Inappropriate Medication Prescriptions in Elderly Adults Surviving an Intensive Care Unit Hospitalization

Alessandro Morandi, MD, MPH; Eduard Vasilevskis, MD; Pratik P. Pandharipande, MD, MSCI; Timothy D. Girard, MD, MSCI; Laurence M. Solberg, MD; Erin B. Neal, PharmD; Tyler Koestner, MS; Renee E. Torres, MS; Jennifer L. Thompson, MPH; Ayumi K. Shintani, PhD, MPH; Jin H. Han, MD, MSc; John F. Schnelle, PhD; Donna M. Fick, PhD; E. Wesley Ely, MD, MPH; Sunil Kripalani, MD, MSc

Disclosures

J Am Geriatr Soc. 2013;61(7):1128–1134 

In This Article

Discussion

Medications are the primary cause of adverse events for elderly adults after hospital discharge.[6,20] Significant attention has been focused on reducing prescription of PIMs, but some of these medications are appropriately prescribed to individuals with complicated health status, who are likely to benefit from them. Thus, attention should be directed specifically toward reducing AIMs. This study found that three of the most commonly prescribed types of PIMs (opioids, antidepressants, and drugs causing orthostasis) were often judged to be appropriate after considering the individual's clinical condition (e.g., postoperative pain control, a new diagnosis of major depressive disorder). These PIM categories, therefore, had low PPV for detecting AIMs in older survivors of critical illness. In addition, the risk factors for being prescribed a PIM at discharge were not necessarily risk factors for being prescribed an AIM. This study, the first to specifically evaluate ICU survivors for receipt of PIMs and AIMs, suggests that published lists of PIMs may not be an efficient screening tool for identifying and thereby reducing prescription of AIMs to older adults after critical illness. Instead, a more-refined list of PIMs with high PPV is needed, as is knowledge regarding risk factors for receipt of AIMs after critical illness.

A critical feature of the investigation was a thorough evaluation of the actual appropriateness of each PIM based on the clinical circumstances. It was recently emphasized that studies of PIMs should determine scenarios in which it is appropriate to prescribe PIMs, moving beyond simply labeling some medications as "potentially inappropriate," because some PIMs are appropriately prescribed in specific clinical situations.[26]Clinicians caring for older adults, especially at the end of a complex hospital stay, must determine which PIMs should be discontinued before hospital discharge and which are appropriately prescribed.

The finding that some common PIMs were rarely AIMs has significant implications. If one views a list of PIMs as a screening tool, any given item (e.g., medication class) on the list has 100% sensitivity for detecting an AIM in that medication class and 100% negative predictive value (NPV) for excluding AIMs in that class. (In general, the NPV is defined as the percentage of subjects with a negative test result who are correctly diagnosed.) Unfortunately, some items on the screening tool will have low PPV for the identification of an AIM (e.g., opiates in this cohort), whereas others will have high PPV (e.g., atypical antipsychotics in this cohort). This study shows that the PPV depends on the drug type. Thus, when developing a screening system, one cannot be concerned only with high NPV, one must consider PPV as well. Screening tools that include medication classes with low PPV will generate false-positive "flags" or warnings, which could lead to misguided clinical decisions or alert fatigue.[27] In the current cohort, for example, if clinicians were alerted to each opiate prescription at the time of discharge, this may have led to inappropriate discontinuation of an appropriate medicine needed for pain control, change to a potentially more-harmful alternative, and a decrease of the effect of such alerts regarding PIMs that have much higher PPVs for being AIMs. It is likely that electronic warning systems will be valuable in reducing AIMs after critical illness, but the systems that rely on PIMs as screening tools should include only those with the highest PPV, which in the current study were the atypical antipsychotics (71%), nonbenzodiazepine hypnotics (67%), benzodiazepines (67%), anticholinergics (55%), and muscle relaxants (100%).

The fact that many PIMs are not AIMs also reveals the value of using a multidisciplinary team to identify AIMs from lists of PIMs generated when discharge medication lists are screened. In this study, a team was created with a geriatrician, internist, and pharmacist, all of whom are often involved in the care of elderly hospitalized adults.[28] Whereas a computer-based decision support system can easily identify PIMs using structured data,[29] evaluating the clinical context is far more complicated, especially for older ICU survivors. Thus, a multidisciplinary team is needed to consider the clinical context to distinguish PIMs from AIMs. Such a team is not available in some settings; when resources are limited, knowledge of which PIMs are most likely AIMs (have high PPVs) could guide the development of computer-based decision support systems or other surveillance approaches that are efficient in that particular setting.

Interventions designed to reduce AIMs need not be implemented solely at the time of hospital discharge. Nearly two of every three AIMs were first prescribed in the ICU, a time during which the medication may have been appropriately given. For example, nonbenzodiazepine sedatives (e.g., zolpidem, choral hydrate) and atypical antipsychotics are frequently used in the ICU because delirium and sleep cycle alteration are common complications of critical illness.[30,31] Even though these and other PIMs may be appropriate early in the ICU course, the indications for their use are usually temporary. Failing to discontinue such medications before hospital discharge is potentially harmful in the long-term.[32,33] Thus, clinicians should seek to identify and discontinue AIMs at three important transitions during a critically ill elderly adult's hospital course. Clinicians should review medication appropriateness at the time of hospital or ICU admission. Another evaluation should be performed at the time of ICU discharge. Finally, medications should be screened for PIMs at hospital discharge, and the individual's clinical situation should be reviewed, ideally by a multidisciplinary team of clinicians, to judge the appropriateness of each PIM. Electronic health records could be leveraged to alert clinicians at each of these times to the presence of PIMs, particularly those with high PPVs for being AIMs.

Strategies designed to reduce AIMs would be more focused if the specific individuals most likely to receive AIMs or the providers most likely to prescribe them were known. In this small study, it was not possible to demonstrate significant risk factors associated with the number of AIMs at discharge; thus, additional research is needed to target AIM-reducing interventions. Although no risk factors were found for AIMs, it was found that a large number of preadmission PIMs, discharge to a location other than home, and discharge from a surgical service were are all predictive of a large number of PIMs at discharge. These risk factors have been found in other studies as well.[9,25,34] The fact that PIM risk factors were not associated with AIMs highlights, once again, that interventions designed to identify PIMs will not always efficiently identify AIMs. A particular PIM category (e.g., opioids) that the clinical panel usually deemed appropriate given the clinical circumstances (e.g., treatment of postoperative pain) may have driven some of the factors that independently predicted PIMs (e.g., discharge from a surgical service). In these situations, it is likely that the PIM risk factors are associated with the indications that led to appropriate prescription and continuation of the PIMs. Risk factors specific to AIMs rather than PIMs are therefore needed to shape efficient interventions. A smaller sample size of AIMs may have hampered the ability to identify risk factors, because that reduced statistical power. Larger, multicenter investigations may therefore still identify risk factors for AIMs. Until such factors are known, efforts to reduce AIMs should focus on the PIM categories that are almost always inappropriate at discharge (those with high PPVs), such as atypical antipsychotics, nonbenzodiazepine hypnotics, benzodiazepines, anticholinergics, and muscle relaxants.

An association between delirium days, PIMs, and AIMs had been hypothesized. The nature of the statistical analysis, which examined potential predictors of PIMs and AIMs overall, may explain the lack of such a relationship. Delirium duration might be associated with greater prescription of specific PIMs or AIMs, such as antipsychotics or benzodiazepines, but the sample size was too small to examine predictors of specific PIM or AIM types. Future studies with larger samples should evaluate this question further.

One limitation of this study is that the short- and long-term adverse clinical outcomes (e.g., functional and cognitive status, rehospitalization, institutionalization) related to AIM prescription were not evaluated. Ultimately, development of an evidence base that specifies the likelihood of harm associated with different medications, under different clinical circumstances, would provide detailed guidance to providers about the relative risks and benefits of particular agents in elderly adults. Such a knowledge base could be incorporated into computerized order entry systems and drug safety surveillance programs. Further studies are needed to link PIMs and AIMs to adverse events so that such systems can be developed.

This study has several other limitations. First, only prescribed medications, and not the cohort, were examined for inappropriate underprescribing or medication discontinuation, any of which can expose individuals to risk, as recently highlighted.[35] Second, the single-center nature of this study limits generalizability of the results to populations similar to the one studied. Third, this study was performed before the 2012 Beers update was published.[23] The majority of the medications added to the 2003 Beers criteria based on a review of the medication safety literature[6,20,21] have also been included in the 2012 update, supporting the approach of the current study, but some of the medications may require further deliberation before widely being considered PIMs. Fourth, owing to the multidisciplinary adjudication process used, agreement between individual clinicians in the panel regarding their determination of AIMs was not assessed. It is possible that biases within the panel (e.g., personality or hierarchical relationships) influenced determinations, although an attempt was made to minimize this by the selection of individuals (who were approximately the same age and did not have dominating personalities) and requirement for agreement between at least two of three adjudicators. Fifth, the effect of each clinical discipline (e.g. cardiology, nephrology, orthopedics, etc.) on the risk of prescribing PIMs and AIMs was not specifically evaluated; this should be further evaluated.

In summary, PIMs (medications often associated with adverse effects) prescribed to elderly adults at hospital discharge were common and most often initiated during their ICU stay. Most of these PIMs were considered appropriate upon clinical review, which may explain why risk factors were identified for PIMs at discharge but not for AIMs. That many PIMs were not AIMs highlights the importance of clinical context in assessing the safety of medications at discharge. If medication safety programs focus on reducing AIMs rather than PIMs (e.g., by screening primarily PIMs with high PPV for AIMs), they may save time and money by avoiding unnecessary scrutiny of medications that are appropriately prescribed and focusing attention on higher-risk medications.

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