Allison McCoy
Tulane University, Biostatistics and Bioinformatics, Faculty Member
Abstract The utilization of clinical decision support (CDS) is increasing among healthcare facilities that have implemented computerized physician order entry or electronic medical records. Formal prospective evaluation of CDS... more
Abstract The utilization of clinical decision support (CDS) is increasing among healthcare facilities that have implemented computerized physician order entry or electronic medical records. Formal prospective evaluation of CDS implementations rarely occurs, and misuse or flaws in system design are often not recognized or corrected. Through retrospective nephrologist adjudication of acute kidney injury (AKI) CDS alerts, we identified patient and knowledgebase factors that contributed to inappropriate, or false positive, alerts.
Clinical decision support systems can decrease common errors related to inappropriate or excessive dosing for nephrotoxic or renally cleared drugs. We developed a comprehensive medication safety intervention with varying levels of... more
Clinical decision support systems can decrease common errors related to inappropriate or excessive dosing for nephrotoxic or renally cleared drugs. We developed a comprehensive medication safety intervention with varying levels of workflow intrusiveness within computerized provider order entry to continuously monitor for and alert providers about early-onset acute kidney injury.
Abstract Increased amounts of data contained in electronic health records (EHRs) has led to inefficiencies for clinicians trying to locate relevant patient information. Automated summarization tools that create condition-specific data... more
Abstract Increased amounts of data contained in electronic health records (EHRs) has led to inefficiencies for clinicians trying to locate relevant patient information. Automated summarization tools that create condition-specific data displays rather than current displays by data type have the potential to greatly improve clinician efficiency. These tools require new kinds of clinical knowledge (eg, problem-medication relationships) that is difficult to obtain.
OBJECTIVE: To quantify the percentage of records with matching identifiers as an indicator for duplicate or potentially duplicate patient records in electronic health records in five different healthcare organisations, describe the... more
OBJECTIVE: To quantify the percentage of records with matching identifiers as an indicator for duplicate or potentially duplicate patient records in electronic health records in five different healthcare organisations, describe the patient safety issues that may arise, and present solutions for managing duplicate records or records with matching identifiers.
METHODS: For each institution, we retrieved deidentified counts of records with an exact match of patient first and last names and dates of birth and determined the number of patient records existing for the top 250 most frequently occurring first and last name pairs. We also identified methods for managing duplicate records or records with matching identifiers, reporting the adoption rate of each across institutions.
RESULTS: The occurrence of matching first and last name in two or more individuals ranged from 16.49% to 40.66% of records; inclusion of date of birth reduced the rates to range from 0.16% to 15.47%. The number of records existing for the most frequently occurring name at each site ranged from 41 to 2552. Institutions varied widely in the methods they implemented for preventing, detecting and removing duplicate records, and mitigating resulting errors.
CONCLUSIONS: The percentage of records having matching patient identifiers is high in several organisations, indicating that the rate of duplicate records or records may also be high. Further efforts are necessary to improve management of duplicate records or records with matching identifiers and minimise the risk for patient harm.
METHODS: For each institution, we retrieved deidentified counts of records with an exact match of patient first and last names and dates of birth and determined the number of patient records existing for the top 250 most frequently occurring first and last name pairs. We also identified methods for managing duplicate records or records with matching identifiers, reporting the adoption rate of each across institutions.
RESULTS: The occurrence of matching first and last name in two or more individuals ranged from 16.49% to 40.66% of records; inclusion of date of birth reduced the rates to range from 0.16% to 15.47%. The number of records existing for the most frequently occurring name at each site ranged from 41 to 2552. Institutions varied widely in the methods they implemented for preventing, detecting and removing duplicate records, and mitigating resulting errors.
CONCLUSIONS: The percentage of records having matching patient identifiers is high in several organisations, indicating that the rate of duplicate records or records may also be high. Further efforts are necessary to improve management of duplicate records or records with matching identifiers and minimise the risk for patient harm.
Research Interests:
Bar coded medication administration (BCMA), the automated electronic verification of medications by nurses at the patient bedside, provides an additional layer of safety to the process of medication administration in the hospital setting.... more
Bar coded medication administration (BCMA), the automated electronic verification of medications by nurses at the patient bedside, provides an additional layer of safety to the process of medication administration in the hospital setting. We performed a retrospective, descriptive study of BCMA alerts for elevated potassium (>5.5 mg/dL) in place within a multihospital healthcare system. Overall, 642 BCMA alerts were analyzed with a 21.3% acceptance rate. In subgroup analysis, we found that the BCMA acceptance rate was 6.9% for patients aged less than one year, and 85.6% for patients aged greater than one year. The major contributing factor to the low overall acceptance rate was the high frequency of alerts in patients less than 1 year of age. Modifications to rules logic may be necessary for this specific population. While BCMA alerts can beneficial, they should be carefully implemented with periodic post-implementation analysis and refinement.
OBJECTIVE: To try to lower patient re-identification risks for biomedical research databases containing laboratory test results while also minimizing changes in clinical data interpretation. MATERIALS AND METHODS: In our threat model, an... more
OBJECTIVE: To try to lower patient re-identification risks for biomedical research databases containing laboratory test results while also minimizing changes in clinical data interpretation.
MATERIALS AND METHODS: In our threat model, an attacker obtains 5-7 laboratory results from one patient and uses them as a search key to discover the corresponding record in a de-identified biomedical research database. To test our models, the existing Vanderbilt TIME database of 8.5 million Safe Harbor de-identified laboratory results from 61 280 patients was used. The uniqueness of unaltered laboratory results in the dataset was examined, and then two data perturbation models were applied-simple random offsets and an expert-derived clinical meaning-preserving model. A rank-based re-identification algorithm to mimic an attack was used. The re-identification risk and the retention of clinical meaning for each model's perturbed laboratory results were assessed.
RESULTS: Differences in re-identification rates between the algorithms were small despite substantial divergence in altered clinical meaning. The expert algorithm maintained the clinical meaning of laboratory results better (affecting up to 4% of test results) than simple perturbation (affecting up to 26%).
DISCUSSION AND CONCLUSION: With growing impetus for sharing clinical data for research, and in view of healthcare-related federal privacy regulation, methods to mitigate risks of re-identification are important. A practical, expert-derived perturbation algorithm that demonstrated potential utility was developed. Similar approaches might enable administrators to select data protection scheme parameters that meet their preferences in the trade-off between the protection of privacy and the retention of clinical meaning of shared data.
MATERIALS AND METHODS: In our threat model, an attacker obtains 5-7 laboratory results from one patient and uses them as a search key to discover the corresponding record in a de-identified biomedical research database. To test our models, the existing Vanderbilt TIME database of 8.5 million Safe Harbor de-identified laboratory results from 61 280 patients was used. The uniqueness of unaltered laboratory results in the dataset was examined, and then two data perturbation models were applied-simple random offsets and an expert-derived clinical meaning-preserving model. A rank-based re-identification algorithm to mimic an attack was used. The re-identification risk and the retention of clinical meaning for each model's perturbed laboratory results were assessed.
RESULTS: Differences in re-identification rates between the algorithms were small despite substantial divergence in altered clinical meaning. The expert algorithm maintained the clinical meaning of laboratory results better (affecting up to 4% of test results) than simple perturbation (affecting up to 26%).
DISCUSSION AND CONCLUSION: With growing impetus for sharing clinical data for research, and in view of healthcare-related federal privacy regulation, methods to mitigate risks of re-identification are important. A practical, expert-derived perturbation algorithm that demonstrated potential utility was developed. Similar approaches might enable administrators to select data protection scheme parameters that meet their preferences in the trade-off between the protection of privacy and the retention of clinical meaning of shared data.
Objective: We describe a novel, crowdsourcing method for generating a knowledge base of problem-medication pairs that takes advantage of manually asserted links between medications and problems. Methods:Through iterative review, we... more
Objective: We describe a novel, crowdsourcing method for generating a knowledge base of problem-medication pairs that takes advantage of manually asserted links between medications and problems.
Methods:Through iterative review, we developed metrics to estimate the appropriateness of manually entered problem-medication links for inclusion in a knowledge base that can be used to infer previously unasserted links between problems and medications.
Results: Clinicians manually linked 231 223 medications (55.30% of prescribed medications) to problems within the electronic health record, generating 41 203 distinct problem-medication pairs, although not all were accurate. We developed methods to evaluate the accuracy of the pairs, and after limiting the pairs to those meeting an estimated 95% appropriateness threshold, 11 166 pairs remained. The pairs in the knowledge base accounted for 183 127 total links asserted (76.47% of all links). Retrospective application of the knowledge base linked 68 316 medications not previously linked by a clinician to an indicated problem (36.53% of unlinked medications). Expert review of the combined knowledge base, including inferred and manually linked problem-medication pairs, found a sensitivity of 65.8% and a specificity of 97.9%.
Conclusion: Crowdsourcing is an effective, inexpensive method for generating a knowledge base of problem-medication pairs that is automatically mapped to local terminologies, up-to-date, and reflective of local prescribing practices and trends.
Methods:Through iterative review, we developed metrics to estimate the appropriateness of manually entered problem-medication links for inclusion in a knowledge base that can be used to infer previously unasserted links between problems and medications.
Results: Clinicians manually linked 231 223 medications (55.30% of prescribed medications) to problems within the electronic health record, generating 41 203 distinct problem-medication pairs, although not all were accurate. We developed methods to evaluate the accuracy of the pairs, and after limiting the pairs to those meeting an estimated 95% appropriateness threshold, 11 166 pairs remained. The pairs in the knowledge base accounted for 183 127 total links asserted (76.47% of all links). Retrospective application of the knowledge base linked 68 316 medications not previously linked by a clinician to an indicated problem (36.53% of unlinked medications). Expert review of the combined knowledge base, including inferred and manually linked problem-medication pairs, found a sensitivity of 65.8% and a specificity of 97.9%.
Conclusion: Crowdsourcing is an effective, inexpensive method for generating a knowledge base of problem-medication pairs that is automatically mapped to local terminologies, up-to-date, and reflective of local prescribing practices and trends.
Research Interests: Medical Informatics, Knowledge Management, Collective Intelligence, Methodology, Health Informatics, and 10 moreHealth Information Systems, Electronic Medical Records, Electronic Health Records, Biomedical informatics, Open Innovation, Crowdsourcing, Biomedical Informatics (Informatics), Health Information Technology, Open science, and Clinical Informatics
OBJECTIVES: Clinical decision support (CDS), such as computerized alerts, improves prescribing in the setting of acute kidney injury (AKI), but considerable opportunity remains to improve patient safety. The authors sought to determine... more
OBJECTIVES: Clinical decision support (CDS), such as computerized alerts, improves prescribing in the setting of acute kidney injury (AKI), but considerable opportunity remains to improve patient safety. The authors sought to determine whether pharmacy surveillance of AKI patients could detect and prevent medication errors that are not corrected by automated interventions.
METHODS: The authors conducted a randomized clinical trial among 396 patients admitted to an academic, tertiary care hospital between June 1, 2010 and August 31, 2010 with an acute 0.5 mg/dl change in serum creatinine over 48 hours and a nephrotoxic or renally cleared medication order. Patients randomly assigned to the intervention group received surveillance from a clinical pharmacist using a web-based surveillance tool to monitor drug prescribing and kidney function trends. CDS alerting and standard pharmacy services were active in both study arms. Outcome measures included blinded adjudication of potential adverse drug events (pADEs), adverse drug events (ADEs) and time to provider modification or discontinuation of targeted nephrotoxic or renally cleared medications.
RESULTS: Potential ADEs or ADEs occurred for 104 (8.0%) of control and 99 (7.1%) of intervention patient-medication pairs (p=0.4). Additionally, the time to provider modification or discontinuation of targeted nephrotoxic or renally cleared medications did not differ between control and intervention patients (33.4 hrs vs. 30.3 hrs, p=0.3).
CONCLUSIONS: Pharmacy surveillance had no incremental benefit over previously implemented CDS alerts.
METHODS: The authors conducted a randomized clinical trial among 396 patients admitted to an academic, tertiary care hospital between June 1, 2010 and August 31, 2010 with an acute 0.5 mg/dl change in serum creatinine over 48 hours and a nephrotoxic or renally cleared medication order. Patients randomly assigned to the intervention group received surveillance from a clinical pharmacist using a web-based surveillance tool to monitor drug prescribing and kidney function trends. CDS alerting and standard pharmacy services were active in both study arms. Outcome measures included blinded adjudication of potential adverse drug events (pADEs), adverse drug events (ADEs) and time to provider modification or discontinuation of targeted nephrotoxic or renally cleared medications.
RESULTS: Potential ADEs or ADEs occurred for 104 (8.0%) of control and 99 (7.1%) of intervention patient-medication pairs (p=0.4). Additionally, the time to provider modification or discontinuation of targeted nephrotoxic or renally cleared medications did not differ between control and intervention patients (33.4 hrs vs. 30.3 hrs, p=0.3).
CONCLUSIONS: Pharmacy surveillance had no incremental benefit over previously implemented CDS alerts.
OBJECTIVE: Clinical summarization, the process by which relevant patient information is electronically summarized and presented at the point of care, is of increasing importance given the increasing volume of clinical data in electronic... more
OBJECTIVE: Clinical summarization, the process by which relevant patient information is electronically summarized and presented at the point of care, is of increasing importance given the increasing volume of clinical data in electronic health record systems (EHRs). There is a paucity of research on electronic clinical summarization, including the capabilities of currently available EHR systems.
METHODS: We compared different aspects of general clinical summary screens used in twelve different EHR systems using a previously described conceptual model: AORTIS (Aggregation, Organization, Reduction, Interpretation and Synthesis).
RESULTS: We found a wide variation in the EHRs' summarization capabilities: all systems were capable of simple aggregation and organization of limited clinical content, but only one demonstrated an ability to synthesize information from the data.
CONCLUSION: Improvement of the clinical summary screen functionality for currently available EHRs is necessary. Further research should identify strategies and methods for creating easy to use, well-designed clinical summary screens that aggregate, organize and reduce all pertinent patient information as well as provide clinical interpretations and synthesis as required.
METHODS: We compared different aspects of general clinical summary screens used in twelve different EHR systems using a previously described conceptual model: AORTIS (Aggregation, Organization, Reduction, Interpretation and Synthesis).
RESULTS: We found a wide variation in the EHRs' summarization capabilities: all systems were capable of simple aggregation and organization of limited clinical content, but only one demonstrated an ability to synthesize information from the data.
CONCLUSION: Improvement of the clinical summary screen functionality for currently available EHRs is necessary. Further research should identify strategies and methods for creating easy to use, well-designed clinical summary screens that aggregate, organize and reduce all pertinent patient information as well as provide clinical interpretations and synthesis as required.
Research Interests:
Increasing use of electronic health records requires comprehensive patient-centered views of clinical data. We describe a prototype knowledge base and SMART app that facilitates organization of patient medications by clinical problems,... more
Increasing use of electronic health records requires comprehensive patient-centered views of clinical data. We describe a prototype knowledge base and SMART app that facilitates organization of patient medications by clinical problems, comprising a preliminary step in building such patient-centered views. The knowledge base includes 7,164,444 distinct problem-medication links, generated from RxNorm, SNOMED CT, and NDF-RT within the UMLS Metathesaurus. In an evaluation of the knowledge base applied to 5000 de-identified patient records, 22.4% of medications linked to an entry in the patient’s active problem list, compared to 32.6% of medications manually linked by providers; 46.5% of total links were unique to the knowledge base, not added by providers. Expert review of a random patient subset estimated a sensitivity of 37.1% and specificity of 98.9%. The SMART API successfully utilized the knowledge base to generate problem-medication links for test patients. Future work is necessary to improve knowledge base sensitivity and efficiency.
Research Interests:
Research Interests:
Inference of patient problems from medications using clinical indication relationships from NDF-RT and usage frequency from the SNOMED-CT CORE problem list subset may contribute to automated methods for summarizing large, complex patient... more
Inference of patient problems from medications using clinical indication relationships from NDF-RT and usage frequency from the SNOMED-CT CORE problem list subset may contribute to automated methods for summarizing large, complex patient records. Manual review of inferred problems found reasonable rates of matching problem list entries (61.8% total, 32.5% exact) and frequently relevant undocumented problems (62%).
Research Interests:
Research Interests:
"BACKGROUND: High-alert medications are frequently responsible for adverse drug events and present significant hazards to inpatients, despite technical improvements in the way they are ordered, dispensed, and administered. METHODS: A... more
"BACKGROUND: High-alert medications are frequently responsible for adverse drug events and present significant hazards to inpatients, despite technical improvements in the way they are ordered, dispensed, and administered.
METHODS: A real-time surveillance application was designed and implemented to enable pharmacy review of high-alert medication orders to complement existing computerized provider order entry and integrated clinical decision support systems in a tertiary care hospital. The surveillance tool integrated real-time data from multiple clinical systems and applied logical criteria to highlight potentially high-risk scenarios. Use of the surveillance system for adult inpatients was analyzed for warfarin, heparin and enoxaparin, and aminoglycoside antibiotics.
RESULTS: Among 28,929 hospitalizations during the study period, patients eligible to appear on a dashboard included 2224 exposed to warfarin, 8383 to heparin or enoxaparin, and 893 to aminoglycosides. Clinical pharmacists reviewed the warfarin and aminoglycoside dashboards during 100% of the days in the study period-and the heparinlenoxaparin dashboard during 71% of the days. Displayed alert conditions ranged from common events, such as 55% of patients receiving aminoglycosides were missing a baseline creatinine, to rare events, such as 0.1% of patients exposed to heparin were given a bolus greater than 10,000 units. On the basis of interpharmacist communication and electronic medical record notes recorded within the dashboards, interventions to prevent further patient harm were frequent.
CONCLUSIONS: Even in an environment with sophisticated computerized provider order entry and clinical decision support systems, real-time pharmacy surveillance of high-alert medications provides an important platform for intercepting medication errors and optimizing therapy."
METHODS: A real-time surveillance application was designed and implemented to enable pharmacy review of high-alert medication orders to complement existing computerized provider order entry and integrated clinical decision support systems in a tertiary care hospital. The surveillance tool integrated real-time data from multiple clinical systems and applied logical criteria to highlight potentially high-risk scenarios. Use of the surveillance system for adult inpatients was analyzed for warfarin, heparin and enoxaparin, and aminoglycoside antibiotics.
RESULTS: Among 28,929 hospitalizations during the study period, patients eligible to appear on a dashboard included 2224 exposed to warfarin, 8383 to heparin or enoxaparin, and 893 to aminoglycosides. Clinical pharmacists reviewed the warfarin and aminoglycoside dashboards during 100% of the days in the study period-and the heparinlenoxaparin dashboard during 71% of the days. Displayed alert conditions ranged from common events, such as 55% of patients receiving aminoglycosides were missing a baseline creatinine, to rare events, such as 0.1% of patients exposed to heparin were given a bolus greater than 10,000 units. On the basis of interpharmacist communication and electronic medical record notes recorded within the dashboards, interventions to prevent further patient harm were frequent.
CONCLUSIONS: Even in an environment with sophisticated computerized provider order entry and clinical decision support systems, real-time pharmacy surveillance of high-alert medications provides an important platform for intercepting medication errors and optimizing therapy."
Research Interests: Pharmacy, Patient Safety, Health Informatics, Health Information Systems, Electronic Medical Records, and 8 moreElectronic Health Records, Biomedical informatics, Pharmacy Informatics, Biomedical Informatics (Informatics), Health Information Technology, Medication Safety, Clinical Informatics, and Clinical Decision Support
Objective: Alerting systems, a type of clinical decision support (CDS), are increasingly prevalent in healthcare, yet few studies have concurrently measured the appropriateness of alerts with provider responses to alerts. Recent reports... more
Objective: Alerting systems, a type of clinical decision support (CDS), are increasingly prevalent in healthcare, yet few studies have concurrently measured the appropriateness of alerts with provider responses to alerts. Recent reports of suboptimal alert system design and implementation highlight the need for better evaluation to inform future designs. The authors present a comprehensive framework for evaluating the clinical appropriateness of synchronous, interruptive medication safety alerts.
Methods: Through literature review and iterative testing, we developed metrics that describe successes, justifiable overrides, provider non-adherence, and unintended adverse consequences of CDS alerts. We validated the framework by applying it to a medication alerting system for patients with acute kidney injury (AKI).
Results: Through expert review, the framework assesses each alert episode for appropriateness of the alert display and the necessity and urgency of a clinical response. Primary outcomes of the framework include the false positive alert rate, alert override rate, provider non-adherence rate, and rate of provider response appropriateness. Application of the framework to evaluate an existing AKI medication alerting system provided a more complete understanding of the process outcomes measured in the AKI medication alerting system. We confirmed that previous alerts and provider responses were most often appropriate.
Conclusion: The new evaluation model offers a potentially effective method to assess the clinical appropriateness of synchronous interruptive medication alerts prior to evaluating patient outcomes in a comparative trial. More work can determine the generalizability of the framework for use in other settings and other alert types.
Methods: Through literature review and iterative testing, we developed metrics that describe successes, justifiable overrides, provider non-adherence, and unintended adverse consequences of CDS alerts. We validated the framework by applying it to a medication alerting system for patients with acute kidney injury (AKI).
Results: Through expert review, the framework assesses each alert episode for appropriateness of the alert display and the necessity and urgency of a clinical response. Primary outcomes of the framework include the false positive alert rate, alert override rate, provider non-adherence rate, and rate of provider response appropriateness. Application of the framework to evaluate an existing AKI medication alerting system provided a more complete understanding of the process outcomes measured in the AKI medication alerting system. We confirmed that previous alerts and provider responses were most often appropriate.
Conclusion: The new evaluation model offers a potentially effective method to assess the clinical appropriateness of synchronous interruptive medication alerts prior to evaluating patient outcomes in a comparative trial. More work can determine the generalizability of the framework for use in other settings and other alert types.
Research Interests: Research Methods and Methodology, Research Methodology, Evaluation Research, Measurement and Evaluation, Health Information Systems, and 7 moreElectronic Medical Records, Biomedical informatics, Biomedical Informatics (Informatics), Health Information Technology, Clinical Informatics, Clinical Decision Support, and Computerized Provider Order Entry
Outcomes assessment for intervention studies requires blinding of reviewers to prevent bias. We used Mozilla Firefox and the Greasemonkey Add-on to remove notes generated for intervention patients during a randomized controlled trial to... more
Outcomes assessment for intervention studies requires blinding of reviewers to prevent bias. We used Mozilla Firefox and the Greasemonkey Add-on to remove notes generated for intervention patients during a randomized controlled trial to ensure blinding during electronic chart review. Similar methods could be employed with other web-based electronic medical records.
Research Interests: Web 2.0, Health Informatics, Web Technologies, Health Information Systems, Randomized Evaluation, and 8 moreElectronic Medical Records, Health And Clinical Research, Biomedical informatics, Biomedical Informatics (Informatics), Clinical research, Randomized Controlled Trials, Clinical Informatics, and Clinical Decision Support
Background: Effective teaching of evidence-based medicine (EBM) to medical students is important for lifelong self-directed learning. Aims: We implemented a brief workshop designed to teach literature searching skills to third-year... more
Background: Effective teaching of evidence-based medicine (EBM) to medical students is important for lifelong self-directed learning. Aims: We implemented a brief workshop designed to teach literature searching skills to third-year medical students. We assessed its impact on students' utilization of EBM resources during their clinical rotation and the quality of EBM integration in inpatient notes. Methods: We developed a physician-led, hands-on workshop to introduce EBM resources to all internal medicine clerks. Pre- and post-workshop measures included student's attitudes to EBM, citations of EBM resources in their clinical notes, and quality of the EBM component of the discussion in the note. Computer log analysis recorded students' online search attempts. Results: After the workshop, students reported improved comfort using EBM and increased utilization of EBM resources. EBM integration into the discussion component of the notes also showed significant improvement. Computer log analysis of students' searches demonstrated increased utilization of EBM resources following the workshop. Conclusions: We describe the successful implementation of a workshop designed to teach third-year medical students how to perform an efficient EBM literature search. We demonstrated improvements in students' confidence regarding EBM, increased utilization of EBM resources, and improved integration of EBM into inpatient notes.
Research Interests:
"BACKGROUND: Frequently, prescribers fail to account for changing kidney function when prescribing medications. We evaluated the use of a computerized provider order entry intervention to improve medication management during acute kidney... more
"BACKGROUND: Frequently, prescribers fail to account for changing kidney function when prescribing medications. We evaluated the use of a computerized provider order entry intervention to improve medication management during acute kidney injury.
STUDY DESIGN: Quality improvement report with time series analyses.
SETTING & PARTICIPANTS: 1,598 adult inpatients with a minimum 0.5-mg/dL increase in serum creatinine level over 48 hours after an order for at least one of 122 nephrotoxic or renally cleared medications. QUALITY IMPROVEMENT PLAN: Passive noninteractive warnings about increasing serum creatinine level appeared within the computerized provider order entry interface and on printed rounding reports. For contraindicated or high-toxicity medications that should be avoided or adjusted, an interruptive alert within the system asked providers to modify or discontinue the targeted orders, mark the current dosing as correct and to remain unchanged, or defer the alert to reappear in the next session.
OUTCOMES & MEASUREMENTS: Intervention effect on drug modification or discontinuation, time to modification or discontinuation, and provider interactions with alerts.
RESULTS: The modification or discontinuation rate per 100 events for medications included in the interruptive alert within 24 hours of increasing creatinine level improved from 35.2 preintervention to 52.6 postintervention (P < 0.001); orders were modified or discontinued more quickly (P < 0.001). During the postintervention period, providers initially deferred 78.1% of interruptive alerts, although 54% of these eventually were modified or discontinued before patient death, discharge, or transfer. The response to passive alerts about medications requiring review did not significantly change compared with baseline.
LIMITATIONS: Single tertiary-care academic medical center; provider actions were not independently adjudicated for appropriateness.
CONCLUSIONS: A computerized provider order entry-based alerting system to support medication management after acute kidney injury significantly increased the rate and timeliness of modification or discontinuation of targeted medications."
STUDY DESIGN: Quality improvement report with time series analyses.
SETTING & PARTICIPANTS: 1,598 adult inpatients with a minimum 0.5-mg/dL increase in serum creatinine level over 48 hours after an order for at least one of 122 nephrotoxic or renally cleared medications. QUALITY IMPROVEMENT PLAN: Passive noninteractive warnings about increasing serum creatinine level appeared within the computerized provider order entry interface and on printed rounding reports. For contraindicated or high-toxicity medications that should be avoided or adjusted, an interruptive alert within the system asked providers to modify or discontinue the targeted orders, mark the current dosing as correct and to remain unchanged, or defer the alert to reappear in the next session.
OUTCOMES & MEASUREMENTS: Intervention effect on drug modification or discontinuation, time to modification or discontinuation, and provider interactions with alerts.
RESULTS: The modification or discontinuation rate per 100 events for medications included in the interruptive alert within 24 hours of increasing creatinine level improved from 35.2 preintervention to 52.6 postintervention (P < 0.001); orders were modified or discontinued more quickly (P < 0.001). During the postintervention period, providers initially deferred 78.1% of interruptive alerts, although 54% of these eventually were modified or discontinued before patient death, discharge, or transfer. The response to passive alerts about medications requiring review did not significantly change compared with baseline.
LIMITATIONS: Single tertiary-care academic medical center; provider actions were not independently adjudicated for appropriateness.
CONCLUSIONS: A computerized provider order entry-based alerting system to support medication management after acute kidney injury significantly increased the rate and timeliness of modification or discontinuation of targeted medications."
Research Interests:
Clinical decision support systems can decrease common errors related to inappropriate or excessive dosing for nephrotoxic or renally cleared drugs. We developed a comprehensive medication safety intervention with varying levels of... more
Clinical decision support systems can decrease common errors related to inappropriate or excessive dosing for nephrotoxic or renally cleared drugs. We developed a comprehensive medication safety intervention with varying levels of workflow intrusiveness within computerized provider order entry to continuously monitor for and alert providers about early-onset acute kidney injury. Initial provider response to the interventions shows potential success in improving medication safety and suggests future enhancements to increase effectiveness.