Negligible impact of highly patient-specific decision support for potassium-increasing drug-drug interactions – a cluster-randomised controlled trial

BACKGROUND AND OBJECTIVE: Clinical decision support (CDS) might improve management of potassium-increasing drug-drug interactions (DDI). We studied CDS with five features intended to increase effectiveness: (i) focus on serious DDIs, (ii) fewer notifications, (iii) presentation of current laboratory results, (iv) timing (when adverse event becomes likelier), (v) removal of notification when appropriate. METHODS: We conducted a 1-year, hospital-wide, cluster- randomised controlled trial in the inpatient setting at a large tertiary-care academic medical centre. Three CDS types were implemented: monitoring reminders (unknown potassium, no monitoring ordered), elevated potassium warnings (≥4.9 mEq/l), and hyperkalaemia alerts (≥5.5 mEq/l). The primary endpoint was the frequency of potassium- monitoring intervals >72 h. RESULTS: We analysed 15,272 and 18,981 stays with 2804 and 2057 potassium-increasing DDIs in the intervention and control groups, respectively. Patient-specific notifications: displayed were 869 reminders (1 per 3.2 potassium- increasing DDIs), 356 warnings (1:7.9), and 62 alerts (1:45.2). Nevertheless, insufficiently monitored DDIs were not reduced (intervention 451 of 9686 intervals >72 h [4.66%]; control 249 of 6140 [4.06%]). The only secondary outcome improved was the length of potassium monitoring intervals (intervention group mean 22.9 h, control 23.7 h; p <0.001). However, in the intervention group, during 50 of 2804 observed potassium-increasing DDI periods (1.78%) one or more serum potassium values ≥ 5.5mEq/ l were measured, in the control group, during 27 of 2057 (1.31%; p = 0.20). CONCLUSIONS: A highly patient-specific CDS feature combination had a negligible impact on the management of potentially serious potassium-increasing DDIs and was unable to improve safety among hospitalised patients. Trial registration number: The study was registered at ClinicalTrials.gov (NCT02020317). Keywords: drug interactions, hyperkalaemia, potassium, medical order entry systems, electronic health records, clinical decision support systems, computer-assissted drug therapy, patient safety, drug monitorin

Patient- and physician-related risk factors for hyperkalaemia in potassium-increasing drug-drug interactions

Purpose: Hyperkalaemia due to potassium-increasing drug-drug interactions (DDIs) is a clinically important adverse drug event. The purpose of this study was to identify patient- and physician-related risk factors for the development of hyperkalaemia. Methods: The risk for adult patients hospitalised in the University Hospital Zurich between 1 December 2009 and 31 December 2011 of developing hyperkalaemia was correlated with patient characteristics, number, type and duration of potassium-increasing DDIs and frequency of serum potassium monitoring. Results: The 76,467 patients included in this study were prescribed 8,413 potentially severe potassium-increasing DDIs. Patient-related characteristics associated with the development of hyperkalaemia were pulmonary allograft [relative risk (RR) 5.1; p 48h: RR 1.6; p < 0.01). Conclusion: Strategies for reducing the risk of hyperkalaemia during potassium-increasing DDIs should consider both patient- and physician-related risk factors

Developing strategies for predicting hyperkalemia in potassium-increasing drug-drug interactions

OBJECTIVE: To compare different strategies predicting hyperkalemia (serum potassium level ≥5.5 mEq/l) in hospitalized patients for whom medications triggering potassium-increasing drug-drug interactions (DDIs) were ordered. MATERIALS AND METHODS: We investigated 5 strategies that combined prediction triggered at onset of DDI versus continuous monitoring and taking into account an increasing number of patient parameters. The considered patient parameters were identified using generalized additive models, and the thresholds of the prediction strategies were calculated by applying Youden's J statistic to receiver operation characteristic curves. Half of the data served as the calibration set, half as the validation set. RESULTS: We identified 132 incidences of hyperkalemia induced by 8413 potentially severe potassium-increasing DDIs among 76 467 patients. The positive predictive value (PPV) of those strategies predicting hyperkalemia at the onset of DDI ranged from 1.79% (undifferentiated anticipation of hyperkalemia due to the DDI) to 3.02% (additionally considering the baseline serum potassium) and 3.10% (including further patient parameters). Continuous monitoring significantly increased the PPV to 8.25% (considering the current serum potassium) and 9.34% (additional patient parameters). CONCLUSION: Continuous monitoring of the risk for hyperkalemia based on current potassium level shows a better predictive power than predictions triggered at the onset of DDI. This contrasts with efforts to improve DDI alerts by taking into account more patient parameters at the time of ordering

Use of an on-demand drug-drug interaction checker by prescribers and consultants: A retrospective analysis in a Swiss teaching hospital

BACKGROUND: Offering a drug-drug interaction (DDI) checker on-demand instead of computer-triggered alerts is a strategy to avoid alert fatigue. OBJECTIVE: The purpose was to determine the use of such an on-demand tool, implemented in the clinical information system for inpatients. METHODS: The study was conducted at the University Hospital Zurich, an 850-bed teaching hospital. The hospital-wide use of the on-demand DDI checker was measured for prescribers and consulting pharmacologists. The number of DDIs identified on-demand was compared to the number that would have resulted by computer-triggering and this was compared to patient-specific recommendations by a consulting pharmacist. RESULTS: The on-demand use was analyzed during treatment of 64,259 inpatients with 1,316,884 prescriptions. The DDI checker was popular with nine consulting pharmacologists (648 checks/consultant). A total of 644 prescribing physicians used it infrequently (eight checks/prescriber). Among prescribers, internists used the tool most frequently and obtained higher numbers of DDIs per check (1.7) compared to surgeons (0.4). A total of 16,553 DDIs were identified on-demand, i.e., <10 % of the number the computer would have triggered (169,192). A pharmacist visiting 922 patients on a medical ward recommended 128 adjustments to prevent DDIs (0.14 recommendations/patient), and 76 % of them were applied by prescribers. In contrast, computer-triggering the DDI checker would have resulted in 45 times more alerts on this ward (6.3 alerts/patient). CONCLUSIONS: The on-demand DDI checker was popular with the consultants only. However, prescribers accepted 76 % of patient-specific recommendations by a pharmacist. The prescribers' limited on-demand use indicates the necessity for developing improved safety concepts, tailored to suit these consumers. Thus, different approaches have to satisfy different target groups

Too frequent low-dose methotrexate prescriptions: multicentre quality control and quality assurance with pre- and post-analysis

INTRODUCTION Methotrexate is used to treat many medical conditions with medication schedules that differ widely in dosage and frequency. The high potential of erroneous too frequent low-dose methotrexate prescriptions leading to severe adverse reactions is well known; however, documentation is mainly limited to case reports. We reviewed all methotrexate prescriptions in a secondary and a tertiary care hospital to analyse the incidence of too frequent low-dose methotrexate prescriptions, and assessed the quality assurance concepts implemented. METHODS All nononcological low-dose methotrexate prescriptions issued for inpatients within 55 months were analysed to identify too frequent prescriptions potentially leading to harmful overdosing. Subsequently, clinical pharmacologists reviewed all new methotrexate prescriptions with resulting interventions at the physician level in the tertiary care hospital. The impact of an interruptive alert displayed at methotrexate order entry was assessed in the secondary care hospital. RESULTS The incidence of too frequent prescriptions at the tertiary hospital was 1.6% (five medication errors and nine near misses in 888 inpatients). After introducing checks by pharmacologists, two prescription errors were intercepted during the 8 month quality assurance period. At the secondary care hospital the incidence dropped from 2.5% (2/79, 20 months) to 0.8% (1/123, 35 months) after the alert was implemented. CONCLUSIONS The incidences of erroneous too frequent low-dose methotrexate prescriptions observed at both hospitals were considered too high due to the high potential for increased morbidity, mortality and costs. Therefore, quality assurance measures were implemented and the preliminary data show a positive impact on patient safety for both approaches

Developing strategies for predicting hyperkalemia in potassium-increasing drug-drug interactions

Objective: To compare different strategies predicting hyperkalemia (serum potassium level ≥5.5 mEq/l) in hospitalized patients for whom medications triggering potassium-increasing drug-drug interactions (DDIs) were ordered. Materials and Methods: We investigated 5 strategies that combined prediction triggered at onset of DDI versus continuous monitoring and taking into account an increasing number of patient parameters. The considered patient parameters were identified using generalized additive models, and the thresholds of the prediction strategies were calculated by applying Youden's J statistic to receiver operation characteristic curves. Half of the data served as the calibration set, half as the validation set. Results: We identified 132 incidences of hyperkalemia induced by 8413 potentially severe potassium-increasing DDIs among 76 467 patients. The positive predictive value (PPV) of those strategies predicting hyperkalemia at the onset of DDI ranged from 1.79% (undifferentiated anticipation of hyperkalemia due to the DDI) to 3.02% (additionally considering the baseline serum potassium) and 3.10% (including further patient parameters). Continuous monitoring significantly increased the PPV to 8.25% (considering the current serum potassium) and 9.34% (additional patient parameters). Conclusion: Continuous monitoring of the risk for hyperkalemia based on current potassium level shows a better predictive power than predictions triggered at the onset of DDI. This contrasts with efforts to improve DDI alerts by taking into account more patient parameters at the time of ordering

Evaluation of alerts for potassium-increasing drug-drug-interactions

Electronic alerts for preventing hyperkalaemia during potassium-increasing drug-drug-interactions (DDIs) are often overridden due to their low specificity. Treatments of 76,467 inpatients were retrospectively analysed to establish more specific alerts. Alerting concepts for identifying DDIs that induced hyperkalaemia (serum potassium ≥5.5 mEq/l were compared. The positive predictive value (PPV) of alerts was 2.9% if they were triggered at onset of each potassium-increasing DDI. The PPV increased to 5.1% if alerts at onset were suppressed for serum potassium levels of &lt;4.0 mEq/l. The PPV rose to 24.2% with a novel approach, triggering alerts whenever an elevated potassium level of &gt;4.8 mEq/l was detected at onset or during the entire DDI period. Thus, triggering DDI alerts based on periodically monitored potassium levels may improve specificity of alerts and thereby reduce alert fatigue

Shifting tasks from nurses to physicians: CDS needed after introduction of CPOE?

Unintended effects can occur by introducing computerized physician order entry (CPOE) if responsibilities are shifted from nurses to physicians, e.g. regarding the specification of the duration of intravenous (IV) administrations. The purpose of this quality assessment was to determine the rate of IV prescriptions with too short durations, when the prescribers were not assisted by clinical decision support (CDS)

Earlier switching from intravenous to oral antibiotics owing to electronic reminders

Paper-based interventions have been shown to stimulate switching from intravenous (i.v.) to oral (p.o.) antibiotic therapies. Shorter i.v. durations are associated with a lower risk of iatrogenic infections as well as reduced workload and costs. The purpose of this study was to determine whether automated electronic reminders are able to promote earlier switching. In this controlled before-and-after study, an algorithm identified patients who were eligible for i.v.-to-p.o. switch 60h after starting i.v. antimicrobials. Reminders offering guidance on the re-assessment of initial i.v. therapy were displayed within the electronic health records in 12 units during the intervention period (year 2012). In contrast, no reminders were visible during the baseline period (2011) and in the control group (17 units). A total of 22863 i.v. antibiotic therapies were analysed; 6082 (26.6%) were switched to p.o. THERAPY: In the intervention group, 757 courses of i.v. antibiotics were administered for a mean±standard deviation duration of 5.4±8.1 days before switching to p.o. antibiotics in the baseline period, and 794 courses for 4.5±5.5 days in the intervention period (P=0.004), corresponding to a 17.5% reduction of i.v. administration time. In contrast, in the control group the duration increased; 2240 i.v. antibiotics were administered for a mean duration of 4.0±5.9 days in the baseline period, and 2291 for 4.3±5.8 days in the intervention period (P=0.03). Electronic reminders fostered earlier i.v.-to-p.o. switches, thereby reducing the duration of initial i.v. therapies by nearly a day

Clinical decision support for monitoring drug-drug-interactions and potassium-increasing drug combinations: need for specific alerts

Computer-triggered reminders alerting physicians on every potentially harmful drug-drug-interaction (DDI) induce alert fatigue due to frequent messages of limited clinical relevance. On demand DDI-checks, however, are not commonly used by physicians. Optimal strategies for sustained quality assurance have to consider patients' risk factors and focus on the most significant DDIs only. An approach is proposed based on the analysis of concurrent prescription of potassium-sparing diuretics and potassium supplements (CPPP), which are the most frequent DDIs classified as contraindicated. Although the frequency of monitoring potassium serum levels declined during prolonged periods of CPPP, the likelihood of observing a hyperkalaemia increased. The median treatment period of CPPP was 3.3 days, whereas hyperkalaemia occurred after a median observation time of 4.5 days of CPPP. Thus, computer-triggered reminders for ordering potassium serum levels may be indicated if monitoring has been discontinued after 48h of CPPP