Amy Linsky

Proton pump inhibitors and risk for recurrent Clostridium difficile infection.

BACKGROUND Proton pump inhibitors (PPIs) are widely used gastric acid suppressants, but they are often prescribed without clear indications and may increase risk of Clostridium difficile infection (CDI). We sought to determine the association between PPI use and the risk of recurrent CDI. METHODS Retrospective, cohort study using administrative databases of the New England Veterans Healthcare System from October 1, 2003, through September 30, 2008. We identified 1166 inpatients and outpatients with metronidazole- or vancomycin hydrochloride-treated incident CDI, of whom 527 (45.2%) received oral PPIs within 14 days of diagnosis and 639 (54.8%) did not. We determined the hazard ratio (HR) for recurrent CDI, defined by a positive toxin finding in the 15 to 90 days after incident CDI. RESULTS Recurrent CDI was more common in those exposed to PPIs than in those not exposed (25.2% vs 18.5%). Using Cox proportional survival methods, we determined that the adjusted HR of recurrent CDI was greater in those exposed to PPIs during treatment (1.42; 95% confidence interval [CI], 1.11-1.82). Risks among exposed patients were highest among those older than 80 years (HR, 1.86; 95% CI, 1.15-3.01) and those receiving antibiotics not targeted to C difficile during follow-up (HR, 1.71; 95% CI, 1.11-2.64). [corrected] CONCLUSIONS Proton pump inhibitor use during incident CDI treatment was associated with a 42% increased risk of recurrence. Our findings warrant further studies to examine this association and careful consideration of the indications for prescribing PPIs during treatment of CDI.

Medication discrepancies in integrated electronic health records

Introduction Medication discrepancies are associated with adverse drug events. Electronic health records (EHRs) may reduce discrepancies, especially if integrated with pharmacy dispensing. We determined the prevalence of discrepancies within a national healthcare system with EHR–pharmacy linkage to characterise the medications involved and to identify factors associated with discrepancies. Methods We conducted a retrospective cohort study of ambulatory care patients at Veterans Affairs Boston Healthcare System, April 2010–July 2011. The primary outcome was the presence of any medication discrepancy or specific types of discrepancies: commission—present in the record but not taken by patient; omission—not present in the record; duplication—present more than once; or alteration in dose or frequency—present but taken differently than documented. Results Sixty-two patients (60%) had at least one medication discrepancy. Prevalence of commissions, omissions, duplications and alterations were 36%, 27%, 11% and 19%, respectively. The involved medications differed by type of discrepancy, but non-opioid analgesics and herbal therapies were common among commissions and omissions. In adjusted analyses, an increasing number of medications was associated with more commissions (OR 1.2; 95% CI 1.1 to 1.3) and duplications (OR 1.2; 95% CI 1.1 to 1.4) and fewer omissions (OR 0.9; 95% CI 0.8 to 1.0). Discussion In a system with a well established EHR linked to pharmacy dispensing, medication discrepancies occurred in 60% of ambulatory clinic patients. Patients with a greater number of medications were more likely to have errors of commission and duplication, but less likely to have errors of omission. Our findings highlight that relying on EHRs alone will not ensure an accurate medication list and stress the need to review medication taking thoroughly with patients to capitalise on the full potential of EHRs.

Lifestyle behaviors in Massachusetts adult cancer survivors

IntroductionAdoption of healthy lifestyles in cancer survivors has potential to reduce subsequent adverse health. We sought to determine the prevalence of tobacco use, alcohol use, and physical inactivity among cancer survivors overall and site-specific survivors.MethodsWe performed a cross-sectional analysis of the Massachusetts Behavioral Risk Factor Surveillance System, 2006–2008, and identified 1,670 survivors and 18,197 controls. Specific cancer sites included prostate, colorectal, female breast, and gynecologic (cervical, ovarian, uterine). Covariates included age, gender, race/ethnicity, education, income, marital status, health insurance, and physical and mental health. Gender stratified logistic regression models associated survivorship with each health behavior.Results4.9% of men and 7.7% of women reported a cancer history. In adjusted regression models, male survivors were similar to gender matched controls, while female survivors had comparable tobacco and alcohol use but had more physical inactivity than controls (OR 1.5; 95% CI, 1.2–1.8). By site, breast cancer survivors were more likely to be physically inactive (OR 1.5; 95% CI, 1.1–2.0) and gynecologic cancer survivors were more likely to report current tobacco use (OR 1.8; 95% CI, 1.2–2.8).Conclusions and Implications for Cancer SurvivorsSpecific subgroups of cancer survivors are more likely to engage in unhealthy behaviors. Accurate assessment of who may derive the most benefit will aid public health programs to effectively target limited resources.

A randomized-controlled trial of computerized alerts to reduce unapproved medication abbreviation use.

Abbreviation use is a preventable cause of medication errors. The objective of this study was to test whether computerized alerts designed to reduce medication abbreviations and embedded within an electronic progress note program could reduce these abbreviations in the non-computer-assisted handwritten notes of physicians. Fifty-nine physicians were randomized to one of three groups: a forced correction alert group; an auto-correction alert group; or a group that received no alerts. Over time, physicians in all groups significantly reduced their use of these abbreviations in their handwritten notes. Physicians exposed to the forced correction alert showed the greatest reductions in use when compared to controls (p=0.02) and the auto-correction alert group (p=0.0005). Knowledge of unapproved abbreviations was measured before and after the intervention and did not improve (p=0.81). This work demonstrates the effects that alert systems can have on physician behavior in a non-computerized environment and in the absence of knowledge.

Proton pump inhibitor discontinuation in long-term care.

OBJECTIVES: To determine factors associated with proton pump inhibitor (PPI) discontinuation in long‐term care.

Medication Complexity, Medication Number, and Their Relationships to Medication Discrepancies

Background: Medication reconciliation to identify discrepancies is a National Patient Safety Goal. Increasing medication number and complex medication regimens are associated with discrepancies, nonadherence, and adverse events. The Medication Regimen Complexity Index (MRCI) integrates information about dosage form, dosing frequency, and additional directions. Objective: This study evaluates the association of MRCI scores and medication number with medication discrepancies and commissions, a discrepancy subtype. Methods: This was a retrospective cohort study of a convenience sample of 104 ambulatory care patients seen from April 2010 to July 2011 within the Department of Veterans Affairs. Primary outcomes included any medication discrepancy and commissions. Primary exposures included MRCI scores and medication number. Multivariable logistic regression models associated MRCI scores and medication number with discrepancies. Receiver operating characteristic (ROC) curves provided discrepancy thresholds. Results: For the 104 patients analyzed, the median MRCI score was 25 (interquartile range [IQR] = 14-43), and the median medication number was 8 (IQR = 5-13); 60% of patients had any discrepancy, whereas 36% had a commission. In adjusted analyses, patients with MRCI scores ≥25 or medication number ≥8 were more likely to have commissions (odds ratio [OR] = 3.64, 95% CI = 1.41-9.41; OR = 4.51, 95% CI = 1.73-11.73, respectively). The unadjusted ROC threshold for commissions was 36 for MRCI (sensitivity, 59%; specificity, 82%) and 9 for medication number (sensitivity 68%; specificity 67%). Conclusion: Patients with either MRCI scores ≥25 or ≥8 medications were more likely to have commissions. Given equal performance in predicting discrepancies, the efficiency and simplicity of medication number supports its use in identifying patients for intensive medication review beyond medication reconciliation.

Patient Perceptions of Deprescribing: Survey Development and Psychometric Assessment.

Background: Although clinicians ultimately decide when to discontinue (deprescribe) medications, patients’ perspectives may guide the process. Objectives: To develop a survey instrument that assesses patients’ experience with and attitudes toward deprescribing. Research Design: We developed a questionnaire with established and newly created items. We used exploratory factor analysis and confirmatory factor analysis (EFA and CFA) to assess the psychometric properties. Subjects: National sample of 1547 Veterans Affairs patients prescribed ≥5 medications. Measures: In the EFA, percent variance, a scree plot, and conceptual coherence determined the number of factors. In the CFA, proposed factor structures were evaluated using standardized root mean square residual, root mean square error of approximation, and comparative fit index. Results: Respondents (n=790; 51% response rate) were randomly assigned to equal derivation and validation groups. EFA yielded credible 4-factor and 5-factor models. The 4 factors were “Medication Concerns,” “Provider Knowledge,” “Interest in Stopping Medicines,” and “Unimportance of Medicines.” The 5-factor model added “Patient Involvement in Decision-Making.” In the CFA, a modified 5-factor model, with 2 items with marginal loadings moved based upon conceptual fit, had an standardized root mean square residual of 0.06, an RMSEA of 0.07, and a CFI of 0.91. The new scales demonstrated internal consistency reliability, with Cronbach &agr;’s of: Concerns, 0.82; Provider Knowledge, 0.86; Interest, 0.77; Involvement, 0.61; and Unimportance, 0.70. Conclusions: The Patient Perceptions of Deprescribing questionnaire is a novel, multidimensional instrument to measure patients’ attitudes and experiences related to medication discontinuation that can be used to determine how to best involve patients in deprescribing decisions.

Supporting medication discontinuation: provider preferences for interventions to facilitate deprescribing

BackgroundOne approach to prevent adverse drug events is to discontinue (“deprescribe”) medications that are outdated, not indicated, or of limited benefit relative to risk for a particular patient. However, there is little guidance to clinicians about how to integrate the process of deprescribing into the workflow of clinical practice. We sought to determine clinical prescribers’ preferences for interventions that would improve their ability to appropriately and proactively discontinue medications.MethodsWe conducted a national web-based survey of 2475 prescribers [physicians, nurse practitioners (NP), physician assistants (PA), and clinical pharmacy specialists] practicing in US Veterans Affairs (VA) primary care clinics. One survey question presented 15 potential changes to medication-related practices and respondents ranked their top three choices for changes that would “most improve [their] ability to discontinue medications.” We summed the weighted rankings for each of the 15 response options. Preferences were determined for the whole sample and within subgroups of respondents defined by demographic and background characteristics, medication-relevant experience, and beliefs.ResultsAmong the 326 respondents who provided rankings, the top choice for a change that would help improve their ability to discontinue medications was “Requiring all medication prescriptions to have an associated ‘indication for use.’” This preference was followed by “Assistance with follow-up of patients as they taper or discontinue medications is performed by another member of the Patient Aligned Care Team (PACT)” and “Increased patient involvement in prescribing decisions.” This combination of options, albeit in varying rank order, was the most commonly selected, with 250 respondents (77%) who answered the question including at least one of these items in their three highest ranked choices, regardless of their demographics, experience, or beliefs.ConclusionsContinued efforts to improve clinicians’ ability to make prescribing decisions, especially around deprescribing, have many potential benefits, including decreased pharmaceutical and health care costs, fewer adverse drug events and complications, and improved patient involvement and satisfaction with their care. Future work, whether as research or quality improvement, should incorporate clinicians’ preferences for interventions, as greater buy-in from front-line staff leads to better adoption of changes.

Patients’ perceptions of their “most” and “least” important medications: a retrospective cohort study

BackgroundDespite benefits of adherence, little is known about the degree to which patients will express their perceptions of medications as more or less important to take as prescribed. We determined the frequency with which Veteran patients would explicitly identify one of their medications as “most important” or “least important.”FindingsWe conducted a retrospective cohort study of patients from ambulatory clinics at VA Boston from April 2010-July 2011. Patients answered two questions: “Which one of your medicines, if any, do you think is the most important? (if none, please write ‘none’)” and “Which one of your medicines, if any, do you think is the least important? (if none, please write ‘none’).” We determined the prevalence of response categories for each question. Our cohort of 104 patients was predominantly male (95%), with a mean of 9 medications (SD 5.7). Regarding their most important medication, 41 patients (39%) identified one specific medication; 26 (25%) selected more than one; 21 (20%) wrote “none”; and 16 (15%) did not answer the question. For their least important medication, 31 Veterans (30%) chose one specific medication; two (2%) chose more than one; 51 (49%) wrote “none”; and 20 (19%) did not directly answer the question.ConclusionsThirty-five percent of patients did not identify a most important medication, and 68% did not identify a least important medication. Better understanding of how patients prioritize medications and how best to elicit this information will improve patient-provider communication, which may in turn lead to better adherence.

Provider and System-Level Barriers to Deprescribing: Interconnected Problems and Solutions

Driven by an ambition to provide high-quality care, the U. S. healthcare system is focused on safe and appropriate medication use. With an aging population and a high rate of multimorbidity, there has been a concomitant rise in polypharmacy, often defined as five or more medications (Anderson, 2010). Polypharmacy has steadily and significantly risen over the past decade (Kantor, Rehm, Haas, Chan, & Giovannucci, 2015), and potentially inappropriate medications (PIMs) may be seen in up to 79% of older adults (Hill-Taylor et al., 2013). Categories of PIMs include unwarranted medicationrelated risks, low likelihood of benefit, or treatment misaligned with patients’ goals of care. Polypharmacy and PIMs are each associated with negative health outcomes, including reduced quality of life and increased risk of falls, hospitalizations, and mortality (Reeve, Thompson, & Farrell, 2017). One mechanism by which exposure to polypharmacy and PIMs can be reduced is deprescribing. Deprescribing has been defined as the “systematic process of identifying and discontinuing drugs when existing or potential harms outweigh existing or potential benefits within the context of an individual patient’s care goals, functional status, life expectancy, values, and preferences” (p. 827) (Scott et al., 2015). Deprescribing has been shown to be generally safe and effective. Additionally, in a consumer-driven (i.e., patient-driven) healthcare system, many patients prefer fewer medicines (Linsky, Simon, & Bokhour, 2015). Defining deprescribing as a process highlights the challenges to proactive, intentional discontinuation. There are patient-, provider-, and system-level barriers to deprescribing, many of which are interconnected. Therefore, innovations and initiatives to address these barriers will frequently require a multi-level approach. While patientlevel barriers are important to address—especially given that patient involvement has been identified as a key component of successful deprescribing interventions (Reeve et al., 2017)—they are not the sole barriers to safe medication use. Herein, we explore the barriers and opportunities to improve deprescribing at both the provider and system levels.