the impact of technological progress on the age profile of ... · we add a synthetic approach of...

IntroductionLiterature

MethodData

Health Technology IndexFindings

DiscussionSummary

The impact of technological progress on theage profile of health expenditures

A decomposition using Ontario administrative data

Roham, Gabrielyan, Archer, Grignon and Spencer

McMaster University, Hamilton, Ontario

November 25, 2015

Roham, Gabrielyan, Archer, Grignon and Spencer Technology and age


MethodData


DiscussionSummary

Outline

1 Introduction

2 Literature

3 Method

4 Data

5 Health Technology Index

6 Findings

7 Discussion



MethodData


DiscussionSummary

Main drivers of health care spending

1 Aging of the population (wave effect)2 Income per capita (neutral if follows GDP)3 Technology and demand for health (tsunami effect)

In effect: age versus technology.



MethodData


DiscussionSummary

The wave effect



MethodData


DiscussionSummary

The tsunami effect



MethodData


DiscussionSummary

Research question

Well established: Technology major driver, aging is notLess well known: factors of medical progressDemand driven: could be age-related (more customers,and gains in LE after 65)Research question: does technical progress change theage profile of spending?



MethodData


DiscussionSummary

Stylised factsAge profile changes with time

Public health care cost per capita of age categories relative tocost of 20-24 years old:

65-69 costs 3.8 more in 2011, was 3.6 in 199970-74 between 4.9 (in 1999) and 5.3 (in 2004)85-89 from 16.7 in 1998 to 14.0 in 201190+ from 17.1 in 1998 to 15.4 in 2011



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DiscussionSummary

Synthetic approach

1 Fuchs, 1999: changing age profile of 7 specific treatments2 Cutler and Meara (1997, and 2001): 2 treatments3 Sheiner, 2004: 2 imaging devices and angioplasty and a

theoretical model suggesting why innovation couldprioritize the young or the old (ability to benefit).

4 In Canada (Tu et al. 202, Pilote et al. 2002): innovationbenefits the elderly (diffusion rates by age).

We add a synthetic approach of all technical innovations.



MethodData


DiscussionSummary

Decomposition of spending by age and technologicalintensity

NTt =

∑j αj,t .[NL

j,t + NMj,t + NH

j,t ]

ETt =

∑j αj,t .[EL

j,t + EMj,t + EH

j,t ]

WithN number of services per capitaE cost per capitaj age groupst yearα proportion of age group j in total populationL, M, and H stand for low-tech, middle-tech, and high-techservices.



MethodData


DiscussionSummary

We study changes in age profiles of spending within each typeof technology (L, M, and H) and more precisely the H type ofservices: do we see that the technical tsunami affects theelderly more than the young?



MethodData


DiscussionSummary

Administrative data on utilization

OHIP data between FY94 and FY04, with 5 years in total(94, 99, 2000, 2001, 2004).Information on costs, services provided (treatments),diagnoses, and dates services provided as well as age andsex of patient.All services provided or prescribed by a physician (in andout-patient) paid Fee-For-ServiceEach service is a line and we cannot link at the patient (orphysician) level: unit of observation is age category of thepatient.



MethodData


DiscussionSummary

Number of observations

1 Overall, 1.3 billion lines2 We drop all prescribed services (not delivered by

physicians)3 We drop services provided outside of province, or not paid

FFS.4 We are left with 811 million lines (services provided)



MethodData


DiscussionSummary

Classify services according to technological intensity

A service is a billing code: 5,272 codes. MOHLTC provides27 groupings.Three dimensions: complexity, knowledge, and “effort”Content and knowledge are qualitative, effort isquantitative (measured by fee)Objective: create three categories (“Low”, “Medium”, and“High”)Steps: assign each service to L, M, or H on eachdimension, then make decisions if discrepancies acrossdimensions based on a weight for each dimension (.5 forcomplexity, and .25 each for knowledge and effort.)



MethodData


DiscussionSummary

Complexity

Expert grouping of 27 MOHLTC groups of codes, except fordiagnosis and imaging (each service within that group assignedto L, M, or H).


decision making, but it has thus far had little impact on the economics literature. (Amore detailed exposition of therelated procedures, including illustrative calculations, will be available in a working paper, accessible online).

The calculations are in six steps, and we consider each in turn.Consider data classification (steps 1a and 1b) and fuzzification (step1.b.2). The procedures differ between

the qualitative components ‘TC’ and ‘technological knowledge’ (TK), and the quantitative component, ‘costof technology’ (CT).

The TC of services is based on the 5272 distinct billing codes reported in the Ontario fee schedule code forphysician services; the Ministry of Health and Long-Term Care groups the individual codes into 25 categories(MOHLTC, 2008), and we aggregate them further into three: low, medium, and high, as shown in Table II. Ofthe 27, only the ‘diagnostic and therapeutic procedures’ category could not be allocated to one of our three.Instead, we allocated each of diagnostic and therapeutic procedures services to our three categories accordingto expert opinions, Canadian and International clinical guidelines, medical standards of technology usage, andsystematic reviews (Stepanenko et al., 2009, pp. 6–7).

Services with high TC are defined as those with ‘substantial setup costs in hiring specialized personnel andthe purchase of specialized equipment’ (McClellan and Kessler, 1999, p. 253). For example, diagnosticimaging procedures, such as MRI, computed tomography (CT), and clinical procedures such as cardiaccatheterization, angioplasty, and bypass surgery, all involve high fixed and incremental costs (McClellan andKessler, 1999, p. 253; OECD, 2003, p. 229).

Table II. Technological complexity of interventions

Class Description

Fee schedule codes Number of records

N % N %

Low 1 0.02 3,446 0.00Consultations and visits 736 13.96 423,270,639 52.20Diagnostic and therapeutic procedures 195 3.70 89,188,914 11.00Preventive care management 4 0.08 59,960 0.01Pronouncement of death hospital minor assessment/certification of death 1 0.02 32,086 0.00Total low 937 17.77 512,555,045 63.21

Medium Diagnostic and therapeutic procedures 746 14.15 125,882,438 15.52Digestive system surgical procedures 427 8.10 9,342,784 1.15Endocrine surgical procedures 20 0.38 124,075 0.02Female genital surgical procedures 133 2.52 2,348,251 0.29Hematic and lymphatic surgical procedures 21 0.40 139,130 0.02Integumentary system surgical procedures 267 5.06 9,123,936 1.13Male genital surgical procedures 74 1.40 603,101 0.07Musculoskeletal system surgical procedures 775 14.70 3,894,856 0.48Obstetrics 54 1.02 10,072,282 1.24Pulmonary function studies 34 0.64 8,653,519 1.07Respiratory surgical procedures 179 3.40 1,590,011 0.20Urogenital and urinary surgical procedures 195 3.70 1,770,995 0.22Total medium 2,925 55.48 173,545,378 21.40

High Cardiovascular surgical procedures 203 3.85 644,835 0.08Clinical procedures associated with diagnostic radiological examinations 71 1.35 645,675 0.08Diagnostic and therapeutic procedures 128 2.43 13,583,268 1.68Diagnostic radiology 198 3.76 67,985,135 8.38Diagnostic ultrasound 94 1.78 30,105,436 3.71Magnetic resonance imaging (MRI) 32 0.61 1,679,251 0.21Neurological surgical procedures 129 2.45 159,907 0.02Nuclear medicine – in vivo 219 4.15 6,810,966 0.84Ocular and aural surgical procedures 205 3.89 2,992,659 0.37Radiation oncology 23 0.44 65,930 0.01Spinal surgical procedures 108 2.05 156,204 0.02Total high 1,410 26.75 124,829,266 15.39

Total 5,272 100 810,929,689 100

THE IMPACT OF TECHNOLOGICAL INTENSITY

Copyright © 2013 John Wiley & Sons, Ltd. Health Econ. (2013)DOI: 10.1002/hec


MethodData


DiscussionSummary

Knowledge

Based on the specialty of the provider: 30 specialties.


Services with low TC have low fixed and incremental costs, and do not require highly specialized training.These include simple injections, preventive care management, and other services that can be provided byhealthcare personnel with ‘little additional inputs of labor, capital equipment, or materials’ (McClellan andKessler, 1999, p.253).

Services with medium TC include those not in the high and low technological categories.Table II shows the number of billing codes and records in each procedure category during the data period.

high TC interventions accounted for 27 percent of all codes and 15 percent of all records.The TK embodied in a service is based on the reported specialty of the physician who provided that service.

The authors separately classified the 30 physician specialties into three classes (low, medium, and high) thatreflect the degree of TC of the specialties, based on a combination of specialization, skills, and specific trainingin technology. The main criterion used was the number of additional years of training involved; a high TKrequires three or more years, medium 1 year to 2 years, and low less than 1 year.

The specialty groupings are shown in Table III, which also shows the distribution of services acrossspecialties. About 55 percent of all services were provided by physicians using low technological skills, and19 percent accounted for high technological skills.

CT is based on the payments to FFS physicians that are made in accordance with the fee schedule code(MOHLTC, 2008). In this quantitative component of the model, the fuzzy Gustafson–Kessel clustering

Table III. Technological knowledge of physician medical specialties

Class Description

Number of records

N %

Low Community medicine 5,048 0.00General and family practice 426,795,508 52.63Geriatrics 424,174 0.05Psychiatry 16,244,711 2.00Total low 443,469,441 54.68

Medium Anesthesia 11,775,089 1.45Dermatology 10,653,452 1.31Emergency medicine 1,454,672 0.18Gastroenterology 3,590,994 0.44General surgery 15,865,137 1.96Internal medicine 88,751,226 10.94Obstetrics and gynecology 28,632,467 3.53Otolaryngology 15,160,168 1.87Pediatrics 20,815,819 2.57Physical medicine 3,349,241 0.41Respiratory disease 3,506,257 0.43Rheumatology 945,213 0.12Urology 7,843,334 0.97Total medium 212,343,069 26.18

High Cardiology 14,987,415 1.85Cardiovascular and thoracic surgery 1,527,949 0.19Diagnostic radiology 95,127,313 11.73General thoracic surgery 565,629 0.07Hematology 1,666,426 0.21Neurology 4,812,821 0.59Neurosurgery 811,722 0.10Nuclear medicine 2,739,852 0.34Ophthalmology 18,750,868 2.31Orthopedic surgery 9,293,703 1.15Plastic surgery 3,353,142 0.41Therapeutic radiology 1,480,339 0.18Total high 155,117,179 19.13

Total 810,929,689 100

Community medicine was added in September 2000.

M. ROHAM ET AL.



MethodData


DiscussionSummary

Effort

Fuzzy clustering of fees. This is the only instance where thenumber of clusters (3) was not set a priori but tested. Fuzzymeans that each element (service) belongs to one or morecluster(s), with varying degrees of membership.



MethodData


DiscussionSummary

Declining share of Low tech services

L represented 60% of total costs in 1994, but 50% only in2004H went from 10 to 20 in the same period of time.Age-standardized physician costs per capita went downfrom $450 to 400 in the period, with cost per capita on Lowtech services decreasing $75, cost per capita on Mediumtech services decreasing $25, and cost per capita on Hightech services increasing $50



MethodData


DiscussionSummary

Technology and the age profile of costs

High tech services increase faster for older patients in Ontario:the age profile does not change for L and M, but steepens for H.


many services each year as do those who are aged 5 years to 9 years or 10 years to 14 years. The profile levelsincrease with age gradually until the late 40s or early 50s, and then more rapidly. The year-to-year differences arerelatively small, but do show a reduction in the level of physician service since the mid-1990s. However, behindthe totals are quite distinct trends for the three levels of technological intensity. For low HTI (Figure 5(a)) the ageprofile has shifted down over time, and the downward shift has been fairly uniform across all age groups. Similarcomments apply to medium HTI (Figure 5(b)), although the downward shift between 1994 and 2000 was partly re-versed by 2004. By contrast, for high HTI (Figure 5(c)) the profile shifted upwards and the shift has beenmuchmorepronounced at the older end of the age distribution. The implication is that over this period the most technologicallyintensive services were increasinglymore likely to be provided tomiddle-aged and older members of the population.

Figure 6 shows age-expenditure profiles that correspond to the age–service profiles in Figure 5. The ageprofiles are generally similar in the two figures, but with more consistent downward shifts over time in boththe total and low HTI expenditure profiles; the downward shift in the medium HTI expenditure profile alsois more consistent across the age spectrum even though the year-to-year differences are slight. Mostimportantly, however, the upward shift in the high HTI expenditure profile applies only to the age groups55–59 and older, indicating that the cost increase in the use of the most technologically intensive physicianinterventions have become much more concentrated for the older age groups.

Much was happening during our data period, including budgetary cuts in the early years and increases in thelater ones. However, our analysis shows that the overall volume of physician services per capita at firstdecreased and then stabilized, and that average cost declined throughout the period (Figures 3 and 4).8 The

8The two sub-periods, 1994–1999 and 1999–2004, are analyzed separately in a working paper version of this study, available on request.

Figure 6. Physician service expenditures per capita by Health Technology Intensity (HTI) and age group, 1994–2004

M. ROHAM ET AL.



MethodData


DiscussionSummary

Limitations

No data on drugs, hospital stays, or rehabilitationImaging and diagnosis services might substitute forknowledge or effort but were accounted for in our studyNot enough years to study services by year it waslaunched.No data on outcomes: we cannot tell whether extra-costsare warranted or not.



MethodData


DiscussionSummary

Conclusions

Technology is clearly a main driverBut it is linked to age: more high-tech services meansspending more concentrated on the elderly.Can be due to expansion effect of innovation (less invasivetype of care easier to provide the elderly), or changes inlife expectancy at older ages (greater ability to benefit), orto R&D being geared toward older patients.



MethodData


DiscussionSummary

Summary

Technology major driver of spending: tsunamiBut technology is linked to ageHigh intensity technological care steepens the age profileof spendingIs it due to expansion or R&D targeting the needs of theelderly?


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