Browsing by Author "Anand, Vibha"
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Item Patient-tailored prioritization for a pediatric care decision support system through machine learning(Oxford University Press, 2013-12-01) Klann, Jeffrey G.; Anand, Vibha; Downs, Stephen M.; Department of Pediatrics, IU School of MedicineObjective Over 8 years, we have developed an innovative computer decision support system that improves appropriate delivery of pediatric screening and care. This system employs a guidelines evaluation engine using data from the electronic health record (EHR) and input from patients and caregivers. Because guideline recommendations typically exceed the scope of one visit, the engine uses a static prioritization scheme to select recommendations. Here we extend an earlier idea to create patient-tailored prioritization. Materials and methods We used Bayesian structure learning to build networks of association among previously collected data from our decision support system. Using area under the receiver-operating characteristic curve (AUC) as a measure of discriminability (a sine qua non for expected value calculations needed for prioritization), we performed a structural analysis of variables with high AUC on a test set. Our source data included 177 variables for 29 402 patients. Results The method produced a network model containing 78 screening questions and anticipatory guidance (107 variables total). Average AUC was 0.65, which is sufficient for prioritization depending on factors such as population prevalence. Structure analysis of seven highly predictive variables reveals both face-validity (related nodes are connected) and non-intuitive relationships. Discussion We demonstrate the ability of a Bayesian structure learning method to ‘phenotype the population’ seen in our primary care pediatric clinics. The resulting network can be used to produce patient-tailored posterior probabilities that can be used to prioritize content based on the patient's current circumstances. Conclusions This study demonstrates the feasibility of EHR-driven population phenotyping for patient-tailored prioritization of pediatric preventive care services.Item Pediatric decision support using adapted Arden Syntax(Elsevier, 2015-10-01) Anand, Vibha; Carroll, Aaron E.; Biondich, Paul G.; Dugan, Tamara M.; Downs, Stephen M.; Department of Pediatrics, School of MedicineBACKGROUND: 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.Item Prevalence of infant television viewing and maternal depression symptoms(Ovid Technologies (Wolters Kluwer) - Lippincott Williams & Wilkins, 2014-04) Anand, Vibha; Downs, Stephen M.; Bauer, Nerissa S.; Carroll, Aaron E.; Department of Pediatrics, IU School of MedicineBACKGROUND: Early television (TV) viewing has been linked with maternal depression and has adverse health effects in children. However, it is not known how early TV viewing occurs. This study evaluated the prevalence at which parents report TV viewing for their children if asked in the first 2 years of life and whether TV viewing is associated with maternal depression symptoms. METHODS: Using a cross-sectional design, TV viewing was evaluated in children 0 to 2 years of age in 4 pediatric clinics in Indianapolis, IN, between January 2011 and April 2012. Families were screened for any parental report of depression symptoms (0-15 months) and for parental report of TV viewing (before 2 years of age) using a computerized clinical decision support system linked to the patient's electronic health record. RESULTS: There were 3254 children in the study. By parent report, 50% of children view TV by 2 months of age, 75% by 4 months of age, and 90% by 2 years of age. Complete data for both TV viewing and maternal depression symptoms were available for 2397 (74%) of children. In regression models, the odds of parental report of TV viewing increased by 27% for each additional month of child's age (odds ratio [OR], 1.27; 95% confidence interval [CI], 1.25-1.30; p < .001). The odds of TV viewing increased by almost half with parental report of depression symptoms (OR, 1.47; CI, 1.07-2.00, p = .016). Publicly insured children had 3 times the odds of TV viewing compared to children with private insurance (OR, 3.00; CI, 1.60-5.63; p = .001). Black children had almost 4 times the odds (OR, 3.75; CI, 2.70-5.21; p < .001), and white children had one-and-a-half times the odds (OR, 1.55; CI, 1.04-2.30; p = .032) of TV viewing when compared to Latino children. CONCLUSIONS: By parental report, TV viewing occurs at a very young age in infancy, usually between 0 and 3 months and varies by insurance and race/ethnicity. Children whose parents report depression symptoms are especially at risk for early TV viewing. Like maternal depression, TV viewing poses added risks for reduced interpersonal interactions to stimulate infant development. This work suggests the need to develop early targeted developmental interventions. Children as young as 0 to 3 months are viewing TV on most days. In the study sample of 0 to 2 year olds, the odds of TV viewing increased by more than a quarter for each additional month of child's age and by as much as half when the mother screened positive for depression symptoms.Item A PROBABILISTIC APPROACH TO DATA INTEGRATION IN BIOMEDICAL RESEARCH: THE IsBIG EXPERIMENTS(2011-03-16) Anand, Vibha; Palakal, Mathew J.; Downs, Stephen M.; McDaniel, Anna M.; Schadow, GuntherBiomedical research has produced vast amounts of new information in the last decade but has been slow to find its use in clinical applications. Data from disparate sources such as genetic studies and summary data from published literature have been amassed, but there is a significant gap, primarily due to a lack of normative methods, in combining such information for inference and knowledge discovery. In this research using Bayesian Networks (BN), a probabilistic framework is built to address this gap. BN are a relatively new method of representing uncertain relationships among variables using probabilities and graph theory. Despite their computational complexity of inference, BN represent domain knowledge concisely. In this work, strategies using BN have been developed to incorporate a range of available information from both raw data sources and statistical and summary measures in a coherent framework. As an example of this framework, a prototype model (In-silico Bayesian Integration of GWAS or IsBIG) has been developed. IsBIG integrates summary and statistical measures from the NIH catalog of genome wide association studies (GWAS) and the database of human genome variations from the international HapMap project. IsBIG produces a map of disease to disease associations as inferred by genetic linkages in the population. Quantitative evaluation of the IsBIG model shows correlation with empiric results from our Electronic Medical Record (EMR) – The Regenstrief Medical Record System (RMRS). Only a small fraction of disease to disease associations in the population can be explained by the linking of a genetic variation to a disease association as studied in the GWAS. None the less, the model appears to have found novel associations among some diseases that are not described in the literature but are confirmed in our EMR. Thus, in conclusion, our results demonstrate the potential use of a probabilistic modeling approach for combining data from disparate sources for inference and knowledge discovery purposes in biomedical research.Item Real Time Alert System: A Disease Management System Leveraging Health Information Exchange(JMIR, 2012) Anand, Vibha; Sheley, Meena E.; Xu, Shawn; Downs, Stephen M.; Pediatrics, School of MedicineBackground: Rates of preventive and disease management services can be improved by providing automated alerts and reminders to primary care providers (PCPs) using of health information technology (HIT) tools. Methods: Using Adaptive Turnaround Documents (ATAD), an existing Health Information Exchange (HIE) infrastructure and office fax machines, we developed a Real Time Alert (RTA) system. RTA is a computerized decision support system (CDSS) that is able to deliver alerts to PCPs statewide for recommended services around the time of the patient visit. RTA is also able to capture structured clinical data from providers using existing fax technology. In this study, we evaluate RTA's performance for alerting PCPs when their patients with asthma have an emergency room visit anywhere in the state. Results: Our results show that RTA was successfully able to deliver "just in time" patient-relevant alerts to PCPs across the state. Furthermore, of those ATADs faxed back and automatically interpreted by the RTA system, 35% reported finding the provided information helpful. The PCPs who reported finding information helpful also reported making a phone call, sending a letter or seeing the patient for follow up care. Conclusions: We have successfully demonstrated the feasibility of electronically exchanging important patient related information with the PCPs statewide. This is despite a lack of a link with their electronic health records. We have shown that using our ATAD technology, a PCP can be notified quickly of an important event such as a patient's asthma related emergency room admission so further follow up can happen in near real time.Item Secondhand smoke exposure, parental depressive symptoms and preschool behavioral outcomes(Elsevier, 2015-01) Bauer, Nerissa S.; Anand, Vibha; Carroll, Aaron E.; Downs, Stephen M.; Department of Pediatrics, Indiana University School of MedicineLittle is known about the association of secondhand smoke (SHS) exposure and behavioral conditions among preschoolers. A cross-sectional analysis was used to examine billing and pharmacy claims from November 2004 to June 2012 linked to medical encounter-level data for 2,441 children from four pediatric community health clinics. Exposure to SHS was associated with attention deficit-hyperactivity disorder/ADHD and disruptive behavior disorder/DBD after adjusting for potential confounding factors. Assessment of exposure to SHS and parental depressive symptoms in early childhood may increase providers' ability to identify children at higher risk of behavioral issues and provide intervention at the earliest stages.Item The Last Mile: Using Fax Machines to Exchange Data between Clinicians and Public Health(JMIR, 2011) Downs, Stephen M.; Anand, Vibha; Sheley, Meena; Grannis, Shaun J.; Pediatrics, School of MedicineThere is overlap in a wide range of activities to support both public health and clinical care. Examples include immunization registries (IR), newborn screening (NBS), disease reporting, lead screening programs, and more. Health information exchanges create an opportunity to share data between the clinical and public health environments, providing decision support to clinicians and surveillance and tracking information to public health. We developed mechanisms to support two-way communication between clinicians in the Indiana Health information Exchange (IHIE) and the Indiana State Department of Health (ISDH). This paper describes challenges we faced and design decisions made to overcome them. We developed systems to help clinicians communicate with the ISDH IR and with the NBS program. Challenges included (1) a minority of clinicians who use electronic health records (EHR), (2) lack of universal patient identifiers, (3) identifying physicians responsible for newborns, and (4) designing around complex security policies and firewalls. To communicate electronically with clinicians without EHRs, we utilize their fax machines. Our rule-based decision support system generates tailored forms that are automatically faxed to clinicians. The forms include coded input fields that capture data for automatic transfer into the IHIE when they are faxed back. Because the same individuals have different identifiers, and newborns' names change, it is challenging to match patients across systems. We use a stochastic matching algorithm to link records. We scan electronic clinical messages (HL7 format) coming into IHIE to find clinicians responsible for newborns. We have designed an architecture to link IHIE, ISDH, and our systems.Item Use of a computerized decision aid for developmental surveillance and screening: a randomized clinical trial(American Medical Association, 2014) Carroll, Aaron E.; Bauer, Nerissa S.; Dugan, Tamara M.; Anand, Vibha; Saha, Chandan; Downs, Stephen M.; Biostatistics and Health Data Science, School of MedicineImportance: 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.