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 < 0.0001), impaired renal function (RR 2.7; p < 0.0001), diabetes mellitus (RR 1.6; p = 0.002) and female gender (RR 1.5; p = 0.007). Risk factors associated with medication were number of concurrently administered potassium-increasing drugs (RR 3.3 per additional drug; p < 0.0001) and longer duration of the DDI (RR 4.9 for duration ≥6 days; p < 0.0001). Physician-related factors associated with the development of hyperkalaemia were undetermined or elevated serum potassium level before treatment initiation (RR 2.2; p < 0.001) and infrequent monitoring of serum potassium during a DDI (interval >48 h: 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.

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.

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.

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.

Chronic Pain: How Challenging Are DDIs in the Analgesic Treatment of Inpatients with Multiple Chronic Conditions?

BACKGROUND: Chronic pain is common in multimorbid patients. However, little is known about the implications of chronic pain and analgesic treatment on multimorbid patients. This study aimed to assess chronic pain therapy with regard to the interaction potential in a sample of inpatients with multiple chronic conditions. METHODS AND FINDINGS: We conducted a retrospective study with all multimorbid inpatients aged ≥18 years admitted to the Department of Internal Medicine of University Hospital Zurich in 2011 (n = 1,039 patients). Data were extracted from the electronic health records and reviewed. We identified 433 hospitalizations of patients with chronic pain and analyzed their combinations of chronic conditions (multimorbidity). We then classified all analgesic prescriptions according to the World Health Organization (WHO) analgesic ladder. Furthermore, we used a Swiss drug-drug interactions knowledge base to identify potential interactions between opioids and other drug classes, in particular coanalgesics and other concomitant drugs. Chronic pain was present in 38% of patients with multimorbidity. On average, patients with chronic pain were aged 65.7 years and had a mean number of 6.6 diagnoses. Hypertension was the most common chronic condition. Chronic back pain was the most common painful condition. Almost 90% of patients were exposed to polypharmacotherapy. Of the chronic pain patients, 71.1% received opioids for moderate to severe pain, 43.4% received coanalgesics. We identified 3,186 potential drug-drug interactions, with 17% classified between analgesics (without coanalgesics). CONCLUSIONS: Analgesic drugs-related DDIs, in particular opioids, in multimorbid patients are often complex and difficult to assess by using DDI knowledge bases alone. Drug-multimorbidity interactions are not sufficiently investigated and understood. Today, the scientific literature is scarce for chronic pain in combination with multiple coexisting medical conditions and medication regimens. Our work may provide useful information to enable further investigations in multimorbidity research within the scope of potential interactions and chronic pain.

Impact of Specific Alerts in Potassium-Increasing Drug-Drug Interactions.

Alerts in potassium(K+)-increasing drug-drug interactions (DDIs) are often ignored due to their low specificity. Although different approaches have been implemented to address DDIs, subsequent clinical studies revealed poor adherence to such alerts. We therefore suggest a novel alert concept currently being evaluated in a randomized clinical trial in a large teaching hospital. Highly specific reminders (to monitor K+) and alerts (of hyperkalaemia) are displayed to the physicians of the intervention group, whereas reminders and alerts are suppressed in the control group. Preliminary analysis shows a high alert specificity. Furthermore, the physicians of the intervention group reacted significantly faster to a problematic situation arising during a K+-increasing DDI compared to the physicians of the control group, indicating that this concept has an impact on physician behaviour.

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.

Earlier switching from intravenous to oral antibiotics owing to electronic reminders.

UNLABELLED: 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 60 h 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.

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.

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 <4.0 mEq/l. The PPV rose to 24.2% with a novel approach, triggering alerts whenever an elevated potassium level of >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.