Background Universal health care systems seek to ensure accessto care on the basis of need rather than income and to improvethe health status of all citizens. We examined the performanceof the Canadian health system with respect to these goals inthe province of Ontario by assessing the effects of neighborhoodincome on access to invasive cardiac procedures and on mortalityone year after acute myocardial infarction.
Methods We linked claims for payment for physicians' services,hospital-discharge abstracts, and vital-status data for allpatients with acute myocardial infarction who were admittedto hospitals in Ontario between April 1994 and March 1997. Patients'income levels were imputed from the median incomes of theirresidential neighborhoods as determined in Canada's 1996 census.We determined rates of use and waiting times for coronary angiographyand revascularization procedures after the index admission foracute myocardial infarction and determined death rates at oneyear. In multivariate analyses, we controlled for the patient'sage, sex, and severity of disease; the specialty of the attendingphysician; the volume of cases, teaching status, and on-sitefacilities for cardiac procedures at the admitting hospital;and the geographic proximity of the admitting hospital to tertiarycare centers.
Results The study cohort consisted of 51,591 patients. Withrespect to coronary angiography, increases in neighborhood incomefrom the lowest to the highest quintile were associated witha 23 percent increase in rates of use and a 45 percent decreasein waiting times. There was a strong inverse relation betweenincome and mortality at one year (P<0.001). Each $10,000increase in the neighborhood median income was associated witha 10 percent reduction in the risk of death within one year(adjusted hazard ratio, 0.90; 95 percent confidence interval,0.86 to 0.94).
Conclusions In the province of Ontario, despite Canada's universalhealth care system, socioeconomic status had pronounced effectson access to specialized cardiac services as well as on mortalityone year after acute myocardial infarction.
Universal health care systems have been organized in most industrializednations with a view to ensuring equitable access to medicalservices and improving health status for all citizens. Canada'sfederal–provincial Medicare plan covers all medicallynecessary services provided by hospitals and physicians withoutany user fees and is based on the principle of access accordingto need rather than income.1,2 Considerable evidence suggeststhat Medicare has improved access to health services for poorerCanadians,3,4 but some studies have found that those of lowsocioeconomic status remain less likely to receive specificservices than wealthier patients.3,5,6,7 Several Canadian studieshave also demonstrated a persistent relation between socioeconomicclass and health status.8,9,10 For example, a recent population-basedstudy conducted in Winnipeg, Manitoba, demonstrated a 43 percentrelative increase in standardized mortality from ischemic heartdisease among the lowest income quintile as compared with thehighest.8
The available data on access to health care according to incomein Canada can be challenged on the grounds that the study designsdid not control adequately for potential differences in theseverity of illness or health status among socioeconomic subgroups.Similarly, Canadian studies addressing differences in healthstatus among socioeconomic groups have generally examined overallpopulations rather than groups of patients with specific majorhealth problems.
We accordingly devised a two-pronged test of the degree to whichthe Canadian health system has achieved equity in access tocare and outcomes. We examined data on patients who were hospitalizedwith acute myocardial infarction in the province of Ontario— first, to determine whether socioeconomic status (asindicated by neighborhood income levels) affected access tomajor coronary procedures and, second, to examine the associationsbetween socioeconomic status and mortality one year after acutemyocardial infarction. Because there is evidence that more aggressiveuse of revascularization does not lead to any immediate gainsin life expectancy after myocardial infarction,11,12,13,14,15we did not expect that differences in the rates of use of procedureswould affect medium-term survival. The two aspects of equityon which we wished to focus could therefore be analyzed independently.
Methods
Sources of Data
We obtained information from the Ontario Myocardial InfarctionDatabase (OMID),16 which draws together data from a varietyof administrative sources. Hospital-discharge abstracts compiledby the Canadian Institute for Health Information (CIHI) yieldedinformation pertaining to the index admission, demographic characteristicsof patients, coexisting illnesses, use of in-hospital procedures,and mortality. Data on claims for payment for physicians' servicesfrom the Ontario Health Insurance Plan and CIHI hospital-dischargedata were used to determine rates of use of cardiac procedures.The Ontario Registered Persons Database provided us with dataon mortality over time, regardless of where death occurred.
The cohort consisted of all patients admitted to a hospitalwith a "most responsible" diagnosis of acute myocardial infarction(code 410 of the International Classification of Diseases, 9thRevision, Clinical Modification [ICD-9-CM]17) between April1, 1994, and March 31, 1997, inclusive. The accuracy of thecoding of acute myocardial infarction in the OMID data basehas been validated previously through multicenter chart audits.16To reduce the chances that subgroups within the cohort variedin terms of the severity of cardiovascular disease, we excludedany patient who had been hospitalized with an acute myocardialinfarction in the year before the index admission. We also excludedpatients who were not residents of Ontario, patients with invalidOntario health card numbers, patients who were younger than20 or more than 105 years of age, those discharged alive forwhom the total length of the hospital stay was less than fourdays, those for whom acute myocardial infarction was coded asan in-hospital complication, and those who had been transferredfrom another acute care facility. Complete details of and therationale for the inclusion and exclusion criteria have beenreported previously.16
In Ontario, administrative data do not include personal income.Hence, we used 1996 official Canadian census data to calculatethe median income for each neighborhood area corresponding tothe first three digits of the postal code (Forward SortationArea), and imputed patients' incomes on the basis of their principalresidence. Statistics Canada suppressed income data for 11 ofthe 504 Forward Sortation Areas in Ontario because of smallsamples. Accordingly, our cohort of patients with acute myocardialinfarction was linked to income data for a total of 493 ForwardSortation Areas. Area-level data have been widely used to imputeindividual socioeconomic status, and inferences based on thismethod appear to be valid.8,18,19,20
Characteristics of the Hospitals
According to previous work by our group and others,21,22,23the likelihood of undergoing a major coronary procedure duringthe 6 to 12 months after acute myocardial infarction is moststrongly influenced by whether the patient was admitted to ahospital with the on-site capacity to perform such procedures(e.g., a catheterization laboratory, with or without revascularizationfacilities). Patients were categorized according to the typeof facilities available at the admitting institution (no on-sitefacilities, on-site facilities for angiography only, or on-sitefacilities for angiography and revascularization), regardlessof whether they were subsequently transferred to another hospital.Since the rates of use of procedures and outcomes after myocardialinfarction are also influenced by other characteristics of thehospitals,24 we adjusted for a number of additional factors,including the hospital volume, the distance from hospitals withouton-site facilities to the nearest tertiary care hospital withon-site facilities for cardiac procedures, teaching or nonteachingstatus, urban or rural location, and the specialty of the attendingphysician. The hospital volume was defined as the annual numberof patients with myocardial infarction admitted to the facility,16and distance to the nearest hospital with on-site facilitiesfor cardiac procedures was measured directly from latitude andlongitude ("as the crow flies").
Severity of Illness
To control for variations in the severity of illness on admission,we used the Ontario acute myocardial infarction mortality predictionrule for 30-day and 1-year mortality.16 ICD-9-CM codes wereused to identify various clinical and demographic variablesfrom the 15 secondary diagnostic fields in the data base forthe index admission only. These variables included age, sex,the severity of cardiac disease (e.g., congestive heart failure,cardiogenic shock, and arrhythmia), and the presence or absenceof coexisting illnesses (e.g., diabetes mellitus, stroke, cancer,and acute or chronic renal disease). The models showed excellentdiscrimination (i.e., areas under the receiver operating curveof 0.775 for 30-day mortality and 0.793 for 1-year mortality).The development of these models is described in more detailelsewhere.16
Use of Procedures
Coronary angiography and revascularization procedures (coronary-arterybypass surgery or percutaneous transluminal coronary angioplasty)were identified with use of both data on claims for physicians'services and procedure codes in the hospital-discharge database. Rates of coronary angiography were examined for up tosix months after myocardial infarction and rates of revascularizationfor one year, in order to allow for appropriate stratificationof risk after the myocardial infarction and for waiting times.All patients who underwent revascularization procedures wererequired to have undergone previously documented coronary angiographyin order for revascularization to be included in our analyses.
The exact dates of referrals for procedures could not be determinedfrom the available administrative data. However, as reasonablesurrogates for waiting times, we tallied the numbers of daysfrom the index admission to the date of angiography and fromangiography to revascularization. Generally, these surrogatemeasures slightly overestimate true waiting times for procedures.
Statistical Analysis
Neighborhoods were divided into five categories according tomedian personal income; each category contained a roughly equalproportion of the Ontario population. The lowest quintile correspondedto a median personal income ranging from $12,508 to $17,930,whereas the highest quintile corresponded to a range of $26,300to $44,409 (all income values are given in Canadian dollars[1 Canadian dollar is equivalent to 68 U.S. cents]). Procedurerates, waiting times, and one-year mortality were adjusted forage, sex, and types of facilities on site at the hospital (i.e.,no on-site facilities for invasive procedures, on-site facilitiesfor angiography only, or on-site facilities for angiographyand revascularization) within each income quintile by meansof direct standardization. The 95 percent confidence intervalsfor the standardized median time to an event were calculatedwith use of bootstrap methods.25 To assess whether there wasa gradient in standardized rates of use of procedures and mortalityrates across income quintiles, we used a Mantel–Haenszelchi-square test for trend. Similarly, to examine the possibilityof a gradient in standardized waiting times for procedures acrossincome quintiles, a weighted linear regression analysis, withone degree of freedom, for income quintiles was used as a testfor trend. One-year mortality across income quintiles was alsoassessed with use of Kaplan–Meier plots and the log-ranktest.
We developed a Cox proportional-hazards model to determine therelations of neighborhood median income to 1-year mortalityand to the likelihood of undergoing coronary angiography, afteradjustment for age, sex, severity of illness (i.e., the predictedprobability of death at 30 days after acute myocardial infarction),and characteristics of the hospitals and physicians. Similarly,we used multiple linear regression techniques with the least-squaresmethod to determine whether neighborhood median income predictedwaiting times for angiography in a manner that was independentof all other base-line characteristics. All multivariate analyseswere constructed in a similar fashion by forcing both patients'characteristics and income into the model. Hospital-relatedand physician-related factors were first examined by univariateanalysis. Variables that were significant at a P value of 0.20or less were included in multivariate analyses. Variables wereselected by means of backward stepwise regression and by comparisonof the –2 log likelihoods and regression sum of the squaresof the Cox proportional-hazards and ordinary least-squares regressionmodels, respectively. In survival models that examined ratesof use of procedures, death was the main reason for censoringdata. To ensure consistency, multiple logistic regression wasalso used to examine the effects of neighborhood income on ratesof angiography and mortality. However, these results are reportedonly if they differed significantly from those of the proportional-hazardsmodel. Statistical significance was considered to be indicatedby a P value of less than 0.05 in all analyses. SAS (version6.12) and S-Plus statistical software packages were used.
Results
Base-Line Data
The study cohort consisted of 51,591 patients. The median agewas 69 years (interquartile range, 58 to 77); 48.5 percent ofthe patients were 70 years old or older (referred to as elderlypatients), and 63.1 percent were male. There were small butsignificant differences with respect to age and sex among incomequintiles (Table 1). Although some clinical characteristicsvaried among income quintiles, no significant differences inoverall predicted 30-day mortality were observed. A disproportionatenumber of patients with acute myocardial infarction were inthe lower income quintiles, illustrating the greater burdenof illness among those with lower socioeconomic status.
Table 1. Base-Line Characteristics of Patients, According to Quintile of Neighborhood Median Income.
Hospital-related characteristics are summarized for patientsin Table 1 and for hospitals in Table 2, according to neighborhoodmedian income. There were significant positive relations betweenthe availability of specialized hospital services and socioeconomicstatus. The degree of mismatching between the income quintileof the patient and that of the hospital was limited, since mostpatients were admitted to local hospitals in neighborhoods thatwere similar in socioeconomic status to those where they lived.
Table 2. Characteristics of the Admitting Hospitals According to Quintile of Neighborhood Median Income.
Rates of Use of Procedures and Waiting Times
We examined the use of angiography according to the availabilityof on-site facilities. As shown in Table 3, there were significantpositive relations between income and the rate of use of angiographyand revascularization, both at hospitals with on-site facilitiesfor angiography and revascularization and at hospitals withoutsuch facilities. Waiting times for coronary angiography wereinversely correlated with neighborhood income quintiles. Medianwaiting times, adjusted for age and sex, varied from 34.5 daysto 23.3 days (P for trend=0.02) for hospitals without on-siterevascularization facilities and from 6.9 days to 4.6 days (Pfor trend=0.04) for hospitals with on-site facilities.
Table 3. Adjusted Rates of Cardiac Procedures and One-Year Mortality According to the Availability of On-Site Facilities and According to Quintile of Neighborhood Median Income.
Figure 1 illustrates the differences in standardized rates ofangiography and waiting times among income quintiles. Patientswith myocardial infarction who lived in higher-income neighborhoodswere significantly more likely to undergo catheterization andhad shorter waiting times for angiography than patients in lower-incomeneighborhoods.
Figure 1. Adjusted Relative Rates of Angiography within Six Months after Acute Myocardial Infarction, Waiting Times for Angiography, and One-Year Mortality According to Income Quintile.
Results have been standardized for age, sex, and type of on-site facilities for cardiac procedures. Quintiles for neighborhood median income were derived from 1996 Canadian census data for 493 Forward Sortation Areas (neighborhoods defined by the first three digits of the postal code); the patients in the highest quintile served as the reference group. The bars show the relative differences in adjusted rates and waiting times. The absolute differences between the lowest and the highest income quintile were 7.4 percent for adjusted rates of angiography, 9.2 days for adjusted waiting times for angiography, and 3.1 percent for adjusted mortality rates. P for trend <0.001 for each of the three outcome variables.
In total, 15.7 percent of patients in the lowest income quintileand 20.3 percent of those in the highest income quintile underwentrevascularization procedures. However, among patients who hadundergone angiography, we found no significant increase in thelikelihood of revascularization in increasing income quintiles(range, 56.3 percent in the lowest quintile to 58.2 percentin the highest; P for trend=0.31) and no significant differencein waiting times (range, 16 days in the lowest quintile to 14days in the highest; P for trend=0.10). Access to angiographywas thus the rate-limiting step in access to revascularization.
The adjusted hazard ratios from the statistical models examiningpredictors of the rate of use of angiography are summarizedin Table 4. Higher neighborhood median income consistently predictedgreater use of angiography, independently of age, sex, the severityof clinical illness, the specialty of the attending physician,and characteristics of the hospital. Moreover, the effect ofincome on the rate of angiography was as pronounced for elderlypatients (adjusted hazard ratio for each additional $10,000of median income among patients 70 years of age and older, 1.27;95 percent confidence interval, 1.17 to 1.38) as it was foryounger patients (adjusted hazard ratio, 1.18; 95 percent confidenceinterval, 1.13 to 1.24). Similarly, higher neighborhood medianincome predicted shorter waiting times for angiography aftercontrol for all of the factors mentioned above (P<0.001).
Table 4. Adjusted Hazard Ratios for Undergoing Coronary Angiography within Six Months and for Death at One Year According to Neighborhood Income and Characteristics of the Patient, Physician, and Hospital.
Mortality
The overall crude 30-day and 1-year mortality rates were 14.7percent and 23.1 percent, respectively. As Table 3 shows, mortalityalso varied according to income quintile within groups of hospitalswith different types of on-site facilities. Figure 1 demonstratesa significant gradient in overall standardized mortality ratesacross income quintiles. The absolute difference in standardizedmortality between the lowest and the highest income quintilewas 3.1 percent (P<0.001). As Figure 2 illustrates, althoughmost deaths occurred within the first 30 days after the acutemyocardial infarction, the effects of income on survival persistedat 1 year (2=61.54 by the log-rank test, P<0.001).
Figure 2. Kaplan–Meier Survival Curves According to Quintile of Neighborhood Median Income.
Quintiles for neighborhood median income were derived from 1996 Canadian census data on 493 Forward Sortation Areas (neighborhoods defined by the first three digits of the postal code). The difference in survival among income quintiles was significant (2=61.54 by the log-rank test, P<0.001).
Income was a consistent independent predictor of mortality (Table 4).The effect of median income on adjusted mortality was large.Specifically, a $10,000 increase in neighborhood median incomewas associated with a 10 percent reduction in the risk of deathat one year (adjusted hazard ratio, 0.90; 95 percent confidenceinterval, 0.86 to 0.94). Moreover, the effect of neighborhoodincome on adjusted mortality was consistent among age groups(adjusted hazard ratio for patients 70 years of age and older,0.92; 95 percent confidence interval, 0.88 to 0.98; for patientsunder 70 years of age, 0.85; 95 percent confidence interval,0.77 to 0.94).
Discussion
In this population-based cohort study, we found pronounced effectsof socioeconomic status on access to specialized cardiac servicesin Ontario's universal health care system, as well as on mortalityone year after acute myocardial infarction. Progressive increasesin neighborhood median income levels predicted greater ratesof use of coronary angiography, shorter waiting times for catheterization,and lower mortality one year after acute myocardial infarction,after adjustment for age, sex, the severity of clinical disease,the specialty of the attending physician, and characteristicsof the hospital.
Although Canada's universal health insurance programs have promotedgreater equity in access to care,3,4 several studies have showncontinuing income-related differences in the rates of use ofspecific services.3,5,6,7 Our findings offer a dramatic demonstrationof these persisting inequities in access for a cohort of personswho were hospitalized with the same condition and who should,in theory, have been treat-ed similarly. Although more affluentneighborhoods tended to have a greater concentration of specializedservices, inequitable distribution of hospital resources didnot account entirely for the effects of socioeconomic statuson access to procedures and on outcome after acute myocardialinfarction. Moreover, it is implausible that these differencesare explained by the presence of less severe illness among patientsin the lower socioeconomic groups. Not only did we adjust forage, sex, and various prognostic markers at the index admission,but in general, one would expect poorer patients who were hospitalizedfor acute myocardial infarction to have more severe coronaryartery disease than those with higher incomes.
Although persons with lower incomes had both reduced accessto invasive procedures and worse outcomes, it is unlikely thatthese two findings are causally related. Indeed, on the basisof the available evidence,11,12,13,14,15,26,27 we interpretedour design as measuring two independent dimensions of equity.Within our study, access to coronary angiography was stronglyinfluenced by whether or not the index admission took placein or near a hospital with on-site facilities for invasive procedures.However, income-related differences in mortality were foundwithin groups of hospitals with different types of on-site facilities.Moreover, lower income was a significant and independent predictorof higher one-year mortality in all our multivariate analyses.
Even if reduced access to coronary revascularization does notaccount for income-related differences in one-year mortality,however, this does not justify the observed disparities in access.Other outcomes, such as the quality of life and functional status,are improved by higher rates of revascularization after acutemyocardial infarction.28,29 Moreover, a one-year follow-up periodmay be too short to demonstrate the full benefits of revascularizationin terms of mortality.
Our study was not designed to address the myriad social andclinical determinants of adverse outcomes. However, poorer medium-termoutcomes for patients in the lower-income groups are consistentwith a large body of research showing that people with lowerincomes live shorter, less healthy lives.30 Indeed, our cohortof patients itself illustrates the consistent inverse relationbetween health status and socioeconomic status. Although eachincome quintile contained essentially the same proportion ofOntario's population, there were significantly more patientswith acute myocardial infarction in the lower income quintiles.With respect to excess mortality from cardiovascular causes,in particular, lower socioeconomic status has been shown tobe associated with a higher prevalence of cardiac risk factorssuch as hypertension, cigarette smoking, obesity, diabetes,and prothrombotic factors such as elevated fibrinogen levels.31,32,33,34Thus, patients of lower socioeconomic status may have more extensivecoronary disease in the first instance, and they are certainlyat greater risk for recurrent events.35 Their higher levelsof risk factors may be compounded by poorer compliance withmedical therapy.27,36 Although the exact mechanisms remain controversial,psychosocial factors are also likely to mediate adverse outcomesfor poorer or less well educated persons with coronary arterydisease. Occupational stress,37,38 social isolation,38 and depression39are all more prevalent among persons with lower socioeconomicstatus and may contribute to higher mortality.31,40
Several limitations of our study should be noted. The use oflinked administrative data limited our ability to characterizethe patients in our cohort, either with regard to their ownbase-line health status or with regard to the specific natureof the care they received during the index hospitalization andthereafter. Nonetheless, we did control for many important prognosticvariables, such as age, sex, presence or absence of coexistingconditions, and presence or absence of complications, such ascardiogenic shock, at the time of the index admission. A furtherlimitation resulted from the fact that we imputed socioeconomicstatus to patients on the basis of median incomes at the neighborhoodlevel rather than on the basis of data on individual patients.However, there is good evidence to support this method of imputingincomes.18,20 Indeed, any risk of inaccuracy due to the so-calledecologic fallacy (the misclassification of personal socioeconomicstatus on the basis of the socioeconomic characteristics ofthe neighborhood) may be offset by the avoidance of an "individualisticfallacy," whereby one wrongly assumes that individual patientsare unaffected by the neighborhood in which they live. Finally,we assessed only one outcome — albeit a very importantone — mortality.
In conclusion, despite universal health insurance coverage,Ontario residents living in lower-income areas have reducedaccess to invasive procedures, as compared with residents ofwealthier neighborhoods, and have sharply higher mortality oneyear after hospitalization for acute myocardial infarction.The causes of these socioeconomic disparities in access andoutcome remain obscure, but their persistence poses a clearchallenge to the egalitarian principles of Canada's publiclyfunded health care system.
The conclusions and opinions presented in this article are thoseof the authors, and no endorsement by any funding agency isintended or should be inferred.
Supported by an operating grant from the Medical Research Councilof Canada. Dr. Alter is the recipient of a Heart and StrokeFoundation of Canada Research Fellowship, Dr. Naylor is a SeniorScientist of the Medical Research Council of Canada, and Dr.Tu is a Scholar of the Medical Research Council of Canada.
Source Information
From the Institute for Clinical Evaluative Sciences (D.A.A., C.D.N., P.A., J.V.T.); the Clinical Epidemiology and Health Care Research Program (C.D.N., J.V.T.) and the Divisions of Cardiology (D.A.A.) and General Internal Medicine (C.D.N., J.V.T.), Sunnybrook and Women's College Health Sciences Centre and the University of Toronto; and the Department of Public Health Sciences (C.D.N., P.A., J.V.T.) and the Dean's Office (C.D.N.), University of Toronto — all in Toronto.
Address reprint requests to Dr. Tu at the Institute for Clinical Evaluative Sciences, G-106, 2075 Bayview Ave., Toronto, ON M4N 3M5, Canada.
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2=61.54 by the log-rank test, P<0.001). 
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