Comparison of comorbidity classification methods for predicting outcomes in a population-based cohort of adults with human immunodeficiency virus infection

A Frailty Index to Predict Mortality, Resource Utilization and Costs in Patients Undergoing Coronary Artery Bypass Graft Surgery in Ontario

Background

People living with frailty are vulnerable to poor outcomes and incur higher health care costs after coronary artery bypass graft (CABG) surgery. Frailty-defining instruments for population-level research in the CABG setting have not been established. The objectives of the study were to develop a preoperative frailty index for CABG (pFI-C) surgery using Ontario administrative data; assess pFI-C suitability in predicting clinical and economic outcomes; and compare pFI-C predictive capabilities with other indices.

Methods

A retrospective cohort study was conducted using health administrative data of 50,682 CABG patients. The pFI-C comprised 27 frailty-related health deficits. Associations between index scores and mortality, resource use and health care costs (2022 Canadian dollars [CAD]) were assessed using multivariable regression models. Capabilities of the pFI-C in predicting mortality were evaluated using concordance statistics; goodness of fit of the models was assessed using Akakie Information Criterion.

Results

As assessed by the pFI-C, 22% of the cohort lived with frailty. The pFI-C score was strongly associated with mortality per 10% increase (odds ratio [OR], 3.04; 95% confidence interval [CI], [2.83,3.27]), and was significantly associated with resource utilization and costs. The predictive performances of the pFI-C, Charlson, and Elixhauser indices and Johns Hopkins Aggregated Diagnostic Groups were similar, and mortality models containing the pFI-C had a concordance (C)-statistic of 0.784. Cost models containing the pFI-C showed the best fit.

Conclusions

The pFI-C is predictive of mortality and associated with resource utilization and costs during the year following CABG. This index could aid in identifying a subgroup of high-risk CABG patients who could benefit from targeted perioperative health care interventions.

Prevalence and predictors for being unscreened for diabetic retinopathy: a population-based study over a decade

OBJECTIVE

To determine the population-level predictors for being unscreened for diabetic retinopathy (DR) among individuals with diabetes in a developed country.

DESIGN

A retrospective population-based repeated-cross-sectional study.

PARTICIPANTS

All individuals with diabetes (types 1 and 2) aged ≥20 years in the universal health care system in Ontario were identified in the 2011-2013 and 2017-2019 time periods.

METHODS

The Mantel-Haenszel test was used for the relative risk (RR) comparison of subcategories stratified by the 2 cross-sectional time periods.

RESULTS

A total of 1 145 645 and 1 346 578 individuals with diabetes were identified in 2011-2013 and 2017-2019, respectively. The proportion of patients unscreened for DR declined very slightly from 35% (n = 405 967) in 2011-2013 to 34% (n = 455 027) in 2017-2019 of the population with diabetes (RR = 0.967; 95% CI, 0.964-0.9693; p < 0.0001). Young adults aged 20-39 years of age had the highest proportion of unscreened patients (62% and 58% in 2011-2013 and 2017-2019, respectively). Additionally, those who had a lower income quintile (RR = 1.039; 95% CI, 1.036-1.044; p < 0.0001), were recent immigrants (RR = 1.286; 95% CI, 1.280-1.293; p < 0.0001), lived in urban areas (RR = 1.149; 95% CI, 1.145-1.154; p < 0.0001), had a mental health history (RR = 1.117; 95% CI, 1.112-1.122; p < 0.0001), or lacked a connection to a primary care provider (RR = 1.656; 95% CI, 1.644-1.668; p < 0.0001) had a higher risk of being unscreened.

CONCLUSIONS

This population-based study suggests that over 1 decade, 33% of individuals with diabetes are unscreened for DR, and young age, low income, immigration, residing in a large city, mental health illness, and no primary care access are the main predictors.

Patient Service Utilization Among Individuals with Co-occurring Disorders: A Comparison of Two Models of Care Coordination

Healthcare systems have increasingly adopted integrated care models with demonstrated effectiveness. However, few studies examine integrated care for individuals with co-morbid mental illness and medical conditions. This quasi-experimental study compared service use for two integrated care models for patients with co-occurring conditions. We used hierarchical negative binomial and logistic regressions with random effects to test the relationship between integration and service use. Patients treated at co-located agencies had significantly higher odds of inpatient hospitalization compared to those in fully integrated settings. Additionally, some comorbidities had significantly different levels of service use. Patients at co-located agencies had more outpatient and emergency visits, but was not statistically significant. Our findings provide evidence that the model of care may impact service use for patients experiencing co-occurring conditions, however, variations in service use for specific co-morbid conditions highlight the need to examine the specific needs and characteristics of this population.

Evaluation of risk adjustment performance of diagnosis-based and medication-based comorbidity indices in patients with chronic obstructive pulmonary disease

Objectives

This study assessed risk adjustment performance of six comorbidity indices in two categories of comorbidity measures: diagnosis-based comorbidity indices and medication-based ones in patients with chronic obstructive pulmonary disease (COPD).

Methods

This was a population–based retrospective cohort study. Data used in this study were sourced from the Taiwan National Health Insurance Research Database. The study population comprised all patients who were hospitalized due to COPD for the first time in the target year of 2012. Each qualified patient was individually followed for one year starting from the index date to assess two outcomes of interest, medical expenditures within one year after discharge and in-hospital mortality of patients. To assess how well the added comorbidity measures would improve the fitted model, we calculated the log-likelihood ratio statistic G2. Subsequently, we compared risk adjustment performance of the comorbidity indices by using the Harrell c-statistic measure derived from multiple logistic regression models.

Results

Analytical results demonstrated that that comorbidity measures were significant predictors of medical expenditures and mortality of COPD patients. Specifically, in the category of diagnosis-based comorbidity indices the Elixhauser index was superior to other indices, while the RxRisk-V index was a stronger predictor in the framework of medication-based codes, for gauging both medical expenditures and in-hospital mortality by utilizing information from the index hospitalization only as well as the index and prior hospitalizations.

Conclusions

In conclusion, this work has ascertained that comorbidity indices are significant predictors of medical expenditures and mortality of COPD patients. Based on the study findings, we propose that when designing the payment schemes for patients with chronic diseases, the health authority should make adjustments in accordance with the burden of health care caused by comorbid conditions.

Charlson Comorbidity Index: A Critical Review of Clinimetric Properties

The present critical review was conducted to evaluate the clinimetric properties of the Charlson Comorbidity Index (CCI), an assessment tool designed specifically to predict long-term mortality, with regard to its reliability, concurrent validity, sensitivity, incremental and predictive validity. The original version of the CCI has been adapted for use with different sources of data, ICD-9 and ICD-10 codes. The inter-rater reliability of the CCI was found to be excellent, with extremely high agreement between self-report and medical charts. The CCI has also been shown either to have concurrent validity with a number of other prognostic scales or to result in concordant predictions. Importantly, the clinimetric sensitivity of the CCI has been demonstrated in a variety of medical conditions, with stepwise increases in the CCI associated with stepwise increases in mortality. The CCI is also characterized by the clinimetric property of incremental validity, whereby adding the CCI to other measures increases the overall predictive accuracy. It has been shown to predict long-term mortality in different clinical populations, including medical, surgical, intensive care unit (ICU), trauma, and cancer patients. It may also predict in-hospital mortality, although in some instances, such as ICU or trauma patients, the CCI did not perform as well as other instruments designed specifically for that purpose. The CCI thus appears to be clinically useful not only to provide a valid assessment of the patient's unique clinical situation, but also to demarcate major diagnostic and prognostic differences among subgroups of patients sharing the same medical diagnosis.

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.

Comparing Five Comorbidity Indices to Predict Mortality in Chronic Kidney Disease: A Retrospective Cohort Study

Background:

Several different indices summarize patient comorbidity using health care data. An accurate index can be used to describe the risk profile of patients, and as an adjustment factor in analyses. How well these indices perform in persons with chronic kidney disease (CKD) is not well known.

Objective:

Assess the performance of 5 comorbidity indices at predicting mortality in 3 different patient groups with CKD: incident kidney transplant recipients, maintenance dialysis patients, and individuals with low estimated glomerular filtration rate (eGFR).

Design:

Population-based retrospective cohort study.

Setting:

Ontario, Canada, between 2004 and 2014.

Patients:

Individuals at the time they first received a kidney transplant, received maintenance dialysis, or were confirmed to have an eGFR less than 45 mL/min per 1.73m².

Measurements:

Five comorbidity indices: Charlson comorbidity index, end-stage renal disease-modified Charlson comorbidity index, Johns Hopkins’ Aggregated Diagnosis Groups score, Elixhauser score, and Wright-Khan index. Our primary outcome was 1-year all-cause mortality.

Methods:

Comorbidity indices were estimated using information in the prior 2 years. Each group was randomly divided 100 times into derivation and validation samples. Model discrimination was assessed using median c-statistics from logistic regression models, and calibration was evaluated graphically.

Results:

We identified 4111 kidney transplant recipients, 23 897 individuals receiving maintenance dialysis, and 181 425 individuals with a low eGFR. Within 1 year, 108 (2.6%), 4179 (17.5%), and 17 898 (9.9%) in each group had died, respectively. In the validation sample, model discrimination was inadequate with median c-statistics less than 0.7 for all 5 comorbidity indices for all 3 groups. Calibration was also poor for all models.

Limitations:

The study used administrative health care data so there is the potential for misclassification. Indices were modeled as continuous scores as opposed to indicators for individual conditions to limit overfitting.

Conclusions:

Existing comorbidity indices do not accurately predict 1-year mortality in patients with CKD. Current indices could be modified with additional risk factors to improve their performance in CKD, or a new index could be developed for this population.

Postoperative Rehabilitation May Reduce the Risk of Readmission After Groin Hernia Repair

Thirty-day readmission after surgery has been proposed as a quality-of-care indicator. We explored the effect of postoperative rehabilitation on readmission risk after groin hernia repair. We used the French National Discharge Database to identify all index hospitalizations for groin hernia repair in 2011. Readmissions within 30 days of discharge were clinically classified in terms of their relationship to the index stay. We used logistic regression to adjust the risk of readmission for patient, procedure and hospital factors. Among 122,952 index hospitalizations for inguinal hernia repair, 3,357 (2.7%) related 30-day readmissions were recorded. Reiterated analyses indicated that readmission risk was consistently associated with patient complexity: age (per year after 60 years, OR 1.03, 95% CI 1.02-1.03, P < 0.001), hospitalization within the previous year (OR 1.56, 95% CI 1.44-1.69, P < 0.001), and increasing severity and combination of co-morbidities. Postoperative rehabilitation was identified as a protective factor (OR 0.56, 95% CI 0.46-0.69, P < 0.001). Older patients and those with greater comorbidity are at elevated risk of readmission after inguinal hernia repair. Postoperative rehabilitation may reduce this risk. Further studies are warranted to confirm the protective effect of postoperative rehabilitation.

Returns to specialization: Evidence from the outpatient surgery market

Technological changes in medicine have created new opportunities to provide surgical care in lower cost, specialized facilities. This paper examines patient outcomes in ambulatory surgery centers (ASCs), which were developed as a low-cost alternative to outpatient surgery in hospitals. Because we are concerned that selection into ASCs may bias estimates of facility quality, we use predicted changes in federally set Medicare facility payment rates as an instrument for ASC utilization to estimate the effect of location of treatment on patient outcomes. We find that patients treated in an ASC are less likely to be admitted to a hospital or visit an emergency room a short time after outpatient surgery. The findings in this paper indicate that factors other than patient and physician heterogeneity contribute to the observed returns to specialization in the ASC market.

Improving medication safety: Development and impact of a multivariate model-based strategy to target high-risk patients

BACKGROUND

Preventive strategies to reduce clinically significant medication errors (MEs), such as medication review, are often limited by human resources. Identifying high-risk patients to allow for appropriate resource allocation is of the utmost importance. To this end, we developed a predictive model to identify high-risk patients and assessed its impact on clinical decision-making.

METHODS

From March 1st to April 31st 2014, we conducted a prospective cohort study on adult inpatients of a 1,644-bed University Hospital Centre. After a clinical evaluation of identified MEs, we fitted and internally validated a multivariate logistic model predicting their occurrence. Through 5,000 simulated randomized controlled trials, we compared two clinical decision pathways for intervention: one supported by our model and one based on the criterion of age.

RESULTS

Among 1,408 patients, 365 (25.9%) experienced at least one clinically significant ME. Eleven variables were identified using multivariable logistic regression and used to build a predictive model which demonstrated fair performance (c-statistic: 0.72). Major predictors were age and number of prescribed drugs. When compared with a decision to treat based on the criterion of age, our model enhanced the interception of potential adverse drug events by 17.5%, with a number needed to treat of 6 patients.

CONCLUSION

We developed and tested a model predicting the occurrence of clinically significant MEs. Preliminary results suggest that its implementation into clinical practice could be used to focus interventions on high-risk patients. This must be confirmed on an independent set of patients and evaluated through a real clinical impact study.

An audit of referral and treatment patterns of high-risk prostate cancer patients in Alberta

INTRODUCTION

We aimed to determine the impact of clinical practice guidelines (CPG) on rates of radiation oncologist (RO) referral, androgen-deprivation therapy (ADT), radiation therapy (RT), and radical prostatectomy (RP) in patients with high-risk prostate cancer (HR-PCa).

METHODS

All men >18 years, diagnosed with PCa in 2005 and 2012 were identified from the Alberta Cancer Registry. Patient age, aggregated clinical risk group (ACRG) score, Gleason score (GS), pre-treatment prostate-specific antigen (PSA), RO referral, and treatment received were extracted from electronic medical records. Logistic regression modelling was used to examine associations between RO referral rates and relevant factors.

RESULTS

HR-PCa was diagnosed in 261 of 1792 patients in 2005 and 435 of 2148 in 2012. Median age and ACRG scores were similar in both years (p>0.05). The rate of patients with PSA >20 were 67% and 57% in 2005 and 2012, respectively (p=0.004). GS ≤6 was found in 13% vs. 5% of patients, GS 7 in 27% vs. 24%, and GS ≥8 in 59% vs. 71% in 2005 and 2012, respectively (p<0.001). In 2005, RO referral rate was 68% compared to 56% in 2012 (p=0.001), use of RT + ADT was 53% compared to 32% (p<0.001), and RP rate was 9% vs. 17% (p=0.002). On regression analysis, older age, 2012 year of diagnosis and higher PSA were associated with decreased RO referral rates (odds ratios [OR] 0.49, 95% confidence interval [CI] 0.39-0.61; OR 0.51, 95% CI 0.34-0.76; and OR 0.64, 95% CI 0.39-0.61), respectively [p<0.001]).

CONCLUSIONS

Since CPG creation in 2005, RO referral rates and ADT + RT use declined and RP rates increased, which demonstrates a need to improve adherence to CPG in the HR-PCa population.

Maternal placental syndromes among women living with HIV in Ontario: a population-based study

BACKGROUND

Maternal placental syndromes are associated with adverse fetal outcomes and maternal cardiovascular disease. However, whether HIV infection increases the risk of maternal placental syndromes is unknown. Our objective was to compare the risk of maternal placental syndromes between women living with and without HIV infection in Ontario.

METHODS

We conducted a population-based study using health administrative data from Ontario. We identified all pregnancies resulting in a live birth between Apr. 1, 2002, and Mar. 31, 2011; we identified women living with HIV using a validated case-finding algorithm. Our primary composite outcome was maternal placental syndromes, defined as a diagnosis of preeclampsia, eclampsia, placental abruption or placental infarction. We used generalized estimating equations with a logit link function to derive adjusted odds ratios (AORs) and 95% confidence intervals (CI) for the association between HIV infection and maternal placental syndromes.

RESULTS

Data from 1 132 871 pregnancies were available for analysis; 634 (0.06%) of the pregnancies were in women living with HIV. After multivariable adjustment, we found no difference in the risk of maternal placental syndromes between women living with HIV and those without HIV infection (5.8% v. 5.6%; AOR 0.85 [95% CI 0.59-1.21]). An increased risk of maternal placental syndromes was associated with pre-existing diabetes (AOR 1.47 [95% CI 1.39-1.54]), pre-existing hypertension (AOR 4.28 [95% CI 4.15-4.42]) and chronic kidney disease (AOR 1.83 [95% CI 1.61-2.08]).

INTERPRETATION

Women with HIV are not at increased risk of maternal placental syndromes. Our results underscore the importance of optimizing the management of comorbid illness associated with maternal placental syndromes during the prenatal period for all women, irrespective of HIV status.

Outcomes in stage I non-small cell lung cancer following the introduction of stereotactic body radiotherapy in Alberta - A population-based study

PURPOSE

To review outcomes of patients with stage I non-small cell lung cancer (NSCLC) following the introduction of stereotactic body radiation therapy (SBRT).

METHODS

SBRT cases were linked to the cancer registry database along with clinical, treatment and health service parameters for n=2146 cases of stage I NSCLC diagnosed between 2005 and 2011. The pre-diagnosis Aggregated Clinical Risk Grouping score (ACRG3) was used as a proxy for pre-treatment patient comorbidity. A Cox regression model and the concordance statistic (C-statistic) were used to examine variables predicted for overall survival (OS).

RESULTS

The SBRT utilization rate increased annually with superior OS to conventional RT (median survival [MS] of 39.4 VS. 23.5months, P<0.001) despite higher ACRG3 scores. Surgical patients were younger, had lower ACRG3, achieving MS of 69.6months. Regression analysis indicated both Surgery (hazard ratio [HR]=0.23, 95% CI: 0.18-0.28) and SBRT (HR=0.33, 95% CI: 0.21-0.51) remained most strongly associated with OS. ACRG3 (HR=0.79, P<0.001) and age (HR=0.83, P=0.03) were independently associated with OS. The OS model was associated with the C-statistic at 0.86, 95% CI: 0.81-0.90.

CONCLUSION

In stage I NSCLC patients treated with surgery have the best survival. SBRT demonstrates improved OS compared to conventional RT. C-statistic result demonstrates discrimination of treatment selection factors on OS.