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Waste not, want not? Healthcare providers are increasingly asking this question as spiraling costs spur greater emphasis on efficiency.

Some are turning to the diagnostic related group (DRG) patient classification system as one solution, but results have been mixed, largely due to inadequate governance.

How does the DRG system compare with alternative provider payment systems such as Fee for Service (FFS), Per Diem, Capitation and Global Budget? In the second entry in a two-part series, RGA explores DRG implementation successes and failures around the world and shares important lessons for providers and insurers.

Five Common DRG Pitfalls

Most commonly known outside the U.S. as the IR-DRG (International Refined DRG), the DRG patient classification system standardizes payments to doctors and hospitals based on the disease being treated, rather than the volume of services provided. The objective is simple: reduce inpatient cost by discouraging unnecessary tests and treatments.

But while the system has been highly successful around the world, it requires a strong governance framework to succeed. Healthcare providers and insurers can learn from the five most common risks that can arise as the result of inadequate oversight:

• Upcoding: Changing diagnosis coding practices and procedures could increase the risk of upcoding, or the fraudulent re-classification of patients by adding non-existent codes to increase reimbursement. For instance, if the compensation for a particular code varies by the level of co-morbidity, some providers may be tempted to use a higher severity code to artificially inflate compensation under the patient classification system.
• Unbundling: A more common phenomenon, unbundling occurs when providers split a single DRG code tied to a set of services into multiple episodes to inflate compensation. For example, two DRG codes relating to two correlated diagnoses, each carrying a different weight under the system, are used instead of one.
• Transfers of Cases: Any DRG launch can involve implementation and adjustment shocks when the initial DRG weighting at first distorts the existing price structures, resulting in provider winners and losers. This trend can become more pronounced if the initial weights were imported from another country and have only been adjusted for relative cost differentials. Providers who are on the losing side will typically optimize by transferring cases into a more highly paid setting. When the DRG patient classification cohabits with fee-for-service outpatient, ambulatory or other cost blocks, legitimate DRG diagnoses can be transferred to an ambulatory setting due to higher compensation. Insurers also have witnessed the “bloody discharge,” where the patients are discharged prior to full health remittance. More generally, there is a risk that DRG implementation may encourage hospitals to increase their activity to maximize hospital revenues through overutilization of outpatient consultations, medications, investigations, and inpatient (IP) readmissions.
• Transfers among regions: When DRG weights are perceived to be providing inadequate compensation, providers have been known to transfer cases from regions having implemented DRG to regions or territories that have not. For instance, there were some cases where some Healthcare Common Procedure Coding System (HCPCS) codes relating to hip replacement were being referred to Dubai for treatment rather than Abu Dhabi due to higher reimbursement levels.
• Patient denials: High-risk patients can be denied care or asked to transfer to other providers due to lack of compensation. While a DRG system encourages providers not to dispense unnecessary services, it can also encourage providers to pursue lower risk patients, or individuals requiring services linked to over-compensation.

Five Risk Mitigation Techniques

For providers seeking a transparent, cost effective and efficient compensation system, DRG offers a very attractive option, but it clearly introduces risks. To address the winners- and-losers syndrome, the DRG weights need to be adjusted periodically on a regular basis, particularly in cases where weights have been imported from another country and adjusted only for cost-differentials. Several key principles can help guide DRG ratemaking and mitigate risks:

• Fair compensation to providers
• Strong governance
• Qualified coders with the strongest sense of ethics, accountability, and responsibility
• Data analytics, including machine learning, and artificial intelligence techniques such as deep learning and natural language processing

How can these principles be achieved? In many markets and countries, authorities are seeking to strengthen governance first by instituting the following practices:

1. Conducting regular audits
2. Employing volume thresholds to discourage unnecessary admissions
3. Applying national budgeting targets on government providers to disincent unbundling or artificially inflating volumes of cases
4. Penalizing re-admission to discourage premature or cost-driven discharges. For instance, in France, if the same patient is re-admitted within 30 days for the same treatment, the hospital must pay a penalty
5. Imposing the DRG system as the major source of hospital revenue by including ambulatory, daycare, or other cost blocks, to disincent case transfers

Every few years, providers or regulators should reevaluate DRG weights to smooth out under-compensation or over-compensation issues, whilst also reducing the likelihood of upcoding. For instance, during a weight review of an actual incurred cost for an upcoded diagnosis, the grouper algorithm will find that if the procedure is over-compensated, weight will be reduced.

In addition, a governance structure that ensures the proper application of DRGs is essential. This framework should also ensure the DRG system is successful in achieving its main objectives of attaining efficiency, encouraging technological innovation and quality of care, and reducing unnecessary costs. It should comprise representatives from providers, payers, regulators, claim administrators, who would meet regularly to discuss issues relating to the application of DRG weights.

There are typically winners and losers on any DRG payment review and different stakeholders will push to get the best outcomes that will improve margins. For instance, providers will push for more compensation for a certain category of DRG if they feel that they are being inadequately compensated. It is pivotal that any DRG review be looked at from a holistic perspective and adjustments be proposed only to services which are being inadequately compensated.

Role of skilled personnel

Of course, the right practices mean nothing without the best people. To succeed with DRG, providers and payers must employ qualified coders with the highest sense of ethics, accountability and responsibility.

Recent experience in the Middle East highlights the challenge. In Abu Dhabi, public hospitals experienced high denial ratios in the first 2 years of DRG implementation. This was particularly attributable to gaps in coder delivery output due to inadequate experience or training. As much as 15%-20% of claims were denied due to incorrect coding. Staff – whether at payer or providers – must be adequately trained to avoid the risk of miscoding incidents.

Usage of data analytics

Data analytics – in particular machine learning – will be of paramount importance to detect unusual claim patterns, inappropriate behaviors from clinicians, members, providers and payers.

The ability to detect upcoding, claims splitting and other behaviors linked to the introduction of DRG will require a sophisticated hands-on approach to look into claims data and come up with conclusive solution.  In addition, these techniques will also be required to detect insurance fraudulent activities through statistical calibration and range analysis. These vital information needs to be fed back into inputs to refine and re-calibrate the DRG weights.

Evaluating DRG Efficiency

Does the DRG system promote efficiency? No billing or patient classification system is perfect, so it is helpful to compare DRG against alternatives based on three major measures of efficiency: level of expenditure, volume of services or activity, and overall quality of care:

Expenditure: DRG is perceived to be more cost-efficient than traditional Fee for Service (FFS) approaches per diagnosis quite simply because FFS encourages healthcare providers to increase activity to maximize revenue. Similarly, the Per Diem system encourages hospitals to require longer patient lengths of stay to increase reimbursement. On the other hand, Global Budget and the Capitation models have the highest cost-efficiency due to annualized expenditure limits.

Activity: The FFS billing system can incent unnecessary tests and treatments, while the Global Budget system often leads providers to curb medical activity to deliver surplus revenue, contributing to lower quality of care. Because the Per Diem system compensates providers at a fixed rate per day, it does not encourage unnecessary activity. In comparison to these systems, the DRG system has a more nuanced impact on the level of activity. On the one hand, it leads to better technical efficiency (as diagnoses are paid a flat amount irrespective of the underlying level of service) but as we saw earlier, it may encourage activities such as unbundling or split services or it may encourage re-admission levels.

Quality: Increasingly, health systems are linking payments to the attainment of quality of care. By this measure, the global budget system encourages the lowest quality of care as the primary focus to attain an allotted and predetermined annual budget. In some countries, providers face a penalty if they fail to meet this threshold, and others have experimented with ‘risk adjustment’ techniques to account for higher cost patient populations. In contrast, FFS is perceived to contribute to the best “quality” as measured by patient satisfaction simply because its underlying reimbursement structure encourages more services, if not necessarily better medical outcomes.  

The DRG system lies between these two extremes. Critics suggest the system can encourage premature patient discharges: in a study in the 1980s, the RAND Corporation estimated a 20% probability that patients would be discharged earlier than clinically necessary. Also, inaccurate categorizations can lead to underpayment and case transfers. It is therefore essential that DRG implementations are closely linked to quality standard metrics to release reimbursement.

Summary

So does DRG work to reduce waste? When viewed across multiple markets, the patient classification system can be an efficient mechanism for provider reimbursement and has been reasonably successful in controlling costs and achieving efficiency without too much compromise on quality.

However, DRG’s success relies on the ratemaking mechanism in place as well as the governance structure at work. Strong governance, coupled with a sound hospital cost information system, can mitigate key risks, enable effective data collection, and ensure a DRG’s successful and smooth operation.