New Healthcare Policy Challenges

Diagnosis-Related Group’s Negative Effects

In November 2022 new way of reimbursing medical services within the framework of the Universal Healthcare Program, the so-called Diagnosis Related Groups (DRG), was instituted. This reimbursement method entails dividing medical cases into groups and determining the care price for these groups. Therefore, starting in November, the cost of medical care was predetermined for 510 groups within the budget program. This payment method from the universal healthcare program implies a rejection of the individual approach and is based on the unification of diagnoses. In particular, the expectation is that medical institutions use similar resources to treat patients with clinically similar inpatient cases (diagnosis). Pricing is determined based on retrospective analysis. Specifically, the medical service price is determined by multiplying the inflation-indexed price per inpatient unit by the weight of the same class. Based on this principle, by 2022, the base rate for a single medical case was defined at 1 959.9 GEL.

For example, the budgetary program will reimburse 17 857.0 GEL for the heart valve surgery of a person beneficiary the Universal Healthcare because the value weight of this group is 9.1112 (17 857.0 = 1 959.9 x 9.112). The amount of compensation for the femur fracture treatment will be 1 313.7 GEL because the value weight for such a diagnosis is 0.6703 (1 313.7 = 1 959.9 x 0.6703). However, a co-payment component should be considered for certain groups of people benefiting from Universal Healthcare. For illustration, suppose a person who is a beneficiary of the healthcare program, but has a 10.0% co-payment, breaks her femur in case of receiving treatment services from a medical institution. In that case, she will pay 131.4 GEL, and the state budget will pay the remaining 1 182.3 GEL.

This method of financing care was first developed at Yale University and was integrated into the US healthcare system in the 1980s (Fetter et al., 1976). In the following years, a similar method was developed in European countries (Schreyögg et al., 2006; Quentin et al., 2013; Tan et al., 2014). Therefore, there is empirical literature that studies the results of implementing DRG, where the main line of inquiry is the effect of DRG on the quality of medical service.

In Georgia, discussions about implementing the DRG method started before the Pandemic, when the government had to deal with rising healthcare costs and deficit problems in the healthcare program (Rakviashvili & Shamugia, 2019). On the one hand, the rising cost of the Universal Healthcare Program is due to opportunistic behaviour, which is more expressed in the hospital sector. Namely, Universal Healthcare is associated with longer hospitalisation periods (Rakviashvili & Shamugia, 2019). Therefore, implementing a new method of financing was a response to the rising costs of the budgetary healthcare program.

However, this is not the first attempt at cost reduction since, in 2017, some groups of people were excluded from the Universal Healthcare Program, and a differentiated approach was taken for them. Namely, the copayment system was implemented. This, however, could not reduce the tendency of rising costs, and the deficit still needs to be eliminated. Moreover, these efforts reduced the increasing tendency of rising costs only for the year, but the same problem resurfaced with new intensity in the following years (see Graph 2 and Graph 3). Therefore, at the end of 2019, a price was determined for various medical services, known to the public as the “520th decree”.

Apart from the budget programs, rising costs can be observed in the total expenditures of the healthcare program (Rakviashvili & Shamugia, 2019). This is not a uniquely Georgian phenomenon nor endemic to developing nations. Rising healthcare costs can be observed globally (see Graph 1), and the instability of Universal Healthcare programs is a challenge for almost every developed nation (OECD, 2021) because the growth of their real economy lags behind rising healthcare costs (see Graph 4  and Graph 5). Therefore, the healthcare system creates high fiscal risks. It should also be noted that in developing nations, healthcare costs are rising faster compared to the developed world (WHO, 2018). Without taking the recent Pandemic into account, the rise in healthcare costs can be explained by implementing modern technologies for treatment. This increases the cost of service (Chernew et al., 1998; Chernew & Newhouse, 2011; Chandra & Skinner, 2012), increasing life expectancy because elderly persons require more medical care (Gerdtham, 1993; Breyer et al., 2010; de Meijer et al., 2013); economic development because due to increasing income, individuals want to spend more on healthcare (Newhouse, 1977; Wildavsky, 1979; Hall & Jones, 2007).


Diagnosis-Related Groups Effects

Although the DRG method is widely popular, it cannot ameliorate all the problems faced by the healthcare system. There appears to be empirical proof that this method can help reduce costs and average hospitalisation duration (Kahn, 1990; Louis et al., 1999; Kwon, 2003; Tsai et al., 2005; Schreyögg et al., 2006; Baroni et al., 2020). However, some studies highlight its negative aspects, namely a decreased quality of care. When the prices are predetermined, clinics try to minimise costs to avoid a reduction in profit margin. This leads to a drop in the intensity and quality of care (Kwon, 2003; Farrar et al., 2009; Paddock et al., 2007; Cutler, 1995; Hamada et al., 2012). There are also cases of discrimination in various circumstances when providers of medical services prefer to treat patients that are more “profitable” (Monrad Aas, 1995; Ellis, 1998). Because of DRGs, medical providers are incentivised to treat more profitable diseases and overlook other services or reduce their scope. On the other hand, there are problems such as hospitalisation duration and diagnosis manipulation. Clinics sometimes are incentivised to move patients to more expensive groups (Eichenwald, 2003; Dafny, 2005). Also, due to this kind of financing, clinics seem to reduce average hospitalisation duration at the expense of short-term stationeries (Norton et al., 2002; Pongpirul et al., 2011). For instance, In Belgium, this kind of policy led to a 42% increase in one-day hospitalisation (Perelman & Closon, 2007).

Implementation of the DRG method could reduce existing opportunistic behaviour. For instance, within the framework of Universal Healthcare, hospitalisation duration could decrease in the short term; however, more severe problems could arise in the long run because healthcare providers will have new incentives. Considering general experience, healthcare providers in Georgia could also reduce treatment intensity and quality of care due to price fixing. On the other hand, the proper functioning of such a complex system of financing requires regular systemic analysis. Thus, maintaining such a policy requires highly qualified human resources, a lack of which could be observed back in 2019 when price fixing on some medical services was introduced. It should also be noted that if complications associated with Universal Healthcare programs emerge, the healthcare system could be sent into a regulatory spiral. Therefore, introducing a more complex regulatory system would lead to more long-term complications, which could give rise to a demand for even more regulatory mechanisms.



Barouni, M., Ahmadian, L., Anari, H. S., & Mohsenbeigi, E. (2020). Investigation of the impact of DRG-based reimbursement mechanisms on quality of care, capacity utilisation, and efficiency- A systematic review. International Journal of Healthcare Management, 14(4), 1463–1474.

Boyd H. Gilman. (2000). Hospital response to DRG refinements: the impact of multiple reimbursement incentives on inpatient length of stay. Health Economics.

Breyer, F., Costa-Font, J., & Felder, S. (2010). Ageing, health, and health care. Oxford Review of Economic Policy, 26(4), 674–690.

Chandra, A., & Skinner, J. (2012). Technology Growth and Expenditure Growth in Health Care. Journal of Economic Literature, 50(3), 645–680.

Chernew, M. E., & Newhouse, J. P. (2011). Health Care Spending Growth. Handbook of Health Economics, 1–43.

Chernew, M. E., Hirth, R. A., Sonnad, S. S., Ermann, R., & Fendrick, A. M. (1998). Managed Care, Medical Technology, and Health Care Cost Growth: A Review of the Evidence. Medical Care Research and Review, 55(3), 259–288.

Cutler, D. M. (1995). The Incidence of Adverse Medical Outcomes Under Prospective Payment. Econometrica, 63(1), 29.

Dafny, L. S. (2005). How Do Hospitals Respond to Price Changes? American Economic Review, 95(5), 1525–1547.

Daniel Z. Louis, E J Yuen, M Braga, Americo Cicchetti, Carol Rabinowitz, C Laine, & Joseph S. Gonnella. (1999). Impact of a DRG-based hospital financing system on quality and outcomes of care in Italy. Health Services Research, 34(1 Pt 2), 405–415.

de Meijer, C., Wouterse, B., Polder, J., & Koopmanschap, M. (2013). The effect of population ageing on health expenditure growth: a critical review. European Journal of Ageing, 10(4), 353–361. 

Eichenwald K. (2003). Operating Profits: Mining Medicare; How One Hospital Benefited on Questionable Operations. (2003, August 12). Retrieved from

Ellis, R. P. (1998). Creaming, skimping and dumping: provider competition on the intensive and extensive margins. Journal of Health Economics, 17(5), 537–555.

Ellis, R. P., & McGuire, T. G. (1996). Hospital response to prospective payment: Moral hazard, selection, and practice-style effects. Journal of Health Economics, 15(3), 257–277.

Farrar, S., Yi, D., Sutton, M., Chalkley, M., Sussex, J., & Scott, A. (2009). Has payment by results affected the way that English hospitals provide care? Difference-in-differences analysis. BMJ, 339(aug27 2), b3047–b3047.

Fetter, R. B., Thompson, J. D., & Mills, R. E. (1976). A system for cost and reimbursement control in hospitals. The Yale journal of biology and medicine, 49(2), 123–136.

Gerdtham, U. G. (1993). The impact of ageing on health care expenditure in Sweden. Health Policy, 24(1), 1–8. 

Hall, R. E., & Jones, C. I. (2007). The Value of Life and the Rise in Health Spending. The Quarterly Journal of Economics, 122(1), 39–72. 

Hamada, H., Sekimoto, M., & Imanaka, Y. (2012). Effects of the per diem prospective payment system with DRG-like grouping system (DPC/PDPS) on resource usage and healthcare quality in Japan. Health Policy, 107(2–3), 194–201.

Kahn, K. L. (1990). Comparing Outcomes of Care Before and After Implementation of the DRG-Based Prospective Payment System. JAMA: The Journal of the American Medical Association, 264(15), 1984.

Kwon, S. (2003). Payment system reform for health care providers in Korea. Health Policy and Planning, 18(1), 84–92.

Liang, L. L. (2014). Do Diagnosis-Related Group-Based Payments Incentivise Hospitals to Adjust the Output Mix? Health Economics, 24(4), 454–469.

Monrad Aas, I. (1995). Incentives and financing methods. Health Policy, 34(3), 205–220.

Newhouse, J. P. (1977). Medical-Care Expenditure: A Cross-National Survey. The Journal of Human Resources, 12(1), 115.

Norton, E. C., Van Houtven, C. H., Lindrooth, R. C., Normand, S. L. T., & Dickey, B. (2002). Does prospective payment reduce inpatient length of stay? Health Economics, 11(5), 377–387.

OECD. (2021). Health expenditure by financing scheme.

Paddock, S. M., Escarce, J. J., Hayden, O., & Buntin, M. B. (2007). Did the Medicare Inpatient Rehabilitation Facility Prospective Payment System Result in Changes in Relative Patient Severity and Relative Resource Use? Medical Care, 45(2), 123–130.

Parkinson, B., Meacock, R., & Sutton, M. (2019). How do hospitals respond to price changes in emergency departments? Health Economics, 28(7), 830–842.

Perelman, J., & Closon, M. C. (2007). Hospital response to prospective financing of in-patient days: The Belgian case. Health Policy, 84(2–3), 200–209.

Pongpirul, K., Walker, D. G., Rahman, H., & Robinson, C. (2011). DRG coding practice: a nationwide hospital survey in Thailand. BMC Health Services Research, 11(1).

Rakviashvili, A., & Shamugia, E. (2019). Analysis of the Reform of Universal Healthcare Programme. Gnomon Wise - Research Institute.

Rakviashvili, A., & Shamugia, E. (2020). Analysis of Georgia’s Universal Healthcare System and Ongoing Reforms. Gnomon Wise - Research Institute.

Schreyögg, J., Stargardt, T., Tiemann, O., & Busse, R. (2006). Methods to determine reimbursement rates for diagnosis-related groups (DRG): A comparison of nine European countries. Health Care Management Science, 9(3), 215–223.

Tsai, Y. W., Chuang, Y. C., Huang, W. F., See, L. C., Yang, C. L., & Chen, P. F. (2005). The effect of changing reimbursement policies on quality of in-patient care, from fee-for-service to prospective payment. International Journal for Quality in Health Care, 17(5), 421–426.

WHO. (2018). Public Spending on Health: A Closer Look at Global Trends.

Wildavsky, A. (1979). Doing Better and Feeling Worse: The Political Pathology of Health Policy. The Art and Craft of Policy Analysis, 284–308.


See the attached file for the full document with relevant graphs and explanations.


Egnate Shamugia