Use of specific indicators to detect warfarin-related adverse events

Improving inpatient warfarin therapy safety using a pharmacist-managed protocol

Introduction

Safe management of warfarin in the inpatient setting can be challenging. At the Mayo Clinic hospitals in Rochester, Minnesota, we set out to improve the safety of warfarin management among surgical and non-surgical inpatients.

Methods

A multidisciplinary team designed a pharmacist-managed warfarin protocol (PMWP) which designated warfarin dosing to inpatient pharmacists with guidance from computerised dosing algorithms. Ordering this protocol was ultimately designed as an ‘opt out’ practice. The primary improvement measure was frequency of international normalised ratio (INR) greater than 5; secondary measures included adoption rate of the protocol, a counterbalance INR metric (INR <1.7 three days after first inpatient warfarin dose), and complication rates, including bleeding and thrombosis events. An interrupted time series analysis was conducted to compare outcomes.

Results

Among over 50 000 inpatient warfarin recipients, the PMWP was adopted for the majority of both surgical and non-surgical inpatients during the study period (1 January 2005 to 31 December 2011). The primary improvement measure decreased from 5.6% to 3.4% for medical patients and from 5.2% to 2.4% for surgical patients during the preimplementation and postimplementation periods, respectively. The INR counterbalance measure did not change. Postoperative bleeding decreased from 13.5% to 11.1% among surgical patients, but bleeding was unchanged among medical patients.

Conclusion

Our PMWP led to achievement of improved INR control for inpatient warfarin recipients and to less near-term bleeding among higher risk, surgical patients.

The Marginal Costs of Adverse Drug Events Associated With Exposures to Anticoagulants and Hypoglycemic Agents During Hospitalization

BACKGROUND

Anticoagulants and hypoglycemic agents are 2 of the most challenging drug classes for medical management in the hospital resulting in many adverse drug events (ADEs).

OBJECTIVE

Estimating the marginal cost (MC) of ADEs associated with anticoagulants and hypoglycemic agents for adults in 5 patient groups during their hospital stay and the total annual ADE costs for all patients exposed to these drugs during their stay.

RESEARCH DESIGN AND SUBJECT

Data are from 2010 to 2013 Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases and Medicare Patient Safety Monitoring System (MPSMS). Deidentified patients were linked using probabilistic matching in the same hospital and year for 5 patient groups. ADE information was obtained from the MPSMS using retrospective structured record review. Costs were derived using HCUP cost-to-charge ratios. MC estimates were made using Extended Estimating Equations controlling for patient characteristics, comorbidities, hospital procedures, and hospital characteristics. MC estimates were applied to the 2013 HCUP National Inpatient Sample to estimate annual ADE costs.

RESULTS

Adjusted MC estimates were smaller than unadjusted measures with most groups showing estimates that were at least 50% less. Adjusted anticoagulant ADE costs added >45% and Hypoglycemic ADE costs added >20% to inpatient costs. The 2013 hospital cost estimates for ADEs associated with anticoagulants and hypoglycemic agents were >$2.5 billion for each drug class.

CONCLUSIONS

This study demonstrates the importance of accounting for confounders in the estimation of ADEs, and the importance of separate estimates of ADE costs by drug class.

Predictors of warfarin-associated adverse events in hospitalized patients: Opportunities to prevent patient harm

BACKGROUND

The optimum international normalized ratio (INR) monitoring frequency for hospitalized patients receiving warfarin is unknown.

OBJECTIVE

Assess relationship between daily versus less frequent INR monitoring and overanticoagulation and warfarin-related adverse events.

DESIGN

Retrospective cohort study using Medicare Patient Safety Monitoring System data.

SETTING

Randomly selected acute care hospitals across the United States.

PATIENTS

Patients hospitalized from 2009 to 2013 for pneumonia, acute cardiac disease, or surgery who received warfarin.

INTERVENTIONS

None.

MEASUREMENTS

(1) Association between frequency of INR monitoring and an INR ≥6.0 or warfarin-related adverse event. (2) Association between the rate of change of the INR and a subsequent INR ≥5.0 and ≥6.0.

RESULTS

Among 8529 patients who received warfarin for ≥3 days, for 1549 (18.2%) the INR was not measured on 2 or more days. These patients had higher propensity-adjusted odds ratios (ORs) of having a warfarin-associated adverse event (OR: 1.48, 95% confidence interval [CI]: 1.02-2.17) for cardiac patients and surgical patients (OR: 1.73, 95% CI: 1.20-2.48), with no significant association for pneumonia patients. Cardiac and pneumonia patients with 1 day or more without an INR measurement had higher propensity-adjusted ORs of having an INR ≥6.0 (OR: 1.61, 95% CI: 1.07-2.41 and OR: 1.92, 95% CI: 1.36-2.71, respectively). A 1-day increase in the INR of ≥0.9 occurred in 621 patients (12.5%) and predicted a subsequent INR of ≥6.0 (positive likelihood ratio of 4.2).

CONCLUSION

Daily INR measurement and recognition of a rapidly rising INR might decrease the frequency of warfarin-associated adverse events in hospitalized patients.

Detection of adverse drug reactions by medication antidote signals and comparison of their sensitivity with common methods of ADR detection

OBJECTIVE

To determine the PPVs of selected ten medication antidote signals in recognizing potential ADRs and comparison of their sensitivity with manual chart analysis, and voluntary reporting recognizing the same ADRs.

METHOD

The inpatient EMR database of internal medicine department was utilized for a period of one year, adult patients prescribed at least one of the ten signals, were included in the study, recipient patients of antidote signals were assessed for the occurrence of an ADR by Naranjo's tool of ADR evaluation. PPVs of each antidote signal were verified.

RESULT

PPV of Methylprednisolone and Phytonadione was 0.28, Metoclopramide and Potassium Chloride - 0.29, Dextrose 50%, Promethazine, Sodium Polystyrene and Loperamide - 0.30, Protamine and Acetylcysteine - 0.33. In comparison of confirmed ADRs of antidote signals with other methods, Dextrose 50%, Metoclopramide, Sodium Polystyrene, Potassium Chloride, Methylprednisolone and Promethazine seem to be extremely significant (P value > 0.0001), while ADRs of Phytonadione, Protamine, Acetylcysteine and Loperamide were insignificant.

CONCLUSION

Antidote medication signals have definitive discerning evaluation value of ADRs over routine methods of ADR detection with a high detection rate with a minimum cost; Their integration with hospital EMR database and routine patient safety surveillance enhances transparency, time-saving and facilitates ADR detection.

A survey of nursing home physicians to determine laboratory monitoring adverse drug event alert preferences

OBJECTIVE

We conducted a survey of nursing home physicians to learn about (1) the laboratory value thresholds that clinical event monitors should use to generate alerts about potential adverse drug events (ADEs); (2) the specific information to be included in the alerts; and (3) the communication modality that should be used for communicating them.

METHODS

Nursing home physician attendees of the 2010 Conference of AMDA: The Society for Post-Acute and Long-Term Care Medicine.

RESULTS

A total of 800 surveys were distributed; 565 completed surveys were returned and seven surveys were excluded due to inability to verify that the respondents were physicians (a 70% net valid response rate). Alerting threshold preferences were identified for eight laboratory tests. For example, the majority of respondents selected thresholds of ≥5.5 mEq/L for hyperkalemia (63%) and ≤3.5 without symptoms for hypokalemia (54%). The majority of surveyed physicians thought alerts should include the complete active medication list, current vital signs, previous value of the triggering lab, medication change in the past 30 days, and medication allergies. Most surveyed physicians felt the best way to communicate an ADE alert was by direct phone/voice communication (64%), followed by email to a mobile device (59%).

CONCLUSIONS

This survey of nursing home physicians suggests that the majority prefer alerting thresholds that would generally lead to fewer alerts than if widely accepted standardized laboratory ranges were used. It also suggests a subset of information items to include in alerts, and the physicians' preferred communication modalities. This information might improve the acceptance of clinical event monitoring systems to detect ADEs in the nursing home setting.

Use of an abnormal laboratory value-drug combination alert to detect drug-induced thrombocytopenia in critically Ill patients

PURPOSE

The aim of this study was to assess the performance of a commercially available clinical decision support system (CDSS) drug-laboratory result alert in detecting drug-induced thrombocytopenia in critically ill patients.

MATERIALS AND METHODS

Adult patients admitted to the medical and cardiac intensive care unit during an 8-week period and identified by 1 of 3 signals in the CDSS, TheraDoc, were eligible. Alerts were generated when the patient had a low platelet count and was ordered a potentially causal drug. Patients were evaluated in real time for the occurrence of an adverse drug reaction using 3 causality instruments. Positive predictive values were calculated for the alert.

RESULTS

Sixty-four patients with a mean age of 54 years met the inclusion criteria, generating 350 alerts. Positive predictive values were 0.36, 0.83, and 0.40 for signals 1, 2, and 3, respectively. Overall, there were 137 adverse drug reactions identified in the 350 alerts, with heparin, vancomycin, and famotidine as the 3 most common potential causes.

CONCLUSIONS

A commercial CDSS drug-laboratory alert is effective at identifying drug-induced thrombocytopenia in the intensive care unit and may improve patient safety. Compared with previous studies, the combination alert performs better than alerts based exclusively on laboratory values and should be considered to reduce alert fatigue.

A systematic review to evaluate the accuracy of electronic adverse drug event detection

OBJECTIVE

Adverse drug events (ADEs), defined as adverse patient outcomes caused by medications, are common and difficult to detect. Electronic detection of ADEs is a promising method to identify ADEs. We performed this systematic review to characterize established electronic detection systems and their accuracy.

METHODS

We identified studies evaluating electronic ADE detection from the MEDLINE and EMBASE databases. We included studies if they contained original data and involved detection of electronic triggers using information systems. We abstracted data regarding rule characteristics including type, accuracy, and rationale.

RESULTS

Forty-eight studies met our inclusion criteria. Twenty-four (50%) studies reported rule accuracy but only 9 (18.8%) utilized a proper gold standard (chart review in all patients). Rule accuracy was variable and often poor (range of sensitivity: 40%-94%; specificity: 1.4%-89.8%; positive predictive value: 0.9%-64%). 5 (10.4%) studies derived or used detection rules that were defined by clinical need or the underlying ADE prevalence. Detection rules in 8 (16.7%) studies detected specific types of ADEs.

CONCLUSION

Several factors led to inaccurate ADE detection algorithms, including immature underlying information systems, non-standard event definitions, and variable methods for detection rule validation. Few ADE detection algorithms considered clinical priorities. To enhance the utility of electronic detection systems, there is a need to systematically address these factors.

Computerized detection of adverse drug reactions in the medical intensive care unit

OBJECTIVE

Clinical event monitors are a type of active medication monitoring system that can use signals to alert clinicians to possible adverse drug reactions. The primary goal was to evaluate the positive predictive values of select signals used to automate the detection of ADRs in the medical intensive care unit.

METHOD

This is a prospective, case series of adult patients in the medical intensive care unit during a six-week period who had one of five signals presents: an elevated blood urea nitrogen, vancomycin, or quinidine concentration, or a low sodium or glucose concentration. Alerts were assessed using 3 objective published adverse drug reaction determination instruments. An event was considered an adverse drug reaction when 2 out of 3 instruments had agreement of possible, probable or definite. Positive predictive values were calculated as the proportion of alerts that occurred, divided by the number of times that alerts occurred and adverse drug reactions were confirmed.

RESULTS

145 patients were eligible for evaluation. For the 48 patients (50% male) having an alert, the mean±SD age was 62±19 years. A total of 253 alerts were generated. Positive predictive values were 1.0, 0.55, 0.38 and 0.33 for vancomycin, glucose, sodium, and blood urea nitrogen, respectively. A quinidine alert was not generated during the evaluation.

CONCLUSIONS

Computerized clinical event monitoring systems should be considered when developing methods to detect adverse drug reactions as part of intensive care unit patient safety surveillance systems, since they can automate the detection of these events using signals that have good performance characteristics by processing commonly available laboratory and medication information.

Evaluating the positive predictive values of antidote signals to detect potential adverse drug reactions (ADRs) in the medical intensive care unit (ICU)

PURPOSE

Signals are used to alert clinicians of potential ADRs. Positive predictive values (PPVs) of antidote signals in ICUs are unknown. The primary purpose was to determine PPVs of six signals. The secondary objective was to determine the sensitivity of various ADR detection strategies including manual chart review, administrative data review, and voluntary reporting at identifying the same ADRs discovered using antidotes as a signal.

METHODS

Adult patients admitted to a medical ICU from July 1, 2005 to June 30, 2006 who were prescribed select signals were eligible. Evaluated antidote signals included injectable diphenhydramine, protamine, phytonadione, dextrose 50%, injectable methylprednisolone, and sodium polystyrene. For each signal, a random sample of 50 patients was evaluated for the presence of an ADR. ADR occurrences were determined using two objective causality instruments through retrospective chart review. Agreement between the instruments was required for ADR consideration. PPVs were determined for each signal.

RESULTS

Two hundred and twenty three patients (52% male) were evaluated, with a mean +/- SD age of 60 +/- 17 years, and a median simplified acute physiology score (SAPSII) of 48. PPVs were 0.64, 0.50, 0.38, 0.26, 0.24, and 0.02 for protamine, sodium polystyrene, dextrose 50%, diphenhydramine, phytonadione, and methylprednisolone, respectively. Sensitivity of other detection strategies from highest to lowest was chart review for explicit documentation, administrative database review, and voluntary reporting.

CONCLUSIONS

Protamine and sodium polystyrene performed the best by detecting ADRs in at least one out of two evaluations. Detection strategies other than signals were not as sensitive at identifying the same ADRs as antidote signals.

A Pilot Study Comparing Two Methods for Warfarin Management in Hospitalized Patients

Background:

The potential for medication errors in a hospital setting has led to a change from daily order writing to scheduled dosing. It has also been hypothesized that scheduled dosing may decrease the pharmacists' workload in a community teaching hospital.

Objective:

To evaluate the impact that scheduled warfarin dosing would have on patient safety for a pharmacist-run anticoagulation service.

Methods:

Two methods for managing warfarin in a pharmacist-run anticoagulation service were compared. A retrospective chart review was conducted on a random sample of 80 inpatients who received warfarin either from January 2006 through December 2006 (control/daily dosing group) or from January 2007 through March 2007 (scheduled dosing group). Patients not managed by pharmacists or with a target international normalized ratio (INR) range other than 2 to 3 were excluded.

Results:

A total of 35 patients met inclusion criteria; 20 patients were in the daily order (control) group and 15 were in the scheduled dosing group. A total of 7 doses were omitted in the daily dosing group, compared with none in the scheduled dosing group. Of the 7, 4 were omissions in administration and 3 were order omissions. In the control group, the dose was changed 47 times (36%) compared with 23 times (28%) in the scheduled dosing group. In the daily dosing group, 28 (22%) INRs were within the therapeutic range and 97 (78%) were in the nontherapeutic range. In the scheduled dosing group, 24 (25%) INRs were within the therapeutic range and 72 (75%) were in the nontherapeutic range.

Conclusions:

Scheduled dosing eliminated omission-type medication errors and was more efficient than daily dosing. The process change decreased pharmacist workload without having a negative impact on patient care.

A systematic review of the performance characteristics of clinical event monitor signals used to detect adverse drug events in the hospital setting

OBJECTIVE

Despite demonstrated benefits, few healthcare organizations have implemented clinical event monitors to detect adverse drug events (ADEs). The objective of this study was to conduct a systematic review of pharmacy and laboratory signals used by clinical event monitors to detect ADEs in hospitalized adults.

DESIGN

We performed a comprehensive search of MEDLINE, CINHAL and EMBASE to identify studies published between 1985 through 2006. Studies were included if they: described a clinical event monitor to detect ADEs in an adult hospital setting; described laboratory or pharmacy ADE signals; and, provided positive predictive values (PPVs) or information to allow the calculation of PPVs for individual ADE signals.

MEASUREMENTS

We calculated overall estimates of PPVs and 95% confidence intervals (CIs) for signals reported in 2 or more studies and contained no evidence heterogeneity. Results were examined by signal category: medication levels, laboratory tests, or antidotes.

RESULTS

We identified 12 observational studies describing 36 unique ADE signals. Fifteen signals (3 antidotes, 4 medication levels, and 8 laboratory values) contained no evidence of heterogeneity. The pooled PPVs for these individual signals ranged from 0.03 [CI=0.03-0.03] for hypokalemia, to 0.50 [CI=0.39-0.61] for supratherapeutic quinidine level. In general, antidotes (range=0.09-0.11) had the lowest PPVs, followed by laboratory values (0.03-0.27), and medication levels (0.03-0.50).

CONCLUSION

Results from this study should help clinical information system and computerized decision support producers develop or improve existing clinical event monitors to detect ADEs in their own hospitals by prioritizing those signals with the highest PPVs [corrected]