Dataset Information

A computerized decision support system for depression in primary care.

ABSTRACT: OBJECTIVE:In 2004, results from The Texas Medication Algorithm Project (TMAP) showed better clinical outcomes for patients whose physicians adhered to a paper-and-pencil algorithm compared to patients who received standard clinical treatment for major depressive disorder (MDD). However, implementation of and fidelity to the treatment algorithm among various providers was observed to be inadequate. A computerized decision support system (CDSS) for the implementation of the TMAP algorithm for depression has since been developed to improve fidelity and adherence to the algorithm. METHOD:This was a 2-group, parallel design, clinical trial (one patient group receiving MDD treatment from physicians using the CDSS and the other patient group receiving usual care) conducted at 2 separate primary care clinics in Texas from March 2005 through June 2006. Fifty-five patients with MDD (DSM-IV criteria) with no significant difference in disease characteristics were enrolled, 32 of whom were treated by physicians using CDSS and 23 were treated by physicians using usual care. The study's objective was to evaluate the feasibility and efficacy of implementing a CDSS to assist physicians acutely treating patients with MDD compared to usual care in primary care. Primary efficacy outcomes for depression symptom severity were based on the 17-item Hamilton Depression Rating Scale (HDRS(17)) evaluated by an independent rater. RESULTS:Patients treated by physicians employing CDSS had significantly greater symptom reduction, based on the HDRS(17), than patients treated with usual care (P < .001). CONCLUSIONS:The CDSS algorithm, utilizing measurement-based care, was superior to usual care for patients with MDD in primary care settings. Larger randomized controlled trials are needed to confirm these findings. TRIAL REGISTRATION:clinicaltrials.gov Identifier: NCT00551083.

SUBMITTER: Kurian BT

PROVIDER: S-EPMC2736031 | biostudies-literature | 2009

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A computerized decision support system for depression in primary care.

Kurian Benji T BT Trivedi Madhukar H MH Grannemann Bruce D BD Claassen Cynthia A CA Daly Ella J EJ Sunderajan Prabha P

Primary care companion to the Journal of clinical psychiatry 20090101 4

<h4>Objective</h4>In 2004, results from The Texas Medication Algorithm Project (TMAP) showed better clinical outcomes for patients whose physicians adhered to a paper-and-pencil algorithm compared to patients who received standard clinical treatment for major depressive disorder (MDD). However, implementation of and fidelity to the treatment algorithm among various providers was observed to be inadequate. A computerized decision support system (CDSS) for the implementation of the TMAP algorithm ...[more]

PMID: 19750065

Similar Datasets

Project description:BackgroundThe EBMeDS system is the computerized clinical decision support (CCDS) system of EBPNet, a national computerized point-of-care information service in Belgium. There is no clear evidence of more complex CCDS systems to manage chronic diseases in primary care practices (PCPs). The objective of this study was to assess the effectiveness of EBMeDS use in improving diabetes care.MethodsA cluster-randomized trial with before-and-after measurements was performed in Belgian PCPs over 1 year, from May 2017 to May 2018. We randomly assigned 51 practices to either the intervention group (IG), to receive the EBMeDS system, or to the control group (CG), to receive usual care. Primary and secondary outcomes were the 1-year pre- to post-implementation change in HbA1c, LDL cholesterol, and systolic and diastolic blood pressure. Composite patient and process scores were calculated. A process evaluation was added to the analysis. Results were analyzed at 6 and 12 months. Linear mixed models and logistic regression models based on generalized estimating equations were used where appropriate.ResultsOf the 51 PCPs that were enrolled and randomly assigned (26 PCPs in the CG and 25 in the IG), 29 practices (3815 patients) were analyzed in the study: 2464 patients in the CG and 1351 patients in the IG. No change differences existed between groups in primary or secondary outcomes. Change difference between CG and IG after 1-year follow-up was - 0.09 (95% CI - 0.18; 0.01, p-value = 0.06) for HbA1c; 1.76 (95% CI - 0.46; 3.98, p-value = 0.12) for LDL cholesterol; and 0.13 (95% CI - 0.91; 1.16, p-value = 0.81) and 0.12 (95% CI - 1.25;1.49, p-value = 0.86) for systolic and diastolic blood pressure respectively. The odds ratio of the IG versus the CG for the probability of no worsening and improvement was 1.09 (95% CI 0.73; 1.63, p-value = 0.67) for the process composite score and 0.74 (95% CI 0.49; 1.12, p-value = 0.16) for the composite patient score. All but one physician was satisfied with the EBMeDS system.ConclusionsThe CCDS system EBMeDS did not improve diabetes care in Belgian primary care. The lack of improvement was mainly caused by imperfections in the organizational context of Belgian primary care for chronic disease management and shortcomings in the system requirements for the correct use of the EBMeDS system (e.g., complete structured records). These shortcomings probably caused low-use rates of the system.Trial registrationClinicalTrials.gov, NCT01830569, Registered 12 April 2013.

Project description:BackgroundThe CDC's Family History Public Health Initiative encourages adoption and increase awareness of family health history. To meet these goals and develop a personalized medicine implementation science research agenda, the Genomedical Connection is using an implementation research (T3 research) framework to develop and integrate a self-administered computerized family history system with built-in decision support into 2 primary care clinics in North Carolina.Methods/designThe family health history system collects a three generation family history on 48 conditions and provides decision support (pedigree and tabular family history, provider recommendation report and patient summary report) for 4 pilot conditions: breast cancer, ovarian cancer, colon cancer, and thrombosis. All adult English-speaking, non-adopted, patients scheduled for well-visits are invited to complete the family health system prior to their appointment. Decision support documents are entered into the medical record and available to provider's prior to the appointment. In order to optimize integration, components were piloted by stakeholders prior to and during implementation. Primary outcomes are change in appropriate testing for hereditary thrombophilia and screening for breast cancer, colon cancer, and ovarian cancer one year after study enrollment. Secondary outcomes include implementation measures related to the benefits and burdens of the family health system and its impact on clinic workflow, patients' risk perception, and intention to change health related behaviors. Outcomes are assessed through chart review, patient surveys at baseline and follow-up, and provider surveys. Clinical validity of the decision support is calculated by comparing its recommendations to those made by a genetic counselor reviewing the same pedigree; and clinical utility is demonstrated through reclassification rates and changes in appropriate screening (the primary outcome).DiscussionThis study integrates a computerized family health history system within the context of a routine well-visit appointment to overcome many of the existing barriers to collection and use of family history information by primary care providers. Results of the implementation process, its acceptability to patients and providers, modifications necessary to optimize the system, and impact on clinical care can serve to guide future implementation projects for both family history and other tools of personalized medicine, such as health risk assessments.

Project description:BackgroundTrials evaluating the effects of interventions usually provide little insight into the factors responsible for (lack of) changes in desired outcomes. A process evaluation alongside a trial can shed light on the mechanisms responsible for the outcomes of a trial. The aim of this study was to investigate exposure to and experiences with a computerized decision support system (CDSS) intervention, in order to gain insight into the intervention's impact and to provide suggestions for improvement.MethodsA process evaluation was conducted as part of a large-scale cluster-randomized controlled trial investigating the effects of the CDSS NHGDoc on quality of care. Data on exposure to and experiences with the intervention were collected during the trial period among participants in both the intervention and control group - whenever applicable - by means of the NHGDoc server and an electronic questionnaire. Multiple data were analyzed using descriptive statistics.ResultsNinety-nine percent (n = 229) of the included practices generated data for the NHGDoc server and 50 % (n = 116) responded to the questionnaire: both general practitioners (GPs; n = 112; 49 %) and practice nurses (PNs; n = 52; 37 %) participated. The actual exposure to the NHGDoc system and specific heart failure module was limited with 52 % of the GPs and 42 % of the PNs reporting to either never or rarely use the system. Overall, users had a positive attitude towards CDSSs. The most perceived barriers to using NHGDoc were a lack of learning capacity of the system, the additional time and work it requires to use the CDSS, irrelevant alerts, too high intensity of alerts and insufficient knowledge regarding the system.ConclusionsSeveral types of barriers may have negatively affected the impact of the intervention. Although users are generally positive about CDSSs, a large share of them is insufficiently aware of the functions of NHGDoc and, finds the decision support not always useful or relevant and difficult to integrate into daily practice. In designing CDSS interventions we suggest to more intensely involve the end-users and increase the system's flexibility and learning capacity. To improve implementation a proper introduction of a CDSS among its target group including adequate training is advocated.Trial registrationClinical trials NCT01773057 .

Project description:BackgroundComputerized clinical decision support systems (CCDSSs) are claimed to improve processes and outcomes of primary preventive care (PPC), but their effects, safety, and acceptance must be confirmed. We updated our previous systematic reviews of CCDSSs and integrated a knowledge translation approach in the process. The objective was to review randomized controlled trials (RCTs) assessing the effects of CCDSSs for PPC on process of care, patient outcomes, harms, and costs.MethodsWe conducted a decision-maker-researcher partnership systematic review. We searched MEDLINE, EMBASE, Ovid's EBM Reviews Database, Inspec, and other databases, as well as reference lists through January 2010. We contacted authors to confirm data or provide additional information. We included RCTs that assessed the effect of a CCDSS for PPC on process of care and patient outcomes compared to care provided without a CCDSS. A study was considered to have a positive effect (i.e., CCDSS showed improvement) if at least 50% of the relevant study outcomes were statistically significantly positive.ResultsWe added 17 new RCTs to our 2005 review for a total of 41 studies. RCT quality improved over time. CCDSSs improved process of care in 25 of 40 (63%) RCTs. Cumulative scientifically strong evidence supports the effectiveness of CCDSSs for screening and management of dyslipidaemia in primary care. There is mixed evidence for effectiveness in screening for cancer and mental health conditions, multiple preventive care activities, vaccination, and other preventive care interventions. Fourteen (34%) trials assessed patient outcomes, and four (29%) reported improvements with the CCDSS. Most trials were not powered to evaluate patient-important outcomes. CCDSS costs and adverse events were reported in only six (15%) and two (5%) trials, respectively. Information on study duration was often missing, limiting our ability to assess sustainability of CCDSS effects.ConclusionsEvidence supports the effectiveness of CCDSSs for screening and treatment of dyslipidaemia in primary care with less consistent evidence for CCDSSs used in screening for cancer and mental health-related conditions, vaccinations, and other preventive care. CCDSS effects on patient outcomes, safety, costs of care, and provider satisfaction remain poorly supported.

Project description:BackgroundComputerized decision support systems (CDSSs) are increasingly used to improve quality of care. There is evidence for moderate to large effects from randomized controlled trials (RCTs), but evidence on their effectiveness when implemented at a national level is lacking. In the Netherlands, the Dutch College of General Practitioners (NHG) initiated their successful guideline program already 30 years ago. NHGDoc, a CDSS based on these NHG guidelines, covering multiple disease areas for general practice, was developed in 2006 with the aim to improve quality of primary care. In this paper, a protocol is presented to evaluate the uptake and effects of NHGDoc.MethodsA cluster RCT will be conducted among 120 general practices in the Netherlands. Eligible general practices will be randomized to receive either the regular NHGDoc decision support modules (control arm) or the regular modules plus an additional module on heart failure (intervention arm). The heart failure module consists of patient-specific alerts concerning the treatment of patients with heart failure. The effect evaluation will focus on performance indicators (e.g., prescription behavior) as well as on patient outcomes (e.g., hospital admissions) relevant in the domain of heart failure. Additionally, a process evaluation will be conducted to gain insight into the barriers and facilitators that affect the uptake and impact of NHGDoc.DiscussionResults of this study will provide insight in the uptake and impact of a multiple-domain covering CDSS for primary care implemented by a national guideline organization to improve the quality of primary care. Whereas the trial focuses on a specific domain of care-heart failure-conclusions of this study will shed light on the functioning of CDSSs covering multiple disease areas for primary care, particularly as this study also explores the factors contributing to the system's uptake and effectiveness.Trial registrationClinical trials NCT01773057.

Dataset Information

A computerized decision support system for depression in primary care.

Publications

A computerized decision support system for depression in primary care.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets