Pediatric decision support using adapted Arden Syntax.

BACKGROUND: Pediatric guidelines based care is often overlooked because of the constraints of a typical office visit and the sheer number of guidelines that may exist for a patient's visit. In response to this problem, in 2004 we developed a pediatric computer based clinical decision support system using Arden Syntax medical logic modules (MLM). METHODS: The Child Health Improvement through Computer Automation system (CHICA) screens patient families in the waiting room and alerts the physician in the exam room. Here we describe adaptation of Arden Syntax to support production and consumption of patient specific tailored documents for every clinical encounter in CHICA and describe the experiments that demonstrate the effectiveness of this system. RESULTS: As of this writing CHICA has served over 44,000 patients at 7 pediatric clinics in our healthcare system in the last decade and its MLMs have been fired 6182,700 times in "produce" and 5334,021 times in "consume" mode. It has run continuously for over 10 years and has been used by 755 physicians, residents, fellows, nurse practitioners, nurses and clinical staff. There are 429 MLMs implemented in CHICA, using the Arden Syntax standard. Studies of CHICA's effectiveness include several published randomized controlled trials. CONCLUSIONS: Our results show that the Arden Syntax standard provided us with an effective way to represent pediatric guidelines for use in routine care. We only required minor modifications to the standard to support our clinical workflow. Additionally, Arden Syntax implementation in CHICA facilitated the study of many pediatric guidelines in real clinical environments.

Effectiveness of Computer Automation for the Diagnosis and Management of Childhood Type 2 Diabetes: A Randomized Clinical Trial.

Importance: Type 2 diabetes (T2D) is increasingly common in young individuals. Primary prevention and screening among children and adolescents who are at substantial risk for T2D are recommended, but implementation of T2D screening practices in the pediatric primary care setting is uncommon. Objective: To determine the feasibility and effectiveness of a computerized clinical decision support system to identify pediatric patients at high risk for T2D and to coordinate screening for and diagnosis of prediabetes and T2D. Design, Setting, and Participants: This cluster-randomized clinical trial included patients from 4 primary care pediatric clinics. Two clinics were randomized to the computerized clinical decision support intervention, aimed at physicians, and 2 were randomized to the control condition. Patients of interest included children, adolescents, and young adults 10 years or older. Data were collected from January 1, 2013, through December 1, 2016. Interventions: Comparison of physician screening and follow-up practices after adding a T2D module to an existing computer decision support system. Main Outcomes and Measures: Electronic medical record (EMR) data from patients 10 years or older were reviewed to determine the rates at which pediatric patients were identified as having a body mass index (BMI) at or above the 85th percentile and 2 or more risk factors for T2D and underwent screening for T2D. Results: Medical records were reviewed for 1369 eligible children (712 boys [52.0%] and 657 girls [48.0%]; median [interquartile range] age, 12.9 [11.2-15.3]), of whom 684 were randomized to the control group and 685 to the intervention group. Of these, 663 (48.4%) had a BMI at or above the 85th percentile. Five hundred sixty-five patients (41.3%) met T2D screening criteria, with no difference between control and intervention sites. The T2D module led to a significant increase in the percentage of patients undergoing screening for T2D (89 of 283 [31.4%] vs 26 of 282 [9.2%]; adjusted odds ratio, 4.6; 95% CI, 1.5-14.7) and a greater proportion attending a scheduled follow-up appointment (45 of 153 [29.4%] vs 38 of 201 [18.9%]; adjusted odds ratio, 1.8; 95% CI, 1.5-2.2). Conclusions and Relevance: Use of a computerized clinical decision support system to automate the identification and screening of pediatric patients at high risk for T2D can help overcome barriers to the screening process. The support system significantly increased screening among patients who met the American Diabetes Association criteria and adherence to follow-up appointments with primary care clinicians. Trial Registration: clinicaltrials.gov Identifier: NCT01814787.

Use of a computerized decision aid for developmental surveillance and screening: a randomized clinical trial.

IMPORTANCE: Developmental delays and disabilities are common in children. Research has indicated that intervention during the early years of a child's life has a positive effect on cognitive development, social skills and behavior, and subsequent school performance. OBJECTIVE: To determine whether a computerized clinical decision support system is an effective approach to improve standardized developmental surveillance and screening (DSS) within primary care practices. DESIGN, SETTING, AND PARTICIPANTS: In this cluster randomized clinical trial performed in 4 pediatric clinics from June 1, 2010, through December 31, 2012, children younger than 66 months seen for primary care were studied. INTERVENTIONS: We compared surveillance and screening practices after adding a DSS module to an existing computer decision support system. MAIN OUTCOMES AND MEASURES: The rates at which children were screened for developmental delay. RESULTS: Medical records were reviewed for 360 children (180 each in the intervention and control groups) to compare rates of developmental screening at the 9-, 18-, or 30-month well-child care visits. The DSS module led to a significant increase in the percentage of patients screened with a standardized screening tool (85.0% vs 24.4%, P < .001). An additional 120 records (60 each in the intervention and control groups) were reviewed to examine surveillance rates at visits outside the screening windows. The DSS module led to a significant increase in the percentage of patients whose parents were assessed for concerns about their child's development (71.7% vs 41.7%, P = .04). CONCLUSIONS AND RELEVANCE: Using a computerized clinical decision support system to automate the screening of children for developmental delay significantly increased the numbers of children screened at 9, 18, and 30 months of age. It also significantly improved surveillance at other visits. Moreover, it increased the number of children who ultimately were diagnosed as having developmental delay and who were referred for timely services at an earlier age. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT01351077.

Use of a computerized decision aid for ADHD diagnosis: a randomized controlled trial.

OBJECTIVE: To determine if implementing attention-deficit/hyperactivity disorder (ADHD) diagnosis and treatment guidelines in a clinical decision support system would result in better care, including higher rates of adherence to clinical care guidelines. METHODS: We conducted a cluster randomized controlled trial in which we compared diagnosis and management of ADHD in 6- to 12-year-olds after implementation of a computer decision support system in 4 practices. RESULTS: Eighty-four charts were reviewed. In the control group, the use of structured diagnostic assessments dropped from 50% in the baseline period to 38% in the intervention period. In the intervention group, however, it rose from 60% to 81%. This difference was statistically significant, even after controlling for age, gender, and race (odds ratio of structured diagnostic assessment in intervention group versus control group = 8.0, 95% confidence interval 1.6-40.6). Significant differences were also seen in the number of ADHD core symptoms noted at the time of diagnosis. Our study was not powered to detect changes in care and management, but the percent of patients who had documented medication adjustments, mental health referrals, and visits to mental health specialists were higher in the intervention group than the control. CONCLUSIONS: The introduction of a clinical decision support module resulted in higher quality of care with respect to ADHD diagnosis including a prospect for higher quality of ADHD management in children. Future work will examine how to further develop the ADHD module and add support for other chronic conditions.

A randomized controlled trial of screening for maternal depression with a clinical decision support system.

OBJECTIVE: To determine if automated screening and just in time delivery of testing and referral materials at the point of care promotes universal screening referral rates for maternal depression. METHODS: The Child Health Improvement through Computer Automation (CHICA) system is a decision support and electronic medical record system used in our pediatric clinics. All families of patients up to 15 months of age seen between October 2007 and July 2009 were randomized to one of three groups: (1) screening questions printed on prescreener forms (PSF) completed by mothers in the waiting room with physician alerts for positive screens, (2) everything in (1) plus 'just in time' (JIT) printed materials to aid physicians, and (3) a control group where physicians were simply reminded to screen on printed physician worksheets. RESULTS: The main outcome of interest was whether physicians suspected a diagnosis of maternal depression and referred a mother for assistance. This occurred significantly more often in both the PSF (2.4%) and JIT groups (2.4%) than in the control group (1.2%) (OR 2.06, 95% CI 1.08 to 3.93). Compared to the control group, more mothers were noted to have depressed mood in the PSF (OR 7.93, 95% CI 4.51 to 13.96) and JIT groups (OR 8.10, 95% CI 4.61 to 14.25). Similarly, compared to the control group, more mothers had signs of anhedonia in the PSF (OR 12.58, 95% CI 5.03 to 31.46) and JIT groups (OR 13.03, 95% CI 5.21 to 32.54). CONCLUSIONS: Clinical decision support systems like CHICA can improve the screening of maternal depression.

Targeted screening for pediatric conditions with the CHICA system.

OBJECTIVE: The Child Health Improvement through Computer Automation (CHICA) system is a decision-support and electronic-medical-record system for pediatric health maintenance and disease management. The purpose of this study was to explore CHICA's ability to screen patients for disorders that have validated screening criteria--specifically tuberculosis (TB) and iron-deficiency anemia. DESIGN: Children between 0 and 11 years were randomized by the CHICA system. In the intervention group, parents were asked about TB and iron-deficiency risk, and physicians received a tailored prompt. In the control group, no screens were performed, and the physician received a generic prompt about these disorders. RESULTS: 1123 participants were randomized to the control group and 1116 participants to the intervention group. Significantly more people reported positive risk factors for iron-deficiency anemia in the intervention group (17.5% vs 3.1%, OR 6.6, 95% CI 4.5 to 9.5). In general, far fewer parents reported risk factors for TB than for iron-deficiency anemia. Again, there were significantly higher detection rates of positive risk factors in the intervention group (1.8% vs 0.8%, OR 2.3, 95% CI 1.0 to 5.0). LIMITATIONS: It is possible that there may be more positive screens without improving outcomes. However, the guidelines are based on studies that have evaluated the questions the authors used as sensitive and specific, and there is no reason to believe that parents misunderstood them. CONCLUSIONS: Many screening tests are risk-based, not universal, leaving physicians to determine who should have a further workup. This can be a time-consuming process. The authors demonstrated that the CHICA system performs well in assessing risk automatically for TB and iron-deficiency anemia.