Gender Differences in Cost Effectiveness of Coronary Angiography Following Hospital

Admission for an Acute Coronary Syndrome

In Canada as in the United States Angiography rates have been increasing in step with

CABG and PCI volumes1. Given the increase in CAD rates, optimal target volumes of

angiographies have been set higher as well2 3. Previous studies, however, suggest

selective as opposed to routine use of Angiography may offer the most cost-effective

benefit to patients4 5 . In spite of the benefits of catheterization, women continue to

receive this procedure at much lower rates than men. An important question to ask is

whether this disparity is warranted. The literature presents a mixed picture with respect to

the outcomes (i.e. death, recurrent ACS events) in women resulting from the routine use

of angiographic procedures6-10.

The objective of our study is to undertake a cost-effectiveness analysis, separately for

men and women, using data provided by Statistics Canada, Canadian Institute for Health

Information (CIHI) as well as peer reviewed literature to assess the incremental benefit

of angiography. In our context, benefit refers to mortality as well as hospital readmission

rates.

Data

Input data was derived from Statistics Canada hospital person oriented information

database (HPOI) reporting angiography for men and women between 2002 and 2005. All

remaining information viz. a viz. probability data was gathered from secondary sources

primarily focusing on peer reviewed medical articles preferably published in Canada or

the U.S.A.

Methods

The cost effectiveness study is based on discrete time Markov model design using a three

state design. The cost methodology will be described separately in the next section.

Markov Models

Increasingly Markov models have become the tool of choice when conducting cost-

effectiveness or other decision analyses. However the basic premise or assumptions

underlying these models have often been ignored. In general terms the future state of a

system must depend only on the current state and not any prior state , for otherwise the

conditions for employing a Markov model are violated. With that caveat in mind , the

essential Markov constructs listed below are briefly reviewed.

Defined time period or cycle

To begin with a period or cycle is predetermined, usually based on calendar time

such as a year or month. In our study data, including costs were available on a yearly

basis.

Health or Disease states

A cohort of 100,000 men and women enter the model following an Acute

Coronary Syndrome (ACS), and are assigned to a hospitalization state. From this

state a patient can transit to either a wellness state (discharged from hospital alive)

, death state (removed from cohort model), or return to a hospital state. The

hospital and well state are deemed recurrent states as returning to these states in

subsequent cycles has a positive probability. The death state is an absorbing state

as once entering this state , exiting is no longer possible (probability of 0). (See

Figure 1)

Probabilities of transition from one health state to another

Transitions from one state to another involve various intermediate decision points

prior to transiting to a new state. These decision pathways are associated with

probabilities derived from previous study results and/or peer reviewed literature .

In our analysis all patients initially transit from a hospital state to an intermediate

state determined by whether they received an Angiography during the same

episode of care. Regardless of which decision path a patient followed, their

survival status is assessed. If the patient died, then the cohort is reduced in size ,

and no longer contributes cost or event data. In the event a patient survives , the

patient follows one of three possible categories of treatment : 1) PTCA; 2)

CABG; 3) non-surgical treatment (Medication only). To be sure patients

undergoing a PTCA or CABG are assumed to be on medication as per guideline

protocols. Following a treatment regime , the patient is assumed to transit to a

well state (discharge from hospital) or a hospital state (readmitted to hospital) at

the beginning of the next cycle. If a patient transits is readmitted to hospital , the

same intermediate transitions as in the initial state are available. Otherwise, in a

healthy or well state, a patient may transit to a hospital state (readmission to

hospital within the cycle), die, or continue to be well to the end of the cycle (see

Figure 2 for a complete illustration of the tree pathways). Table 1 lists all

transition probabilities for both men and women along with their references.

Initial probabilities of starting in any given health state

In our study all patients enter the model hospitalized following an ACS. Hence

the probability of initially being in the hospitalization state is 1, and 0 for the

remaining states.

Termination Conditions

In order for a Markov model to terminate in the sense that any computer model

requires some stopping rule, the simulation was allowed to run for up to 5 cycles.

In other words a follow-up of 5 years was allotted.

Each cycle should correspond to the associated probability of any event.

Outcomes from each cycle are comprised of cumulative costs , events, and

transition probabilities.

Hospital costs

Hospitalization costs were calculated using the Canadian Institute for Health Information

(CIHI) methodology which translates the Canadian inpatient data into CMGs, equivalents

of DRGs. The standard costs, based on typical inpatient data, by diagnosis, were

estimated using CMG + 2011 Discharge Abstract Database. The CMG + 2011

methodology was based on ICD-10CA and CCI classification systems. Inpatient data

from Alberta, British Columbia and Ontario, of approximately 1 million cases, were used

to calculate the case-cost data used for the RIW calculations. The CIHI data include all

hospital care costs except physician fees.

Inpatient and outpatient physician fees

The unit costs of physician services for emergency, inpatient and outpatient care were

estimated using reimbursement fees from Ontario and adjusted rates from Quebec, to

calculate the average fees for those two provinces, since over 60% of health care costs are

spent in these two provinces.

Costs of outpatient diagnostic laboratory services Costs of outpatient diagnostic

laboratory services, including the professional and technical components, were estimated

using Ontario and adjusted Quebec reimbursement fees.

Costs of outpatient prescription drugs

Costs of outpatient prescription drugs, directly to the patient, including the dispensing

fees and the pharmacy mark-ups, were estimated using data from IMS Health Canada.

Results

Costs

Table 1 presents average hospitalization costs for patients presenting with an Acute

Coronary Syndrome . Specifically hospital costs per stay are reported across age strata of

18-59 , 60-79, and 80+ years along with intensity weights (RIW). Filling out the table

are the primary CMG codes and average physician fees. All costs are assumed to apply

equally for men and women. Outpatient costs are reported in Table 2, and categorized by

physician, diagnostic, and drug costs. Once again we assume that once discharged, men

and women incur the same costs. Hence the assumption is that once hospitalized there is

no difference in cost between men and women.

Events

The discrete time Markov model was designed to run over a 5 year period starting with a

patients initial hospitalization for an ACS. With each year corresponding to a cycle ,

Figure 2 presents all possible pathways that may occur over this period as elucidated by

the probabilities laid out in tables 3 and 4. Beginning with a cohort of patients who are

hospitalized with probability 1, patients travers the tree (Figure 2) according to prescribed

probabilities derived from our study and peer reviewed literature. According to the data

derived from the HPOI Statistics Canada database , more men than women had a

likelihood of undergoing an Angiogram following an ACS during the same episode of

care (43.5% vs. 31.5%). Similarly, the remaining probabilities are listed corresponding

to the Markov model in Figure 2. Along with a description of the probabilities is a

column listing the number corresponding to the cited reference in the bibliography.

Outcomes

Following hospitalizations for an ACS, first year costs were higher for men than for

women ($1,163,781,630 vs. $1,020,880,422). However costs post 1 year were lower for

Men than for women ($965,128,460 vs $926,556,442) or an average of $9.6 million a

year . Corresponding to the increased cost incurred by women, between years 1 and 5

they sustained 90,803 readmissions as compared with 76,150 for men. The excess cost of

$38,572,018 and 14,653 readmissions post year 1 resulted in an average of cost of

$2632 per additional hospitalization in women.

Discussion

After the first year of follow-up, the cost of treating women with ACS exceeds that of

men by virtue of increased hospital admission over the subsequent 4 year period.

The additional cost resulting from the excess readmissions in women amounted to over

$2600 per stay. This study assumes that men and women benefit equally from the use of

catheterization. Furthermore, no adjustment is made for disease severity. Likewise, the

administrative data component of our database provided details of the diagnosis and

subsequent procedures, but little information on the extent, severity of disease (i.e. single

vs. multi vessel involvement), or classification of the ACS. Specifically, we could not

deduce the category of disease be it ST-segment elevation myocardial infarction

(STEMI) or non ST-segment elevation myocardial infarction (NSTEMI). That said,

recent studies, Elbarasi et al.11 and Nguyen et al.12 have demonstrated that age and pre-

existing comorbidities were, independent of all other factors, strong predictors of whether

a patient underwent catheterization following an ACS. Finally, data on the admitting

institution – such as the presence of a catheterization laboratory was not present although

we were able to access data on the procedures performed in all hospitals treating the

patient during the same episode of care.

In addition, caution should be taken in assuming the course of treatment for women

would be identical to men regardless of whether or not catheterization was performed.

These differences may simply be attributed to accessibility to catheterization labs.

From a policy perspective, targeting specific populations subgroups, including gender

that are underserved in their health care needs , such as access to medical technology,

may be a more cost-effective approach to spending health care dollars.

Results

Table 1: Inpatient costs by RIW, by age, in $2010Diagnosis Average LOS RIW Avg hospital$/stay CMG codes Avg physician feesCABG with angiography 18–59 Years 10.5 3.38850 18,007 166-169 $3,887

60–79 Years 11.6 3.58623 19,057 $3,95080+ Years 13.2 3.85736 20,498 $4,046

CABG no angiography 18–59 Years 5.8 2.57898 13,705 170-172 $3,086

60–79 Years 6.5 2.71760 14,441 $3,12680+ Years 7.6 2.99210 15,900 $3,193

PTCA 18–59 Years 2.6 1.56912 8,338 175+176 $66960–79 Years 2.7 1.59958 8,500 $67280+ Years 3.6 1.79621 9,545 $728

ACS with angiography 18–59 Years 3.4 1.04858 5,572 193+203 $906

60–79 Years 3.9 1.13399 6,026 $93880+ Years 4.9 1.29674 6,891 $995

ACS no angiography 18–59 Years 3.1 0.77653 4,126 194+204 $361

60–79 Years 3.7 0.85438 4,540 $39780+ Years 4.7 1.00246 5,327 $453

Medical follow-up 18–59 Years 2.4 0.49806 2,647 196+204+208 $31960–79 Years 3.8 0.70991 3,772 $40380+ Years 5.2 0.91030 4,837 $482

Table 2 : Outpatient Costs

Items Visits/year Unit cost Total costs/year

Physician initial GP 1 $69.17 $69.17repeat GP 3 $34.37 $103.10cardiologist 2 $92.13 $184.26

Diagnostic tests $567ECGChest XrayCardiac catheterizationRadionuclide ventriculogramEchocardiographyBiPapCT ThoraxVentilation perfusion scanHolter testTreadmill test

Drugs $625

Total outpatient costs $1,549

Table 3 : MalesDescription of Probability

Variable Name Probability Reference

Probability of Angiography

PangioM 0.435 Study(HPOI, Statistics Canada)

Probability of death (No Angiography)

PdtnoangM 0.046 13

Probability of PCTA following Angiography

PangpciM 0.425 13

Probability of CABG following Angiography

PAngcabgM 0.29 13

Probability of PCTA without Angiography

PNoAngpciM 0.254 13

Probabilty of CABG without Angiography

PNoAngcabgM 0.207 13

Probability of death (Angiography)

PdtangM 0.043 13

Probability of readmission following PCTA(No Angiography)

PreadpctaM 0.189 6 14-16

Probability of readmission following CABG(No Angiography)

PreadcabgM 0.078 6 14-16

Probabilty of readmission following medical trx (No Angiography)

preadmedsM 0.303 6 14-16

Probability of readmission following PCTA(Angiography)

PreadpctaAngM 0.127 6 14-16

Probability of readmission following CABG(Angiography)

PreadcabgangM 0.052 6 14-16

Probability of readmission following Medical Trx(Angiography)

PreadmedsAngM 0.291 6 14-16

Table 4: FemalesDescription of Probability

Variable Name Probability Reference

Probability of Angiography

PangioF 0.315 Study(HPOI, Statistics Canada)

Probability of death (No Angiography)

PdtnoangF 0.039 13

Probability of PCTA following Angiography

PangpciF 0.412 13

Probability of CABG following Angiography

PAngcabgF 0.199 13

Probability of PCTA without Angiography

PNoAngpciF 0.247 13

Probabilty of CABG without Angiography

PNoAngcabgF 0.153 13

Probability of death (Angiography)

PdtangF 0.043 13

Probability of readmission following PCTA(No Angiography)

PreadpctaF 0.206 6 14-16

Probability of readmission following CABG(No Angiography)

PreadcabgF 0.105 6 14-16

Probabilty of readmission following medical trx (No Angiography)

PreadmedsF 0.346 6 14-16

Probability of readmission following PCTA(Angiography)

PreadpctaAngF 0.169 6 14-16

Probability of readmission following CABG(Angiography)

PreadcabgangF 0.086 6 14-16

Probability of readmission following Medical Trx(Angiography)

PreadmedsAngF 0.332 6 14-16

Table 5

First Year Cost 1-5 Year Cost Hospitalizations Years 1 - 5

Females 16700 Without Angiography

$591,540,663 $561,126,530 62442

With Angiography

$429,339,759 $404,001,930 28361

Total $1,020,880,422 $965,128,460 90803

Males 17800 Without Angiography

$525,663,427 $423,235,013 43217

With Angiography

$638,118,203 $503,321,429 32933

Total $1,163,781,630 $926,556,442 76150

References

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Figure 1

Figure 2