Jens Kaltschmidt

What, if all alerts were specific – Estimating the potential impact on drug interaction alert burden

PURPOSE Clinical decision support systems (CDSS) may potentially improve prescribing quality, but are subject to poor user acceptance. Reasons for alert overriding have been identified and counterstrategies have been suggested; however, poor alert specificity, a prominent reason of alert overriding, has not been well addressed. This paper aims at structuring modulators that determine alert specificity and estimating their quantitative impact on alert burden. METHODS We developed and summarized optimizing strategies to guarantee the specificity of alerts and applied them to a set of 100 critical and frequent drug interaction (DDI) alerts. Hence, DDI alerts were classified as dynamic, i.e. potentially sensitive to prescription-, co-medication-, or patient-related factors that would change alert severity or render the alert inappropriate compared to static, i.e. always applicable alerts not modulated by cofactors. RESULTS Within the subset of 100 critical DDI alerts, only 10 alerts were considered as static and for 7 alerts, relevant factors are not generally available in todays patient charts or their consideration would not impact alert severity. The vast majority, i.e. 83 alerts, might require a decrease in alert severity due to factors related to the prescription (N=13), the co-medication (N=11), individual patient data (N=36), or combinations of them (N=23). Patient-related factors consisted mainly of three lab values, i.e. renal function, potassium, and therapeutic drug monitoring results. CONCLUSION This paper outlines how promising the refinement of knowledge bases is in order to increase specificity and decrease alert burden and suggests how to structure knowledge bases to refine DDI alerting.

“Quality of prenatal and maternal care: bridging the know-do gap” (QUALMAT study): an electronic clinical decision support system for rural Sub-Saharan Africa

BackgroundDespite strong efforts to improve maternal care, its quality remains deficient in many countries of Sub-Saharan Africa as persistently high maternal mortality rates testify. The QUALMAT study seeks to improve the performance and motivation of rural health workers and ultimately quality of primary maternal health care services in three African countries Burkina Faso, Ghana, and Tanzania. One major intervention is the introduction of a computerized Clinical Decision Support System (CDSS) for rural primary health care centers to be used by health care workers of different educational levels.MethodsA stand-alone, java-based software, able to run on any standard hardware, was developed based on assessment of the health care situation in the involved countries. The software scope was defined and the final software was programmed under consideration of test experiences. Knowledge for the decision support derived from the World Health Organization (WHO) guideline “Pregnancy, Childbirth, Postpartum and Newborn Care; A Guide for Essential Practice”.ResultsThe QUALMAT CDSS provides computerized guidance and clinical decision support for antenatal care, and care during delivery and up to 24 hours post delivery. The decision support is based on WHO guidelines and designed using three principles: (1) Guidance through routine actions in maternal and perinatal care, (2) integration of clinical data to detect situations of concern by algorithms, and (3) electronic tracking of peri- and postnatal activities. In addition, the tool facilitates patient management and is a source of training material. The implementation of the software, which is embedded in a set of interventions comprising the QUALMAT study, is subject to various research projects assessing and quantifying the impact of the CDSS on quality of care, the motivation of health care staff (users) and its health economic aspects. The software will also be assessed for its usability and acceptance, as well as for its influence on workflows in the rural setting of primary health care in the three countries involved.ConclusionThe development and implementation of a CDSS in rural primary health care centres presents challenges, which may be overcome with careful planning and involvement of future users at an early stage. A tailored software with stable functionality should offer perspectives to improve maternal care in resource-poor settings.Trial registrationhttp://www.clinicaltrials.gov/NCT01409824.

Multidisciplinary pain management based on a computerized clinical decision support system in cancer pain patients

ABSTRACT A prospective controlled intervention cohort study in cancer pain patients (n = 50 per group) admitted to radiation oncology wards (62 beds, 3 wards) was conducted in a 1621‐bed university hospital. We investigated the effect of an intervention consisting of daily pain assessment using the numeric visual analog scale (NVAS) and pain therapy counseling to clinicians based on a computerized clinical decision support system (CDSS) to correct deviations from pain therapy guidelines. Effects on guideline adherence (primary outcome), pain relief (NVAS) at rest and during physical activity (both groups: cross‐sectional assessment on day 5; intervention group: every day assessment), co‐analgesic prescription, and acceptance rates of recommendations (secondary outcomes) were assessed. The number of patients with at least one deviation from guidelines at discharge was decreased by the intervention from 37 (74%) in controls to 7 (14%, p < 0.001). In the intervention group, pain (NVAS) decreased during hospital stay at rest from 3.0 (Δ0.5 (Q75% − Q25%) = 3.0) on admission to 1.5 (Δ0.5 = 1.0) at discharge (p < 0.01) and during physical activity from 7.0 (Δ0.5 = 4.0) on admission to 2.5 (Δ0.5 = 3.8) at discharge (p < 0.001). At discharge, the number of patients treated with co‐analgesics increased from 23 (46%) in controls to 33 (66%) in the intervention group (p = 0.04). From 279 recommendations issued in the intervention 85% were fully accepted by the physicians. Deviations from well‐established guidelines are frequent in pain therapy. A multidisciplinary pain management increased adherence to pain management guidelines.

Successful strategy to improve the specificity of electronic statin?drug interaction alerts

PurposeA considerable weakness of current clinical decision support systems managing drug–drug interactions (DDI) is the high incidence of inappropriate alerts. Because DDI-induced, dose-dependent adverse events can be prevented by dosage adjustment, corresponding DDI alerts should only be issued if dosages exceed safe limits. We have designed a logical framework for a DDI alert-system that considers prescribed dosage and retrospectively evaluates the impact on the frequency of statin–drug interaction alerts.MethodsUpper statin dose limits were extracted from the drug label (SPC) (20 statin-drug combinations) or clinical trials specifying the extent of the pharmacokinetic interaction (43 statin–drug combinations). We retrospectively assessed electronic DDI alerts and compared the number of standard alerts to alerts that took dosage into account.ResultsFrom among 2457 electronic prescriptions, we identified 73 high-risk statin–drug pairs. Of these, SPC dosage information classified 19 warnings as inappropriate. Data from pharmacokinetic trials took quantitative dosage information more often into consideration and classified 40 warnings as inappropriate. This is a significant reduction in the number of alerts by 55% compared to SPC-based information (26%; p < 0.001).ConclusionThis retrospective study of pharmacokinetic statin interactions demonstrates that more than half of the DDI alerts that presented in a clinical decision support system were inappropriate if DDI-specific upper dose limits are not considered.

Substantial reduction of inappropriate tablet splitting with computerised decision support: a prospective intervention study assessing potential benefit and harm

BackgroundCurrently ambulatory patients break one in four tablets before ingestion. Roughly 10% of them are not suitable for splitting because they lack score lines or because enteric or modified release coating is destroyed impairing safety and effectiveness of the medication. We assessed impact and safety of computerised decision support on the inappropriate prescription of split tablets.MethodsWe performed a prospective intervention study in a 1680-bed university hospital. Over a 15-week period we evaluated all electronically composed medication regimens and determined the fraction of tablets and capsules that demanded inappropriate splitting. In a subsequent intervention phase of 15 weeks duration for 10553 oral drugs divisibility characteristics were indicated in the system. In addition, an alert was generated and displayed during the prescription process whenever the entered dosage regimen demanded inappropriate splitting (splitting of capsules, unscored tablets, or scored tablets unsuitable for the intended fragmentation).ResultsDuring the baseline period 12.5% of all drugs required splitting and 2.7% of all drugs (257/9545) required inappropriate splitting. During the intervention period the frequency of inappropriate splitting was significantly reduced (1.4% of all drugs (146/10486); p = 0.0008). In response to half of the alerts (69/136) physicians adjusted the medication regimen. In the other half (67/136) no corrections were made although a switch to more suitable drugs (scored tablets, tablets with lower strength, liquid formulation) was possible in 82% (55/67).ConclusionThis study revealed that computerised decision support can immediately reduce the frequency of inappropriate splitting without introducing new safety hazards.

Health workers knowledge of and attitudes towards computer applications in rural African health facilities.

Background The QUALMAT (Quality of Maternal and Prenatal Care: Bridging the Know-do Gap) project has introduced an electronic clinical decision support system (CDSS) for pre-natal and maternal care services in rural primary health facilities in Burkina Faso, Ghana, and Tanzania. Objective To report an assessment of health providers’ computer knowledge, experience, and attitudes prior to the implementation of the QUALMAT electronic CDSS. Design A cross-sectional study was conducted with providers in 24 QUALMAT project sites. Information was collected using structured questionnaires. Chi-squared tests and one-way ANOVA describe the association between computer knowledge, attitudes, and other factors. Semi-structured interviews and focus groups were conducted to gain further insights. Results A total of 108 providers responded, 63% were from Tanzania and 37% from Ghana. The mean age was 37.6 years, and 79% were female. Only 40% had ever used computers, and 29% had prior computer training. About 80% were computer illiterate or beginners. Educational level, age, and years of work experience were significantly associated with computer knowledge (p<0.01). Most (95.3%) had positive attitudes towards computers – average score (±SD) of 37.2 (±4.9). Females had significantly lower scores than males. Interviews and group discussions showed that although most were lacking computer knowledge and experience, they were optimistic about overcoming challenges associated with the introduction of computers in their workplace. Conclusions Given the low levels of computer knowledge among rural health workers in Africa, it is important to provide adequate training and support to ensure the successful uptake of electronic CDSSs in these settings. The positive attitudes to computers found in this study underscore that also rural care providers are ready to use such technology.

Impact of an electronic clinical decision support system on workflow in antenatal care: the QUALMAT eCDSS in rural health care facilities in Ghana and Tanzania

Background The implementation of new technology can interrupt established workflows in health care settings. The Quality of Maternal Care (QUALMAT) project has introduced an electronic clinical decision support system (eCDSS) for antenatal care (ANC) and delivery in rural primary health care facilities in Africa. Objective This study was carried out to investigate the influence of the QUALMAT eCDSS on the workflow of health care workers in rural primary health care facilities in Ghana and Tanzania. Design A direct observation, time-and-motion study on ANC processes was conducted using a structured data sheet with predefined major task categories. The duration and sequence of tasks performed during ANC visits were observed, and changes after the implementation of the eCDSS were analyzed. Results In 24 QUALMAT study sites, 214 observations of ANC visits (144 in Ghana, 70 in Tanzania) were carried out at baseline and 148 observations (104 in Ghana, 44 in Tanzania) after the software was implemented in 12 of those sites. The median time spent combined for all centers in both countries to provide ANC at baseline was 6.5 min [interquartile range (IQR) =4.0-10.6]. Although the time spent on ANC increased in Tanzania and Ghana after the eCDSS implementation as compared to baseline, overall there was no significant increase in time used for ANC activities (0.51 min, p=0.06 in Ghana; and 0.54 min, p=0.26 in Tanzania) as compared to the control sites without the eCDSS. The percentage of medical history taking in women who had subsequent examinations increased after eCDSS implementation from 58.2% (39/67) to 95.3% (61/64) p<0.001 in Ghana but not in Tanzania [from 65.4% (17/26) to 71.4% (15/21) p=0.70]. Conclusions The QUALMAT eCDSS does not increase the time needed for ANC but partly streamlined workflow at sites in Ghana, showing the potential of such a system to influence quality of care positively.Background The implementation of new technology can interrupt established workflows in health care settings. The Quality of Maternal Care (QUALMAT) project has introduced an electronic clinical decision support system (eCDSS) for antenatal care (ANC) and delivery in rural primary health care facilities in Africa. Objective This study was carried out to investigate the influence of the QUALMAT eCDSS on the workflow of health care workers in rural primary health care facilities in Ghana and Tanzania. Design A direct observation, time-and-motion study on ANC processes was conducted using a structured data sheet with predefined major task categories. The duration and sequence of tasks performed during ANC visits were observed, and changes after the implementation of the eCDSS were analyzed. Results In 24 QUALMAT study sites, 214 observations of ANC visits (144 in Ghana, 70 in Tanzania) were carried out at baseline and 148 observations (104 in Ghana, 44 in Tanzania) after the software was implemented in 12 of those sites. The median time spent combined for all centers in both countries to provide ANC at baseline was 6.5 min [interquartile range (IQR) =4.0–10.6]. Although the time spent on ANC increased in Tanzania and Ghana after the eCDSS implementation as compared to baseline, overall there was no significant increase in time used for ANC activities (0.51 min, p=0.06 in Ghana; and 0.54 min, p=0.26 in Tanzania) as compared to the control sites without the eCDSS. The percentage of medical history taking in women who had subsequent examinations increased after eCDSS implementation from 58.2% (39/67) to 95.3% (61/64) p<0.001 in Ghana but not in Tanzania [from 65.4% (17/26) to 71.4% (15/21) p=0.70]. Conclusions The QUALMAT eCDSS does not increase the time needed for ANC but partly streamlined workflow at sites in Ghana, showing the potential of such a system to influence quality of care positively.

Detection and prevention of prescriptions with excessive doses in electronic prescribing systems

IntroductionDose dependent adverse drug reactions are often caused by prescribing errors ignoring upper dose limits. Thus, computerised physician order entry incorporating maximum recommended therapeutic doses (MRTDs) might reduce prescriptions of excessive doses. We evaluated the suitability of MRTD information as published in the Summary of Product Characteristics (SPC) (MRTDSPC) or by the US Food and Drug Administration (MRTDFDA) and the value of Defined Daily Doses (DDD, World Health Organisation) as knowledge bases for an alerting system.MethodsIn a large set of critical-dose drugs (N = 140) we compared MRTDFDA and DDD values with the corresponding German MRTDSPC. We then retrospectively assessed a set of 633 electronically prescribed drugs (EPDs) issued at a university hospital and calculated prescription rates of excessive doses.ResultsMRTDFDA was similar to MRTDSPC in 37% (N = 140), higher in 32%, and lower in 31% of drugs. On average, available DDD values (N = 129) were 1.6 times lower than MRTDSPC, with 64% being lower, 33% similar, and 3% larger than MRTDSPC. Prescription rates of excessive doses according to MRTDFDA were 2.5-fold higher (6.1%) than according to MRTDSPC (2.5%) (p < 0.01). However, only one in four EPDs categorised as overdosed according to MRTDFDA exceeded MRTDSPC, and MRTDFDA values were available only for 67% of all assessed EPDs.ConclusionOur study revealed a remarkable number of prescriptions with doses exceeding approved limits. Their prevention appears feasible but the choice of an appropriate database for MRTDs is essential, and differences between available information sources are large.

Memorandum on the Use of Information Technology to Improve Medication Safety

BACKGROUND Information technology in health care has a clear potential to improve the quality and efficiency of health care, especially in the area of medication processes. On the other hand, existing studies show possible adverse effects on patient safety when IT for medication-related processes is developed, introduced or used inappropriately. OBJECTIVES To summarize definitions and observations on IT usage in pharmacotherapy and to derive recommendations and future research priorities for decision makers and domain experts. METHODS This memorandum was developed in a consensus-based iterative process that included workshops and e-mail discussions among 21 experts coordinated by the Drug Information Systems Working Group of the German Society for Medical Informatics, Biometry and Epidemiology (GMDS). RESULTS The recommendations address, among other things, a stepwise and comprehensive strategy for IT usage in medication processes, the integration of contextual information for alert generation, the involvement of patients, the semantic integration of information resources, usability and adaptability of IT solutions, and the need for their continuous evaluation. CONCLUSION Information technology can help to improve medication safety. However, challenges remain regarding access to information, quality of information, and measurable benefits.

Misspellings in drug information system queries: Characteristics of drug name spelling errors and strategies for their prevention

INTRODUCTION Efficient search for and finding drugs is essential for electronic drug information systems which, for their part, are prerequisites for computerized physician order entry systems and clinical decision support with the potential to prevent medication errors. Search failures would be critical: they may delay or even prohibit prescription processes or timely retrieval of vital drug information. We analyzed spelling-correction and error characteristics in drug searches and the suitability of auto-completion as prevention strategy. METHODS A blank entry field was presented to the user for unbiased queries in a web-based drug information system containing >105,000 brand names and active ingredients accessible from all 5500 computers of the Heidelberg University Hospital. The system was equipped with an error-tolerant search. Misspelled but found drug names confirmed by users were aligned by dynamic programming algorithms, opposing misspelled and correct names letter by letter. We analyzed the ratios of correctly and incorrectly spelled but found drugs, frequencies of characters, and their position in misspelled search words. RESULTS Without error-tolerant search, no results were found in 17.5% of all queries. Users confirmed 31% of all results found with phonetic error-correction support. Sixteen percent of all spelling errors were letters in close proximity to the correct letter on keyboards. On average, 7% of the initial letters in misspelled words contained errors. CONCLUSION Drug information systems should be equipped with error-tolerant algorithms to reduce search failures. Drug initial letters are also error-prone, thus auto-completion is not a sufficient error-prevention strategy and needs additional support by error-tolerant algorithms.