Improving adherence to asthma clinical guidelines and discharge documentation from emergency departments: implementation of a dynamic and integrated electronic decision support system

Evaluating Pilot Implementation of 'PenCS Flu Topbar' App in Medical Practices to Improve National Immunisation Program-Funded Seasonal Influenza Vaccination in Central Queensland, Australia

BACKGROUND

The 'PenCS Flu Topbar' app was deployed in Central Queensland (CQ), Australia, medical practices through a pilot programme in March 2021.

METHODS

We evaluated the app's user experience and examined whether the introduction of 'PenCS Flu Topbar' in medical practices could improve the coverage of NIP-funded influenza vaccinations. We conducted a mixed-method study including a qualitative analysis of in-depth interviews with key end-users and a quantitative analysis of influenza vaccine administrative data.

RESULTS

'PenCS Flu Topbar' app users reported positive experiences identifying patients eligible for NIP-funded seasonal influenza vaccination. A total of 3606 NIP-funded influenza vaccinations was administered in the eight intervention practices, 14% higher than the eight control practices. NIP-funded vaccination coverage within practices was significantly higher in the intervention practices (31.2%) than in the control practices (27.3%) (absolute difference: 3.9%; 95% CI: 2.9%-5.0%; p < 0.001). The coverage was substantially higher in Aboriginal and Torres Strait Islander people aged more than 6 months, pregnant women and children aged 6 months to less than 5 years for the practices where the app was introduced when compared to control practices: incidence rate ratio (IRR) 2.4 (95% CI: 1.8-3.2), IRR 2.7 (95% CI: 1.8-4.2) and IRR 2.3 (1.8-2.9) times higher, respectively.

CONCLUSIONS

Our evaluation indicated that the 'PenCS Flu Topbar' app is useful for identifying the patients eligible for NIP-funded influenza vaccination and is likely to increase NIP-funded influenza vaccine coverage in the eligible populations. Future impact evaluation including a greater number of practices and a wider geographical area is essential.

Expectation of clinical decision support systems: a survey study among nephrologist end-users

BACKGROUND

Chronic kidney disease (CKD), a major public health problem with differing disease etiologies, leads to complications, comorbidities, polypharmacy, and mortality. Monitoring disease progression and personalized treatment efforts are crucial for long-term patient outcomes. Physicians need to integrate different data levels, e.g., clinical parameters, biomarkers, and drug information, with medical knowledge. Clinical decision support systems (CDSS) can tackle these issues and improve patient management. Knowledge about the awareness and implementation of CDSS in Germany within the field of nephrology is scarce.

PURPOSE

Nephrologists' attitude towards any CDSS and potential CDSS features of interest, like adverse event prediction algorithms, is important for a successful implementation. This survey investigates nephrologists' experiences with and expectations towards a useful CDSS for daily medical routine in the outpatient setting.

METHODS

The 38-item questionnaire survey was conducted either by telephone or as a do-it-yourself online interview amongst nephrologists across all of Germany. Answers were collected and analysed using the Electronic Data Capture System REDCap, as well as Stata SE 15.1, and Excel. The survey consisted of four modules: experiences with CDSS (M1), expectations towards a helpful CDSS (M2), evaluation of adverse event prediction algorithms (M3), and ethical aspects of CDSS (M4). Descriptive statistical analyses of all questions were conducted.

RESULTS

The study population comprised 54 physicians, with a response rate of about 80-100% per question. Most participants were aged between 51-60 years (45.1%), 64% were male, and most participants had been working in nephrology out-patient clinics for a median of 10.5 years. Overall, CDSS use was poor (81.2%), often due to lack of knowledge about existing CDSS. Most participants (79%) believed CDSS to be helpful in the management of CKD patients with a high willingness to try out a CDSS. Of all adverse event prediction algorithms, prediction of CKD progression (97.8%) and in-silico simulations of disease progression when changing, e. g., lifestyle or medication (97.7%) were rated most important. The spectrum of answers on ethical aspects of CDSS was diverse.

CONCLUSION

This survey provides insights into experience with and expectations of out-patient nephrologists on CDSS. Despite the current lack of knowledge on CDSS, the willingness to integrate CDSS into daily patient care, and the need for adverse event prediction algorithms was high.

Using Theories, Models, and Frameworks to Inform Implementation Cycles of Computerized Clinical Decision Support Systems in Tertiary Health Care Settings: Scoping Review

BACKGROUND

Computerized clinical decision support systems (CDSSs) are essential components of modern health system service delivery, particularly within acute care settings such as hospitals. Theories, models, and frameworks may assist in facilitating the implementation processes associated with CDSS innovation and its use within these care settings. These processes include context assessments to identify key determinants, implementation plans for adoption, promoting ongoing uptake, adherence, and long-term evaluation. However, there has been no prior review synthesizing the literature regarding the theories, models, and frameworks that have informed the implementation and adoption of CDSSs within hospitals.

OBJECTIVE

This scoping review aims to identify the theory, model, and framework approaches that have been used to facilitate the implementation and adoption of CDSSs in tertiary health care settings, including hospitals. The rationales reported for selecting these approaches, including the limitations and strengths, are described.

METHODS

A total of 5 electronic databases were searched (CINAHL via EBSCOhost, PubMed, Scopus, PsycINFO, and Embase) to identify studies that implemented or adopted a CDSS in a tertiary health care setting using an implementation theory, model, or framework. No date or language limits were applied. A narrative synthesis was conducted using full-text publications and abstracts. Implementation phases were classified according to the "Active Implementation Framework stages": exploration (feasibility and organizational readiness), installation (organizational preparation), initial implementation (initiating implementation, ie, training), full implementation (sustainment), and nontranslational effectiveness studies.

RESULTS

A total of 81 records (42 full text and 39 abstracts) were included. Full-text studies and abstracts are reported separately. For full-text studies, models (18/42, 43%), followed by determinants frameworks (14/42,33%), were most frequently used to guide adoption and evaluation strategies. Most studies (36/42, 86%) did not list the limitations associated with applying a specific theory, model, or framework.

CONCLUSIONS

Models and related quality improvement methods were most frequently used to inform CDSS adoption. Models were not typically combined with each other or with theory to inform full-cycle implementation strategies. The findings highlight a gap in the application of implementation methods including theories, models, and frameworks to facilitate full-cycle implementation strategies for hospital CDSSs.

Monitoring the Implementation of Tobacco Cessation Support Tools: Using Novel Electronic Health Record Activity Metrics

BACKGROUND

Clinical decision support (CDS) tools in electronic health records (EHRs) are often used as core strategies to support quality improvement programs in the clinical setting. Monitoring the impact (intended and unintended) of these tools is crucial for program evaluation and adaptation. Existing approaches for monitoring typically rely on health care providers' self-reports or direct observation of clinical workflows, which require substantial data collection efforts and are prone to reporting bias.

OBJECTIVE

This study aims to develop a novel monitoring method leveraging EHR activity data and demonstrate its use in monitoring the CDS tools implemented by a tobacco cessation program sponsored by the National Cancer Institute's Cancer Center Cessation Initiative (C3I).

METHODS

We developed EHR-based metrics to monitor the implementation of two CDS tools: (1) a screening alert reminding clinic staff to complete the smoking assessment and (2) a support alert prompting health care providers to discuss support and treatment options, including referral to a cessation clinic. Using EHR activity data, we measured the completion (encounter-level alert completion rate) and burden (the number of times an alert was fired before completion and time spent handling the alert) of the CDS tools. We report metrics tracked for 12 months post implementation, comparing 7 cancer clinics (2 clinics implemented the screening alert and 5 implemented both alerts) within a C3I center, and identify areas to improve alert design and adoption.

RESULTS

The screening alert fired in 5121 encounters during the 12 months post implementation. The encounter-level alert completion rate (clinic staff acknowledged completion of screening in EHR: 0.55; clinic staff completed EHR documentation of screening results: 0.32) remained stable over time but varied considerably across clinics. The support alert fired in 1074 encounters during the 12 months. Providers acted upon (ie, not postponed) the support alert in 87.3% (n=938) of encounters, identified a patient ready to quit in 12% (n=129) of encounters, and ordered a referral to the cessation clinic in 2% (n=22) of encounters. With respect to alert burden, on average, both alerts fired over 2 times (screening alert: 2.7; support alert: 2.1) before completion; time spent postponing the screening alert was similar to completing (52 vs 53 seconds) the alert, and time spent postponing the support alert was more than completing (67 vs 50 seconds) the alert per encounter. These findings inform four areas where the alert design and use can be improved: (1) improving alert adoption and completion through local adaptation, (2) improving support alert efficacy by additional strategies including training in provider-patient communication, (3) improving the accuracy of tracking for alert completion, and (4) balancing alert efficacy with the burden.

CONCLUSIONS

EHR activity metrics were able to monitor the success and burden of tobacco cessation alerts, allowing for a more nuanced understanding of potential trade-offs associated with alert implementation. These metrics can be used to guide implementation adaptation and are scalable across diverse settings.

Effectiveness of a computerized clinical decision support system for prevention of glucocorticoid-induced osteoporosis

Glucocorticoids are widely used for a variety of diseases, but the prevention of glucocorticoid-induced osteoporosis is sometimes neglected. Therefore, the effectiveness of a computerized clinical decision support system (CDSS) to improve the performance rate of preventive care for glucocorticoid-induced osteoporosis was evaluated. We conducted a prospective cohort study of outpatients who used glucocorticoids for three months or longer and who met the indication for preventive care based on a guideline. The CDSS recommended bisphosphonate (BP) prescription and bone mineral density (BMD) testing based on the risk of osteoporosis. The observation period was one year (phase 1: October 2017-September 2018) before implementation and the following one year (phase 2: October 2018-September 2019) after implementation of the CDSS. Potential alerts were collected without displaying them during phase 1, and the alerts were displayed during phase 2. We measured BP prescriptions and BMD testing for long-term prescription of glucocorticoids. A total of 938 patients (phase 1, 457 patients; phase 2, 481 patients) were included, and the baseline characteristics were similar between the phases. The median age was 71 years, and men accounted for 51%. The primary disease for prescription of glucocorticoids was rheumatic disease (28%), followed by hematologic diseases (18%). The prevalence of patients who needed an alert for BP prescription (67% vs. 63%, P = 0.24) and the acceptance rate of BP prescription (16% vs. 19%, P = 0.33) were similar between the phases. The number of patients who had orders for BMD testing was significantly increased (4% vs. 24%, P < 0.001) after CDSS implementation. The number of patients who needed an alert for BMD testing was significantly decreased from 93% in phase 1 to 87% in phase 2 (P = 0.004). In conclusion, the CDSS significantly increased BMD testing in patients with a higher risk of glucocorticoid-induced osteoporosis, but did not increase BP prescription.

Evaluation of the impact of enhanced virtual forms and gamification on intervention identification in a pharmacist-led ambulatory care clinic

Background

Adoption of healthcare technology in the ambulatory care setting is nearly universal. Clinical decision support system (CDSS)2 technologies improve patient care through the identification of additional care opportunities. With the movement from paper-based to electronic clinical intake forms, the opportunity to improve identification of gaps in care utilizing CDSS in the ambulatory care setting exists.

Objective

To evaluate the impact of CDSS-enhanced digital intake forms, with- and without aspects of gamification, on the identification of intervention opportunities in an ambulatory care pharmacy setting.

Methods

Patients were invited to complete visit intake paperwork via virtual forms as part of a CDSS-enhanced mobile application designed to identify potential interventions based on patient age, sex, disease state(s), and user-provided information. Patients were randomized to receive optional patient-specific health questions 1) with or 2) without elements of gamification. Gamification elements included trivia questions, fun facts, and the chance to win a prize. A retrospective review was used to assess interventions identified for a random sample of patients seen within the same time frame who did not utilize the mobile application. Interventions were compared across groups utilizing ANOVA. t-tests were used for a subgroup analysis.

Results

From January to May 2019, 353 potential interventions were identified for 220 study participants. 0.44 (±0.82), 1.8 (±2.0) and 2.1 (±1.8) interventions per participant were identified for the control, virtual forms, and virtual forms + gamification groups, respectively. Significant differences in intervention identification across groups were found using a one-way ANOVA (F = 17.46, p < .001). Post hoc analysis demonstrated a significant difference in interventions identified for those completing 50–100% (n = 32) and those completing less than 50% (n = 18; p < .001) of the optional health questions in the virtual forms + gamification group.

Conclusions

Utilization of CDSS-enhanced clinical intake forms increased identification of potential interventions, though gamification did not significantly impact this identification.

ERS/EAACI statement on adherence to international adult asthma guidelines

Guidelines aim to standardise and optimise asthma diagnosis and management. Nevertheless, adherence to guidelines is suboptimal and may vary across different healthcare professional (HCP) groups.Further to these concerns, this European Respiratory Society (ERS)/European Academy of Allergy and Clinical Immunology (EAACI) statement aims to: 1) evaluate the understanding of and adherence to international asthma guidelines by HCPs of different specialties via an international online survey; and 2) assess strategies focused at improving implementation of guideline-recommended interventions, and compare process and clinical outcomes in patients managed by HCPs of different specialties via systematic reviews.The online survey identified discrepancies between HCPs of different specialties which may be due to poor dissemination or lack of knowledge of the guidelines but also a reflection of the adaptations made in different clinical settings, based on available resources. The systematic reviews demonstrated that multifaceted quality improvement initiatives addressing multiple challenges to guidelines adherence are most effective in improving guidelines adherence. Differences in outcomes between patients managed by generalists or specialists should be further evaluated.Guidelines need to consider the heterogeneity of real-life settings for asthma management and tailor their recommendations accordingly. Continuous, multifaceted quality improvement processes are required to optimise and maintain guidelines adherence. Validated referral pathways for uncontrolled asthma or uncertain diagnosis are needed.

Design, development, and deployment of an indication- and kidney function-based decision support tool to optimize treatment and reduce medication dosing errors

Delivering clinical decision support (CDS) at the point of care has long been considered a major advantage of computerized physician order entry (CPOE). Despite the widespread implementation of CPOE, medication ordering errors and associated adverse events still occur at an unacceptable level. Previous attempts at indication- and kidney function-based dosing have mostly employed intrusive CDS, including interruptive alerts with poor usability. This descriptive work describes the design, development, and deployment of the Adult Dosing Methodology (ADM) module, a novel CDS tool that provides indication- and kidney-based dosing at the time of order entry. Inclusion of several antimicrobials in the initial set of medications allowed for the additional goal of optimizing therapy duration for appropriate antimicrobial stewardship. The CDS aims to decrease order entry errors and burden on providers by offering automatic dose and frequency recommendations, integration within the native electronic health record, and reasonable knowledge maintenance requirements. Following implementation, early utilization demonstrated high acceptance of automated recommendations, with up to 96% of provided automated recommendations accepted by users.

Following Guidelines for Drug-Resistant Tuberculosis: “Yes, it’s a challenge”

Background

Drug-resistant tuberculosis (DR-TB) is a major contributor to antimicrobial resistance (AMR) globally and is projected to be responsible for up to a quarter of AMR-associated deaths in the future. Management of DR-TB is increasingly decentralised to primary healthcare settings, and simultaneously becoming more complex due to a growing range of treatment options (e.g. novel agents, shorter regimens). This is reflected in the numerous recent updates to international guidelines and as such understanding the barriers and enablers to how healthcare workers access and use guidelines is vital.

Materials and Methods

We used an established psychological framework – the theoretical domains framework (TDF) – to construct and analyse an online survey and focus groups to explore healthcare workers current use of DR-TB guidelines in South Africa. We aimed to identify barriers and enablers with which to direct future attempts at improving guideline use.

Results

There were 19 responses to the online survey and 14 participants in two focus groups. 28% used the most up-to-date national guidelines, 79% accessed guidelines primarily on electronic devices. The TDF domains of ‘Social Influences’ (mean Likert score = 4.3) and ‘Beliefs about Consequences’ (4.2) were key enablers, with healthcare workers encouraged to use guidelines and also recognising the value in doing so. ‘Environmental Resources’ (3.7) and ‘Knowledge’ (3.3) were key barriers with limited, or variable access to guidelines and lack of confidence using them being notable issues. This was most noted for certain subgroups: children, HIV co-infected, pregnant women (2.7).

Discussion

Current use of DR-TB guidelines in South Africa is suboptimal. Planned interventions should focus on overcoming the identified key barriers and might include an increased use of digital tools.

An overview of clinical decision support systems: benefits, risks, and strategies for success

Computerized clinical decision support systems, or CDSS, represent a paradigm shift in healthcare today. CDSS are used to augment clinicians in their complex decision-making processes. Since their first use in the 1980s, CDSS have seen a rapid evolution. They are now commonly administered through electronic medical records and other computerized clinical workflows, which has been facilitated by increasing global adoption of electronic medical records with advanced capabilities. Despite these advances, there remain unknowns regarding the effect CDSS have on the providers who use them, patient outcomes, and costs. There have been numerous published examples in the past decade(s) of CDSS success stories, but notable setbacks have also shown us that CDSS are not without risks. In this paper, we provide a state-of-the-art overview on the use of clinical decision support systems in medicine, including the different types, current use cases with proven efficacy, common pitfalls, and potential harms. We conclude with evidence-based recommendations for minimizing risk in CDSS design, implementation, evaluation, and maintenance.

Collaborative writing applications in healthcare: effects on professional practice and healthcare outcomes

BACKGROUND

Collaborative writing applications (CWAs), such as wikis and Google Documents, hold the potential to improve the use of evidence in both public health and healthcare. Although a growing body of literature indicates that CWAs could have positive effects on healthcare, such as improved collaboration, behavioural change, learning, knowledge management, and adaptation of knowledge to local context, this has never been assessed systematically. Moreover, several questions regarding safety, reliability, and legal aspects exist.

OBJECTIVES

The objectives of this review were to (1) assess the effects of the use of CWAs on process (including the behaviour of healthcare professionals) and patient outcomes, (2) critically appraise and summarise current evidence on the use of resources, costs, and cost-effectiveness associated with CWAs to improve professional practices and patient outcomes, and (3) explore the effects of different CWA features (e.g. open versus closed) and different implementation factors (e.g. the presence of a moderator) on process and patient outcomes.

SEARCH METHODS

We searched CENTRAL, MEDLINE, Embase, and 11 other electronic databases. We searched the grey literature, two trial registries, CWA websites, individual journals, and conference proceedings. We also contacted authors and experts in the field. We did not apply date or language limits. We searched for published literature to August 2016, and grey literature to September 2015.

SELECTION CRITERIA

We included randomised controlled trials (RCTs), non-randomised controlled trials (NRCTs), controlled before-and-after (CBA) studies, interrupted time series (ITS) studies, and repeated measures studies (RMS), in which CWAs were used as an intervention to improve the process of care, patient outcomes, or healthcare costs.

DATA COLLECTION AND ANALYSIS

Teams of two review authors independently assessed the eligibility of studies. Disagreements were resolved by discussion, and when consensus was not reached, a third review author was consulted.

MAIN RESULTS

We screened 11,993 studies identified from the electronic database searches and 346 studies from grey literature sources. We analysed the full text of 99 studies. None of the studies met the eligibility criteria; two potentially relevant studies are ongoing.

AUTHORS' CONCLUSIONS

While there is a high number of published studies about CWAs, indicating that this is an active field of research, additional studies using rigorous experimental designs are needed to assess their impact and cost-effectiveness on process and patient outcomes.

The use of computerized clinical decision support systems in emergency care: a substantive review of the literature

OBJECTIVES

: This paper provides a substantive review of international literature evaluating the impact of computerized clinical decision support systems (CCDSSs) on the care of emergency department (ED) patients.

MATERIAL AND METHODS

: A literature search was conducted using Medline, Cumulative Index of Nursing and Allied Health Literature (CINAHL), Embase electronic resources, and gray literature. Studies were selected if they compared the use of a CCDSS with usual care in a face-to-face clinical interaction in an ED.

RESULTS

: Of the 23 studies included, approximately half demonstrated a statistically significant positive impact on aspects of clinical care with the use of CCDSSs. The remaining studies showed small improvements, mainly around documentation. However, the methodological quality of the studies was poor, with few or no controls to mitigate against confounding variables. The risk of bias was high in all but 6 studies.

DISCUSSION

: The ED environment is complex and does not lend itself to robust quantitative designs such as randomized controlled trials. The quality of the research in ∼75% of the studies was poor, and therefore conclusions cannot be drawn from these results. However, the studies with a more robust design show evidence of the positive impact of CCDSSs on ED patient care.

CONCLUSION

This is the first review to consider the role of CCDSSs in emergency care and expose the research in this area. The role of CCDSSs in emergency care may provide some solutions to the current challenges in EDs, but further high-quality research is needed to better understand what technological solutions can offer clinicians and patients.

A systematic review of the implementation and impact of asthma protocols

BACKGROUND

Asthma is one of the most common childhood illnesses. Guideline-driven clinical care positively affects patient outcomes for care. There are several asthma guidelines and reminder methods for implementation to help integrate them into clinical workflow. Our goal is to determine the most prevalent method of guideline implementation; establish which methods significantly improved clinical care; and identify the factors most commonly associated with a successful and sustainable implementation.

METHODS

PUBMED (MEDLINE), OVID CINAHL, ISI Web of Science, and EMBASE.

STUDY SELECTION

Studies were included if they evaluated an asthma protocol or prompt, evaluated an intervention, a clinical trial of a protocol implementation, and qualitative studies as part of a protocol intervention. Studies were excluded if they had non-human subjects, were studies on efficacy and effectiveness of drugs, did not include an evaluation component, studied an educational intervention only, or were a case report, survey, editorial, letter to the editor.

RESULTS

From 14,478 abstracts, we included 101 full-text articles in the analysis. The most frequent study design was pre-post, followed by prospective, population based case series or consecutive case series, and randomized trials. Paper-based reminders were the most frequent with fully computerized, then computer generated, and other modalities. No study reported a decrease in health care practitioner performance or declining patient outcomes. The most common primary outcome measure was compliance with provided or prescribing guidelines, key clinical indicators such as patient outcomes or quality of life, and length of stay.

CONCLUSIONS

Paper-based implementations are by far the most popular approach to implement a guideline or protocol. The number of publications on asthma protocol reminder systems is increasing. The number of computerized and computer-generated studies is also increasing. Asthma guidelines generally improved patient care and practitioner performance regardless of the implementation method.

A guideline-based approach to asthma management

The management of asthma has dramatically improved in recent years because of a better understanding of the disease and an organized approach to therapy. All of the various components and tools for evaluating individuals with asthma may be found in the Expert Panel Report Guidelines by the National Heart, Lung, and Blood Institute, initially published in 2007. These comprehensive guidelines help health care professionals care for individuals with asthma throughout their lifespan. This article will assist the health care provider to use these evidence-based guidelines.

Decision support system in prehospital care: a randomized controlled simulation study

INTRODUCTION

Prehospital emergency medicine is a challenging discipline characterized by a high level of acuity, a lack of clinical information and a wide range of clinical conditions. These factors contribute to the fact that prehospital emergency medicine is a high-risk discipline in terms of medical errors. Prehospital use of Computerized Decision Support System (CDSS) may be a way to increase patient safety but very few studies evaluate the effect in prehospital care. The aim of the present study is to evaluate a CDSS.

METHODS

In this non-blind block randomized, controlled trial, 60 ambulance nurses participated, randomized into 2 groups. To compensate for an expected learning effect the groups was further divided in two groups, one started with case A and the other group started with case B. The intervention group had access to and treated the two simulated patient cases with the aid of a CDSS. The control group treated the same cases with the aid of a regional guideline in paper format. The performance that was measured was compliance with regional prehospital guidelines and On Scene Time (OST).

RESULTS

There was no significant difference in the two group's characteristics. The intervention group had a higher compliance in the both cases, 80% vs. 60% (p<0.001) but the control group was complete the cases in the half of the time compare to the intervention group (p<0.001).

CONCLUSION

The results indicate that this CDSS increases the ambulance nurses' compliance with regional prehospital guidelines but at the expense of an increase in OST.

Accuracy of a computerized clinical decision-support system for asthma assessment and management

OBJECTIVE

To evaluate the accuracy of a computerized clinical decision-support system (CDSS) designed to support assessment and management of pediatric asthma in a subspecialty clinic.

DESIGN

Cohort study of all asthma visits to pediatric pulmonology from January to December, 2009.

MEASUREMENTS

CDSS and physician assessments of asthma severity, control, and treatment step.

RESULTS

Both the clinician and the computerized CDSS generated assessments of asthma control in 767/1032 (74.3%) return patients, assessments of asthma severity in 100/167 (59.9%) new patients, and recommendations for treatment step in 66/167 (39.5%) new patients. Clinicians agreed with the CDSS in 543/767 (70.8%) of control assessments, 37/100 (37%) of severity assessments, and 19/66 (29%) of step recommendations. External review classified 72% of control disagreements (21% of all control assessments), 56% of severity disagreements (37% of all severity assessments), and 76% of step disagreements (54% of all step recommendations) as CDSS errors. The remaining disagreements resulted from pulmonologist error or ambiguous guidelines. Many CDSS flaws, such as attributing all 'cough' to asthma, were easily remediable. Pediatric pulmonologists failed to follow guidelines in 8% of return visits and 18% of new visits.

LIMITATIONS

The authors relied on chart notes to determine clinical reasoning. Physicians may have changed their assessments after seeing CDSS recommendations.

CONCLUSIONS

A computerized CDSS performed relatively accurately compared to clinicians for assessment of asthma control but was inaccurate for treatment. Pediatric pulmonologists failed to follow guideline-based care in a small proportion of patients.

Development of a prototype clinical decision support tool for osteoporosis disease management: a qualitative study of focus groups

BACKGROUND

Osteoporosis affects over 200 million people worldwide, and represents a significant cost burden. Although guidelines are available for best practice in osteoporosis, evidence indicates that patients are not receiving appropriate diagnostic testing or treatment according to guidelines. The use of clinical decision support systems (CDSSs) may be one solution because they can facilitate knowledge translation by providing high-quality evidence at the point of care. Findings from a systematic review of osteoporosis interventions and consultation with clinical and human factors engineering experts were used to develop a conceptual model of an osteoporosis tool. We conducted a qualitative study of focus groups to better understand physicians' perceptions of CDSSs and to transform the conceptual osteoporosis tool into a functional prototype that can support clinical decision making in osteoporosis disease management at the point of care.

METHODS

The conceptual design of the osteoporosis tool was tested in 4 progressive focus groups with family physicians and general internists. An iterative strategy was used to qualitatively explore the experiences of physicians with CDSSs; and to find out what features, functions, and evidence should be included in a working prototype. Focus groups were conducted using a semi-structured interview guide using an iterative process where results of the first focus group informed changes to the questions for subsequent focus groups and to the conceptual tool design. Transcripts were transcribed verbatim and analyzed using grounded theory methodology.

RESULTS

Of the 3 broad categories of themes that were identified, major barriers related to the accuracy and feasibility of extracting bone mineral density test results and medications from the risk assessment questionnaire; using an electronic input device such as a Tablet PC in the waiting room; and the importance of including well-balanced information in the patient education component of the osteoporosis tool. Suggestions for modifying the tool included the addition of a percentile graph showing patients' 10-year risk for osteoporosis or fractures, and ensuring that the tool takes no more than 5 minutes to complete.

CONCLUSIONS

Focus group data revealed the facilitators and barriers to using the osteoporosis tool at the point of care so that it can be optimized to aid physicians in their clinical decision making.

Are we failing to document adequate smoking histories? A brief review 1999-2009

BACKGROUND

Documenting a detailed smoking history is of obvious importance. Failure to adequately document the smoking history may result in the misdiagnosis and management of asthma, and may be associated with a deficiency of care in patients with cardiovascular disease and several other common diseases.

SCOPE

The purpose of this article is to review the evidence over the past decade that demonstrates inadequate documentation of smoking history. A literature search of English language journals from 1999 to 2009 was completed using several databases, including PubMed, MEDLINE, EMBASE, and SCOPUS.

FINDINGS

Fourteen studies demonstrated inadequate documentation of smoking histories by primary care clinicians, specialists, residents, and medical students. Failure to document smoking histories was observed in patients with conditions such as heart failure, coronary artery disease, and asthma. Electronic decision support systems and simple medical record reminders were effective in improving the documentation of smoking histories.

CONCLUSIONS

Failure to adequately document the smoking history appears to be common. Strategies such as electronic decision support systems are needed to correct this problem in order for patients to receive optimal therapy for their appropriate diagnoses.