Case Studies Flashcards
Newhouse et al (1982)
User charges
RAND Health Experiment
- Tested 14 different types of insurance plans within Medicare across 6 different sites in the US. These plans, which covered over 6,000 individuals, had varying forms of coverage.
o Co-insurance: 0%, 25%, 50%, 95%
o Expenditure limits of 5%, 10% and 15% of household income up to $1000 - Followed up with the families after 5 years.
- Found that per capita spending for people on the free plan (0% co-insurance) was 45% higher than people on the 95% co-insurance plan
- User charges did not impact the quality of care received by individuals between the plans
- Poorest and sickest individuals on the free plan had better health outcomes than the poorest and sickest on other plans
- 10% increase in co-insurance led to a 1-2% drop in healthcare demand
o Reduced the demand for both effective and ineffective care
People did not look for cheaper care, they just forewent care altogether - People on the free plan were more likely to visit their GP and access hospital services
Lagarde and Palmer (2011)
User charges
LMICs
- When user charges were implemented in LMICs results were varied
- People’s use of preventative and curative services generally decreased
- However, when user charges were combined with quality improvements, the use of curative services increased
- When user fees were removed, there was no immediate impact on people’s use of preventative health services
- When user fees were reduced, there was an increase in the use of preventative and curative services
Tamblyn et al (2001)
User charges
US and Canada
Found that cost sharing in pharmaceuticals led to worse health outcomes in the elderly
Canada - user charges
- High user charges for pharmaceuticals
- People who can afford it enrol in voluntary health insurance to cover the cost of the user charges
o This means that the only people paying user charges are low-income who cannot afford it. - Studies have indicated that there are issues with medication adherence as people do not want to pay for their medications
- Trying to raise revenue from low-income as well as incentivising them to forego care means they are not a good method of raising revenue
- No incentive for high income to reduce consumption
US - user charges
- Ties the user charge to the effectiveness of the service. Effective care has low user charge and ineffective has high user charge.
- Encourages patients to select high-value care that leads to better health outcomes
- Used in the US
o Some insurers now offer enrolees reduced user charges for drugs prescribed for certain conditions such as asthma and diabetes, or specific drug groups such as beta blockers.
o This was created because regular user charges failed to grow health spending or increase efficiency
Thomson (2010)
User charges
Value-based limitations have limitations - determining clinical effectiveness and cost-effectiveness is difficult, expensive to implement, individual and patient characteristics can affect clinical effectiveness and all patients are so different
- NHS uses this and allows them to achieve similar outcomes to value-based user charges (Thomson, 2010)
o Free (incentive) to register with doctor, enrol in disease management programs, adhere to medications
o Strong primary care focus
o Specialist care gatekeeping
o Generic prescribing
o QOF focuses on preventative care
Bokour et al (2006)
P4P
- Equal payment to all providers
o Limited incentive to improve
o May encourage collaboration instead of competition - Payments to providers based on individual performance
o Most likely to influence provider behaviour - Payments to practices based on performance
o Less likely to influence provider behaviour but members of practice may rally together to achieve targets - Payments wholly managed by organisation
o Least incentive for individual providers to improve but can lead to system-wide improvements such as investment in training, equipment, processes - Hybrid; mix of individual and provider payments
o Influence individual provider behaviour while also allowing for system-wide changes
Papworth Hospital
P4P
- Flagged by the Care Quality Commission as having an outlier mortality rate
- Responded that based on their own risk-adjusted mortality formulas they had above-average performance
- In their response to CQC proposed reason for inaccurate flagging;
o Data being used by the CQC (Hospital Episode Statistics) was not created to measure clinical effectiveness, staff were inadequatley trained, the data was incomplete, data entry errors
o Argued that analysis did not consider patient risk factors – they serve a high-risk population
o Grouped diagnoses which made mortality comparisons irrelevant since patients are diverse
QOF
P4P
- Provides incentives to GPs in the UK for providing quality care
- Originally 76 clinical indicators for 10 conditions
- Doctors could exclude patients if they were considered to be exceptions, QOF could not accurately demonstrate quality of care
- Benefits
o Minimised inequalities of care
o Reduced readmissions
o Some improvement in chronic condition outcomes - Limitations
o Cost £1 billion, creating significant additional income for GPs
o GPs were already meeting these targets before implementation of QOF which risked crowding out intrinsic motivation
o No impact on mortality
o Payment formulas favoured larger, better resourced hospitals
o Lack of regulation for exemption reporting
o Increased admin load
o Diagnostic codes were sometimes incorrectly specified
o Did not accommodate for multimorbidity
McIllvenan et al (2015)
P4P - HRRP
- Design Benefits
o Readmissions are easy to measure
o Focused on integration between siloes of care within and outside of the hospital, improving patient experience and hopefully outcomes
o Since based on all-cause readmission, incentivised hospitals to consider the patient’s primary condition but also co-morbid, mental, social and environmental conditions that could lead to readmission - Design Limitations
o Readmissions are easier to manipulate than clinical outcomes
o Potential to penalise poorer hospitals; original formula did not account for SES
o Avoiding readmissions may increase mortality
o Hospitals with higher admission rates will likely also have higher readmission rates
o Concerns about root cause attribution; readmission could be due to patient behaviour. Need to be able to determine if the readmission was due to a preventable event
o Concerns for coding manipulation
o Arbitrary time window
Ross (2017)
P4P - HRRP
- reduction in readmission could mainly be attributed to the way hospitals were coding cases
- some evidence suggests that 30-day mortality was declining at a faster rate pre-HRRP when compared to after implementation
Hospital Readmission Reduction Program
P4P
- Created in 2012 to replace a DRG payment system which did not include any consideration of post-discharge care or interventions which would reduce the risk of readmission
- Hospitals were financially penalised if they had higher than expected risk standardised 30 day readmission rates for acute myocardial infarction, heart failure and pneumonia. In 2015 this was expanded to include other conditions
o Readmission rates were adjusted for based on age, sex and co-existing conditions - This approach assumes that readmissions are associated with unfavourable patient outcomes
- HRRP was successful in lowering readmission rates
o Proves that if you incentivise/penalise something you will see more/less of that activity
OECD (2010)
P4P
Rwanda
- Implemented P4P program to address poor performance of public sector health providers
- Prioritised services such as vaccinations, anti-natal care, and strong primary care
- Result was increased activity at primary healthcare centres, better employee participation (less absence, more efficient, participated in more training), increased childhood immunisation, reduced childhood mortality
- Had a strong evaluation program. Other health reforms were rolled out at the same time as P4P and evaluation methodology separated this from P4P to ensure they were monitoring real performance of P4P. OECD 2010 considers this a successful implementation of P4P.
Chile VHI
o People can opt out of the public system into VHI, but the only people that can afford it are the wealthy
Risk segmentation
o Spending in the private sector is much higher than the public despite the people using VHI on average having lower risk
Skewing resources
Germany VHI
o Once individuals reach a certain income level they are able to opt out of public and participate in VHI
o Premiums are risk rated and dependents are not covered so the people who switch to VHI often have a favourable risk profile; male, no dependents, young
o Because premiums are risk rated they rise steeply with age. Noticed that the elderly, old, people with chronic diseases, and those with general poor health were staying in the public program leading to risk segmentation
This went against VHI’s goal and instead placed an extra burden on the public system
o Reforms to mitigate the VHI issues
Only have to be high income for 1 year to be able to enter VHI system
* Making it easier for people to qualify, reducing segmentation
Once in VHI cannot opt out after the age of 55
* Prevent burden on public system
New premiums contain a 10% surcharge that goes towards and ageing reserve which
* Lower the premiums for the elderly in the future
* Make the VHI more stable
Drug prices are held constant between public and private system
* To eliminate the problem of higher prices in the public system
