In older adults, the consumption of potentially inappropriate medications (PIMs) is an essential concern that contributes to serious medication-related problems. Inappropriate prescribing signifies the prescription of medication that significantly aggravates the probability of adverse drug events (ADEs) whereas, PIMs refer to the categories of medications which possibly damage the positive clinical outcomes through potential ADEs that outweighs the benefits, and they typically ought to be avoided, especially within the older population [1]. According to the demographic survey of 2011, there are approximately 104 million senior individuals (60 years and above) in India, comprising of 53 million females and 51 million male citizens [2].

The global occurrence of potentially inappropriate medication (PIM) usage among older adults is substantial, reaching nearly 37%, with an upward trend over the past two decades. In the last ten years, the implementation of PIMs in senior citizens' outpatient settings has exceeded 40%, with prevalence ranging from 14% to 56.3% [3].

PIM utilization varies across continents: Africa (47%), South America (47%), Asia (37%), Europe (35%), North America (29%), and Oceania (24%) [3]. In India, PIM use affects approximately 28% of the elderly population, with regional variations: East (23%), West (33%), North (18%), and South (32%). Among those aged 70 years and older, the PIM usage rate is 35%. Individuals consuming prescribed drugs (≥5 drugs per day) show a prevalence of 27%, and those using a higher count of PIMs (≥3) have a prevalence of 29% [4]. During hospitalization, hyper polypharmacy reaches 37%, with higher PIM usage in private healthcare facilities (31%) compared to government hospitals (25%) [4].

The rationale for this study on the use of potentially inappropriate medications (PIMs) in older adults, based on the Beers Criteria (BC), is to enhance patient safety, health outcomes, and quality of care. The BC is a widely recognized tool for identifying PIMs, aimed at reducing complications and adverse drug events (ADEs) in the elderly. Inappropriate medication use in this population is associated with increased risks of falls, hospitalizations, and mortality. By investigating and addressing the factors contributing to inappropriate prescribing, healthcare providers can improve medication selection and prescribing practices, ultimately enhancing the overall treatment and quality of life for older patients. This study seeks to systematically assess prescribing trends and the prevalence of PIMs in elderly prescriptions, providing evidence-based insights for optimizing geriatric pharmacotherapy [4].

The high prevalence of potentially inappropriate medications (PIMs) among elderly populations is a growing public health concern. Dedhiya et al. (2010) reported that 42% of senior citizens in Indiana Medicaid nursing homes were prescribed PIMs, which led to a 27% increase in hospitalization and a 46% rise in mortality rates, underscoring the urgency for intervention strategies [5]. Similarly, Fick et al. (2008) found that 40% of individuals aged 65 and older received PIM prescriptions, with 14% experiencing drug-related problems, highlighting the need for interdisciplinary approaches to reduce PIM use [6]. A meta-analysis by Morin et al. (2016) revealed that PIM utilization in nursing homes grew from 30% in the 1990s to 50% after 2005, indicating a rising concern over PIM use among the elderly [7]. Tosato et al. (2014) further emphasized the prevalence of PIMs in hospitalized elderly patients, noting significant associations between PIM use, adverse drug reactions, and decreased physical well-being, thus advocating for the use of combined criteria in assessing PIMs [8]. In the U.S., Davidoff et al. (2015) observed that 43% of seniors had at least one PIM prescription, though a slight decline in prevalence was noted from 2006 to 2010, suggesting that targeted interventions could be effective [9]. Similarly, Akazawa et al. (2010) highlighted that 44% of elderly patients in Japan were prescribed PIMs, which led to higher hospitalization rates and increased medical costs, further stressing the healthcare burden posed by PIMs in older adults [10]. The primary objectives of the study were to estimate the prevalence of PIM use among the elderly patients in a private tertiary hospital and examine the association of PIMs between socio-demographic factors.

The study employed a cross-sectional design, targeting older adults aged 60 years and above over a six-month period from July 2023 to January 2024. The inclusion criteria required participants to be 60 years or older and willing to provide informed consent, while those under 60 years of age or unwilling to consent were excluded. Participants were recruited through convenient sampling from in-patients at a private teaching hospital, ensuring a focused approach to capturing relevant data from the target population.

The sample size for the study was calculated to be 290 using the Raosoft calculator, with a 95% confidence level, a 5% margin of error, and a 50% response rate. The Case Collection Form (CCF) was carefully designed in English and organized into three sections: patient information, drug interactions, and current medications/PIMs. To ensure accuracy and reliability, the form was validated by experts in geriatrics, pharmacology, and pharmacy practice, and was also reviewed by the project review committee and the institutional review board. Ethical approval was obtained from the GCP Institutional Review Board (ref. No. GCPK/PD23/01, dated 22.08.2023), and informed consent was secured from all participants. The collected data were entered into Microsoft Excel and analysed using SPSS version 26.0, with both descriptive and inferential statistics applied, and statistical significance determined at p < 0.05.

Socio-Demographic Characteristics of Research Participants

The study analyzed data from 295 valid Case Collection Forms (CCFs) out of a total of 300 collected, resulting in an overall response rate of 98%. The sample was predominantly male (78%) with a mean age of 67.3 years (S.D. 6.12). Most participants (67%) were aged 60-69 years, followed by 27% aged 70-79 years, 5% aged 80-89 years, and only 1% aged 90 years or older. Socioeconomically, 45% of the participants reported an income between 20,000 and 30,000 INR, while smaller proportions reported incomes below 20,000 INR (29%), between 30,000 and 40,000 INR (18%), between 40,000 and 50,000 INR (5%), between 50,000 and 100,000 INR (2%), and above 100,000 INR (1%).

Health data revealed an average of 0.93 co-morbidities (S.D. 0.92) per participant, with 60% reporting at least one co-morbidity. The participants were prescribed an average of 8.99 drugs (S.D. 2.91), with 47% receiving 9-12 drugs and 40% receiving 5-8 drugs. Potentially inappropriate medications (PIMs) were prescribed to 42% of the population, with an average of 0.64 PIMs (S.D. 0.48) per participant. Additionally, 56% of the population experienced at least one drug interaction, highlighting the complexity and potential risks of their medication regimens.

Table 1: Socio-Demographic Characteristics of Research Participants

Co-morbidities associated with various disease conditions

The study focused on the association between disease conditions and co-morbidities among 295 participants, providing valuable insights into the distribution of these health challenges. Within the cardiovascular category (N=148), hypertension was the dominant condition, accounting for 93% of the cardiovascular co-morbidities. Specifically, 48% of those with cardiovascular issues had one co-morbidity, while 37% had two, reflecting a significant correlation between hypertension and additional co-morbidities (X² = 271.71, P < .001).

In the endocrine system, diabetes mellitus (DM) was the most prevalent condition, representing 94% of endocrine-related co-morbidities (N=82). Of those with DM, 60% had two co-morbidities, further emphasizing the strong link between DM and additional health burdens (X² = 456.43, P < .001). Pulmonary diseases, particularly asthma, constituted 79% of pulmonary co-morbidities (N=19), and showed a significant association with multiple co-morbidities (X² = 86.023, P < .001).

Distribution of primary diagnosis of study participants

The primary diagnoses of hospitalized patients were categorized according to the affected body systems. Among these, gastrointestinal (GIT) disorders were the most prevalent, accounting for 46 cases, followed by musculoskeletal system disorders and respiratory conditions.

Fig 1: Frequency distribution of primary diagnosis by body systems

Association between Primary Diagnosis and Comorbidities

The analysis of associations between primary diagnosis categories—based on the affected body system—and comorbidities revealed significant patterns. Notably, patients whose primary diagnosis involved the cardiovascular system exhibited a higher prevalence of cardiovascular comorbidities, suggesting that individuals with cardiac conditions are more likely to present with additional heart-related disorders. Similarly, consistent associations were identified across other body systems. Of particular interest, primary neurological diagnoses demonstrated a strong association with both cardiovascular and endocrine comorbidities, indicating potential pathophysiological or risk factor overlap between these systems.

Fig2: Association between Primary Diagnosis and Comorbidities

Polypharmacy Associated with various Disease Conditions

The study examines polypharmacy associated with various disease conditions among 264 participants. In the cardiovascular category (N=148), hypertension is prevalent, with 89% of patients on five or more drugs. Endocrine conditions show a high association with polypharmacy, particularly diabetes mellitus, where 84% of patients are on multiple drugs (N=82). In the pulmonary category (N=19), 79% of asthma patients are on polypharmacy. Neurological conditions like epilepsy also display a 100% polypharmacy rate. Despite these findings, the Chi-square tests did not indicate significant statistical associations across these conditions (p > 0.05).

PIMs Prescribed to Older Adults with various Disease Conditions

The analysis of Potentially Inappropriate Medications (PIMs) prescribed to older adults with various disease conditions shows significant findings. Within the cardiovascular group (N=148), 39% of hypertension patients were prescribed one PIM, and 21% received two or more PIMs. Of those with diabetes mellitus (N=82), 44% were given one PIM, and 22% received two or more. In pulmonary diseases (N=19), 53% of asthma patients received at least one PIM, with 21% receiving two. In neurology, 50% of epilepsy patients were prescribed no PIMs, but 40% had two or more PIMs.

Chi-square tests across these conditions did not reveal statistically significant associations (p > 0.05), indicating that PIM prescription was not significantly linked to the number of drugs prescribed in this cohort.

DI with Prescriptions for various Disease conditions

The study analyzed drug interactions (DIs) among older adults with various disease conditions. In cardiovascular diseases (N=148), hypertension patients had a high incidence of multiple DIs: 40% had none, 18% had one, 35% had two or more DIs, with a significant association (X² = 40.98, P = .002). Endocrine disorders, primarily diabetes mellitus (N=82), showed that 48% had no DIs, but 25% had two or more DIs. Pulmonary diseases, especially asthma, had 68% of patients experiencing at least one DI (X² = 23.41, P = .005). The data highlights significant risks of DIs in hypertension and asthma patients, warranting careful prescription practices.

Corelation of each measured Associated Factor

A Spearman’s correlation analysis was conducted to examine the associations between primary diagnosis categories across various body systems. The results indicated a statistically significant weak negative correlation between the primary diagnosis and pulmonology (r = –.123, p < .05), suggesting a slight inverse relationship in the distribution pattern of pulmonary diagnoses compared to other systems. A moderate positive correlation was observed between cardiovascular and endocrine disorders (r = .278, p < .01), indicating a notable tendency for co-occurrence of these conditions. Additionally, haematology demonstrated a weak but significant positive correlation with endocrine disorders (r = .148, p < .05), implying a possible overlap in metabolic and hematologic disturbances. Other associations, including those involving neurology and gastrointestinal diagnoses, were not statistically significant and reflected very weak correlations (r values ranging from –.051 to .076). These findings may reflect underlying clinical overlaps or shared pathophysiological pathways between specific body systems, particularly between cardiovascular and endocrine conditions.

Table 6: Corelation matrix of each measured associated factors.

Association of demographic factors and PIMs

The analysis of demographic factors and PIM usage among older adults highlights important trends. Of the 230 males, 150 were affected by PIMs, with 50% using one PIM, 21% using two, and 8% using three. Among 65 females, 40 were affected, with 15% using one PIM, 5% using two, and 2% using three. A significant association was found with the number of co-morbidities (P = .04), where individuals with multiple conditions had a higher likelihood of PIM use. Other factors, like age and income, were not significantly associated with PIMs.

*Chi square test, P < .05 is significant.

Distribution of PIMS among various wards

Among the common medications attributing to PIMs in elderly prescriptions, tramadol (36%) was found to be the most, followed by gabapentin (8%) and others like nortriptyline, spironolactone, and chlordiazepoxide.  Amitriptyline has the lowest count, with only 1 prescription at < .5%. Other notable medications include baclofen, nifedipine, and pregabalin. This comprehensive overview underscores the diversity in prescribing patterns, shedding light on the usage of different medications within the analysed dataset. In the GM department, about 69% of PIM prescriptions were observed with substantial high prevalence. A similar trend was observed in the male surgery (67%), Orthopaedics (100%), emphasizing a need for targeted interventions.

The prevalence of potentially inappropriate medications (PIMs) in this study, found to be 64%, is significantly higher than in previous research, highlighting a potential area of concern in the prescribing practices within the studied population. For example, European studies by Moriarty et al. and Gallagher et al. documented PIM rates between 20% and 40%. [11][12] The observed disparity could stem from differences in healthcare systems, medication availability, or the adherence to prescribing guidelines across regions. The higher prevalence in the present study suggests a potential need for stricter prescribing regulations and enhanced oversight.

Furthermore, the study noted a higher likelihood of PIM prescriptions among males (65%) compared to females (62%), which contrasts with findings from other regions where females are generally more affected by PIM use. [13][14] This variation could be attributed to cultural differences in healthcare-seeking behavior or the specific disease profiles predominant in males, such as cardiovascular conditions, whiency distribution ofch were prevalent in this study and are commonly associated with increased PIM use. [15]

Interestingly, the study found that older age groups, particularly those aged 60-69, were prescribed fewer medications compared to older groups. This finding diverges from studies by Nobili et al. and Maher et al., where polypharmacy was more prevalent among older adults, likely due to the accumulation of chronic conditions. The lower rate of polypharmacy in the 60-69 age group in this study might suggest more conservative prescribing practices or better overall health in this demographic. [16][14]

Cardiovascular diseases, particularly hypertension, were the most prevalent comorbidities and were significantly associated with PIM use. This observation is consistent with global studies, such as those by Moriarty et al. and Gallagher et al., which also found that cardiovascular conditions often lead to complex medication regimens and an increased likelihood of PIMs. The significant association between diabetes and PIM use observed in this study aligns with findings from Lau et al., emphasizing the critical need for careful medication management in patients with endocrine disorders. [11][12][13]

The study also revealed departmental variations in PIM use, with particularly high rates in Orthopaedics and General Medicine (GM). This pattern aligns with findings from Bregnhoj et al., where PIM rates were elevated in specialties dealing with chronic pain or complex medical conditions. The higher PIM rates in Orthopaedics, potentially due to the frequent use of opioids and other high-risk medications for chronic pain management, echo the concerns raised in the study by Spinewine et al. [17][18]

Another key finding was the association between higher income and increased odds of drug interactions, a trend also noted by Johnell and Klarin, who found that wealthier patients often see multiple healthcare providers, leading to polypharmacy and a heightened risk of drug interactions. The significant association between cardiology departments and drug interactions further underscores the complexity of treatment regimens required in managing cardiovascular diseases, which Maher et al. also identified as a significant factor in the risk of adverse drug interactions. [19][14]

Common PIMs such as tramadol and gabapentin were frequently prescribed, reflecting global trends where these drugs are implicated in PIMs due to their adverse side effect profiles. [11] These findings are consistent with guidelines like the Beers Criteria and STOPP/START criteria, which also highlight the risks associated with these medications, particularly in older adults. [18]

Overall, the study underscores the need for targeted interventions to reduce PIM use and enhance medication safety, particularly in high-risk departments and among patients with significant comorbidities. This aligns with global efforts to implement stricter prescribing guidelines and the use of tools like the STOPP/START criteria to guide safer prescribing practices. Additionally, the observed association between higher income and increased drug interactions suggests a need for better coordination of care among patients who see multiple specialists, as supported by Johnell and Klarin.[11][12][19].

The study did have its limitations. Given time constraints, the prescriptions were undertaken within a limited timeframe of 6 months. Efficiency was prioritized in the aforementioned studies, resulting in a concise research period. Data were obtained from a single hospital with limited sample which limits the generalizability and external validity of the study findings. The study's results may not be comparable to those of other studies that use different tools to identify PIMs, such as STOPP criteria instead of BC.

Our research discovered that, the older population has a considerable prevalence of using medications inappropriately. PIM risk factors include aging, asthma, diabetes, hypertension, and polypharmacy. It is essential to consider strategies for preventing PIMs from initiating. A lot of medications are only considered perhaps inappropriate in certain situations, or most of the time with a few notable exceptions. The criteria used to decide whether medications might not be acceptable and whether a suggestion or justification is necessary are based on certain categories. Medical professionals need to be aware of the possible side effects that these drugs may have on the elderly and take the appropriate precautions to prevent them. In addition, deprescribing plays a major role in the current decline in PIM use and necessitates active patient and medical professional participation.

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