Managing Warfarin in the Long-term Care Setting

Based on a Survey, Initiating, Monitoring, and Managing Warfarin May Require Substantial Nursing Time and Resources

Survey results indicate the median weekly nursing time required for each resident starting warfarin.*,1

Nurses report that dietary consults and obtaining baseline INR, PT, and CBC have some of the highest completion times 1

Median nursing time spent every week on monitoring and management of each resident stable on warfarin.1

LTC Residents Spend 50% of the Time Outside an INR Range of 2-3†,2

An unstable INR increases the risk of overall mortality and anticoagulant-related bleeding or thrombosis.‡,3

CBC = complete blood count; INR = international normalized ratio; LTC = long-term care; PT = prothrombin time.

Warfarin Caused More LTC Medication Errors Than Any Other Drug§,4

In one study of an elderly population aged 65 and older, in the most recent year for which data are available, 2007

1/3 of all hospitalizations related to adverse drug events are caused by warfarin.||,5

More than insulin, oral antiplatelet agents, and opioids combined.5

(95% CI, 28.0-38.5)   CI = confidence interval

Warfarin May Interact With Commonly Used Medications

of warfarin-related hospitalizations are attributed to an interaction with another drug1

The study also included other drug classes that were found not to significantly increase bleeding risk.¶,6
In a cohort study of patients with AF treated with warfarin, there was an increased risk of major hemorrhage in patients taking SSRIs, including citalopram, escitalopram, fluoxetine, fluvoxamine, paroxetine, sertraline, and venlafaxine vs no antidepressant.#,7
SSRI = selective serotonin reuptake inhibitor.
Mean duration of therapy was 3.5 years, patients were followed up for a median of 6 years

Newer-Generation Anticoagulants Have Been Recommended in Multiple Treatment Guidelines

August 2018 - ACCP Guidelines Antithrombotic Therapy for Atrial Fibrillation9

2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation8

2014 AHA/ASA Guidelines for the Prevention of Strokein Patients With Stroke and Transient Ischemic Attack10

2014 AAN Guidelinefor the Prevention of Stroke in Nonvalvular Atrial Fibrillation11

2013 ACCF/AHA Guideline for the Management of Heart Failure (Anticoagulation Recommendations for Atrial Fibrillation)12

2012 ACCP Guidelines for the Prevention of Venous Thromboembolism in Orthopedic Surgery Patients13
AAN = American Academy of Neurology; ACC = American College of Cardiology; ACCF = American College of Cardiology Foundation; ACCP = American College of Chest Physicians; AF = atrial fibrillation; AHA = American Heart Association; ASA = American Stroke Association; HRS = Heart Rhythm Society; SSRI = selective serotonin reuptake inhibitor.

* Patel study design: A primary, semi-quantitative, web-based survey of staff nurses who were responsible for the care of LTC residents receiving warfarin. Specific objectives included determining the specific nursing tasks related to warfarin therapy and estimating the time requirements for treatment initiation, warfarin management, and monitoring. Forty LTC nurses validated the survey to determine what protocols/procedures were involved in warfarin management. Twenty LTC nurses completed the survey, quantifying the time they spent on procedures related to warfarin management, and how often they performed each procedure for each resident each week.1
Limitations: Study limitations included the potential for bias due to small sample size, representativeness of the sample, and the possibility of inaccuracies in respondents’ self-reported time estimation of warfarin-related procedures. The study was not powered to determine differences in the time taken to perform warfarin-related procedures based on nurse designations and type of LTC. Additional work carried out by other LTC personnel (eg, laboratory staff and assistant nurses) and other factors not related to time estimation (eg, quality of care) were not accounted for. Study results should be regarded as a conservative estimate of resource time required for carrying out warfarin-related procedures in LTC facilities in the United States.1

† Gurwitz study design: A cohort study of all LTC residents of 25 nursing homes (sizes ranging from 90 to 360 beds) in Connecticut during a 12-month observation period. The total number of residents in these facilities ranged from 2946 to 3212 per quarter. A total of 490 residents received warfarin therapy. Possible warfarin-related incidents were detected by quarterly retrospective review of nursing home records by trained nurse abstractors. Each incident was independently classified by 2 physician reviewers to determine whether it constituted a warfarin-related event, its severity, and its preventability. The primary outcome was an adverse warfarin-related event, defined as an injury associated with the use of warfarin. Potential adverse warfarin-related events were defined as situations in which the INR was noted to be 4.5 or greater, an error in management was noted, but no injury occurred. Time in specified INR ranges per nursing home resident day on warfarin was also assessed.2
Limitations: Study authors relied on information that could be ascertained solely through retrospective review of nursing home records to assess the occurrence of warfarin-related incidents. The study was not designed to assess the effectiveness of warfarin therapy for the prevention of thromboembolic events.2

‡ Witt study design: Retrospective, longitudinal cohort study conducted at Kaiser Permanente Colorado of patients, aged >18 years, with a duration of warfarin therapy >90 days, at least 1 INR determination during the study time frame (2000–2005), and warfarin therapy continuing throughout a 6-month observation period (N=6073). INR stability was defined as having all INR values within the strictly defined therapeutic reference interval for the first identifiable continuous 6-month period. Occurrences of thromboembolism, bleeding, and death were compared. Multivariate logistic regression models were used to identify predictors of stable INR control.3
Limitations:This retrospective study included data from administrative databases, which may have failed to capture important clinical variables or clinical care delivered outside of participating institutions. The study was not able to establish causative relationships between study variables and outcomes due to the observational nature of the study. Also, the study was conducted within an integrated healthcare delivery system with a specialized anticoagulation service using standardized warfarin dosing protocols, so results may not directly translate to other healthcare settings.3

§ Hansen study design: Retrospective analysis using data from the Medication Error Quality Initiative (MEQI) individual event reporting system. Participants were North Carolina nursing homes that submitted incident reports to the web-based MEQI data repository during the 2006 and 2007 reporting years. Data from 206 nursing homes were summarized descriptively, and then a disproportionality analysis was applied. Data collected in 2007 analyzed for this study included individual reports of incidents, near misses, and circumstances of unsafe conditions submitted. Associations between medication type and possible causes at the state level were explored. A single nursing home was selected to illustrate how the method might inform quality improvement at the facility level. Disproportionality analysis of drug errors in this nursing home was compared with benchmarking.4
Limitations: Applying the study approach for prospective quality improvement may face barriers as there may be insufficient volume of medication error reports over short intervals for early detection of error signals. Participation in MEQI is mandatory under North Carolina licensing regulations, but reporting is effectively voluntary in that there is no auditing process. Even among the nursing homes that frequently report their errors, the accuracy of safety signals depends on the correct classification of causes and other error characteristics. The facility selected for the prototype was atypical with respect to the total number of errors it reported, therefore running the analyses for other facilities may be less informative. Disproportionality analysis is subject to reporting bias if there is a correlation between propensity to report an error and other relevant variables (eg, drug, error type, or personnel). As with all adverse event data mining, disproportionality analysis generates hypotheses that are only the first steps in a quality improvement process.4

|| Budnitz study design: Adverse-event data from the National Electronic Injury Surveillance System—Cooperative Adverse Drug Surveillance Project was used to estimate the frequency and rates of hospitalization after emergency department (ED) visits for adverse drug events in patients aged ≥65 years from January 2007 through December 2009 (N=5077 hospitalized; N=7589 ED visits but not hospitalized). The contribution of specific medications, including those identified as high risk or potentially inappropriate by national quality measures, was also assessed.5
Limitations: The study utilized public health surveillance systems, which may underestimate the number of emergency hospitalizations because of unintended bias towards detecting acute, known drug effects or effects for which testing is available. Estimates of emergency hospitalizations for adverse drug events did not include patients who were directly admitted for diagnostic evaluation or transferred from another hospital. Data utilized did not provide direct estimates of person-year exposure to medications and excluded medications initiated in nursing homes, ambulatory surgery centers, at hospital discharge, and through telephone or email contact.5

Suh study design: A nested case-control study of long-term warfarin-treated AF patients ≥18 years old using the Medstat MarketScan database of health insurance claims from 2004 to 2009 (N=7971). Patients with a hemorrhagic event were matched to control patients using incidence density sampling. Drug potentiating warfarin effects were identified within 30 days before the hemorrhagic event. The association between use of potentiating drugs and hemorrhagic risk was calculated using conditional logistic regression. Potentiating medications that increased the anticoagulant effect of warfarin or increased the risk of bleeding through alternate mechanisms were identified from published drug interaction references.6
Limitations: The study was unable to capture the use of any over-the-counter agents or assess potential effects of patient diet and adherence on the effectiveness of warfarin due to the nature of claims data. Selection of treatment by variables not available from health insurance claims data was not controlled in the analysis. Also, there was an essential selection bias and potential underestimation of the risk of hemorrhage from combination therapy. The use of ICD-9-CM codes may have also underestimated the true incidence of hemorrhagic events.6

#Quinn study design: The AnTicoagulation and Risk factors In Atrial fibrillation (ATRIA) study was a cohort of 13,559 patients enrolled in Kaiser Permanente Northern California between July 1, 1996 and December 31, 1997 with diagnosed AF, who were followed for a median of 6 years. Of this cohort, 9186 patients were exposed to warfarin during the study period and were assessed to determine the association between selective serotonin reuptake inhibitor (SSRI) and tricyclic antidepressant (TCA) exposure and major hemorrhage events. Longitudinal warfarin exposure was determined using a validated algorithm based on serial pharmacy dispensings and outpatient INR measurements, which were obtained from health plan outpatient laboratory databases. Longitudinal exposure, duration, and timing of SSRI exposure was determined by the date of dispensation and number of medication days supplied between serial prescriptions. All hemorrhage events included were either during warfarin exposure or within 5 days of preceding warfarin exposure. Major hemorrhages were defined as bleeding events that were fatal, required ≥2 units of transfused blood, or hemorrhage into a critical anatomic site (eg, intracranial, retroperitoneal, or intraocular).7
Limitations: The study may not have captured additional or unmeasured confounding factors causing differences in bleeding risk. There were no measures of depression, frailty, or indication for SSRIs or TCAs. Also, information on aspirin exposure was not available except for those patients who developed hemorrhage, and differential aspirin or nonsteroidal anti-inflammatory drugs (NSAIDs) used in the entire cohort may have led to differences in hemorrhage rates. Additionally, the investigators could not explain why more patients on SSRIs who had a bleeding event presented with supratherapeutic INRs.7

  1. Patel AA, Nelson WW. Nurses’ self-reported time estimation of anticoagulation therapy: a survey of warfarin management in long-term care. BMC Nursing. 2015;14:8.
  2. Gurwitz JH, Field TS, Radford MJ, et al. The safety of warfarin therapy in the nursing home setting. Am J Med. 2007;120(6):539-544.
  3. Witt DM, Delate T, Clark NP, et al; on behalf of the Warfarin Associated Research Projects and other EnDeavors (WARPED) Consortium. Outcomes and predictors of very stable INR control during chronic anticoagulation therapy. Blood. 2009;114(5):952-956.
  4. Hansen RA, Cornell PY, Ryan PB, et al. Patterns in nursing home medication errors: disproportionality analysis as a novel method to identify quality improvement opportunities. Pharmacoepidemiol Drug Saf. 2010;19(10):1087-1094.
  5. Budnitz DS, Lovegrove MC, Shehab N, Richards CL. Emergency hospitalizations for adverse drug events in older Americans. N Engl J Med. 2011;365(21):2002-2012.
  6. Suh D-C, Nelson WW, Choi JC, Choi I. Risk of hemorrhage and treatment costs associated with warfarin drug interactions in patients with atrial fibrillation. Clin Ther. 2012;34(7):1569-1582.
  7. Quinn GR, Singer DE, Chang Y, et al. Effect of selective serotonin reuptake inhibitors on bleeding risk in patients with atrial fibrillation taking warfarin. Am J Cardiol. 2014;114(4):583-586.
  8. January CT, Wann LS, Alpert JS, et al. 2014 AHA/ACC/HRS guideline for the management of patients with atrial fibrillation: a report of the American College of Cardiology/American Heart Association task force on practice guidelines and the Heart Rhythm Society. Circulation. 2014;130(23):e199-e267.
  9. Lip GYH, Banerjee A, Boriani G, et al. Antithrombotic Therapy for Atrial Fibrillation: CHEST Guideline and Expert Panel Report. Chest. 2018 Aug 21. pii: S0012-3692(18)32244-X. doi: 10.1016/j.chest.2018.07.040. [Epub ahead of print]
  10. Kernan WN, Ovbiagele B, Black HR, et al. Guidelines for the prevention of stroke in patients with stroke and transient ischemic attack: a guideline for healthcare professionals from the American Heart Association/American Stroke Association. Stroke. 2014;45(7):2160-2236.
  11. Culebras A, Messé SR, Chaturvedi S, et al. Summary of evidence-based guideline update: prevention of stroke in nonvalvular atrial fibrillation: report of the guideline development subcommittee of the American Academy of Neurology. Neurology. 2014;82(8):716-724.
  12. Yancy CW, Jessup M, Bozkurt B, et al. 2013 ACCF/AHA guideline for the management of heart failure: a report of the American College of Cardiology Foundation/American Heart Association task force on practice guidelines. Circulation. 2013;128(16):e240-e327.
  13. Falck-Ytter Y, Francis CW, Johanson NA, et al. Prevention of VTE in orthopedic surgery patients: antithrombotic therapy and prevention of thrombosis, 9th ed: American College of Chest Physicians evidence-based clinical practice guidelines. Chest. 2012;141(2 suppl):e278S-e325S.

Sebastian Ferreira, Untitled
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