Performance of comorbidity measures for predicting outcomes in population-based osteoporosis cohorts

Comorbidity and osteoporotic fracture: approach through predictive modeling techniques using the OSTEOMED registry

Purpose

To examine the response to anti-osteoporotic treatment, considered as incident fragility fractures after a minimum follow-up of 1 year, according to sex, age, and number of comorbidities of the patients.

Methods

For this retrospective observational study, data from baseline and follow-up visits on the number of comorbidities, prescribed anti-osteoporotic treatment and vertebral, humerus or hip fractures in 993 patients from the OSTEOMED registry were analyzed using logistic regression and an artificial network model.

Results

Logistic regression showed that the probability of reducing fractures for each anti-osteoporotic treatment considered was independent of sex, age, and the number of comorbidities, increasing significantly only in males taking vitamin D (OR = 7.918), patients without comorbidities taking vitamin D (OR = 4.197) and patients with ≥ 3 comorbidities taking calcium (OR = 9.412). Logistic regression correctly classified 96% of patients (Hosmer–Lemeshow = 0.492) compared with the artificial neural network model, which correctly classified 95% of patients (AUC = 0.6).

Conclusion

In general, sex, age and the number of comorbidities did not influence the likelihood that a given anti-osteoporotic treatment improved the risk of incident fragility fractures after 1 year, but this appeared to increase when patients had been treated with risedronate, strontium or teriparatide. The two models used classified patients similarly, but predicted differently in terms of the probability of improvement, with logistic regression being the better fit.

Simple Excel and ICD-10 based dataset calculator for the Charlson and Elixhauser comorbidity indices

Background

The Charlson and Elixhauser Comorbidity Indices are the most widely used comorbidity assessment methods in medical research. Both methods are adapted for use with the International Classification of Diseases, which 10th revision (ICD-10) is used by over a hundred countries in the world. Available Charlson and Elixhauser Comorbidity Index calculating methods are limited to a few applications with command-line user interfaces, all requiring specific programming language skills. This study aims to use Microsoft Excel to develop a non-programming and ICD-10 based dataset calculator for Charlson and Elixhauser Comorbidity Index and to validate its results with R- and SAS-based methods.

Methods

The Excel-based dataset calculator was developed using the program’s formulae, ICD-10 coding algorithms, and different weights of the Charlson and Elixhauser Comorbidity Index. Real, population-wide, nine-year spanning, index hip fracture data from the Estonian Health Insurance Fund was used for validating the calculator. The Excel-based calculator’s output values and processing speed were compared to R- and SAS-based methods.

Results

A total of 11,491 hip fracture patients’ comorbidities were used for validating the Excel-based calculator. The Excel-based calculator’s results were consistent, revealing no discrepancies, with R- and SAS-based methods while comparing 192,690 and 353,265 output values of Charlson and Elixhauser Comorbidity Index, respectively. The Excel-based calculator’s processing speed was slower but differing only from a few seconds up to four minutes with datasets including 6250–200,000 patients.

Conclusions

This study proposes a novel, validated, and non-programming-based method for calculating Charlson and Elixhauser Comorbidity Index scores. As the comorbidity calculations can be conducted in Microsoft Excel’s simple graphical point-and-click interface, the new method lowers the threshold for calculating these two widely used indices.

Trial registration

retrospectively registered.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-021-01492-7.

A Revised Comorbidity Model for Administrative Databases Using Clinical Classifications Software Refined Variables

Background and objective

Database research has shaped policies, identified trends, and informed healthcare guidelines for numerous disease conditions. However, despite their abundant uses and vast potential, administrative databases have several limitations. Adjusting outcomes for comorbidities is often needed during database analysis as a means of overcoming non-randomization. We sought to obtain a model for comorbidity adjustment based on Clinical Classifications Software Refined (CCSR) variables and compare this with current models. Our aim was to provide a simplified, adaptable, and accurate measure for comorbidities in the Agency for Healthcare Research and Quality (AHRQ) databases, in order to strengthen the validity of outcomes. 

Methods

The Nationwide Inpatient Sample (NIS) database for 2018 was the data source. We obtained the mortality rate among all included hospitalizations in the dataset. A model based on CCSR categories was mapped from disease groups in Sundararajan's adaptation of the modified Deyo’s Charlson Comorbidity Index (CCI). We employed logistic regression analysis to obtain the final model using CCSR variables as binary variables. We tested the final model on the 10 most common reasons for hospitalizations.

Results

The model had a higher area under the curve (AUC) compared to the three modalities of the CCI studied in all the categories. Also, the model had a higher AUC compared to the Elixhauser model in 8/10 categories. However, the model did not have a higher AUC compared to a model made from stepwise backward regression analysis of the original 21-variable model.

Conclusion

We developed a 15-CCSR-variable model that showed good discrimination for inpatient mortality compared to prior models.

Health care utilization and excess costs after pelvic fractures among older people in Germany

Our study demonstrates a strong increase in utilization of inpatient health care and clear excess costs in older people in the first year after pelvic fracture, the latter even after adjustment for several confounders. Excess costs were particularly high in the first few months and mainly attributable to inpatient treatment.

INTRODUCTION

We aimed to estimate health care utilization and excess costs in patients aged minimum 60 years up to 1 year after pelvic fracture compared to a population without pelvic fracture.

METHODS

In this retrospective population-based observational study, we used routine data from a large statutory health insurance (SHI) in Germany. Patients with a first pelvic fracture between 2008 and 2010 (n=5685, 82% female, mean age 80±9 years) were frequency matched with controls (n=193,159) by sex, age at index date, and index month. We estimated health care utilization and mean total direct costs (SHI perspective) with 95% confidence intervals (CIs) using BCA bootstrap procedures for 52 weeks before and after the index date. We calculated cost ratios (CRs) in 4-week intervals after the index date by fitting mixed two-part models including adjustment for possible confounders and repeated measurement. All analyses were further stratified for men/women, in-/outpatient-treated, and major/minor pelvic fractures.

RESULTS

Health care utilization and mean costs in the year after the index date were higher for cases than for controls, with inpatient treatment being particularly pronounced. CRs (95% CIs) decreased from 10.7 (10.2-11.1) within the first 4 weeks to 1.3 (1.2-1.4) within week 49-52. Excess costs were higher for inpatient than for outpatient-treated persons (CRs of 13.4 (12.9-13.9) and 2.3 (2.0-2.6) in week 1-4). In the first few months, high excess costs were detected for both persons with major and minor pelvic fracture.

CONCLUSION

Pelvic fractures come along with high excess costs and should be considered when planning and allocating health care resources.

Hysterectomies are associated with an increased risk of osteoporosis and bone fracture: A population-based cohort study

AIM

This study investigated the risk of osteoporosis or bone fractures (vertebrae, hip and others) in hysterectomized women in Taiwan.

MATERIALS AND METHODS

This is a retrospective population-based cohort study from 2000 to 2013. Women aged ≥30 years who underwent hysterectomy between 2000 and 2012 were included in this study. The comparison group was randomly selected from the database with a 1:4 matching with age and index year. Incidence rate and hazard ratios of osteoporosis and bone fracture between hysterectomized women and the comparison group were calculated. Cox proportional hazard regressions were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs).

RESULTS

We identified 9,189 hysterectomized women and 33,942 age-matched women without a hysterectomy. All women were followed for a median time of about 7 years. The adjusted hazard ratio (aHR) of subsequent osteoporosis or bone fracture was higher in the hysterectomy women (2.26, 95% confidence interval [CI] = 2.09-2.44) than in the comparison group. In the subgroup analysis, oophorectomy and estrogen therapy increase the risk of osteoporosis or fracture in both groups. Regarding the fracture site, the aHR of vertebral fracture (4.92, 95% CI = 3.78-6.40) was higher in the hysterectomized women than in the comparison group. As follow-up time increasing, the aHR of vertebral fracture in hysterectomized women were 4.33 (95% CI = 2.99-6.28), 3.89 (95% CI = 2.60-5.82) and 5.42 (95% CI = 2.66-11.01) for <5, 5-9 and ≥9 years of follow-up, respectively.

CONCLUSIONS

In conclusion, we found that hysterectomized women might be associated with increased risks of developing osteoporosis or bone fracture.

Predictors of hip fractures and mortality in long-term care homes in Saskatchewan: Does vitamin D supplementation play a role?

High rates of hip fracture (HF) in long-term care (LTC) lead to increased hospitalization and greater risk of death. Supplementation of residents with vitamin D3 (vitD) has been recommended, but may be infrequently acted upon. Using a prospective cohort design, we explored use of vitD at doses ≥800 IU for hip fractures (HF) and for mortality among permanent LTC residents in Saskatchewan between 2008 and 2012, using provincial administrative health databases (N = 23178). We used stepwise backward regression with Cox proportional hazard multivariate analysis for time to first HF or to death upon entry into LTC (excluding the first three months), the association of daily vitD (determined during the first three months), age, sex, age*sex interaction, prior HF, osteoporosis diagnosis and Charlson Comormidity Score (CCS) was determined. Users of VitD were more likely older, women and those with previous HF. For HF, no significant impact of vitD or CCS was found. Models for mortality, stratified by sex, showed in women only, that vitD use resulted in a significant inverse association with time to death [HR (0.91(0.87-0.96)]; for men it was 0.94(0.88-1.01). The impact of VitD supplementation in LTC deserves further investigation, however, the mechanisms for its effect on mortality remain unclear.

Predicting the Cost of Health Care Services: A Comparison of Case-mix Systems and Comorbidity Indices That Use Administrative Data

BACKGROUND

Case-mix systems and comorbidity indices aggregate clinical information about patients over time and are used to characterize need for health care services. These tools were validated for their original purpose, but those purposes are varied, and they have not been compared directly in the context of predicting costs of health care services.

OBJECTIVE

To compare predictions of next-year health care service costs across 4 tools, including: the Johns Hopkins Adjusted Clinical Groups (ACG), the Elixhauser Comorbidity Index, Charlson-Deyo Comorbidity Index, and the Canadian Institute for Health Information (CIHI) population grouper.

METHODS

British Columbia administrative data from fiscal years 2012-2013 were used to generate case-mix variables and the comorbidity indices. Outcome variables include next-year (2013-2014) total, physician, acute care, and pharmaceutical costs, Outcomes were modeled using 2-part models. Performance was compared using adjusted R, root mean squared error, and mean absolute error using the predicted and the actual next-year cost.

RESULTS

Models including the CIHI grouper (239 conditions) and ACG system had similar performance in most cost categories and slightly better fit than Charlson Comorbidity Index (CCI) and Elixhauser Comorbidity Index (ECI). Adding a dummy variable for nonusers in the models for CCI and ECI increased R values slightly.

CONCLUSIONS

All these systems have empirical support for use in predicting health care costs, despite in some cases being developed for other purposes. No system is particularly effective at predicting next-year acute care cost, likely because acute events are often by definition unexpected. The freely available ECI and CCI comorbidity indices implemented using the highest-performing methods developed here may be a good choice in many circumstances.

Comparative Performance of Comorbidity Measures in Predicting Health Outcomes in Patients with Chronic Obstructive Pulmonary Disease

Purpose

Multiple studies have suggested that comorbidities pose negative impacts on the survival of patients with chronic obstructive pulmonary disease (COPD); few have applied comorbidity measures driven from health insurance claims databases to predict various health outcomes. We aimed to examine the performance of commonly used comorbidity measures based on diagnosis and pharmacy dispensing claims information in predicting future death and hospitalization in COPD patients.

Methods

We identified COPD patients in a population-based Taiwanese database. We built logistic regression models with age, sex, and baseline comorbidities measured by either diagnosis or pharmacy claims information as predictors of subsequent-year death or hospitalization in a random 50% sample and validated the discrimination in the other 50%. The diagnosis-based comorbidity measures included the Charlson Index and the Elixhauser comorbidity measure; the pharmacy-based comorbidity measures included the updated Chronic Disease Score (CDS) and the Pharmacy-Based Comorbidity Index (PBDI).

Results

We identified 428,251 eligible patients. For overall death, the Elixhauser comorbidity measure showed the best predictive performance (c-statistic=0.832), followed by the PBDI (c-statistic=0.822), the Charlson Index (c-statistic=0.815), and the updated CDS (c-statistic=0.808). For overall hospitalization, the PBDI (c-statistics=0.730) and the Elixhauser comorbidity measure (c-statistics=0.724) outperformed the updated CDS (c-statistics=0.714) and the Charlson Index (c-statistics=0.710). For hospitalization due to cardiovascular, cerebrovascular, or respiratory diseases, the comorbidity models showed similar predictive ranks and demonstrated c-statistics higher than 0.75. However, none of the models could adequately predict hospitalization due to other reasons (c-statistics < 0.60).

Conclusion

Our study comprehensively compared the predictive performance of comorbidity measures. The Elixhauser comorbidity measure and the PBDI are useful tools for describing comorbid conditions and predicting health outcomes in COPD patients.

Healthcare provision, functional ability and quality of life after proximal femoral fracture - 'ProFem': Study protocol of a population-based, prospective study based on individually linked survey and statutory health insurance data

INTRODUCTION

Proximal femoral fractures (PFF) are among the most frequent fractures in older people. However, the situation of people with a PFF after hospital discharge is poorly understood. Our aim is to (1) analyse healthcare provision, (2) examine clinical and patient-reported outcomes (PROs), (3) describe clinical and sociodemographic predictors of these and (4) develop an algorithm to identify subgroups with poor outcomes and a potential need for more intensive healthcare.

METHODS AND ANALYSIS

This is a population-based prospective study based on individually linked survey and statutory health insurance (SHI) data. All people aged minimum 60 years who have been continuously insured with the AOK Rheinland/Hamburg and experience a PFF within 1 year will be consecutively included (SHI data analysis). Additionally, 700 people selected randomly from the study population will be consecutively invited to participate in the survey. Questionnaire data will be collected in the participants' private surroundings at 3, 6 and 12 months after hospital discharge. If the insured person considers themselves to be only partially or not at all able to take part in the survey, a proxy person will be interviewed where possible. SHI variables include healthcare provision, healthcare costs and clinical outcomes. Questionnaire variables include information on PROs, lifestyle characteristics and socioeconomic status. We will use multiple regression models to estimate healthcare processes and outcomes including mortality and cost, investigate predictors, perform non-responder analysis and develop an algorithm to identify vulnerable subgroups.

ETHICS AND DISSEMINATION

The study was approved by the ethics committee of the Faculty of Medicine, Heinrich-Heine-University Düsseldorf (approval reference 6128R). All participants including proxies providing written and informed consent can withdraw from the study at any time. The study findings will be disseminated through scientific journals and public information.

TRIAL REGISTRATION NUMBER

DRKS00012554.

Predicting fracture risk in patients with chronic obstructive pulmonary disease: a UK-based population-based cohort study

OBJECTIVE

To assess the incidence of hip fracture and all major osteoporotic fractures (MOF) in patients with chronic obstructive pulmonary disease (COPD) compared with non-COPD patients and to evaluate the use and performance of fracture risk prediction tools in patients with COPD. To assess the prevalence and incidence of osteoporosis.

DESIGN

Population-based cohort study.

SETTING

UK General Practice health records from The Health Improvement Network database.

PARTICIPANTS

Patients with an incident COPD diagnosis from 2004 to 2015 and non-COPD patients matched by age, sex and general practice were studied.

OUTCOMES

Incidence of fracture (hip alone and all MOF); accuracy of fracture risk prediction tools in COPD; and prevalence and incidence of coded osteoporosis.

METHODS

Cox proportional hazards models were used to assess the incidence rates of osteoporosis, hip fracture and MOF (hip, proximal humerus, forearm and clinical vertebral fractures). The discriminatory accuracies (area under the receiver operating characteristic [ROC] curve) of fracture risk prediction tools (FRAX and QFracture) in COPD were assessed.

RESULTS

Patients with COPD (n=80 874) were at an increased risk of fracture (both hip alone and all MOF) compared with non-COPD patients (n=308 999), but this was largely mediated through oral corticosteroid use, body mass index and smoking. Retrospectively calculated ROC values for MOF in COPD were as follows: FRAX: 71.4% (95% CI 70.6% to 72.2%), QFracture: 61.4% (95% CI 60.5% to 62.3%) and for hip fracture alone, both 76.1% (95% CI 74.9% to 77.2%). Prevalence of coded osteoporosis was greater for patients (5.7%) compared with non-COPD patients (3.9%), p<0.001. The incidence of osteoporosis was increased in patients with COPD (n=73 084) compared with non-COPD patients (n=264 544) (adjusted hazard ratio, 1.13, 95% CI 1.05 to 1.22).

CONCLUSION

Patients with COPD are at an increased risk of fractures and osteoporosis. Despite this, there is no systematic assessment of fracture risk in clinical practice. Fracture risk tools identify those at high risk of fracture in patients with COPD.

Breakage in Two Points of a Short and Undersized "Affixus" Cephalomedullary Nail in a Very Active Elderly Female: A Case Report and Review of the Literature

Introduction

Trochanteric fractures of the femur are common in elderly individuals with osteoporosis. The use of cephalomedullary nails is increasing, and they are now the most commonly used fixation devices, especially for the treatment of unstable trochanteric fractures. The nail breakage is not the most common complication of intramedullary nailing. Many scientific papers report nail breakage in a specific location: through the lag screw hole, the nail shaft, or the distal locking hole.

Materials and Methods

We present a case of an 84-year-old patient treated with modular revision hip arthroplasty due to the breakage in two points of a cephalomedullary nail implanted 3 years earlier for a subtrochanteric fracture.

Results

After modular revision hip arthroplasty, the functional results and quality of life have been excellent.

Conclusions

As far as we could determine, this appears to be the first case of a breakage of a cephalomedullary nail in two points after nonunion in a very active elderly female.

Excess Mortality After Pelvic Fractures Among Older People

The study aimed to estimate excess mortality in patients aged 60 years or older up to 1 year after pelvic fracture compared with a population without pelvic fracture. In this retrospective population-based observational study, we use routine data from a large health insurance in Germany. For each patient with a first pelvic fracture between 2008 and 2010 (n = 5685 cases, 82% female, mean age 80 ± 9 years), about 34 individuals without pelvic fracture (n = 193,159 controls) were frequency matched by sex, age at index date, and index month. We estimated survival probabilities in the first year after the index date separated for cases (further stratified into inpatient/outpatient treated or minor/major pelvic fractures) and controls using Kaplan-Meier curves. Additionally, time-dependent hazard ratios (HRs) measuring excess mortality in 4-week intervals up to 52 weeks were estimated by fitting Cox regression models including adjustment for relevant confounders. Twenty-one percent of cases and 11% of controls died within 1 year. HRs (95% confidence intervals) decreased from 3.9 (3.5-4.5) within the first 4 weeks to 1.4 (1.1-1.9) within weeks 49 to 52 after the index date. After full adjustment, HRs lowered substantially (3.0 [2.6-3.4] and 1.0 [0.8-1.4]) but were still significantly increased up to week 32. Adjusted HRs in women were lower than in men: 2.8 (2.4-3.2) and 1.0 (0.7-1.4) versus 3.8 (2.9-5.0) and 1.2 (0.6-2.3). We found a clear excess mortality among older people in the first 8 months after pelvic fracture even after full adjustment. Excess mortality was higher among men in the beginning as well as for inpatient-treated persons. Absence of excess mortality was noticed for outpatient-treated persons within the first 3 months. When broken down into site-specific data, excess mortality was no longer significant for most pelvic fractures classified as minor. The only exception was fracture of pubis within the first 4 weeks. © 2017 American Society for Bone and Mineral Research.

External validation and comparison of two variants of the Elixhauser comorbidity measures for all-cause mortality

Assessing prevalent comorbidities is a common approach in health research for identifying clinical differences between individuals. The objective of this study was to validate and compare the predictive performance of two variants of the Elixhauser comorbidity measures (ECM) for inhospital mortality at index and at 1-year in the Cerner Health Facts® (HF) U.S. database. We estimated the prevalence of select comorbidities for individuals 18 to 89 years of age who received care at Cerner contributing health facilities between 2002 and 2011 using the AHRQ (version 3.7) and the Quan Enhanced ICD-9-CM ECMs. External validation of the ECMs was assessed with measures of discrimination [c-statistics], calibration [Hosmer–Lemeshow goodness-of-fit test, Brier Score, calibration curves], added predictive ability [Net Reclassification Improvement], and overall model performance [R²]. Of 3,273,298 patients with a mean age of 43.9 years and a female composition of 53.8%, 1.0% died during their index encounter and 1.5% were deceased at 1-year. Calibration measures were equivalent between the two ECMs. Calibration performance was acceptable when predicting inhospital mortality at index, although recalibration is recommended for predicting inhospital mortality at 1 year. Discrimination was marginally better with the Quan ECM compared the AHRQ ECM when predicting inhospital mortality at index (c_Quan = 0.887, 95% CI: 0.885–0.889 vs. c_AHRQ = 0.880, 95% CI: 0.878–0.882; p < .0001) and at 1-year (c_Quan = 0.884, 95% CI: 0.883–0.886 vs. c_AHRQ = 0.880, 95% CI: 0.878–0.881, p < .0001). Both the Quan and the AHRQ ECMs demonstrated excellent discrimination for inhospital mortality of all-causes in Cerner Health Facts®, a HIPAA compliant observational research and privacy-protected data warehouse. While differences in discrimination performance between the ECMs were statistically significant, they are not likely clinically meaningful.

The challenge of non-union in subtrochanteric fractures with breakage of intramedullary nail: evaluation of outcomes in surgery revision with angled blade plate and allograft bone strut

PURPOSE

Subtrochanteric fractures have a bimodal age distribution. They usually require open reduction and internal fixation. Closed reduction and intramedullary nail fixation rate are increased for this type of fracture. As a result, the hardware breakage and non-union rate is high among such patients. Our purpose is to evaluate the outcomes of the role of blade plate and bone strut allograft in the management of subtrochanteric non-union by femoral nailing.

MATERIALS AND METHODS

We reported a group of 22 patients with subtrochanteric non-union, associated with breakage of the intramedullary nail with medial femoral allograft bone and lateral blade plate and wire (PS) s; and a group of 13 patients with subtrochanteric non-union, associated with breakage of the intramedullary nail treated with lateral blade plate and screws (CG). The chosen criteria to evaluate the two group during the clinical and radiological follow-up were the quality of life, measured by The Short Form (12) Health Survey (SF-12), the hip function and quality of life related to it, measured by the Harris Hip Score (HHS), bone healing, measured by Radiographic Union Score (RUS) by XR and CT at 1 year after the surgery, and postoperative complications. The evaluation endpoint was set at 12 months.

RESULTS

The Bone healing measured by RUS occurred and also the full recovery before the first trauma measured by SF-12 and HHS are better in PS group. We only had three unimportant complications in PS while four breakage hardware in CG.

CONCLUSION

We conclude that in complicated non-unions, the use of blade plate and bone strut allograft has a definite positive role in the management of such cases.

Comparison of pharmacy-based and diagnosis-based comorbidity measures from medical administrative data

PURPOSE

Health status is sometimes quantified by chronic condition (CC) scores calculated from medical administrative data. We sought to modify two pharmacy-based comorbidity measures and compare their performance in predicting hospitalization and/or death. The reference was a diagnosis-based score.

METHODS

One of the two measures applied an updated approach linking specific ATC codes of dispensed drugs to 22 CCs; the other used a list of 37 drug categories, without linking them to specific CCs. Using logistic regressions that took repeated measures into account and hospitalization and/or death the following year as the outcome, we assigned weights to each CC/drug category. Comorbidity scores were calculated as the weighted sum of the 22 CCs/37 drug categories. We compared the performance of both measures in predicting hospitalization and/or death with that of a diagnosis-based score based on 30 groups of long-term illnesses (LTIs), a status granted in France to exempt beneficiaries with chronic diseases from copayments. We assessed the predictive performance of the scores with the quasi-likelihood under the independence model criterion (QIC), the c statistic and the Brier score.

RESULTS

The two pharmacy-based scores performed better than the LTI score, with lower QIC and Brier scores and higher c statistics. Their predictive performance was very similar.

CONCLUSIONS

While there is no clear consensus or recommendations about the optimal choice of comorbidity measure, both pharmacy-based scores may be useful for limiting confounding in observational studies among general populations of adults from health insurance databases. Copyright © 2016 John Wiley & Sons, Ltd.

Influence of Using Different Databases and 'Look Back' Intervals to Define Comorbidity Profiles for Patients with Newly Diagnosed Hypertension: Implications for Health Services Researchers

OBJECTIVE

To determine the data sources and 'look back' intervals to define comorbidities.

DATA SOURCES

Hospital discharge abstracts database (DAD), physician claims, population registry and death registry from April 1, 1994 to March 31, 2010 in Alberta, Canada.

STUDY DESIGN

Newly-diagnosed hypertension cases from 1997 to 2008 fiscal years were identified and followed up to 12 years. We defined comorbidities using data sources and duration of retrospective observation (6 months, 1 year, 2 years, and 3 years). The C-statistics for logistic regression and concordance index (CI) for Cox model of mortality and cardiovascular disease hospitalization were used to evaluate discrimination performance for each approach of defining comorbidities.

PRINCIPAL FINDINGS

The comorbidities prevalence became higher with a longer duration. Using DAD alone underestimated the prevalence by about 75%, compared to using both DAD and physician claims. The C-statistic and CI were highest when both DAD and physician claims were used, and model performance improved when observation duration increased from 6 months to one year or longer.

CONCLUSION

The comorbidities prevalence is greatly impacted by the data source and duration of retrospective observation. A combination of DAD and physicians claims with at least one year observation duration improves predictions for cardiovascular disease and one-year mortality outcome model performance.

Post-acute pathways among hip fracture patients: a system-level analysis

BACKGROUND

Hip fractures among older adults are one of the leading causes of hospitalization and result in significant morbidity, mortality, and health care use. Guidelines suggest that rehabilitation after surgery is imperative to return patients to pre-morbid function. However, post-acute care (which encompasses rehabilitation) is currently delivered in a multitude of settings, and there is a lack of evidence with regards to which hip fracture patients should use which post-acute settings. The purpose of this study is to describe hip fracture patient characteristics and the most common post-acute pathways within a 1-year episode of care, and to examine how these vary regionally within a health system.

METHODS

This study took place in the province of Ontario, Canada, which has 14 health regions and universal health coverage for all residents. Administrative health databases were used for analyses. Community-dwelling patients aged 66 and over admitted to an acute care hospital for hip fracture between April 2008 and March 2013 were identified. Patients' post-acute destinations within each region were retrieved by linking patients' records within various institutional databases using a unique encoded identifier. Post-acute pathways were then characterized by determining when each patient went to each post-acute destination within one year post-discharge from acute care. Differences in patient characteristics between regions were detected using standardized differences and p-values.

RESULTS

Thirty-six thousand twenty nine hip fracture patients were included. The study cohort was 71.9 % female with a mean age of 82.9 (±7.5SD). There was significant variation between regions with respect to the immediate post-acute discharge destination: four regions discharged a substantially higher proportion of their patients to inpatient rehabilitation compared to all others. However, the majority of patient characteristics between those four regions and all other regions did not significantly differ. There were 49 unique post-acute pathways taken by patients, with the largest proportion of patients admitted to either community-based or short-term institutionalized rehabilitation, regardless of region.

CONCLUSIONS

The observation that similar hip fracture patients are discharged to different post-acute settings calls into question both the appropriateness of care delivered in the post-acute period and health system expenditures. As policy makers continue to develop performance-based funding models to increase accountability of institutions in the provision of quality care to hip fracture patients, ensuring patients receive appropriate rehabilitative care is a priority for health system planning.

Factors associated with the health care cost in older Australian women with arthritis: an application of the Andersen's Behavioural Model of Health Services Use

OBJECTIVE

Factors associated with the utilisation of health care have not been rigorously examined in people with arthritis. The objective of this study was to examine the determinants of health care utilisation and costs in older women with arthritis using the Andersen's behavioural model as a framework.

STUDY DESIGN

Longitudinal cohort study.

METHODS

Participants of Surveys 3 to 5 of the Australian Longitudinal Study on Women's Health who reported arthritis were included in the study. Information about health care utilisation and unit prices were based on linked Medicare Australia data, which included prescription medicines and health services. Total health care costs of participants with arthritis were measured for the years 2002 to 2003, 2005 to 2006, and 2008 to 2009, which corresponded to the survey years. Potential explanatory variables of the health care cost and other characteristics of the participants were collected from the health surveys. Explanatory variables were grouped into predisposing characteristics, enabling factors and need variables conforming to the Andersen's Behavioural Model of Health Services Use. Longitudinal data analysis was conducted using generalized estimating equations.

RESULTS

A total of 5834 observations were included for the three periods. Regression analysis results show that higher health care cost in older Australian women with arthritis was significantly associated with residing in an urban area, having supplementary health insurance coverage, more comorbid conditions, using complementary and alternative medicine, and worse physical functioning. It was also found that predisposing characteristics (such as the area of residence) and enabling factors (such as health insurance coverage) accounted for more variance in the health care cost than need variables (such as comorbid conditions).

CONCLUSION

These results may indicate an inefficient and unfair allocation of subsidised health care among older Australian women with arthritis, where individuals with less enabling resources and more socio-economic disadvantages have a lower level of health care utilisation. Future research may focus on evaluating the effectiveness of policies designed to reduce excessive out-of-pocket costs and to improve equity in health care access in the older population.

Why Summary Comorbidity Measures Such As the Charlson Comorbidity Index and Elixhauser Score Work

BACKGROUND

Comorbidity adjustment is an important component of health services research and clinical prognosis. When adjusting for comorbidities in statistical models, researchers can include comorbidities individually or through the use of summary measures such as the Charlson Comorbidity Index or Elixhauser score. We examined the conditions under which individual versus summary measures are most appropriate.

METHODS

We provide an analytic proof of the utility of comorbidity summary measures when used in place of individual comorbidities. We compared the use of the Charlson and Elixhauser scores versus individual comorbidities in prognostic models using a SEER-Medicare data example. We examined the ability of summary comorbidity measures to adjust for confounding using simulations.

RESULTS

We devised a mathematical proof that found that the comorbidity summary measures are appropriate prognostic or adjustment mechanisms in survival analyses. Once one knows the comorbidity score, no other information about the comorbidity variables used to create the score is generally needed. Our data example and simulations largely confirmed this finding.

CONCLUSIONS

Summary comorbidity measures, such as the Charlson Comorbidity Index and Elixhauser scores, are commonly used for clinical prognosis and comorbidity adjustment. We have provided a theoretical justification that validates the use of such scores under many conditions. Our simulations generally confirm the utility of the summary comorbidity measures as substitutes for use of the individual comorbidity variables in health services research. One caveat is that a summary measure may only be as good as the variables used to create it.

Standard Comorbidity Measures Do Not Predict Patient-reported Outcomes 1 Year After Total Hip Arthroplasty

BACKGROUND

Comorbidities influence surgical outcomes and therefore need to be included in risk adjustment when predicting patient-reported outcomes. However, there is no consensus on how best to use the available data about comorbidities in registry-based predictive models.

QUESTIONS/PURPOSES

The purposes of this study were (1) to determine whether the International Classification of Diseases, 10(th) Revision (ICD-10)-based comorbidity measures (Elixhauser, Charlson, and Royal College of Surgeons Charlson) offer added value in explaining patients' health-related quality of life (HRQoL), pain, and satisfaction after total hip arthroplasty (THA) when preoperative HRQoL, pain, and Charnley classification were known; and (2) to determine the ideal timeframe for recording the different diagnoses that serves as the basis for comorbidity measure calculations.

METHODS

There were 22,263 patients who had undergone THA with complete pre- and postoperative patient-reported outcome measures (PROMs) included in the Swedish Hip Arthroplasty Register between 2002 and 2007. The three comorbidity indices were calculated with ICD-10 codes identified in the Swedish National Patient Register from 1, 2, and 5 years before the patient underwent THA. The impact of the comorbidity indices on the PROM scores (EQ-5D index, EQ visual analog scale [VAS], pain VAS, and satisfaction VAS) was modeled with linear regression where the 1-year patient postoperative outcome score was the dependent variable and independent variables included patient preoperative Charnley classification, preoperative HRQoL and pain, and comorbidity indices. The partial R(2) value indicated how much each variable uniquely contributed to the predictive capacity of the model.

RESULTS

The ICD-10-based comorbidity measures added little predictive value to the models for each of the outcomes of interest (EQ-5D index, EQ VAS, pain VAS, and satisfaction VAS). Charnley classification and the preoperative scores were the strongest predictors of both measures of postoperative HRQoL, of postoperative pain, and postoperative satisfaction with outcomes from surgery. Of all the predictors considered, only the Charnley classification was associated with all outcomes, irrespective of the timeframe considered. For each of the outcomes considered, there was a gradual increase in the models' predictive power with the length of the timeframe considered for calculating the comorbidity measures.

CONCLUSIONS

For predicting outcomes 1 year after THA, we found that there was no added value in ICD-10-based comorbidity measures if patient Charnley classification and preoperative HRQoL and pain measures were known.

LEVEL OF EVIDENCE

Level III, therapeutic study.

Factors associated with higher healthcare costs in individuals living with arthritis: evidence from the quantile regression approach

OBJECTIVE

To examine the factors associated with higher healthcare cost in women with arthritis, using generalized linear models (GLMs) and quantile regression (QR).

METHODS

This is a cross-sectional healthcare cost study of individuals with arthritis that focused on older Australian women. Cost data were drawn from the Medicare Australia datasets.

RESULTS

GLM results show that healthcare cost was significantly associated with various socio-demographic and health factors. Although QR analysis results show the same direction of association between these factors and healthcare cost as in the GLMs, they indicate progressively increased effect sizes at the 50th, 75th, 90th and 95th percentiles.

CONCLUSION

Findings suggest traditional regression models such as GLMs that assume a single rate of change to accurately describe the relationships between explanatory variables and healthcare costs across the entire distribution of cost can produce biased results. QR should be considered in future healthcare cost research.

Which risk-adjustment index performs better in predicting 30-day mortality? A systematic review and meta-analysis

RATIONALE, AIMS AND OBJECTIVES

Individual comparisons of the performance of risk-adjustment indices have been widely conducted. Few reviews have been conducted to summarize the performance of different risk-adjustment indices. A 30-day mortality rate is widely used to evaluate the quality of care in hospitals by federal agencies like the Centers for Medicare and Medicaid Services. This study examined relative performance of risk-adjustment indices that predict 30-day mortality.

METHODS

Databases including Medline, PubMed and PsycINFO were searched for studies that compared risk-adjustment indices. The search protocol included comparative studies in which the performance of risk-adjustment indices were compared across any defined cohort to compare 30-day mortality, including mortality within 30 days and intensive care unit mortality, which lasts less than 30 days. Data were extracted using a structured form and abstract data included author and publication year, population studied (including location, sample size, study time period), comparison indices, outcome studied, results and conclusions from the results. A meta-analytical approach was used to summarize all the studies. Scaled ranking score was used to estimate the relative superiority of any given risk-adjustment indices. A hypergeometric test was carried out to evaluate the performance of risk-adjustment measures.

RESULTS

Out of 2805 studies identified, 23 studies met the eligibility criteria. Main risk-adjustment indices used for comparison included Acute Physiology and Chronic Health Evaluation, Sequential Organ Failure Assessment score, Charlson co-morbidity index, Model for End-Stage Liver Disease score and Simplified Acute Physiology Score (SAPS). Based on scaled ranking score, SAPS performed best (score 0.510) among all the risk-adjustment indices. However, based on hypergeometric test, the five measures performed equally well.

CONCLUSIONS

Although all the selected risk-adjustment indices perform equally well, SAPS seems better than other indices for short-term mortality based on scaled ranking score.

Identifying a standard set of outcome parameters for the evaluation of orthogeriatric co-management for hip fractures

BACKGROUND AND PURPOSE

Osteoporotic fractures are an increasing problem in the world due to the ageing of the population. Different models of orthogeriatric co-management are currently in use worldwide. These models differ for instance by the health-care professional who has the responsibility for care in the acute and early rehabilitation phases. There is no international consensus regarding the best model of care and which outcome parameters should be used to evaluate these models. The goal of this project was to identify which outcome parameters and assessment tools should be used to measure and compare outcome changes that can be made by the implementation of orthogeriatric co-management models and to develop recommendations about how and when these outcome parameters should be measured. It was not the purpose of this study to describe items that might have an impact on the outcome but cannot be influenced such as age, co-morbidities and cognitive impairment at admission.

METHODS

Based on a review of the literature on existing orthogeriatric co-management evaluation studies, 14 outcome parameters were evaluated and discussed in a 2-day meeting with panellists. These panellists were selected based on research and/or clinical expertise in hip fracture management and a common interest in measuring outcome in hip fracture care.

RESULTS

We defined 12 objective and subjective outcome parameters and how they should be measured: mortality, length of stay, time to surgery, complications, re-admission rate, mobility, quality of life, pain, activities of daily living, medication use, place of residence and costs. We could not recommend an appropriate tool to measure patients' satisfaction and falls. We defined the time points at which these outcome parameters should be collected to be at admission and discharge, 30 days, 90 days and 1 year after admission.

CONCLUSION

Twelve objective and patient-reported outcome parameters were selected to form a standard set for the measurement of influenceable outcome of patients treated in different models of orthogeriatric co-managed care.

Clostridium difficile colitis in patients undergoing lower-extremity arthroplasty: rare infection with major impact

BACKGROUND

The prevalence of Clostridium difficile colitis is reportedly increasing in surgical patients and can negatively impact their outcome. However, as yet there are no clear estimates of the C difficile infection colitis rate and its consequences among patients undergoing total joint arthroplasty (TJA).

QUESTIONS/PURPOSES

We asked: (1) What is the rate of C difficile colitis in TJA patients? (2) What are the risk factors of C difficile colitis in these patients? And (3) what is the effect of C difficile colitis on length of stay, in-hospital mortality, and estimated total charges?

METHODS

Using ICD-9-CM diagnosis and procedure codes, we queried the Nationwide Inpatient Sample database for patients undergoing TJA for the years 2002 to 2010. Demographic data, comorbidities, occurrence of C difficile colitis, length of hospital stay, mortality, and hospital charges were extracted. Logistic regression was performed to identify predictors of C difficile colitis and its impact on in-hospital mortality.

RESULTS

The incidence of C difficile remained less than 0.6% during the study period. Revision TJAs (odds ratio=6.9 and 4.4 for hip and knee, respectively) and number of comorbidities (odds ratio=1.5) increased risk of C difficile colitis. C difficile increased length of hospital stay by a week, hospital charges by USD 40,000, and in-hospital mortality to 4.66% from 0.24%.

CONCLUSIONS

Using lower and fewer doses of antibiotics in revision TJAs and among patients with many comorbidities may diminish risk of C difficile colitis and its consequent mortality.

LEVEL OF EVIDENCE

Level II, prognostic study. See Instructions for Authors for a complete description of levels of evidence.

Systematic review of comorbidity indices for administrative data

BACKGROUND

Adjustment for comorbidities is common in performance benchmarking and risk prediction. Despite the exponential upsurge in the number of articles citing or comparing Charlson, Elixhauser, and their variants, no systematic review has been conducted on studies comparing comorbidity measures in use with administrative data. We present a systematic review of these multiple comparison studies and introduce a new meta-analytical approach to identify the best performing comorbidity measures/indices for short-term (inpatient + ≤ 30 d) and long-term (outpatient+>30 d) mortality.

METHODS

Articles up to March 18, 2011 were searched based on our predefined terms. The bibliography of the chosen articles and the relevant reviews were also searched and reviewed. Multiple comparisons between comorbidity measures/indices were split into all possible pairs. We used the hypergeometric test and confidence intervals for proportions to identify the comparators with significantly superior/inferior performance for short-term and long-term mortality. In addition, useful information such as the influence of lookback periods was extracted and reported.

RESULTS

Out of 1312 retrieved articles, 54 articles were eligible. The Deyo variant of Charlson was the most commonly referred comparator followed by the Elixhauser measure. Compared with baseline variables such as age and sex, comorbidity adjustment methods seem to better predict long-term than short-term mortality and Elixhauser seems to be the best predictor for this outcome. For short-term mortality, however, recalibration giving empirical weights seems more important than the choice of comorbidity measure.

CONCLUSIONS

The performance of a given comorbidity measure depends on the patient group and outcome. In general, the Elixhauser index seems the best so far, particularly for mortality beyond 30 days, although several newer, more inclusive measures are promising.

[Comorbidity from the patient perspective - does it work? Validity of a questionnaire on self-estimation of comorbidity (SCQ-D)]

To minimize the medical effort for the measurement of comorbidity, which is a relevant factor for various outcome measures, the Self-Administered Comorbidity Questionnaire (SCQ) for patient self-evaluation has been developed. After successfully testing the psychometric characteristics and content of the original English version a validation of the German translation (SCQ-D) has so far been lacking. A total of 218 patients with gonarthrosis and coxarthrosis (average age 71.5 years) were included in the survey. A questionnaire for doctors as well as patients was used to collect data at five different measurement times (postoperative, beginning and end of rehabilitation as well as 4 months and 1 year postoperatively). To evaluate the matching of comorbidities according to the SCQ-D and the Charlson Comorbidity Index (CCI), aggregate indices for "problems" and "treatment" as well as correlation and kappa coefficients were calculated. The assessment of predictive validity in terms of treatment outcome was operationalized using the WOMAC and the postoperative 1 year hospitalization by applying multilevel models. The patient self-assessment using the SCQ-D correlated well with the physician assessment using CCI in terms of aggregate indices of 13 given disease groups with r = 0.49 (problems) and r = 0.48 (treatment). However, the results showed significant differences for certain diseases in the conclusions. The comorbidity measured by the SCQ-D proved to be a valid predictor of the hospitalization and the treatment outcome. Concerning the need for resource efficient data collection especially in large sample studies, the SCQ-D is a useful patient self-administered instrument to assess the type and extent of comorbidities.