Electronic Administrative Databases Research Articles

Severe mental illness and ophthalmic health: A linked administrative data study.

While evidence has emerged highlighting the potential benefits of the eye as a window to the central nervous system, research on severe mental illness (SMI) and eye health is rare. We examine the association of SMI with a range of ophthalmic health outcomes, and whether any relationship is modified by age. We used linked administrative data from general practitioner (GP), hospital and ophthalmic records to examine receipt of any Health and Social Care (HSC) eye-test; and (based on eligibility recorded for a sight test) any glaucoma, any diabetes, and any blindness among the Northern Ireland (NI) hospital population between January 2015 and November 2019 (N = 798,564). When compared with non-SMI patients, those with SMI recorded a higher prevalence of having had a sight test, diabetes, and blindness. In fully adjusted logistic regression models, higher likelihood of an eye-test and diabetes (OR = 1.71: 95%CI = 1.63, 1.79 and OR = 1.29: 1.19, 1.40 respectively); and lower likelihood of glaucoma remained (OR = 0.69: 0.53, 0.90). Amongst persons with SMI there was evidence that the likelihood of having had an eye-test was lower in the older age-groups. Our study provides new evidence on ophthalmic health inequalities associated with SMI. While the study has immediate relevance to its NI context, we believe it is generalizable to wider UK health concerns. We emphasize the need for more research of this type, using large linkable electronic administrative databases to further our understanding of both health inequalities associated with SMI and poor eye health, and health outcomes in general.

Risk Factors of Readmission to Pediatric Intensive Care Unit Within 1 Year: A Case-Control Study.

BackgroundResearch on pediatric intensive care unit (PICU) readmission is lacking in China. This study was conducted to describe the risk factors associated with PICU readmission within 1 year after PICU discharge.MethodsThis retrospective case-control study included patients aged from 1 month to 16 years who were discharged between January 2018 and May 2020. The case group included readmitted patients with two or more PICU admissions within 1 year during the study period. The control group included survivors with only one PICU admission during the same study period, and the controls were matched on age and sex. Demographic and clinical variables were collected from the electronic administrative database. Risk factors were analyzed by univariate and multivariate analyses.ResultsFrom January 2018 to May 2020, 2,529 patients were discharged from the PICU, and 103 (4.07%) were readmitted within 1 year. In the univariate analysis, PICU readmission within 1 year was associated with lower weight, the presence of chronic conditions, a higher StrongKids score on admission, length of PICU stay of more than 2 weeks, the presence of dysfunction at discharge, sedation medications use, vasopressor use, and invasive mechanical ventilation in the first PICU stay. Patients had a higher StrongKids score as a surrogate for increased risk of malnutrition. In the multivariate analysis, the factors most significantly associated with PICU readmission within 1 year were the presence of chronic conditions, a higher StrongKids score on admission, and length of PICU stay of more than 2 weeks in the first PICU stay. In the subgroup analysis, compared with the control group, the factors most significantly associated with readmission within 48 h of discharge were the presence of chronic conditions, a higher StrongKids score on admission, and vasopressor use during the first PICU stay. The mortality rate was 8.74% (9/103) in patients with PICU readmission. The overall PICU mortality rate was 7.39% (201/2,721) during the study period.ConclusionsPatients with chronic conditions, a higher StrongKids score on admission, and length of PICU stay of more than 2 weeks were at much higher risk for PICU readmission within 1 year. Patients with vasopressor use during the first PICU hospitalization were more likely to be readmitted within 48 h of discharge.

Severe Outcomes, Readmission, and Length of Stay Among COVID-19 Patients with Intellectual and Developmental Disabilities

ObjectivesThe aim of this study was to evaluate the association between intellectual and developmental disabilities (IDDs) and severe COVID-19 outcomes, 30-day readmission, and/or increased length of stay (LOS) using a large electronic administrative database. MethodsPatients hospitalized with COVID-19 were identified between March 2020 and June 2021 from more than 900 hospitals in the United States. IDDs included intellectual disability, cerebral palsy, Down syndrome, autism spectrum disorder (ASD), and other intellectual disabilities. Outcomes included intensive care unit (ICU) admission, invasive mechanical ventilation (IMV), 30-day readmission, mortality, and LOS. ResultsAmong 643,765 patients with COVID-19, multivariate models showed that patients with any IDD were at a significantly greater risk of at least 1 severe outcome, 30-day readmission, or longer LOS than patients without any IDD. Compared with those without any IDD, patients with Down syndrome had the greatest odds of ICU admission (odds ratio [OR] and 95% confidence interval [CI]: 1.96 [1.73-2.21]), IMV (OR: 2.37 [2.07-2.70]), and mortality (OR: 2.33 [2.00-2.73]). Patients with ASD and those with Down syndrome both had over a 40% longer mean LOS. Patients with intellectual disabilities had a 23% (12-35%) increased odds of 30-day readmission. ConclusionsResults suggest that patients hospitalized with COVID-19 with IDD have a significantly increased risk of severe outcomes, 30-day readmission, and longer LOS.

Use of Electronic Administrative Databases to Measure Quality Indicators of Breast Cancer Care: Experience of Five Regional Oncology Networks in Italy.

PURPOSE:Assuring quality of care, while maintaining sustainability, in complex conditions such as breast cancer (BC) is an important challenge for health systems. Here, we describe a methodology to define a set of quality indicators, assess their computability from administrative data, and apply them to a large cohort of BC cases.MATERIALS AND METHODS:Clinical professionals from the Italian Regional Oncology Networks identified 46 clinically relevant indicators of BC care; 22 were potentially computable using administrative data. Incident cases of BC diagnosed in 2016 in five Italian regions were identified using administrative databases from regional repositories. Each indicator was calculated through record linkage of anonymized individual data.RESULTS:A total of 15,342 incident BC cases were identified. Nine indicators were actually computable from administrative data (two structure and seven process indicators). Although most indicators were consistent with guidelines, for one indicator (blood tumor markers in the year after surgery, 44.2% to 64.5%; benchmark ≤ 20%), deviation was evident throughout the five regions, highlighting systematic overlooking of clinical recommendations. Two indicators (radiotherapy within 4 months after surgery if no adjuvant chemotherapy; 42% to 83.8%; benchmark ≥ 90%; and mammography 6 to 18 months after surgery, 55.1% to 72.6%; benchmark ≥ 90%) showed great regional variability and were lower than expected, possibly as result of an underestimation in indicator calculation by administrative data.CONCLUSION:Despite highlighting some limitations in the use of administrative data to measure health care performance, this study shows that evaluating the quality of BC care at a population level is possible and potentially useful for guiding quality improvement interventions.

Content and validation of the Electronic Patient Medication module (EPM)-the administrative in-hospital drug use database in the Capital Region of Denmark.

Aims: Registries on in-hospital drug use are sparse, especially those that can be linked to nationwide registries. In this study, we present and validate the Electronic Patient Medication module (EPM)-the electronic administrative database on in-hospital drug use covering the Capital Region of Denmark. Methods: The research database (EPM-research) is an adaptation of the database underlying the electronic administrative database for in-hospital drug use (EPM-clinic). The validation study was comprised of two sub-studies. Sub-study 1: Accordance of registration between EPM-clinic and EPM-research was investigated by analyzing randomly chosen retrospective patient records. Sub-study 2: Workflows and real-life registration practices were investigated through visits to three different (two medical and one emergency) departments. An observer followed a nurse while dispensing and administering drugs. This information was compared with EPM-research. The primary endpoint for both sub-studies was accordance of generic name between registrations. Secondary endpoints were exact brand name, dose, and time of each administration. Accordance (proportions) with 95% confidence intervals (CI) using the Clopper-Pearson method were calculated. The study was approved by the Danish Data Protection Agency (BFH-2016-058-04906) and the Danish Patient Safety Authority (3-3013-1884/1/). Results: In sub-study 1 227 retrospective drug administrations were reviewed. Accordance of generic name was 100.0% (CI 98.4%-100.0%). In sub-study 2 176 drug administrations were observed of which 173 were recorded with identical generic name, resulting in 98.3% (CI 95.1%-99.6%) accordance of data. Conclusions: Our validation of the EPM-research showed very high accordance. With detailed information on in-hospital drug use, the EPM-research may be a useful tool in pharmacoepidemiological research.

Paediatric emergency department overcrowding and adverse patient outcomes.

General emergency department crowding negatively impacts patient care, and increases patient morbidity. This study seeks to determine if markers of paediatric emergency department (PED) flow are independently associated with negative outcomes and increased health care utilization. We conducted a retrospective cohort study of PED visits from 2008 to 2012. Data were pulled from an electronic administrative database. Using multivariate logistic regression models, we measured the association between odds of adverse outcomes (hospital/paediatric intensive care unit [PICU] admission, unscheduled return visits and mortality) with markers of PED flow (shift mean length of stay [LOS] and daily rate of patients leaving without being seen [LWBS]). We found an association between the daily LWBS proportion and the odds of being admitted to the hospital (odds ratio [OR]: 2.1; 95% confidence interval [CI]: 1.2, 3.7), as well as admission to the PICU (OR: 8.9; 95% CI: 1.1, 71.3). We found a statistically significant increase in the odds of admission if seen during shifts in the third or fourth quartile mean shift LOS. We observed lower odds of returning to the PED with increased daily LWBS proportions (OR: 0.4; 95% CI: 0.2, 0.7), but found no association between the odds of returning to the PED and mean shift LOS. While we found an association between our pre-defined measures of adverse outcomes and markers of PED flow (or crowding), further studies are needed to determine whether PED overcrowding is the cause or effect of increased hospital and PICU admissions.

Pilot Study of a Palliative Care and Medical Oncology Co-Rounding Model for Advanced Cancer Inpatients in a Tertiary Hospital in Singapore.

Our aim was to obtain initial estimates of the effect of a palliative care and medical oncology co-rounding model on hospital length of stay, proportion of patients reviewed by specialist palliative care (SPC), and proportion of patients who were readmitted within 7 and 30 days of hospital discharge. Earlier timing of palliative care improves patient outcomes, but current consultative models of palliative care service delivery are not feasible for widespread implementation. We conducted a pilot pre-post intervention study of a palliative care and medical oncology co-rounding model of care in the inpatient hospital setting. All patients admitted under the care of an inpatient oncology team during the study period were included. Hospital length of stay, proportion of patients reviewed by SPC, and readmission data were retrieved from the electronic administrative database. There were 595 unique patients (352 in the "consultative" group and 243 in the "co-rounding" group). There was no significant difference in the proportion of patients who were reviewed by a SPC physician (consultative model 21.02% vs. co-rounding model 25.10%, p = 0.243). The hospital length of stay was shorter for the co-rounding group (median 3 days, interquartile range 2-7 days) compared with the consultative group (median 4 days, interquartile range 2-7 days) (p = 0.025). There was no significant difference in proportion of patients readmitted within 30 days of hospital discharge (consultative model 29.78% vs. co-rounding model 28.90%, p = 0.773). In our target population, the co-rounding model was associated with a shorter hospital length of stay.

Readmissions in internal medicine: Epidemiology and determinants

Introduction: Readmissions are frequent in Internal Medicine wards and can be considered a score for quality and efficiency in health care. The readmission rate (RR) is commonly used as a hospital quality indicator and is frequently included in the evaluation of hospital performance. Penalties based on RR are being introduced in several models for hospital financing. The effective value of RR and the time frame to be considered are not consensual. Objective: Quantify the RR, characterize the readmission episodes and identify its determinants. Methods: Retrospective study of all the admissions in an Internal Medicine ward of a university central hospital in 2011. Data source: Diagnostic Related Categories (DRG) electronic administrative database. Readmission was defined as any new admission following an index admission during the year 2011. Variables: patient demographics, diagnosis (ICD-9 and Clinical Classification Software — AHRQ, U.S.A.) and DRG, length of stay (LoS), comorbidity indexes (CoI) (Charlson and Elixhauser) and chronic conditions (Chronic Condition Indicator — AHRQ, U.S.A.). Results: From 3826 admissions, 663 (17.3%) were readmissions (5.8% below 7 days and 11.9% below 30 days). There were no differences in gender distribution. The average age of the readmission episodes was greater than the non-readmissions (74.2 vs 72.7 years, p = 0.001). The LoS of the index episodes preceding a readmission was higher than those without a subsequent readmission (9.3 vs 7.3 days, p < 0.001). Only 22.5% of the readmissions were coded in the same DRG and only 24.1% in the same main diagnosis of the index preceding admission. The cases associated with a readmission had a higher number of coded diagnosis (7.5 vs 6.8) and chronic conditions (4.7 vs 4.1). The CoI were also greater in the readmission index cases (Elixhauser: 2.8 vs 2.3 and Charlson: 2.9 vs 2.2) (p < 0.001). In the logistic regression multivariate model for the occurrence of readmission after an initial episode, age, LoS and CoI were identified as significant variables. Conclusions: Readmissions have relevant weight in inpatient hospital activity in Internal Medicine. In our study the early RR was low and 3/4 of the readmissions occurred in clinical contexts distinct from the initial index episode. We stress the inverse relation between the shorter LoS and the probability of readmission and emphasize the higher complexity associated with readmission episodes. Extra-hospitalar facts, namely individual patient characteristics, are relevant determinants for readmission. In Internal Medicine the raw RR should not be used as a quality, performance or efficiency indicator, as RR should be adjusted to the patient clinical complexity, gaged accordingly to the nosological profile of the institution and weighted taking into account the efficiency of community health care.

A Retrospective Study of Hospitalized Pneumonia in Two Polish Counties (2006–2008)

In Poland, multi-cause pneumonia is not well characterized, and there is limited pneumococcal vaccination in the youngest and oldest age groups. The goal of this study was to assess hospitalized pneumonia across all age groups in two Polish counties. Using electronic administrative databases, cases were identified as county residents hospitalized at Chrzanów and Inowrocław County Hospitals from 2006-2008, assigned a diagnosis of pneumonia. Calculations by admission year, sex, and age category were: hospitalization rates per 1000 persons; in-hospital mortality rates per 100 persons; and median length of stay (LOS). There were 1444 and 2956 hospitalizations for new episodes of pneumonia with rates of 3.76 (95% confidence interval [CI] 3.57-3.96) and 5.99 (95% CI 5.77-6.21) per 1000 persons in Chrzanów and Inowrocław counties, respectively. In combined data, the highest hospitalization rate was among patients aged 0-4 years (30.77; 95% CI 29.06-32.55) followed by those aged ≥ 75 years (25.39; 95% CI 24.01-26.83). In-hospital mortality rates increased with age at both sites. The median LOS was 8 days. Pneumonia hospitalizations were substantial, especially for the youngest and oldest age groups. Future public health interventions aimed at these age groups might improve disease outlook.

Patterns of retreatment with radiotherapy in a large academic centre

To characterise retreatment rates with radiotherapy at a large multifacility academic radiotherapy centre and assess the effect of distance on retreatment rate. Electronic administrative records were reviewed for patients receiving radiotherapy between 1998 and 2010 at regional and metropolitan facilities. Course-level data were reconstructed from electronic administrative databases. Intent of therapy, treatment dates and diagnosis were available for analysis. Retreatment characteristics were derived, including proportion of patients receiving retreatment, proportion of total radiotherapy prescriptions dedicated to retreatment and retreatment per treating facility. Travel distance for each patient to their treatment centre was estimated, and retreatment rates were reported as a function of increasing distance. A total of 48 200 patients were treated with 66 277 treatment courses during the study period. Retreatment courses constituted 25.2% of all courses prescribed. During the study period, 20.4% of all patients received at least one treatment course. Of these, the average number of retreatment courses prescribed was 1.84. Patients treated with radical intent had a retreatment rate of 13% compared with 45% for those treated initially with palliative intent. Retreatment rates in individual tumour sites ranged from 1.3 to 44.4%. The retreatment rate for those living less than 100 km from treatment facility was 24.8%, and 20.5% for those living more than 100 km from treatment centre (P < 0.001) CONCLUSION: Retreatment accounted for over one quarter of radiotherapy courses, with the rate influenced by casemix and follow-up duration. With increasing distance from treatment centre, a decrease in retreatment rate was observed.

The Elders Risk Assessment Index, an Electronic Administrative Database–Derived Frailty Index, Can Identify Risk of Hip Fracture in a Cohort of Community-Dwelling Adults

ObjectiveTo determine whether an Elders Risk Assessment (ERA) index can predict incident hip fractures without the need for physician-patient encounter or bone mineral density testing. Patients and MethodsA retrospective cohort study was conducted in a community-based cohort of 12,650 patients aged 60 years and older. An ERA score was computed for each subject at index time (January 1, 2005). Incidents of hip fracture from January 1, 2005, through December 31, 2006, were obtained from electronic medical records. We divided the cohort into 5 groups, with the lowest ERA scores forming group A (<15%); 15% to 49%, group B; 50% to 74%, group C; 75% to 89%, group D; and the top 11%, group E. With group A as a reference group, we used logistic regression to compute odds ratios of sustaining hip fracture during a 2-year period (January 1, 2005, through December 31, 2006) for groups B, C, D, and E. Sensitivity and specificity of each possible ERA score were calculated, and a receiver operating characteristic curve was created. ResultsTwo hundred sixty-five patients (2.1%) sustained at least 1 hip fracture from January 1, 2005, through December 31, 2006. Odds ratios (95% confidence intervals) for groups B, C, D, and E were 1.6 (0.7-3.4), 4.5 (2.2-9.4), 6.9 (3.3-14.3), and 18.4 (8.9-37.9), respectively. The area under the receiver operating characteristic curve was 74.5%. ConclusionAn electronic medical record–based, easily derived ERA index might be useful in hip fracture risk stratification.

Improving quality of breast cancer surgery through development of a national breast cancer surgical outcomes (BRCASO) research database

BackgroundCommon measures of surgical quality are 30-day morbidity and mortality, which poorly describe breast cancer surgical quality with extremely low morbidity and mortality rates. Several national quality programs have collected additional surgical quality measures; however, program participation is voluntary and results may not be generalizable to all surgeons. We developed the Breast Cancer Surgical Outcomes (BRCASO) database to capture meaningful breast cancer surgical quality measures among a non-voluntary sample, and study variation in these measures across providers, facilities, and health plans. This paper describes our study protocol, data collection methods, and summarizes the strengths and limitations of these data.MethodsWe included 4524 women ≥18 years diagnosed with breast cancer between 2003-2008. All women with initial breast cancer surgery performed by a surgeon employed at the University of Vermont or three Cancer Research Network (CRN) health plans were eligible for inclusion. From the CRN institutions, we collected electronic administrative data including tumor registry information, Current Procedure Terminology codes for breast cancer surgeries, surgeons, surgical facilities, and patient demographics. We supplemented electronic data with medical record abstraction to collect additional pathology and surgery detail. All data were manually abstracted at the University of Vermont.ResultsThe CRN institutions pre-filled 30% (22 out of 72) of elements using electronic data. The remaining elements, including detailed pathology margin status and breast and lymph node surgeries, required chart abstraction. The mean age was 61 years (range 20-98 years); 70% of women were diagnosed with invasive ductal carcinoma, 20% with ductal carcinoma in situ, and 10% with invasive lobular carcinoma.ConclusionsThe BRCASO database is one of the largest, multi-site research resources of meaningful breast cancer surgical quality data in the United States. Assembling data from electronic administrative databases and manual chart review balanced efficiency with high-quality, unbiased data collection. Using the BRCASO database, we will evaluate surgical quality measures including mastectomy rates, positive margin rates, and partial mastectomy re-excision rates among a diverse, non-voluntary population of patients, providers, and facilities.

A comparison of comorbidities obtained from hospital administrative data and medical charts in older patients with pneumonia

BackgroundThe use of comorbidities in risk adjustment for health outcomes research is frequently necessary to explain some of the observed variations. Medical charts reviews to obtain information on comorbidities is laborious. Increasingly, electronic health care databases have provided an alternative for health services researchers to obtain comorbidity information. However, the rates obtained from databases may be either over- or under-reported. This study aims to (a) quantify the agreement between administrative data and medical charts review across a set of comorbidities; and (b) examine the factors associated with under- or over-reporting of comorbidities by administrative data.MethodsThis is a retrospective cross-sectional study of patients aged 55 years and above, hospitalized for pneumonia at 3 acute care hospitals. Information on comorbidities were obtained from an electronic administrative database and compared with information from medical charts review. Logistic regression was performed to identify factors that were associated with under- or over-reporting of comorbidities by administrative data.ResultsThe prevalence of almost all comorbidities obtained from administrative data was lower than that obtained from medical charts review. Agreement between comorbidities obtained from medical charts and administrative data ranged from poor to very strong (kappa 0.01 to 0.78). Factors associated with over-reporting of comorbidities were increased length of hospital stay, disease severity, and death in hospital. In contrast, those associated with under-reporting were number of comorbidities, age, and hospital admission in the previous 90 days.ConclusionsThe validity of using secondary diagnoses from administrative data as an alternative to medical charts for identification of comorbidities varies with the specific condition in question, and is influenced by factors such as age, number of comorbidities, hospital admission in the previous 90 days, severity of illness, length of hospitalization, and whether inhospital death occurred. These factors need to be taken into account when relying on administrative data for comorbidity information.

Evaluation of venous thromboembolism risk following hospitalization

A better understanding of the relationship between outpatient venous thromboembolism (VTE) and prior hospitalization is needed including data regarding the utilization of inpatient pharmacologic VTE prophylaxis and its effect on outpatient venous thromboembolic risk. The primary objective was to assess the association between development of outpatient VTE and inpatient hospitalization within the previous 90 days. Additional outcome measures included describing patients who received pharmacologic anticoagulation during hospitalization and identification of factors independently associated with VTE. Case patients in this matched case-control study were diagnosed with an outpatient deep vein thrombosis or pulmonary embolus between January 2005 and December 2007 and were matched on age with up to five to patients who were seen for an outpatient health maintenance visit but had no VTE during the same time frame as their matched case. Information collected from electronic administrative databases and patient medical records included health services utilization, medication use, medical diagnoses, and patient demographic information. Of 2190 cases, 560 patients (25.6%) compared to 151 (1.4%) of 10,942 control patients were hospitalized in the previous 90 days (P < 0.001). Among hospitalized patients, 53.5% of cases and 47.0% of controls received an anticoagulant during hospitalization (P = 0.186). Factors associated with a VTE diagnosis included hospitalization for a surgical, medical, or orthopedic indication in the previous 90 days, younger age, longer hospitalization, cancer and an elevated Chronic Disease Score. A strong association exists between outpatient VTE diagnosis and hospitalization and gaps in pharmacologic prophylaxis utilization during hospitalization are evident.

Use of an electronic administrative database to identify older community dwelling adults at high-risk for hospitalization or emergency department visits: The elders risk assessment index

BackgroundThe prevention of recurrent hospitalizations in the frail elderly requires the implementation of high-intensity interventions such as case management. In order to be practically and financially sustainable, these programs require a method of identifying those patients most at risk for hospitalization, and therefore most likely to benefit from an intervention. The goal of this study is to demonstrate the use of an electronic medical record to create an administrative index which is able to risk-stratify this heterogeneous population.MethodsWe conducted a retrospective cohort study at a single tertiary care facility in Rochester, Minnesota. Patients included all 12,650 community-dwelling adults age 60 and older assigned to a primary care internal medicine provider on January 1, 2005. Patient risk factors over the previous two years, including demographic characteristics, comorbid diseases, and hospitalizations, were evaluated for significance in a logistic regression model. The primary outcome was the total number of emergency room visits and hospitalizations in the subsequent two years. Risk factors were assigned a score based on their regression coefficient estimate and a total risk score created. This score was evaluated for sensitivity and specificity.ResultsThe final model had an AUC of 0.678 for the primary outcome. Patients in the highest 10% of the risk group had a relative risk of 9.5 for either hospitalization or emergency room visits, and a relative risk of 13.3 for hospitalization in the subsequent two year period.ConclusionsIt is possible to create a screening tool which identifies an elderly population at high risk for hospital and emergency room admission using clinical and administrative data readily available within an electronic medical record.

218: The Death after Emergency Department Study

The emergency department (ED) is an inherently high-risk setting in which unanticipated events often occur during or after discharge. Early death after discharge (DeAD) may signify a sentinel event which could indicate opportunities to improve care. Population level information on death following ED discharge is lacking. Understanding early DeAD can potentially help improve patient care and ED quality improvement efforts. To describe characteristics, discharge diagnoses, and causes of death of patients who suffer early ED DeAD and identify predictors of DeAD. Administrative data from an integrated health system were used to identify death after discharge in adults age 18 or older within 7 days of ED presentation from 1/1/07-12/31/07. This system provides comprehensive care to 3.1 million members throughout Southern California with an electronic administrative database that tracks all health care encounters within the system and a claims reimbursement system that tracks health care provided at outside facilities. The study cohort has similar age, race, and ethnic characteristics as the general California population. Death was identified using the California vital statistics files and the Social Security Death Index. Cause of death was identified using a collapsed classification of ICD-10 codes derived from the AHRQ single level Clinical Categorization Software (CCS). Co-morbidities were identified using the Elixhauser comorbidity classification system. Discharge Diagnoses were classified based on aggregated multi-level CCS ICD-9 codes. Patients who were not members, in hospice care, or discharged to another acute-care hospital were excluded. Predictors of 7-day ED DeAD were identified using multivariable logistic regression using SAS version 9.0. There were a total of 344,709 patients with 483,756 visits to Southern California EDs in 2007. Subjects were 57% female, with a mean age of 47.8 + 18.9 years. Death within 7 days of discharge occurred in 824 cases (0.2%) with the majority being male (54%) and age 60 or older (73%). The most common causes of death included malignancy (28%), coronary heart disease (15%), and non-athersclerotic heart disease (9%). In regression analyses, there was an exponential increase in ED DeAD associated with age: age 40-59 (OR 3.75, 95%CI 2.6-5.4), age 60-79 (OR 12.00, 95%CI 8.4-17.2), and age > 80 (OR 21.23, 95%CI 14.5-31.1). The top 5 discharge diagnoses with greatest odds of suffering DeAD were non-atherosclerotic heart disease (OR 5.02, 95%CI 3.8-6.6), traumatic injuries (OR 2.91, 95%CI 1.7-5.1), cerebrovascular disease (OR 2.68, 95%CI 2.0-3.6), non-infectious lung conditions (OR 2.36, 95%CI 1.5-3.8), and neoplasms (OR 2.17, 95% CI 1.7-2.7). In this large cohort of patients, the most common deaths within 7 days of discharge from the ED were caused by malignancy, coronary heart disease, and non-atherosclerotic heart disease. We identified discharge diagnoses that were strongly associated with 7-day ED DeAD even after controlling for demographic variables. Our results provide an epidemiologic foundation for future studies to identify modifiable predictors of potentially avoidable deaths after ED discharge.

Validity of ascertainment of co-morbid illness using administrative databases: a systematic review

Co-morbid illnesses have a major influence on the epidemiology of infectious diseases. Although International Classification of Diseases (ICD) discharge codes are frequently used to evaluate the presence of co-morbidities in observational research, additional research is required about their validity. We reviewed the evidence supporting the use of routinely coded administrative data for ascertainment of co-morbid diseases with emphasis as it relates to the study of infectious diseases. A systematic Medline, Embase, and bibliographic review were conducted in order to identify and critically appraise published (1990–2008) studies comparing administrative databases with conventional chart review. Twenty-one co-morbidities commonly associated with infectious diseases risk were a priori selected for specific evaluation. Of the 21 co-morbid conditions chosen, only 19 had adequate data available for evaluation. Thirteen studies were included; only one focused on an infectious disease population. Eleven articles validated individual co-morbid conditions data in electronic administrative databases and reported a wide range of pooled sensitivity (13–82%) but overall high pooled specificity (>97%) when compared with medical chart review. Seven articles compared Charlson Co-morbidity Index scores derived from administrative data algorithms as compared with that calculated from medical record review and found that administrative data underscored the index in all articles with kappa agreement ranging from 0.30 to 0.56. The small body of literature published to date suggests that electronic administrative databases have limited validity for co-morbidity evaluation. Studies evaluating administrative database ascertainment of co-morbidities specifically in infectious diseases research are needed.

Medication Use Across Transition Points from the Emergency Department: Identifying Factors Associated with Medication Discrepancies

As patients move across transition points of care, medication discrepancies are likely to occur. In the emergency department (ED), patients are vulnerable to medication discrepancies because they are in an environment in which rapid decisions need to be made under high levels of stress. To identify the patient-, environment-, and medication-related factors involving unexplained medication discrepancies across transition points after ED presentation. Using a retrospective chart review design, a stratified, random sampling of data was undertaken over a 12-month period. Information was obtained from an electronic administrative database and medical records as patients moved from the ED to another transition point of care. Medication discrepancies were classified into 2 outcome groups: (1) no discrepancies and situations in which discrepancies were adequately explained and (2) discrepancies that had no adequate explanation. For the 12-month period, 210 randomly selected patients were included; 73 (34.8%) had at least one unexplained medication discrepancy. Binary logistic regression modeling showed 4 factors that were statistically significant in determining the incidence of at least one unexplained medication discrepancy. Benefit card holders (individuals who receive benefits from government insurance programs comparable to the US-based Medicare and Medicaid initiatives, which include the elderly, the disabled, low income earners, and unemployed persons) had 3.73 greater odds of experiencing an unexplained medication discrepancy (95% CI 1.72 to 8.07; p = 0.001). Patients prescribed 5 or more drugs at discharge from the ED had 12.22 greater odds of having at least one unexplained medication discrepancy (95% CI 5.52 to 27.08; p < 0.001). Patients who were first seen by a physician within 1 hour of a change in working shift had 3.70 greater odds of having an unexplained medication discrepancy (95% CI 1.67 to 8.18; p = 0.001). For each additional minute of wait time for a physician, the odds of having an unexplained medication discrepancy increased by a factor of 1.01 (95% CI 1.00 to 1.01; p = 0.042). Patient-, environment-, and drug-related factors contribute to the risk of medication discrepancies across transition points from the ED.

Processes and Outcomes of Care for Soft Tissue Sarcoma of theExtremities

Purpose: A population-based cohort study of soft tissue sarcoma of the extremities (STSE) in Ontario, Canada was conducted using linked administrative databases. Methods and materials: Electronic administrative databases were linked from the Ontario Cancer Registry, the Canadian Institute for Health Information, and Radiation Oncology Research Unit database of radiation therapy (RT) records. Results: The definitive surgery was amputation for 6.0%, resection for 60.9%, biopsy for 7.5%; the remainder had no surgical record. Adjuvant RT was administered to 40.2% of cases. Among cases initially treated by surgical resection, 2.0% later underwent amputation and 9.5% underwent further resection during follow-up. The adjusted odds ratio (OR) for amputation as definitive surgery was 2.3 (1.19, 4.45) in eastern Ontario relative to Toronto. The likelihood of adjuvant RT among those not registered at a cancer centre within 3 months of diagnosis was decreased (OR = 0.20 (95% CI (0.13, 0.30)) relative to those registered. The adjusted relative risk of amputation at any time following diagnosis was 3.48 (95% CI (1.63, 7.46)) among cases not attending a cancer centre. The adjusted relative risk of death was 1.4; 95% CI (1.1, 1.7) among those not attending a cancer centre. Conclusions: Cases not seen at a multidisciplinary cancer centre within 3 months following diagnosis of STSE have an increased relative risk for amputation at any time, and for death due to any cause. Many hypotheses for further study are suggested by the results of this analysis.

Spine update. Administrative databases in spine research.

The use of administrative health care databases for the storage and retrieval of information is increasing. The data collection, entry, and collation follows a predictable process for hospital admissions. Many conclusions have been drawn from research performed using administrative databases. These conclusions can have significant and important implications for patients, providers, and society at large, to the extent that such data inform participants in the current health care policy debate. In an effort to better understand the significance of conclusions drawn from studies that rely on electronic administrative databases as their source of information, the present report addresses the process, strengths, weaknesses, and future plans for the use of administrative databases in spine research.