Andrew D. Boyd

Evolving gene/transcript definitions significantly alter the interpretation of GeneChip data

Genome-wide expression profiling is a powerful tool for implicating novel gene ensembles in cellular mechanisms of health and disease. The most popular platform for genome-wide expression profiling is the Affymetrix GeneChip. However, its selection of probes relied on earlier genome and transcriptome annotation which is significantly different from current knowledge. The resultant informatics problems have a profound impact on analysis and interpretation the data. Here, we address these critical issues and offer a solution. We identified several classes of problems at the individual probe level in the existing annotation, under the assumption that current genome and transcriptome databases are more accurate than those used for GeneChip design. We then reorganized probes on more than a dozen popular GeneChips into gene-, transcript- and exon-specific probe sets in light of up-to-date genome, cDNA/EST clustering and single nucleotide polymorphism information. Comparing analysis results between the original and the redefined probe sets reveals ∼30–50% discrepancy in the genes previously identified as differentially expressed, regardless of analysis method. Our results demonstrate that the original Affymetrix probe set definitions are inaccurate, and many conclusions derived from past GeneChip analyses may be significantly flawed. It will be beneficial to re-analyze existing GeneChip data with updated probe set definitions.

miBLAST: scalable evaluation of a batch of nucleotide sequence queries with BLAST

A common task in many modern bioinformatics applications is to match a set of nucleotide query sequences against a large sequence dataset. Exis-ting tools, such as BLAST, are designed to evaluate a single query at a time and can be unacceptably slow when the number of sequences in the query set is large. In this paper, we present a new algorithm, called miBLAST, that evaluates such batch workloads efficiently. At the core, miBLAST employs a q-gram filtering and an index join for efficiently detecting similarity between the query sequences and database sequences. This set-oriented technique, which indexes both the query and the database sets, results in substantial performance improvements over existing methods. Our results show that miBLAST is significantly faster than BLAST in many cases. For example, miBLAST aligned 247 965 oligonucleotide sequences in the Affymetrix probe set against the Human UniGene in 1.26 days, compared with 27.27 days with BLAST (an improvement by a factor of 22). The relative performance of miBLAST increases for larger word sizes; however, it decreases for longer queries. miBLAST employs the familiar BLAST statistical model and output format, guaranteeing the same accuracy as BLAST and facilitating a seamless transition for existing BLAST users.

The University of Michigan Honest Broker: a Web-based service for clinical and translational research and practice.

For the success of clinical and translational science, a seamless interoperation is required between clinical and research information technology. Addressing this need, the Michigan Clinical Research Collaboratory (MCRC) was created. The MCRC employed a standards-driven Web Services architecture to create the U-M Honest Broker, which enabled sharing of clinical and research data among medical disciplines and separate institutions. Design objectives were to facilitate sharing of data, maintain a master patient index (MPI), deidentification of data, and routing data to preauthorized destination systems for use in clinical care, research, or both. This article describes the architecture and design of the U-M HB system and the successful demonstration project. Seventy percent of eligible patients were recruited for a prospective study examining the correlation between interventional cardiac catheterizations and depression. The U-M Honest Broker delivered on the promise of using structured clinical knowledge shared among providers to help clinical and translational research.

The discriminatory cost of ICD-10-CM transition between clinical specialties: metrics, case study, and mitigating tools

Objective Applying the science of networks to quantify the discriminatory impact of the ICD-9-CM to ICD-10-CM transition between clinical specialties. Materials and Methods Datasets were the Center for Medicaid and Medicare Services ICD-9-CM to ICD-10-CM mapping files, general equivalence mappings, and statewide Medicaid emergency department billing. Diagnoses were represented as nodes and their mappings as directional relationships. The complex network was synthesized as an aggregate of simpler motifs and tabulation per clinical specialty. Results We identified five mapping motif categories: identity, class-to-subclass, subclass-to-class, convoluted, and no mapping. Convoluted mappings indicate that multiple ICD-9-CM and ICD-10-CM codes share complex, entangled, and non-reciprocal mappings. The proportions of convoluted diagnoses mappings (36% overall) range from 5% (hematology) to 60% (obstetrics and injuries). In a case study of 24 008 patient visits in 217 emergency departments, 27% of the costs are associated with convoluted diagnoses, with ‘abdominal pain’ and ‘gastroenteritis’ accounting for approximately 3.5%. Discussion Previous qualitative studies report that administrators and clinicians are likely to be challenged in understanding and managing their practice because of the ICD-10-CM transition. We substantiate the complexity of this transition with a thorough quantitative summary per clinical specialty, a case study, and the tools to apply this methodology easily to any clinical practice in the form of a web portal and analytic tables. Conclusions Post-transition, successful management of frequent diseases with convoluted mapping network patterns is critical. The http://lussierlab.org/transition-to-ICD10CM web portal provides insight in linking onerous diseases to the ICD-10 transition.

The transition to ICD-10-CM: challenges for pediatric practice.

BACKGROUND AND OBJECTIVES: Diagnostic codes are used widely within health care for billing, quality assessment, and to measure clinical outcomes. The US health care system will transition to the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM), in October 2015. Little is known about how this transition will affect pediatric practices. The objective of this study was to examine how the transition to ICD-10-CM may result in ambiguity of clinical information and financial disruption for pediatricians. METHODS: Using a statewide data set from Illinois Medicaid specified for pediatricians, 2708 International Classification of Diseases, Ninth Revision, Clinical Modification, diagnosis codes were identified. Diagnosis codes were categorized into 1 of 5 categories: identity, class-to-subclass, subclass-to-class, convoluted, and no translation. The convoluted and high-cost diagnostic codes (n = 636) were analyzed for accuracy and categorized into “information loss,” “overlapping categories,” “inconsistent,” and “consistent.” Finally, reimbursement by Medicaid was calculated for each category. RESULTS: Twenty-six percent of pediatric diagnosis codes are convoluted, which represents 21% of Illinois Medicaid pediatric patient encounters and 16% of reimbursement. The diagnosis codes represented by information loss (3.6%), overlapping categories (3.2%), and inconsistent (1.2%) represent 8% of Medicaid pediatric reimbursement. CONCLUSIONS: The potential for financial disruption and administrative errors from 8% of reimbursement diagnosis codes necessitates special attention to these codes in preparing for the transition to ICD-10-CM for pediatric practices.

The complexity and challenges of the International Classification of Diseases, Ninth Revision, Clinical Modification to International Classification of Diseases, 10th Revision, Clinical Modification transition in EDs.

Beginning October 2015, the Center for Medicare and Medicaid Services will require medical providers to use the vastly expanded International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) system. Despite wide availability of information and mapping tools for the next generation of the ICD classification system, some of the challenges associated with transition from ICD-9-CM to ICD-10-CM are not well understood. To quantify the challenges faced by emergency physicians, we analyzed a subset of a 2010 Illinois Medicaid database of emergency department ICD-9-CM codes, seeking to determine the accuracy of existing mapping tools in order to better prepare emergency physicians for the change to the expanded ICD-10-CM system. We found that 27% of 1830 codes represented convoluted multidirectional mappings. We then analyzed the convoluted transitions and found that 8% of total visit encounters (23% of the convoluted transitions) were clinically incorrect. The ambiguity and inaccuracy of these mappings may impact the workflow associated with the translation process and affect the potential mapping between ICD codes and Current Procedural Codes, which determine physician reimbursement.

Screening for Depression, Sleep-Related Disturbances, and Anxiety in Patients with Adenocarcinoma of the Pancreas: A Preliminary Study

Purpose. Screening for depression, sleep-related disturbances, and anxiety in patients with diagnosed adenocarcinoma of the pancreas. Materials and Methods. Patients were evaluated at initial consultation and subsequent visits at the multidisciplinary pancreatic cancer clinic at our University Cancer Center. Cross-sectional and longitudinal psychosocial distress was assessed utilizing Personal Health Questionnaire 9 (PHQ9) to screen for depression and monitor symptoms, the Penn State Worry Questionnaire (PSWQ) for generalized anxiety, and the University of Michigan Sleep Questionnaire to monitor sleep symptoms. Results. Twenty-two patients diagnosed with pancreatic cancer participated during the 6-month pilot study with longitudinal followup for thirteen patients. In this study, mild-to-moderate depressive symptoms, anxiety, and potential sleep problems were common. The main finding of the study was 23% of the patients who were part of this pilot project screened positive for moderately severe major depressive symptoms, likely anxiety disorder or a potential sleep disorder during the study. One patient screened positive for moderately severe depressive symptoms in longitudinal followup. Conclusions. Depression, anxiety, and sleep problems are evident in patients with pancreatic cancer. Prospective, longitudinal studies, with larger groups of patients, are needed to determine if these comorbid symptoms impact outcome and clinical course.

Challenges and remediation for Patient Safety Indicators in the transition to ICD-10-CM

Reporting of hospital adverse events relies on Patient Safety Indicators (PSIs) using International Classification of Diseases, Ninth Edition, Clinical Modification (ICD-9-CM) codes. The US transition to ICD-10-CM in 2015 could result in erroneous comparisons of PSIs. Using the General Equivalent Mappings (GEMs), we compared the accuracy of ICD-9-CM coded PSIs against recommended ICD-10-CM codes from the Centers for Medicaid/Medicare Services (CMS). We further predict their impact in a cohort of 38 644 patients (1 446 581 visits and 399 hospitals). We compared the predicted results to the published PSI related ICD-10-CM diagnosis codes. We provide the first report of substantial hospital safety reporting errors with five direct comparisons from the 23 types of PSIs (transfusion and anesthesia related PSIs). One PSI was excluded from the comparison between code sets due to reorganization, while 15 additional PSIs were inaccurate to a lesser degree due to the complexity of the coding translation. The ICD-10-CM translations proposed by CMS pose impending risks for (1) comparing safety incidents, (2) inflating the number of PSIs, and (3) increasing the variability of calculations attributable to the abundance of coding system translations. Ethical organizations addressing ‘data-, process-, and system-focused’ improvements could be penalized using the new ICD-10-CM Agency for Healthcare Research and Quality PSIs because of apparent increases in PSIs bearing the same PSI identifier and label, yet calculated differently. Here we investigate which PSIs would reliably transition between ICD-9-CM and ICD-10-CM, and those at risk of under-reporting and over-reporting adverse events while the frequency of these adverse events remain unchanged.

Identifying Clinically Disruptive International Classification of Diseases 10th Revision Clinical Modification Conversions to Mitigate Financial Costs Using an Online Tool

PURPOSE To quantify coding ambiguity in International Classification of Diseases Ninth Revision Clinical Modification conversions (ICD-9-CM) to ICD-10-CM mappings for hematology-oncology diagnoses within an Illinois Medicaid database and an academic cancer center database (University of Illinois Cancer Center [UICC]) with the goal of anticipating challenges during ICD-10-CM transition. METHODS One data set of ICD-9-CM diagnosis codes came from the 2010 Illinois Department of Medicaid, filtered for diagnoses generated by hematology-oncology providers. The other data set of ICD-9-CM diagnosis codes came from UICC. Using a translational methodology via the Motif Web portal ICD-9-CM conversion tool, ICD-9-CM to ICD-10-CM code conversions were graphically mapped and evaluated for clinical loss of information. RESULTS The transition to ICD-10-CM led to significant information loss, affecting 8% of total Medicaid codes and 1% of UICC codes; 39 ICD-9-CM codes with information loss accounted for 2.9% of total Medicaid reimbursements and 5.3% of UICC billing charges. CONCLUSION Prior work stated hematology-oncology would be the least affected medical specialty. However, information loss affecting 5% of billing costs could evaporate the operating margin of a practice. By identifying codes at risk for complex transitions, the analytic tools described can be replicated for oncology practices to forecast areas requiring additional training and resource allocation. In summary, complex transitions and diagnosis codes associated with information loss within clinical oncology require additional attention during the transition to ICD-10-CM.

A formal approach to discovering simultaneous additive masking between auditory medical alarms

The failure of humans to respond to auditory medical alarms has resulted in numerous patient injuries and deaths and is thus a major safety concern. A relatively understudied source of response failures has to do with simultaneous masking, a condition where concurrent sounds interact in ways that make one or more of them imperceptible due to physical limitations of human perception. This paper presents a method, which builds on a previous implementation, that uses a novel combination of psychophysical modeling and formal verification with model checking to detect masking in a modeled configuration of medical alarms. Specifically, the new method discussed here improves the original method by adding the ability to detect additive masking while concurrently improving method usability and scalability. This paper describes how these additions to our method were realized. It then demonstrates the scalability and detection improvements via three different case studies. Results and future research are discussed.