Research and applications: 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.     

Can poison control data be used for pharmaceutical poisoning surveillance?

Objective

To determine the association between the frequencies of pharmaceutical exposures reported to a poison control center (PCC) and those seen in the emergency department (ED).

Design

A statewide population-based retrospective comparison of frequencies of ED pharmaceutical poisonings with frequencies of pharmaceutical exposures reported to a regional PCC. ED poisonings, identified by International Classification of Diseases, Version 9 (ICD-9) codes, were grouped into substance categories. Using a reproducible algorithm facilitated by probabilistic linkage, codes from the PCC classification system were mapped into the same categories. A readily identifiable subset of PCC calls was selected for comparison.

Measurements

Correlations between frequencies of quarterly exposures by substance categories were calculated using Pearson correlation coefficients and partial correlation coefficients with adjustment for seasonality.

Results

PCC reported exposures correlated with ED poisonings in nine of 10 categories. Partial correlation coefficients (r_p) indicated strong associations (r_p>0.8) for three substance categories that underwent large changes in their incidences (opiates, benzodiazepines, and muscle relaxants). Six substance categories were moderately correlated (r_p>0.6). One category, salicylates, showed no association.

Limitations

Imperfect overlap between ICD-9 and PCC codes may have led to miscategorization. Substances without changes in exposure frequency have inadequate variability to detect association using this method.

Conclusion

PCC data are able to effectively identify trends in poisonings seen in EDs and may be useful as part of a pharmaceutical poisoning surveillance system. The authors developed an algorithm-driven technique for mapping American Association of Poison Control Centers codes to ICD-9 codes and identified a useful subset of poison control exposures for analysis.     

Migrating existing clinical content from ICD-9 to SNOMED

Objective

To identify challenges in mapping internal International Classification of Disease, 9th edition, Clinical Modification (ICD-9-CM) encoded legacy data to Systematic Nomenclature of Medicine (SNOMED), using SNOMED-prescribed compositional approaches where appropriate, and to explore the mapping coverage provided by the US National Library of Medicine (NLM)''s SNOMED clinical core subset.

Design

This study selected ICD-CM codes that occurred at least 100 times in the organization''s problem list or diagnosis data in 2008. After eliminating codes whose exact mappings were already available in UMLS, the remainder were mapped manually with software assistance.

Results

Of the 2194 codes, 784 (35.7%) required manual mapping. 435 of these represented concept types documented in SNOMED as deprecated: these included the qualifying phrases such as ‘not elsewhere classified’. A third of the codes were composite, requiring multiple SNOMED code to map. Representing 45 composite concepts required introducing disjunction (‘or’) or set-difference (‘without’) operators, which are not currently defined in SNOMED. Only 47% of the concepts required for composition were present in the clinical core subset. Search of SNOMED for the correct concepts often required extensive application of knowledge of both English and medical synonymy.

Conclusion

Strategies to deal with legacy ICD data must address the issue of codes created by non-taxonomist users. The NLM core subset possibly needs augmentation with concepts from certain SNOMED hierarchies, notably qualifiers, body structures, substances/products and organisms. Concept-matching software needs to utilize query expansion strategies, but these may be effective in production settings only if a large but non-redundant SNOMED subset that minimizes the proportion of extensively pre-coordinated concepts is also available.     

Applying MetaMap to Medline for identifying novel associations in a large clinical dataset: a feasibility analysis

Objective

We describe experiments designed to determine the feasibility of distinguishing known from novel associations based on a clinical dataset comprised of International Classification of Disease, V.9 (ICD-9) codes from 1.6 million patients by comparing them to associations of ICD-9 codes derived from 20.5 million Medline citations processed using MetaMap. Associations appearing only in the clinical dataset, but not in Medline citations, are potentially novel.

Methods

Pairwise associations of ICD-9 codes were independently identified in both the clinical and Medline datasets, which were then compared to quantify their degree of overlap. We also performed a manual review of a subset of the associations to validate how well MetaMap performed in identifying diagnoses mentioned in Medline citations that formed the basis of the Medline associations.

Results

The overlap of associations based on ICD-9 codes in the clinical and Medline datasets was low: only 6.6% of the 3.1 million associations found in the clinical dataset were also present in the Medline dataset. Further, a manual review of a subset of the associations that appeared in both datasets revealed that co-occurring diagnoses from Medline citations do not always represent clinically meaningful associations.

Discussion

Identifying novel associations derived from large clinical datasets remains challenging. Medline as a sole data source for existing knowledge may not be adequate to filter out widely known associations.

Conclusions

In this study, novel associations were not readily identified. Further improvements in accuracy and relevance for tools such as MetaMap are needed to realize their expected utility.     

Leveraging informatics for genetic studies: use of the electronic medical record to enable a genome-wide association study of peripheral arterial disease

Background

There is significant interest in leveraging the electronic medical record (EMR) to conduct genome-wide association studies (GWAS).

Methods

A biorepository of DNA and plasma was created by recruiting patients referred for non-invasive lower extremity arterial evaluation or stress ECG. Peripheral arterial disease (PAD) was defined as a resting/post-exercise ankle-brachial index (ABI) less than or equal to 0.9, a history of lower extremity revascularization, or having poorly compressible leg arteries. Controls were patients without evidence of PAD. Demographic data and laboratory values were extracted from the EMR. Medication use and smoking status were established by natural language processing of clinical notes. Other risk factors and comorbidities were ascertained based on ICD-9-CM codes, medication use and laboratory data.

Results

Of 1802 patients with an abnormal ABI, 115 had non-atherosclerotic vascular disease such as vasculitis, Buerger''s disease, trauma and embolism (phenocopies) based on ICD-9-CM diagnosis codes and were excluded. The PAD cases (66±11 years, 64% men) were older than controls (61±8 years, 60% men) but had similar geographical distribution and ethnic composition. Among PAD cases, 1444 (85.6%) had an abnormal ABI, 233 (13.8%) had poorly compressible arteries and 10 (0.6%) had a history of lower extremity revascularization. In a random sample of 95 cases and 100 controls, risk factors and comorbidities ascertained from EMR-based algorithms had good concordance compared with manual record review; the precision ranged from 67% to 100% and recall from 84% to 100%.

Conclusion

This study demonstrates use of the EMR to ascertain phenocopies, phenotype heterogeneity and relevant covariates to enable a GWAS of PAD. Biorepositories linked to EMR may provide a relatively efficient means of conducting GWAS.     

Evaluation of factors influencing intention to quit smokeless and cigarette tobacco use among Nigerian adolescents

Background:

Smokeless and cigarette tobacco use is becoming increasingly popular among Nigerian adolescents. This study aimed to evaluate predictors of intention to quit tobacco use among adolescents that currently use tobacco products in Nigeria.

Materials and Methods:

A total of 536 male and female high school students in senior classes in Benue State, Nigeria were enrolled into the cross-sectional study. The survey instrument was adapted from the Global Youth Tobacco Survey (GYTS) questionnaire.

Results:

Among adolescents with tobacco habits, 80.5% of smokeless tobacco users and 82.8% of cigarette smokers intended to quit tobacco use within 12 months. After adjustment, significant predictors of intention to quit cigarette smoking were parents’ smoking status (P<0.01), peers’ smokeless use status (P<0.01) and perception that smoking made one comfortable at social events (P<0.01). For intention to quit smokeless tobacco use, significant predictors after adjustment were parents’ smokeless use status, (P=0.03) perception that smokeless tobacco use made one more comfortable at social events (P=0.04) and perception of harm from smokeless use (P=0.02).

Conclusion:

This study demonstrates that the intention to quit smokeless and cigarette tobacco use is significantly predicted by perception about the societal acceptance of tobacco use at social events, parents and peers’ tobacco use status as well as the perception of harm from use of tobacco products. Providing social support may increase quit attempts among youth smokers.     

Influenza surveillance using electronic health records in the American Indian and Alaska Native population

Objective

Increasing use of electronic health records (EHRs) provides new opportunities for public health surveillance. During the 2009 influenza A (H1N1) virus pandemic, we developed a new EHR-based influenza-like illness (ILI) surveillance system designed to be resource sparing, rapidly scalable, and flexible. 4 weeks after the first pandemic case, ILI data from Indian Health Service (IHS) facilities were being analyzed.

Materials and methods

The system defines ILI as a patient visit containing either an influenza-specific International Classification of Disease, V.9 (ICD-9) code or one or more of 24 ILI-related ICD-9 codes plus a documented temperature ≥100°F. EHR-based data are uploaded nightly. To validate results, ILI visits identified by the new system were compared to ILI visits found by medical record review, and the new system''s results were compared with those of the traditional US ILI Surveillance Network.

Results

The system monitored ILI activity at an average of 60% of the 269 IHS electronic health databases. EHR-based surveillance detected ILI visits with a sensitivity of 96.4% and a specificity of 97.8% based on chart review (N=2375) of visits at two facilities in September 2009. At the peak of the pandemic (week 41, October 17, 2009), the median time from an ILI visit to data transmission was 6 days, with a mode of 1 day.

Discussion

EHR-based ILI surveillance was accurate, timely, occurred at the majority of IHS facilities nationwide, and provided useful information for decision makers. EHRs thus offer the opportunity to transform public health surveillance.     

Patient engagement in the inpatient setting: a systematic review

Objective

To systematically review existing literature regarding patient engagement technologies used in the inpatient setting.

Methods

PubMed, Association for Computing Machinery (ACM) Digital Library, Institute of Electrical and Electronics Engineers (IEEE) Xplore, and Cochrane databases were searched for studies that discussed patient engagement (‘self-efficacy’, ‘patient empowerment’, ‘patient activation’, or ‘patient engagement’), (2) involved health information technology (‘technology’, ‘games’, ‘electronic health record’, ‘electronic medical record’, or ‘personal health record’), and (3) took place in the inpatient setting (‘inpatient’ or ‘hospital’). Only English language studies were reviewed.

Results

17 articles were identified describing the topic of inpatient patient engagement. A few articles identified design requirements for inpatient engagement technology. The remainder described interventions, which we grouped into five categories: entertainment, generic health information delivery, patient-specific information delivery, advanced communication tools, and personalized decision support.

Conclusions

Examination of the current literature shows there are considerable gaps in knowledge regarding patient engagement in the hospital setting and inconsistent use of terminology regarding patient engagement overall. Research on inpatient engagement technologies has been limited, especially concerning the impact on health outcomes and cost-effectiveness.     

Resolution pattern of jaundice among children presenting with severe malaria in rural South-West Nigeria

Objective

To compare the pattern of jaundice resolution among children with severe malaria treated with quinine and artemether.

Methods

Thirty two children who fulfilled the inclusion criteria were recruited for the study from two hospitals with intensive care facilities. They were divided into two groups; ‘Q’ and ‘A’, receiving quinine and artemether, respectively. Jaundice was assessed by clinical examination.

Results

Sixteen out of 32 children recruited (representing 50%) presented with jaundice on the day of recruitment. The mean age was (7.00°C2.56) years. On day 3, four patients in ‘A’ and six patients in ‘Q’ had jaundice. By day 7, no child had jaundice.

Conclusion

The study has shown that both drugs resolve jaundice although artemether relatively resolves it faster by the third day.     

Longitudinal analysis of pain in patients with metastatic prostate cancer using natural language processing of medical record text

Objectives

To test the feasibility of using text mining to depict meaningfully the experience of pain in patients with metastatic prostate cancer, to identify novel pain phenotypes, and to propose methods for longitudinal visualization of pain status.

Materials and methods

Text from 4409 clinical encounters for 33 men enrolled in a 15-year longitudinal clinical/molecular autopsy study of metastatic prostate cancer (Project to ELIminate lethal CANcer) was subjected to natural language processing (NLP) using Unified Medical Language System-based terms. A four-tiered pain scale was developed, and logistic regression analysis identified factors that correlated with experience of severe pain during each month.

Results

NLP identified 6387 pain and 13 827 drug mentions in the text. Graphical displays revealed the pain ‘landscape’ described in the textual records and confirmed dramatically increasing levels of pain in the last years of life in all but two patients, all of whom died from metastatic cancer. Severe pain was associated with receipt of opioids (OR=6.6, p<0.0001) and palliative radiation (OR=3.4, p=0.0002). Surprisingly, no severe or controlled pain was detected in two of 33 subjects’ clinical records. Additionally, the NLP algorithm proved generalizable in an evaluation using a separate data source (889 Informatics for Integrating Biology and the Bedside (i2b2) discharge summaries).

Discussion

Patterns in the pain experience, undetectable without the use of NLP to mine the longitudinal clinical record, were consistent with clinical expectations, suggesting that meaningful NLP-based pain status monitoring is feasible. Findings in this initial cohort suggest that ‘outlier’ pain phenotypes useful for probing the molecular basis of cancer pain may exist.

Limitations

The results are limited by a small cohort size and use of proprietary NLP software.

Conclusions

We have established the feasibility of tracking longitudinal patterns of pain by text mining of free text clinical records. These methods may be useful for monitoring pain management and identifying novel cancer phenotypes.     

Psychological Well-being of Medical Students

Background

Training in medicine is emotionally demanding. Psychological well being of medical students is a matter of concern. There is lack of Indian studies in this area.

Methods

A total of 105 medical student of one batch were assessed utilizing psychophysiological state inventory, Institute for personality and ability testing (IPAT) anxiety and depression scale, achievement motivation scale, scale for locus of control and 16 PF in three phases at one-year intervals.

Result

Majority of the students had average achievement, motivation and adaptability. Anxiety and depression scores fell within normal limits. In personality profile factor ‘B’, ‘M’ and ‘Q4₁’ had changed significantly. Achievement motivation showed significant decreases and CSS1 and PO1 scores showed significant increase during the years of medical education.

Conclusion

The results demonstrate that over satisfaction and relaxed attitude may have poor academic outcome.Key Words: Psychological well-being, Anxiety, Depression, Achievement motivation     

Tobacco consumption and its association with education among women residing in a rural area of Maharashtra: A?cross-sectional study

Background

Tobacco use is increasing among women and girls across the globe as well as in all parts of India. In India, 8 to 10 lakh people die due to tobacco related diseases every year. This tobacco epidemic among women needs to be prevented.

Objectives

Study was conducted to find the prevalence and pattern of tobacco consumption and it''s association with education among females (15–49 years) in a rural village of Pune, Maharashtra, India.

Material and Methods

A cross-sectional study was carried out among 313 females (15–49 years) in a rural field practice area of a Medical College in Pune during Feb 11 to May 11. Pre-tested questionnaire was used for collecting data by interview after obtaining informed consent. Statistical analysis was performed (Epinfo software version 3.5.3.).

Results

Out of 313 female studied, 14.05% (44) and 0.96% (03) were found to be current and former tobacco user respectively while 84.98% (266) never used any form of tobacco in their lifetime. Mishri consumption (45%) was commonest form of smokeless tobacco use followed by quid use (36%). Majority of the tobacco users (54.55%) were illiterate. There was significant association between tobacco consumption and education level (p = 0.0295). Tobacco consumption was more with increasing age.

Conclusion

Tobacco consumption was found to be prevalent in 14.05% of women. Almost all of them used smokeless tobacco, mainly mishri. Tobacco consumption was directly associated with age and inversely with educational level. Therefore increasing women''s literacy may bring down tobacco use among women.     

Waterpipe (narghile) smoking among medical and non-medical university students in Turkey

Objectives

This investigation was performed in order to determine the prevalence rate of waterpipe smoking in students of Erciyes University and the effects of some socio-demographic factors.

Methods

A total of 645 students who study the first three grades of the medical faculty and the engineering faculty of Erciyes University were enrolled in the study. A questionnaire including 48 questions was applied. Chi-square test and logistic regression method were performed for the statistical analyses.

Results

The total prevalence rate of waterpipe smoking was found to be 32.7%. The prevalence rate of waterpipe smoking was 28.6% in the medical and 37.5% in the non-medical students. It was determined that 41.6% of the males and 20.2% of the females currently smoke waterpipe. Gender, cigarette smoking, and the presence of waterpipe smokers among family members and friends have significant effects on the prevalence of waterpipe smoking. Residence and economical status of the family and with whom the students live have no significant effect on the prevalence rate.

Conclusions

Approximately one-third of the students currently smoke waterpipe. Smoking of both cigarette and waterpipe was frequently found. The measures against all tobacco products should be combined.     

Psychosocial Variables of Voluntary Blood Donors at Blood Bank of a Medical College

Background

This study was undertaken to study the motivational factors leading to voluntary blood donation and understanding the psychosocial variables of blood donors.

Methods

300 blood donors were selected by systematic random sampling method.

Result

It was observed that most of the voluntary donors were males (89.3%) and belonged to age group 16-25 years (48%). Most of the donors (93.46%) had studied upto high school and above and 84.33% of the donors belonged to the middle class. 27% of the donors had donated blood previously. The common motivational factors to donate blood were for ‘a good cause'', ‘for the society’ and ‘to save a life''. 4.67% of them donated blood for self satisfaction.

Conclusion

Motivation, recruitment and retention of voluntary blood donors are important criteria to achieve safe blood donation.Key Words: Motivation, Psychosocial, Voluntary, Blood Donors     

Mediation of adoption and use: a key strategy for mitigating unintended consequences of health IT implementation

Objective

Without careful attention to the work of users, implementation of health IT can produce new risks and inefficiencies in care. This paper uses the technology use mediation framework to examine the work of a group of nurses who serve as mediators of the adoption and use of a barcode medication administration (BCMA) system in an inpatient setting.

Materials and methods

The study uses ethnographic methods to explore the mediators'' work. Data included field notes from observations, documents, and email communications. This variety of sources enabled triangulation of findings between activities observed, discussed in meetings, and reported in emails.

Results

Mediation work integrated the BCMA tool with nursing practice, anticipating and solving implementation problems. Three themes of mediation work include: resolving challenges related to coordination, integrating the physical aspects of BCMA into everyday practice, and advocacy work.

Discussion

Previous work suggests the following factors impact mediation effectiveness: proximity to the context of use, understanding of users'' practices and norms, credibility with users, and knowledge of the technology and users'' technical abilities. We describe three additional factors observed in this case: ‘influence on system developers,’ ‘influence on institutional authorities,’ and ‘understanding the network of organizational relationships that shape the users'' work.’

Conclusion

Institutionally supported clinicians who facilitate adoption and use of health IT systems can improve the safety and effectiveness of implementation through the management of unintended consequences. Additional research on technology use mediation can advance the science of implementation by providing decision-makers with theoretically durable, empirically grounded evidence for designing implementations.     

Efficacy of Deltamethrin and Cyfluthrin Impregnated Cloth over Uniform against Mosquito Bites

Background

The difficulty with insecticide treated mosquito nets is that in military operation, it may not be practical for the personnel to carry mosquito nets with them. In mobile military operations, availability of pre-treated ‘patches of cloth’ or ‘bands’, which can be applied over the uniform at strategic sites, could be a feasible alternative.

Methods

A double blind randomised controlled trial was undertaken among troops deployed in counter-insurgency operations in the northeastern parts of the country, to assess the efficacy of synthetic pyrethroid pretreated patches in reducing man mosquito contact, as compared to conventional repellents.

Result

The study indicated that pretreated patches, when affixed over the uniform, provided significantly higher protection from mosquito bites, when used in addition to the conventional repellents.

Conclusion

The study recommends that synthetic pyrethroid treated patches be made available to troops operating in highly malarious areas.Key Words: Synthetic pyrethroid treated patches, Man-mosquito contact     

Research and applications: Role of genetic heterogeneity and epistasis in bladder cancer susceptibility and outcome: a learning classifier system approach

Background and objective

Detecting complex patterns of association between genetic or environmental risk factors and disease risk has become an important target for epidemiological research. In particular, strategies that provide multifactor interactions or heterogeneous patterns of association can offer new insights into association studies for which traditional analytic tools have had limited success.

Materials and methods

To concurrently examine these phenomena, previous work has successfully considered the application of learning classifier systems (LCSs), a flexible class of evolutionary algorithms that distributes learned associations over a population of rules. Subsequent work dealt with the inherent problems of knowledge discovery and interpretation within these algorithms, allowing for the characterization of heterogeneous patterns of association. Whereas these previous advancements were evaluated using complex simulation studies, this study applied these collective works to a ‘real-world’ genetic epidemiology study of bladder cancer susceptibility.

Results and discussion

We replicated the identification of previously characterized factors that modify bladder cancer risk—namely, single nucleotide polymorphisms from a DNA repair gene, and smoking. Furthermore, we identified potentially heterogeneous groups of subjects characterized by distinct patterns of association. Cox proportional hazard models comparing clinical outcome variables between the cases of the two largest groups yielded a significant, meaningful difference in survival time in years (survivorship). A marginally significant difference in recurrence time was also noted. These results support the hypothesis that an LCS approach can offer greater insight into complex patterns of association.

Conclusions

This methodology appears to be well suited to the dissection of disease heterogeneity, a key component in the advancement of personalized medicine.     

Automated concept-level information extraction to reduce the need for custom software and rules development

Objective

Despite at least 40 years of promising empirical performance, very few clinical natural language processing (NLP) or information extraction systems currently contribute to medical science or care. The authors address this gap by reducing the need for custom software and rules development with a graphical user interface-driven, highly generalizable approach to concept-level retrieval.

Materials and methods

A ‘learn by example’ approach combines features derived from open-source NLP pipelines with open-source machine learning classifiers to automatically and iteratively evaluate top-performing configurations. The Fourth i2b2/VA Shared Task Challenge''s concept extraction task provided the data sets and metrics used to evaluate performance.

Results

Top F-measure scores for each of the tasks were medical problems (0.83), treatments (0.82), and tests (0.83). Recall lagged precision in all experiments. Precision was near or above 0.90 in all tasks.

Discussion

With no customization for the tasks and less than 5 min of end-user time to configure and launch each experiment, the average F-measure was 0.83, one point behind the mean F-measure of the 22 entrants in the competition. Strong precision scores indicate the potential of applying the approach for more specific clinical information extraction tasks. There was not one best configuration, supporting an iterative approach to model creation.

Conclusion

Acceptable levels of performance can be achieved using fully automated and generalizable approaches to concept-level information extraction. The described implementation and related documentation is available for download.     

MITRE system for clinical assertion status classification

Objective

To describe a system for determining the assertion status of medical problems mentioned in clinical reports, which was entered in the 2010 i2b2/VA community evaluation ‘Challenges in natural language processing for clinical data’ for the task of classifying assertions associated with problem concepts extracted from patient records.

Materials and methods

A combination of machine learning (conditional random field and maximum entropy) and rule-based (pattern matching) techniques was used to detect negation, speculation, and hypothetical and conditional information, as well as information associated with persons other than the patient.

Results

The best submission obtained an overall micro-averaged F-score of 0.9343.

Conclusions

Using semantic attributes of concepts and information about document structure as features for statistical classification of assertions is a good way to leverage rule-based and statistical techniques. In this task, the choice of features may be more important than the choice of classifier algorithm.