Resource Intensity Weight Research Articles

Sepsis Inpatient Diagnostic Testing at Mid-Size Academic and Non-academic Health Systems

Abstract Introduction/Objective Comparison of clinical laboratory test and radiology imaging utilization for sepsis inpatients across multiple academic and non-academic health systems would be useful for healthcare resource utilization benchmarking. Methods/Case Report We compared laboratory and imaging utilization for adult patients hospitalized for sepsis procedures at mid-size (250-450 hospital beds), academic (N=12; 31,353 hospitalizations) and non-academic (N=18; 54,192 hospitalizations), hospitals using the Vizient Clinical Data Base™ over 3 years (2019-2021). We used Medicare Severity Diagnosis Related Groups (MSDRG), used by the US Centers for Medicare and Medicaid Services (CMS), to identify hospitalizations for sepsis (MSDRG triplet 870/871/872). We stratified patients by severity comorbid conditions and complications into high, moderate, and low severity groups. We compared the mean number of clinical laboratory (CPT codes 80000-89999) and imaging studies (CPT codes 70000-79999) per hospitalization and per hospital day. We also measured aggregate clinical Resource Intensity Weight (RIW) per hospitalization to quantify diagnostic resource consumption for each encounter. The RIW is based on the US Centers for Medicare and Medicaid Services (CMS) Ambulatory Payment Classification (APC) weights. Results (if a Case Study enter NA) Mean laboratory tests were significantly greater (p<.01) at academic hospitals per encounter (152.2 vs. 95.4 tests, 59.5% higher) and per hospital day (14.5 vs. 9.9 tests, 46.5% higher). Laboratory RIW was also higher per hospitalization (21.0 vs. 13.5 RIW, 55.6% higher) and per hospital day (2.0 vs. 1.4 RIW, 42.9% higher) at academic hospitals. Mean imaging studies at academic hospitals were higher per case (7.8 vs. 7.2 studies, 8.3% higher) but not different per day (0.80 for both hospital groups). Imaging RIW was not significantly different between academic and non-academic hospitals either by encounter (11.1 vs. 9.9, 12.1% higher) or per day (1.2 for both hospital groups). Imaging comparisons lacked statistical significance. Analysis of utilization after stratification for severity levels revealed a similar pattern with greater differences in the high severity group. Conclusion Mean laboratory tests and laboratory RIW per hospitalization are greater at academic hospitals. These differences persist after adjustment for hospital length of stay and severity level. Differences in imaging studies and imaging RIW were not significant.

Correlation Between Large-Scale Health System Operational Parameters and Laboratory Test Utilization

Abstract Introduction/Objective The extent of correlation between clinical laboratory test utilization and large-scale operational parameters would be helpful to adjust for these parameters when benchmarking utilization. Methods/Case Report We compared clinical laboratory and imaging utilization over 3 years (2019-2021) for adult patients hospitalized for specific surgical, medical, and obstetrics diagnoses at multiple academic hospitals (N=58; 625,436 hospitalizations) ranging in size from 250-1300 hospital beds. We queried the Vizient Clinical Data Base with permission from Vizient, Inc.® employing Medicare Severity Diagnosis Related Groups (MSDRG), used by the US Centers for Medicare and Medicaid Services (CMS), to identify hospitalizations for gastrointestinal (GI) surgery (MSDRG triplet 329/330/331), sepsis (MSDRG triplet 870/871/872), and vaginal delivery (MSDGR triplet 805/806/807). We stratified patients within each diagnostic group for comorbid conditions and complications into high, moderate, and low severity groups. We compared mean laboratory tests and Resource Intensity Weight (RIW) per hospitalization and hospital day. The RIW is based on the CMS Ambulatory Payment Classification (APC) weights. We measured correlation of laboratory utilization with hospital bed size as well as annual discharges (sepsis group), surgical procedures (GI surgery group), births (vaginal delivery group), and diagnosis-specific discharges. Results (if a Case Study enter NA) For sepsis hospitalizations, there were small significant (p<.01) negative correlations (r2 0.05-0.16) between laboratory utilization, measured as test numbers or RIW, and diagnosis-specific discharges for low and moderate severity groups; there was no significant correlation with either bed size or overall annual discharges. There were no consistent correlations of laboratory utilization with bed size, annual surgical procedures, or diagnosis-specific discharges for GI surgery patients. Hospitalizations for vaginal delivery demonstrated small negative correlations between laboratory utilization and bed size, annual births, and diagnosis- specific discharges. Conclusion For specific diagnostic groups, laboratory utilization (tests as well as laboratory RIW) exhibited negative correlations with large-scale hospital operational parameters. These correlations were typically weak with varying statistical significance. The findings suggest that laboratory test utilization efficiency may require evaluation of individual health systems on a case-by-case basis.

Machine Learning and Causal Approaches to Predict Readmissions and Its Economic Consequences Among Canadian Patients With Heart Disease: Retrospective Study.

Unplanned patient readmissions within 30 days of discharge pose a substantial challenge in Canadian health care economics. To address this issue, risk stratification, machine learning, and linear regression paradigms have been proposed as potential predictive solutions. Ensemble machine learning methods, such as stacked ensemble models with boosted tree algorithms, have shown promise for early risk identification in specific patient groups. This study aims to implement an ensemble model with submodels for structured data, compare metrics, evaluate the impact of optimized data manipulation with principal component analysis on shorter readmissions, and quantitatively verify the causal relationship between expected length of stay (ELOS) and resource intensity weight (RIW) value for a comprehensive economic perspective. This retrospective study used Python 3.9 and streamlined libraries to analyze data obtained from the Discharge Abstract Database covering 2016 to 2021. The study used 2 sub-data sets, clinical and geographical data sets, to predict patient readmission and analyze its economic implications, respectively. A stacking classifier ensemble model was used after principal component analysis to predict patient readmission. Linear regression was performed to determine the relationship between RIW and ELOS. The ensemble model achieved precision and slightly higher recall (0.49 and 0.68), indicating a higher instance of false positives. The model was able to predict cases better than other models in the literature. Per the ensemble model, readmitted women and men aged 40 to 44 and 35 to 39 years, respectively, were more likely to use resources. The regression tables verified the causality of the model and confirmed the trend that patient readmission is much more costly than continued hospital stay without discharge for both the patient and health care system. This study validates the use of hybrid ensemble models for predicting economic cost models in health care with the goal of reducing the bureaucratic and utility costs associated with hospital readmissions. The availability of robust and efficient predictive models, as demonstrated in this study, can help hospitals focus more on patient care while maintaining low economic costs. This study predicts the relationship between ELOS and RIW, which can indirectly impact patient outcomes by reducing administrative tasks and physicians' burden, thereby reducing the cost burdens placed on patients. It is recommended that changes to the general ensemble model and linear regressions be made to analyze new numerical data for predicting hospital costs. Ultimately, the proposed work hopes to emphasize the advantages of implementing hybrid ensemble models in forecasting health care economic cost models, empowering hospitals to prioritize patient care while simultaneously decreasing administrative and bureaucratic expenses.

A64 THE UPTAKE AND IMPACT OF AN ELECTRONIC CIRRHOSIS ADMISSION ORDER SET: AN EARLY EXPERIENCE AT A SINGLE CENTRE

Abstract Background Cirrhosis is a chronic disease that confers high morbidity and mortality. It is a leading cause for hospital admissions and leads to significant healthcare resource utilization. Several guidelines outline recommendations to provide best practice to hospitalized patients with cirrhosis. Despite studies supporting a reduction in mortality when guideline based care is followed, this is achieved in less than 50% of hospitalized patients with cirrhosis1. Standardized electronic order sets can be a potential tool to improving clinical outcomes and bridging this gap in care. Purpose Since March 2021, an electronic cirrhosis admission order set has been available for at our hospital site. Using administrative data, we aimed to describe our early experience with: a) order set uptake by various services, b) characteristics of the population in which the order set was used versus not used, and explore c) the impact of order set use on in-hospital mortality. Method In this single centre cohort study, patients with cirrhosis were identified based an administrative data algorithm containing codes for cirrhosis and complications. This data was used to retrieve parameters such as patient age, sex, primary admitting service, resource intensity weight (RIW), Charlson comorbidity index (CCI) and in-hospital mortality. The chi-squared test and independent samples t-test were used to compare characteristics of patients in whom the order set was used versus not used. Multivariable logistic regression was used to determine the impact of order set use on in-hospital mortality. P value significance was established at <0.05. Result(s) A total of 825 patients were included in the analysis. The overall mean age (standard deviation) of patients was 58.5 (14.2) years with 57.5% being male. Average length of stay was 11.3 days with a mean CCI of 3.2 (2.3) and RIW of 3.3 (7.2). The primary admitting service was Gastroenterology in 36.1%, Internal Medicine in 35.6% and other services in 28.3% of cases. Of those admitted, the order set was used in 27.2% of cases. The overall in-hospital mortality of patients was 14.2%. Mean age, sex and CCI were not significantly different in patients admitted with the order set versus without. In patients admitted with the order set compared to without, RIW was significantly lower (2.06 (2.62) versus 3.80 (8.2), p<0.001), as was length of stay (9.5 (11.8) days compared to 12.0 (18.6) days, p =0.03) and in-hospital mortality (8.5% versus 16.3%, p =0.003). On multivariable regression analysis (Table 1), after adjustment for age, RIW and CCI, use of the order set was associated with lower in-hospital mortality (odds ratio 0.53 (95% CI 0.3 to 0.9), p=0.02). Image Conclusion(s) Uptake of the electronic cirrhosis admission order set was modest at only 27% of eligible admissions. Although it appears to be associated with lower in-hospital mortality, a chart review is in process to assess if this association still holds after accounting for the impact of additional confounders. Please acknowledge all funding agencies by checking the applicable boxes below None Disclosure of Interest None Declared

Prolonged mechanical ventilation in Alberta: A 10 year historical cohort study

INTRODUCTION Patients requiring Prolonged Mechanical Ventilation (PMV) are a small but important subset of critically ill patients treated in an Intensive Care Unit (ICU). The purpose of this study is to identify and characterize the PMV population in Alberta, Canada over a period of 10 years and to determine mortality, discharge disposition and healthcare cost. METHODS A search of the Alberta Health Services Enterprise Data Warehouse was performed to characterize all patients with 7 days or more of mechanical ventilation in an acute care hospital in Alberta from 2009-2019. Data linkages were performed to identify survival up to 2 years and Healthcare cost was estimated using resource intensity weight (RIW) score. RESULTS The search identified 11,739 patients ventilated for ≥7 days from 2009-2019. In this cohort, 59% of patients were ventilated for 7-13 days, 20% for 14-20 days and 21% for 21 days or more. The in-hospital survival rate was 68% and the one-year survival from initiation of ventilation was 61%. Of the patients discharged alive, 93% were discharged to community and 7% were discharged to a continuing care center. The median healthcare cost for index hospital admission was $119,627 ($70,549-$200,036) CONCLUSION PMV users require a significant duration of mechanical ventilation, a prolonged stay in the ICU and hospital and high healthcare resource utilization. The majority of these patients survive their index admission and are discharged to community.

Laboratory Testing for Obstetrics Patients at Academic and Non-Academic Health Systems

Abstract Introduction/Objective Evaluation of obstetric clinical laboratory test utilization differences between academic and non-academic health systems would provide important benchmarking information for healthcare leaders and policy makers. Methods/Case Report Over a 3-year period (2019-2021), using the Vizient® Clinical Data Base with permission from Vizient, Inc. (All rights reserved.), we compared clinical laboratory utilization for adult obstetrics inpatients at mid-size (250-450 hospital beds) academic (N=9; 27,036 hospitalizations) and non-academic (N=17; 50,462 hospitalizations) hospitals across the US. We used Medicare Severity Diagnosis Related Groups (MSDRG), employed by the US Centers for Medicare and Medicaid Services (CMS), to identify Cesarean section (MSDRG triplet 786-788) and vaginal delivery (MSDGR triplet 805-807) patient groups. For both groups, we stratified by comorbid conditions and complications into high, moderate, and low severity subgroups. We compared the mean number of laboratory tests (CPT codes 80000-89999) per hospitalization and per hospital day. We measured aggregate Clinical Resource Intensity Weight (RIW) per hospitalization to quantify laboratory resource consumption for each encounter. The RIW is based on the CMS Ambulatory Payment Classification (APC) weights. Results (if a Case Study enter NA) Academic hospitals had a significantly (p<.01) higher mean number of lab tests per Cesarean section hospitalization (20.3 vs. 10.3 tests, 97.1% higher) and hospital day (4.7 vs. 3.3 tests, 42.4% higher). Laboratory RIW per case was also significantly (p<.01) higher at academic hospitals (4.8 vs. 3.6 RIW, 33.3% higher); however, RIW per day did not differ between academic and non-academic hospitals. Significant differences (p<.01) persisted after adjusting for severity level. Although differences were smaller, academic hospitals had greater lab tests per case (12.1 vs. 8.1 tests, 49.4% higher) and day (4.3 vs. 3.6 tests, 19.4% higher) for vaginal delivery hospitalizations. Laboratory RIW per case was also significantly (p<.01) higher at academic hospitals (3.4 vs. 2.8 RIW, 21.4% higher). Laboratory RIW per day did not differ significantly. Significant differences remained for the high and moderate severity vaginal delivery groups. Conclusion Academic hospitals have greater laboratory test utilization for obstetrics patients. This difference appears to be largely due to a longer mean length of stay as well as use of tests with higher RIW.

Multi-Health System Comparison of Outpatient Diagnostic Testing for Urinary Tract Infection

Abstract Introduction/Objective Comparisons of diagnostic test utilization for outpatient encounters across multiple health systems are uncommon. Such comparisons are helpful to establish baseline diagnostic testing patterns across health systems. Methods/Case Report Using the Vizient Clinical Database, we compared the number of clinical laboratory tests (CPT codes 80000-89999) and imaging studies (CPT codes 70000-79999) per outpatient encounter for patients with urinary tract infection (UTI, N=97,714) or dysuria (N=125,388). We employed primary ICD-10 codes for UTI (N39.0) and dysuria (R30.0, R30.9, R35.0, R39.15) to define each patient group. We measured the aggregate Clinical Resource Intensity Weight (RIW) per outpatient visit to quantify diagnostic resource consumption for each encounter. The RIW is based on the US Centers for Medicare and Medicaid Services (CMS) Ambulatory Payment Classification (APC) weights. CMS assigns an APC weight to each diagnostic test based on the geometric mean cost of each particular test. We compared diagnostic testing at 20 academically affiliated health systems across the United States (2017- 2019) with >500 annual outpatient visits for UTI and dysuria. We also examined two relevant tests: urinalysis (CPT codes 8100, 81001, 81002, 81003, 81005, 81007, and 81015) and basic urine culture (CPT code 87086) testing patterns. Results (if a Case Study enter NA) The mean number of laboratory tests was 4.30 tests (range 3.04-5.89) and 3.01 (range 2.41-3.86) for UTI and dysuria patients, respectively. Average laboratory RIW and quantity were moderately correlated with a mean RIW of 0.50 and 0.38 for UTI and dysuria patients, respectively. The mean number of imaging studies for each group was 0.26 (range 0.08-0.46) and 0.05 (range 0.01-0.14), respectively. Average imaging RIW and quantity were more highly correlated with a mean RIW of 0.52 and 0.11 for UTI and dysuria patients, respectively. UTI encounters averaged 0.78 (range 0.38-1.28) urinalysis tests and 0.65 (range 0.39-0.86) urine cultures. Dysuria patient visits averaged 0.77 (range 0.45-1.17) urinalysis tests and 0.58 (range 0.13-0.76) urine cultures. Conclusion There are significant differences in diagnostic tests and resource utilization between large health systems for patients with UTI and dysuria. These differences persist with specific test comparisons for urinalysis and urine culture.

P617 Trends in Pediatric Inflammatory Bowel Disease-attributable direct costs: A Canadian population-based analysis

Abstract Background Background: In addition to its symptomatic burden, inflammatory bowel disease (IBD) has a major financial burden on patients and healthcare systems. However, there is a paucity of evidence on IBD-attributable costs in children. In a population-based analysis, we determined the trends of IBD-attributable direct costs over 22 years. Methods Data were extracted from Manitoba Health Provider Claims, and other population registry datasets from 1995 to 2017. Children with IBD were matched by age, sex, and location with children without IBD. IBD-attributable direct costs were calculated using utilization counts from the administrative data and cost estimates from different sources. Inpatient hospitalization and outpatient procedure costs were estimated using the resource intensity weight (RIW) that is attached to each record in the data. Costs were expressed in 2018 Canadian dollars. Results We included 733 (428 with Crohn’s disease) prevalent cases who were diagnosed with IBD before the age of 18 years and were followed for 2450 person-years. An age, sex and geography matched control group of 6763 persons without IBD who were followed for 21558 person-years was included. The median annual physician’s billing fees increased from $381 (IQR 215–1064) in 1995 to $936 (IQR 579–1932) in 2017 (p<.001). The annual ambulatory care days for persons with IBD also significantly increased from a median of 8 days per year (IQR 5–13) in 1995 to 12 days per year (IQR 8–17) in 2017 (p < 0.0001) while they remained stable (median 2 days per year) in the control group (p=0.12). The annual medication costs per patient increased from a median of $270.9 in 1995 to $7944 in 2017 (p<.0001). Between 2012 and 2017, the median annual medication costs for all persons on anti-tumor necrosis factor (TNF) medications were $28,582 (IQR 21854–36736)compared to $861for persons with IBD not on an anti-TNF agent (IQR 355–1,714) (p<0.0001) with a relatively stable costs over the 5-year period. The median annual direct costs per patient with IBD was $1810.716 in 2004 as compared to $14791.55 (p<.0001) in 2017. Conclusion Over 2 decades, there was a significant increase in the pediatric IBD-attributable direct costs mainly driven by medication costs mainly anti-TNF biologics.

Trends in paediatric inflammatory bowel disease-attributable direct costs: a population-based analysis.

In addition to its morbidities, inflammatory bowel disease (IBD) has a major financial burden on patients and healthcare systems. However, there is a paucity of evidence on IBD-attributable costs in children. To determine the trends of IBD-attributable direct costs over time using a population-based analysis. Data were extracted from Manitoba Health Provider Claims and other population registry datasets from 1995 to 2017. Children with IBD were matched by age, sex and location with children without IBD. IBD-attributable direct costs were calculated using utilization counts from the administrative data and cost estimates from different sources. Inpatient hospitalisation and outpatient procedure costs were estimated using the resource intensity weight (RIW) that is attached to each record in the data. Costs were expressed in Canadian dollars. We included 733 (428 with Crohn's disease) prevalent cases who were diagnosed with IBD before the age of 18years and were followed for 2450 person-years. A matched control group of 6763 persons who were followed for 21558 person-years was included. The median annual costs of physician services billed per patient increased from $381 (IQR 215-1064) in 1995 to $936 (IQR 579-1932) in 2017 (P<0.001). The annual medication costs per patient increased from a median of $270 in 1995 to $7944 in 2017 (P<0.0001). The median annual direct cost per patient was $1810 in 2004 as compared to $14791 (P<0.0001) in 2017. Over two decades, there was a significant increase in the paediatric IBD-attributable direct costs mainly driven by medication costs.

Association of diabetes with frequency and cost of hospital admissions: a retrospective cohort study.

Background:Acute inpatient hospital admissions account for more than half of all health care costs related to diabetes. We sought to identify the most common and costly conditions leading to hospital admission among patients with diabetes compared with patients without diabetes.Methods:We used data from the General Internal Medicine Inpatient Initiative (GEMINI) study, a retrospective cohort study, of all patients admitted to a general internal medicine service at 7 Toronto hospitals between 2010 and 2015. The Canadian Institute for Health Information (CIHI) Most Responsible Diagnosis code was used to identify the 10 most frequent reasons for admission in patients with diabetes. Cost of hospital admission was estimated using the CIHI Resource Intensity Weight. Comparisons were made between patients with or without diabetes using the Pearson χ2 test for frequency and distribution-free confidence intervals (CIs) for median cost.Results:Among the 150 499 hospital admissions in our study, 41 934 (27.8%) involved patients with diabetes. Compared with patients without diabetes, hospital admissions because of soft tissue and bone infections were most frequent (2.5% v. 1.9%; prevalence ratio [PR] 1.28, 95% CI 1.19–1.37) and costly (Can$8794 v. Can$5845; cost ratio [CR] 1.50, 95% CI 1.37–1.65) among patients with diabetes. This was followed by urinary tract infections (PR 1.16, 95% CI 1.11–1.22; CR 1.23, 95% CI 1.17–1.29), stroke (PR 1.13, 95% CI 1.07–1.19; CR 1.19, 95% CI 1.14–1.25) and electrolyte disorders (PR 1.11, 95% CI 1.03–1.20; CR 1.20, 95% CI 1.08–1.34).Interpretation:Soft tissue and bone infections, urinary tract infections, stroke and electrolyte disorders are associated with a greater frequency and cost of hospital admissions in patients with diabetes than in those without diabetes. Preventive strategies focused on reducing hospital admissions secondary to these disorders may be beneficial in patients with diabetes.

Associations between hospital deaths (HSMR), readmission and length of stay (LOS): a longitudinal assessment of performance results and facility characteristics of teaching and large-sized hospitals in Canada between 2013–2014 and 2017–2018

ObjectivesTo examine the association between hospital deaths (hospital standardised mortality ratio, HSMR), readmission, length of stay (LOS) and eight hospital characteristics.DesignLongitudinal observational study.SettingA total of 119 teaching and large-sized hospitals...

Comparative effectiveness of long-term acute care hospital versus skilled nursing facility transfer

BackgroundLong-term acute care hospital (LTACH) use varies considerably across the U.S., which may reflect uncertainty about the effectiveness of LTACHs vs. skilled nursing facilities (SNF), the principal post-acute care alternative. Given that LTACHs provide more intensive care and thus receive over triple the reimbursement of SNFs for comparable diagnoses, we sought to compare outcomes and spending between LTACH versus SNF transfer.MethodsUsing Medicare claims linked to electronic health record (EHR) data from six Texas Hospitals between 2009 and 2010, we conducted a retrospective cohort study of patients hospitalized on a medicine service in a high-LTACH use region and discharged to either an LTACH or SNF and followed for one year. The primary outcomes included mortality, 60-day recovery without inpatient care, days at home, and healthcare spendingResultsOf 3503 patients, 18% were transferred to an LTACH. Patients transferred to LTACHs were younger (median 71 vs. 82 years), less likely to be female (50.5 vs 66.6%) and white (69.0 vs. 84.1%), but were sicker (24.3 vs. 14.2% for prolonged intensive care unit stay; median diagnosis resource intensity weight of 2.03 vs. 1.38). In unadjusted analyses, patients transferred to an LTACH vs. SNF were less likely to survive (59.1 vs. 65.0%) or recover (62.5 vs 66.0%), and spent fewer days at home (186 vs. 200). Adjusting for demographic and clinical confounders available in Medicare claims and EHR data, LTACH transfer was not significantly associated with differences in mortality (HR, 1.12, 95% CI, 0.94–1.33), recovery (SHR, 1.07, 0.93–1.23), and days spent at home (IRR, 0.96, 0.83–1.10), but was associated with greater Medicare spending ($16,689 for one year, 95% CI, $12,216–$21,162).ConclusionLTACH transfer for Medicare beneficiaries is associated with similar clinical outcomes but with higher healthcare spending compared to SNF transfer. LTACH use should be reserved for patients who require complex inpatient care and cannot be cared for in SNFs.

49 Rooming-In to Treat Neonatal Abstinence Syndrome

Abstract Background Ontario has been facing a steady rise in the number of individuals abusing narcotics. Newly implemented rooming-in programs in Ontario have allowed infants of opioid-dependent mothers to stay in the same room as their mother while the infant continues to be monitored for signs of neonatal abstinence syndrome (NAS). Objectives To retroactively review the impact of a rooming-in program for babies at risk of NAS on the need for pharmacologic treatment and length of stay in one community hospital site in Belleville, Ontario. Design/Methods Belleville General Hospital developed a rooming-in program for newborns at risk of NAS in July 2015. Prior to its inception, the standard of care was to admit these infants to the special care nursery for monitoring and treatment. Charts were reviewed to collect data on infants born to mothers using opioids in the 24 months prior to (July 2013 – June 2015) and after (July 2015 – June 2017) the implementation of our program. The two groups were compared for the primary outcomes studied, including the number of babies started on morphine and length of stay in hospital. Secondary outcomes were also examined, including breast feeding rates, resource intensity weight, and total hospital cost. Results Rooming-in is associated with a reduction in the need for treatment with morphine, shorter length of stay in hospital, improved breast feeding rates, and lower total hospital cost. Conclusion Our study demonstrates that rooming-in programs for babies born to mothers using opioids have benefits in terms of quality of care and health care resource utilization. These findings add to the existing literature on NAS that rooming-in can be successfully implemented in a community hospital.

PCN350 USING REAL WORLD DATA TO DETERMINE HEALTH SYSTEM COSTS OF CANADIANS DIAGNOSED WITH CHRONIC LYMPHOCYTIC LEUKEMIA

With the recent advances of novel treatments for patients with chronic lymphocytic leukemia (CLL), and fiscal constraints of the publicly funded healthcare system in Canada, understanding the real world economic impact of CLL is critical. The objective of this study was to determine the health system costs of CLL patients treated in Ontario, Canada. Patients diagnosed and treated between January 1, 2010 and December 31, 2017 were identified in the Ontario Cancer Registry and linked to provincial administrative databases, capturing hospitalizations, cancer clinic visits, physician services and novel treatments (radiation and inexpensive chemotherapies were excluded). Total cohort, annual and mean per patient/control costs (CAD 2017) were determined using a costing methodology available at the Institute for Clinical Evaluative Sciences called GETCOST. Short-term episodes (e.g., hospitalizations) attributed costs by multiplying the encounter’s resource intensity weight by an annual cost per weighted case; long-term episodes (e.g., complex care) attributed costs by weighted days, and costs of visit-based encounters were determined by utilization. 2,572 CLL patients/cases were identified and matched with 7,611 controls (median age 68 years; 66% male). The overall total cost for cases was $254.7M (mean cost per patient was $99,900); oral medications based on list price ($56.5M), inpatient hospitalizations ($49.1M), and cancer clinic visits ($46.2M) were the top three cost contributors. The mean cost per control was $46,382 with inpatient hospitalizations, physician services and oral medications the top three cost contributors. For CLL patients, year 1 after diagnosis had the highest mean cost ($31,928) followed by year 2 ($17,665). By calendar year, 2016 and 2017 had the highest mean costs. Real world costs for CLL patients may have been increasing over time. Exploring whether investment in new novel agents resulted in improved survival would be key.

Impact of adverse drug reactions on the coding of a hospital stay in Quebec: exploratory descriptive study by simulation.

The discharge summary sheet's coding allows calculation of the severity index (SI), mortality index (MI), and resource intensity weight (RIW). These indicators help to describe the burden of care for individual cases and could potentially influence patient-based funding. This study was undertaken to simulate the impact of different adverse drug reactions (ADRs) on the hospital length of stay, thus allowing calculation of the effect of ADRs on the SI, MI, and RIW. This exploratory descriptive study was based on computer simulations. We created, by simulation, seven patient profiles of various complexities representative of our patients. Fifteen types of combination of drug and ADR manifestation comprising 15 ADR caused by eight different drug classes were identified based on the most frequently coded ADR in fiscal years 2016-2017 and 2017-2018. Those 15 combinations were applied to the patient profile to simulate the impact on the SI, MI, and RIW in eight scenarios. From these data, we measured the impact of the ADRs on these indicators. A total of 1,571 simulations were run. In general, the addition of a couple of drug and ADR manifestation contributed to increases in all three of the indicators. More specifically, the SI and RIW both increased in 30.7% (n = 482), whereas the MI increased in 14.6% (n = 229). For a same scenario, the impact on the three indicators could vary depending on the patient profile to which it was applied. This study has presented simulation data on the impact of the coding of ADRs on the hospital stay of a patient in Quebec.

PCN210 - USING REAL WORLD DATA TO DETERMINE HEALTH SYSTEM COSTS OF A 5-YEAR NON-SMALL CELL LUNG CANCER COHORT

With the recent advances in the treatment of advanced non-small cell lung cancer (NSCLC) and fiscal constraints of publicly funded healthcare systems, understanding the real world economic impact of lung cancer is increasingly important. The objective of this study was to determine the health system costs of a 5-year cohort of NSCLC patients treated in Ontario, Canada. Patients diagnosed between April 1, 2010 and March 31, 2015 were identified in the Ontario Cancer Registry and linked to provincial administrative databases, capturing hospitalizations, cancer clinic visits, physician services and expensive chemotherapies. Activity level reporting of radiation and inexpensive chemotherapies was not reported. Total cohort, annual and mean per patient costs (CAD 2017) were determined using a costing methodology available at the Institute for Clinical Evaluative Sciences called GETCOST. Short-term episodes (e.g., hospital-based encounters) calculate costs by multiplying the encounter’s resource intensity weight by an annual cost per weighted case for total costs, long-term episodes (e.g., complex continuing care) calculate costs by weighted days, and costs of visit-based encounters are determined at utilization. It was assumed that costs were attributable to NSCLC. 24,729 NSCLC patients were identified (median age 70yr; 48.5% female; stage I=20.7%, II=9.3%, III=20.8%, IV=49.2%). The overall total cost was $1.9B (mean cost per patient= $76,816); inpatient hospitalizations ($635.2M), cancer clinic visits ($323.7M) and physician services ($301.4M) were the top three cost contributors while the total cost of expensive chemotherapies was $61.5M. Year 1 after diagnosis had the highest costs ($1.3B) followed by year 2 ($316.3M). Mean cost per patient varied by stage, being highest for stage II ($94,553) and lowest for stage IV ($66,652). Real world costs during the 5-year period (prior to the use of immuno-oncology drugs) were substantial even with poor survival of NSCLC patients and those receiving no active treatment.

PCN221 - STAGE III UNRESECTABLE NON-SMALL CELL LUNG CANCER TREATMENT PATTERNS AND COSTS: AN ONTARIO, CANADA ANALYSIS

With recent changes in the treatment of Stage III, non-small cell lung cancer (NSCLC), understanding the economic impact from a public payers’ perspective is key. A longitudinal, population-level study was carried out to determine baseline treatment patterns and health system costs prior to the introduction of emerging treatments. Patients diagnosed between April 1, 2010 and March 31, 2015 were identified in the Ontario Cancer Registry. Stage III patients were unresectable if no surgery was undertaken within 3 months of diagnosis. Initial treatments included radiation (RT), targeted therapy, chemotherapy, concurrent and sequential chemo+RT (cCRT, sCRT). Costs from provincial administrative databases included inpatient hospitalizations, cancer clinic visits, physician services, and chemotherapies. Activity level reporting of radiation and inexpensive chemotherapies was not reported. Total cohort, annual and mean per patient costs (CAD 2017) were determined using a costing methodology from the Institute for Clinical Evaluative Sciences called GETCOST. Short-term episodes (e.g., hospital-based) calculate costs by multiplying the encounter’s resource intensity weight by an annual cost per weighted case, long-term episodes (e.g., complex continuing care) calculate costs by weighted days, and costs of visit-based encounters are determined at utilization. It was assumed costs were attributable to NSCLC. 4,542 (18.4%) of the 24,729 patients identified were Stage III unresectable (median age 70yr, 54.2% male). Treatment distribution was: cCRT (21.6%), palliative RT (21.3%), curative RT (20.2%), no treatment (19.6%), chemotherapy (11.6%), sCRT (4.9%) and targeted therapy (0.7%). The overall total cost was $396.9M (mean cost per patient= $87,393); 68.4% of total costs ($271.3M) were incurred in the first year. Cost drivers were inpatient hospitalizations ($108.4M), cancer clinic visits ($107.5M), and physician services ($56.9M). cCRT was only administered in 21.6% of Stage III unresectable patients, even though considered the standard of care and chemotherapies were not a cost driver in this cohort.

The Effect of Hospital Isolation Precautions on Patient Outcomes and Cost of Care: A Multi-Site, Retrospective, Propensity Score-Matched Cohort Study

BackgroundIsolation precautions have negative effects on patient safety, psychological well-being, and healthcare worker contact. However, it is not known whether isolation precautions affect certain hospital-related outcomes.ObjectiveTo examine the effect of isolation precautions on hospital-related outcomes and cost of care.DesignRetrospective, propensity-score matched cohort study of inpatients admitted to general internal medicine (GIM) services at three academic hospitals in Toronto, Ontario, Canada between January 2010 and December 2012.ParticipantsAdult (≥18 years of age) patients on isolation precautions for respiratory illnesses and methicillin-resistant Staphylococcus aureus (MRSA) were matched to controls based on propensity scores derived from nine covariates: age, sex, Resource Intensity Weight, number of hospital readmissions within 90 days, total length of stay for hospital admissions within 90 days, site of admission, month of isolation, year of isolation, and Case Mix Group.Main MeasuresThirty-day readmission rates and emergency department visits, hospital length of stay, expected length of stay, adverse events, in-hospital mortality, patient complaints, and cost of care in Canadian doll ars (CAD).Key ResultsA total of 17,649 non-isolated patients were admitted to the participating hospitals during the study period. We identified 1506 patients isolated for respiratory illnesses and 745 patients isolated for MRSA. Compared to non-isolated individuals, those on isolation precautions for respiratory illnesses stayed 17 % longer (95 % CI: 9 %, 25 %), stayed 9 % longer than expected (95 % CI: 3 %, 15 %), and had 23 % higher cost of care (95 % CI: 14 %, 32 %). Patients isolated for MRSA had similar outcomes, but they also had a 4.4 % higher (95 % CI: 1.4 %, 7.3 %) rate of readmission to hospital within 30 days.ConclusionsIsolation precautions are associated with adverse effects which may result in poorer hospital outcomes. Balancing the benefits for the many with the harms to the few will be a future challenge.

P113: Presentations for hypoglycemia associated with diabetes mellitus to emergency departments in a Canadian province: a database and cost analysis

Introduction: Diabetes mellitus (DM) is a common chronic disease. The Canadian Diabetes Association (CDA) estimated that the national direct cost of DM accounts for approximately 3.5% of public healthcare spending. The economic burden has been estimated to be $12.2 billion in 2010 and projected to increase by $4.7 billion (38%) by 2020. For the province of Alberta, the estimated cost was $1.3 billion in 2015 and $1.7 billion for 2025. The cost of lesser complications of DM like hypoglycemia is not as well understood. The objective of this study was to estimate the health system cost of presentations by adults to Alberta emergency departments (ED) for hypoglycemia associated with type 1 (T1DM) or type 2 (T2DM) diabetes. Methods: A retrospective cohort study was conducted using administrative data for Alberta for a five-year period (fiscal years 2010/11-2014/15). Data were sourced from an administrative database: National Ambulatory Care Reporting System (NACRS). Records of interest were those for ED patients with an ICD-10-CA diagnosis of DM-associated hypoglycemia. A top-down approach was used to estimate costs, excluding physician and ambulance fees. This involved resource intensity weight (RIW), cost of a standard hospital stay (CSHS), and adjustment for inflation (to average value of Canadian dollar for Alberta for January-September 2015). A descriptive analysis was conducted. Results: Data extraction yielded 7,835 presentations by 5,884 patients. The median RIW was 0.0547. RIWs are centered at 1, thus the resource-use/cost of these presentations is well below that of the “average” case. Estimated costs per episode ranged from $108.63 to $4,136.59 with median of $431.11 (IQR: 369.40-639.50). Median episodic subgrouped costs were as follows: sex: $427.72 for males, $439.20 for females; DM type: $411.61 for T1DM, $511.63 for T2DM; date period: $835,862.09/year, $69,655.17/month, $16,030.23/week, and $2,288.78/day. Conclusion: Using population-based administrative data, we identified median costs for DM-associated hypoglycemia of approximately $430/case. Given the frequency, this condition incurs significant healthcare resource use and costs; continued efforts to reduce these ED visits seem worthwhile.

Impact of an innovative inpatient patient navigator program on length of stay and 30-day readmission.

The current climate of increasing patient complexity coupled with rising costs have prompted the need for adaptive innovation. There are limited data describing inpatient interventions targeting improvements in both communication and transitional care. Evaluate the patient navigator (PN) program, an innovative inpatient intervention intended to enhance navigation through the complexity of hospital admissions for patients and providers. PNs were dedicated patient-care facilitators without clinical responsibilities integrated as full members of the inpatient care team responsible for enhancing communication between and among patients and providers. Observational retrospective cohort study. All patients admitted to the general medical service between July 2010 and March 2014. Academic medical center. Primary outcomes were hospital length of stay (LOS) and 30-day readmission rate matched by case mix group, age category, and resource intensity weight. Our matched cohort included 5628 admissions (4592 patients) exposed and 2213 admissions (1920 patients) not exposed to PNs. Admissions with PNs were 1.3 days (21%) shorter than admission without PNs (6.2 vs 7.5 days, P < 0.001). Thirty-day readmission rate was not different between the 2 groups (13.1 vs 13.8%, P = 0.48). Implementation of this intervention was associated with a reduction in LOS without an increase in 30-day readmission.