Francesca Ruggiero

Effectiveness of Computerized Decision Support Systems Linked to Electronic Health Records: A Systematic Review and Meta-Analysis

We systematically reviewed randomized controlled trials (RCTs) assessing the effectiveness of computerized decision support systems (CDSSs) featuring rule- or algorithm-based software integrated with electronic health records (EHRs) and evidence-based knowledge. We searched MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, and Cochrane Database of Abstracts of Reviews of Effects. Information on system design, capabilities, acquisition, implementation context, and effects on mortality, morbidity, and economic outcomes were extracted. Twenty-eight RCTs were included. CDSS use did not affect mortality (16 trials, 37395 patients; 2282 deaths; risk ratio [RR]u2009=u20090.96; 95% confidence interval [CI]u2009=u20090.85, 1.08; I(2)u2009=u200941%). A statistically significant effect was evident in the prevention of morbidity, any disease (9 RCTs; 13868 patients; RRu2009=u20090.82; 95% CIu2009=u20090.68, 0.99; I(2)u2009=u200964%), but selective outcome reporting or publication bias cannot be excluded. We observed differences for costs and health service utilization, although these were often small in magnitude. Across clinical settings, new generation CDSSs integrated with EHRs do not affect mortality and might moderately improve morbidity outcomes.

Barriers and facilitators to the uptake of computerized clinical decision support systems in specialty hospitals: protocol for a qualitative cross-sectional study

BackgroundComputerized clinical decision support systems (CDSSs) have been shown to improve the efficiency and quality of patient care by connecting healthcare professionals with high quality, evidence-based information at the point-of-care. The mere provision of CDSSs, however, does not guarantee their uptake. Rather, individual and institutional perceptions can foster or inhibit the integration of CDSSs into routine clinical workflow. Current studies exploring health professionals’ perceptions of CDSSs focus primarily on technical and usability issues, overlooking the social or cultural variables as well as broader administrative or organizational roles that may influence CDSS adoption. Moreover, there is a lack of data on the evolution of perceived barriers or facilitators to CDSS uptake across different stages of implementation.MethodsWe will conduct a qualitative, cross-sectional study in three Italian specialty hospitals involving frontline physicians, nurses, information technology staff, and members of the hospital board of directors. We will use semi-structured interviews following the Grounded Theory framework, progressively recruiting participants until no new information is gained from the interviews.DiscussionCDSSs are likely to become an integral and diffuse part of clinical practice. Various factors must be considered when planning their introduction in healthcare settings. The findings of this study will guide the development of strategies to facilitate the successful integration of CDSSs into the regular clinical workflow. The evaluation of diverse health professionals across multiple hospital settings in different stages of CDSS uptake will better capture the complexity of roles and contextual factors affecting CDSS uptake.

Implementing an evidence-based computerized decision support system to improve patient care in a general hospital: the CODES study protocol for a randomized controlled trial

BackgroundComputerized decision support systems (CDSSs) are information technology-based software that provide health professionals with actionable, patient-specific recommendations or guidelines for disease diagnosis, treatment, and management at the point-of-care. These messages are intelligently filtered to enhance the health and clinical care of patients. CDSSs may be integrated with patient electronic health records (EHRs) and evidence-based knowledge.Methods/designWe designed a pragmatic randomized controlled trial to evaluate the effectiveness of patient-specific, evidence-based reminders generated at the point-of-care by a multi-specialty decision support system on clinical practice and the quality of care. We will include all the patients admitted to the internal medicine department of one large general hospital. The primary outcome is the rate at which medical problems, which are detected by the decision support software and reported through the reminders, are resolved (i.e., resolution rates). Secondary outcomes are resolution rates for reminders specific to venous thromboembolism (VTE) prevention, in-hospital all causes and VTE-related mortality, and the length of hospital stay during the study period.DiscussionThe adoption of CDSSs is likely to increase across healthcare systems due to growing concerns about the quality of medical care and discrepancy between real and ideal practice, continuous demands for a meaningful use of health information technology, and the increasing use of and familiarity with advanced technology among new generations of physicians. The results of our study will contribute to the current understanding of the effectiveness of CDSSs in primary care and hospital settings, thereby informing future research and healthcare policy questions related to the feasibility and value of CDSS use in healthcare systems. This trial is seconded by a specialty trial randomizing patients in an oncology setting (ONCO-CODES).Trial registrationClinicalTrials.gov, https://clinicaltrials.gov/ct2/show/NCT02577198?term=NCT02577198&rank=1

Implementing an evidence-based computerized decision support system linked to electronic health records to improve care for cancer patients: The ONCO-CODES study protocol for a randomized controlled trial

BackgroundComputerized decision support systems (CDSSs) are computer programs that provide doctors with person-specific, actionable recommendations, or management options that are intelligently filtered or presented at appropriate times to enhance health care. CDSSs might be integrated with patient electronic health records (EHRs) and evidence-based knowledge.Methods/DesignThe Computerized DEcision Support in ONCOlogy (ONCO-CODES) trial is a pragmatic, parallel group, randomized controlled study with 1:1 allocation ratio. The trial is designed to evaluate the effectiveness on clinical practice and quality of care of a multi-specialty collection of patient-specific reminders generated by a CDSS in the IRCCS Istituto Scientifico Romagnolo per lo Studio e la Curaxa0dei Tumori (IRST) hospital. We hypothesize that the intervention can increase clinician adherence to guidelines and, eventually, improve the quality of care offered to cancer patients. The primary outcome is the rate at which the issues reported by the reminders are resolved, aggregating specialty and primary care reminders. We will include all the patients admitted to hospital services. All analyses will follow the intention-to-treat principle.DiscussionThe results of our study will contribute to the current understanding of the effectiveness of CDSSs in cancer hospitals, thereby informing healthcare policy about the potential role of CDSS use. Furthermore, the study will inform whether CDSS may facilitate the integration of primary care in cancer settings, known to be usually limited. The increasing use of and familiarity with advanced technology among new generations of physicians may support integrated approaches to be tested in pragmatic studies determining the optimal interface between primary and oncology care.Trial registrationClinicalTrials.gov, NCT02645357

What hinders the uptake of computerized decision support systems in hospitals? A qualitative study and framework for implementation

BackgroundAdvanced Computerized Decision Support Systems (CDSSs) assist clinicians in their decision-making process, generating recommendations based on up-to-date scientific evidence. Although this technology has the potential to improve the quality of patient care, its mere provision does not guarantee uptake: even where CDSSs are available, clinicians often fail to adopt their recommendations. This study examines the barriers and facilitators to the uptake of an evidence-based CDSS as perceived by diverse health professionals in hospitals at different stages of CDSS adoption.MethodsQualitative study conducted as part of a series of randomized controlled trials of CDSSs. The sample includes two hospitals using a CDSS and two hospitals that aim to adopt a CDSS in the future. We interviewed physicians, nurses, information technology staff, and members of the boards of directors (nxa0=xa030). We used a constant comparative approach to develop a framework for guiding implementation.ResultsWe identified six clusters of experiences of, and attitudes towards CDSSs, which we label as “positions.” The six positions represent a gradient of acquisition of control over CDSSs (from low to high) and are characterized by different types of barriers to CDSS uptake. The most severe barriers (prevalent in the first positions) include clinicians’ perception that the CDSSs may reduce their professional autonomy or may be used against them in the event of medical-legal controversies. Moving towards the last positions, these barriers are substituted by technical and usability problems related to the technology interface. When all barriers are overcome, CDSSs are perceived as a working tool at the service of its users, integrating clinicians’ reasoning and fostering organizational learning.ConclusionsBarriers and facilitators to the use of CDSSs are dynamic and may exist prior to their introduction in clinical contexts; providing a static list of obstacles and facilitators, irrespective of the specific implementation phase and context, may not be sufficient or useful to facilitate uptake. Factors such as clinicians’ attitudes towards scientific evidences and guidelines, the quality of inter-disciplinary relationships, and an organizational ethos of transparency and accountability need to be considered when exploring the readiness of a hospital to adopt CDSSs.

Sistemi computerizzati di supporto alle decisioni cliniche: l’EBM al letto del malato

Introduction One of the aims of Evidence-Based Medicine is to improve quality and appropriateness of care by the expedition of the knowledge transfer process. Computerized Decision Support Systems (CDSSs) are computer programs that provide alerts to the prescribing doctor directly at the moment of medical examination. In fact, alerts are integrated within the single patient electronic health record. CDSS based on the best available and updated evidence and guidelines may be an efficient tool to facilitate the transfer of the latest results from clinical research directly at the bedside, thus supporting decision-making. Objectives The CODES (COmputerized DEcision Support) trial is a research program funded by the Italian Ministry of Health and the Lombardy Region. It aims to evaluate the feasibility of the implementation of a CDSS at the hospital level and to assess its efficacy in daily clinical practice. Methods The CODES project includes two pragmatic RCTs testing a CDSS (i.e. the EBMeDS - MediDSS) in two large Italian hospitals: the first is a general hospital in Vimercate (Lombardy), the second is an oncologic research center in Meldola (Emilia Romagna). The CDSS supports a full spectrum of decisions: therapy, drug interactions, diagnosis, and management of health care services are covered by a hundreds of reminders. However only few reminders are activated per patient, highlighting crucial problems in the delivery of high-quality care. The two trials have similar design and primary outcome, the rate at which alerts detected by the software are resolved by a decision of the clinicians. The project also includes the assessment of barriers and facilitators in the adoption of these new technologies by hospital staff members and the retrospective evaluation of the repeated risks in prescription habits. Results The trials are ongoing and currently more than 10,000 patients have been randomized. The qualitative analysis revealed a progressive shift in the perception of the tool. Doctors are now seeing it as a trusted second opinion, available 24/7, which is tailored to the needs of the patient. The retrospective analysis showed the opportunity to achieve a better healthcare quality through an active risk management. Aggregating data from whole hospitals emerge rare drug interactions that otherwise would not be recognizable. Discussion CDSS are promising tools to support clinicians in everyday practice. They can be used as a real time app or to perform retrospective analyses. These data can provide unique resources to hospital management.INTRODUCTIONnOne of the aims of Evidence-Based Medicine is to improve quality and appropriateness of care by the expedition of the knowledge transfer process. Computerized Decision Support Systems (CDSSs) are computer programs that provide alerts to the prescribing doctor directly at the moment of medical examination. In fact, alerts are integrated within the single patient electronic health record. CDSS based on the best available and updated evidence and guidelines may be an efficient tool to facilitate the transfer of the latest results from clinical research directly at the bedside, thus supporting decision-making.nnnOBJECTIVESnThe CODES (COmputerized DEcision Support) trial is a research program funded by the Italian Ministry of Health and the Lombardy Region. It aims to evaluate the feasibility of the implementation of a CDSS at the hospital level and to assess its efficacy in daily clinical practice.nnnMETHODSnThe CODES project includes two pragmatic RCTs testing a CDSS (i.e. the EBMeDS - MediDSS) in two large Italian hospitals: the first is a general hospital in Vimercate (Lombardy), the second is an oncologic research center in Meldola (Emilia Romagna). The CDSS supports a full spectrum of decisions: therapy, drug interactions, diagnosis, and management of health care services are covered by a hundreds of reminders. However only few reminders are activated per patient, highlighting crucial problems in the delivery of high-quality care. The two trials have similar design and primary outcome, the rate at which alerts detected by the software are resolved by a decision of the clinicians. The project also includes the assessment of barriers and facilitators in the adoption of these new technologies by hospital staff members and the retrospective evaluation of the repeated risks in prescription habits.nnnRESULTSnThe trials are ongoing and currently more than 10,000 patients have been randomized. The qualitative analysis revealed a progressive shift in the perception of the tool. Doctors are now seeing it as a trusted second opinion, available 24/7, which is tailored to the needs of the patient. The retrospective analysis showed the opportunity to achieve a better healthcare quality through an active risk management. Aggregating data from whole hospitals emerge rare drug interactions that otherwise would not be recognizable.nnnDISCUSSIONnCDSS are promising tools to support clinicians in everyday practice. They can be used as a real time app or to perform retrospective analyses. These data can provide unique resources to hospital management.

[Computerized decision support systems: EBM at the bedside].

Introduction One of the aims of Evidence-Based Medicine is to improve quality and appropriateness of care by the expedition of the knowledge transfer process. Computerized Decision Support Systems (CDSSs) are computer programs that provide alerts to the prescribing doctor directly at the moment of medical examination. In fact, alerts are integrated within the single patient electronic health record. CDSS based on the best available and updated evidence and guidelines may be an efficient tool to facilitate the transfer of the latest results from clinical research directly at the bedside, thus supporting decision-making. Objectives The CODES (COmputerized DEcision Support) trial is a research program funded by the Italian Ministry of Health and the Lombardy Region. It aims to evaluate the feasibility of the implementation of a CDSS at the hospital level and to assess its efficacy in daily clinical practice. Methods The CODES project includes two pragmatic RCTs testing a CDSS (i.e. the EBMeDS - MediDSS) in two large Italian hospitals: the first is a general hospital in Vimercate (Lombardy), the second is an oncologic research center in Meldola (Emilia Romagna). The CDSS supports a full spectrum of decisions: therapy, drug interactions, diagnosis, and management of health care services are covered by a hundreds of reminders. However only few reminders are activated per patient, highlighting crucial problems in the delivery of high-quality care. The two trials have similar design and primary outcome, the rate at which alerts detected by the software are resolved by a decision of the clinicians. The project also includes the assessment of barriers and facilitators in the adoption of these new technologies by hospital staff members and the retrospective evaluation of the repeated risks in prescription habits. Results The trials are ongoing and currently more than 10,000 patients have been randomized. The qualitative analysis revealed a progressive shift in the perception of the tool. Doctors are now seeing it as a trusted second opinion, available 24/7, which is tailored to the needs of the patient. The retrospective analysis showed the opportunity to achieve a better healthcare quality through an active risk management. Aggregating data from whole hospitals emerge rare drug interactions that otherwise would not be recognizable. Discussion CDSS are promising tools to support clinicians in everyday practice. They can be used as a real time app or to perform retrospective analyses. These data can provide unique resources to hospital management.INTRODUCTIONnOne of the aims of Evidence-Based Medicine is to improve quality and appropriateness of care by the expedition of the knowledge transfer process. Computerized Decision Support Systems (CDSSs) are computer programs that provide alerts to the prescribing doctor directly at the moment of medical examination. In fact, alerts are integrated within the single patient electronic health record. CDSS based on the best available and updated evidence and guidelines may be an efficient tool to facilitate the transfer of the latest results from clinical research directly at the bedside, thus supporting decision-making.nnnOBJECTIVESnThe CODES (COmputerized DEcision Support) trial is a research program funded by the Italian Ministry of Health and the Lombardy Region. It aims to evaluate the feasibility of the implementation of a CDSS at the hospital level and to assess its efficacy in daily clinical practice.nnnMETHODSnThe CODES project includes two pragmatic RCTs testing a CDSS (i.e. the EBMeDS - MediDSS) in two large Italian hospitals: the first is a general hospital in Vimercate (Lombardy), the second is an oncologic research center in Meldola (Emilia Romagna). The CDSS supports a full spectrum of decisions: therapy, drug interactions, diagnosis, and management of health care services are covered by a hundreds of reminders. However only few reminders are activated per patient, highlighting crucial problems in the delivery of high-quality care. The two trials have similar design and primary outcome, the rate at which alerts detected by the software are resolved by a decision of the clinicians. The project also includes the assessment of barriers and facilitators in the adoption of these new technologies by hospital staff members and the retrospective evaluation of the repeated risks in prescription habits.nnnRESULTSnThe trials are ongoing and currently more than 10,000 patients have been randomized. The qualitative analysis revealed a progressive shift in the perception of the tool. Doctors are now seeing it as a trusted second opinion, available 24/7, which is tailored to the needs of the patient. The retrospective analysis showed the opportunity to achieve a better healthcare quality through an active risk management. Aggregating data from whole hospitals emerge rare drug interactions that otherwise would not be recognizable.nnnDISCUSSIONnCDSS are promising tools to support clinicians in everyday practice. They can be used as a real time app or to perform retrospective analyses. These data can provide unique resources to hospital management.

Modello decisionale per l’adozione del vaccino antivaricella: una sfida di fattibilità

INTRODUCTIONnDecision makers adopt interventions, including vaccines, which are most beneficial to populations. A transparent, unbiased, and comprehensive framework based on evidence-based criteria is a promising tool to guide decision-making on vaccine adoption: we developed a multi-dimensional framework conceived from the DECIDE - Evidence to decision Framework (EtD framework). We validated the framework by conducting a real data and evidence set collection on varicella vaccination and tested it with a multidisciplinary group.nnnMETHODSnThe EtD framework presented evidence concerning the varicella vaccination organized in six dimensions: Burden of disease, Vaccine characteristics and impact of immunization program, Values and preferences, Resource use, Equity and Feasibility. Two reviewers completed each dimension with information about varicella vaccine. A multidisciplinary group of 42 participants were asked to evaluate the information in the framework, decide whether to introduce varicella vaccine in the national immunization program, assess the usefulness, and propose some impovements of the decision-making tool.nnnRESULTSnFrom 33 responders (79%) out of 42, 61% supported the adoption of the varicella vaccine as part of the national immunization program. A half (50%) favored the monovalent vaccine while the other half chose the tetravalent vaccine. About 90% of responders found information in the EtD framework comprehensive, easy to understand, and presented in a way that helped make decisions.nnnCONCLUSIONSnComplete and transparent information are welcome. The EtD identified a situation of important divergences between policy makers regarding the introduction and the choice of vaccine. In our case study, for example, a third of the multidisciplinary group did not recommend the adoption of varicella vaccine.

Barriere e facilitatori all’implementazione dei sistemi di supporto decisionale computerizzati in ospedale: uno studio “grounded theory”

INTRODUCTION Computerized Decision Support Systems (CDSSs) connect health care professionals with high-quality, evidence-based information at the point-of-care to guide clinical decision-making. Current research shows the potential of CDSSs to improve the efficiency and quality of patient care. The mere provision of the technology, however, does not guarantee its uptake. This qualitative study aims to explore the barriers and facilitators to the use of CDSSs as identified by health providers. METHODS The study was performed in three Italian hospitals, each characterized by a different level of familiarity with the CDSS technology. We interviewed frontline physicians, nurses, information technology staff, and members of the hospital board of directors (n=24). A grounded theory approach informed our sampling criteria as well as the data collection and analysis. RESULTS The adoption of CDSSs by health care professionals can be represented as a process that consists of six positionings, each corresponding to an individuals use and perceived mastery of the technology. In conditions of low mastery, the CDSS is perceived as an object of threat, an unfamiliar tool that is difficult to control. On the other hand, individuals in conditions of high mastery view the CDSS as a helpful tool that can be locally adapted and integrated with clinicians competences to fulfil their needs. In the first positionings, the uptake of CDSSs is hindered by representational obstacles. The last positionings, alternatively, featured technical obstacles to CDSS uptake. DISCUSSION Our model of CDSS adoption can guide hospital administrators interested in the future integration of CDSSs to evaluate their organizational contexts, identify potential challenges to the implementation of the technology, and develop an effective strategy to address them. Our findings also allow reflections concerning the misalignment between most Italian hospitals and the current innovation trends toward the uptake of computerized decision support technologies.