Biomedical subjects

Spencer S Jones

Publications and source records attributed to Spencer S Jones.

6 recordsLinked to original sources

PubMed2006

A framework for information system usage in collaborative care.

UNLABELLED: Clinical information systems (CIS) can affect the quality of patient care. In this paper, we focus on CIS use in the collaborative treatment of chronic diseases. We have developed a framework to determine which CIS functions have general usefulness for improving patient outcomes. METHODS: We reviewed the use of clinical information systems within a collaborative care environment, identifying CIS functions important in chronic disease care. We grouped the functions into categories of access, best practices, and communication (ABC). Three independent raters selected the most important collaborative care related functions from the HL7 Electronic Health Record Systems functional model, and mapped the HL7 functions against the ABC categories. We then built a model of CIS use and tested it on data from a cohort of patients with chronic illnesses. RESULTS: Of the 133 HL7 elements in the ABC model, 60 (45%) were ranked as important for collaborative care by two reviewers. Agreement was moderate for importance (kappa=.20) but high for ABC categorization (kappa=.67). In our data tests, for the 1105 patients, access 4.4+/-6.5, best practices 0.8+/-1.6, and communication 2.9+/-4.5. CIS functions were used per episode of care. We were able to identify several key functions that may affect patient care. For example, certain CIS functions related to best practices were associated with higher clinician adherence to testing guidelines. DISCUSSION: This framework may be useful to assess and compare CIS systems for collaborative care. Future refinements of the model are discussed.

Chronic Disease↗

PubMed2006

An independent evaluation of four quantitative emergency department crowding scales.

BACKGROUND: Emergency department (ED) overcrowding has become a frequent topic of investigation. Despite a significant body of research, there is no standard definition or measurement of ED crowding. Four quantitative scales for ED crowding have been proposed in the literature: the Real-time Emergency Analysis of Demand Indicators (READI), the Emergency Department Work Index (EDWIN), the National Emergency Department Overcrowding Study (NEDOCS) scale, and the Emergency Department Crowding Scale (EDCS). These four scales have yet to be independently evaluated and compared. OBJECTIVES: The goals of this study were to formally compare four existing quantitative ED crowding scales by measuring their ability to detect instances of perceived ED crowding and to determine whether any of these scales provide a generalizable solution for measuring ED crowding. METHODS: Data were collected at two-hour intervals over 135 consecutive sampling instances. Physician and nurse agreement was assessed using weighted kappa statistics. The crowding scales were compared via correlation statistics and their ability to predict perceived instances of ED crowding. Sensitivity, specificity, and positive predictive values were calculated at site-specific cut points and at the recommended thresholds. RESULTS: All four of the crowding scales were significantly correlated, but their predictive abilities varied widely. NEDOCS had the highest area under the receiver operating characteristic curve (AROC) (0.92), while EDCS had the lowest (0.64). The recommended thresholds for the crowding scales were rarely exceeded; therefore, the scales were adjusted to site-specific cut points. At a site-specific cut point of 37.19, NEDOCS had the highest sensitivity (0.81), specificity (0.87), and positive predictive value (0.62). CONCLUSIONS: At the study site, the suggested thresholds of the published crowding scales did not agree with providers' perceptions of ED crowding. Even after adjusting the scales to site-specific thresholds, a relatively low prevalence of ED crowding resulted in unacceptably low positive predictive values for each scale. These results indicate that these crowding scales lack scalability and do not perform as designed in EDs where crowding is not the norm. However, two of the crowding scales, EDWIN and NEDOCS, and one of the READI subscales, bed ratio, yielded good predictive power (AROC >0.80) of perceived ED crowding, suggesting that they could be used effectively after a period of site-specific calibration at EDs where crowding is a frequent occurrence.

Crowding↗

PubMed2006

The incidence of fibromyalgia and its associated comorbidities: a population-based retrospective cohort study based on International Classification of Diseases, 9th Revision codes.

BACKGROUND: The epidemiology of fibromyalgia is poorly defined. The incidence of fibromyalgia has not been determined using a large population base. Previous studies based on prevalence data demonstrated that females are 7 times more likely to have fibromyalgia than males and that the peak age for females is during the childbearing years. OBJECTIVE: We have calculated the incidence rate of fibromyalgia in a large, stable population and determined the strength of association between fibromyalgia and 7 comorbid conditions. METHODS: We conducted a retrospective cohort study of a large, stable health insurance claims database (62,000 nationwide enrollees per year). Claims from 1997 to 2002 were examined using the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes to identify fibromyalgia cases (ICD code 729.1) and 7 predetermined comorbid conditions. RESULTS: A total of 2595 incident cases of fibromyalgia were identified between 1997 and 2002. Age-adjusted incidence rates were 6.88 cases per 1000 person-years for males and 11.28 cases per 1000 person-years for females. Females were 1.64 times (95% confidence interval = 1.59-1.69) more likely than males to have fibromyalgia. Patients with fibromyalgia were 2.14 to 7.05 times more likely to have one or more of the following comorbid conditions: depression, anxiety, headache, irritable bowel syndrome, chronic fatigue syndrome, systemic lupus erythematosus, and rheumatoid arthritis. CONCLUSION: Females are more likely to be diagnosed with fibromyalgia than males, although to a substantially smaller degree than previously reported, and there are strong associations for comorbid conditions that are commonly thought to be associated with fibromyalgia.

Age Distribution↗

PubMed2006

Use of health-related, quality-of-life metrics to predict mortality and hospitalizations in community-dwelling seniors.

OBJECTIVES: To investigate whether health-related quality-of-life (HRQoL) scores in a primary care population can be used as a predictor of future hospital utilization and mortality. DESIGN: Prospective cohort study measuring Short Form 12 (SF-12) scores obtained using a mailed survey. SF-12 scores, age, and a comorbidity score were used to predict hospitalization and mortality rate using multivariable logistic regression and Cox proportional hazards during the ensuing 28-month period for elderly patients. SETTING: Intermountain Health Care, a large integrated-delivery network serving a population of more than 150,000 seniors. PARTICIPANTS: Participants were senior patients who had one or more chronic diseases, were community dwelling, and were initially treated in primary care clinics. MEASUREMENTS: SF-12 survey Version 1. RESULTS: Seven thousand seventy-six surveys were sent to eligible participants; 3,042 (43%) were returned. Of the returned surveys, 2,166 (71%) were complete and scoreable. For the respondent group, a multivariable analysis demonstrated that older age, male sex, higher comorbidity score, and lower mental and physical summary measures of SF-12 predicted higher mortality and hospitalization. On average, nonresponders were older and had higher comorbidity scores and mortality rates than responders. CONCLUSION: The SF-12 survey provided additional predictive ability for future hospitalizations and mortality. Such predictive ability might facilitate preemptive interventions that would change the course of disease in this segment of the population. However, nonresponder bias may limit the utility of mailed SF-12 surveys in certain populations.

Aged↗

PubMed2005

Use and impact of a computer-generated patient summary worksheet for primary care.

Advanced clinical information systems have been proposed to improve patient care in terms of safety, effectiveness, and efficiency. In order to be effective, such systems require detailed patient-specific clinical information in a form easily reviewed by clinicians. We have developed a patient summary worksheet for use in outpatient clinics, which presents a structured overview of patient health information. The worksheet provides patient demographic information, specific problems and conditions, the patient's current medication profile, laboratory test results pertinent to patient problems, and disease-specific or preventive care actionable advisories. Usage has grown from a few hundred to over 25,000 unique patients per month during a two-year period. Diabetic patients for whom the worksheet is accessed are significantly more likely to be in compliance with accepted testing regimens for glycosolated hemoglobin (OR 1.47, 95% CI 1.28, 1.61).

Ambulatory Care Facilities↗

PubMed2005

The effect of longitudinal EMR access on laboratory ordering.

A longitudinal electronic medical record (EMR) allows physicians to access laboratory results in the context of the patient's medical history. Daily lab order volumes were tracked for physicians with access to an EMR and physicians with no EMR access to assess whether physicians with EMR access changed their lab order habits significantly more than a matched set of controls. This study shows that physicians will change their ordering habits in order to access the lab results in the context of an EMR.

Clinical Laboratory Information Systems↗