F |
| Song et al. (2019) | South Korea | Cross-sectional | Outpatient | 2014ø | National insurance claims data | 59 (±13.2) | 67.3 | 8.0 (±6.7) patients with polypharmacy~ | Cancer | MultipleE | (Potentially) clinically important | 118,258 | 41,697 | 4923 | 11.8% [11.5–12.1]H,# |
| Steinman et al. (2014) | USA | Cross-sectional | Outpatient | 2007 | National Veterans Affairs data linked with Medicare claims data | 75 | 2 | 5 (3–8) | – | Lexi-interact® | (Potentially) clinically important | 462,405 | 462,405 | 139,807 | 30.2 [30.1–30.4]F |
| Teixeira et al. (2012) | Brazil | Cross-sectional | Community | May–Dec 2010 | Electronic medical record data | 64.1 (±10.6) | 65.9 | NR* | – | Micromedex® | All | 827 | 394 | 253 | 64.2% [59.4–68.8]F |
| Tragni et al. (2013) | Italy | Cross-sectional | Community | Jan 2004–Aug 2005 | Pharmacy claims data | NR | 51.2 | NR* | – | Micromedex® | (Potentially) clinically important | 2,115,326 | 456,852 | 88,394 | 19.3% [19.2–19.5] H§ |
| Trevisan et al. (2019) | Italy | Cohort | Community | Feb 2002–Feb 2004 | GP databases and records | 76 (71–80) | 61.1 | 53.5% used ≥ 3 prescription drugs | Mild cognitive impairment | INTERcheck® | All | 342 | 342 | 154 | 45.0% [39.8–50.3]F |
| Truong et al. (2019) | Vietnam | Cross-sectional | Outpatient | Aug 2018 | Prescription database | 63.4 (±11.3) | 64.3 | 6.8 ± (2.3); 85.7% used ≥ 5 drugs¥ | Coronary artery diseases | Drugs.com Interactions Checker | (Potentially) clinically important | 683 | 314¥ | 62¥ | 19.7% [15.7–24.5]F |
| Yazdanshenas et al. (2016) | USA | Cross-sectional | Community | 2013 | Patient interview, drug inventory method | NR | 65 | NR | – | Drugs.com Interactions Checker | Unclear | 400 | 400 | 211 | 52.7% [47.8–57.6]F |
AGS American Geriatrics Society, BPSD Behavioural and Psychological Symptoms of Dementia and prescribed an atypical antipsychotic, CDSS clinical decision support system, CGCOF General Council of Official Colleges of Pharmacists, CYP cytochrome P450, F female, GP general practitioner, NR not reported, NR* not reported for the ≥ 65 years of age population, n numerator (number aged ≥ 65 years with a DDI), N denominator (sample size, aged ≥65 years)
£Age data for the full study population, presented as mean; mean (± standard deviation); mean (minimum-maximum); median (interquartile range); or median (minimum-maximum)
◊Data on sex are for the full study population and were extracted directly or estimated from the data reported in the published study
∆Data on the number of drugs used are reported for the population aged ≥65 years, and are presented as mean; mean (± standard deviation); median (minimum-maximum); or median (interquartile range), unless otherwise stated
∑Per ANZCTR registry (trial ID ACTRN12607000117415)
øDDI prevalence data for ≥65 years of age population reported in the published study for 2014 only
¥Data provided by corresponding author
µRefers to the cohort of study participants with a potential CYP DDI
~Definition of polypharmacy not provided in this study
πA full description of the DDI classification for each study is included in Appendix 6 of the ESM
†A full description of the numerator and denominator for each study is provided in Appendix 7 of the ESM
≈Almost 23% (43 out of 188 potentially inappropriate medications) of potentially inappropriate medications were due to drugs with potential DDIs
ΩThe total number of drug combinations potentially leading to serious DDIs was 33,321
#9.6% is reported in Table 6 of the published study; however, the corresponding denominator for this % does not reconcile with the data reported in Table 1, see Appendix 7 of the ESM
‡DDI prevalence data from year 2 of this study were extracted. Hanlon et al., 2017 used the same data source (Health ABC study), but the authors report data from year 1 of the study
AUS Food and Drug Administration-approved package insert as the primary source, supplemented with the literature; Medscape Drug Interactions Checker; as well as consulting lists of interactions from other proprietary services: Micromedex®; Clinical Pharmacology; and Lexicomp®
BLiterature and 2015 AGS Beers criteria®
C2015 AGS Beers criteria®, Mimica Matanovic and Vlahovic-Palcevski protocol DDI list, and other expert panel consensus explicit criteria from the literature
DVidal, British National Formulary, Drug Interaction Facts, and Micromedex® Drug-Reax
EDrug Interaction Facts®, Micromedex®, Lexi-interact®
FDispensing/prescribing pattern for DDI prevalence: all drugs dispensed/prescribed
GDispensing/prescribing pattern for DDI prevalence: concomitant
HDispensing/prescribing pattern for DDI prevalence: co-prescribed
IDispensing/prescribing pattern for DDI prevalence: concurrent
§Tragni et al., 2013 DDI prevalence for concomitantly dispensed/prescribed drugs: n = 120,921 (26.5% [26.3–26.6])