Can computerised decision support systems deliver improved quality in primary care? Interview by Abi Berger

Clinical Decision Support Systems for Diagnosis in Primary Care: A Scoping Review

Diagnosis is one of the crucial tasks performed by primary care physicians; however, primary care is at high risk of diagnostic errors due to the characteristics and uncertainties associated with the field. Prevention of diagnostic errors in primary care requires urgent action, and one of the possible methods is the use of health information technology. Its modes such as clinical decision support systems (CDSS) have been demonstrated to improve the quality of care in a variety of medical settings, including hospitals and primary care centers, though its usefulness in the diagnostic domain is still unknown. We conducted a scoping review to confirm the usefulness of the CDSS in the diagnostic domain in primary care and to identify areas that need to be explored. Search terms were chosen to cover the three dimensions of interest: decision support systems, diagnosis, and primary care. A total of 26 studies were included in the review. As a result, we found that the CDSS and reminder tools have significant effects on screening for common chronic diseases; however, the CDSS has not yet been fully validated for the diagnosis of acute and uncommon chronic diseases. Moreover, there were few studies involving non-physicians.

Clinical decision support systems-based interventions to improve medication outcomes: A systematic literature review on features and effects

Background: Clinical decision support systems (CDSSs) interventions were used to improve the life quality and safety in patients and also to improve practitioner performance, especially in the field of medication. Therefore, the aim of the paper was to summarize the available evidence on the impact, outcomes and significant factors on the implementation of CDSS in the field of medicine. Methods: This study is a systematic literature review. PubMed, Cochrane Library, Web of Science, Scopus, EMBASE, and ProQuest were investigated by 15 February 2017. The inclusion requirements were met by 98 papers, from which 13 had described important factors in the implementation of CDSS, and 86 were medicated-related. We categorized the system in terms of its correlation with medication in which a system was implemented, and our intended results were examined. In this study, the process outcomes (such as; prescription, drug-drug interaction, drug adherence, etc.), patient outcomes, and significant factors affecting the implementation of CDSS were reviewed. Results: We found evidence that the use of medication-related CDSS improves clinical outcomes. Also, significant results were obtained regarding the reduction of prescription errors, and the improvement in quality and safety of medication prescribed. Conclusion: The results of this study show that, although computer systems such as CDSS may cause errors, in most cases, it has helped to improve prescribing, reduce side effects and drug interactions, and improve patient safety. Although these systems have improved the performance of practitioners and processes, there has not been much research on the impact of these systems on patient outcomes.

Novel Health Information Technology to Aid Provider Recognition and Treatment of Major Depressive Disorder and Posttraumatic Stress Disorder in Primary Care

BACKGROUND

Millions of traumatized refugees worldwide have resettled in the United States. For one of the largest, the Cambodian community, having their mental health needs met has been a continuing challenge. A multicomponent health information technology screening tool was designed to aid provider recognition and treatment of major depressive disorder and posttraumatic stress disorder (PTSD) in the primary care setting.

METHODS

In a clustered randomized controlled trial, 18 primary care providers were randomized to receive access to a multicomponent health information technology mental health screening intervention, or to a minimal intervention control group; 390 Cambodian American patients empaneled to participating providers were assigned to the providers' randomized group.

RESULTS

Electronic screening revealed that 65% of patients screened positive for depression and 34% screened positive for PTSD. Multilevel mixed effects logistic models, accounting for clustering structure, indicated that providers in the intervention were more likely to diagnose depression [odds ratio (OR), 6.5; 95% confidence interval (CI), 1.48-28.79; P=0.013] and PTSD (OR, 23.3; 95% CI, 2.99-151.62; P=0.002) among those diagnosed during screening, relative to the control group. Providers in the intervention were more likely to provide evidence-based guideline (OR, 4.02; 95% CI, 1.01-16.06; P=0.049) and trauma-informed (OR, 15.8; 95% CI, 3.47-71.6; P<0.001) care in unadjusted models, relative to the control group. Guideline care, but not trauma-informed care, was associated with decreased depression at 12 weeks in both study groups (P=0.003), and neither was associated with PTSD outcomes at 12 weeks.

CONCLUSIONS

This innovative approach offers the potential for training primary care providers to diagnose and treat traumatized patients, the majority of whom seek mental health care in primary care (ClinicalTrials.gov number, NCT03191929).

Development and Application of a System Based on Artificial Intelligence for Transcatheter Aortic Prosthesis Selection

Introduction

The interest in Expert systems has increased in the medical area. Some of them are employed even for diagnosis. With the variability of transcatheter prostheses, the most appropriate choice can be complex. This scenario reveals an enabling environment for the use of an Expert system. The goal of the study was to develop an Expert system based on artificial intelligence for supporting the transcatheter aortic prosthesis selection.

Methods

The system was developed on Expert SINTA. The rules were created according to anatomical parameters indicated by the manufacturing company. Annular aortic diameter, aortic area, aortic perimeter, ascending aorta diameter and Valsalva sinus diameter were considered. After performing system accuracy tests, it was applied in a retrospective cohort of 22 patients with submitted to the CoreValve prosthesis implantation. Then, the system indications were compared to the real heart team decisions.

Results

For 10 (45.4%) of the 22 patients there was no concordance between the Expert system and the heart team. In all cases with discordance, the software was right in the indication. Then, the patients were stratified in two groups (same indication vs. divergent indication). The baseline characteristics did not show any significant difference. Mortality, stroke, acute myocardial infarction, atrial fibrillation, atrioventricular block, aortic regurgitation and prosthesis leak did not present differences. Therefore, the maximum aortic gradient in the post-procedure period was higher in the Divergent Indication group (23.9 mmHg vs. 11.9 mmHg, P=0.03), and the mean aortic gradient showed a similar trend.

Conclusion

The utilization of the Expert system was accurate, showing good potential in the support of medical decision. Patients with divergent indication presented high post-procedure aortic gradients and, even without clinical repercussion, these parameters, when elevated, can lead to early prosthesis dysfunction and the necessity of reoperation.

Models Used in Clinical Decision Support Systems Supporting Healthcare Professionals Treating Chronic Wounds: Systematic Literature Review

Background

Chronic wounds such as diabetic foot ulcers, venous leg ulcers, and pressure ulcers are a massive burden to health care facilities. Many randomized controlled trials on different wound care elements have been conducted and published in the Cochrane Library, all of which have only a low evidential basis. Thus, health care professionals are forced to rely on their own experience when making decisions regarding wound care. To progress from experience-based practice to evidence-based wound care practice, clinical decision support systems (CDSS) that help health care providers with decision-making in a clinical workflow have been developed. These systems have proven useful in many areas of the health care sector, partly because they have increased the quality of care, and partially because they have generated a solid basis for evidence-based practice. However, no systematic reviews focus on CDSS within the field of wound care to chronic wounds.

Objective

The aims of this systematic literature review are (1) to identify models used in CDSS that support health care professionals treating chronic wounds, and (2) to classify each clinical decision support model according to selected variables and to create an overview.

Methods

A systematic review was conducted using 6 databases. This systematic literature review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement for systematic reviews. The search strategy consisted of three facets, respectively: Facet 1 (Algorithm), Facet 2 (Wound care) and Facet 3 (Clinical decision support system). Studies based on acute wounds or trauma were excluded. Similarly, studies that presented guidelines, protocols and instructions were excluded, since they do not require progression along an active chain of reasoning from the clinicians, just their focus. Finally, studies were excluded if they had not undergone a peer review process. The following aspects were extracted from each article: authors, year, country, the sample size of data and variables describing the type of clinical decision support models. The decision support models were classified in 2 ways: quantitative decision support models, and qualitative decision support models.

Results

The final number of studies included in the systematic literature review was 10. These clinical decision support models included 4/10 (40%) quantitative decision support models and 6/10 (60%) qualitative decision support models. The earliest article was published in 2007, and the most recent was from 2015.

Conclusions

The clinical decision support models were targeted at a variety of different types of chronic wounds. The degree of accessibility of the inference engines varied. Quantitative models served as the engine and were invisible to the health care professionals, while qualitative models required interaction with the user.

Meaningful use's benefits and burdens for US family physicians

Objective

The federal meaningful use (MU) program was aimed at improving adoption and use of electronic health records, but practicing physicians have criticized it. This study was aimed at quantifying the benefits (ie, usefulness) and burdens (ie, workload) of the MU program for practicing family physicians.

Materials and Methods

An interdisciplinary national panel of experts (physicians and engineers) identified the work associated with MU criteria during patient encounters. They conducted a national survey to assess each criterion's level of patient benefit and compliance burden.

Results

In 2015, 480 US family physicians responded to the survey. Their demographics were comparable to US norms. Eighteen of 31 MU criteria were perceived as useful for more than half of patient encounters, with 13 of those being useful for more than two-thirds. Thirteen criteria were useful for less than half of patient encounters. Four useful criteria were reported as having a high compliance burden.

Discussion

There was high variability in physicians' perceived benefits and burdens of MU criteria. MU Stage 1 criteria, which are more related to basic/routine care, were perceived as beneficial by most physicians. Stage 2 criteria, which are more related to complex and population care, were perceived as less beneficial and more burdensome to comply with.

Conclusion

MU was discontinued, but the merit-based incentive payment system within the Medicare Access and CHIP Reauthorization Act of 2015 adopted its criteria. For many physicians, MU created a significant practice burden without clear benefits to patient care. This study suggests that policymakers should not assess MU in aggregate, but as individual criteria for open discussion.

ERAS: Safety checklists, antibiotics, and VTE prophylaxis

The concept rested on several components that many of us have now tried to adopt or improve on, inclusive of a multidisciplinary team, a multimodal approach to anesthesia and preoperative preparedness, evidence-based approach to care protocols; and a change in management using interactive and continuous audit prior to and post-procedure. This article describes the development of ERAS protocols relative to checklist implementation, antibiotic use, and venous thromboembolism (VTE) prevention, how these ideas are developed and operationalized as well as how they are evolving and spreading across the care continuum to achieve sustained outcome improvements.

Rationale and study protocol for a multi-component Health Information Technology (HIT) screening tool for depression and post-traumatic stress disorder in the primary care setting

The prevalence rate of depression in primary care is high. Primary care providers serve as the initial point of contact for the majority of patients with depression, yet, approximately 50% of cases remain unrecognized. The under-diagnosis of depression may be further exacerbated in limited English-language proficient (LEP) populations. Language barriers may result in less discussion of patients' mental health needs and fewer referrals to mental health services, particularly given competing priorities of other medical conditions and providers' time pressures. Recent advances in Health Information Technology (HIT) may facilitate novel ways to screen for depression and other mental health disorders in LEP populations. The purpose of this paper is to describe the rationale and protocol of a clustered randomized controlled trial that will test the effectiveness of an HIT intervention that provides a multi-component approach to delivering culturally competent, mental health care in the primary care setting. The HIT intervention has four components: 1) web-based provider training, 2) multimedia electronic screening of depression and PTSD in the patients' primary language, 3) Computer generated risk assessment scores delivered directly to the provider, and 4) clinical decision support. The outcomes of the study include assessing the potential of the HIT intervention to improve screening rates, clinical detection, provider initiation of treatment, and patient outcomes for depression and post-traumatic stress disorder (PTSD) among LEP Cambodian refugees who experienced war atrocities and trauma during the Khmer Rouge. This technology has the potential to be adapted to any LEP population in order to facilitate mental health screening and treatment in the primary care setting.

The role of standardized data and terminological systems in computerized clinical decision support systems: literature review and survey

INTRODUCTION

Clinical decision support systems (CDSSs) should be seamlessly integrated with existing clinical information systems to enable automatic provision of advice at the time and place where decisions are made. It has been suggested that a lack of agreed data standards frequently hampers this integration. We performed a literature review to investigate whether CDSSs used standardized (i.e. coded or numerical) data and which terminological systems have been used to code data. We also investigated whether a lack of standardized data was considered an impediment for CDSS implementation.

METHODS

Articles reporting an evaluation of a CDSS that provided a computerized advice based on patient-specific data items were identified based on a former literature review on CDSS and on CDSS studies identified in AMIA's 'Year in Review'. Authors of these articles were contacted to check and complete the extracted data. A questionnaire among the authors of included studies was used to determine the obstacles in CDSS implementation.

RESULTS

We identified 77 articles published between 1995 and 2008. Twenty-two percent of the evaluated CDSSs used only numerical data. Fifty one percent of the CDSSs that used coded data applied an international terminology. The most frequently used international terminology were the ICD (International Classification of Diseases), used in 68% of the cases and LOINC (Logical Observation Identifiers Names and Codes) in 12% of the cases. More than half of the authors experienced barriers in CDSS implementation. In most cases these barriers were related to the lack of electronically available standardized data required to invoke or activate the CDSS.

CONCLUSION

Many CDSSs applied different terminological systems to code data. This diversity hampers the possibility of sharing and reasoning with data within different systems. The results of the survey confirm the hypothesis that data standardization is a critical success factor for CDSS development.

Features predicting the success of computerized decision support for prescribing: a systematic review of randomized controlled trials

Background

Computerized decision support systems (CDSS) are believed to have the potential to improve the quality of health care delivery, although results from high quality studies have been mixed. We conducted a systematic review to evaluate whether certain features of prescribing decision support systems (RxCDSS) predict successful implementation, change in provider behaviour, and change in patient outcomes.

Methods

A literature search of Medline, EMBASE, CINAHL and INSPEC databases (earliest entry to June 2008) was conducted to identify randomized controlled trials involving RxCDSS. Each citation was independently assessed by two reviewers for outcomes and 28 predefined system features. Statistical analysis of associations between system features and success of outcomes was planned.

Results

Of 4534 citations returned by the search, 41 met the inclusion criteria. Of these, 37 reported successful system implementations, 25 reported success at changing health care provider behaviour, and 5 noted improvements in patient outcomes. A mean of 17 features per study were mentioned. The statistical analysis could not be completed due primarily to the small number of studies and lack of diversity of outcomes. Descriptive analysis did not confirm any feature to be more prevalent in successful trials relative to unsuccessful ones for implementation, provider behaviour or patient outcomes.

Conclusion

While RxCDSSs have the potential to change health care provider behaviour, very few high quality studies show improvement in patient outcomes. Furthermore, the features of the RxCDSS associated with success (or failure) are poorly described, thus making it difficult for system design and implementation to improve.

The reliability of point-of-care prothrombin time testing. A comparison of CoaguChek S and XS INR measurements with hospital laboratory monitoring

The development of point-of-care (POC) testing devices enables patients to test their own international normalized ratio (INR) at home. However, previous studies have shown that when compared with clinical laboratory values, statistically significant differences may occur between the two methods of INR measurement. The aim of this study was to evaluate the accuracy of the CoaguChek S and XS POC meters relative to clinical laboratory measurements. As part of a randomized, crossover patient self-testing (PST) study at Cork University Hospital, patients were randomized to 6 months PST or 6 months routine care by the anticoagulation management service. During the PST arm of the study, patients measured their INR at home using the CoaguChek S or XS POC meter. External quality control was performed at enrollment, 2 months and 4 months by comparing the POC measured INR with the laboratory determined value. One hundred and fifty-one patients provided 673 paired samples. Good correlation was shown between the two methods of determination (r = 0.91), however, statistically significant differences did occur. A Bland-Altman plot illustrated good agreement of INR values between 2.0 and 3.5 INR units but there was increasing disagreement as the INR rose above 3.5. Eighty-seven per cent of all dual measurements were within the recommended 0.5 INR units of each other. This study adds to the growing evidence that POC testing is a reliable and safe alternative to hospital laboratory monitoring but highlights the importance of external quality control when these devices are used for monitoring oral anticoagulation.

A decision support system for telemedicine through the mobile telecommunications platform

In this paper we have discussed the application of artificial intelligence in telemedicine using mobile device. The main goal of our research is to develop methods and systems to collect, analyze, distribute and use medical diagnostics information from multiple knowledge sources and areas of expertise. Physicians may collect and analyze information obtained from experts worldwide with the help of a medical decision support system. In this information retrieval system, modern communication tools such as computers and mobile phones can be used efficiently. In this work we propose a medical decision support system using the general packet radio service (GPRS). GPRS, a data extension of the mobile telephony standard Global system for mobile communications (GSM) is emerging as the first true packet-switched architecture to allow mobile subscribers to benefit from high-speed transmission rates and run JAVA based applications from their mobile terminals. An academic prototype of a medical decision support system using mobile device was implemented. The results reveal that the system could find acceptance from the medical community and it could be an effective means of providing quality health care in developing countries.

The Influence of a Physician's Use of a Diagnostic Decision Aid on the Malpractice Verdicts of Mock Jurors

Background . One reason why physicians may be reluctant to use diagnostic decision aids is that such usage might increase the likelihood of an unfavorable malpractice verdict. The authors tested this hypothesis by sending a DVD of a malpractice trial to a national sample of jury-eligible adults. Methods. There were 3 independent variables: 1) the physician did or did not use a diagnostic aid, 2) the patient's symptoms either were or were not consistent with a diagnosis of probable appendicitis, and 3) the physician's decision to operate or not operate was either concordant or discordant with the severity of the patient's symptoms. Jurors rendered a verdict, and if they deemed the physician not to have met the standard of care, they indicated how punitive they felt toward the physician. Results . Mock jurors were more likely to side with the physician-defendant if he recommended an operation when there were many symptoms and refrained when there were few symptoms compared with a physician who did the converse. The use of a decision aid had no influence on this binary standard-of-care decision. Among those physicians deemed liable by the jurors, defying the aid resulted in heightened punishment compared with heeding it. Conclusion . Contrary to many physicians' fears, use of a diagnostic decision aid did not influence the likelihood of an adverse malpractice verdict. Complying with the aid's recommendation provided a measure of protection against jurors' punitiveness for those physicians deemed liable for malpractice.

Patient safety features of clinical computer systems: questionnaire survey of GP views

AIM

To investigate general practitioners' (GPs') stated knowledge, use and training needs related to the patient safety features of computerised clinical systems in England.

DESIGN

Questionnaire survey.

SUBJECTS AND SETTING

GPs from six English primary care trusts.

OUTCOME MEASURES

GPs' views on the importance of specified patient safety features on their computer system; their knowledge of the presence of specified safety features; previous training and perceived future training needs.

RESULTS

Three hundred and eighty one GPs (64.0%) completed and returned the questionnaire. Although patient safety features were considered to be an important part of their computer system by the vast majority of GPs, many were unsure as to whether the system they were currently using possessed some of the specified features. Some respondents erroneously believed that their computers would warn them about potential contraindications or if an abnormal dose frequency had been prescribed. Only a minority had received formal training on the use of their system's patient safety features.

CONCLUSIONS

Patient safety was an issue high on the agenda of this GP sample. The importance of raising GPs' awareness of both the potential use and deficiencies of the patient safety features on their systems and ensuring that appropriate training is available should not be underestimated.

Decision support system for the diagnosis of schizophrenia disorders

Clinical decision support systems are useful tools for assisting physicians to diagnose complex illnesses. Schizophrenia is a complex, heterogeneous and incapacitating mental disorder that should be detected as early as possible to avoid a most serious outcome. These artificial intelligence systems might be useful in the early detection of schizophrenia disorder. The objective of the present study was to describe the development of such a clinical decision support system for the diagnosis of schizophrenia spectrum disorders (SADDESQ). The development of this system is described in four stages: knowledge acquisition, knowledge organization, the development of a computer-assisted model, and the evaluation of the system's performance. The knowledge was extracted from an expert through open interviews. These interviews aimed to explore the expert's diagnostic decision-making process for the diagnosis of schizophrenia. A graph methodology was employed to identify the elements involved in the reasoning process. Knowledge was first organized and modeled by means of algorithms and then transferred to a computational model created by the covering approach. The performance assessment involved the comparison of the diagnoses of 38 clinical vignettes between an expert and the SADDESQ. The results showed a relatively low rate of misclassification (18-34%) and a good performance by SADDESQ in the diagnosis of schizophrenia, with an accuracy of 66-82%. The accuracy was higher when schizophreniform disorder was considered as the presence of schizophrenia disorder. Although these results are preliminary, the SADDESQ has exhibited a satisfactory performance, which needs to be further evaluated within a clinical setting.

Integrating Decision Making and Mental Health Interventions Research: Research Directions

The importance of incorporating patient and provider decision-making processes is in the forefront of the National Institute of Mental Health (NIMH) agenda for improving mental health interventions and services. Key concepts in patient decision making are highlighted within a simplified model of patient decision making that links patient-level/"micro" variables to services-level/"macro" variables via the decision-making process that is a target for interventions. The prospective agenda for incorporating decision-making concepts in mental health research includes (a) improved measures for characterizing decision-making processes that are matched to study populations, complexity, and types of decision making; (b) testing decision aids in effectiveness research for diverse populations and clinical settings; and (c) improving the understanding and incorporation of preference concepts in enhanced intervention designs.

Improving evidence based cardiac care and policy implementation over the patient journey: the potential of coronary heart disease registers

Coronary heart disease registers offer considerable potential for providing increased support for practitioners, facilitating improvements in patient care, and allowing efficient monitoring of care provision and outcomes.

Clinical decision support systems for neonatal care

BACKGROUND

Clinical decision support systems (CDSS) are computer-based information systems used to integrate clinical and patient information to provide support for decision-making in patient care. They may be useful in aiding the diagnostic process, the generation of alerts and reminders, therapy critiquing/planning, information retrieval, and image recognition and interpretation. CDSS for use in adult patients have been evaluated using randomised control trials and their results analysed in systematic reviews. There is as yet no systematic review on CDSS use in neonatal medicine.

OBJECTIVES

To examine whether the use of clinical decision support systems has an effect on 1. the mortality and morbidity of newborn infants and 2. the performance of physicians treating them

SEARCH STRATEGY

The standard search method of the Cochrane Neonatal Review Group was used. Searches were made of the Cochrane Central Register of Controlled Trials (CENTRAL, The Cochrane Library, Issue 1, 2004), MEDLINE (from 1966 to August 2004), EMBASE (1980-2004), CINAHL (1982 to August 2004) and AMED (1985 to August 2004).

SELECTION CRITERIA

Randomised or quasi-randomised controlled trials which compared the effects of CDSS versus no CDSS in the care of newborn infants. Trials which compared CDSS against other CDSS were also considered. The eligible interventions were CDSS for computerised physician order entry, computerised physiological monitoring, diagnostic systems and prognostic systems.

DATA COLLECTION AND ANALYSIS

Studies were assessed for eligibility using a standard pro forma. Methodological quality was assessed independently by the different investigators.

MAIN RESULTS

Two studies fitting the selection criteria were found for computer aided prescribing and one study for computer aided physiological monitoring.Computer-aided prescribing: one study (Cade 1997) examined the effects of computerised prescribing of parenteral nutrition ordering. No significant effects on short-term outcomes were found and longer term outcomes were not studied. The second study (Balaguer 2001) investigated the effects of a database program in aiding the calculation of neonatal drug dosages. It was found that the time taken for calculation was significantly reduced and there was a significant reduction in the number of calculation errors.Computer-aided physiological monitoring: one eligible study (Cunningham 1998) was found which examined the effects of computerised cot side physiological trend monitoring and display. There were no significant effects on mortality, volume of colloid infused, frequency of blood gases sampling (samples per day) or severe (Papile Grade 4) intraventricular haemorrhage. Published data did not permit us to analyse effects on long-term neurodevelopmental outcome.

AUTHORS' CONCLUSIONS

There are very limited data from randomised trials on which to assess the effects of clinical decision support systems in neonatal care. Further evaluation of CDSS using randomised controlled trials is warranted.

Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success

OBJECTIVE

To identify features of clinical decision support systems critical for improving clinical practice.

DESIGN

Systematic review of randomised controlled trials.

DATA SOURCES

Literature searches via Medline, CINAHL, and the Cochrane Controlled Trials Register up to 2003; and searches of reference lists of included studies and relevant reviews.

STUDY SELECTION

Studies had to evaluate the ability of decision support systems to improve clinical practice.

DATA EXTRACTION

Studies were assessed for statistically and clinically significant improvement in clinical practice and for the presence of 15 decision support system features whose importance had been repeatedly suggested in the literature.

RESULTS

Seventy studies were included. Decision support systems significantly improved clinical practice in 68% of trials. Univariate analyses revealed that, for five of the system features, interventions possessing the feature were significantly more likely to improve clinical practice than interventions lacking the feature. Multiple logistic regression analysis identified four features as independent predictors of improved clinical practice: automatic provision of decision support as part of clinician workflow (P < 0.00001), provision of recommendations rather than just assessments (P = 0.0187), provision of decision support at the time and location of decision making (P = 0.0263), and computer based decision support (P = 0.0294). Of 32 systems possessing all four features, 30 (94%) significantly improved clinical practice. Furthermore, direct experimental justification was found for providing periodic performance feedback, sharing recommendations with patients, and requesting documentation of reasons for not following recommendations.

CONCLUSIONS

Several features were closely correlated with decision support systems' ability to improve patient care significantly. Clinicians and other stakeholders should implement clinical decision support systems that incorporate these features whenever feasible and appropriate.

Computer Assisted Anticoagulant Therapy

The constantly workload increase has led to the development of Computerised Decision Support Systems (CDSS) for a better management of patient care. Many clinical situations have been investigated to verify the utility of CDSS: few have demonstrated stable effects. One area where success has been reported is the field of oral anticoagulation management. CDSS system has demonstrated to be able to improve the treatment quality in comparison to manual method. In the future scenario of oral anticoagulant management CDSS will have a pivotal part, the constant increase of patients number and their pressure on thrombosis centres had led to the development of alternative models for delivery OAT: Primary care, General Practitioner, Patient self testing and self management and the use of CDSS has been central to the decentralisation process and may be useful in maintaining the efficacy and quality of anticoagulant control. GP with the aid of CDSS are able to deliver OAT as well as expert physician of Thrombosis Centre in terms of time spent by patient in therapeutic range.

Barriers to the adoption of computerised decision support systems in general practice consultations: a qualitative study of GPs' perspectives

INTRODUCTION

Computerised decision support systems are increasingly important in primary care for the practice of evidence-based medicine and the development of shared GP-patient decision making. However, despite their emergence, such systems have not been entirely embraced by GPs. There is little qualitative research exploring practical barriers to the adoption of decision support systems in this setting.

METHOD

Qualitative interviews with 15 GPs in the West Midlands.

RESULTS

Several practical barriers were identified to the use of computerised support systems in primary care consultations. These included limitations of practitioners' IT skills, problems for GPs in understanding the risk output of systems and GP concerns about communicating risk sufficiently well to patients. Concerns over the time implications of using a system in a consultation was also identified as a barrier.

CONCLUSION

Designers of decision support systems for use in primary care consultations must account for the practical needs of users when developing computerised support systems. Systems must be acceptable to the format of a consultation, include definitions of what output means, and help facilitate dialogue between the GP and the patient.

Risk reduction in general practice: the impacts of technology

States that risk and risk management in general practice in the UK are now integral parts of the clinical effectiveness and clinical governance agenda, rather than being primarily concerned with negligence and malpractice. Notes that this has led to the introduction of a variety of technologies for improving care and thus reducing risk. Considers the frequency, nature and causes of adverse incidents in general practice, and the rise of evidence‐based practice and clinical practice guidelines, and then looks at some of those technologies currently in use. Concludes that technology seems to have a growing impact on the practice of primary care medicine and the management of clinical risk.

Learning support for the consultation: information support and decision support should be placed in an educational framework

BACKGROUND

Advances in information technology mean that it is now possible to provide contextually relevant, evidence-based information during the course of the consultation. As a consequence, the practitioner has to consider the new information (from the computer) in the situation of the present consultation and in the light of his or her own experience. This task has to be carried out in a short time, in the presence of the patient.

METHOD

Drawing on experience of the development of one decision support system, this paper places that task for the practitioner in an educational framework. We begin by reviewing theories of professional experience and knowledge and go on to look at schema theory and the role of cognitive dissonance and reflection in learning.

CONCLUSION

This paper considers the provision of real time decision support in the light of learning and the experienced practitioner. We conclude that framing the implementation of decision support in this way provides useful insights. The key process is learning by the practitioner, in the course of the consultation. This process should be supported by decision support and information support software. There are implications here for the design of such software, and also for the way in which practitioners are trained to use it.

Computerization of clinical practice in Hong Kong

The objective of this study was to assess the current level of computerization in clinical practice in Hong Kong through a population-based, physician survey conducted in 2000.A self-completed, 20-question, postal questionnaire was sent to 4850 randomly selected doctors in Hong Kong. We received 897 completed responses. Over one-third of doctors in the overall sample were already recording patient summaries, processing laboratory results and specialist reports, and preparing referral notes electronically. Patient registration (52.2%), billing systems (40.2%), appointment scheduling (39.9%), and payroll (36.9%), were the commonest administrative functions to have been computerized. Seventy per cent of doctors in solo or small-group ('individual') practices did not yet have any clinical function computerized compared with only 30.7% for those working in large, corporate organizations. Similarly, approximately two-thirds of administrative tasks in 'individual' clinics were not computerized, while corporate physicians reported a corresponding percentage of 39.3%. Younger age, male gender, specialist qualifications, more computers in the practice, higher numbers of administrative tasks already computerized, higher levels of knowledge about and positive attitudes towards computer applications in clinical practice were all positively associated with more clinical tasks already computerized in the practice. The present study has systematically documented the extent of clinical computer use in Hong Kong and identified areas for improvement as well as specific groups of physicians who might benefit from targeted efforts promoting computerization in practice.