Potentially inappropriate medication (PIM) use is a problem related to safety in older adults. The prevalence of PIM use is approximately 50% in the older adult U.S. population, and many adults 65 and older take at least one PIM (Beer et al., 2011). Commonly used PIMs are psychotropic drugs such as long-acting benzodiazepine agents, tricyclic antidepressant agents, and anticholinergic medications (Albert, Colombi, & Hanlon, 2010; Bao, Shao, Bishop, Schackman, & Bruce, 2012; Bierman et al., 2007; Howard, Dolovich, Kaczorowski, Sellers, & Sellors, 2004; Lau, Mercaldo, Shega, Rademaker, & Weintraub, 2011; Lechevallier-Michel et al., 2005; Lin, Liao, Cheng, Wang, & Hsueh, 2008; Maio, Yuen, Novielli, Smith, & Louis, 2006; Mort & Aparasu, 2000; Rochon et al., 2004; Zhan et al., 2001). These drugs have been documented as posing high risk for negative effects and have limited effectiveness.
According to the World Health Organization (WHO), an estimated 157 million Americans will be affected by at least one chronic condition requiring medication therapy by the year 2020 (Freudenberg & Olden, 2011). Older adults consume large numbers of medications, accounting for more than one third of total outpatient spending on prescription medications in the United States (National Institute on Drug Abuse, 2011). According to Gu, Dillon, and Burt (2010), 37% of adults 60 and older use five or more prescription medications. Although the use of multiple medications (polypharmacy) may be necessary to manage chronic conditions, long-term use of drugs and particular combinations pose safety risks in older adults.
As the adult body ages, changes in pharmacodynamics and pharmacokinetics increase the hazards of medication use. Research has shown that as more medications are prescribed, the risk of PIM use increases (Blozik, Rapold, von Overbeck, & Reich, 2013). At times, side effects are mistaken for new onset illnesses or other comorbidities that are treated with additional medications. This is sometimes referred to as the “prescribing cascade” and leads to additional PIM use (Knight & Avorn, 2001). The use of PIMs can trigger and alter the central nervous system (CNS) and other mechanisms that increase older adults’ risk for injury and hospitalization (Finkle et al., 2011). Older adults are vulnerable to adverse drug reactions (ADRs) and adverse drug events (ADEs) that relate to poor health outcomes, mortality, and increased health costs (Pretorius, Gataric, Swedlund, & Miller, 2013). The use of PIMs by older adults has been studied in the nursing home and acute health care settings where pharmaceutical management includes medication monitoring. Older adults living independently may seek multiple care providers and pharmacies, which increases the risk of acquiring PIMs. Disease–drug and drug–drug interactions, falls, and functional decline are consequences that can lead to reduced independence and quality of life (QOL) (American Geriatrics Society [AGS], 2012; Berdot et al., 2009).
Providing quality geriatric care and health management involves optimizing medication use. Fick and Semla (2012) emphasized the importance of decreasing problems related to PIM use as an attempt to improve the health of older adults. The WHO (2008) calls for an awareness and assessment of the risks and benefits of medicines, and the National Institute on Aging (2013) has set a goal of disseminating evidence to help decrease older adult diseases and disabilities and improve health and QOL.
Health care professionals who are aware of the science surrounding PIMs in the community setting are seeking interventions to prevent consequences of their use. The purpose of this state of the science article is to appraise the definitions, models, measurements, and results of the literature addressing PIMs in community-dwelling older adults. This appraisal will also identify gaps in the knowledge and recommend directions for future research.
An electronic database search was conducted in June 2013 using CINAHL, MEDLINE, Biomedical Reference Collection, and PubMed. The time frame of January 1991 to June 2013 was selected to identify specific articles based on the Beers criteria, which were first published in 1991. A keyword search included, but was not limited to: potentially, inappropriate medications, drugs, prescriptions, polypharmacy, elderly, older adult, aged adult, community-dwelling, and home-dwelling.
Journal articles were included based on the following characteristics: (a) study sample of adults 65 and older who were community-dwelling and living independently; (b) primary goal was to reduce inappropriate medications; and (c) article was published in the English language. Studies were excluded if they were conducted in a nursing home, skilled facility, or acute hospital inpatient setting. Studies that compared settings, examined specific disease states or explicit medications, or tested instruments for measuring inappropriate medications were also excluded. Identifying older adults prior to, or in the midst of, using PIMs is helpful in decreasing medication-related complications. The age range of 65 and older was chosen to align with societal norms, such as eligibility for Medicare. Community-dwelling older adults possess the independence to obtain medications from local pharmacies or retail establishments. Professional monitoring of medication use is not heavily regulated in these settings compared to environments such as nursing homes and acute care facilities.
The database search yielded 352 publications representing retrospective and prospective descriptive designs, intervention studies, reviews, and non-peer-reviewed articles. Duplicates (n = 285) were removed, resulting in 67 articles for abstract review. Abstracts of the articles were reviewed, and 28 articles were removed based on the inclusion/exclusion criteria. A manual search was performed on the identified articles, and 28 additional studies were included. After full-text examination, a total of 38 retrospective, 19 prospective, and 10 intervention studies were selected. The search did not retrieve any qualitative or mixed-method design studies. The Figure provides a flow chart of the literature search.
Flow chart of search results. PIM = potentially inappropriate medications.
PIM use is not well defined in the literature. The risk–benefit definition of appropriateness declares a drug as appropriate if its use and potential benefits outweigh potential risks (Beers, 1997). Several terms are used interchangeably with PIM use, including medication misuse, potentially inappropriate prescriptions, and potentially inappropriate prescribing; the latter two have been represented by the same abbreviation (PIP). Clearly defining the concept of PIM use is essential to study the problem. Analysis of the concept of PIM use helps differentiate it from similar concepts. Dissection of each word and the identification of attributes and antecedents allow for the conceptual definition to be derived (Walker & Avant, 2011). A review of the literature helped derive the attributes and antecedents of this concept. Attributes associated with the concept of PIM use in independent, community-dwelling older adults include physician, pharmacy, pharmacodynamics, pharmacotherapeutics, age, polypharmacy, and multiple chronic conditions. Antecedents of the concept of PIM use include recommending, advising, suggesting, advocating, proposing the use, and seeking of remedies. For the purpose of this review, PIM use will be conceptually defined as substances that may be unsuitable if taken for treating conditions.
Studies presented in this analysis include combinations of PIM and PIP literature due to overlapping definitions. PIP also lacks conceptual clarity, and a consensus definition and has been described as potentially prescribing medications in high frequency, for long durations, in the presence of multiple medications with interactions, and the underuse of beneficial medications (Gallagher, Barry, & O’Mahony, 2007; Page, Linnebur, Bryant, & Ruscin, 2010). A relationship exists between the use of PIM and PIP, as studies regarding PIP are focused on the prescribing behaviors of the health care provider.
Experts have reported associations among PIM use, ADRs, and ADEs. According to Edwards and Aronson (2000), the WHO has historically defined an ADE as “any untoward occurrence that may be present during treatment with a pharmaceutical product, but does not necessarily have a causal relation to the treatment” (p. 1256). An ADR is a type of ADE that is defined as any harmful, unintended, and undesired effect of a drug (WHO, 2008). Many reports use the terms interchangeably, do not define these concepts, or simply call them ADEs. Other reports use related but unique terms, such as adverse drug effects.
The literature exemplifies underpinnings from a post positivist philosophical perspective. Studies were approached from the pharmaceutical models with minimal use of theoretical frameworks. The Andersen Newman Model is one sociological theoretical framework that has been used to explore PIMs in association with the societal and individual determinants of medical care utilization. The model has been revised and the latest (phase 4) model includes the environment, population characteristics, health behavior, and outcomes (Andersen, 1995; Andersen & Newman, 2005). Two teams have used this model, asserting better understanding of health care utilization and economical and humanistic outcomes resulting from the use of PIMs (Aparasu & Mort, 2004; Blalock et al., 2005).
The Andersen Newman Model provides a theoretical approach to studying how the use of PIMs can affect use of health services (Andersen & Newman, 2005). This model has the ability to predict and explain the use of health services; however, it has a limited presence in current literature. This may be due to society’s ever-changing health care system and needs. Andersen (1995) claimed that the variables of the model were criticized as being conservative and outcome measures as being unrefined.
The literature provides several criteria to operationalize the use of PIMs. However, due to the lack of conceptually agreed upon definitions, studies have used measurements to quantify PIM and PIP equally. Instruments have been developed worldwide and will continue to be revised as older adults and health care changes. Strategies for instrument development have involved an extensive literature review and often used a modified Delphi method to determine appropriate versus inappropriate medications (Brown, 1968).
The Beers criteria are frequently used to operationally measure the use of PIMs in older adults (age ≥65). According to these criteria, medications should be prescribed based on a risk–benefit definition of appropriateness (Beers, 1997). The Beers criteria were initially developed in the United States in 1991 in response to problems with medication use in nursing home residents. The list was revised in 1997, 2003, and 2012 for use in all care settings (AGS, 2012; Beers, 1997; Beers et al., 1991; Fick et al., 2003). PIMs were originally assigned within two categories: (a) medications to avoid in older adults regardless of diseases or conditions, and (b) medications that were considered potentially inappropriate when used in older adults with specific diseases or syndromes. The updated AGS Beers criteria lists 53 medications or medication classes; a third category, medications that should be used with caution in older adults, was added. The current criteria can be viewed on the AGS website (access http://www.americangeriatrics.org/files/documents/beers/2012AGSBeersCriteriaCitations.pdf).
The Healthcare Effectiveness Data and Information Set (HEDIS) criteria were recently updated according to the 2012 AGS Beers criteria (National Committee on Quality Assurance [NCQA], 2013). The consensus panel of the NCQA originally developed this quality measure to identify rates of inappropriate prescribing in older adults. A past criticism of the Beers criteria claimed that the list contained medications no longer commercially available or used in clinical practice in the United States. The Beers criteria have also been criticized for not including over-the-counter (OTC) medications and not providing a list of alternative medications.
Physicians and pharmacists in several countries have used these criteria but have not had optimal success due to different medication formularies. Fortunately, countries such as Germany and Norway have developed lists such as the PRISCUS and Norwegian General Practice (NORGEP), respectively, to address PIM use in older adults based on their country’s commonly used medications (Holt, Schmiedl, & Thürmann, 2010; Rognstad et al., 2009).
Medication Appropriateness Index
The Medication Appropriateness Index (MAI) was developed in the early 1990s to assess the appropriateness of medications. The 10 criteria include: indication, effectiveness, dosage, directions, practicality, drug–drug interactions, drug–disease interactions, unnecessary duplications, duration, and cost (Hanlon et al., 1992). The MAI can be used to determine whether medications are proper to prescribe, but it does not list specific inappropriate medications for clinical guidance (Kaur, Mitchell, Vitetta, & Roberts, 2009).
The McLeod criteria were developed in Canada in 1997 as an attempt to expand the Beers criteria. Thirty-eight medications were placed into three categories: (a) drugs generally contraindicated for older adults, (b) drug–disease interactions, and (c) drug–drug interactions (McLeod, Huang, Tamblyn, & Gayton, 1997).
The Zhan criteria were developed in 2001 in response to an awareness of the limitations of the Beers criteria. Thirty-three drugs were placed in three categories: (a) medications that should always be avoided, (b) rarely appropriate medications, and (c) medications that have some indication but are often misused (Zhan et al., 2001). There is minimal application of the McLeod and Zhan criteria as a measure of PIM use in the current literature.
The Screening Tool of Older Persons’ Potentially Inappropriate Prescriptions (STOPP) was developed in 2008 by Gallagher and O’Mahony. STOPP contains commonly occurring PIMs in older adults, including drug–drug and drug–disease interactions, drugs that negatively affect older patients at risk of falls, and duplicate drug class prescriptions. This tool was intended to be used along with a Screening Tool to Alert doctors to the Right Treatment (START), developed by Gallagher, Ryan, Byrne, Kennedy, and O’Mahony (2008). The STOPP criteria are not used as widely as the Beers criteria in community settings. Effectiveness of the STOPP criteria has been compared with the Beers criteria (Gallagher & O’Mahony, 2008; Ryan et al., 2009).
Assessing Care of Vulnerable Elders (ACOVE) was developed by the RAND Corporation (Santa Monica, CA) and Pfizer Corporation (New York, NY) to establish indicators that measure quality of care. A set of quality indicators was released that focuses on pharmacological care provided to community-dwelling vulnerable adults (Shrank, Polinski, & Avorn, 2007). Although promising, our search did not produce intervention studies using this tool to study the use of PIMs in community-dwelling older adults.
Literature Review on PIMs in Community-Dwelling Older Adults
The goal of this state of the science review is to synthesize the results of the literature, identify areas of strength and weakness, and designate gaps in the science for future study. The current literature regarding PIM use in community-dwelling older adults consists of reviews relating to PIM use in all settings, descriptive correlation studies, and prospective intervention studies.
Most reviews analyzed literature in settings such as nursing homes and hospitals rather than focusing on community-dwelling older adults. Opondo et al. (2012) published the only review in the primary care setting that focused on inappropriate prescriptions in older adults, but they excluded studies on community-dwelling older adults. Two reviews (Gallagher et al., 2007; Kaur et al., 2009) focused on the prevalence of inappropriate prescribing in older adults and provided a synthesis of evidence for interventions for reducing inappropriate prescribing. These reviews examined inappropriate medication use as a function of prescribing behavior, missing the opportunity that independent older adults have to acquire PIMs by other means. Jano and Aparasu (2007) reported that the use of PIMs is associated with increased hospitalization but not mortality or health utilization in selected studies of community-dwelling older adults. A Cochrane review analyzed intervention studies designed to improve the use of appropriate medications in older adults. The summary reported that studies had poor methodology, design, and small samples (Patterson, Hughes, Kerse, Cardwell, & Bradley, 2012).
Descriptive Correlational Studies
Retrospective Studies. The primary type of study describing PIM use in community-dwelling older adults is the retrospective cohort study design. This design uses large databases of past patient information to describe the prevalence, frequency, risk factors, and outcomes of PIM use (Bierman et al., 2007; Blozik et al., 2013; Buck et al., 2009; Cannon, Choi, & Zuniga, 2006; Chen et al., 2009; Fialová et al., 2005; Fick, Mion, Beers, & Waller, 2008; French et al., 2007; Hanlon et al., 2002; Klarin, Wimo, & Fastbom, 2005; Lin et al., 2008).
Health Outcomes. Inconsistent results were reported between PIM use and health outcomes in retrospective studies. Some studies report an association between PIM use and ADEs, whereas others report no relationship (Budnitz, Lovegrove, Shehab, & Richards, 2011; Chen et al., 2009; Fick et al., 2008; Hanlon et al., 2002; Lau et al., 2011). Studies varied in results describing the association between the use of PIMs and functional status. One study reported the use of PIMs in association with a decline in basic self-care, but another did not report an association (Hanlon et al., 2002; Lau et al., 2011). Retrospective designs are useful for analysis but have limitations that may lead to an underrepresentation of PIMs. Studies are limited to the records included in the database, and influential data may be absent, leading to inaccurate results.
Prospective Studies. The authors identified 19 published prospective studies examining PIM use in community-dwelling older adults. Studies conducted in different countries reported varying prevalence rates (9% to 18%) when examining PIMs in the home (Ay, Akici, & Harmanc, 2005; Fiss et al., 2011; Pitkala, Strandberg, & Tilvis, 2002). In comparison to the home setting, a 38% prevalence of PIM use was found in Portuguese community pharmacies (de Oliveria Martins, Soares, Foppe van Mil, & Cabrita, 2006).
Several factors, including multiple medication use, comorbidities, female gender, and depression, have been reported to increase the risk for PIM use in community-dwelling older adults (Blalock et al., 2005; Saab, Hachem, Sinno, & El-Moalem, 2006; Stuck et al., 1994). An adapted version of the Andersen Newman Model was used to report that the risk of PIM use was higher in those with greater medication needs (Blalock et al., 2005).
Saab et al. (2006) specifically addressed the use of OTC medications in Lebanon. The factors of alcohol and OTC drug use were associated with an increased likelihood of PIM use in older adults visiting a community outpatient clinic. The study reported an 18% missed dose frequency and 13% incorrect frequency of medications used. PIM use prevalence was higher than that reported by studies conducted in outpatient and ambulatory clinics in India and the United States (Woelfel, Patel, Walberg, & Amaral, 2011; Zaveri, Mansuri, & Patel, 2010). Literature on the use of PIMs in the rural community is limited.
Fadare, Agboola, Opeke, and Alabi (2013) investigated the prevalence of PIP for older adults being treated in a rural outpatient department in Nigeria. The prevalence was 25% higher than the study conducted by Ryan et al. (2009) in an Irish primary care clinic. The Ryan et al. study compared urban and rural community-dwelling adults, in addition to comparing two criteria of PIM use measurements. Overall, PIP prevalence was found to be 18% with the Beers criteria and 21% with the STOPP tool.
Prospective evidence is limited regarding the relationship between the use of PIMs and ADEs in community-dwelling older adults. Chrischilles, VanGilder, Wright, Kelly, and Wallace (2009) used surveys and concluded that a relationship exists between PIM use and self-reported adverse drug effects. The study did not examine ADEs but specifically looked at “side-effects” of PIM use. ADEs are commonly manifested as falls, orthostatic hypotension, heart failure, and delirium (Pretorius et al., 2013). In Taiwan, Chang et al. (2005) found a positive association between PIP and possible ADRs (relative risk = 15.3). Berdot et al. (2009) examined the differences in regular and occasional users of PIMs in France and reported an increased risk of falling. The odds ratios of falling were between 1.4 and 1.7 in regular users of psychotropic and anticholinergic medications and in occasional and regular users of long-acting benzodiazepine agents. Beer et al. (2011) reported 18.2% of community-dwelling Australian older men ages 70 to 88 reported a fall that was associated with the use of PIMs.
A relationship was found between cognitive status and PIM use over time in community-dwelling women with dementia (Koyama, Steinman, Ensrud, Hillier, & Yaffe, 2013). In Italy, Landi et al. (2007) reported that those using more than one PIM had significantly low physical functioning. An older study in Chicago by Chin et al. (1999) also reported that older adults who presented to the emergency department with PIMs and adverse drug–disease interactions and those who were discharged with PIMs reported low physical function. Lukazewski, Mikula, Servi, and Martin (2012) reported that PIM use is associated with increased geriatric syndromes, including memory and cognitive problems, which place older adults at risk for adverse events.
The authors found 10 published interventions aimed at reducing PIM use in community-dwelling older adults (Table). Multifactorial approaches included medication review and screening as well as computerized, behavioral, and educational strategies.
Medication review and screening have been performed by teams or a pharmacist. Allard, Hébert, Rioux, Asselin, and Voyer’s (2001) longitudinal study used a multidisciplinary approach to conduct medication reviews in community-dwelling Canadian older adults at risk of losing autonomy. The intervention used a non-validated measurement and did not significantly decrease the number of PIPs given to participants. Pharmacists Dunn, Harrison, and Ripley (2011) used the Beers criteria as a screening intervention to alert physicians of the prescribing of PIMs. The mean number of PIMs was reduced as patients were being seen in a U.S. outpatient clinic (Dunn et al., 2011). A pharmacist review intervention by Taylor, Byrd, and Krueger (2003) reduced PIP and hospital and emergency department visits and improved clinical levels of blood pressure, cholesterol, hemoglobin A1C, and coagulation values in older rural-dwelling adults in Alabama. A similar study by Hanlon et al. (1996) involved a clinical pharmacist and nurse who used the MAI to identify the use of PIMs during medication reviews to reduce PIP in an outpatient Veterans Affairs clinic. The study provided evidence supporting the implementation of dual nurse and pharmacist medication reviews to decrease PIP and potentially reduce ADEs.
Computerized approaches were used to alert pharmacists when patients 65 and older were newly prescribed PIMs (Raebel et al., 2007; Simon et al., 2006; Tamblyn et al., 2003). Although the studies significantly affected PIP, computerized support for prescribing may not give a full picture of the patient’s medication use. Prescriptions for PIMs may be obtained from providers and taken to other pharmacies not connected with the intervention alert. Additionally, PIMs can be purchased OTC without the pharmacist being aware. These circumstances could increase the older adult’s risk of ADEs.
Three studies used educational and behavioral approaches to limit PIM use in older community-dwelling adults. The use of a multicomponent educational intervention resulted in reductions in PIM use and exposure in Italian primary and outpatient clinics (Keith, Maio, Dudash, Templin, & Del Canale, 2013). Combined education and feedback were used to improve mean MAI scores in Denmark (Bregnhoj, Thirstrup, Kristensen, Bjerrum, & Sonne, 2009). The only nurse-led study by Fick et al. (2004) used a strategy for behavior change in physicians to decrease PIM use of members continuously enrolled in a southeastern managed care organization.
This review includes an appraisal of the research specifically exploring the definition, models, measurement, and results of prospective and intervention studies addressing the use of PIMs in community-dwelling older adults. Strengths of the literature are that scientists described the prevalence and influencing factors of the use of PIMs. Researchers also studied the effects of using PIMs and their relationships with specific outcomes.
Definitions and Models
The research on the use of PIMs is limited by the lack of concrete and conceptually clear definitions. This state of the science highlights the vague conceptualization of PIMs that impedes understanding of the problem among colleagues. The literature represents blurred concepts that do not share the same meaning. PIPs are instructions given by health care providers, and use of PIMs can include any substance for treating a disease with or without a prescription. Assessing the prescribed medications or prescribing behavior of the provider only examines one aspect of PIM use. Studies rarely distinguished clearly between ADEs, adverse drug effects, and drug-related problems.
Defined concepts need to be placed in a research model and measured operationally by tools that have established reliability and validity for that concept. Most models examining the use of PIMs are pharmaceutical or medical in nature. This review described the use of the Andersen Newman Model as one theoretical framework that has been used to study the use of PIMs. The model is appropriate to study independent community-dwelling older adults rather than hospitalized or institutionalized adults. The Andersen Newman Model has the ability to predict and explain the use of health services for translational research. The use of PIMs can be studied using a variety of theoretical approaches to gain other perspectives of the problem.
Study methods varied in this review. In several studies, pertinent health history, such as cognitive status, was not addressed prior to data collection by self-report, interview, or survey. Responses given on self-report measurements of ADEs or falls may be inaccurate if older adults experience decline in cognitive status. Few researchers reported including OTC medications in their studies. PIMs such as ibuprofen or diphenhydramine (Benadryl®) can be obtained OTC and without a prescription. Addressing the use of PIMs requires the assessment of all medications taken by the individual. The measurement of PIM use was most commonly performed using the Beers criteria. Several studies were conducted abroad, and medications on this list were not used in those countries. The reliability of instruments to measure secondary outcomes was often not provided in the study reports.
Results of the Literature Review
Descriptive studies provided varying findings regarding prevalence, influencing factors, and outcomes associated with the use of PIMs. The primary investigator in all studies was a pharmacist or physician. The prevalence of PIP was addressed specifically in the community outpatient, ambulatory clinic, and pharmacy settings. Most studies examined only the prevalence of PIM use; however, several examined the use of PIMs with falls, ADEs, ADRs, and aspects of functional status. More studies are needed relating the use of PIMs to ADEs, falls, cognitive function, sleep, and QOL in community-dwelling older adults. Evidence of the relationships between the use of PIMs and health outcomes will improve care as older adults continue to live independently and self-manage chronic diseases. Interventions aimed to change the behavior of the prescribing physician and monitor the pharmacist. Minimal research has been published focusing on the consequential effects of interventions to reduce the use of PIMs and improve health outcomes in community-dwelling older adults.
This analysis examined the state of the science’s knowledge on the use of PIMs in community-dwelling older adults and is not without limitations. Journal articles may have been missed that represent the population of interest. Studies conducted in the outpatient, ambulatory, or clinic settings may not have provided complete information regarding the residential living conditions of the participants. Older adults who live in nursing homes can be seen in these settings, and several articles did not identify the specific living arrangements of their participants. The rationale for including these studies was an attempt to provide an analysis of older adults living in community settings who access primary care clinics.
Implications for Nursing Research
The increased number of older adults and the prevalence of chronic conditions requiring pharmacological management call for enhanced nursing oversight of pharmacological interventions in older adults (Edlund, 2010). Many gaps in knowledge need to be addressed. Prospective studies need to use conceptual models and rigorous methods with appropriate sample sizes, power, and reliable and valid measures. Nurse-led studies with interprofessional colleagues need to address PIM use with health status and independence in community-dwelling older adults. Interprofessional teamwork can increase the translation of science to improve patient care.
Nursing professionals have not been engaged in studies addressing the prevention and use of PIMs in community-dwelling older adults. The nurse is an important member of the health care team—one who is trusted and in frequent contact with patients. The nurse frequently communicates, monitors, and assesses medication ADEs and ADRs. Teams of doctorally prepared nurses, advanced practice RNs, pharmacists, and physicians can lead and evaluate interventions to reduce the use of PIMs. Studies led by a PhD-prepared nurse can incorporate theoretical models into the study design to test theoretically based behavior change interventions.
Randomized controlled trials with large samples are needed when pilot studies demonstrate positive effects. Randomized studies that compare an intervention group with a control group other than usual care, or examine the outcomes when implementing two different interventions, are needed. Qualitative or mixed-method approaches could provide further strength in analysis and interventions for reducing PIM use. The use of quality indicators (e.g., ACOVE) and incorporation of the current version of the Beers criteria (AGS, 2012; Shrank et al., 2007) would provide current evidence to the science.
Future studies need to examine the prevention and use of PIMs in relation to older adults’ ADEs, health status, QOL, health beliefs, and behavior. Interventions should emphasize the contribution of the patient/family rather than focus primarily on the physician/pharmacist. Studies are needed that show the effects of medication optimization and telehealth strategies on the use of PIMs and health outcomes. Collaborative and integrated models are best suited to respond to the chronic multimorbidities of older adults and improve the pharmacological management of their conditions (Topinková, Baeyens, Michel, & Lang, 2012). A cooperative partnership between the physician, nurse, pharmacist, and patient may be the key.
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Interventions for Potentially Inappropriate Medication (PIM) Use in Community-Dwelling Older Adults
|Author, Design, and Purpose||Intervention||Sampling and Setting||Measures and Analysis||Results||Limitations and Comments|
|Allard, Hébert, Rioux, Asselin, & Voyer, 2001|
RCT, 2 groups
1-year longitudinal study
To decrease PIPs given to older adults by physicians
Control group: usual care
The team consisted of two physicians, one pharmacist, and one nurse, who reviewed the medications and diagnoses of the experimental group.
The team’s suggestions were mailed to the PCP justifying the changes.
The nurse followed up monthly with the patient.
|N = 266 patients
Intervention group: n = 127
Control group: n = 130
Characteristics: community-dwelling, at risk of losing autonomy, and taking >3 medications.
PIPs: Quebec Committee on Drug Use list
Measures were completed before and after the intervention
Primary outcome: Number of PIPs
Independent t tests, paired t test, ANCOVA
|Intervention group had a larger decline in the mean number of PIPs than controls, but this was not statistically significant.|
38% of participants in the intervention group did not receive the intervention.
A possible interaction occurred between the primary investigator and the physicians and patients.
|Bregnhoj, Thirstrup, Kristensen, Bjerrum, & Sonne, 2009|
RCT, 3 groups
To increase the prescribing of appropriate medications among GPs
Combined interactive educational meeting plus feedback on patients’ medications.
Single interactive educational meeting.
Control group (no intervention).
|n = 41 GPs, n = 166 patients
Characteristics: Taking >5 scheduled medications over a 3-month period prior to recruitment
MAI and number of medications in the intervention groups
Chi square test, Wilcoxon signed rank test
|MAI mean scores improved in the combined intervention groups by 5 points. Change in number of medications in the combined intervention group had a significant decrease of −1.03 (95% CI, [−1.7, −0.30]).|
The level of appropriateness of the medication may be overestimated due to the collection method (GPs and medical records).
Hawthorne effect could have occurred.
GP served as gatekeeper for medications.
|Dunn, Harrison, & Ripley, 2011|
Non-randomized prospective pre/post pilot study
To decrease the use of PIMs by conducting outpatient screening
Medication profiles of the participants were screened using the Beers criteria before a patient’s scheduled appointment.
Physicians were informed of PIMs and given options to discontinue, continue, or change medications.
Medication profiles were followed after the appointment.
|Six individual medicine and medicine specialty clinics
N = 120 patient charts
PIMs: Beers criteria 2003 (Fick et al., 2003)
Dependent measures t test
|37.5% of patients were taking PIMs. Statistically significant decrease in the mean number of Beers criteria medications (p = 0.032).|
Accuracy of the medication profiles was unknown.
Knowledge of the Beers list among health care team was unknown.
|Fick et al., 2004|
Randomized block design, 2 groups
To change physician behavior and decrease PIP in older patients
Control group: usual care
Physician received a detailed brochure listing PIMs, suggested PIM alternatives, and a personally addressed letter from MCO describing the patients taking ≥1 PIM.
Physicians were invited to comment on PIM changes by using a fax-back form.
|N = 355 Medicare and choice product line of southeastern MCO physicians
Intervention group: n = 170, control group: n = 185
PIMs: Beers criteria 1997
Descriptive investigation of physician response to PIMs and the action taken
Chi square tests
|69.4% of providers prescribed at least 1 PIM; 71% of physicians responded via fax.
12.5% of physicians discontinued the medication, 1.7% modified dosage, and 1.2% used alternative medication.
Number of continuously enrolled members with at least 1 PIM declined from 19.4% to 17.9% (p < 0.001).|
Fax was not an form of communication.
The initial education brochure given 3 months prior to the study may have had an effect on the actual reality of the prescribing practices.
|Hanlon et al., 1996|
RCT, 2 groups
To decrease PIP in outpatients
|Intervention group: Received usual and clinical pharmacist care.
Usual care: review of current medications before and after visit by a nurse.
Clinical pharmacist care:
Control group: usual care
Prior to the visit, the clinical pharmacist monitors drug therapy, identifies drug-related problems, and meets with patient and caregivers.
Suggestions from the pharmacist are given to the physicians.
The pharmacist provided patient education following the physician visit.
The pharmacist provided compliance strategies to the patient.
|General medicine clinic, N = 208 patients
Intervention group: n = 105
Control group: n = 103
Characteristics: Taking ≥5 medications, visited VA medical center
PIMs: MAI criteria
Student t test, chi square, or Fisher’s exact test; ANCOVA and MANCOVA on other outcomes
Baseline, 3-, and 12-monthmeasures
|At 3 months, the intervention group had a decline in PIP when compared to the control group (p = 0.0006) and was consistent at 12 months (p = 0.0006). Fewer patients experienced ADEs but this was not statistically significant.|
Patient randomization without physician randomization.
This study focused on regularly scheduled medications only and did not include as needed or OTC medications.
|Keith, Maio, Dudash, Templin, & Del Canale, 2013|
Prospective study, 2-group design
Multicomponent intervention designed to decrease PIP in older patients in primary care
Physicians received a list of PIMs to always be avoided with alternatives; annual reviews of PIM incidence data.
Educational sessions on PIMs via academic information and case study reviews were done with physicians. Reggio Emilia LHA was the comparator and received usual care.
|Stratified by location n = 303 GPs in Parma LHA n = 325 GPs in Reggio Emilia LHA
Parma LHA n = 78,482 patients
Reggio Emilia LHA n = 81,597 patients
PIMs: Modified Beers criteria
The percentage of change in PIMs from baseline 2007 4th quarter to the end of the study post intervention, 2009 4th quarter
Significance of change in incidence rates over time within each LHA
Chi square and estimated percentage of change
|Both LHAs experienced reductions in PIM exposure rates.|
Patient diagnosis data were not in the database.
Inpatient prescriptions and OTC medications were not available.
Possible confounding variables.
|Raebel et al., 2007|
RCT using a two-arm parallel design
To reduce newly prescribed PIMs in older adults
Control group: Wait-listed for 6 months with usual care during that time period.
Pharmacist was alerted when patients ages ≥65 were prescribed one of 11 medications.
Pharmacist alerted the provider and made notes in the computer system.
|KP Colorado, a group model U.S. HMO
N = 59,680 (29,840 each group)
Physicians, patients, and pharmacists blinded to group assignment
PIMs: Physician and pharmacist collaboration used Beers criteria, Zhan criteria, and KP list of medications to avoid in older adults
Chi square, Wilcoxon rank, and Fisher’s exact tests
|Higher percentage of PIMs prescribed in the usual care group (2.2%) than in the intervention group (1.8%). Most commonly reduced prescriptions were amitriptyline (p < 0.001) and diazepam (p = 0.02).|
The use of health plan prescription data to assess drug dispensing does not ensure that patients did not go other places for prescriptions.
This study did not consider the refilled prescriptions as PIMs for alerts.
|Simon et al., 2006|
Cluster RCT, 2 groups
Interrupted time series analysis
Conducted over 3 years
To reduce newly prescribed PIMs in older adults
Group 1: Alerts and academic detail intervention
Group 2: Alerts only
The computer system gave age-specific alerts when older adults were prescribed specific PIMs.
Physician also received academic detail, which is evidence-based education.
|Clinic sites N = 15
Group 1: n = 113 with 7 sites, n = 24,119 patients
Group 2: n = 91 with 8 sites, n = 26,805 patients
PIMs: Investigator developed instrument
PIMs dispensed per 10,000 patients per quarter
t tests, chi square, segmented regression models
|Downward trend occurred in alerts for targeted medications being dispensed. The academic detailing did not statistically change the number of PIMs dispensed.|
|Tamblyn et al., 2003|
Clustered RCT, 2 groups
To reduce inappropriate prescriptions given to older adults
Control group: usual care
Physicians were given CDS consisting of a computer, health record software, and Internet capabilities.
Physicians were given downloaded updates on prescriptions that were dispensed to their patients from the RAMQ drug insurance program.
Alerts were generated describing the problem with the medication, consequences, and alternative therapies.
|N = 107 PCPs
Intervention group: n = 54
Control group: n = 53
N = 12,560 patients (age ≥66, community-dwelling, and seen on at least two occasions by their physician)
Initiation and discontinuation rates of those given at least one inappropriate prescription.
Descriptive statistics, Pearson’s correlation coefficient, Poisson regression with generalized estimating equation
|Number of newly PIMs per 1,000 visits was lower in the CDS group by 18% when compared to the control group (RR = 0.82). A non-statistically significant discontinuation (14%) of preexisting PIPs occurred in the CDS group. There was a significant difference in the discontinuation of prescriptions for drug interactions among 68.6 per 1,000 visits in the CDS group versus 51.5 per 1,000 visits in the control group. Drug–disease, drug– age, and excessive duration were common prescribing problems.|
The previous computer experience of the physician was unknown.
Patients received care from at least three other physicians prescribing medications.
|Taylor, Byrd, & Krueger, 2003|
RCT, 2 groups
Prevention and monitoring of PIP and drug-related problems in older rural community-dwelling adults
Control group: usual care.
Patient met with one of four pharmacists for 20 minutes before seeing the physician.
Pharmacist used published algorithms and guide-lines to make recommendations to the provider.
Written and oral education was provided to the patient. Intervention group: usual and pharmaceutical care.
|Three community family medicine clinics in rural Alabama
Intervention group: n = 33
Control group: n = 36
Clinical endpoints: blood pressure, hemoglobin A1C, low density lipoproteins, and INR
Number of hospitalizations and ED visits and quality of life
RMANOVA, t test, chi square
|Number of hospitalizations and ED visits decreased in the intervention group (p = 0.003). The intervention group was closer to or met the goal blood pressure, hemoglobin A1C, cholesterol, and INR levels. Quality-of-life changes were not significant. The percentage of PIP decreased in the intervention group compared with the control group.|
Short follow-up period.
Physicians were not randomized, only patients.