Administrative Data Repositories Research Articles

Modifiable Risk Factors for Subarachnoid Hemorrhage: Narrative Review With an Emphasis on Common Controversies and Epidemiologic Pitfalls.

Given the relatively low incidence, high prehospital death rate, substantial geographical differences, and complex disease origin (combination of genetic and environmental risk factors), epidemiologic research on subarachnoid hemorrhage (SAH) and its risk factors is challenging. In practice, we are more or less forced to exploit compromised study designs and nonrepresentative data in such circumstances where it is almost impossible to gather comprehensive data through an optimal design. For example, hospital-based patient cohorts, administrative data repositories, and short-term population-based studies from small geographical regions are often used to research the incidence, case fatality, and risk factors of SAH, regardless of their inherent and self-evident limitations. Since studies on the epidemiology of SAH focus largely on identifying possible risk factors that could aid in disease diagnostics, treatment, and prevention, we aimed to review recent evidence on modifiable risk factors for SAH. In this context, we also try to explain the methodological reasons behind some of the conflicting results and to discuss the primary strengths and limitations of different study designs used in the field of SAH epidemiology. Based on our findings, smoking, high blood pressure, and possibly low physical activity are the only risk factors with high-quality evidence supporting their causal role in SAH. In addition, since all 3 commonly used study designs in SAH epidemiology, namely, hospital-based, population-based, and administrative register-based studies, have their own strengths and limitations, the most robust risk factor estimates and other epidemiologic measures of SAH can likely be established by combining various overlapping and high-quality sources of information in the future.

Inequities in Physical Therapy Receipt of US Service Members and Veterans With Low Back Pain.

To investigate inequities in time to physical therapy (PT) for patients with low back pain (LBP). Retrospective observational study using data from the Department of Defense and Veterans Health Administration clinical and administrative data repositories derived from medical records, claims, and enrolment data. Military Health System, Veterans Health Administration, and civilian health care facilities. Active duty service members, veterans, and retirees seeking health care for LBP between January 2017 and December 2020, with no LBP diagnoses for at least 1 year prior (N=1,252,959). Not applicable. Time to-outpatient PT evaluation within 13 weeks of LBP diagnosis. Approximately 9.4% of included patients received an outpatient PT evaluation from a physical therapist within 13 weeks of diagnosis. In a piecewise exponential additive model, many covariates were time-varying, such that the probability of PT receipt varied throughout the 13-week period. Black, Latinx, and American Indian and Alaskan Native patients had lower probabilities of PT receipt than White patients from 1 to 3-6 weeks after index diagnosis. At 5 and 7 weeks, Black and Latinx patients, respectively, were more likely to receive PT than White patients, which continued until the end of the observation period. Patients assigned female relative to patients assigned male relative had a higher probability of initiating PT across the entire observation window, as did active duty service members, relative to retired service members and veterans. Inequities in the timing and receipt of PT exist in the US Military Health System and Veterans Health Administration by race and ethnicity, assigned sex, and beneficiary group. Standardizing referral and practice patterns, improving accessibility of PT services, and encouraging health-seeking behavior may help alleviate the inequities in initiating PT.

Identifying a Birth Cohort of Twins from Linked Data – Challenges and Opportunities

ObjectiveIn the absence of accurate perinatal records, identifying and differentiating twins in administrative records is difficult because of their similarity; they share surnames, dates of birth, and residences. In administrative databases, events within twin pairs are often incorrectly identified as being from one individual, representing a threat to data accuracy. An inability to identify twins in administrative data precludes applying powerful twin-based causal inference methods to understand health and social well-being. ApproachWe developed an algorithm using linked administrative birth, perinatal, emergency department, and hospital records in Victoria, Australia from 1 January 1993 to 31 December 2023. We probabilistically linked a sample of 1,434 ‘known’ twin pairs from the Australian Twin Registry to validate the sensitivity of our algorithm. We calculated specificity using a sample of non-twins derived from linked data. ResultsOur algorithm identified 37,900 twin pairs, 75,800 twin individuals, in the Victorian linked dataset. The accuracy of our ascertainment of twins by key characteristics will be presented and discussed. ConclusionsThe birth cohort we have generated is one of the largest twin cohorts in the world with unprecedented granularity in longitudinal health and social data. ImplicationsOur algorithm improves the accuracy of administrative data repositories and linkage, providing novel information on where errors in previous linkages have occurred due to limited familial or intergenerational information. Our large population-based birth cohort of twins can be used to investigate the familial and non-familial determinants of health using advanced causal inference which leverages the natural similarity between twins.

The diagnostic intersection of cognitive-communication disorders and aphasia secondary to TBI.

The present retrospective study examines veterans and military personnel who have sustained a cognitive-communication deficit/disorder (CCD) and/or aphasia secondary to traumatic brain injury (TBI). The prevalence of each disorder secondary to TBI is identified and demographic factors are analysed to determine whether specific characteristics (age, gender, race and/or ethnicity) differentially influenced diagnosis (CCD or aphasia). A retrospective analysis examining the prevalence of CCD and aphasia among US service personnel with a complicated mild-to-severe TBI treated over a 4-year period (1 January 2016-31 December 2019) was conducted. Medical diagnoses and demographic factors were obtained from administrative data repositories and a logistic regression was performed to identify the relationship between demographic factors and diagnoses. Analyses revealed that 8.8% of individuals studied had a secondary diagnosis of CCD (6.9%), aphasia (1.5%) or both (0.4%). This signifies 6863 cases of CCD, 1516 cases of aphasia and 396 cases of CCD and aphasia (dual diagnosis) per 100,000 individuals who have sustained a complicated mild-to-severe TBI. The proportion of cases observed with these diagnoses was consistent with the racial, gender and ethnic demographics of those diagnosed with TBI. Statistical modelling revealed that increased age is predictive of a diagnosis of aphasia relative to CCD. Service personnel sustaining TBIs are at increased risk of communication impairments with deficits observed across all gender, racial and ethnic demographics. CCD is more commonly observed than aphasia, though clinicians should be cognisant of both when performing assessments. Age is a factor that can influence diagnosis. What is already known on the subject Military personnel are at increased risk of communication disorders (CCDs) with TBI associated with multiple types of communication impairments including CCD, aphasia, dysarthria and apraxia of speech. What this paper adds to existing knowledge This paper examines CCD and aphasia occurring following TBI. The proportion of observed cases of CCD and aphasia secondary to TBI are calculated over a 4-year period and the prevalence of these disorders is provided. Additionally, statistical modelling is used to identify differences in the diagnosis of CCD relative to aphasia using the demographic factors of age, racial identity and ethnicity. What are the potential or actual clinical implications of this work? CCD is a frequently occurring issue following TBI, and the findings of this study demonstrate that it is a concern observed across gender, racial and ethnic lines. Advanced age is linked with the diagnosis of aphasia relative to CCD following TBI and should be a consideration during evaluation of patients who have sustained significant head trauma.

Congenital lung malformation patients experience respiratory infections after resection: A population-based cohort study

PurposeThe benefit of elective resection of congenital lung malformations continues to be debated. Proponents of resection endorse a decreased risk of respiratory complications as one indication for surgery. Our study aimed to compare the prevalence of respiratory infections in cases, before and after resection of congenital lung malformations, to controls without a history of congenital lung malformation. MethodsWe performed a retrospective cohort study of children born from 1991 to 2007 who underwent congenital lung malformation resection. Patients were identified from Winnipeg´s Surgical Database of Outcomes and Management (WiSDOM), and a 10:1 date-of-birth matched control group was generated from a population-based administrative data repository. International Classification of Disease codes were used to assess pulmonary infection outcomes. Relative rates (RR) were calculated to compare the frequency of pneumonia, respiratory infections and influenza between cases and controls. ResultsWe included 31 congenital lung malformation cases and 310 controls. Cases consisted of 14 (45.16%) congenital pulmonary airway malformations, 9 (29.03%) bronchopulmonary sequestrations and 8 (25.81%) hybrid lesions. Before resection, pneumonia was more common in cases than controls (RR 6.85; 95%CI 3.89, 11.9), while the risk of acute respiratory infections (RR 1.21; 95%CI 0.79, 1.79) and influenza (RR 0.46; 95%CI 0.01, 3.22) were similar to controls. Post-resection, the risk of pneumonia (RR 9.75; 5.06, 18.50) was still higher in cases than controls, and respiratory infections (RR 1.77; 95%CI 1.20, 2.53) and influenza (RR 3.98; 95%CI 1.48, 9.36) were more common in cases than controls. ConclusionOur study demonstrated that after resection of congenital lung malformations, children experience more frequent respiratory infections compared to the general population. Resection does not eliminate the increased risk of pneumonia.

Impact of hospital geographic remoteness on short‐term outcomes after colorectal cancer resection using state‐wide administrative data

This study aimed to use validated coding algorithms, applied to a central repository of administrative data (AD), to report on short-term outcomes following resection for colorectal cancer (CRC) comparing regional to metropolitan Victorian hospitals. This is a retrospective cohort study using prospectively gathered AD. The primary outcome was prolonged length of stay (LOS). Secondary outcomes were: inpatient mortality, return to theatre, discharge destination and need for mechanical ventilation/intensive care unit support. Outcomes were adjusted for potential confounders via multivariable logistic regression analysis. This study of 18 470 patients found strong evidence for lower odds of prolonged LOS (odds ratio (OR) 0.53, 95% confidence interval (CI) 0.48-0.58, P ≤ 0.001) and inpatient mortality (OR 0.67, 95% CI 0.49-0.91, P = 0.01) in inner regional hospital compared with metropolitan hospitals. For outer regional hospitals, there was strong evidence of decreased odds of prolonged LOS (OR 0.64, 95% CI 0.52-0.77, P = <0.001) and return to theatre (OR 0.67, 95% CI 0.47-0.95, P = 0.03). This is the largest and most detailed study concerning short-term outcomes following CRC resection in Victorian public hospitals. Inner and outer regional centres had similar or better short-term outcomes than metropolitan hospitals after CRC resection. AD with validated algorithms serves as a large accurate database to report on CRC outcomes.

Assessing the quality of administrative data for research: a framework from the Manitoba Centre for Health Policy.

The growth of administrative data repositories worldwide has spurred the development and application of data quality frameworks to ensure that research analyses based on these data can be used to draw meaningful conclusions. However, the research literature on administrative data quality is sparse, and there is little consensus regarding which dimensions of data quality should be measured. Here we present the core dimensions of the data quality framework developed at the Manitoba Centre for Health Policy, a world leader in the use of administrative data for research purposes, and provide examples and context for the application of these dimensions to conducting data quality evaluations. In sharing this framework, our ultimate aim is to promote best practices in rigorous data quality assessment among users of administrative data for research.

Increasing research capacity with ICES Data &amp; Analytic Services (DAS)

ABSTRACTBackgroundThe Institute for Clinical Evaluative Sciences (ICES) is a not-for-profit organization that conducts research to evaluate health care delivery and outcomes. Established in 1992, ICES houses a vast and secure array of linkable, coded health-related data on more than 13 million Ontarians, including health services data, health care provider data, registries and population-based health surveys. ICES has a reputation for generating strong evidence-based knowledge to inform policy and practice, however the use of the data was restricted to ICES’ purposes. In March 2014, ICES launched the Data &amp; Analytic Services (DAS) platform with the primary objective of increasing access to its data to publicly-funded researchers, health care providers and administrators, policymakers and students.&#x0D; MethodDAS provides access to highly de-identified, risk-reduced datasets created from ICES’ data holdings; analytic support; and complete data analysis and report writing services. DAS also enables the importation of external data for linkage to ICES’ data holdings. Research objectives and methodology are led by the requestor and ICES analysts rely on their subject matter expertise to direct the deliverables.&#x0D; ResultsSince launch, over 200 requests from Canada, United States and United Kingdom have been adjudicated, of which 187 have been deemed feasible and eligible. Over the same period of time, ICES as an organization had over 700 active projects of which 348 were initiated, an increase in capacity of 26%. Though Toronto-based researchers represent the majority of the requests (62%), there have been requests from outside Ontario interested in comparing aspects of Ontario’s healthcare to their home province. Research topics have varied and include assessments of health care provision by sector, disease prevalence and treatment, and statistical methods. An unexpected outcome of increasing access has been the large interest from small physician groups and knowledge users who are not typically involved in research for academic purposes. Access to ICES’ data holdings provides an opportunity to examine a larger cohort of patients who share the same characteristics as their clinic patients or group. Furthermore, by enabling remote access to the data, DAS is able to leverage the capabilities of ICES’ data holdings and increase research capacity in a short period of time.&#x0D; ConclusionIn making one of the most comprehensively linked health administrative data repositories in the world widely available to the broader research and healthcare community, DAS engages investigators involved in front-line care, stimulates new avenues of research and fosters collaboration that was previously unachievable.

Fracture prediction from repeat BMD measurements in clinical practice

We investigated whether repeat BMD measurements in clinical populations are useful for fracture risk assessment. We report that repeat BMD measurements are a robust predictor of fracture in clinical populations; this is not affected by preceding BMD change or recent osteoporosis therapy. In clinical practice, many patients selectively undergo repeat bone mineral density (BMD) measurements. We investigated whether repeat BMD measurements in clinical populations are useful for fracture risk assessment and whether this is affected by preceding change in BMD or recent osteoporosis therapy. We identified women and men aged ≥ 50 years who had a BMD measurement during 1990-2009 from a large clinical BMD database for Manitoba, Canada (n = 50,215). Patient subgroups aged ≥ 50 years at baseline with repeat BMD measures were identified. Data were linked to an administrative data repository, from which osteoporosis therapy, fracture outcomes, and covariates were extracted. Using Cox proportional hazards models, we assessed covariate-adjusted risk for major osteoporotic fracture (MOF) and hip fracture according to BMD (total hip, lumbar spine, femoral neck) at different time points. Prevalence of osteoporosis therapy increased from 18 % at baseline to 55 % by the fourth measurement. Total hip BMD was predictive of MOF at each time point. In the patient subgroup with two repeat BMD measurements (n = 13,481), MOF prediction with the first and second measurements was similar: adjusted-hazard ratio (HR) per SD 1.45 (95 % CI 1.34-1.56) vs. 1.64 (95 % CI 1.48-1.81), respectively. No differences were seen when the second measurement results were stratified by preceding change in BMD or osteoporosis therapy (both p-interactions >0.2). Similar results were seen for hip fracture prediction and when spine and femoral neck BMD were analyzed. Repeat BMD measurements are a robust predictor of fracture in clinical populations; this is not affected by preceding BMD change or recent osteoporosis therapy.

The effect of neighborhood socioeconomic status on education and health outcomes for children living in social housing.

We explored differences in health and education outcomes between children living in social housing and not, and effects of social housing's neighborhood socioeconomic status. In this cohort study, we used the population-based repository of administrative data at the Manitoba Centre for Health Policy. We included children aged 0 to 19 years in Winnipeg, Manitoba, in fiscal years 2006-2007 to 2008-2009 (n = 13,238 social housing; n = 174,017 others). We examined 5 outcomes: age-2 complete immunization, a school-readiness measure, adolescent pregnancy (ages 15-19 years), grade-9 completion, and high-school completion. Logistic regression and generalized estimating equation modeling generated rates. We derived neighborhood income quintiles (Q1 lowest, Q5 highest) from average household income census data. Children in social housing fared worse than comparative children within each neighborhood income quintile. When we compared children in social housing by quintile, preschool indicators (immunization and school readiness) were similar, but adolescent outcomes (grade-9 and high-school completion, adolescent pregnancy) were better in Q3 to Q5. Children in social housing had poorer health and education outcomes than all others, but living in social housing in wealthier areas was associated with better adolescent outcomes.

A4-1: Validating Electronic Health Record Demographic Data Using Self-reported Data from the Autism Registry Survey

Background/AimsThe use of administrative patient data via the electronic health record (EHR) is very important in research. It’s critical we have a sense of the validity and relative accuracy of key data in this widely available data source. The HMORN Virtual Data Warehouse (VDW) is an example of a large repository of administrative data used in numerous studies. The recent Mental Health Research Network (MHRN) Autism Spectrum Disorder (ASD) Registry Survey was hosted by four HMORN sites inviting Kaiser Permanente members to complete a Web-based questionnaire on behalf of their child identified as having an ASD diagnosis in the EHR.MethodsIn addition to an extensive battery of questions regarding ASD, the survey collected data on a number of demographic data elements also available in the VDW. These are: age, gender, race/ethnicity (child), income (household) and education (household adult). A total of 1155 adults responded to the ASD Registry Survey. These records were matched with demographic data from the VDW for the same child.ResultsPreliminary examination of race-ethnicity and gender data shows that there‘s a good to excellent level of agreement between the two sources when data are non-missing in both data sources. A total of 992 records had non-missing race/ethnicity data from both data sources. In 81.1% (805/992) of the cases, both data sources agreed (kappa = 0.68, CI = 0.64–0.72). The categories that had the highest level of agreement are White, Black, and Asian, while the Hispanic and multi-racial groupings had a comparatively much lower level of agreement (46.9%). For gender, level of agreement was very high (99.0%, 1118/1129, kappa = 0.97, CI = 0.95–0.99).ConclusionsIn this study, race in the electronic health record was a very accurate measure for major race categories but was far less accurate when reporting the emergent and important multi-racial category and Hispanic ethnicity. Gender had an excellent level of agreement between the two sources. Age, gender, and race-ethnicity are key covariates for many studies analyzing EHR data. Income and education can serve to illuminate socioeconomic factors very relevant to health care research. Having a sense of the validity and accuracy of these data is crucial to the research process.

Evaluating the Ability of Hospital Information Systems to Establish Evidence-Based Medicine in Iran

Evidence-based medicine (EBM) is the correct use of the best evidences in clinical decision making for patient care. Hospital Information Systems (HIS) can act as a bridge between medical data and medical knowledge through context-sensitive merging and filtering of patient data, individual clinical knowledge and external evidence. The aim of this study was to determine the ability of HISs to establish EBM in Iran. This descriptive cross-sectional study was carried out on HISs of 30 hospitals from March 2011 to October 2011. Data were collected using a researcher-constructed checklist including applicant's background information as well as information based on research objectives: clinical decision support system (CDSS), reference databases, contextual and case-specific information, clinical and administrative data repositories and Internet-based health information. Face and content validity of the checklist were assessed by the qualified specialists and then the data were analyzed using descriptive statistics and SPSS 16 software. The results of the study revealed that the HISs lacked the essential components to providing access to CDSS, reference databases and Internet-based health information in 19, 16 and 20 hospitals were 63.3 %, 53.3 % and 66.7, respectively. Twenty-two hospitals (70 %) had more than two-thirds of the essential components to access clinical and administrative data repositories; 23 hospitals (76.7 %) had at least one essential component to access contextual and case-specific information. It can be concluded that the ability of the HISs to establish EBM in providing access to the clinical and administrative data repositories is better than other research objectives. Furthermore, more attention should be paid to other related objectives.

The contributions of First Nations ethnicity, income, and delays in surgery on mortality post-fracture: a population-based analysis

We examined the independent contributions of First Nations ethnicity and lower income to post-fracture mortality. A similar relative increase in mortality associated with fracture appears to translate into a larger absolute increase in post-fracture mortality for First Nations compared to non-First Nations peoples. Lower income also predicted increased mortality post-fracture. First Nations peoples have a greater risk of mortality than non-First Nations peoples. We examined the independent contributions of First Nations ethnicity and income to mortality post-fracture, and associations with time to surgery post-hip fracture. Non-traumatic fracture cases and fracture-free controls were identified from population-based administrative data repositories for Manitoba, Canada (aged≥50 years). Populations were retrospectively matched for sex, age (within 5 years), First Nations ethnicity, and number of comorbidities. Differences in mortality post-fracture of hip, wrist, or spine, 1996-2004 (population 1, n=63,081), and the hip, 1987-2002(Population 2, n=41,211) were examined using Cox proportional hazards regression to model time to death. For hip fracture, logistic regression analyses were used to model the probability of death within 30 days and 1 year. Population 1: First Nations ethnicity was associated with an increased mortality risk of 30-53% for each fracture type. Lower income was associated with an increased mortality risk of 18-26%. Population 2: lower income predicted mortality overall (odds ratio (OR) 1.15, 95% confidence interval (CI) 1.07-1.23) and for hip fracture cases (OR 1.18, 95%CI 1.05-1.32), as did older age, male sex, diabetes, and >5 comorbidities (all p≤0.01). Higher mortality was associated with pertrochanteric fracture (OR 1.14, 95% CI 1.03-1.27), or surgery delay of 2-3 days (OR 1.34, 95% CI 1.18-1.52) or ≥4 days (OR 2.35, 95% CI 2.07-2.67). A larger absolute increase in mortality post-fracture was observed for First Nations compared to non-First Nations peoples. Lower income and surgery delay>2 days predicted mortality post-fracture. These data have implications regarding prioritization of healthcare to ensure targeted, timely care for First Nations peoples and/or individuals with lower income.

A comparative study of using non-hip bone density inputs with FRAX®

Use of lumbar spine T-score or minimum T-score as a bone mineral density (BMD) input to the FRAX® algorithm led to miscalibration compared with the recommended femoral neck input. Use of a weighted mean between the lumbar spine and femoral neck T-scores was found to provide an arithmetically equivalent result to a previously described offset adjustment. FRAX assumes that the BMD input, when used in the calculation, is from the femoral neck. Use of other BMD inputs is not recommended, but there are no studies describing how this affects the performance of FRAX. Ten-year probabilities of a major osteoporotic fracture were calculated with different BMD inputs for 20,477 women and men aged 50 years and older from Manitoba, Canada. FRAX probability calculated with femoral neck BMD was designated the reference method. We also derived FRAX probabilities where the BMD input was based upon the lumbar spine T-score, minimum T-score (lumbar spine or femoral neck), weighted mean T-score (lumbar spine or femoral neck), or used an adjustment for the spine-hip T-score difference (offset). Fracture outcomes were assessed using a population-based administrative data repository. All FRAX models showed good risk stratification with minimal differences. There was no consistent improvement in FRAX performance when lumbar spine or minimum T-score were used as inputs, but calibration was adversely affected due to higher mean fracture probabilities compared with the femoral neck. The weighted mean T-score was found to be equivalent to the spine-hip T-score offset adjustment, and both slightly improved risk classification without a change in calibration. The choice of BMD input to the FRAX model has a large effect on performance. The lumbar spine T-score or minimum T-score should not be used as inputs to the FRAX algorithm. Use of a weighted mean between the lumbar spine and femoral neck T-scores slightly improves risk classification.

Estimates of the treated prevalence of bipolar disorders by mental health services in the general population: comparison of results from administrative and health survey data

Informed provision of population mental health services requires accurate estimates of disease burden. We estimated the treated prevalence of bipolar disorders by mental health services in the Calgary Zone, a catchment area in Alberta with a population of over one million. Administrative data in a central repository provides information of mental health care contacts for about 95% of publically funded mental health services. We compared this treated prevalence against self-reported data in the 2002 Canadian Community Health Survey: Mental Health and Well-Being (CCHS 1.2). Of the 63 016 individuals aged 18 years plus treated in the Calgary Zone in 2002-2008, 3659 (5.81%) and 1065 (1.70%) were diagnosed with bipolar I and bipolar II disorder, respectively. The estimated treated population prevalence of these disorders was 0.41% and 0.12%, respectively. We estimated that 0.44% to 1.17% of the Canadian population was being treated by psychiatrists for bipolar I disorder from CCHS 1.2. For bipolar I disorder the estimate based on local administrative data is close to the lower end of the health survey range. The degree of agreement in our estimates reinforces the utility of administrative data repositories in the surveillance of chronic mental disorders.

A population-based analysis of the post-fracture care gap 1996–2008: the situation is not improving

The post-fracture care gap has not narrowed in recent years. Following an initial improvement, rates of medication initiation have actually declined. The current study characterizes temporal changes in post-fracture bone mineral density (BMD) testing or osteoporosis treatment initiation from 1996/1997 to 2007/2008. A population-based administrative data repository for Manitoba, Canada was accessed to identify non-traumatic fractures in individuals aged 50 years and older. Outcomes included BMD testing or dispensation of an osteoporosis medication in the 12 months following the fracture. Thirty thousand nine hundred and twenty (30,920) fracture events met the inclusion criteria; 15,670 affected major osteoporotic fracture sites. Based on either BMD testing or treatment initiation, intervention rates reached a maximum of only 15.5% in 2003/2004, compared with 6.3% in 1996/1997, and 13.2% in 2007/2008 (p-for-trend < 0.001). Post-fracture BMD testing increased from 0.7% in 1996/1997 to 8.9% 2007/2008 (p-for-trend < 0.001). Osteoporosis medication use increased from 6.1% in 1996/1997 to 12.3% in 2001/2002 and then progressively declined to 5.9% by 2007/2008 (p-for-trend = 0.025). Similar trends were observed when only major osteoporotic fractures were included. The initiation of BMD testing or medication varied according to age, gender, geographic region, and income. Despite increased attention to gaps in osteoporosis management post-fracture in the last 10 years, the situation has not improved: in 2007/20008, fewer than 20% of untreated individuals with a low-trauma fracture received intervention. Novel strategies are required to disseminate and implement best practices at the point of care to reduce the risk of recurrent fractures.

Factors Associated With Falls During Hospitalization in an Older Adult Population

Falls of hospitalized older adults are of concern for patients, family members, third-party payers, and caregivers. Falls are the most common safety incident among hospitalized patients with fall rates from 2.9-13 per 1,000 patient days. Little effectiveness research has been conducted on nursing interventions and other variables associated with falls of older adults during hospitalization. The purpose of this exploratory outcomes effectiveness study was to examine variables associated with falls during hospitalization of older adults. An effectiveness research model composed of patient characteristics, clinical conditions, nursing unit characteristics, medical, pharmacy, and nursing interventions was tested using generalized estimating equations (GEE) analysis. The sample consisted of 10,187 hospitalizations of 7,851 patients, aged 60 or older, admitted for acute care services over a 4-year period. Those included in the sample either had received the Nursing Interventions Classification (NIC) intervention of Fall Prevention (defined as "instituting special precautions with patient at risk for injury from falling" [Dochterman & Bulechek, 2004, p. 363]) or were at risk for falling as defined by a fall risk assessment scale. Data were obtained retrospectively from 9 clinical and administrative data repositories from 1 tertiary care hospital. Variables that were positively associated with falls, after controlling for other variables in the model, included several medical and nursing treatments; several types of medications including antidepressants, benzodiazepines, antipsychotic, and psychotropic agents; and several types of nursing treatments including restraints and neurologic monitoring (at low use rates of < 2 times a day). Variables inversely associated with falls included registered nurse (RN) skill mix, pressure ulcer care, pain management, and tube care. The study demonstrates the importance of conducting interdisciplinary effectiveness research that includes nursing care. Most of the variables associated with falls were interventions (medical, pharmacy, and nursing). Dose of nursing treatments and RN skill mix were also associated with falls.

The Effect of High Nursing Surveillance on Hospital Cost

The purpose of this study was to determine the cost of one nursing treatment, surveillance, for older, hospitalized adults at risk for falling. An observational study using information from data repositories at one Midwestern tertiary hospital. The inclusion criteria included patients age>60 years, admitted to the hospital between July 1, 1998 and June 31, 2002, at risk for falls or received the nursing treatment of fall prevention. Data came from clinical and administrative data repositories that included Nursing Interventions Classification (NIC). The nursing treatment of interest was surveillance and total hospital cost associated with surveillance was the dependent variable. Propensity-score analysis and generalized estimating equations (GEE) were used as methods to analyze the data. Independent variables related to patient characteristics, clinical conditions, nurse staffing, medical treatments, pharmaceutical treatments, and other nursing treatments were controlled for statistically. The total median cost per hospitalization was $9,274 for this sample. The median cost was different (p=0.050) for patients who received high versus low surveillance. High surveillance delivery cost $191 more per hospitalization than did low surveillance delivery. Propensity scores were applied to determine the cost of surveillance among hospitalized adults at risk for falls in this observational study. The findings show the effect of high surveillance delivery on total hospital cost compared to low surveillance delivery and provides an example of a useful method of determining cost of nursing care rather than including it in the room rate. More studies are needed to determine the effects of nursing treatments on cost and other patient outcomes in order for nurses to provide cost-effective care. Propensity scores were a useful method for determining the effect of nursing surveillance on hospital cost in this observational study. The results of this study along with possible clinical benefits would indicate that frequent nursing surveillance is important and might support the need for additional nursing staff to deliver frequent surveillance.

Cost of care for seniors hospitalized for hip fracture and related procedures

Hospitalization and treatment for hip fracture and elective hip replacement surgery are increasing as the number of elderly increases and with new surgical breakthroughs. Little research has been conducted on the interventions and other variables that impact cost of care; no research has been published that includes the impact of nursing care on hospital cost. To explain the cost of hospital care that includes nursing interventions for an older patient population hospitalized for a hip fracture and/or related procedure. An effectiveness research model composed of patient characteristics, clinical conditions, nursing unit characteristics, medical, pharmacy, and nursing interventions related to the outcome of hospital cost was tested using GEE analysis. The analysis included 195 variables systematically reduced to 71 that were then examined in a sample of 568 hospitalizations (n = 523 patients, > or = 60 years old) admitted for treatment of a hip fracture or elective hip procedure over a 4-year period. Data were obtained retrospectively from nine clinical and administrative data repositories from one tertiary care hospital. The best predictors of increased hospital cost were the nursing intervention of Tube Care, the level of RN staffing below the unit's average, total number of medical procedures, total number of different medications, and low levels of the nursing intervention of Surgical Preparation. More RN hours per patient day and some nursing interventions were associated with reduced cost. The study demonstrates the importance of conducting effectiveness research in nursing. Some nursing interventions were associated with increased cost and some with decreased cost, but when compared with medical and pharmacy interventions, fewer nursing interventions were associated with increased cost. Inadequate RN staffing raised cost whereas increased RN staffing was associated with lower costs.

Information systems: the key to evidence-based health practice.

Increasing prominence is being given to the use of best current evidence in clinical practice and health services and programme management decision-making. The role of information in evidence-based practice (EBP) is discussed, together with questions of how advanced information systems and technology (IS&T) can contribute to the establishment of a broader perspective for EBP. The author examines the development, validation and use of a variety of sources of evidence and knowledge that go beyond the well-established paradigm of research, clinical trials, and systematic literature review. Opportunities and challenges in the implementation and use of IS&T and knowledge management tools are examined for six application areas: reference databases, contextual data, clinical data repositories, administrative data repositories, decision support software, and Internet-based interactive health information and communication. Computerized and telecommunications applications that support EBP follow a hierarchy in which systems, tasks and complexity range from reference retrieval and the processing of relatively routine transactions, to complex "data mining" and rule-driven decision support systems.