Queuing Theory to Guide the Implementation of a Heart Failure Inpatient Registry Program

Objective

The authors previously implemented an electronic heart failure registry at a large academic hospital to identify heart failure patients and to connect these patients with appropriate discharge services. Despite significant improvements in patient identification and connection rates, time to connection remained high, with an average delay of 3.2 days from the time patients were admitted to the time connections were made. Our objective for this current study was to determine the most effective solution to minimize time to connection.

Design

We used a queuing theory model to simulate 3 different potential solutions to decrease the delay from patient identification to connection with discharge services.

Measurements

The measures included average rate at which patients were being connected to the post discharge heart failure services program, average number of patients in line, and average patient waiting time.

Results

Using queuing theory model simulations, we were able to estimate for our current system the minimum rate at which patients need to be connected (262 patients/mo), the ideal patient arrival rate (174 patients/mo) and the maximal patient arrival rate that could be achieved by adding 1 extra nurse (348 patients/mo).

Conclusions

Our modeling approach was instrumental in helping us characterize key process parameters and estimate the impact of adding staff on the time between identifying patients with heart failure and connecting them with appropriate discharge services.     

Disparities in Use of a Personal Health Record in a Managed Care Organization

Objective

Personal health records (PHRs) can increase patient access to health care information. However, use of PHRs may be unequal by race/ethnicity.

Design

The authors conducted a 2-year cohort study (2005-2007) assessing differences in rates of registration with KP.org, a component of the Kaiser Permanente electronic health record (EHR).

Measurements

At baseline, 1,777 25-59 year old Kaiser Permanente Georgia enrollees, who had not registered with KP.org, responded to a mixed mode (written or Internet) survey. Baseline, EHR, and KP.org data were linked. Time to KP.org registration by race from 10/1/05 (with censoring for disenrollment from Kaiser Permanente) was adjusted for baseline education, comorbidity, patient activation, and completion of the baseline survey online vs. by paper using Cox proportional hazards.

Results

Of 1,777, 34.7% (616) registered with KP.org between Oct 2005 and Nov 2007. Median time to registering a KP.org account was 409 days. Among African Americans, 30.1% registered, compared with 41.7% of whites (p < 0.01). In the hazards model, African Americans were again less likely to register than whites (hazard ratio [HR] = 0.652, 95% CI: 0.549-0.776) despite adjustment. Those with baseline Internet access were more likely to register (HR = 1.629, 95% CI: 1.294-2.050), and a significant educational gradient was also observed (more likely registration with higher educational levels).

Conclusions

Differences in education, income, and Internet access did not account for the disparities in PHR registration by race. In the short-term, attempts to improve patient access to health care with PHRs may not ameliorate prevailing disparities between African Americans and whites.     

Evaluation of a Method to Identify and Categorize Section Headers in Clinical Documents

Objective

Clinical notes, typically written in natural language, often contain substructure that divides them into sections, such as “History of Present Illness” or “Family Medical History.” The authors designed and evaluated an algorithm (“SecTag”) to identify both labeled and unlabeled (implied) note section headers in “history and physical examination” documents (“H&P notes”).

Design

The SecTag algorithm uses a combination of natural language processing techniques, word variant recognition with spelling correction, terminology-based rules, and naive Bayesian scoring methods to identify note section headers. Eleven physicians evaluated SecTag's performance on 319 randomly chosen H&P notes.

Measurements

The primary outcomes were the algorithm's recall and precision in identifying all document sections and a predefined list of twenty-nine major sections. A secondary outcome was to evaluate the algorithm's ability to recognize the correct start and end boundaries of identified sections.

Results

The SecTag algorithm identified 16,036 total sections and 7,858 major sections. Physician evaluators classified 15,329 as true positives and identified 160 sections omitted by SecTag. The recall and precision of the SecTag algorithm were 99.0 and 95.6% for all sections, 98.6 and 96.2% for major sections, and 96.6 and 86.8% for unlabeled sections. The algorithm determined the correct starting and ending text boundaries for 94.8% of labeled sections and 85.9% of unlabeled sections.

Conclusions

The SecTag algorithm accurately identified both labeled and unlabeled sections in history and physical documents. This type of algorithm may assist in natural language processing applications, such as clinical decision support systems or competency assessment for medical trainees.     

The Influence that Electronic Prescribing Has on Medication Errors and Preventable Adverse Drug Events: an Interrupted Time-series Study

Objective

This study evaluated the effect of a Computerized Physician Order Entry system with basic Clinical Decision Support (CPOE/CDSS) on the incidence of medication errors (MEs) and preventable adverse drug events (pADEs).

Design

Interrupted time-series design.

Measurements

The primary outcome measurements comprised the percentage of medication orders with one or more MEs and the percentage of patients with one or more pADEs.

Results

Pre-implementation, the mean percentage of medication orders containing at least one ME was 55%, whereas this became 17% post-implementation. The introduction of CPOE/CDSS has led to a significant immediate absolute reduction of 40.3% (95% CI: −45.13%; −35.48%) in medication orders with one or more errors.Pre-implementation, the mean percentage of admitted patients experiencing at least one pADE was 15.5%, as opposed to 7.3% post-implementation. However, this decrease could not be attributed to the introduction of CPOE/CDSS: taking into consideration the interrupted time-series design, the immediate change was not significant (−0.42%, 95% CI: −15.52%; 14.68%) because of the observed underlying negative trend during the pre-CPOE period of −4.04% [95% CI: −7.70%; −0.38%] per month.

Conclusions

This study has shown that CPOE/CDSS reduces the incidence of medication errors. However, a direct effect on actual patient harm (pADEs) was not demonstrated.     

Early predictors of success of non-invasive positive pressure ventilation in hypercapnic respiratory failure

Background

Non-invasive positive pressure ventilation (NIPPV) has emerged as a significant advancement in the management of acute hypercapnic respiratory failure.

Method

Patients with hypercapnic respiratory failure requiring ventilation therapy (respiratory rate [RR] of > 30 breaths per minutes, PaCO2 > 55 mmHg and arterial pH < 7.35) were included in the study. Baseline clinical parameters and arterial blood gas (ABG) were recorded before initiating NIPPV. Clinical parameters including heart rate (HR), RR, oxygen saturation and ABG were revaluated at 1, 4, and 24 hours after initiation of NIPPV. Change in these parameters and need for intubation was evaluated.

Results

Of the 100 patients, 76 (76%) showed improvement in clinical parameters and ABG. There was improvement in HR and RR, pH, and PCO2 within the first hour in the success group and these parameters continued to improve even after four and 24 hours of NIPPV treatment. Out of 24 (24%) patients who failed to respond, 13 (54%) needed endotracheal intubation within one hour. The failure group had higher baseline HR than the success group.

Conclusion

Improvement in HR, RR, pH, and PCO2 one hour after putting the patient on NIPPV predicts success of non-invasive positive pressure ventilation in hypercapnic respiratory failure.     

A Randomized Trial Comparing Telemedicine Case Management with Usual Care in Older, Ethnically Diverse, Medically Underserved Patients with Diabetes Mellitus: 5 Year Results of the IDEATel Study

Context

Telemedicine is a promising but largely unproven technology for providing case management services to patients with chronic conditions and lower access to care.

Objectives

To examine the effectiveness of a telemedicine intervention to achieve clinical management goals in older, ethnically diverse, medically underserved patients with diabetes.

Design, Setting, and Patients

A randomized controlled trial was conducted, comparing telemedicine case management to usual care, with blinded outcome evaluation, in 1,665 Medicare recipients with diabetes, aged ≥ 55 years, residing in federally designated medically underserved areas of New York State.

Interventions

Home telemedicine unit with nurse case management versus usual care.

Main Outcome Measures

The primary endpoints assessed over 5 years of follow-up were hemoglobin A1c (HgbA1c), low density lipoprotein (LDL) cholesterol, and blood pressure levels.

Results

Intention-to-treat mixed models showed that telemedicine achieved net overall reductions over five years of follow-up in the primary endpoints (HgbA1c, p = 0.001; LDL, p < 0.001; systolic and diastolic blood pressure, p = 0.024; p < 0.001). Estimated differences (95% CI) in year 5 were 0.29 (0.12, 0.46)% for HgbA1c, 3.84 (−0.08, 7.77) mg/dL for LDL cholesterol, and 4.32 (1.93, 6.72) mm Hg for systolic and 2.64 (1.53, 3.74) mm Hg for diastolic blood pressure. There were 176 deaths in the intervention group and 169 in the usual care group (hazard ratio 1.01 [0.82, 1.24]).

Conclusions

Telemedicine case management resulted in net improvements in HgbA1c, LDL-cholesterol and blood pressure levels over 5 years in medically underserved Medicare beneficiaries. Mortality was not different between the groups, although power was limited.

Trial Registration

http://clinicaltrials.gov Identifier: NCT00271739.     

Using Semantic and Structural Properties of the Unified Medical Language System to Discover Potential Terminological Relationships

Objective

To use the semantic and structural properties in the Unified Medical Language System (UMLS) Metathesaurus to characterize and discover potential relationships.

Design

The UMLS integrates knowledge from several biomedical terminologies. This knowledge can be used to discover implicit semantic relationships between concepts. In this paper, the authors propose a problem-independent approach for discovering potential terminological relationships that employs semantic abstraction of indirect relationship paths to perform classification and analysis of network theoretical measures such as topological overlap, preferential attachment, graph partitioning, and number of indirect paths. Using different versions of the UMLS, the authors evaluate the proposed approach's ability to predict newly added relationships.

Measurements

Classification accuracy, precision-recall.

Results

Strong discriminative characteristics were observed with a semantic abstraction based classifier (classification accuracy of 91%), the average number of indirect paths, preferential attachment, and graph partitioning to identify potential relationships. The proposed relationship prediction algorithm resulted in 56% recall in top 10 results for new relationships added to subsequent versions of the UMLS between 2005 and 2007.

Conclusions

The UMLS has sufficient knowledge to enable discovery of potential terminological relationships.     

The Use of Wireless E-Mail to Improve Healthcare Team Communication

Objective

To assess the impact of using wireless e-mail for clinical communication in an intensive care unit (ICU).

Design

The authors implemented push wireless e-mail over a GSM cellular network in a 26-bed ICU during a 6-month study period. Daytime ICU staff (intensivists, nurses, respiratory therapists, pharmacists, clerical staff, and ICU leadership) used handheld devices (BlackBerry, Research in Motion, Waterloo, ON) without dedicated training. The authors recorded e-mail volume and used standard methods to develop a self-administered survey of ICU staff to measure wireless e-mail impact.

Measurements

The survey assessed perceived impact of wireless e-mail on communication, team relationships, staff satisfaction and patient care. Answers were recorded on a 7-point Likert scale; favorable responses were categorized as Likert responses 5, 6, and 7.

Results

Staff sent 5.2 (1.9) and received 8.9 (2.1) messages (mean [SD]) per day during 5 months of the 6-month study period; usage decreased after study completion. Most (106/125 [85%]) staff completed the questionnaire. The majority reported that wireless e-mail improved speed (92%) and reliability (92%) of communication, improved coordination of ICU team members (88%), reduced staff frustration (75%), and resulted in faster (90%) and safer (75%) patient care; Likert responses were significantly different from neutral (p < 0.001 for all). Staff infrequently (18%) reported negative effects on communication. There were no reports of radiofrequency interference with medical devices.

Conclusions

Interdisciplinary ICU staff perceived wireless e-mail to improve communication, team relationships, staff satisfaction, and patient care. Further research should address the impact of wireless e-mail on efficiency and timeliness of staff workflow and clinical outcomes.     

Effects of a Pharmacist-to-Dose Computerized Request on Promptness of Antimicrobial Therapy

Objectives

To examine the effects of computerized requests for pharmacist-to-dose (PTD), an advanced clinical decision support tool for dosing guidance, on antimicrobial therapy with vancomycin and aminoglycosides, describe PTD request utilization, and identify factors that may prolong this process.

Design

A retrospective review was conducted of patients hospitalized from Jan 2004 to Jun 2006 with suspected pneumonia who received vancomycin, tobramycin, or gentamicin via PTD (study) or routine provider order entry (control).

Measurements

The primary endpoint was time to pharmacist completion of PTD request. Secondary data points included medication turn-around times for first doses of vancomycin or aminoglycosides and for first doses of any antibiotic, dose adjustment for renal dysfunction, medication errors, and time of order entry. Multivariate analysis was conducted to identify predictors of total time to pharmacist verification and time to administration of first doses of vancomycin or aminoglycosides.

Results

Median time for pharmacist completion of PTD requests was 29 minutes. Delays were noted in the study group (n = 49) by comparison with the control group (n = 48) for median time to first dose of vancomycin or aminoglycoside (185 vs. 138 min, p = 0.45) and for any antibiotic (134 vs. 118 min, p = 0.42), respectively. Fewer medication errors were reported in the study group (5 vs. 18 errors, p = 0.002). In a multivariate model, PTD was not significantly predictive of time to pharmacy verification or medication turn-around time.

Conclusions

Pharmacists completed pharmacist-to-dose consultations for dosing guidance of vancomycin and aminoglycosides within a median of 30 minutes. Implementation of a computerized request for clinical pharmacists to provide medication-related clinical decision support increased medication turn-around time of vancomycin and aminoglycosides and reduced medication errors. Consultation of clinical pharmacists by computerized request for initial antibiotic dosing of medications with narrow therapeutic windows is an option for medication-related clinical decision support but providers should be aware that consultation may delay medication turn-around time.     

Article not available electronically: Neurocognitive impairment in alcohol-dependence syndrome cases and its response to treatment

Background

A sizeable portion of psychiatric ward beds in military hospitals is occupied by patients with psychoactive substance abuse and especially by alcohol-dependence syndrome (ADS) cases. Though there have been significant advances in the diagnosis and management of these cases, not much of work has been done in our set up for the evaluation of their cognitive impairment and its response to treatment.

Methods

Neuropsychological evaluation of 100 cases of freshly diagnosed ADS was done by using postgraduate battery of brain dysfunction (PGI-BBD). The findings were compared with controls. They were detoxified, treated and after four weeks were re-evaluated and the findings were analysed.

Results

There was significant impairment in all parameters of cognition. All of them showed improvement with treatment but after four weeks, the impairment persisted to significant level in some parameters.

Conclusion

Alcohol-dependence syndrome cases have significant cognitive impairment but improve with detoxification, multivitamin supplement and abstinence. This aspect has to be kept in mind while deploying them in sensitive appointments.     

A Text Mining Approach to the Prediction of Disease Status from Clinical Discharge Summaries

Objective

The authors present a system developed for the Challenge in Natural Language Processing for Clinical Data—the i2b2 obesity challenge, whose aim was to automatically identify the status of obesity and 15 related co-morbidities in patients using their clinical discharge summaries. The challenge consisted of two tasks, textual and intuitive. The textual task was to identify explicit references to the diseases, whereas the intuitive task focused on the prediction of the disease status when the evidence was not explicitly asserted.

Design

The authors assembled a set of resources to lexically and semantically profile the diseases and their associated symptoms, treatments, etc. These features were explored in a hybrid text mining approach, which combined dictionary look-up, rule-based, and machine-learning methods.

Measurements

The methods were applied on a set of 507 previously unseen discharge summaries, and the predictions were evaluated against a manually prepared gold standard. The overall ranking of the participating teams was primarily based on the macro-averaged F-measure.

Results

The implemented method achieved the macro-averaged F-measure of 81% for the textual task (which was the highest achieved in the challenge) and 63% for the intuitive task (ranked 7^th out of 28 teams—the highest was 66%). The micro-averaged F-measure showed an average accuracy of 97% for textual and 96% for intuitive annotations.

Conclusions

The performance achieved was in line with the agreement between human annotators, indicating the potential of text mining for accurate and efficient prediction of disease statuses from clinical discharge summaries.     

BHMT gene polymorphisms as risk factors for cleft lip and cleft palate in a Chinese population

Objective Convincing evidence suggests a link between increased risk of nonsyndromic cleft lip with or without cleft palate (NSCL/P) and low intake of folic acid by the mother during pregnancy. The present study was designed to explore if genetic variation in the betaine‐homocysteine methyltransferase (BHMT) gene contributes to NSCL/P. Methods DNA was obtained from 166 individuals with NSCL/P and 285 healthy subjects. Three known single nucleotide polymorphisms (SNPs) present in the BHMT gene (rs651852, rs3...     

Automated Semantic Indexing of Figure Captions to Improve Radiology Image Retrieval

Objective

We explored automated concept-based indexing of unstructured figure captions to improve retrieval of images from radiology journals.

Design

The MetaMap Transfer program (MMTx) was used to map the text of 84,846 figure captions from 9,004 peer-reviewed, English-language articles to concepts in three controlled vocabularies from the UMLS Metathesaurus, version 2006AA. Sampling procedures were used to estimate the standard information-retrieval metrics of precision and recall, and to evaluate the degree to which concept-based retrieval improved image retrieval.

Measurements

Precision was estimated based on a sample of 250 concepts. Recall was estimated based on a sample of 40 concepts. The authors measured the impact of concept-based retrieval to improve upon keyword-based retrieval in a random sample of 10,000 search queries issued by users of a radiology image search engine.

Results

Estimated precision was 0.897 (95% confidence interval, 0.857-0.937). Estimated recall was 0.930 (95% confidence interval, 0.838-1.000). In 5,535 of 10,000 search queries (55%), concept-based retrieval found results not identified by simple keyword matching; in 2,086 searches (21%), more than 75% of the results were found by concept-based search alone.

Conclusion

Concept-based indexing of radiology journal figure captions achieved very high precision and recall, and significantly improved image retrieval.     

Risk factors for age-related macular degeneration in elderly Chinese population in Shenyang of China

Objective The paper aims to evaluate the risk factors for age‐related macular degeneration (AMD) in elderly Chinese population in Shenyang,a northeast city of China.Methods A case‐control study was conducted to investigate the risk factors for the prevalence of AMD.Ninety three AMD patients diagnosed by a complete ophthalmic examination were recruited as cases from the outpatient departments of two eye hospitals in Shenyang,while 108 normal subjects of similar age and sex were recruited as controls.A questi...     

Medication Administration Errors in Nursing Homes Using an Automated Medication Dispensing System

Objective

To identify the frequency of medication administration errors as well as their potential risk factors in nursing homes using a distribution robot.

Design

The study was a prospective, observational study conducted within three nursing homes in the Netherlands caring for 180 individuals.

Measurements

Medication errors were measured using the disguised observation technique. Types of medication errors were described. The correlation between several potential risk factors and the occurrence of medication errors was studied to identify potential causes for the errors.

Results

In total 2,025 medication administrations to 127 clients were observed. In these administrations 428 errors were observed (21.2%). The most frequently occurring types of errors were use of wrong administration techniques (especially incorrect crushing of medication and not supervising the intake of medication) and wrong time errors (administering the medication at least 1 h early or late).The potential risk factors female gender (odds ratio (OR) 1.39; 95% confidence interval (CI) 1.05-1.83), ATC medication class antibiotics (OR 11.11; 95% CI 2.66-46.50), medication crushed (OR 7.83; 95% CI 5.40-11.36), number of dosages/day/client (OR 1.03; 95% CI 1.01-1.05), nursing home 2 (OR 3.97; 95% CI 2.86-5.50), medication not supplied by distribution robot (OR 2.92; 95% CI 2.04-4.18), time classes “7-10 am” (OR 2.28; 95% CI 1.50-3.47) and “10 am-2 pm” (OR 1.96; 1.18-3.27) and day of the week “Wednesday” (OR 1.46; 95% CI 1.03-2.07) are associated with a higher risk of administration errors.

Conclusions

Medication administration in nursing homes is prone to many errors. This study indicates that the handling of the medication after removing it from the robot packaging may contribute to this high error frequency, which may be reduced by training of nurse attendants, by automated clinical decision support and by measures to reduce workload.     

Ground-based observations of ultraviolet and total solar radiation in Shenyang, northeast China

Objective This work explores the diurnal variation of Solar ultraviolet radiation (UVR) and total solar radiation (TSR) in northeast China,using daily observations of UVR and TSR in Shenyang.Methods UVR and TSR measurements were carried out from March 1st,2006 to December 31st,2009 in Shenyang,Liaoning province,China (41°51' N,123°27' E).Results Both TSR and UVR showed seasonal variation,reaching the highest levels in summer and the lowest in winter.They showed the greatest fluctuation in summer and autumn....     

Using Empiric Semantic Correlation to Interpret Temporal Assertions in Clinical Texts

Objective

To measure the uncertainty of temporal assertions like “3 weeks ago” in clinical texts.

Design

Temporal assertions extracted from narrative clinical reports were compared to facts extracted from a structured clinical database for the same patients.

Measurements

The authors correlated the assertions and the facts to determine the dependence of the uncertainty of the assertions on the semantic and lexical properties of the assertions.

Results

The observed deviation between the stated duration and actual duration averaged about 20% of the stated deviation. Linear regression revealed that assertions about events further in the past tend to be more uncertain, smaller numeric values tend to be more uncertain (1 mo v. 30 d), and round numbers tend to be more uncertain (10 versus 11 yrs).

Conclusions

The authors empirically derived semantics behind statements of duration using “ago,” and verified intuitions about how numbers are used.     

Forecasting Emergency Department Crowding: A Prospective, Real-time Evaluation

Objective

Emergency department crowding threatens quality and access to health care, and a method of accurately forecasting near-future crowding should enable novel ways to alleviate the problem. The authors sought to implement and validate the previously developed ForecastED discrete event simulation for real-time forecasting of emergency department crowding.

Design and Measurements

The authors conducted a prospective observational study during a three-month period (5/1/07-8/1/07) in the adult emergency department of a tertiary care medical center. The authors connected the forecasting tool to existing information systems to obtain real-time forecasts of operational data, updated every 10 minutes. The outcome measures included the emergency department waiting count, waiting time, occupancy level, length of stay, boarding count, boarding time, and ambulance diversion; each forecast 2, 4, 6, and 8 hours into the future.

Results

The authors obtained crowding forecasts at 13,239 10-minute intervals, out of 13,248 possible (99.9%). The R² values for predicting operational data 8 hours into the future, with 95% confidence intervals, were 0.27 (0.26, 0.29) for waiting count, 0.11 (0.10, 0.12) for waiting time, 0.57 (0.55, 0.58) for occupancy level, 0.69 (0.68, 0.70) for length of stay, 0.61 (0.59, 0.62) for boarding count, and 0.53 (0.51, 0.54) for boarding time. The area under the receiver operating characteristic curve for predicting ambulance diversion 8 hours into the future, with 95% confidence intervals, was 0.85 (0.84, 0.86).

Conclusions

The ForecastED tool provides accurate forecasts of several input, throughput, and output measures of crowding up to 8 hours into the future. The real-time deployment of the system should be feasible at other emergency departments that have six patient-level variables available through information systems.     

Induction of interleukin-8 production by angiotensin Ⅱ in rat vascular smooth muscle cells

Objective:Interleukin-8(IL-8) represents the prototypical chemokine that is made by a wide variety of cell types.Previously studies have suggested that angiotensin Ⅱ(Ang Ⅱ) is involved in atherogenesis through induction ofproinflammatory cytokines such as interleukin-6 or monocyte chemoattractant protein-1 (MCP-1) in vascular smooth muscle cells(VSMCs),while the role orang Ⅱ on IL-8 expression in VSMCs is poorly studied.Methods:In this study,VSMCs were isolated from the thoracic aorta of Sprague-Dawley rats.The expression of smooth muscle α-actin was confirmed by an immunohistochemical method.Semi-quantitative RT-PCR and enzyme-linked immunosorbent assay (ELISA) analyses were conducted to detect IL-8 expression.Results:In the present study we found that Ang Ⅱ significantly increased the expression of IL-8 both at the mRNA and protein levels in rat VSMCs in a dose- and time-dependent manner.Conclusion:These findings suggested that Ang Ⅱ may participate in atherosclerosis through induction of inflammatory mediator in VSMCs.