Definition of variables required for comprehensive description of drug dosage and clinical pharmacokinetics.

PURPOSE: Electronic clinical decision support systems (CDSS) require drug information that can be processed by computers. The goal of this project was to determine and evaluate a compilation of variables that comprehensively capture the information contained in the summary of product characteristic (SmPC) and unequivocally describe the drug, its dosage options, and clinical pharmacokinetics. METHODS: An expert panel defined and structured a set of variables and drafted a guideline to extract and enter information on dosage and clinical pharmacokinetics from textual SmPCs as published by the European Medicines Agency (EMA). The set of variables was iteratively revised and evaluated by data extraction and variable allocation of roughly 7% of all centrally approved drugs. RESULTS: The information contained in the SmPC was allocated to three information clusters consisting of 260 variables. The cluster "drug characterization" specifies the nature of the drug. The cluster "dosage" provides information on approved drug dosages and defines corresponding specific conditions. The cluster "clinical pharmacokinetics" includes pharmacokinetic parameters of relevance for dosing in clinical practice. A first evaluation demonstrated that, despite the complexity of the current free text SmPCs, dosage and pharmacokinetic information can be reliably extracted from the SmPCs and comprehensively described by a limited set of variables. CONCLUSION: By proposing a compilation of variables well describing drug dosage and clinical pharmacokinetics, the project represents a step forward towards the development of a comprehensive database system serving as information source for sophisticated CDSS.

Promising adoption of an electronic clinical decision support system for antenatal and intrapartum care in rural primary healthcare facilities in sub-Saharan Africa: The QUALMAT experience.

BACKGROUND: The QUALMAT project has successfully implemented an electronic clinical decision support system (eCDSS) for antenatal and intrapartum care in two sub-Saharan African countries. The system was introduced to facilitate adherence to clinical practice guidelines and to support decision making during client encounter to bridge the know-do gap of health workers. OBJECTIVES: This study aimed to describe health workers' acceptance and use of the eCDSS for maternal care in rural primary health care (PHC) facilities of Ghana and Tanzania and to identify factors affecting successful adoption of such a system. METHODS: This longitudinal study was conducted in Lindi rural district in Tanzania and Kassena-Nankana district in Ghana between October 2011 and December 2013 employing mixed methods. The study population included healthcare workers who were involved in the provision of maternal care in six rural PHC facilities from one district in each country where the eCDSS was implemented. RESULTS: All eCDSS users participated in the study with 61 and 56 participants at the midterm and final assessment, respectively. After several rounds of user training and support the eCDSS has been successfully adopted and constantly used during patient care in antenatal clinics and maternity wards. The eCDSS was used in 71% (2703/3798) and 59% (14,189/24,204) of all ANC clients in Tanzania and Ghana respectively, while it was also used in 83% (1185/1427) and 67% (1435/2144) of all deliveries in Tanzania and in Ghana, respectively. Several barriers reported to hinder eCDSS use were related to individual users, tasks, technology, and organization attributes. CONCLUSION: Implementation of an eCDSS in resource-constrained PHC facilities in sub-Saharan Africa was successful and the health workers accepted and continuously used the system for maternal care. Facilitators for eCDSS use included sufficient training and regular support whereas the challenges to sustained use were unreliable power supply and perceived high workload. However our study also shows that most of the perceived challenges did not substantially hinder adoption and utilization of the eCDSS during patient care.

Cost-effectiveness of clinical decision support system in improving maternal health care in Ghana.

OBJECTIVE: This paper investigated the cost-effectiveness of a computer-assisted Clinical Decision Support System (CDSS) in the identification of maternal complications in Ghana. METHODS: A cost-effectiveness analysis was performed in a before- and after-intervention study. Analysis was conducted from the provider's perspective. The intervention area was the Kassena- Nankana district where computer-assisted CDSS was used by midwives in maternal care in six selected health centres. Six selected health centers in the Builsa district served as the non-intervention group, where the normal Ghana Health Service activities were being carried out. RESULTS: Computer-assisted CDSS increased the detection of pregnancy complications during antenatal care (ANC) in the intervention health centres (before-intervention = 9 /1,000 ANC attendance; after-intervention = 12/1,000 ANC attendance; P-value = 0.010). In the intervention health centres, there was a decrease in the number of complications during labour by 1.1%, though the difference was not statistically significant (before-intervention =107/1,000 labour clients; after-intervention = 96/1,000 labour clients; P-value = 0.305). Also, at the intervention health centres, the average cost per pregnancy complication detected during ANC (cost -effectiveness ratio) decreased from US$17,017.58 (before-intervention) to US$15,207.5 (after-intervention). Incremental cost -effectiveness ratio (ICER) was estimated at US$1,142. Considering only additional costs (cost of computer-assisted CDSS), cost per pregnancy complication detected was US$285. CONCLUSIONS: Computer -assisted CDSS has the potential to identify complications during pregnancy and marginal reduction in labour complications. Implementing computer-assisted CDSS is more costly but more effective in the detection of pregnancy complications compared to routine maternal care, hence making the decision to implement CDSS very complex. Policy makers should however be guided by whether the additional benefit is worth the additional cost.

Tailoring of alerts substantially reduces the alert burden in computerized clinical decision support for drugs that should be avoided in patients with renal disease.

OBJECTIVE: Electronic alerts are often ignored by physicians, which is partly due to the large number of unspecific alerts generated by decision support systems. The aim of the present study was to analyze critical drug prescriptions in a university-based nephrology clinic and to evaluate the effect of different alerting strategies on the alert burden. METHODS: In a prospective observational study, two advanced strategies to automatically generate alerts were applied when medication regimens were entered for discharge letters, outpatient clinic letters, and written prescriptions and compared to two basic reference strategies. Strategy A generated alerts whenever drug-specific information was available, whereas strategy B generated alerts only when the estimated glomerular filtration rate of a patient was below a drug-specific value. Strategies C and D included further patient characteristics and drug-specific information to generate even more specific alerts. RESULTS: Overall, 1012 medication regimens were entered during the observation period. The average number of alerts per drug preparation in medication regimens entered for letters was 0.28, 0.080, 0.019, and 0.011, when using strategy A, B, C, or D (P<0.001, for comparison between the strategies), leading to at least one alert in 87.5%, 39.3%, 13.5%, or 7.81 % of the regimens. Similar average numbers of alerts were observed for medication regimens entered for written prescriptions. CONCLUSIONS: The prescription of potentially hazardous drugs is common in patients with renal impairment. Alerting strategies including patient and drug-specific information to generate more specific alerts have the potential to reduce the alert burden by more than 90 %.

Cost of installing and operating an electronic clinical decision support system for maternal health care: case of Tanzania rural primary health centres.

BACKGROUND: Poor quality of care is among the causes of high maternal and newborn disease burden in Tanzania. Potential reason for poor quality of care is the existence of a "know-do gap" where by health workers do not perform to the best of their knowledge. An electronic clinical decision support system (CDSS) for maternal health care was piloted in six rural primary health centers of Tanzania to improve performance of health workers by facilitating adherence to World Health Organization (WHO) guidelines and ultimately improve quality of maternal health care. This study aimed at assessing the cost of installing and operating the system in the health centers. METHODS: This retrospective study was conducted in Lindi, Tanzania. Costs incurred by the project were analyzed using Ingredients approach. These costs broadly included vehicle, computers, furniture, facility, CDSS software, transport, personnel, training, supplies and communication. These were grouped into installation and operation cost; recurrent and capital cost; and fixed and variable cost. We assessed the CDSS in terms of its financial and economic cost implications. We also conducted a sensitivity analysis on the estimations. RESULTS: Total financial cost of CDSS intervention amounted to 185,927.78 USD. 77% of these costs were incurred in the installation phase and included all the activities in preparation for the actual operation of the system for client care. Generally, training made the largest share of costs (33% of total cost and more than half of the recurrent cost) followed by CDSS software- 32% of total cost. There was a difference of 31.4% between the economic and financial costs. 92.5% of economic costs were fixed costs consisting of inputs whose costs do not vary with the volume of activity within a given range. Economic cost per CDSS contact was 52.7 USD but sensitive to discount rate, asset useful life and input cost variations. CONCLUSIONS: Our study presents financial and economic cost estimates of installing and operating an electronic CDSS for maternal health care in six rural health centres. From these findings one can understand exactly what goes into a similar investment and thus determine sorts of input modification needed to fit their context.

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.

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.

Costs associated with implementation of computer-assisted clinical decision support system for antenatal and delivery care: case study of Kassena-Nankana district of northern Ghana.

OBJECTIVE: This study analyzed cost of implementing computer-assisted Clinical Decision Support System (CDSS) in selected health care centres in Ghana. METHODS: A descriptive cross sectional study was conducted in the Kassena-Nankana district (KND). CDSS was deployed in selected health centres in KND as an intervention to manage patients attending antenatal clinics and the labour ward. The CDSS users were mainly nurses who were trained. Activities and associated costs involved in the implementation of CDSS (pre-intervention and intervention) were collected for the period between 2009-2013 from the provider perspective. The ingredients approach was used for the cost analysis. Costs were grouped into personnel, trainings, overheads (recurrent costs) and equipment costs (capital cost). We calculated cost without annualizing capital cost to represent financial cost and cost with annualizing capital costs to represent economic cost. RESULTS: Twenty-two trained CDSS users (at least 2 users per health centre) participated in the study. Between April 2012 and March 2013, users managed 5,595 antenatal clients and 872 labour clients using the CDSS. We observed a decrease in the proportion of complications during delivery (pre-intervention 10.74% versus post-intervention 9.64%) and a reduction in the number of maternal deaths (pre-intervention 4 deaths versus post-intervention 1 death). The overall financial cost of CDSS implementation was US$23,316, approximately US$1,060 per CDSS user trained. Of the total cost of implementation, 48% (US$11,272) was pre-intervention cost and intervention cost was 52% (US$12,044). Equipment costs accounted for the largest proportion of financial cost: 34% (US$7,917). When economic cost was considered, total cost of implementation was US$17,128-lower than the financial cost by 26.5%. CONCLUSIONS: The study provides useful information in the implementation of CDSS at health facilities to enhance health workers' adherence to practice guidelines and taking accurate decisions to improve maternal health care.

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 today's 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.

Development of a standardized knowledge base to generate individualized medication plans automatically with drug administration recommendations.

AIMS: We aimed to develop a generic knowledge base with drug administration recommendations which allows the generation of a dynamic and comprehensive medication plan and to evaluate its comprehensibility and potential benefit in a qualitative pilot study with patients and physicians. METHODS: Based on a literature search and previously published medication plans, a prototype was developed and iteratively refined through qualitative evaluation (interviews with patients and focus group discussions with physicians). To develop the recommendations for safe administration of specific drugs we screened the summary of product characteristics (SmPC) of different exemplary brands, allocated the generated advice to groups with brands potentially requiring the same advice, and reviewed these allocations regarding applicability and appropriateness of the recommendations. RESULTS: For the recommendations, 411 SmPCs of 140 different active ingredients including all available galenic formulations, routes of administrations except infusions, and administration devices were screened. Finally, 515 distinct administration recommendations were included in the database. In 926 different generic groups, 29,879 allocations of brands to general advice, food advice, indications, step-by-step instructions, or combinations thereof were made. Thereby, 27,216 of the preselected allocations (91.1%) were confirmed as appropriate. In total, one third of the German drug market was labelled with information. CONCLUSIONS: Generic grouping of brands according to their active ingredient and other drug characteristics and allocation of standardized administration recommendations is feasible for a large drug market and can be integrated in a medication plan.

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

BACKGROUND: Despite 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. METHODS: A 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". RESULTS: The 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. CONCLUSION: The 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.

Development and evaluation of a computerised clinical decision support system for switching drugs at the interface between primary and tertiary care.

BACKGROUND: Upon admission to a hospital patients' medications are frequently switched to alternative drugs compiled in so called hospital drug formularies. This substitution process is a laborious and error-prone task which should be supported by sophisticated electronic tools. We developed a computerised decision support system and evaluated benefit and potential harm associated with its use. METHODS: Based on a multi-step algorithm we identified drug classes suitable for exchange, defined conversion factors for therapeutic interchange, built a web-based decision support system, and implemented it into the computerised physician order entry of a large university hospital. For evaluation we compared medications manually switched by clinical pharmacists with the results of automated switching by the newly developed computer system and optimised the system in an iterative process. Thereafter the final system was tested in an independent set of prescriptions. RESULTS: After iterative optimisation of the logical framework the tool was able to switch drugs to pharmaceutical equivalents and alternatives; in addition, it contained 21 different drug classes for therapeutic substitution. In this final version it switched 91.6% of 202 documented medication consultations (containing 1,333 drugs) automatically, leaving 8.4% for manual processing by clinical professionals. No incorrect drug switches were found. CONCLUSION: A large majority (>90%) of drug switches performed at the interface between primary and tertiary care can be handled automatically using electronic decision support systems, indicating that medication errors and workload of healthcare professionals can be considerably reduced.

Assessment of a computerised decision support system for allergic rhino-conjunctivitis counselling in German pharmacy.

OBJECTIVE: In a prospective two-phase intervention study we evaluated a newly developed computerised pharmacy decision support system (PDSS) for the counselling of patients with allergic rhinitis and conjunctivitis. METHOD: Community pharmacists were invited to counsel a virtual patient in a first interview. Immediately thereafter, we trained pharmacists to operate the PDSS, which they applied in a second patient interview immediately following the training. We assessed the completeness of mandatory questions asked as defined by national guidelines. RESULTS: Participating pharmacists (n = 50, 78% female, mean age 34 [IQR: 27-40] years, 8 [2-14.5] years of practical experience, 32% specialised in community pharmacy) asked considerably more mandatory questions to confirm appropriateness of self-medication with 7 (5.25-9; 78%) from 9 questions compared to 2 (1-3; 22%) without PDSS (median; P < 0.001). In particular, using the PDSS more than doubled mandatory questions (9/12, 6.25-10; 75% vs. 4/12, 3-5; 33%; P < 0.001) relevant for appropriate drug selection. CONCLUSION: Pharmacists omitted many questions mandatory to assess whether self-medication is appropriate. Using the newly developed PDSS more than doubled the number of mandatory questions asked. The results suggest that the PDSS is ready for evaluation of its impact in real patients.

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.

Prevention of adverse drug reactions in intensive care patients by personal intervention based on an electronic clinical decision support system.

OBJECTIVE: We investigated the effect of written drug information for senior clinicians on the incidence of drug-drug interactions (DDIs) and DDI-related adverse events in intensive care patients. DESIGN AND METHODS: A prospective controlled intervention cohort study was conducted in a medical intensive and intermediate care unit in a university hospital. From 1,062 consecutive intensive care patients, those 265 (control: 136, intervention: 129) with > or =8 concurrently prescribed drugs were included in the study (to include high-risk patients with polypharmacy). The DDI information for senior clinicians during an intervention period of 3 months was based on a computerised clinical decision support system (CDSS) containing information on risk and management of 9,453 drug combinations. RESULTS: The number of patients with at least one DDI at the end of the respective study phase decreased by 18% (relative risk reduction) from 90 (66%) patients in controls to 70 (54%) in the intervention group (p = 0.02). The relative risk of a patient suffering from at least one DDI-related adverse event decreased by 43% from 60 (44%) patients in controls to 32 (25%) in the intervention group (p < 0.01). Among these events, the incidence of QT(C) prolongation was reduced by 64% from 15 (11%) patients in the control group to 5 (4%) in the intervention group (p = 0.04), and the incidence of hypokalemia by 80% from 14 (10%) to 2 (2%, p < 0.01). CONCLUSION: Written drug information based on a CDSS considerably decreased DDIs and DDI-related adverse events in routine practice.

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

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 (Delta(0.5) (Q(75%)-Q(25%))=3.0) on admission to 1.5 (Delta(0.5)=1.0) at discharge (p<0.01) and during physical activity from 7.0 (Delta(0.5)=4.0) on admission to 2.5 (Delta(0.5)=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.

PURPOSE: A 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. METHODS: Upper 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. RESULTS: From 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). CONCLUSION: This 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.

BACKGROUND: Currently 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. METHODS: We 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). RESULTS: During 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). CONCLUSION: This study revealed that computerised decision support can immediately reduce the frequency of inappropriate splitting without introducing new safety hazards.

Prescribing errors in patients with documented drug allergies: comparison of ICD-10 coding and written patient notes.

INTRODUCTION: Allergies to drugs are a major cause for hospitalisation and inappropriate prescriptions to patients. However, allergies can be prevented if the patient's history of drug allergy is known and coded. OBJECTIVE OF THE STUDY: Assessment of the value of the widely used ICD-10 codes for drug-allergies (e.g. Z88, L27) as triggers for decision support in an electronic prescription system and evaluation of the potential impact of such an alert system. We also evaluated the usefulness of manual drug allergy notes recorded in patients' charts in the prevention of prescribing errors due to drug allergies. SETTING: University hospital providing primary and tertiary care. METHODS: Using Anatomical Therapeutic Chemical (ATC) classification codes we allocated to drug specifying ICD-10 codes (i.e. Z88) all drugs belonging to the same group of compounds or those known to induce cross-allergy. In a randomly selected cohort of 200 in-patients we then assessed documentation and coding of drug allergies and incident prescribing errors ignoring patients' drug allergies. RESULTS: Eighteen of the 200 patients had an allergy-related ICD code in the chart, 51 had a written note, and 13 had both. About 21% of patients with documented drug allergies were prescribed a drug potentially triggering the allergy. There was no difference in prescribing errors due to drugs potentially inducing allergies when the allergy was only documented as an ICD-10 code or the information was available in the paper record (P > 0.05). CONCLUSION: The findings of this study emphasise the necessity of a more precise and efficient documentation system of drug allergies along with the implementation of an electronic CDS for drug allergies that makes physicians aware of patients' drug allergies during the prescribing process.

Characteristics of effective electronic mail messages distributed to healthcare professionals in a hospital setting.

Electronic mailing systems (e-mail) are an important means to disseminate information within electronic networks. However, in large business communities including the hectic environment of hospitals it may be difficult to induce account holders to read the e-mail. In two mailings disseminated in a large university hospital we evaluated the impact of e-mail layout (three e-mail text versions, two e-mails with graphics) on the willingness of its approximately 6500 recipients to seek additional electronic information and open an integrated link. Overall access rates after 90 days were 21.1 and 23.5% with more than 70% of the respondents opening the link within 3 days. Differences between different layouts were large and artwork text, HTML text, animated GIF, and static image prompted 1.2, 1.7, 1.8, and 2.3 times more often access than the courier plain text message (p