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JANUARY 2015–VOL. 63, NO. 1
LETTERS TO THE EDITOR
6. McCloskey LW, Koepsell TD, Wolf ME et al. Motor vehicle collision injuries and sensory impairments of older drivers. Age Ageing 1994;23:267– 273. 7. Cross JM, McGwin G Jr, Rubin GS et al. Visual and medical risk factors for motor vehicle collision involvement among older drivers. Br J Ophthalmol 2009;93:400–404. 8. Platts-Mills TF, Hunold KM, Esserman DA et al. Motor vehicle collisionrelated emergency department visits by older adults in the United States. Acad Emerg Med 2012;19:821–827. 9. Platts-Mills TF, Ballina L, Bortsov AV et al. Using emergency departmentbased inception cohorts to determine genetic characteristics associated with long term patient outcomes after motor vehicle collision: Methodology of the CRASH Study. BMC Emerg Med 2011;11:14.
ASSOCIATION BETWEEN POTENTIALLY INAPPROPRIATE MEDICATION USE IN ELDERLY ADULTS AND HOSPITAL-RELATED OUTCOMES To the Editor: The Beers Criteria, which were updated in 2012 with support from the American Geriatrics Society, identify 34 potentially inappropriate medications (PIMs), independent of diagnoses, to avoid in individuals aged 65 and older.1 Prior research regarding the effect of PIMs on health outcomes has focused on community and nursing home settings, and data from hospitalized individuals are minimal.2–6 The objective of the current study was to evaluate the association between the inpatient use of PIMs and hospital outcomes.
METHODS Participants were individuals aged 65 and older admitted to the hospital between May 2012 and April 2013 with a primary International Classification of Diseases, Ninth Revision, code of pneumonia, acute myocardial infarction, or heart failure. Individuals admitted for observation, as outpatients, or to a surgical or intensive care service were excluded. Participants were categorized into four groups based on the number of PIMs prescribed during the index hospitalization using the 2012 Beers Criteria, independent of diagnosis. Categorical variables were evaluated using the chi-square test and continuous variables using analysis of variance between the four PIM categories. Four outcomes were evaluated: 30-day length of hospital stay (length of the index admission plus length of any readmission that occurred within 30 days), length of stay, total hospital costs, and 30-day readmission rate. Multivariate logistic
185
regression and multivariate general linear models were assembled to evaluate the outcomes, using one PIM as the reference in all cases. Statistical analyses were conducted using SPSS version 21 for Windows (IBM/ SPSS, Inc., Chicago, IL).
RESULTS Of 560 participants, 53% were male, 81% were Caucasian, 32% were aged 85 and older, and 68% had a mild burden of disease according to Charlson score; 46% were admitted for HF, 33% for myocardial infarction, and 21% for pneumonia. Six hundred forty-eight PIMs were prescribed to 380 participants, with the most common being sliding scale insulin (SSI) (33.5%), alprazolam (9.3%), lorazepam (9.3%), quetiapine (5.4%), and diphenhydramine (4.6%). In the fully adjusted model, participants prescribed two PIMs or three or more PIMs had significantly longer lengths of stay and 30-day hospital lengths of stay than those prescribed one PIM (Table 1). Individuals with three or more PIMs also had significantly higher hospital costs than those with one PIM. The number of PIMs prescribed did not significantly affect the odds of readmission within 30 days.
DISCUSSION Prescribing multiple PIMs in hospitalized elderly adults was associated with longer length of stay and higher hospital costs. The most common PIM was SSI, which the Beers Criteria suggest avoiding because of the risk of hypoglycemia and lack of efficacy in blood glucose control. Despite these recommendations, SSI is still prescribed, although the results may be overestimating its use because the current order entry system does not differentiate between sliding and correction scale. Other PIMs frequently encountered in this study also have risk:benefit profiles to be considered. For example, lorazepam is the preferred drug used at Hartford Hospital to manage alcohol withdrawal. The Beers Criteria acknowledge that some PIMs may be appropriate in certain situations such as advanced severe disease, highlighting the need for thorough clinical judgment for appropriateness. With this in mind, providers are encouraged to use the Beers Criteria to help screen for PIMs and limit their use when possible. Individuals aged 65 and older account for 41% of total hospital costs.7 As the population ages, this is expected to increase, highlighting the importance of
Table 1. Effect of Potentially Inappropriate Medications (PIMs) on Outcomes of Interest Outcome
Length of stay, days (95% CI) 30-day length of hospital stay, days (95% CI) Total hospital costs, $ (95% CI) 30-day readmission, adjusted odds ratio (95% CI)
0 PIM, n = 180
0.56 ( 0.31–1.45) 0.93 ( 0.80–2.67) 83.54 ( 2,063.45–1,896.35) 0.79 (0.34–1.85)
2 PIMs, n = 119
0.94 (0.01–1.86) 1.91 (0.90–3.74) 128.61 ( 2,208.96–1,951.72) 0.84 (0.39–1.58)
≥3 PIMs, n = 62
2.50 (1.26–3.74) 3.28 (0.85–5.71) 2,889.74 (1,14.10–5,665.39) 0.78 (0.46–1.53)
CI = confidence interval. Reference 1 PIM. All outcomes adjusted for age, admission diagnosis, Charlson Comorbidity Index, sex, race and ethnicity, marital status, payer, attending provider, and number of prescribed medications.
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identifying interventions to improve efficiency in healthcare spending. Results of this study suggest that PIMs may be one such intervention, although this should be evaluated in future research. Prior studies in hospitalized individuals have found no association between PIM use and mortality, length of stay, decline in activities of daily living, or discharge to a higher level of care.3–6 This study differs most notably in the categorization of number of PIMs rather than evaluating PIM use dichotomously. Along with achieving the estimated sample size, this allowed at which level PIM use negatively affected outcomes to be discerned. Nevertheless, the results should be considered in the context of study limitations. This study reflects prescribing patterns of one hospital in certain medical conditions, so the results may not be broadly applicable. PIM use was defined based on prescribing rather than actual use, and the results may have underestimated the risks associated with PIMs. Future prospective studies would eliminate the potential for residual confounding of variables that it was not possible to adjust for. Kelly Hagstrom, PharmD Pharmacy Services, Hartford Hospital, Hartford, Connecticut Michael Nailor, PharmD Pharmacy Services, Hartford Hospital, Hartford, Connecticut School of Pharmacy, University of Connecticut, Storrs, Connecticut Michael Lindberg, MD Geriatric and Palliative Medicine Institute, Hartford HealthCare, Hartford, Connecticut Laura Hobbs, PharmD Pharmacy Services, Hartford Hospital, Hartford, Connecticut Diana M. Sobieraj, PharmD School of Pharmacy, University of Connecticut, Storrs, Connecticut
ACKNOWLEDGMENTS The authors would like to thank Denis Gannon, PharmD, for his assistance with data collection. Conflict of Interest: The editor in chief has reviewed the conflict of interest checklist provided by the authors and has determined that the authors have no financial or any other kind of personal conflicts with this paper. Author Contributions: All authors contributed to this paper. Sponsor’s Role: None.
REFERENCES 1. American Geriatrics Society 2012 Beers Criteria Update Expert Panel. American Geriatrics Society updated Beers Criteria for potentially inappropriate medication use in older adults. J Am Geriatr Soc 2012;60:616– 631.
JANUARY 2015–VOL. 63, NO. 1
JAGS
2. Rothberg MB, Pekow PS, Liu F et al. Potentially inappropriate medication use in hospitalized elders. J Hosp Med 2008;3:91–102. 3. Jano E, Aparasu RR. Healthcare outcomes associated with Beers’ Criteria: A systematic review. Ann Pharmacother 2007;41:438–448. 4. Passarelli MCG, Jacob-Filho W, Figueras A. Adverse drug reactions in an elderly hospitalized population. Drugs Aging 2005;22:767–777. 5. Onder G, Landi F, Liperoti R et al. Impact of inappropriate drug use among hospitalized older adults. Eur J Clin Pharmacol 2005;61:453–459. 6. Corsonello A, Pedone C, Lattanzio F et al. Potentially inappropriate medications and functional decline in elderly hospitalized patients. J Am Geriatr Soc 2009;57:1007–1014. 7. Elixhaurse A, Steiner C. Readmissions to U.S. hospitals by diagnosis, 2010. HCUP statistical brief #153. Agency for Healthcare Research and Quality, Rockville, MD [on-line]. 2013. Available at http://www.hcup-us.ahrq.gov/ reports/statbriefs/sb153.pdf Accessed December 6 2014.
DEVELOPMENT OF AN AGE-DEPENDENT ANTIBIOGRAM IN A VETERANS AFFAIRS COMMUNITY
To the Editor: An antibiogram is a representation of the cumulative in vitro sensitivity of isolated bacterial species to different antibiotics at a given facility or healthcare system. Data from antibiograms are most useful when initiating empirical therapy and tracking antimicrobial resistance over time within a hospital or healthcare system.1 The Clinical and Laboratory Standards Institute, has published a guide for antibiogram development, Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data: Approved Guideline, which was most recently updated with its third edition in 2009.2 Though antibiograms are a feasible, inexpensive, and relatively rapid and accurate surveillance option for estimating prevalence and trends of antimicrobial susceptibility, they do not allow susceptibility results to be evaluated based on potential variables of interest, such as age. Previous research has shown variability in rates of susceptibility of individual pathogens with respect to different age groups.3 To the knowledge of the authors of the present study, there have been no published trials comparing age-stratified antibiograms. The William Jennings Bryan (WJB) Dorn Veterans Affairs Medical Center (VAMC) is a 216-bed facility in South Carolina that houses acute medical, surgical, and psychiatric services, as well as long-term care beds and a variety of primary care services. Primary care services are available to veterans at the main hospital location, as well as seven community-based outpatient clinics. Final culture and sensitivity results obtained during inpatient admissions and outpatient visits from January 1, 2013, through December 31, 2013, were used to identify individuals. Only the first isolate per microorganism per individual was considered for study inclusion. Additional isolates per species per individual within the study period were not included for analysis. Isolates were stratified based on patient age at the time of isolate collection into the adult antibiogram (aged
JANUARY 2015–VOL. 63, NO. 1
LETTERS TO THE EDITOR
6. McCloskey LW, Koepsell TD, Wolf ME et al. Motor vehicle collision injuries and sensory impairments of older drivers. Age Ageing 1994;23:267– 273. 7. Cross JM, McGwin G Jr, Rubin GS et al. Visual and medical risk factors for motor vehicle collision involvement among older drivers. Br J Ophthalmol 2009;93:400–404. 8. Platts-Mills TF, Hunold KM, Esserman DA et al. Motor vehicle collisionrelated emergency department visits by older adults in the United States. Acad Emerg Med 2012;19:821–827. 9. Platts-Mills TF, Ballina L, Bortsov AV et al. Using emergency departmentbased inception cohorts to determine genetic characteristics associated with long term patient outcomes after motor vehicle collision: Methodology of the CRASH Study. BMC Emerg Med 2011;11:14.
ASSOCIATION BETWEEN POTENTIALLY INAPPROPRIATE MEDICATION USE IN ELDERLY ADULTS AND HOSPITAL-RELATED OUTCOMES To the Editor: The Beers Criteria, which were updated in 2012 with support from the American Geriatrics Society, identify 34 potentially inappropriate medications (PIMs), independent of diagnoses, to avoid in individuals aged 65 and older.1 Prior research regarding the effect of PIMs on health outcomes has focused on community and nursing home settings, and data from hospitalized individuals are minimal.2–6 The objective of the current study was to evaluate the association between the inpatient use of PIMs and hospital outcomes.
METHODS Participants were individuals aged 65 and older admitted to the hospital between May 2012 and April 2013 with a primary International Classification of Diseases, Ninth Revision, code of pneumonia, acute myocardial infarction, or heart failure. Individuals admitted for observation, as outpatients, or to a surgical or intensive care service were excluded. Participants were categorized into four groups based on the number of PIMs prescribed during the index hospitalization using the 2012 Beers Criteria, independent of diagnosis. Categorical variables were evaluated using the chi-square test and continuous variables using analysis of variance between the four PIM categories. Four outcomes were evaluated: 30-day length of hospital stay (length of the index admission plus length of any readmission that occurred within 30 days), length of stay, total hospital costs, and 30-day readmission rate. Multivariate logistic
185
regression and multivariate general linear models were assembled to evaluate the outcomes, using one PIM as the reference in all cases. Statistical analyses were conducted using SPSS version 21 for Windows (IBM/ SPSS, Inc., Chicago, IL).
RESULTS Of 560 participants, 53% were male, 81% were Caucasian, 32% were aged 85 and older, and 68% had a mild burden of disease according to Charlson score; 46% were admitted for HF, 33% for myocardial infarction, and 21% for pneumonia. Six hundred forty-eight PIMs were prescribed to 380 participants, with the most common being sliding scale insulin (SSI) (33.5%), alprazolam (9.3%), lorazepam (9.3%), quetiapine (5.4%), and diphenhydramine (4.6%). In the fully adjusted model, participants prescribed two PIMs or three or more PIMs had significantly longer lengths of stay and 30-day hospital lengths of stay than those prescribed one PIM (Table 1). Individuals with three or more PIMs also had significantly higher hospital costs than those with one PIM. The number of PIMs prescribed did not significantly affect the odds of readmission within 30 days.
DISCUSSION Prescribing multiple PIMs in hospitalized elderly adults was associated with longer length of stay and higher hospital costs. The most common PIM was SSI, which the Beers Criteria suggest avoiding because of the risk of hypoglycemia and lack of efficacy in blood glucose control. Despite these recommendations, SSI is still prescribed, although the results may be overestimating its use because the current order entry system does not differentiate between sliding and correction scale. Other PIMs frequently encountered in this study also have risk:benefit profiles to be considered. For example, lorazepam is the preferred drug used at Hartford Hospital to manage alcohol withdrawal. The Beers Criteria acknowledge that some PIMs may be appropriate in certain situations such as advanced severe disease, highlighting the need for thorough clinical judgment for appropriateness. With this in mind, providers are encouraged to use the Beers Criteria to help screen for PIMs and limit their use when possible. Individuals aged 65 and older account for 41% of total hospital costs.7 As the population ages, this is expected to increase, highlighting the importance of
Table 1. Effect of Potentially Inappropriate Medications (PIMs) on Outcomes of Interest Outcome
Length of stay, days (95% CI) 30-day length of hospital stay, days (95% CI) Total hospital costs, $ (95% CI) 30-day readmission, adjusted odds ratio (95% CI)
0 PIM, n = 180
0.56 ( 0.31–1.45) 0.93 ( 0.80–2.67) 83.54 ( 2,063.45–1,896.35) 0.79 (0.34–1.85)
2 PIMs, n = 119
0.94 (0.01–1.86) 1.91 (0.90–3.74) 128.61 ( 2,208.96–1,951.72) 0.84 (0.39–1.58)
≥3 PIMs, n = 62
2.50 (1.26–3.74) 3.28 (0.85–5.71) 2,889.74 (1,14.10–5,665.39) 0.78 (0.46–1.53)
CI = confidence interval. Reference 1 PIM. All outcomes adjusted for age, admission diagnosis, Charlson Comorbidity Index, sex, race and ethnicity, marital status, payer, attending provider, and number of prescribed medications.
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identifying interventions to improve efficiency in healthcare spending. Results of this study suggest that PIMs may be one such intervention, although this should be evaluated in future research. Prior studies in hospitalized individuals have found no association between PIM use and mortality, length of stay, decline in activities of daily living, or discharge to a higher level of care.3–6 This study differs most notably in the categorization of number of PIMs rather than evaluating PIM use dichotomously. Along with achieving the estimated sample size, this allowed at which level PIM use negatively affected outcomes to be discerned. Nevertheless, the results should be considered in the context of study limitations. This study reflects prescribing patterns of one hospital in certain medical conditions, so the results may not be broadly applicable. PIM use was defined based on prescribing rather than actual use, and the results may have underestimated the risks associated with PIMs. Future prospective studies would eliminate the potential for residual confounding of variables that it was not possible to adjust for. Kelly Hagstrom, PharmD Pharmacy Services, Hartford Hospital, Hartford, Connecticut Michael Nailor, PharmD Pharmacy Services, Hartford Hospital, Hartford, Connecticut School of Pharmacy, University of Connecticut, Storrs, Connecticut Michael Lindberg, MD Geriatric and Palliative Medicine Institute, Hartford HealthCare, Hartford, Connecticut Laura Hobbs, PharmD Pharmacy Services, Hartford Hospital, Hartford, Connecticut Diana M. Sobieraj, PharmD School of Pharmacy, University of Connecticut, Storrs, Connecticut
ACKNOWLEDGMENTS The authors would like to thank Denis Gannon, PharmD, for his assistance with data collection. Conflict of Interest: The editor in chief has reviewed the conflict of interest checklist provided by the authors and has determined that the authors have no financial or any other kind of personal conflicts with this paper. Author Contributions: All authors contributed to this paper. Sponsor’s Role: None.
REFERENCES 1. American Geriatrics Society 2012 Beers Criteria Update Expert Panel. American Geriatrics Society updated Beers Criteria for potentially inappropriate medication use in older adults. J Am Geriatr Soc 2012;60:616– 631.
JANUARY 2015–VOL. 63, NO. 1
JAGS
2. Rothberg MB, Pekow PS, Liu F et al. Potentially inappropriate medication use in hospitalized elders. J Hosp Med 2008;3:91–102. 3. Jano E, Aparasu RR. Healthcare outcomes associated with Beers’ Criteria: A systematic review. Ann Pharmacother 2007;41:438–448. 4. Passarelli MCG, Jacob-Filho W, Figueras A. Adverse drug reactions in an elderly hospitalized population. Drugs Aging 2005;22:767–777. 5. Onder G, Landi F, Liperoti R et al. Impact of inappropriate drug use among hospitalized older adults. Eur J Clin Pharmacol 2005;61:453–459. 6. Corsonello A, Pedone C, Lattanzio F et al. Potentially inappropriate medications and functional decline in elderly hospitalized patients. J Am Geriatr Soc 2009;57:1007–1014. 7. Elixhaurse A, Steiner C. Readmissions to U.S. hospitals by diagnosis, 2010. HCUP statistical brief #153. Agency for Healthcare Research and Quality, Rockville, MD [on-line]. 2013. Available at http://www.hcup-us.ahrq.gov/ reports/statbriefs/sb153.pdf Accessed December 6 2014.
DEVELOPMENT OF AN AGE-DEPENDENT ANTIBIOGRAM IN A VETERANS AFFAIRS COMMUNITY
To the Editor: An antibiogram is a representation of the cumulative in vitro sensitivity of isolated bacterial species to different antibiotics at a given facility or healthcare system. Data from antibiograms are most useful when initiating empirical therapy and tracking antimicrobial resistance over time within a hospital or healthcare system.1 The Clinical and Laboratory Standards Institute, has published a guide for antibiogram development, Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data: Approved Guideline, which was most recently updated with its third edition in 2009.2 Though antibiograms are a feasible, inexpensive, and relatively rapid and accurate surveillance option for estimating prevalence and trends of antimicrobial susceptibility, they do not allow susceptibility results to be evaluated based on potential variables of interest, such as age. Previous research has shown variability in rates of susceptibility of individual pathogens with respect to different age groups.3 To the knowledge of the authors of the present study, there have been no published trials comparing age-stratified antibiograms. The William Jennings Bryan (WJB) Dorn Veterans Affairs Medical Center (VAMC) is a 216-bed facility in South Carolina that houses acute medical, surgical, and psychiatric services, as well as long-term care beds and a variety of primary care services. Primary care services are available to veterans at the main hospital location, as well as seven community-based outpatient clinics. Final culture and sensitivity results obtained during inpatient admissions and outpatient visits from January 1, 2013, through December 31, 2013, were used to identify individuals. Only the first isolate per microorganism per individual was considered for study inclusion. Additional isolates per species per individual within the study period were not included for analysis. Isolates were stratified based on patient age at the time of isolate collection into the adult antibiogram (aged
