research and reports

Research and Reports Prevalence of and Factors Associated with Therapeutic Failure-Related Hospitalizations in the Elderly Roshni S. Patel, Zachary A. Marcum, Emily P. Peron, Christine M. Ruby Objective: A therapeutic failure (TF) is defined as a failure to

accomplish the goals of treatment attributable to inadequate therapy, a drug-drug interaction that results in a subtherapeutic level for a drug, or medication nonadherence. The objective of this study was to evaluate the prevalence of and factors associated with TF-related hospitalizations in older adults. Design: This investigation was a retrospective cohort study. Setting: This study was conducted within a university-based hospital setting. Patients: This investigation included patients with a primary care physician from the University of Pittsburgh Medical Center (UPMC) Senior Care Institute admitted to any UPMC hospital between September 1, 2011, and December 1, 2011. Interventions: Chart abstracts of patient records were screened for a TF using a validated tool called the Therapeutic Failure Questionnaire (TFQ). Covariate data were also obtained. Descriptive statistics and bivariate analyses using Fisher’s exact tests were conducted to assess the association between the covariates and the primary outcome. Main Outcome Measure(s): The primary outcome was the presence of a TF as measured by the TFQ. Secondary outcomes included associations between covariates and the presence of a TF. Results: Of the 93 hospitalizations screened, 57 met inclusion criteria, and 18% of hospitalizations were as a result of preventable TFs. On bivariate analyses, both congestive heart failure (P = 0.03) and dependency for medication management (P = 0.04) were significantly associated with occurrence of TF. Conclusions: TFs are a potentially preventable cause of hospitalization in the elderly population and are commonly caused by omission of therapy. Key Words: Elderly, Geriatrics, Hospitalizations, Medication errors, Therapeutic failure.

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Abbreviations: ACE = Angiotensin-converting enzyme,

CHF = Congestive heart failure, CKD = Chronic kidney disease, COPD = Chronic obstructive pulmonary disease, CVA = Cerebrovascular accident, HF = Heart failure, PCP = Primary care physician, START = Screening Tool to Alert doctors to Right Treatment, STOPP = Screening Tool of Older Person’s Prescriptions, TF = Therapeutic failure, TFQ = Therapeutic failure questionnaire, UPMC = University of Pittsburgh Medical Center, UTI = Urinary tract infection, VA = Veterans Affairs. Consult Pharm 2014;29:376-86.

Introduction Older adults (65 years of age or older) represent about 13% of the United States population; yet they account for approximately 37% of hospital discharges.1,2 With the elderly population predicted to double to an estimated 71 million by 2030, hospitalizations among older adults are a significant public health concern.3 More specifically, drugrelated hospitalizations are a significant cause of morbidity and mortality in older adults, and they are associated with substantial health care costs and resource consumption.4 Of particular concern is that many of these hospitalizations are deemed preventable. For example, in a systematic review of 17 observational studies, Howard and colleagues found that two-thirds of drug-related admissions were a result of either suboptimal prescribing or patient nonadherence.5 This is important because suboptimal prescribing and patient nonadherence are two of the most common causes of therapeutic failures (TFs). A TF is defined as a failure to accomplish the goals of treatment.6 A TF can be attributed to inadequate medication therapy, either as a result of the omission of a necessary drug or a prescribing issue resulting in an inappropriate drug dose. A TF can also arise from a drug-drug interaction that results in a subtherapeutic level for a drug. Medication nonadherence on the part of the patient can also result in a TF. There is a validated and reliable instrument called the Therapeutic Failure Questionnaire (TFQ) that is available for the measurement of TFs. It was created using the

The Consultant Pharmacist JUNE 2014 Vol. 29, No. 6

Factors Associated with Therapeutic Failure-Related Hospitalizations

same concepts as the Naranjo Adverse Drug Reaction algorithm.6 However, limited literature is available assessing TF-related hospitalizations. To date, only two studies within the United States have documented TF-related admissions in the older adult population using this tool.6,7 In the first study, more than 10% of patients were found to have had at least one TF that led to hospitalization.6 In the second study, 5% of unplanned hospitalizations were caused by TFs, and approximately 90% of admissions were found to be preventable.7 Both studies identified congestive heart failure (CHF) and chronic obstructive pulmonary disease (COPD) as the most common medical conditions associated with TFs. However, both were also limited to an older veterans population. Thus, the current study sought to expand the literature on TF-related hospitalizations by assessing the prevalence of and factors associated with TF-related hospitalizations in older adults in a university-based hospital setting. Additionally, we examined the preventability of these events.

Methods Study Design, Setting, and Sample A retrospective cohort study was conducted including patients with a primary care physician from the University of Pittsburgh Medical Center (UPMC) Senior Care Institute clinic who were admitted to any UPMC hospital between September 1, 2011, and December 1, 2011. Patients were considered eligible if they were 65 years of age or older and were patients of the senior care clinic (i.e., having had at least one documented visit at the site within one year prior to the date of admission). Patients who did not have at least one history and physical note and at least one discharge summary note associated with the hospitalization in the medical record were excluded. Patients who were transferred from a non-UPMC-affiliated facility were also excluded as were patients whose admissions were “planned,” operationally defined as admissions for any elective or scheduled surgical procedures. Finally, any repeat hospitalization within the three-month time period was excluded. This study was approved by the University of Pittsburgh Institutional Review Board.

Data Sources Data were obtained from a combination of sources. First, inpatient hospital records from the time of admission were collected, which included the admission history and physical, discharge summary, laboratory data, and progress notes. Second, medication data were obtained from the electronic medical record that included both inpatient and outpatient records. Third, outpatient records (all notes and documented encounters, including office, informational, and telephone) were subject to examination, beginning with encounters that occurred one year prior to the date of hospital admission. Fourth, laboratory data within the year prior to admission and obtained in the outpatient setting were also subject to examination. Study Chart Abstracts, Data Collection, Screening, and Evaluation Patients were identified by a computer-generated summary of UPMC inpatient discharges for patients with a primary care physician from the senior care clinic. A chart abstract was then constructed for each patient who met the inclusion criteria. These abstracts included information obtained from data sources, described above. Total number of medications at hospital admission, medication allergies, the event description for admission, primary and secondary admission diagnoses (along with International Classification of Diseases-9 codes), a list of the patient’s medications at admission and discharge, and documented medical conditions were all collected from the study chart abstract and summarized on a data collection form. The drug(s) suspected to be involved in the potential TF was also recorded. To screen for potential TFs, a clinical pharmacist, who was adequately trained in using the TFQ, reviewed each chart abstract using previously established methods.6,7 If the hospitalization was considered to be medicationrelated, a TFQ assessment was conducted for each medication potentially associated with the TF for that patient (Appendix I). TFs were categorized into one of four groups, depending upon the TFQ score: unlikely TF (score -2 to 0), possible TF (score 1-3), probable TF (score 4-7), or likely TF (score ≥ 8). For TF-related


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Research and Reports hospitalizations that involved more than one medication, the cause of the hospitalization was determined based on the medication with the highest TFQ score. For chart abstracts that screened positive for a possible, probable, or likely TF, a separate clinical pharmacist, also trained to use the TFQ, independently evaluated whether the hospitalization was causally related to a TF using the TFQ. Evaluation discordances were resolved by consensus of a third clinical pharmacist. Additionally, a fourth clinical pharmacist reviewed every tenth abstract to determine whether the hospitalization was related to a TF using the TFQ to ensure interrater reliability of the TF assessment (measured using the kappa statistic), which was found to be adequate (0.77). Each confirmed TF was evaluated further for preventability. It is important to note that this assessment of preventability has not been previously validated and was not included in the original TFQ assessment. However, preventability is an important concept in any such study conducted to assess medication-related problems, and we based our assessment on previous research.7 For this study, preventability was defined as a medication error occurring in the prescribing, ordering, communicating, dispensing, or monitoring of the medication-use process or medication nonadherence.7 Additionally, the specific reason for the TF (i.e., omission of therapy, inappropriate drug use, drug-drug interaction, inappropriate monitoring, or nonadherence) was recorded. In this study, nonadherence was identified solely by provider documentation.

Primary Outcome The primary outcome was the presence of a TF as measured by the TFQ. The outcome was dichotomized as any possible, probable, or likely event versus unlikely. Covariates To determine which factors were associated with the primary outcome, various potential covariates were obtained. Using an established model for health services research, these covariates were grouped into three categories: demographics, health status, and access to care.8

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Demographics Patient records were evaluated for identification of age at admission (in years), race, gender, and marital status. Type of residence of the patient prior to admission (e.g., whether the patient was admitted to the hospital from a community setting or from an assisted living facility) was also identified. Health Status The presence of particular baseline comorbid conditions was recorded. These conditions were chosen based on the Agency for Healthcare Research and Quality’s previously collected data on the top 10 reasons for hospitalizations among older adults.3 A categorical variable was created for the number of regularly scheduled medications the patient was prescribed on admission (0-4, 5-8, or ≥ 9). Medication management data were collected from the hospital admission or outpatient encounter notes, and patients were categorized as either dependent (relying on another individual for any component of taking their medications) or independent. Finally, whether the patient received influenza and pneumococcal vaccinations prior to the admission was determined. Access to Care The use of a community pharmacy, a mail-order pharmacy, or both was recorded. A categorical variable was created for the number of primary care physician appointments at the senior care clinic within the past year, and a dichotomous (none; ≥ 1) variable was created for UPMC emergency department visits within the past year. Statistical Analysis Descriptive statistics (means and percentages) were used to summarize the primary dependent variable and covariates. In addition, for descriptive purposes, the preventability and reason for the TF were assessed. Bivariate analyses using Fisher’s exact tests were conducted to assess the association between the covariates (demographics, health status, and access to care) and the primary outcome (TF). Of note, because of the small number of TF-related admissions, we were not able to conduct multivariable statistical



analyses for this outcome.9 All statistical analyses were conducted using SAS® version 9.2 (SAS® Institute, Inc., Cary, NC).

Results There were a total of 93 hospitalizations assessed during the three-month period. Of these hospitalizations, 57 met the inclusion criteria and 36 admissions were excluded for reasons described in Figure 1. The mean age of the sample population was 83.8 years (± 7); 35% of the patients were male and 86% were white (Table 1). A majority of patients were married and admitted from a community setting. In addition, 58% of the patients had a history of having a fracture or fall, 49% had coronary atherosclerosis, 46% had a history of dysrhythmias, and 37% had CHF at baseline. Overall, 10 (17.5%) hospitalizations were found to be a result of a TF and were associated with 13 different medications. Metoprolol was involved in two separate TFs. All 10 hospitalizations were rated to be “probable” TFs, with a TFQ score between 4 and 7. The most common organ system involved in the reason for admission was the cardiovascular system (6/10). Other TF-related hospitalizations were gastrointestinal (2/10), infectious (1/10), and respiratory (1/10) in nature.

The most common reason for TF was omission of therapy. Nonadherence and prescribing too low of a dose were additional causes of TFs (Table 2). Regardless of the cause, all TFs were considered to be potentially preventable as all 10 identified TFs were a result of a medication error occurring in the prescribing aspect of the medication-use process (8/10) or medication nonadherence (2/10). On bivariate analysis, the presence of CHF as a baseline comorbid condition was associated with a TF-related hospitalization (P = 0.03; Table 3). The medication class most commonly involved in these CHF cases was loop diuretics. In addition, requiring assistance with medication management was associated with a TF-related hospitalization (P = 0.04).

Discussion We found that approximately 18% of hospitalizations in older adults at a university-based hospital were the result of TFs. This rate is higher than the 11% previously reported in the study by Kaiser et al. and the 5% reported by Marcum et al.6,7 One reason for this difference in TF prevalence might be that our study population was older compared with the previous two studies. Similar to the previous two studies, the most common TF-related

Figure 1. Inclusion and Exclusion Criteria


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Research and Reports

Table 1. Characteristics of Senior Care Institute Clinic Patients Admitted to the Hospital (N = 57) Covariate

n (%)

Demographic Covariates Age (years), mean (± SD) Male gender Race/Ethnicity Black White

84 (± 7) 20 (35.1)

Number of regularly scheduled medications 0-4 5 (8.8) 5-8 16 (28.0) ≥ 9 36 (63.2)

8 (14.0) 49 (86.0)

Management of medications Independent Dependent

Marital status Single Married Divorced Widowed

3 (5.3) 29 (50.9) 1 (1.7) 24 (42.1)

Residence prior to admission Community-dwelling Assisted living facility Health Status Covariates Presence of comorbid conditions Congestive heart failure History of pneumonia Coronary atherosclerosis Cardiac dysrhythmias History of myocardial infarction History of acute cerebrovascular event (stroke) History of thromboembolism Diabetes mellitus Chronic obstructive pulmonary disease History of fracture/fall

Vaccination Influenza vaccination Pneumococcal vaccination

24 (42.1) 49 (86.0)

Access to Health Care Covariates Number of primary care physician appointment(s) in the last year 1-2 17 (29.8) 3-5 31 (54.4) > 5 9 (15.8) UPMC emergency department 34 (59.7) visit(s) in the past year (≥ 1) Type of pharmacy utilized Community pharmacy 47 (82.5) Community and mail- 10 (17.5) order pharmacy

47 (82.5) 10 (17.5)

21 (36.8) 4 (7.0) 28 (49.1) 26 (45.6) 15 (26.3) 14 (24.6)

Abbreviation: UPMC = University of Pittsburgh Medical Center.

6 (10.5) 18 (31.6) 9 (15.8) 33 (57.9)

admissions were CHF exacerbations; the involvement of loop diuretics in these TF-related admissions was consistent with previous literature as well. In addition, this study was able to show a statistically significant correlation between having CHF at baseline and experiencing any TF-related admission, which is a new finding. The correlation between requiring assistance with medication management and experiencing any TF-related admission was also a new finding.

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30 (52.6) 27 (47.4)

The most common cause of TF-related hospitalization was omission of therapy, which accounted for 70% of the TF-related admissions identified in this study. In the previous two studies, nonadherence was the most common cause of TF-related admission. This could be because the previous two studies were conducted in a Veterans Affairs (VA) setting, and refill records from the VA’s electronic medical record were used to determine adherence. Thus, because of limited access to refill histories in our study,



Table 2. Characteristics of TF-Related Hospitalizations TF No.

Specific Medical Condition

Medication(s) Involved

1 2

Crohn’s disease AF

3 4 5 6 7 8 9

Pancreatic insufficiency CHF TIA/CVA COPD TIA/CVA UTI CHF

10

CHF

Mesalamine Amiodarone Metoprolol Pancrealipase Furosemide Warfarin Fluticasone/Salmeterol Statin therapy Escherichia coli-sensitive antibiotic Telmisartan Furosemide Metoprolol Lisinopril Bumetanide

TFQ Score Cause of TF 4 6 6 4 5 4 4 4 5 3 5 6 2 5

Omission of therapy Omission of therapy Nonadherence Nonadherence Omission of therapy Omission of therapy Omission of therapy Omission of therapy Omission of therapy

Dose too low

Abbreviations: AF = Atrial fibrillation, CHF = Congestive heart failure, COPD = Chronic obstructive pulmonary disease, CVA = Cerebrovascular accident, TF = Therapeutic failure, TFQ = Therapeutic Failure Questionnaire, TIA = Transient ischemic attack, UTI = Urinary tract infection.

adherence to medications may have been overestimated. In one TF-related admission associated with warfarin, the patient had previously been on the drug for atrial fibrillation and had developed a hematoma. Because of the hematoma, warfarin was discontinued; subsequently the reason for admission in this study was a cerebrovascular accident (CVA), after which warfarin was thus restarted. This is important because hematomas are not absolute contraindications to warfarin therapy, and continued use of the drug may have prevented the CVA and admission. The American Geriatrics Society Updated Beers Criteria are often used to identify potentially inappropriate prescribing in older adults.10 However, a separate approach to identify inappropriate prescribing also exists and is known as the Screening Tool of Older Person’s Prescriptions (STOPP) and the Screening Tool to Alert Doctors to Right Treatment (START).11 In particular, the START criteria are an effort to avoid underprescribing in the presence of no contraindications to therapy. The use of warfarin in the presence of chronic atrial fibrillation is listed on

the START criteria. Other START criteria include statin therapy with documented history of cerebral vascular disease, angiotensin-converting enzyme (ACE) inhibitor with CHF, and regularly inhaled beta2-agonist and corticosteroid for moderate asthma or COPD, all of which were found to be omitted in this study and subsequently the cause of a TF-related hospitalization. Therefore, the need for evidence-based pharmacologic regimens is highlighted by our findings. Previous international studies also describe the importance of using optimal therapeutic regimens to prevent TFs.12,13 However, it is important to recognize that a patient’s remaining life expectancy can influence new prescribing decisions. Patient preference may also play a role in omission of therapy, especially when a patient makes the decision not to use an evidencebased medication secondary to previously experiencing an adverse event. In a TF-related admission classified as infectious in nature, a specific drug was not identified as being omitted, but rather any drug that was sensitive to Escherichia coli as


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Table 3. Comparison of Covariates According to the Presence or Absence of TF (N = 57) Covariate

With TF n = 10 n (%)

P-Value

6 (12.8) 19 (40.4) 22 (46.8)

1 (10.0) 3 (30.0) 6 (60.0)

0.88

17 (36.2) 30 (63.8)

3 (30.0) 7 (70.0)

1.00

8 (17.0) 39 (83.0)

0 (0.0) 10 (100.0)

0.33

3 (6.4) 23 (48.9) 1 (2.1) 20 (42.5)

0 (0.0) 6 (60.0) 0 (0.0) 4 (40.0)

1.00

7 (70.0) 3 (30.0)

0.36

14 (29.8) 2 (4.2) 24 (51.1) 19 (40.4) 13 (27.7) 9 (19.2) 5 (10.6) 14 (29.8) 7 (14.9) 25 (53.2)

7 (70.0) 2 (20.0) 4 (40.0) 7 (70.0) 2 (20.0) 5 (50.0) 1 (10.0) 4 (40.0) 2 (20.0) 8 (80.0)

0.03 0.14 0.73 0.16 1.00 0.10 1.00 0.71 0.65 0.17

5 (10.6) 14 (29.8) 28 (59.6)

0 (0.0) 2 (20.0) 8 (80.0)

0.65

28 (59.6) 19 (40.4) 19 (40.4) 41 (87.2)

2 (20.0) 8 (80.0) 5 (50.0) 8 (80.0)

0.04

Without TF n = 47 n (%) Demographic Covariates

Age (years) 65-74 75-84 85+ Gender Male Female Race/Ethnicity Black White Marital status Single Married Divorced Widowed Residence prior to admission Community-dwelling Assisted living facility

40 (85.1) 7 (14.9) Health Status Covariates

Presence of comorbid conditions Congestive heart failure History of pneumonia Coronary atherosclerosis Cardiac dysrhythmias History of myocardial infarction History of acute cerebrovascular event (stroke) History of thromboembolism Diabetes mellitus Chronic obstructive pulmonary disease History of fracture/fall Number of regularly scheduled medications 0-4 5-8 ≥9 Management of medications Independent Dependent Influenza vaccination Pneumococcal vaccination 382

0.73 0.62



Table 3. Comparison of Covariates According to the Presence or Absence of TF (N = 57) (continued) Covariate

Without TF n = 47 n (%)

Access to Health Care Covariates Number of primary care physician appointments in the last year 1-2 16 (34.0) 3-5 24 (51.1) >5 7 (14.9) UPMC emergency department visit(s) in the past 27 (57.4) year (≥ 1) Type of pharmacy utilized Community pharmacy 39 (83.0) Community and mail-order pharmacy 8 (17.0)

With TF n = 10 n (%)

P-Value

1 (10.0) 7 (70.0) 2 (20.0) 7 (70.0)

0.29

8 (80.0) 2 (20.0)

1.00

0.72

Abbreviations: TF = Therapeutic failure, UPMC = University of Pittsburgh Medical Center.

determined by urinalysis. In this particular TF, the patient had an outpatient appointment at the senior care clinic at which time she presented with symptoms of a urinary tract infection (UTI). A urinalysis was obtained, and ciprofloxacin was ordered (as the patient had a sulfa allergy). The results of the urinalysis demonstrated that the E. coli infection was resistant to ciprofloxacin; however, therapy was not changed, and the patient subsequently developed Clostridium difficile, in addition to her persistent UTI, and was hospitalized. Proper attention and response to sensitivity data and appropriate pharmacotherapy for the UTI may have prevented this hospitalization. For the geriatric population, polypharmacy is often the target of clinical interventions, as an increase in the number of medications cannot only lead to nonadherence and multiple drug-drug interactions, but also can serve as a risk factor for morbidity and mortality.14,15 Despite this, polypharmacy was not found to be associated with TF-related hospitalizations in this study. This finding may be related to the fact that omission of therapy was the most common cause of TF-related hospitalization, indicating that patients should have been on additional therapy. Previous studies have also failed to show an association between the number of regularly scheduled home medications and TF-related admissions.6,7 Therefore, solely using

polypharmacy as a risk factor for a TF may be inappropriate. However, since CHF was shown to be associated with TF-related hospitalizations, it may be important to focus clinical pharmacy services on targeting older adults with specific medical conditions, such as CHF, in addition to polypharmacy. In fact, a pharmacist-led intervention has been shown to have a beneficial effect among heart failure (HF) patients; specifically, the intervention led to a 19.4% reduction in the incidence rate ratio for emergency department visits and hospital admissions compared with control patients.16 Pharmacists involved in a multidisciplinary HF team can offer a variety of clinical services, such as those involving a medication profile and laboratory review, medication titration, therapeutic drug monitoring, patient education and adherence counseling, and solutions for increasing medication access.17 Performing medication reconciliation can also help to avoid medication errors associated with complex HF regimens, especially during transitions in care. Ultimately, targeting patients with CHF, and ensuring that they are on evidence-based therapy (e.g., adequate doses of a diuretic, beta-blocker, and ACE inhibitor), may lead to optimal patient outcomes, avoidance of both hospitalizations and reimbursement penalties for readmissions, and an overall reduction in health care costs. When considering medical conditions


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Research and Reports other than CHF that may serve as a risk factor for TF-related hospitalizations, note that previously there has been mixed results regarding the association between severe chronic kidney disease (CKD) and the presence of a TF.6,7 However, this study did not include CKD as a covariate, and therefore we cannot rule out the possibility of such an association. This study was the first to identify assistance with medication management as a variable associated with TF-related hospitalizations and suggests that those patients requiring assistance with their medication management are at risk for experiencing a TF-related admission. Patients requiring assistance with their medications often have complex medication regimens and may be functionally and/or cognitively impaired; it is possible that these patients are more ill than their counterparts who do not require assistance. Moreover, caregivers’ administration of medications is often subject to error because of the complexity of the medication regimen and of a caregiver’s work schedule.18 In this study, nonadherence was also a cause of TF-related hospitalization for 2 of the 10 TFs. In both cases, patients required assistance from a second party with regards to medication management. Therefore, it is prudent to stress the importance of educating caregivers, as well as the patients themselves, about medication regimens. This study has several limitations. The small sample size and the small number of TF cases precluded us from conducting multivariate analysis to account for confounding variables when determining association between covariates and the primary outcome. Therefore, further research in assessing for TF-related hospitalizations utilizing the TFQ should be conducted in large representative samples. Additionally, medication adherence may have been overestimated as described previously and could possibly be additional and hidden causes of TFs. Finally, it is important to recognize that medications are often initiated at lower doses in the elderly population to avoid adverse drug events; this may influence those TFs caused by too low of a dose. Despite these limitations, this study also had several strengths worth noting. Unlike previous studies, it was not limited to a VA population and thus included a

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more gender-balanced study sample. Additionally, having access to both the inpatient and outpatient records for data collection was beneficial for detecting TFs, as many decisions made in the outpatient setting during clinic visits contributed to the indication for admission.

Conclusion TFs are a potentially preventable cause of hospitalization among older adults. The prevalence of TF-related hospitalization in this study was 18%, most TFs were caused by omission of therapy, and all were deemed preventable. CHF and dependency for medication management were both found to be associated with TF-related hospitalizations; these factors may represent new targets for identifying older adults with the greatest potential to benefit from pharmacy services and clinical interventions. However, more studies are needed to fully examine risk factors for TF-related hospitalizations. Roshni S. Patel, PharmD, BCPS, is assistant professor, Department of Pharmacy Practice, Thomas Jefferson University, Jefferson School of Pharmacy, Philadelphia, Pennsylvania. Zachary A. Marcum, PharmD, MS, BCPS, is assistant professor, Division of Geriatric Medicine, University of Pittsburgh, School of Medicine, Pittsburgh, Pennsylvania. Emily P. Peron, PharmD, MS, is assistant professor, Department of Pharmacotherapy and Outcomes Science, School of Pharmacy, Virginia Commonwealth University, Richmond, Virginia. Christine M. Ruby, PharmD, BCPS, is assistant professor, Department of Pharmacy and Therapeutics, University of Pittsburgh, School of Pharmacy, Pittsburgh. For correspondence: Roshni S. Patel, PharmD, BCPS, Department of Pharmacy Practice, Thomas Jefferson University, Jefferson School of Pharmacy, 901 Walnut St, Suite 901, Philadelphia, PA 19107; Phone: 215-503-8526; Fax: 215-503-9052; E-mail: [email protected]. Acknowledgement: This research was presented as a poster at the American College of Clinical Pharmacy Annual Meeting, Hollywood, Florida, October 2012, and as a platform session at the 31st Annual Eastern States Conference for Pharmacy Residents and Preceptors, Hershey, Pennsylvania, May 2012. Disclosure: No funding was received for the development of this manuscript. The authors have no potential conflicts of interest. © 2014 American Society of Consultant Pharmacists, Inc. All rights reserved. Doi:10.4140/TCP.n.2014.376.



References 1. Department of Health & Human Services. Administration on Aging. 2011. Available at www.aoa.gov. 2. Hall MJ, DeFrances CJ, William SN et al. National hospital discharge survey: 2007 summary. National Health Statistics Reports; no 29. Hyattsville, MD: National Center for Health Statistics; 2010. 3. Nagamine M, Jiang HJ, Merrill CT. Trends in elderly hospitalizations, 1997-2004. HCUP Statistical Brief #14. Agency for Healthcare Research and Quality. 2006. 4. Committee on Quality of Health Care in America and Institute of Medicine. To Err is Human – Building a Safer Health System. Washington, DC: National Academy Press; 1999. 5. Howard RL, Avery AJ, Slavenburg S et al. Which drugs cause preventable admissions to hospital? A systematic review. Br J Clin Pharmacol 2007;63:136-47. 6. Kaiser RM, Schmader KE, Pieper CF et al. Therapeutic failurerelated hospitalisations in the frail elderly. Drugs Aging 2006;23: 579-86. 7. Marcum ZA, Pugh MV, Amuan ME et al. Prevalence of potentially preventable unplanned hospitalizations caused by therapeutic failures and adverse drug withdrawal events among older Veterans. J Gerontol A Biol Sci Med Sci 2012;67:867-74. 8. Anderson RM. Revisiting the behavioral model and access to medical care: does it matter? J Health Soc Behav 1995;36:1-10. 9. Rosner B. Fundamentals of Biostatistics. 2nd ed. Boston, MA: Duxbury Press; 1986. 10. The American Geriatrics Society 2012 Beers Criteria Update Expert Panel. AGS updated Beers Criteria for Potentially Inappropriate Medication Use in Older Adults. J Am Geriatr Soc 2012;60:616-31.

11. O’Mahony D, Gallagher P, Ryan C et al. STOPP & START criteria: a new approach to detecting potentially inappropriate prescribing in old age. Eur Geriatr Med 2010;1:45-51. 12. Hallas J, Gram LF, Grodum E et al. Drug related admissions to medical wards: a population based survey. Br J Clin Pharmacol 1992;33:61-8. 13. Franceschi A, Tuccori M, Bocci G et al. Drug therapeutic failures in emergency department patients: a university hospital experience. Pharmacol Res 2004;49:85-91. 14. Hanlon JT, Lindblad CI, Maher R et al. Geriatric pharmacotherapy. In Tallis RC, Fillit HM, eds. Brocklehurst’s Textbook of Geriatric Medicine. New York, NY: Churchill Livingstone; 2003:1289-96. 15. Hajjar ER, Cafiero AC, Hanlon JT. Polypharmacy in elderly patients. Am J Geriatr Pharmacother 2007;5:345-51. 16. Murray MD, Young J, Hoke S et al. Pharmacist intervention to improve medication adherence in heart failure: a randomized trial. Ann Intern Med 2007;146:714-25. 17. Milfred-Laforest SK, Chow SL, Didomenico RJ et al. Clinical pharmacy services in heart failure: an opinion paper from the Heart Failure Society of American and American College of Clinical Pharmacy Cardiology Practice and Research Network. J Cardiol Fail 2013;19:354-69. 18. Travis SS, Bethea LS, Winn P. Medication administration hassles reported by caregivers of dependent elderly persons. J Gerontol A Biol Sci Med Sci 2000;55A:M412-7.


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Appendix I Therapeutic Failure Questionnaire Patient ID Number:________________ Admission Date:________________ Date of Screen:__________________ TF (ICD-9 Code):____________________________________________________________________________ Drug/Disease (VA Class Code):_________________________________________________________________

Question Yes No NA 1. Was drug therapy omitted for the condition? 2. Did the condition improve with drug therapy? 3. Was the drug prescribed at too low a dose by the physician or taken at too low a dose by the patient? 4. Was the drug detected in the blood in subtherapeutic concentrations? 5. Was there a drug-drug interaction that interfered with the effectiveness of the drug prescribed for the condition? 6. Did the condition improve with an increase in dose or worsen with a decreased dose? 7. Are there conclusive reports of efficacy for a drug for the condition? 8. Are there alternative causes that on their own could have caused the condition? 9. Did the patient have the same condition related to absent or inadequate drug therapy previously? 10. Was therapeutic failure confirmed by objective evidence?

1 2 1

0 -1 0

0 0 0

1 1

0 0

0

2

0

0

1 -1

0 2

0

1

0

1

0

TFQ SCORE:________ Scoring: Range of scoring = -2 to 9; Unlikely = -2 to 0; Possible = 1-3; Probable = 4-7; Likely = ≥ 8 Notes__________________________________________________________________________________ Was the TF preventable? ______ Yes, it was probably or definitely preventable (i.e., resulting from a medication error [suboptimal prescribing, suboptimal order communication, medication dispensing error, medication administration error, suboptimal monitoring, or nonadherence]) ______ No, it was probably or definitely not preventable Abbreviations: NA = Not Applicable, TF = Therapeutic failure, TFQ = Therapeutic Failure Questionnaire. Source: Reference 6.

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