search for




 

Opioid Injection Prescription Rates Over an Eight-Year Period for the Non-Cancer Patients in South Korea: A Population-Based Study
Yakhak Hoeji 2024;68(6):446-453
Published online December 31, 2024
© 2024 The Pharmaceutical Society of Korea.

Miryoung Kim*,***,*****,†, Siin Kim**,†, and Hae Sun Suh***,****,*****,#

*College of Pharmacy, Pusan National University
**Department of Pharmacy, College of Pharmacy, Woosuk University, Jeollabuk-do Woosuk University
***College of Pharmacy, Kyung Hee University
****Department of Regulatory Science, Graduate School, Kyung Hee University
*****Institute of Regulatory Innovation through Science, Kyung Hee University
Correspondence to: #Hae Sun Suh, Ph.D., College of Pharmacy, Department of Regulatory Science, Graduate School, Institute of Regulatory Innovation through Science, Kyung Hee University, Seoul, Republic of Korea
Tel: +82-2-961-9492, Fax: +82-2-961-9580
E-mail: haesun.suh@khu.ac.kr

These authors contributed equally to this work.
Received August 3, 2024; Revised September 10, 2024; Accepted September 13, 2024.
Abstract
The objective of this study was to assess opioid injections prescription rate in Korea. This study utilized the National Health Insurance Service-National Sample Cohort data. The general population consisted of non-cancer outpatients with at least one injection prescription, and the opioid population consisted of non-cancer outpatients with at least one opioid injection prescription from 2008 to 2015. We calculated the total injection rate by dividing the number of injection prescriptions by the number of outpatient visits. The opioid injection rate was calculated similarly, using only opioid injection prescriptions. Stratification was based on sex, age, institution location, and type, with annual trends assessed using the Cochran-Armitage test. Opioid-injections constituted 24.62% of total injection prescriptions. Over the eight years, tramadol was the most frequently prescribed opioid, accounting for approximately 98% of opioid-injection prescriptions. Of tramadol, 93% was prescribed in the clinic, primarily to treat inflammatory-related conditions. The total injection rates for the opioid population were significantly higher than those for the general population during all time periods (27.39% vs. 35.51% in 2015, p<0.001). Although the opioid injection rate decreased from 9.10% in 2008 to 7.20% in 2015 (p<0.001), the proportion of opioid-injections among the total injection prescriptions remained relatively consistent. Opioid injection rates were notably higher among females, elderly, rural residents, and clinic visits (p<0.001). Despite the ongoing decline in Korea’s annual opioid prescription rates, the seriousness of this matter cannot be underestimated. Further investigations are imperative to ascertain whether the prescription of opioid injections correlates with an elevated risk of opioid abuse.
Keywords : Analgesics, opioid, Opioid, Tramadol, Injections, Prescriptions, Medication Therapy Management
Introduction

The global opioid crisis has manifested in various trends, notably encompassing elevated opioid prescription rates, a rising trend of non-medical prescription opioid use, and an alarming surge in associated morbidity and mortality (Volkow et al., 2019). Of particular concern is the prescription of opioids for non-cancer pain, which has raised worries about the indiscriminate use of these drugs and increased the economic burden (Dhalla et al., 2011; M. Kim et al., 2022; Shipton et al., 2018). According to the United Nations Office on Drugs and Crime’s report on West Africa, the trafficking and non-medical use of tramadol have reached epidemic proportions (Organization, 2018; Salm-Reifferscheidt, 2018). This can be attributed to its affordability, wide availability, and the public perception that it is safe and non-addictive as a legal medicine.

South Korea has long been recognized for having relatively minimal public concerns surrounding opioids (Lee, 2019). Nevertheless, emerging apprehensions regarding potential harm have spurred investigations into opioid prescription patterns within the country (Cho et al., 2021; J. Kim et al., 2022; Noh et al., 2022). Over time, the opioid prescription rates in South Korea has gradually increased, surging from 347.5 per 1,000 individuals in 2009 to 531.3 per 1,000 individuals in 2019 (Cho et al., 2021). One study reported a 1.1-fold increase in the prevalence of potentially inappropriate opioid prescriptions between 2012 and 2018 (Noh et al., 2022).

Meanwhile, South Korea’s injection prescription rate is notably high. In 2015, the Health Insurance Review and Assessment Service of South Korea reported an injection prescription rate of 18% (Statistics Korea). The indicator of injection prescription rates is a yardstick employed to gauge healthcare service quality within medical institutions, as outlined by the World Health Organization (WHO) (Ofori-Asenso, 2016; Tefera et al., 2021). The WHO proposes an optimal value of less than 20% for developing countries (Ofori-Asenso, 2016; Tefera et al., 2021). Global experts from Australia, England, and the US recommend an optimal injection prescription rate of less than 5% (Eui-kyung Lee, 2001).

Given the notable prevalence of injection prescriptions in South Korea, it is reasonable to expect a correspondingly high opioid injection prescription rates. However, research on the prescription rate of opioid injection is lacking. Most studies have focused on oral opioids or neglected to differentiate between administration routes. Increased opioid injection prescription rates, similar to those of oral opioids, may contribute to increased misuse or abuse. Considering the global issues associated with opioid injections and South Korea's high opioid injection prescription rates, it is crucial to investigate trends in prescription opioid injection.

This study investigated the opioid injection prescription rates in the Korean population and identified prescription trends based on patient and institutional characteristics.

Methods

Data source and study population

This retrospective cross-sectional study was conducted using data from the National Health Insurance Service-National Sample Cohort (NHIS-NSC) version 2.0 in South Korea (NHIS-2022-2- 136). The NHIS-NSC is a population-based cohort that provides representative data for research and policy development (Kim et al., 2014). This study’s general population comprised non-cancer outpatients who had received one or more injections prescriptions between 2008 and 2015. For the opioid population, we selected non-cancer outpatients who had received one or more opioid injection prescriptions between 2008 and 2015. Opioid injection prescriptions were chosen based on the Drug Enforcement Administration (II) Schedule II-IV opioids and Korean guidelines, including fentanyl, hydromorphone, pethidine (meperidine), morphine, oxycodone, pentazocine, and tramadol (Kim et al., 2021; Sullivan et al., 2008). We identified non-cancer patients by excluding individuals with cancer diagnoses from the claims data. We excluded patients under 18 years of age as of 2008 and those diagnosed with any cancer between 2008 and 2015. Patients with cancer were excluded because they may have required repeated opioid injections for pain management, which could have significantly influenced the injection rates. This study followed the guidelines outlined in the Declaration of Helsinki and was approved by the Kyung Hee University Institutional Review Board, which granted exemption from ethical review. This exemption was based on the study’s non-interventional nature as secondary database research (Approval number: KHSIRB-21-529 (EA)).

Outcome measures

The baseline characteristics of the opioid population were assessed as of 2015 for each drug type. Patient-level information, including sex, age, and insurance type (National Healthcare Insurance (NHI) and Medical Aid programs), was collected. At the prescription level, we examined the most frequent major diagnoses associated with the prescription of opioid injections in 2015 using the Korean Classification of Disease codes set based on the International Classification of Diseases 10th edition.

The total injection prescription rates were assessed annually in both general and opioid populations using the following equation:

Furthermore, the opioid injection prescription rates were examined annually within the opioid population, employing the subsequent equation:

The opioid injection prescription rates were presented for subgroups based on sex, age, insurance type, institution location (urban and rural), and institution type (tertiary hospitals, general hospitals, public hospitals, clinics, and others, such as oriental hospitals and dentists’ clinics). Additionally, the adjusted total injection prescription rates for both the general and opioid populations were calculated, with the aim of excluding mandatory prescription injections that cannot be substituted with oral medications. To calculate the adjusted injection prescription rate, the total number of overall injection prescriptions was calculated by subtracting the essential prescription injections from the total, and then dividing the result by the total number of patient visits. The essential prescription injections included anticancer injections, injections for inspection, hematopoietic injections, and insulin.

Statistical Analysis

The characteristics of the study population are expressed as proportions or mean with standard deviations (SD). Categorical variables were analyzed using the chi-squared test or Fisher’s exact test, whereas continuous variables were analyzed using Student’s t-test or ANOVA. The chi-square test was used to examine differences in the opioid injection prescription rates, and the Cochran-Armitage test for trends was used to explore linear trends in injection rates. A p-value <0.05 was considered statistically significant. All statistical analyses were performed using SAS® Enterprise Guide version 9.4.

Results

Baseline characteristics at the patient and prescription level

Among the total number of injection prescriptions (n=19,315,148) in the study population from 2008 to 2015, 24.62% (n=4,753,802) were opioid injection prescriptions (Appendix A). The composition and proportion of opioid injection prescriptions remained consistent each year. As of 2015, the study population included 196,319 patients, with 56.88% female and a mean age of 49.95± 16.61 years (mean±SD) (Table 1). There were statistically significant differences in sex and age between the different drugs (p<0.001).

Baseline characteristics of patients prescribed opioid injections by opioid types in 2015

Total (N=196,319) Tramadol (N=189,017) Pethidine (N=11,228) Morphine (N=418) Fentanyl (N=315) p-valuea
Patients-level information
Female, n (column %) 111,673 (56.88) 108,417 (57.36) 5,261 (46.86) 196 (46.89) 213 (67.62) <0.001
Age (years), mean (SD) 49.95 (16.61) 49.90 (16.72) 52.36 (13.42) 49.46 (16.24) 44.59 (14.81) <0.001
Insurance type
NHI, n (column %) 189,846 (96.70) 182,670 (96.64) 10,982 (97.81) 401 (95.93) 304 (96.51) <0.001
Medical Aid, n (column %) 6,473 (3.30) 6,347 (3.36) 246 (2.19) 17 (4.07) 11 (3.49) <0.001
Prescription-level information
No. prescriptions, n (row %) 578,139 (100.00) 565,279 (97.71) 12,198 (2.11) 668 (0.12) 360 (0.06) -
Institution type Tertiary hospitals, n (column %) 3,253 (0.56) 1,100 (0.19) 1,711 (14.03) 380 (56.89) 52 (14.44) <0.001
General hospitals, n (column %) 44,278 (7.66) 36,319 (6.43) 7,425 (60.87) 284 (42.51) 249 (69.17) <0.001
Clinics, n (column %) 530,095 (91.69) 526,977 (93.29) 3,058 (25.07) 3 (0.45) 57 (15.83) <0.001
Public hospitals, n (column %) 355 (0.06) 348 (0.06) 4 (0.03) 1 (0.15) 2 (0.56) <0.001
Othersb, n (column %) 158 (0.03) 158 (0.03) 0 (0.00) 0 (0.00) 0 (0.00) -
No. prescriptions per person, mean (SD) 1.4 (5.65) 2.99 (5.65) 1.09 (1.13) 1.60 (4.50) 1.14 (0.72) <0.001

The patients overlapped in each drug; Hydromorphone (n=10) and oxycodone (n=1) are not shown in the table.

aThe chi-squared test or Fisher’s exact test was used for categorical variable analysis, and ANOVA was used for continuous variables.

bIncluded oriental hospitals and dentist clinics

Abbreviations: NHI, national health insurance; No, number of; SD, Standard deviation.



Table 1 also shows a breakdown of opioid injection prescriptions in 2015, showing the type and proportion of each. Tramadol accounted for the most significant proportion (97.71%), followed by pethidine (2.11%), morphine (0.12%), and fentanyl (0.06%). Hydromorphone (n=10) and oxycodone (n=1) had fewer than ten prescriptions. The mean number of opioid injection prescriptions per person in 2015 varied by drug type (p<0.001), with tramadol having the highest mean (2.99±5.65), followed by pethidine (1.09±1.13), morphine (1.60±4.50), and fentanyl (1.14±0.72). The type and proportion of opioid injections differed significantly across institutions (p<0.001). Tramadol injection prescriptions were most prevalent in clinics (93.29%), whereas pethidine injections were prescribed predominantly in general hospitals (60.87%), followed by clinics (25.07%) and tertiary hospitals (14.03%). Tertiary hospitals (56.89%) and general hospitals (42.51%) were the primary prescribers of morphine injections, whereas fentanyl injections were most prescribed in general hospitals (69.17%), followed by clinics (15.83%) and tertiary hospitals (14.44%). Although most opioid injection prescriptions were used for pain-related reasons, each drug was associated with various diagnoses (Fig. 1). Tramadol has also been used to treat inflammation-related diseases such as acute bronchitis (10.4%), acute tonsillitis (4.5%), and acute pharyngitis (2.5%). The top 10 diagnoses for pethidine (65.7%) were predominantly related to gastrointestinal pain. Fentanyl was primarily used to treat diseases of the genitourinary system (26.1%) and conditions related to pregnancy and childbirth (12.5%).



Fig. 1. Top 10 Diagnoses associated with opioid injection prescriptions for tramadol, pethidine, morphine, and fentanyl in 2015.

Trend in opioid injection prescription rates

Figure 2 illustrates annual trends in opioid injection prescription rates. The opioid injection prescription rates decreased from 9.10% in 2008 to 7.20% in 2015 (p<0.001). Detailed results for the entire study period are presented in Appendix B. The total injection prescription rates saw a decline in both the general population and the opioid population: in the general population, from 31.5% in 2008 to 25.51% in 2015 (p<0.001); and in the opioid population, from 33.49% in 2008 to 27.39% in 2015 (p<0.001). The adjusted total injection prescription rates in 2015 stood at 23.73% for the general population and 25.63% for the opioid population, respectively (p<0.001). Throughout all the periods, the total injection prescription rates in the opioid population were significantly higher than those in the general population, as did the adjusted prescription rate of total injections (p<0.001 for each year). The proportion of opioid injections among the adjusted total injections exhibited minimal change (28.00% in 2008 and 28.11% in 2015; p=1.00).



Fig. 2. Total injection prescription rates and opioid injections prescription rates from 2008 to 2015.
All injection prescription rates-indicated by the blue, green, and orange lines-experienced significant declines from 2008 to 2015 (p<0.001). The proportion of opioid injections among the total injections-indicated by histogram-remained relatively stable at approximately 28%. Prescription rates were calculated by dividing the total number of prescriptions by the total number of visits per year. The general population is characterized as non-cancer outpatients who received one or more injection prescriptions, while the opioid population encompasses non-cancer outpatients who were issued one or more opioid injection prescriptions.

Opioid injection prescription rates by subgroups

The annual trend in the opioid injection prescription rates for the different subgroups are presented in Fig. 3. The opioid injection prescription rates exhibited a decreasing year-by-year trend in both males and females (p<0.001) (Fig. 3A). Females consistently had significantly higher the opioid injection prescription rates than males in all periods (e.g., 9.49% vs. 8.35% in 2008 and 7.34% vs. 6.98% in 2015, p<0.001 in each year).



Fig. 3. Opioid injection prescription rates within subgroups categorized by (A) sex; (B) age; (C) insurance type; (D) institution location; and (E) institution type.
Statistically significant differences were observed across all subgroups and for all periods (p<0.001)

The opioid injection prescription rates decreased annually for all age groups except for individuals in their 20s (p<0.001). Among all the age groups, those in their 80s had the highest rate, followed by those in their 70s (Fig. 3B). Those in their 20s did not exhibit a statistically significant decrease or increase in the opioid injection prescription rates between 2008 and 2010 (p=0.472). However, from 2011 onwards, those in their 20s showed a statistically significant increase from 5.89% in 2011 to 6.77% in 2015 (p<0.001).

The opioid injection prescription rates decreased over the years for all insurance types and institutional locations (p<0.001) (Fig. 3C and 3D). The rates for the Medical Aid program were consistently higher than those for the NHI program in all periods: 11.42 and 8.93% in 2008 and 8.33 and 7.14% in 2015. Rural areas also had significantly higher the opioid injection prescription rates than urban areas throughout all periods: 10.57 and 7.45% in 2008; 7.94 and 6.40% in 2015.

The opioid injection prescription rates varied across different institutions (Fig. 3E). The rates decreased in tertiary hospitals (p<0.001), general hospitals (p<0.001), clinics (p<0.001), and other (i.e., oriental hospitals and dentist clinics) (p=0.007). Conversely, public hospitals tended to have higher the opioid injection prescription rates (p<0.001). Clinics consistently had significantly higher injection rates than other types of institutions during all periods (p<0.001). The detailed results of the opioid injection prescription rates for each subgroup are provided in Appendix B.

Discussion

This study provides evidence that opioid injection prescriptions rates per outpatient visit in South Korea decreased annually by approximately 1.9% from 2008 to 2015. However, the proportion of opioid injections among the total number of injections remained consistent high at approximately 28%. Our findings revealed distinct patterns in the opioid injection prescription rates based on sex, age, insurance type, location of the institution, and institution type. Specifically, rates were higher for females than for males, older individuals than younger ones, rural areas than urban areas, and clinics than tertiary hospitals, general hospitals, and other types of institutions (eg, oriental hospitals and dentist clinics).

Since 2002, the HIRA in South Korea has managed the quality of healthcare services in healthcare institutions, including monitoring drug utilization patterns, such as prescription rates of injections. Prescription rates of injections at the institutional level in Korea decreased from 20% in 2011 to 18% in 2015, as reported by the HIRA. Although these rates are within the recommended standards of the WHO for developing countries, which are below 20%, they are substantially higher than the threshold of 5% recommended by global experts in Organization for Economic Co-operation and Development countries such as Australia, England, and the United States (Eui-kyung Lee, 2001; Ofori-Asenso et al., 2016; Statistics Korea). Additionally, the prescription rates of injections in South Korea were higher than those reported in countries such as Egypt (10% in 2010) and upper-middle and high-income countries such as Mexico, Brazil, and Malaysia (11% from 2006 to 2009) (Akl et al., 2014; Ofori- Asenso et al., 2016; World Health Organization, 2009). A direct comparison between the results of this study and the HIRA data is not appropriate because the HIRA reports the average opioid injection prescription rates at the institutional level. However, our findings, particularly the adjusted total injection prescription rates of the general population, which decreased from 30% in 2008 to 24% in 2015, are consistent with the trends observed in HIRA reports.

Notably, approximately 98% of the opioid injection prescriptions in our study were for tramadol, predominantly prescribed in the clinics (93% of all institutions). Tramadol injections are commonly used to reduce propofol dosage during surgery or alleviate postoperative pain (James et al., 1996; Pang et al., 1999). However, our findings revealed that 21% of tramadol injections in Korea were administered to outpatients with relatively mild inflammation, such as bronchitis, tonsillitis, upper respiratory inflammations, and pharyngitis. While we cannot confirm that tramadol was specifically prescribed for treating these inflammatory conditions, an association between tramadol use and the treatment of mild inflammations cannot be ruled out. Given the more severe adverse events, such as nausea, dizziness, and drowsiness, commonly reported with tramadol compared to nonsteroidal anti-inflammatory drugs, caution should be exercised when using tramadol for relatively mild inflammatory conditions (Scott & Perry, 2000). Additionally, a study found that among patients aged 50 years and older, the hazard ratio of death associated with tramadol compared to naproxen was 1.71 (95% confidence interval [CI], 1.41-2.07), and the hazard ratio of mortality compared to diclofenac was 1.88 (95% CI, 1.51-2.35) (Zeng et al., 2019).

Although more caution is required, one of the reasons for the widespread and indiscriminate use of tramadol is its easy accessibility compared with other opioids. Unlike the United States, the United Kingdom, and China, tramadol is not classified as a narcotic in Korea. Although tramadol has a lower potential for dependence than other opioids, it is crucial not to overlook its potential for abuse or misuse. Reports indicate prescription misuse rates of 4.6% for tramadol and 6.9% for morphine as of 2017 in the United States (Reines et al., 2020).

According to Musich S. et al, in patients aged 65 years and older, the hazard ratio (HR) for falls/hip fractures among continuing tramadol users compared to non-users was 1.48 (95% CI: 1.35-1.61). In our study, opioid injections were more frequently prescribed to elderly patients. It is important to consider that the risk of adverse effects from opioid injections, particularly tramadol, may increase in the elderly, as the injectable form reaches a higher concentration than the oral form.

Patients enrolled in the Medical Aid program had higher opioid injection prescription rates. This may be attributed to the lower economic burden associated with healthcare utilization under this program compared to the NHI program. Regarding the location of the healthcare institutions, the prescription rate of opioid injection was higher in rural areas than in urban areas. This finding is consistent with that of a previous study, which reported an odds ratio of 0.3 (95% CI: 0.1-0.8) for the injection rate in urban areas compared to rural areas (Choi et al., 2012). According to the Statistical database of the Korean Statistical Information Service, clinics had the highest rate of approximately 20% in 2015 (Statistics Korea) among the average injection prescription rates per institution. Similarly, our study revealed higher opioid injection prescription rates for clinics (9% in 2015) compared to other types of institutions (1%-5% in 2015) and overall opioid injection prescription rates (7% in 2015). Considering that the injection prescription rate can be influenced by physicians' misconceptions and patients’ strong demands, it is crucial to provide adequate education to physicians and patients, particularly in clinical settings.

The present study has several limitations. First, the clinical appropriateness of the opioid injection prescriptions was not considered. Due to the lack of clinical information in the claims data, it was challenging to determine whether the prescriptions were clinically appropriate for each case. Second, because we analyzed the main diagnosis, the reasons for medication use may vary across different clinical settings. Third, a direct comparison with previous studies that analyzed injection rates per institution was limited. Although previous studies focused on evaluating the quality of healthcare institutions by examining injection rates per institution, our analysis was conducted at the population level to identify patterns based on patient characteristics and prescriptions. Fourth, due to the utilization of sample cohort data spanning from 2008 to 2015, the analysis of more current treatment patterns was not feasible. Therefore, further studies using updated data are warranted.

To the best of our knowledge, this is the first study to provide insight into the treatment patterns of prescription opioid injections using real-world data in Korea. Given that this study's cohort sample represents the Korean population, the findings can be considered highly generalizable. We hope that understanding these treatment patterns will contribute to efforts to reduce the likelihood of misuse or abuse of opioid injections.

Conclusion

While the rate of opioid injection prescriptions has been declining annually, consistent with the overall decrease in injection prescriptions, the proportion of opioid injections among all injections remains high. In recent years, prescription rates have been notably elevated among individuals in their 20s, indicating a need for further research into the potential side effects and clinical appropriateness of these prescriptions. Further research is warranted to investigate the potential impact of higher opioid injection prescription rates on abuse, misuse, and mortality risks.

Acknowledgment

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (Ministry of Science and ICT) [grant numbers NRF-2020R1F1A1069526]; and the Ministry of Food and Drug Safety in 2024 [grant number 21153MFDS601].

Conflict of Interest

The authors report no conflicts of interest in this work.

Authors’ Positions

Miryoung Kim : Postdoc

Siin Kim : Professor

Hae Sun Suh : Professor

References
  1. Akl OA, El Mahalli AA, Elkahky AA, Salem AM (2014) WHO/INRUD drug use indicators at primary healthcare centers in Alexandria, Egypt. Journal of Taibah University Medical Sciences 9(1):54-64.
    CrossRef
  2. Cho NR, Chang YJ, Lee D, Kim JR, Ko DS, Choi JJ (2021) Trends in opioid prescribing practices in South Korea, 2009-2019: Are we safe from an opioid epidemic?. Plos one 16(5):e0250972.
    Pubmed KoreaMed CrossRef
  3. Choi KH, Park SM, Lee JH, Kwon S (2012) Factors affecting the prescribing patterns of antibiotics and injections. Journal of Korean Medical Science 27(2):120-127.
    Pubmed KoreaMed CrossRef
  4. Dhalla IA, Persaud N, Juurlink DN (2011) Facing up to the prescription opioid crisis. BMJ 343:d5142.
    Pubmed CrossRef
  5. Lee EK, Jang SM, Shin CG, Park JY (2001) Separation of Prescription and Dispensing: Changes in Pharmaceutical Costs and Related Policy Issues, Korea Institute for Health and Social Affairs.
  6. James MF, Heijke SA, Gordon PC (1996) Intravenous tramadol versus epidural morphine for postthoracotomy pain relief: a placebocontrolled double-blind trial. Anesthesia & Analgesia 83(1):87-91.
    CrossRef
  7. Kim J, Shin SJ, Yoon J, Kim HS, Lee JW, Kim YS, Kim Y, You HS, Kang HT (2022) Recent trends in opioid prescriptions in Korea from 2002 to 2015 based on the Korean NHIS-NSC cohort. Epidemiology and Health 44.
    Pubmed KoreaMed CrossRef
  8. Kim L, Kim JA, Kim S (2014) A guide for the utilization of Health Insurance Review and Assessment Service National Patient Samples. Epidemiology and Health 36:e2014008-e2014008.
    Pubmed KoreaMed CrossRef
  9. Kim M, Kim S, Suh HS (2022) Economic burden of opioid misuse focused on direct medical costs. Frontiers in Pharmacology 13:928890.
    Pubmed KoreaMed CrossRef
  10. Kim S, Kim E, Suh HS (2021) Cost-Effectiveness of an Opioid Abuse-Prevention Program Using the Narcotics Information Management System in South Korea. Value in Health 24(2):174-181.
    Pubmed CrossRef
  11. Lee JH (2019) The opioid epidemic and crisis in US: how about Korea?. The Korean Journal of Pain 32(4):243-244.
    Pubmed KoreaMed CrossRef
  12. Noh Y, Heo KN, Yu YM, Lee JY, Ah YM (2022) Trends in potentially inappropriate opioid prescribing and associated risk factors among Korean noncancer patients prescribed non-injectable opioid analgesics. Therapeutic Advances in Drug Safety 13:20420986221091001.
    Pubmed KoreaMed CrossRef
  13. Ofori-Asenso R (2016) A closer look at the World Health Organization's prescribing indicators. Journal of Pharmacology and Pharmacotherapeutics 7(1):51-54.
    Pubmed KoreaMed CrossRef
  14. Ofori-Asenso R, Brhlikova P, Pollock AM (2016) Prescribing indicators at primary health care centers within the WHO African region: a systematic analysis (1995-2015). BMC Public Health 16(1):1-14.
    Pubmed KoreaMed CrossRef
  15. Organization WH (2018 September 24-25) Fifth WHO‐UNODC expert consultation on new psychoactive substances: addressing the challenges of non‐medical use of opioids, meeting report, WHO Headquarters, Geneva, Switzerland.
    CrossRef
  16. Pang WW, Huang PY, Chang DP, Huang MH (1999) The peripheral analgesic effect of tramadol in reducing propofol injection pain: a comparison with lidocaine. Regional Anesthesia and Pain Medicine 24(3):246-249.
    CrossRef
  17. Reines SA, Goldmann B, Harnett M, Lu L (2020) Misuse of Tramadol in the United States: An Analysis of the National Survey of Drug Use and Health 2002-2017. Substance Abuse:. Research and Treatment 14:1178221820930006.
    Pubmed KoreaMed CrossRef
  18. Salm-Reifferscheidt L (2018) Tramadol: Africa's opioid crisis. The Lancet 391(10134):1982-1983.
    CrossRef
  19. Scott LJ, Perry CM (2000) Tramadol. Drugs 60(1):139-176.
    Pubmed CrossRef
  20. Shipton EA, Shipton EE, Shipton AJ (2018) A review of the opioid epidemic: what do we do about it?. Pain and Therapy 7:23-36.
    Pubmed KoreaMed CrossRef
  21. Statistics. Statistical database of Korean Statistical Information Service (KOSIS). Retrieved Sep 20 from https://kosis.kr/eng/
  22. Sullivan MD, Edlund MJ, Fan MY, DeVries A, Braden JB, Martin BC (2008) Trends in use of opioids for non-cancer pain conditions 2000-2005 in commercial and Medicaid insurance plans: the TROUP study. Pain 138(2):440-449.
    Pubmed KoreaMed CrossRef
  23. Tefera BB, Getachew M, Kebede B (2021) Evaluation of drug prescription pattern using World Health Organization prescribing indicators in public health facilities found in Ethiopia: systematic reviews and meta-analysis. Journal of Pharmaceutical Policy and Practice 14(1):1-10.
    Pubmed KoreaMed CrossRef
  24. Volkow ND, Icaza MEMM, Poznyak V, Saxena S, Gerra G, Network UWIS (2019) Addressing the opioid crisis globally. World Psychiatry 18(2):231-232.
    Pubmed KoreaMed CrossRef
  25. World Health Organization (2009) Medicines use in primary care in developing and transitional countries: fact book summarizing results from studies reported between 1990 and 2006.
    CrossRef
  26. Zeng C, Dubreuil M, LaRochelle MR, Lu N, Wei J, Choi HK, Lei G, Zhang Y (2019) Association of tramadol with all-cause mortality among patients with osteoarthritis. JAMA 321(10):969-982.
    Pubmed KoreaMed CrossRef


December 2024, 68 (6)
Full Text(PDF) Free

Social Network Service
Services

Cited By Articles
  • CrossRef (0)

Funding Information