Effects of an online personal health record on medication accuracy and safety: a cluster-randomized trial

Objective

To determine the effects of a personal health record (PHR)-linked medications module on medication accuracy and safety.

Design

From September 2005 to March 2007, we conducted an on-treatment sub-study within a cluster-randomized trial involving 11 primary care practices that used the same PHR. Intervention practices received access to a medications module prompting patients to review their documented medications and identify discrepancies, generating ‘eJournals’ that enabled rapid updating of medication lists during subsequent clinical visits.

Measurements

A sample of 267 patients who submitted medications eJournals was contacted by phone 3 weeks after an eligible visit and compared with a matched sample of 274 patients in control practices that received a different PHR-linked intervention. Two blinded physician adjudicators determined unexplained discrepancies between documented and patient-reported medication regimens. The primary outcome was proportion of medications per patient with unexplained discrepancies.

Results

Among 121 046 patients in eligible practices, 3979 participated in the main trial and 541 participated in the sub-study. The proportion of medications per patient with unexplained discrepancies was 42% in the intervention arm and 51% in the control arm (adjusted OR 0.71, 95% CI 0.54 to 0.94, p=0.01). The number of unexplained discrepancies per patient with potential for severe harm was 0.03 in the intervention arm and 0.08 in the control arm (adjusted RR 0.31, 95% CI 0.10 to 0.92, p=0.04).

Conclusions

When used, concordance between documented and patient-reported medication regimens and reduction in potentially harmful medication discrepancies can be improved with a PHR medication review tool linked to the provider''s medical record.

Trial registration number

This study was registered at ClinicalTrials.gov ({"type":"clinical-trial","attrs":{"text":"NCT00251875","term_id":"NCT00251875"}}NCT00251875).     

The effectiveness of a new generation of computerized drug alerts in reducing the risk of injury from drug side effects: a cluster randomized trial

Context

Computerized drug alerts for psychotropic drugs are expected to reduce fall-related injuries in older adults. However, physicians over-ride most alerts because they believe the benefit of the drugs exceeds the risk.

Objective

To determine whether computerized prescribing decision support with patient-specific risk estimates would increase physician response to psychotropic drug alerts and reduce injury risk in older people.

Design

Cluster randomized controlled trial of 81 family physicians and 5628 of their patients aged 65 and older who were prescribed psychotropic medication.

Intervention

Intervention physicians received information about patient-specific risk of injury computed at the time of each visit using statistical models of non-modifiable risk factors and psychotropic drug doses. Risk thermometers presented changes in absolute and relative risk with each change in drug treatment. Control physicians received commercial drug alerts.

Main outcome measures

Injury risk at the end of follow-up based on psychotropic drug doses and non-modifiable risk factors. Electronic health records and provincial insurance administrative data were used to measure outcomes.

Results

Mean patient age was 75.2 years. Baseline risk of injury was 3.94 per 100 patients per year. Intermediate-acting benzodiazepines (56.2%) were the most common psychotropic drug. Intervention physicians reviewed therapy in 83.3% of visits and modified therapy in 24.6%. The intervention reduced the risk of injury by 1.7 injuries per 1000 patients (95% CI 0.2/1000 to 3.2/1000; p=0.02). The effect of the intervention was greater for patients with higher baseline risks of injury (p<0.03).

Conclusion

Patient-specific risk estimates provide an effective method of reducing the risk of injury for high-risk older people.

Trial registration number

clinicaltrials.gov Identifier: NCT00818285.     

Impact of iron supplementation on schistosomiasis control in Zambian school children in a highly endemic area

Aim

To study impact of once weekly iron supplementation on praziquantel cure rate, Schistosoma haematobium reinfection, and haematological parameters in pupils aged between 9 and 15 years of age in Nchelenge district, Zambia.

Methods

Pupils in the intervention group received once weekly dose of ferrous sulphate at 200mg while those in the control received once weekly vitamin C at 100mg for up to 9 months. Both study groups received a single dose of praziquantel at baseline.

Results

S haematobium reinfection intensity was significantly lower in boys in the intervention group than in boys in the control group at 6 months (P<0.001) and 9 months (P<0.001) of supplementation. Significantly lower S haematobium reinfection intensity was found in girls in the intervention group than in girls in the control group only at 6 months of supplementation (P=0.018). Boys in the intervention group were 42% (Adjusted Risk Ratio =0.58, 95% confidence interval 0.39, 0.86) less likely to be reinfected with S haematobium than in the control group at 6 months follow up.

Conclusion

Once weekly iron supplementation can decrease S haematobium reinfection after 6 months and should be incorporated into school based schistosomiasis control programs in highly endemic areas.

Clinical trials.gov identifier

{"type":"clinical-trial","attrs":{"text":"NCT 00276224","term_id":"NCT00276224"}}NCT 00276224, sponsored by DBL-Institute for Health Research and Development, Denmark.     

Personal health records and hypertension control: a randomized trial

Purpose

To examine the impact of a personal health record (PHR) in patients with hypertension measured by changes in biological outcomes, patient empowerment, patient perception of quality of care, and use of medical services.

Methods

A cluster-randomized effectiveness trial with PHR and no PHR groups was conducted in two ambulatory clinics. 453 of 1686 (26.4%) patients approached were included in the analyses. A PHR tethered to the patient''s electronic medical record (EMR) was the primary intervention and included security measures, patient control of access, limited transmission of EMR data, blood pressure (BP) tracking, and appointment assistance. BP was the main outcome measure. Patient empowerment was assessed using the Patient Activation Measure and Patient Empowerment Scale. Quality of care was assessed using the Clinician and Group Assessment Score (CAHPS) and the Patient Assessment of Chronic Illness Care. Frequency of use of medical services was self-reported.

Results

No impact of the PHR was observed on BP, patient activation, patient perceived quality, or medical utilization in the intention-to-treat analysis. Sub-analysis of intervention patients self-identified as active PHR users (25.7% of those with available information) showed a 5.25-point reduction in diastolic BP. Younger age, self-reported computer skills, and more positive provider communication ratings were associated with frequency of PHR use.

Conclusions

Few patients provided with a PHR actually used the PHR with any frequency. Thus simply providing a PHR may have limited impact on patient BP, empowerment, satisfaction with care, or use of health services without additional education or clinical intervention designed to increase PHR use.

Clinical trial registration number

http://ClinicalTrials.gov Identifier: {"type":"clinical-trial","attrs":{"text":"NCT01317537","term_id":"NCT01317537"}}NCT01317537.     

A method and knowledge base for automated inference of patient problems from structured data in an electronic medical record

Background

Accurate knowledge of a patient''s medical problems is critical for clinical decision making, quality measurement, research, billing and clinical decision support. Common structured sources of problem information include the patient problem list and billing data; however, these sources are often inaccurate or incomplete.

Objective

To develop and validate methods of automatically inferring patient problems from clinical and billing data, and to provide a knowledge base for inferring problems.

Study design and methods

We identified 17 target conditions and designed and validated a set of rules for identifying patient problems based on medications, laboratory results, billing codes, and vital signs. A panel of physicians provided input on a preliminary set of rules. Based on this input, we tested candidate rules on a sample of 100 000 patient records to assess their performance compared to gold standard manual chart review. The physician panel selected a final rule for each condition, which was validated on an independent sample of 100 000 records to assess its accuracy.

Results

Seventeen rules were developed for inferring patient problems. Analysis using a validation set of 100 000 randomly selected patients showed high sensitivity (range: 62.8–100.0%) and positive predictive value (range: 79.8–99.6%) for most rules. Overall, the inference rules performed better than using either the problem list or billing data alone.

Conclusion

We developed and validated a set of rules for inferring patient problems. These rules have a variety of applications, including clinical decision support, care improvement, augmentation of the problem list, and identification of patients for research cohorts.     

Randomized clinical trial of a customized electronic alert requiring an affirmative response compared to a control group receiving a commercial passive CPOE alert: NSAID�Cwarfarin co-prescribing as a test case

Background

Studies that have looked at the effectiveness of computerized decision support systems to prevent drug–drug interactions have reported modest results because of low response by the providers to the automated alerts.

Objective

To evaluate, within an inpatient computerized physician order entry (CPOE) system, the incremental effectiveness of an alert that required a response from the provider, intended as a stronger intervention to prevent concurrent orders of warfarin and non-steroidal anti-inflammatory drugs (NSAIDs).

Design

Randomized clinical trial of 1963 clinicians assigned to either an intervention group receiving a customized electronic alert requiring affirmative response or a control group receiving a commercially available passive alert as part of the CPOE. The study duration was 2 August 2006 to 15 December 2007.

Measurements

Alert adherence was compared between study groups.

Results

The proportion of desired ordering responses (ie, not reordering the alert-triggering drug after firing) was lower in the intervention group (114/464 (25%) customized alerts issued) than in the control group (154/560 (28%) passive alerts firing). The adjusted OR of inappropriate ordering was 1.22 (95% CI 0.69 to 2.16).

Conclusion

A customized CPOE alert that required a provider response had no effect in reducing concomitant prescribing of NSAIDs and warfarin beyond that of the commercially available passive alert received by the control group. New CPOE alerts cannot be assumed to be effective in improving prescribing, and need evaluation.     

Efficacy and Safety of Tenofovir and Lamivudine in Combination with Efavirenz in Patients Co-infected with Human Immunodeficiency Virus and Hepatitis B Virus in China

Background:

The prevalence of hepatitis B virus (HBV) infection is high among individuals infected with human immunodeficiency virus (HIV) in China. Both HIV and HBV can be treated with tenofovir disoproxil fumarate (TDF) and lamivudine (3TC), so we evaluated the safety and efficacy of combination antiretroviral therapy (ART) that included TDF, 3TC, and efavirenz (EFV) among ART-naive individuals who were co-infected with HIV and HBV.

Methods:

One hundred HIV/HBV co-infected ARV-naive individuals were started on the regimen of TDF, 3TC, and EFV, and the levels of plasma HBV DNA, HIV RNA, and biochemical evaluation related to the function of liver and kidney were analyzed.

Results:

Concerning efficacy, this study found that by week 48, the vast majority co-infected participants receiving this ART regimen had undetectable HBV DNA levels (71%) and/or HIV RNA levels (90%). Concerning safety, this study found that the median estimated glomerular filtration rate of participants decreased from baseline (109 ml·min⁻¹·1.73 m⁻²) to week 12 (104 ml·min⁻¹·1.73 m⁻²) but was almost back to baseline at week 48 (111 ml·min⁻¹·1.73 m⁻²).

Conclusion:

This combination ART regimen is safe and effective for patients with HIV/HBV co-infection.

Trial Registration:

ClinicalTrials.gov, {"type":"clinical-trial","attrs":{"text":"NCT01751555","term_id":"NCT01751555"}}NCT01751555; https://clinicaltrials.gov/ct2/show/{"type":"clinical-trial","attrs":{"text":"NCT01751555","term_id":"NCT01751555"}}NCT01751555.     

Recommending MeSH terms for annotating biomedical articles

Background

Due to the high cost of manual curation of key aspects from the scientific literature, automated methods for assisting this process are greatly desired. Here, we report a novel approach to facilitate MeSH indexing, a challenging task of assigning MeSH terms to MEDLINE citations for their archiving and retrieval.

Methods

Unlike previous methods for automatic MeSH term assignment, we reformulate the indexing task as a ranking problem such that relevant MeSH headings are ranked higher than those irrelevant ones. Specifically, for each document we retrieve 20 neighbor documents, obtain a list of MeSH main headings from neighbors, and rank the MeSH main headings using ListNet–a learning-to-rank algorithm. We trained our algorithm on 200 documents and tested on a previously used benchmark set of 200 documents and a larger dataset of 1000 documents.

Results

Tested on the benchmark dataset, our method achieved a precision of 0.390, recall of 0.712, and mean average precision (MAP) of 0.626. In comparison to the state of the art, we observe statistically significant improvements as large as 39% in MAP (p-value <0.001). Similar significant improvements were also obtained on the larger document set.

Conclusion

Experimental results show that our approach makes the most accurate MeSH predictions to date, which suggests its great potential in making a practical impact on MeSH indexing. Furthermore, as discussed the proposed learning framework is robust and can be adapted to many other similar tasks beyond MeSH indexing in the biomedical domain. All data sets are available at: http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/indexing.     

Provider management strategies of abnormal test result alerts: a cognitive task analysis

Objective

Electronic medical records (EMRs) facilitate abnormal test result communication through “alert” notifications. The aim was to evaluate how primary care providers (PCPs) manage alerts related to critical diagnostic test results on their EMR screens, and compare alert-management strategies of providers with high versus low rates of timely follow-up of results.

Design

28 PCPs from a large, tertiary care Veterans Affairs Medical Center (VAMC) were purposively sampled according to their rates of timely follow-up of alerts, determined in a previous study. Using techniques from cognitive task analysis, participants were interviewed about how and when they manage alerts, focusing on four alert-management features to filter, sort and reduce unnecessary alerts on their EMR screens.

Results

Provider knowledge of alert-management features ranged between 4% and 75%. Almost half (46%) of providers did not use any of these features, and none used more than two. Providers with higher versus lower rates of timely follow-up used the four features similarly, except one (customizing alert notifications). Providers with low rates of timely follow-up tended to manually scan the alert list and process alerts heuristically using their clinical judgment. Additionally, 46% of providers used at least one workaround strategy to manage alerts.

Conclusion

Considerable heterogeneity exists in provider use of alert-management strategies; specific strategies may be associated with lower rates of timely follow-up. Standardization of alert-management strategies including improving provider knowledge of appropriate tools in the EMR to manage alerts could reduce the lack of timely follow-up of abnormal diagnostic test results.     

Making electronic prescribing alerts more effective: scenario-based experimental study in junior doctors

Objective

Expert authorities recommend clinical decision support systems to reduce prescribing error rates, yet large numbers of insignificant on-screen alerts presented in modal dialog boxes persistently interrupt clinicians, limiting the effectiveness of these systems. This study compared the impact of modal and non-modal electronic (e-) prescribing alerts on prescribing error rates, to help inform the design of clinical decision support systems.

Design

A randomized study of 24 junior doctors each performing 30 simulated prescribing tasks in random order with a prototype e-prescribing system. Using a within-participant design, doctors were randomized to be shown one of three types of e-prescribing alert (modal, non-modal, no alert) during each prescribing task.

Measurements

The main outcome measure was prescribing error rate. Structured interviews were performed to elicit participants'' preferences for the prescribing alerts and their views on clinical decision support systems.

Results

Participants exposed to modal alerts were 11.6 times less likely to make a prescribing error than those not shown an alert (OR 11.56, 95% CI 6.00 to 22.26). Those shown a non-modal alert were 3.2 times less likely to make a prescribing error (OR 3.18, 95% CI 1.91 to 5.30) than those not shown an alert. The error rate with non-modal alerts was 3.6 times higher than with modal alerts (95% CI 1.88 to 7.04).

Conclusions

Both kinds of e-prescribing alerts significantly reduced prescribing error rates, but modal alerts were over three times more effective than non-modal alerts. This study provides new evidence about the relative effects of modal and non-modal alerts on prescribing outcomes.     

Comparison of a basic and an advanced pharmacotherapy-related clinical decision support system in a hospital care setting in the Netherlands

Objective

To compare the clinical relevance of medication alerts in a basic and in an advanced clinical decision support system (CDSS).

Design

A prospective observational study.

Materials and methods

We collected 4023 medication orders in a hospital for independent evaluation in two pharmacotherapy-related decision support systems. Only the more advanced system considered patient characteristics and laboratory test results in its algorithms. Two pharmacists assessed the clinical relevance of the medication alerts produced. The alert was considered relevant if the pharmacist would undertake action (eg, contact the physician or the nurse). The primary analysis concerned the positive predictive value (PPV) for clinically relevant medication alerts in both systems.

Results

The PPV was significantly higher in the advanced system (5.8% vs 17.0%; p<0.05). Significant differences were found in the alert categories: drug–(drug) interaction (9.9% vs 14.8%; p<0.05), drug–age interaction (2.9% vs 73.3%; p<0.05), and dosing guidance (5.6% vs 16.9%; p<0.05). Including laboratory values and other patient characteristics resulted in a significantly higher PPV for the advanced CDSS compared to the basic medication alerts (12.2% vs 23.3%; p<0.05).

Conclusion

The advanced CDSS produced a higher proportion of clinically relevant medication alerts, but the number of irrelevant alerts remained high. To improve the PPV of the advanced CDSS, the algorithms should be optimized by identifying additional risk modifiers and more data should be made electronically available to improve the performance of the algorithms. Our study illustrates and corroborates the need for cyclic testing of technical improvements in information technology in circumstances representative of daily clinical practice.     

An Open-label,Self-control,Prospective Study on Cognitive Function,Academic Performance,and Tolerability of Osmotic-release Oral System Methylphenidate in Children with Attention-deficit Hyperactivity Disorder

Background:

Attention-deficit hyperactivity disorder (ADHD) is the most common mental and behavioral disorder in school-aged children. This study evaluated the effect of osmotic-release oral system (OROS) methylphenidate (MPH) on cognitive function and academic performance of Chinese school-aged children with ADHD.

Methods:

This 12-week, prospective, multicenter, open-label, self-controlled study enrolled 153 Chinese school-aged children with ADHD and 41 non-ADHD children. Children with ADHD were treated with once-daily OROS-MPH (18 mg, 36 mg, or 54 mg). The primary endpoints were Inattention/Overactivity (I/O) with Aggression Conners Behavior Rating Scale (IOWA) and Digit Span Test at week 12 compared with baseline. Secondary endpoints included opposition/defiant (O/D) subscale of IOWA, Clinical Global Impression (CGI), Coding Test, Stroop Color-word Test, Wisconsin Card Sorting Test (WCST), academic performance on teacher-rated school examinations, and safety at week 12 compared with baseline. Both non-ADHD and ADHD children received the same frequency of cognitive operational test to avoid the possible bias caused by training.

Results:

A total of 128 patients were evaluated with cognitive assessments. The OROS-MPH treatment significantly improved IOWA Conners I/O subscale scores at week 12 (3.8 ± 2.3) versus baseline (10.0 ± 2.4; P < 0.0001). Digit Span Test scores improved significantly (P < 0.0001) with a high remission rate (81.1%) at week 12 versus baseline. A significant (P < 0.0001) improvement was observed in O/D subscale of IOWA, CGI, Coding Test, Stroop Color-word Test, WCST, and academic performance at week 12 versus baseline. Very few practice-related improvements were noticed in the non-ADHD group at week 12 compared with baseline. No serious adverse events and deaths were reported during the study.

Conclusions:

The OROS-MPH treatment effectively controlled symptoms of ADHD and significantly improved academic performance and cognitive function of Chinese school-aged children with ADHD. The treatment was found to be safe and generally well-tolerated over 12 weeks.

Trial Registration:

ClinicalTrials.gov, {"type":"clinical-trial","attrs":{"text":"NCT01933880","term_id":"NCT01933880"}}NCT01933880; http://clinicaltrials.gov/ct2/show/{"type":"clinical-trial","attrs":{"text":"NCT01933880","term_id":"NCT01933880"}}NCT01933880?term=CONCERTAATT4099&rank=1     

How is the electronic health record being used? Use of EHR data to assess physician-level variability in technology use

Background

Studies of the effects of electronic health records (EHRs) have had mixed findings, which may be attributable to unmeasured confounders such as individual variability in use of EHR features.

Objective

To capture physician-level variations in use of EHR features, associations with other predictors, and usage intensity over time.

Methods

Retrospective cohort study of primary care providers eligible for meaningful use at a network of federally qualified health centers, using commercial EHR data from January 2010 through June 2013, a period during which the organization was preparing for and in the early stages of meaningful use.

Results

Data were analyzed for 112 physicians and nurse practitioners, consisting of 430 803 encounters with 99 649 patients. EHR usage metrics were developed to capture how providers accessed and added to patient data (eg, problem list updates), used clinical decision support (eg, responses to alerts), communicated (eg, printing after-visit summaries), and used panel management options (eg, viewed panel reports). Provider-level variability was high: for example, the annual average proportion of encounters with problem lists updated ranged from 5% to 60% per provider. Some metrics were associated with provider, patient, or encounter characteristics. For example, problem list updates were more likely for new patients than established ones, and alert acceptance was negatively correlated with alert frequency.

Conclusions

Providers using the same EHR developed personalized patterns of use of EHR features. We conclude that physician-level usage of EHR features may be a valuable additional predictor in research on the effects of EHRs on healthcare quality and costs.     

Glycemic Variation in Tumor Patients with Total Parenteral Nutrition

Background:Hyperglycemia is associated with poor clinical outcomes and mortality in several patients.However,studies evaluating hyperglycemia variation in tumor patients receiving total parenteral nutr...     

Randomized Trial to Improve Prescribing Safety During Pregnancy

Objective

This study sought to determine whether a computerized tool that alerted pharmacists when pregnant patients were prescribed U.S. Food and Drug Administration pregnancy risk category D or X medications was effective in decreasing dispensings of these medications.

Design

Randomized trial. Pharmacy, diagnostic, and laboratory data were linked to identify pregnant patients prescribed targeted medications. Women (n = 11,100) were randomized to intervention or usual care. Physicians and pharmacists collaborated on the intervention.

Measurements

The primary outcome was the proportion of pregnant women dispensed a category D or X medication. The secondary outcome was the total number of first dispensings of targeted medications.

Results

A total of 2.9% of intervention (n = 177) and 5.5% of usual care (n = 276) patients were dispensed targeted medications (p < 0.001): 1.8% of intervention (n = 108) and 3.9% of usual care (n = 198) patients were dispensed only category D medication(s); 0.9% of intervention (n = 54) and 1.2% of usual care (n = 58) patients were dispensed only category X medication(s); 0.2% of intervention (n = 15) and 0.4% of usual care (n = 20) patients were dispensed both category D and X medications (p = 0.05). This resulted in intervention patients receiving 238 dispensings of unique targeted medications and usual care patients receiving 361 dispensings of unique targeted medications (p = 0.03). The study was stopped primarily due to 2 false-positive alert types: Misidentification of medications as contraindicated in pregnancy by the pharmacy information system and misidentification of pregnancy related to delayed transfer of diagnosis information.

Conclusion

Coupling data from information systems with knowledge and skills of physicians and pharmacists resulted in improved prescribing safety. Systems limitations contributed to project discontinuation. Linking ambulatory clinical, laboratory, and pharmacy information to provide safety alerts is not sufficient to ensure project success and sustainability.     

Practitioners’ Views on Computerized Drug–Drug Interaction Alerts in the VA System

Objectives

To assess Veterans Affairs (VA) prescribers’ and pharmacists’ opinions about computer-generated drug–drug interaction (DDI) alerts and obtain suggestions for improving DDI alerts.

Design

A mail survey of 725 prescribers and 142 pharmacists from seven VA medical centers across the United States.

Measurements

A questionnaire asked respondents about their sources of drug and DDI information, satisfaction with the combined inpatient and outpatient computerized prescriber order entry (CPOE) system, attitude toward DDI alerts, and suggestions for improving DDI alerts.

Results

The overall response rate was 40% (prescribers: 36%; pharmacists: 59%). Both prescribers and pharmacists indicated that the CPOE system had a neutral to positive impact on their jobs. DDI alerts were not viewed as a waste of time and the majority (61%) of prescribers felt that DDI alerts had increased their potential to prescribe safely. However, only 30% of prescribers felt DDI alerts provided them with what they needed most of the time. Both prescribers and pharmacists agreed that DDI alerts should be accompanied by management alternatives (73% and 82%, respectively) and more detailed information (65% and 89%, respectively). When asked about suggestions for improving DDI alerts, prescribers most preferred including management options whereas pharmacists most preferred making it more difficult to override lethal interactions. Prescribers and pharmacists reported primarily relying on electronic references for general drug information (62% and 55%, respectively) and DDI information (51% and 79%, respectively).

Conclusion

Respondents reported neutral to positive views regarding the effect of CPOE on their jobs. Their opinions suggest DDI alerts are useful but still require additional work to increase their clinical utility.     

Developing High-specificity Anti-hypertensive Alerts by Therapeutic State Analysis of Electronic Prescribing Records

Objective

This paper presents a model for analysis of chronic disease prescribing action over time in terms of transitions in status of therapy as indicated in electronic prescribing records. The quality of alerts derived from these therapeutic state transitions is assessed in the context of antihypertensive prescribing.

Design

A set of alert criteria is developed based on analysis of state-transition in past antihypertensive prescribing of a rural Australian General Practice. Thirty active patients coded as hypertensive with alerts on six months of previously un-reviewed prescribing, and 30 hypertensive patients without alerts, are randomly sampled and independently reviewed by the practice’s two main general practice physicians (GPs), each GP reviewing 20 alert and 20 non-alert cases (providing 10 alert and 10 non-alert cases for agreement assessment).

Measurements

GPs provide blind assessment of quality of hypertension management and retrospective assessment of alert relevance.

Results

Alerts were found on 66 of 611 cases with coded hypertension with 37 alerts on the 30 sampled alert cases. GPs assessed alerting sensitivity as 74% (CI 52% - 89%) and specificity as 61% (CI 45% - 74%) for the sample, which is estimated as 26% sensitivity and 93% specificity for the antihypertensive population. Agreement between the GPs on assessment of alert relevance was fair (kappa = 0.37).

Conclusions

Data-driven development of alerts from electronic prescribing records using analysis of therapeutic state transition shows promise for derivation of high-specificity alerts to improve the quality of chronic disease management activities.