On the alert: future priorities for alerts in clinical decision support for computerized physician order entry identified from a European workshop

Background: Clinical decision support (CDS) for electronic prescribing systems (computerized physician order entry) should help prescribers in the safe and rational use of medicines. However, the best ways to alert users to unsafe or irrational prescribing are uncertain. Specifically, CDS systems may generate too many alerts, producing unwelcome distractions for prescribers, or too few alerts running the risk of overlooking possible harms. Obtaining the right balance of alerting to adequately improve patient safety should be a priority. Methods: A workshop funded through the European Regional Development Fund was convened by the University Hospitals Birmingham NHS Foundation Trust to assess current knowledge on alerts in CDS and to reach a consensus on a future research agenda on this topic. Leading European researchers in CDS and alerts in electronic prescribing systems were invited to the workshop. Results: We identified important knowledge gaps and suggest research priorities including (1) the need to determine the optimal sensitivity and specificity of alerts; (2) whether adaptation to the environment or characteristics of the user may improve alerts; and (3) whether modifying the timing and number of alerts will lead to improvements. We have also discussed the challenges and benefits of using naturalistic or experimental studies in the evaluation of alerts and suggested appropriate outcome measures. Conclusions: We have identified critical problems in CDS, which should help to guide priorities in research to evaluate alerts. It is hoped that this will spark the next generation of novel research from which practical steps can be taken to implement changes to CDS systems that will ultimately reduce alert fatigue and improve the design of future systems

How to assess pharmacogenomic tests for implementation in the NHS in England

AIMS: Pharmacogenomic testing has the potential to target medicines more effectively towards those who will benefit and avoid use in individuals at risk of harm. Health economies are actively considering how pharmacogenomic tests can be integrated into health care systems to improve use of medicines. However, one of the barriers to effective implementation is evaluation of the evidence including clinical usefulness, cost-effectiveness, and operational requirements. We sought to develop a framework that could aid the implementation of pharmacogenomic testing. We take the view from the National Health Service (NHS) in England. METHODS: We used a literature review using EMBASE and Medline databases to identify prospective studies of pharmacogenomic testing, focusing on clinical outcomes and implementation of pharmacogenomics. Using this search, we identified key themes relating to the implementation of pharmacogenomic tests. We used a clinical advisory group with expertise in pharmacology, pharmacogenomics, formulary evaluation, and policy implementation to review data from our literature review and the interpretation of these data. With the clinical advisory group, we prioritized themes and developed a framework to evaluate proposals to implement pharmacogenomics tests. RESULTS: Themes that emerged from review of the literature and subsequent discussion were distilled into a 10-point checklist that is proposed as a tool to aid evidence-based implementation of pharmacogenomic testing into routine clinical care within the NHS. CONCLUSION: Our 10-point checklist outlines a standardized approach that could be used to evaluate proposals to implement pharmacogenomic tests. We propose a national approach, taking the view of the NHS in England. Using this approach could centralize commissioning of appropriate pharmacogenomic tests, reduce inequity and duplication using regional approaches, and provide a robust and evidence-based framework for adoption. Such an approach could also be applied to other health systems

A systematic review and meta-analysis of thiazide-induced hyponatraemia: time to reconsider electrolyte monitoring regimens after thiazide initiation?

Aims: Hyponatraemia is one of the major adverse effects of thiazide and thiazide-like diuretics and the leading cause of drug-induced hyponatraemia requiring hospital admission. We sought to review and analyze all published cases of this important condition. Methods: Ovid Medline, Embase, Web of Science and PubMed electronic databases were searched to identify all relevant articles published before October 2013. A proportions meta-analysis was undertaken. Results: One hundred and two articles were identified of which 49 were single patient case reports. Meta-analysis showed that mean age was 75 (95% CI 73, 77) years, 79% were women (95% CI 74, 82) and mean body mass index was 25 (95% CI 20, 30) kg m−2. Presentation with thiazide-induced hyponatraemia occurred a mean of 19 (95% CI 8, 30) days after starting treatment, with mean trough serum sodium concentration of 116 (95% CI 113, 120) mm and serum potassium of 3.3 (95% CI 3.0, 3.5) mm. Mean urinary sodium concentration was 64 mm (95% CI 47, 81). The most frequently reported drugs were hydrochlorothiazide, indapamide and bendroflumethiazide. Conclusions: Patients with thiazide-induced hyponatraemia were characterized by advanced age, female gender, inappropriate saliuresis and mild hypokalaemia. Low BMI was not found to be a significant risk factor, despite previous suggestions. The time from thiazide initiation to presentation with hyponatraemia suggests that the recommended practice of performing a single investigation of serum biochemistry 7–14 days after thiazide initiation may be insufficient or suboptimal. Further larger and more systematic studies of thiazide-induced hyponatraemia are required

A systematic review and meta-analysis of thiazide-induced hyponatraemia: time to reconsider electrolyte monitoring regimens after thiazide initiation?

Aims: Hyponatraemia is one of the major adverse effects of thiazide and thiazide-like diuretics and the leading cause of drug-induced hyponatraemia requiring hospital admission. We sought to review and analyze all published cases of this important condition. Methods: Ovid Medline, Embase, Web of Science and PubMed electronic databases were searched to identify all relevant articles published before October 2013. A proportions meta-analysis was undertaken. Results: One hundred and two articles were identified of which 49 were single patient case reports. Meta-analysis showed that mean age was 75 (95% CI 73, 77) years, 79% were women (95% CI 74, 82) and mean body mass index was 25 (95% CI 20, 30) kg m−2. Presentation with thiazide-induced hyponatraemia occurred a mean of 19 (95% CI 8, 30) days after starting treatment, with mean trough serum sodium concentration of 116 (95% CI 113, 120) mm and serum potassium of 3.3 (95% CI 3.0, 3.5) mm. Mean urinary sodium concentration was 64 mm (95% CI 47, 81). The most frequently reported drugs were hydrochlorothiazide, indapamide and bendroflumethiazide. Conclusions: Patients with thiazide-induced hyponatraemia were characterized by advanced age, female gender, inappropriate saliuresis and mild hypokalaemia. Low BMI was not found to be a significant risk factor, despite previous suggestions. The time from thiazide initiation to presentation with hyponatraemia suggests that the recommended practice of performing a single investigation of serum biochemistry 7–14 days after thiazide initiation may be insufficient or suboptimal. Further larger and more systematic studies of thiazide-induced hyponatraemia are required

Hypoglycemia in Non-Diabetic In-Patients: Clinical or Criminal?

BACKGROUND AND AIM: We wished to establish the frequency of unexpected hypoglycemia observed in non diabetic patients outside the intensive care unit and to determine if they have a plausible clinical explanation. METHODS: We analysed data for 2010 from three distinct sources to identify non diabetic hypoglycaemic patients: bedside and laboratory blood glucose measurements; medication records for those treatments (high-strength glucose solution and glucagon) commonly given to reverse hypoglycemia; and diagnostic codes for hypoglycemia. We excluded from the denominator admissions of patients with a diagnosis of diabetes or prescribed diabetic medication. Case notes of patients identified were reviewed. We used capture-recapture methods to establish the likely frequency of hypoglycemia in non-diabetic in-patients outside intensive care unit at different cut-off points for hypoglycemia. We also recorded co-morbidities that might have given rise to hypoglycemia. RESULTS: Among the 37,898 admissions, the triggers identified 71 hypoglycaemic episodes at a cut-off of 3.3 mmol/l. Estimated frequency at 3.3 mmol/l was 50(CI 33-93), at 3.0 mmol/l, 36(CI 24-64), at 2.7 mmol/l, 13(CI 11-19), at 2.5 mmol/l, 11(CI 9-15) and at 2.2 mmol/l, 8(CI 7-11) per 10,000 admissions. Admissions of patients aged above 65 years were approximately 50% more likely to have an episode of hypoglycemia. Most were associated with important co-morbidities. CONCLUSION: Significant non-diabetic hypoglycemia in hospital in-patients (at or below 2.7 mmol/l) outside critical care is rare. It is sufficiently rare for occurrences to merit case-note review and diagnostic blood tests, unless an obvious explanation is found