Regional Variation in healthcare costs in South Africa Linda Kemp - - PowerPoint PPT Presentation

Regional Variation in healthcare costs in South Africa

Linda Kemp Shirley Collie

Agenda

Private healthcare insurance in South Africa The argument for analysing healthcare consumption regionally Methodology applied to obtain South African healthcare drainage districts Methodology to calculate disease burden index Are South African regional healthcare consumption patterns explained by the underlying burden of disease and access to benefits?

• Cost of death in the last six months by region
• Cost efficiency by region
• Supply of beds per region
• Are the regional supply of beds commensurate with the underlying demand
• Is there a relationship between competition and the variation in supply?

Concluding remarks

Agenda

Private healthcare insurance in South Africa The argument for analysing healthcare consumption regionally Methodology applied to obtain South African healthcare drainage districts Methodology to calculate disease burden index Are South African regional healthcare consumption patterns explained by the underlying burden of disease and access to benefits?

• Cost of death in the last six months by region
• Cost efficiency by region
• Supply of beds per region
• Are the regional supply of beds commensurate with the underlying demand
• Is there a relationship between competition and the variation in supply?

Concluding remarks

Private healthcare insurance in South Africa

Public healthcare available to all with cost in line with ability to pay

• Can opt for private cover through medical aid

Legislative framework for medical aids:

• Open enrolment, community rating
• No risk equalisation or mandatory enrolment

Schemes must deal with selective joining and withdrawals

• Different risk profiles for different schemes and benefit options

Reimbursed on a fee for service basis Private healthcare expenditure per insured life has increased 3-4% above inflation for several years There are long terms concerns regarding the affordability and sustainability

• f private healthcare given the regulatory environment

0.0% 0.5% 1.0% 1.5% 2.0% 2.5% 3.0% 3.5% 4.0% 4.5% 5.0% 5.5% 6.0% 6.5% U… 1-4 5-9 10… 15… 20… 25… 30… 35… 40… 45… 50… 55… 60… 65… 70… 75… 80… 85+ U… 1-4 5-9 10… 15… 20… 25… 30… 35… 40… 45… 50… 55… 60… 65… 70… 75… 80… 85+ Female Male Percentage of People Gender and Age Bands

Coverage: Insurable Families

Total Population Current Voluntary Medical Schemes Mandatory from Tax Threshold Mandatory Formal Wage Earners

Private healthcare insurance in South Africa South Africa

• Medical schemes are not-for-profit funders of private healthcare

services

• 8.7 million lives were covered by medical schemes at end of 2012

Discovery Health Medical Scheme

• Roughly 2.5 million lives under administration
• Fastest growing open medical scheme (average growth of 5.5% p.a.

since 2005)

• More than half the lives have been on the scheme for five years or

longer

• Claims data provides opportunity for deep analysis

Agenda

Private healthcare insurance in South Africa The argument for analysing healthcare consumption regionally Methodology applied to obtain South African healthcare drainage districts Methodology to calculate disease burden index Are South African regional healthcare consumption patterns explained by the underlying burden of disease and access to benefits?

• Cost of death in the last six months by region
• Cost efficiency by region
• Supply of beds per region
• Are the regional supply of beds commensurate with the underlying demand
• Is there a relationship between competition and the variation in supply?

Concluding remarks

The argument for regional healthcare analysis

Patients access local healthcare for the majority of their needs

• Secondary and tertiary services may be further away

Patterns of how general practitioners choose to refer to specialists and hospitals allows for consideration of a region as a healthcare system Dartmouth Atlas Project considers variations in how medical resources are distributed and used in the US based on Medicare data

• Improve their understanding of the efficiency and effectiveness of health care systems

Regional variation in cost of providing healthcare can exist due to disease burden, access issues, technology etc. Where variation is not due to disease burden: Dartmouth atlas promotes learning from regions that have attained sustainable growth rates and consumption levels

Agenda

Private healthcare insurance in South Africa The argument for analysing healthcare consumption regionally Methodology applied to obtain South African healthcare drainage districts Methodology to calculate disease burden index Are South African regional healthcare consumption patterns explained by the underlying burden of disease and access to benefits?

• Cost of death in the last six months by region
• Cost efficiency by region
• Supply of beds per region
• Are the regional supply of beds commensurate with the underlying demand
• Is there a relationship between competition and the variation in supply?

Concluding remarks

Obtaining South African Drainage Districts Patients allocated to a district based on where they access the majority of their primary care Hospital referral regions defined as where patients receive the majority of major cardiovascular and neurosurgery care Hospital service areas are defined as areas where at least 60%

• f policyholders receive cardiovascular and neurosurgery care

within the region Adjacent magisterial districts are collapsed into the hospital service areas where the majority of patients receive their care

Obtaining South African Drainage Districts

Agenda

Private healthcare insurance in South Africa The argument for analysing healthcare consumption regionally Methodology applied to obtain South African healthcare drainage districts Methodology to calculate disease burden index Are South African regional healthcare consumption patterns explained by the underlying burden of disease and access to benefits?

• Cost of death in the last six months by region
• Cost efficiency by region
• Supply of beds per region
• Are the regional supply of beds commensurate with the underlying demand
• Is there a relationship between competition and the variation in supply?

Concluding remarks

Development of disease burden index

0.00 1.00 2.00 3.00 4.00 5.00 6.00 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64 66 68 70 72 74 76 78 80 82 84 Axis Title

Indexed costs by age and gender

F M 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 Plan 1 Plan 2 Plan 3 Plan 4 Plan 5 Plan 6 Plan 7 Plan 8 Plan 9

Indexed costs by plan type

Costs Costs adjusted for demographic differences

Development of disease burden index

0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64 66 68 70 72 74 76 78 80 82 84

Females on plan 5 by chronic registration status

Not Registered for a chronic condition Registered for a chronic condition 0.00 0.50 1.00 1.50 2.00 2.50 3.00 Plan 1 Plan 2 Plan 3 Plan 4 Plan 5 Plan 6 Plan 7 Plan 8 Plan 9

Indexed costs adjusted for age, gender and plan by registered chronic status

Not registered for chronic conditions Registered for chronic conditions

Development of disease burden index

10 20 30 40 50 60 70 80 90 Age 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83

Indexed costs for females registered for a chronic condition on plan 5 by RUB

1 2 3 4 5 2 4 6 8 10 12 14 16 18 20 Plan 1 Plan 2 Plan 3 Plan 4 Plan 5 Plan 6 Plan 7 Plan 8 Plan 9

Indexed costs adjusted for age, gender, chronic and plan by RUB

1 2 3 4 5

Disease burden index results

0.00 0.50 1.00 1.50 2.00 2.50 3.00 Plan group 1 Plan group 2 Plan group 3 Plan group 4 Plan group 5 Plan group 6

Disease burden index in 2010 by plan group

0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00 100 300 500 700 900 1100 1300 1500 1711 1721 1731 1741 1751 1761 1771 1800 2000 2200 2400 2600 2800 3000 3200 3400 3600 3800 4000 4210 4310 4330 4420 4510 4610 4710 4730 4820 4910 4930 5010 5030 5050 5070 5200 5311 5321 5331 5341

Case weights for claimed ACG in 2010

Plan Group 2 Plan Group 3 Plan Group 4 Plan Group 5

Disease burden - conclusions

Disease burden is a function of:

• Age
• Gender
• Chronic conditions
• Other clinical interactions
• Access to benefits (including data considerations)

Adjusting for the calculated disease burden allows all

• f these factors to be taken into account

Are South African regional healthcare consumption patterns explained by the underlying burden of disease and access to benefits? Applications

Agenda

Private healthcare insurance in South Africa The argument for analysing healthcare consumption regionally Methodology applied to obtain South African healthcare drainage districts Methodology to calculate disease burden index Are South African regional healthcare consumption patterns explained by the underlying burden of disease and access to benefits?

• Cost of death in the last six months by region
• Cost efficiency by region
• Supply of beds per region
• Are the regional supply of beds commensurate with the underlying demand
• Is there a relationship between competition and the variation in supply?

Concluding remarks

Healthcare costs in the last six months of life

East Rand Johann esburg North & Surroun ds Johann esburg Pretoria Potchef stroom Bloemfo ntein Durban Rustenb urg West Coast & Karoo Cape Peninsu la Nelsprui t Vaal Triangle Maritzb urg Port Elizabet h Polokwa ne Overber g Garden Route East London PLPM 24,508 24,486 23,971 23,415 23,194 19,287 19,186 19,000 18,133 17,210 16,586 16,572 16,233 16,108 14,756 14,072 13,739 12,077 Cost_index 1.19 1.19 1.17 1.14 1.13 0.94 0.93 0.92 0.88 0.84 0.81 0.81 0.79 0.78 0.72 0.68 0.67 0.59

• 5,000

10,000 15,000 20,000 25,000 30,000 0.40 0.50 0.60 0.70 0.80 0.90 1.00 1.10 1.20 1.30

Axis Title

Last 6 months cost index by Tertiary Referral Region

40% 45% 50% 55% 60% 65% 70%

Proportion of deaths in hospital

Agenda

Private healthcare insurance in South Africa The argument for analysing healthcare consumption regionally Methodology applied to obtain South African healthcare drainage districts Methodology to calculate disease burden index Are South African regional healthcare consumption patterns explained by the underlying burden of disease and access to benefits?

• Cost of death in the last six months by region
• Cost efficiency by region
• Supply of beds per region
• Are the regional supply of beds commensurate with the underlying demand
• Is there a relationship between competition and the variation in supply?

Concluding remarks

Regional variation

Proportion of DHMS lives Paid PLPM Disease Burden Index adjusting for access to benefits Paid PLPM Disease Burden Adjusted

Agenda

Private healthcare insurance in South Africa The argument for analysing healthcare consumption regionally Methodology applied to obtain South African healthcare drainage districts Methodology to calculate disease burden index Are South African regional healthcare consumption patterns explained by the underlying burden of disease and access to benefits?

• Cost of death in the last six months by region
• Cost efficiency by region
• Supply of beds per region
• Are the regional supply of beds commensurate with the underlying demand
• Is there a relationship between competition and the variation in supply?

Concluding remarks

Supply of hospital beds

Estimate the demand for hospital beds in South Africa Find areas with oversupply Intervene Estimate impact

Actual beds per referral region

• 1,000

2,000 3,000 4,000 5,000 6,000

Variability in supply of hospital beds

Actual beds per 1,000 lives per region

• 1.00

2.00 3.00 4.00 5.00 6.00

Actual beds per 1,000 lives in 2012

Variability in supply of hospital beds per 1,000 lives

Expected (required) beds methodology

Use ACGs as risk adjustment tool Based on 2008 bed days per 1,000 lives per ACG Calculate required overall bed days in each region for 2012 Assumptions:

• ACG (disease burden) distribution of lives for DHMS is

representative of population

• 2008 provides a good benchmark for hospitalisation need
• f members by ACG

Compare actual bed days per region in 2012 to required Back test for earlier years

ACG model results (70% occupancy) A/E

(2.00) (1.50) (1.00) (0.50)

• 0.50

1.00 1.50 2.00 2.50 2012

Over/under supply of beds per 1,000 lives per region assuming 70% occupancy

Over/under supply of beds at different

• ccupancy rates

Over/under supply of beds per 1,000 lives per region assuming different levels of occupancy

Example Representation Concentration Index Indication JHB & Surrounds Combination 0.28 Moderate concentration East London 100% Life Healthcare 1 High concentration

Herfindahl concentration index

• Measure of competition among hospital networks in regions
• Concentration index measures representation of network by number
• f beds relative to industry

Other

Understanding the impact of competition

Herfindahl concentration index results

Drainage region Concentration index 2012 Major network in region Oversupply of beds in 2012 East London 1.00 Life Healthcare

• 0.61

Polokwane 0.86 Mediclinic

• 1.47

Overberg 0.80 Mediclinic

• 0.06

Potchefstroom 0.55 NHN 1.27 Garden Route 0.54 Mediclinic 0.24 Nelspruit 0.51 Mediclinic

• 0.77

Port Elizabeth 0.50 Netcare

• 1.09

West Coast & Karoo 0.49 Mediclinic 0.27 Durban 0.44 Life Healthcare

• 0.02

Maritzburg 0.42 NHN 2.07 East Rand 0.38 Netcare 0.62 Johannesburg 0.36 Netcare 0.38 Bloemfontein 0.32 NHN 1.67 Vaal Triangle 0.32 Mediclinic 1.79 Rustenburg 0.32 Life Healthcare and Netcare

• 0.49

Johannesburg North & Surrounds 0.28 Netcare

• 0.37

Pretoria 0.26 Even split of networks 0.53 Cape Peninsula 0.25 Even split of networks 0.51 Total 0.25 Even split of networks 0.18

Does competition impact the admission rate?

10% 15% 20% 25% 30% 35% 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 Admission rate

Concentration index

Admission rate Admission rate adjusted for disease burden Linear (Admission rate) Linear (Admission rate adjusted for disease burden)

Competitive High concentration

After adjusting for disease burden, the admission rate is higher in areas with high competition (low concentration)

• 1.00

2.00 3.00 4.00 5.00 6.00 7.00 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 Beds/1,000 lives Concentration index

Does competition impact the supply of beds?

Correlation:

• 60%

High concentration Competitive

More beds in highly competitive areas Is this required based on disease burden?

• 1.00

2.00 3.00 4.00 5.00 6.00 7.00 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 Beds/1,000 lives Concentration index Actual beds per 1,000 lives Required beds per 1,000 lives Linear (Actual beds per 1,000 lives) Linear (Required beds per 1,000 lives)

Does competition impact the supply of beds?

High concentration Competitive

Disease burden does not explain the difference in number of beds between competitive and concentrated areas

Agenda

Private healthcare insurance in South Africa The argument for analysing healthcare consumption regionally Methodology applied to obtain South African healthcare drainage districts Methodology to calculate disease burden index Are South African regional healthcare consumption patterns explained by the underlying burden of disease and access to benefits?

• Cost of death in the last six months by region
• Cost efficiency by region
• Supply of beds per region
• Are the regional supply of beds commensurate with the underlying demand
• Is there a relationship between competition and the variation in supply?

Concluding remarks

Concluding remarks

Understanding referral regions gives insight into healthcare costs and throughput Costs are variable across referral regions Variation in costs may be driven by various underlying factors such as disease burden, supply of beds, concentration and competition mix