Use of an electronic alert to identify patients with acute kidney injury

Effect of electronic alerts on the care and outcomes in patients with acute kidney injury: a meta-analysis and trial sequential analysis

BACKGROUND

Although electronic alerts are being increasingly implemented in patients with acute kidney injury (AKI), their effect remains unclear. Therefore, we conducted this meta-analysis aiming at investigating their impact on the care and outcomes of AKI patients.

METHODS

PubMed, Embase, Cochrane Library, and Clinical Trial Registries databases were systematically searched for relevant studies from inception to March 2024. Randomized controlled trials comparing electronic alerts with usual care in patients with AKI were selected.

RESULTS

Six studies including 40,146 patients met the inclusion criteria. The pooled results showed that electronic alerts did not improve mortality rates (relative risk (RR) = 1.02, 95% confidence interval (CI) = 0.97-1.08, P = 0.44) or reduce creatinine levels (mean difference (MD) =  - 0.21, 95% CI =  - 1.60-1.18, P = 0.77) and AKI progression (RR = 0.97, 95% CI = 0.90-1.04, P = 0.40). Instead, electronic alerts increased the odds of dialysis and AKI documentation (RR = 1.14, 95% CI = 1.05-1.25, P = 0.002; RR = 1.21, 95% CI = 1.01-1.44, P = 0.04, respectively), but the trial sequential analysis (TSA) could not confirm these results. No differences were observed in other care-centered outcomes including renal consults and investigations between the alert and usual care groups.

CONCLUSIONS

Electronic alerts increased the incidence of AKI and dialysis in AKI patients, which likely reflected improved recognition and early intervention. However, these changes did not improve the survival or kidney function of AKI patients. The findings warrant further research to comprehensively evaluate the impact of electronic alerts.

Mixed methods evaluation of a computerised audit and feedback dashboard to improve patient safety through targeting acute kidney injury (AKI) in primary care

BACKGROUND

Reducing the harms associated with acute kidney injury (AKI) requires addressing a wide range of patient safety issues, including polypharmacy and transitions of care, particularly for vulnerable patient groups. Computerised audit and feedback can transform the way healthcare organisations measure, analyse and learn from quality and safety data across different care settings, potentially improving patient safety.

OBJECTIVE

To implement and evaluate an audit and feedback dashboard targeting AKI to improve patient safety, focusing on factors affecting a range of user characteristics in primary care.

METHODS

We performed a mixed methods study in three stages. Semi-structured interviews were initially performed with both primary (n = 10) and secondary care (n = 5) staff to gather user requirements for six quality indicators extracted from national guidance on post-discharge AKI care. Modified indicators were implemented in the Performance Improvement plaN GeneratoR (PINGR) audit and feedback dashboard for six months, across 45 general practices in Salford. Primary care professionals were then interviewed again (n = 7) and completed usability questionnaires. This was triangulated with an interrupted time series analysis on indicator performance, alongside software usage statistics.

RESULTS

Improvements were observed for the indicators for medication review (+9.01 %; 95 % Confidence Interval (CI), +6.95 % to +11.06 %) and blood pressure measurement (+5.20 %; 95 % CI + 3.61 % to +6.78 %). Variable performance and engagement were observed for other indicators including AKI coding (+0.39 %; 95 % CI -1.88 % to +2.65 %), serum creatinine (-3.40 %; 95 % CI -7.66 % to +0.85 %), proteinuria (-1.08 %; 95 % CI -1.47 % to +0.32 %) and providing patient information (+0.16 %; 95 % CI -0.41 % to +0.73 %). A key facilitator to engagement was the development of 'champions of change', achieved through a raised awareness of high-risk patients, guidelines, inconsistencies in coding practice and evidence for quality and safety performance. Barriers related to the specificity and perceived achievability of indicators, and limitations in resources.

CONCLUSION

In a six-month, quasi-experimental evaluation of an electronic audit and feedback dashboard targeting AKI, we found improvements for two out of six quality indicators. While information technology can facilitate improvements in patient safety, further allocation of protected staff time and investment into shared learning are needed to realise those improvements in practice.

Combination of biomarker with clinical risk factors for prediction of severe acute kidney injury in critically ill patients

Background

Acute kidney injury (AKI) occurs commonly in the intensive care unit (ICU). Insulin-like growth factor-binding protein 7 (IGFBP7) and tissue inhibitor of metalloproteinase-2 (TIMP-2), known as [TIMP-2] x [IGFBP7] (NephroCheck), have been identified as novel biomarkers for the prediction of AKI risk. However, the effective use of disease biomarkers is indispensable from an appropriate clinical context. We conducted a retrospective cohort study to find risk factors and assess the performance of the combination of NephroCheck with risk factors, so as to provide feasible information for AKI prediction.

Methods

All patients who were admitted in the ICU (from June 2016 to July 2017) participated in the study. The primary outcome was the detection of severe AKI within the first 7 days after patients being admitted to the ICU. The predictors were separated into three categories: chronic risk factors, acute risk factors and biochemical indicators.

Results

The study included 577 patients. 96 patients developed to severe AKI (16.6%) within 7 days. In addition to NephroCheck (+) (OR = 2.139, 95% CI (1.260–3.630), P = 0.005), age > 65 years (OR = 1.961, 95% CI (1.153–3.336), P = 0.013), CKD (OR = 2.573, 95% CI (1.319–5.018), P = 0.006) and PCT (+)(OR = 3.223, 95% CI (1.643–6.321), P = 0.001) were also the independent predictors of severe AKI within 7 days. Compared to NephroCheck (+) only (AUC = 0.66, 95% CI:0.60–0.72), the combination of NephroCheck (+) and risk factors (age > 65 years, CKD and PCT positive) (AUC = 0.75, 95% CI:0.70–0.81) led to a significant increase in the area under ROC curve for severe AKI prediction within 7 days.

Conclusions

Although NephroCheck is an effective screening tool for recognizing high-risk patients, we found that combination with biomarker and risk factors (age > 65 years, CKD, procalcitonin positive) for risk assessment of AKI has the greatest significance to patients with uncertain disease trajectories.

Development and initial implementation of electronic clinical decision supports for recognition and management of hospital-acquired acute kidney injury

BACKGROUND

Acute kidney injury (AKI) is common in hospitalized patients and is associated with poor patient outcomes and high costs of care. The implementation of clinical decision support tools within electronic medical record (EMR) could improve AKI care and outcomes. While clinical decision support tools have the potential to enhance recognition and management of AKI, there is limited description in the literature of how these tools were developed and whether they meet end-user expectations.

METHODS

We developed and evaluated the content, acceptability, and usability of electronic clinical decision support tools for AKI care. Multi-component tools were developed within a hospital EMR (Sunrise Clinical Manager™, Allscripts Healthcare Solutions Inc.) currently deployed in Calgary, Alberta, and included: AKI stage alerts, AKI adverse medication warnings, AKI clinical summary dashboard, and an AKI order set. The clinical decision support was developed for use by multiple healthcare providers at the time and point of care on general medical and surgical units. Functional and usability testing for the alerts and clinical summary dashboard was conducted via in-person evaluation sessions, interviews, and surveys of care providers. Formal user acceptance testing with clinical end-users, including physicians and nursing staff, was conducted to evaluate the AKI order set.

RESULTS

Considerations for appropriate deployment of both non-disruptive and interruptive functions was important to gain acceptability by clinicians. Functional testing and usability surveys for the alerts and clinical summary dashboard indicated that the tools were operating as desired and 74% (17/23) of surveyed healthcare providers reported that these tools were easy to use and could be learned quickly. Over three-quarters of providers (18/23) reported that they would utilize the tools in their practice. Three-quarters of the participants (13/17) in user acceptance testing agreed that recommendations within the order set were useful. Overall, 88% (15/17) believed that the order set would improve the care and management of AKI patients.

CONCLUSIONS

Development and testing of EMR-based decision support tools for AKI with clinicians led to high acceptance by clinical end-users. Subsequent implementation within clinical environments will require end-user education and engagement in system-level initiatives to use the tools to improve care.

Global epidemiology and outcomes of acute kidney injury

Acute kidney injury (AKI) is a commonly encountered syndrome associated with various aetiologies and pathophysiological processes leading to decreased kidney function. In addition to retention of waste products, impaired electrolyte homeostasis and altered drug concentrations, AKI induces a generalized inflammatory response that affects distant organs. Full recovery of kidney function is uncommon, which leaves these patients at risk of long-term morbidity and death. Estimates of AKI prevalence range from <1% to 66%. These variations can be explained by not only population differences but also inconsistent use of standardized AKI classification criteria. The aetiology and incidence of AKI also differ between high-income and low-to-middle-income countries. High-income countries show a lower incidence of AKI than do low-to-middle-income countries, where contaminated water and endemic diseases such as malaria contribute to a high burden of AKI. Outcomes of AKI are similar to or more severe than those of patients in high-income countries. In all resource settings, suboptimal early recognition and care of patients with AKI impede their recovery and lead to high mortality, which highlights unmet needs for improved detection and diagnosis of AKI and for efforts to improve care for these patients.

Identifying on admission patients likely to develop acute kidney injury in hospital

Background

The incidence of Acute Kidney Injury (AKI) continues to increase in the UK, with associated mortality rates remaining significant. Approximately one fifth of hospital admissions are associated with AKI and approximately a third of patients with AKI in hospital develop AKI during their time in hospital. A fifth of these cases are considered avoidable. Early risk detection remains key to decreasing AKI in hospitals, where sub-optimal care was noted for half of patients who developed AKI.

Methods

Electronic anonymised data for adults admitted into the Royal Cornwall Hospitals Trust (RCHT) between 18th March and 31st December 2015 was trimmed to that collected within the first 24 h of hospitalisation. These datasets were split according to three separate time periods: data used for training the Takagi-Sugeno Fuzzy Logic Systems (FLS) and the multivariable logistic regression (MLR) models; data used for testing; and data from a later patient spell used for validation.

Three fuzzy logic models and three MLR models were developed to link characteristics of patients diagnosed with a maximum stage AKI within 7 days of admission: the first models to identify any AKI Stage (FLS I, MLR I), the second for patterns of AKI Stage 2 or 3 (FLS II, MLR II), and the third to identify AKI Stage 3 (FLS III, MLR III). Model accuracy is expressed by area under the curve (AUC).

Results

Accuracy for each model during internal validation was: FLS I and MLR I (AUC 0.70, 95% CI: 0.64–0.77); FLS II (AUC 0.77, 95% CI: 0.69–0.85) and MLR II (AUC 0.74, 95% CI: 0.65–0.83); FLS III and MLR III (AUC 0.95, 95% CI: 0.92–0.98).

Conclusions

FLS II and FLS III (and the respective MLR models) can identify with a high level of accuracy patients at high risk of developing AKI in hospital. These two models cannot be properly assessed against prior studies as this is the first attempt at quantifying the risk of developing specific Stages of AKI for a broad cohort of both medical and surgical inpatients. FLS I and MLR I performance is comparable to other existing models.

Electronic supplementary material

The online version of this article (10.1186/s12882-019-1237-x) contains supplementary material, which is available to authorized users.

Impact of introducing electronic acute kidney injury alerts in primary care

Background

Acute kidney injury (AKI) is associated with decreased survival, future risk of chronic kidney disease and longer hospital stays. Electronic alerts (e-alerts) for AKI have been introduced in the UK in order to facilitate earlier detection and improve management. The aim of this study was to establish if e-alerts in primary care were acted on by examining timing of repeat creatinine testing.

Methods

The National Health Service England Acute Kidney Injury electronic alert algorithm was introduced in April 2015 across both primary and secondary care in NHS Tayside accompanied by a programme of education. Data from a 12-month period (2012) predating introduction of the e-alerts were compared with a 12-month period following implementation of e-alerts for AKI. Biochemistry testing following the AKI episode, timing of repeat tests and numbers of patients hospitalized within 7 days of episode were compared between the two time periods.

Results

During the 12 months after e-alert introduction, 9781 AKI e-alerts were generated. Of these, 1460 (14.9%) alerts were generated in primary care. Median duration to repeat blood testing for these primary care alerts was 5 days for AKI Stage 1 [interquartile range (IQR) 2–10], 2 days for Stage 2 (IQR 1–5) and 1 day (IQR 0–2) for Stage 3. During 2012 (prior to e-alert implementation) 8812 AKI episodes were identified. Of these, 2650 tests (30.1%) were requested by primary care staff. Median duration to repeat creatinine testing was longer: 55 days (IQR 20–142) for Stage 1, 38 days (IQR 15–128) for Stage 2 was and 53 days (IQR 20–137) for Stage 3. More patients had biochemistry tests repeated within 7 days of AKI onset, pre-alert implementation; 252 (9.5%) versus 857 (58.7%) (P < 0.001). Rates of hospitalization within 7 days of AKI increased from 342 (12.9%) pre-implementation to 372 (25.5%) post-implementation (P < 0.001).

Conclusions

Within primary care, e-alert implementation was associated with higher rates of creatinine monitoring, but also higher rates of hospitalization.

Computer decision support for acute kidney injury: current and future

PURPOSE OF REVIEW

Growing awareness regarding the impact of acute kidney injury (AKI) as a grave consequence of critical illnesses resulted in the expansion of the need for early detection and appropriate management strategies. Clinical decision support systems (CDSS) can generate information to improve the care of AKI patients by providing point-of-care accurate patient-specific information and recommendations. Our objective is to describe the characteristics of CDSS and review the current knowledge regarding the impact of CDSS on patients in the acute care settings, and specifically for AKI.

RECENT FINDINGS

Several recent systematic analyses showed the positive impact of CDSS on critically ill patients care processes. These studies also highlighted the scarcity of data regarding the effect of CDSS on the patient outcomes. In the field of AKI, there have been several reports to describe development and validation of homegrown CDSS and electronic alert systems. A large number of investigations showed the implementation of CDSS could improve the quality of AKI care; although, only in a very small subgroup of these studies patient outcomes improved.

SUMMARY

The heterogeneity of these studies in their size, design, and conduct has produced controversial findings; hence, this has left the field completely open for further investigations.

Acute kidney injury is under-recognised and under-reported in hospitalised patients in Australia

Acute kidney injury (AKI) in hospitalised patients is associated with adverse outcomes; however, it remains unrecognised and under-reported. A total of 48 045 serum creatinine results from 8129 tertiary hospital inpatients were reviewed. The prevalence of AKI was 4.33%. Mortality was significantly higher in patients with AKI (16.76%) compared to those without AKI (1.88%, P < 0.001). Documentation of AKI in discharge summaries was poor.

The assessment of acute kidney injury in critically ill patients

Acute kidney injury (AKI) is common in critically ill patients and is associated with high morbidity and mortality. The availability of several biomarkers of kidney injury offers new tools for its early recognition and management. The early identification of high-risk patients provides an opportunity to develop strategies for the prevention, early diagnosis and treatment of AKI. Despite progress in critical care medicine over the past decade, the treatment strategies for AKI in critically ill patients, such as when to start renal replacement therapy, remain controversial. A recently proposed risk prediction score for AKI, based on routinely available clinical variables, presents a new means of identifying patients at high risk of AKI.

Impact of e-alert systems on the care of patients with acute kidney injury

With the recent advancement in electronic health record systems and meaningful use of information technology incentive programs (i.e., the American Recovery and Reinvestment Act, the Health Information Technology for Economic and Clinical Health Act, and the Centers for Medicare & Medicaid Services), interest in clinical decision support systems has risen. These systems have been used to examine a variety of different syndromes with variable reported effects. In recent years, electronic alerts (e-alerts) have been implemented at various institutions to decrease the morbidity associated with acute kidney injury (AKI). AKI is common, accounting for 1 in 7 hospital admissions, and is associated with increased length of hospital stay and mortality. AKI is often underrecognized, causing delayed intervention. The use of e-alerts may result in earlier recognition and intervention, as well as decreased morbidity and mortality. This must be balanced with the possibility of increased resource utilization that e-alerts may cause. Before widespread implementation, the ethical and legal consequences of not following e-alert recommendations must be established, and the optimal algorithm for AKI e-alert detection must be determined.

Information Technology and Acute Kidney Injury: Alerts, Alarms, Bells, and Whistles

The goal of this review is to describe the rationale for alerting systems for acute kidney injury, the challenges associated with alert implementation, and the efficacy (or lack thereof) of acute kidney injury alerts to date.

Electronic Alerts for Acute Kidney Injury

BACKGROUND

Acute kidney injury (AKI) often takes a complicated course if diagnosed late and undertreated. Electronic alerts that provide an early warning of AKI are intended to support treating physicians in making the diagnosis of AKI and treating it appropriately. The available evidence on the effects of such alert systems is inconsistent.

METHODS

We employed the PRISMA recommendations for systematic literature reviews to identify relevant articles in the PubMed, Scopus, and Web of Science databases. All of the studies that were retrieved were independently assessed by two of the authors with respect to the methods of computer-assisted electronic alert systems and their effects on process indicators and clinical endpoints.

RESULTS

16 studies with a total of 32 842 patients were identified. 8.5% of admitted patients had community-acquired or hospital-acquired AKI, with an in-hospital mortality of 22.8%. Fifteen electronic alert systems were in use throughout the participating hospitals. In 13 of 15 studies, alarm activation was accompanied by concrete treatment recommendations. A randomized controlled trial in which no such recommendations were given did not reveal any benefit of the alert system for the patients. In controlled but non-randomized trials, however, the provision of concrete treatment recommendations when the alert was activated led to more frequent implementation of diagnostic or therapeutic measures, less loss of renal function, lower in-hospital mortality, and lower mortality after discharge compared to control groups without an electronic alert for AKI.

CONCLUSION

Non-randomized controlled trials of electronic alerts for AKI that were coupled with treatment recommendations have yielded evidence of improved care processes and treatment outcomes for patients with AKI. This review is limited by the low number of randomized trials and the wide variety of endpoints used in the studies that were evaluated.

Acute Kidney Injury in the Era of the AKI E-Alert

BACKGROUND AND OBJECTIVES

Our aim was to use a national electronic AKI alert to define the incidence and outcome of all episodes of community- and hospital-acquired adult AKI.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

A prospective national cohort study was undertaken in a population of 3.06 million. Data were collected between March of 2015 and August of 2015. All patients with adult (≥18 years of age) AKI were identified to define the incidence and outcome of all episodes of community- and hospital-acquired AKI in adults. Mortality and renal outcomes were assessed at 90 days.

RESULTS

There was a total of 31,601 alerts representing 17,689 incident episodes, giving an incidence of AKI of 577 per 100,000 population. Community-acquired AKI accounted for 49.3% of all incident episodes, and 42% occurred in the context of preexisting CKD (Chronic Kidney Disease Epidemiology Collaboration eGFR); 90-day mortality rate was 25.6%, and 23.7% of episodes progressed to a higher AKI stage than the stage associated with the alert. AKI electronic alert stage and peak AKI stage were associated with mortality, and mortality was significantly higher for hospital-acquired AKI compared with alerts generated in a community setting. Among patients who survived to 90 days after the AKI electronic alert, those who were not hospitalized had a lower rate of renal recovery and a greater likelihood of developing an eGFR<60 ml/min per 1.73 m2 for the first time, which may be indicative of development of de novo CKD.

CONCLUSIONS

The reported incidence of AKI is far greater than the previously reported incidence in studies reliant on clinical identification of adult AKI or hospital coding data. Although an electronic alert system is Information Technology driven and therefore, lacks intelligence and clinical context, these data can be used to identify deficiencies in care, guide the development of appropriate intervention strategies, and provide a baseline against which the effectiveness of these interventions may be measured.

Improving acute kidney injury diagnostics using predictive analytics

PURPOSE OF REVIEW

Acute kidney injury (AKI) is a multifactorial syndrome affecting an alarming proportion of hospitalized patients. Although early recognition may expedite management, the ability to identify patients at-risk and those suffering real-time injury is inconsistent. The review will summarize the recent reports describing advancements in the area of AKI epidemiology, specifically focusing on risk scoring and predictive analytics.

RECENT FINDINGS

In the critical care population, the primary underlying factors limiting prediction models include an inability to properly account for patient heterogeneity and underperforming metrics used to assess kidney function. Severity of illness scores demonstrate limited AKI predictive performance. Recent evidence suggests traditional methods for detecting AKI may be leveraged and ultimately replaced by newer, more sophisticated analytical tools capable of prediction and identification: risk stratification, novel AKI biomarkers, and clinical information systems. Additionally, the utility of novel biomarkers may be optimized through targeting using patient context, and may provide more granular information about the injury phenotype. Finally, manipulation of the electronic health record allows for real-time recognition of injury.

SUMMARY

Integrating a high-functioning clinical information system with risk stratification methodology and novel biomarker yields a predictive analytic model for AKI diagnostics.

Recent developments in electronic alerts for acute kidney injury

PURPOSE OF REVIEW

Efforts to improve outcomes from acute kidney injury (AKI) have focussed on timely diagnosis and effective delivery of basic patient care. Electronic alerts (e-alerts) for AKI have attracted interest as a tool to facilitate this. Initial feasibility has already been demonstrated; this review will discuss recent advances in alert methodology, implementation beyond single centres and reported effect on outcomes.

RECENT FINDINGS

On-going descriptions of e-alerts highlight increasing variation in both detection algorithms and alert processes. In England, this is being addressed by national rollout of a standardized detection algorithm; recent data have shown this to have good diagnostic performance. In critical care, fully automated detection systems incorporating both serum creatinine and urine output criteria have been developed. A recent randomized trial of e-alerts has also been reported, in which isolated use of a text message e-alert did not affect either clinician behaviour or patient outcome.

SUMMARY

As e-alerts gain popularity, consideration must be given to both the method of AKI detection and the method by which results are communicated to end-users; these aspects influence the degree of these systems' effectiveness. This approach should be coupled to further work to study the effect on patient outcomes of those interventions that have been demonstrated to influence clinician behaviour.

Technology innovation for patients with kidney disease

The loss of kidney function is a life-changing event leading to life-long dependence on healthcare. Around 5000 people are diagnosed with kidney failure every year. Historically, technology in renal medicine has been employed for replacement therapies. Recently, a lot of emphasis has been placed on technologies that aid early identification and prevent progression of kidney disease, while at the same time empowering affected individuals to gain control over their chronic illness. There is a shift in diversity of technology development, driven by collaborative innovation initiatives such the National Institute's for Health Research Healthcare Technology Co-operative for Devices for Dignity. This has seen the emergence of the patient as a key figure in designing technologies that are fit for purpose, while business involvement has ensured uptake and sustainability of these developments. An embodiment of this approach is the first successful Small Business Research Initiative in the field of renal medicine in the UK.

Clinical Use of the Urine Biomarker [TIMP-2] × [IGFBP7] for Acute Kidney Injury Risk Assessment

Acute kidney injury (AKI) is a serious complication, commonly occurring in the critically ill population, with devastating short- and long-term consequences. Despite standardization of the definition and staging of AKI, early recognition remains challenging given that serum creatinine level is a marker, albeit imperfect, of kidney function and not kidney injury. Furthermore, the delay in increase in serum creatinine level after loss of glomerular filtration also prevents timely detection of decreased kidney function in patients with AKI. During the past decade, numerous clinical investigations have evaluated the utility of several biomarkers in the early diagnosis and risk stratification of AKI. In 2014, the US Food and Drug Administration approved the marketing of a test based on the combination of urine concentrations of tissue inhibitor of metalloproteinase 2 and insulin-like growth factor binding protein 7 ([TIMP-2] × [IGFBP7]) to determine whether certain critically ill patients are at risk for developing moderate to severe AKI. The optimal role of this biomarker in the diagnosis, management, and prognosis of AKI in different clinical settings requires further clarification. In this perspective, we summarize the biological actions of these 2 cell-cycle arrest biomarkers and present important considerations regarding the clinical application, interpretation, and limitations of this novel test for the early detection of AKI.

Impact of electronic-alerting of acute kidney injury: workgroup statements from the 15(th) ADQI Consensus Conference

Purpose of the review

Among hospitalized patients, acute kidney injury is common and associated with significant morbidity and risk for mortality. The use of electronic health records (EHR) for prediction and detection of this important clinical syndrome has grown in the past decade. The steering committee of the 15^th Acute Dialysis Quality Initiative (ADQI) conference dedicated a workgroup with the task of identifying elements that may impact the course of events following Acute Kidney Injury (AKI) e-alert.

Sources of information

Following an extensive, non-systematic literature search, we used a modified Delphi process to reach consensus regarding several aspects of the utilization of AKI e-alerts.

Findings

Topics discussed in this workgroup included progress in evidence base practices, the characteristics of an optimal e-alert, the measures of efficacy and effectiveness, and finally what responses would be considered best practices following AKI e-alerts. Authors concluded that the current evidence for e-alert system efficacy, although growing, remains insufficient. Technology and human-related factors were found to be crucial elements of any future investigation or implementation of such tools. The group also concluded that implementation of such systems should not be done without a vigorous plan to evaluate the efficacy and effectiveness of e-alerts. Efficacy and effectiveness of e-alerts should be measured by context-specific process and patient outcomes. Finally, the group made several suggestions regarding the clinical decision support that should be considered following successful e-alert implementation.

Limitations

This paper reflects the findings of a non-systematic review and expert opinion.

Implications

We recommend implementation of the findings of this workgroup report for use of AKI e-alerts.

Acute kidney injury-how does automated detection perform?

BACKGROUND

Early detection of acute kidney injury (AKI) is important for safe clinical practice. NHS England is implementing a nationwide automated AKI detection system based on changes in blood creatinine. Little has been reported on the similarities and differences of AKI patients detected by this algorithm and other definitions of AKI in the literature.

METHODS

We assessed the NHS England AKI algorithm and other definitions using routine biochemistry in our own health authority in Scotland in 2003 (adult population 438 332). Linked hospital episode codes (ICD-10) were used to identify patients where AKI was a major clinical diagnosis. We compared how well the algorithm detected this subset of AKI patients in comparison to other definitions of AKI. We also evaluated the potential 'alert burden' from using the NHS England algorithm in comparison to other AKI definitions.

RESULTS

Of 127 851 patients with at least one blood test in 2003, the NHS England AKI algorithm identified 5565 patients. The combined NHS England algorithm criteria detected 91.2% (87.6-94.0) of patients who had an ICD-10 AKI code and this was better than any individual AKI definition. Some of those not captured could be identified by algorithm modifications to identify AKI in retrospect after recovery, but this would not be practical in real-time. Any modifications also increased the number of alerted patients (2-fold in the most sensitive model).

CONCLUSIONS

The NHS England AKI algorithm performs well as a diagnostic adjunct in clinical practice. In those without baseline data, AKI may only be seen in biochemistry in retrospect, therefore proactive clinical care remains essential. An alternative algorithm could increase the diagnostic sensitivity, but this would also produce a much greater burden of patient alerts.

Impact of Compliance with a Care Bundle on Acute Kidney Injury Outcomes: A Prospective Observational Study

Background

A recent report has highlighted suboptimal standards of care for acute kidney injury (AKI) patients in England. The objective of this study was to ascertain if improvement in basic standard of care by implementing a care bundle (CB) with interruptive alert improved outcomes in patients with AKI.

Methods

An AKI CB linked to electronic recognition of AKI, coupled with an interruptive alert, was introduced to improve basic care delivered to patients with AKI. Outcomes were compared in patients who had the CB completed within 24 hours (early CB group) versus those who didn’t have the CB completed or had it completed after 24 hours.

Results

In the 11-month period, 2297 patients had 2500 AKI episodes, with 1209 and 1291 episodes occurring before and after implementation of the AKI CB with interruptive alert, respectively. The CB was completed within 24 hours in 306 (12.2%) of AKI episodes. In-hospital case-fatality was significantly lower in the early CB group (18% versus 23.1%, p 0.046). Progression to higher AKI stages was lower in the early CB group (3.9% vs. 8.1%, p 0.01). In multivariate analysis, patients in the early CB group had lower odds of death at discharge (0.641; 95% CI 0.46, 0.891), 30 days (0.707; 95% CI 0.527, 0.950), 60 days (0.704; 95% CI 0.526, 0.941) and after a median of 134 days (0.771; 95% CI 0.62, 0.958).

Conclusions

Compliance with AKI CB was associated with a decrease in case-fatality and reduced progression to higher AKI stage. Further interventions are required to improve utilization of the CB.

Maximising Acute Kidney Injury Alerts--A Cross-Sectional Comparison with the Clinical Diagnosis

BACKGROUND

Acute kidney injury (AKI) is serious and widespread across healthcare (1 in 7 hospital admissions) but recognition is often delayed causing avoidable harm. Nationwide automated biochemistry alerts for AKI stages 1-3 have been introduced in England to improve recognition. We explored how these alerts compared with clinical diagnosis in different hospital settings.

METHODS

We used a large population cohort of 4464 patients with renal impairment. Each patient had case-note review by a nephrologist, using RIFLE criteria to diagnose AKI and chronic kidney disease (CKD). We identified and staged AKI alerts using the new national NHS England AKI algorithm and compared this with nephrologist diagnosis across hospital settings.

RESULTS

Of 4464 patients, 525 had RIFLE AKI, 449 had mild AKI, 2185 had CKD (without AKI) and 1305 were of uncertain chronicity. NHS AKI algorithm criteria alerted for 90.5% of RIFLE AKI, 72.4% of mild AKI, 34.1% of uncertain cases and 14.0% of patients who actually had CKD.The algorithm identified AKI particularly well in intensive care (95.5%) and nephrology (94.6%), but less well on surgical wards (86.4%). Restricting the algorithm to stage 2 and 3 alerts reduced the over-diagnosis of AKI in CKD patients from 14.0% to 2.1%, but missed or delayed alerts in two-thirds of RIFLE AKI patients.

CONCLUSION

Automated AKI detection performed well across hospital settings, but was less sensitive on surgical wards. Clinicians should be mindful that restricting alerts to stages 2-3 may identify fewer CKD patients, but including stage 1 provides more sensitive and timely alerting.

[Electronic alerts for acute kidney injury: Opportunities and limits]

BACKGROUND

Acute kidney injury (previously: acute renal failure) is a frequent disorder of hospitalized patients with serious complications contributing to worse prognosis as seen in patients with acute myocardial infarction. Acute kidney injury carries a high economic health burden. Early diagnosis and treatment and outpatient care may avoid complications such as development or progression of chronic kidney disease.

OBJECTIVES

The opportunities and limits of electronic alert systems for acute kidney injury were evaluated.

MATERIALS AND METHODS

Narrative review.

RESULTS

In accordance with the literature, more than 95% of affected patients are treated by nonrenal specialties. Results from such systems established in the UK are promising. Patients with acute kidney injury are reliably and early detected by electronic alert systems. Quality of care is improved by hospital-wide electronic alert systems for acute kidney injury. Also, early initiated treatment seems to contribute to favorable patient-related outcome and to reduce mortality.

CONCLUSIONS

Implementation of hospital-wide electronic alert systems for acute kidney injury should be seriously considered.

The effects of acute kidney injury on long-term renal function and proteinuria in a general hospitalised population

BACKGROUND

Acute kidney injury (AKI) is common in hospitalised patients and is associated with adverse long-term consequences. There is an urgent need to understand these sequelae in general hospitalised patients utilising a prospective cohort-based approach. We aimed to test the feasibility of study methodology prior to commencing a large-scale study and investigate the effects of AKI on chronic kidney disease (CKD) progression and proteinuria.

METHODS

Pilot study testing novel methodology for remote patient recruitment within a prospective case-control design. 300 cases (hospitalised patients with AKI) and controls (hospitalised patients without AKI) were matched 1:1 for age and baseline estimated glomerular filtration rate (eGFR). 70% of cases had AKI stage 1, 16% AKI stage 2 and 14% AKI stage 3. Renal function and proteinuria were measured 3 and 12 months after hospital admission.

RESULTS

The study met pre-defined recruitment, withdrawal and matching criteria. Renal function was worse in the AKI group at 3 (eGFR 61 ± 20 vs. 74 ± 23 ml/min/1.73 m(2), p < 0.001) and 12 months (eGFR 64 ± 23 vs. 75 ± 25 ml/min/1.73 m(2), p < 0.001). More cases than controls had CKD progression at 3 months (14 vs. 0.7%, p < 0.001). This difference persisted to 12 months, but there was no significant change between 3 and 12 months. Proteinuria and albuminuria were more prevalent in the AKI group and associated with CKD progression.

CONCLUSIONS

We describe a method of remote patient recruitment which could be employed more widely for prospective observational studies. Even mild AKI is associated with long-term renal dysfunction. Further investigation using this methodology is now underway.

Multicentre study of investigation and management of inpatient hyponatraemia in the UK

Purpose

Hyponatraemia is associated with significant morbidity and mortality. The objectives of this study were to evaluate the investigation and management of hyponatraemia and to assess the use of different therapeutic modalities and their effectiveness in routine practice.

Study design

This multicentre, retrospective, observational study was conducted at three acute NHS Trusts in March 2013. A retrospective chart review was performed on the first 100 inpatients with serum sodium (sNa) ≤128 mmol/L during hospitalisation.

Results

One hundred patients (47 male, 53 female) with a mean±SD age of 71.3±15.4 years and nadir sNa of 123.4±4.3 mmol/L were included. Only 23/100 (23%) had measurements of paired serum and urine osmolality and sodium, while 31% had an assessment of adrenal reserve. The aetiology of hyponatraemia was unrecorded in 58% of cases. The mean length of hospital stay was 17.5 days with an inpatient mortality rate of 16%. At hospital discharge, 53/84 (63.1%) patients had persistent hyponatraemia, including 20/84 (23.8%) with sNa <130 mmol/L. Overall 37/100 (37%) patients did not have any treatment for hyponatraemia. Among 76 therapeutic episodes, the most commonly used treatment modalities were isotonic saline in 38/76 cases (50%) and fluid restriction in 16/76 (21.1%). Fluid restriction failed to increase sNa by >1 mmol/L/day in 8/10 (80%) cases compared with 4/26 (15.4%) for isotonic saline.

Conclusions

Underinvestigation and undertreatment of hyponatraemia is a common occurrence in UK clinical practice. Therefore, development of UK guidelines and introduction of electronic alerts for hyponatraemia should be considered to improve clinical practice.