Capturing patients' needs in casemix: a systematic literature review on the value of adding functioning information in reimbursement systems.

BACKGROUND: Contemporary casemix systems for health services need to ensure that payment rates adequately account for actual resource consumption based on patients' needs for services. It has been argued that functioning information, as one important determinant of health service provision and resource use, should be taken into account when developing casemix systems. However, there has to date been little systematic collation of the evidence on the extent to which the addition of functioning information into existing casemix systems adds value to those systems with regard to the predictive power and resource variation explained by the groupings of these systems. Thus, the objective of this research was to examine the value of adding functioning information into casemix systems with respect to the prediction of resource use as measured by costs and length of stay. METHODS: A systematic literature review was performed. Peer-reviewed studies, published before May 2014 were retrieved from CINAHL, EconLit, Embase, JSTOR, PubMed and Sociological Abstracts using keywords related to functioning ('Functioning', 'Functional status', 'Function*, 'ICF', 'International Classification of Functioning, Disability and Health', 'Activities of Daily Living' or 'ADL') and casemix systems ('Casemix', 'case mix', 'Diagnosis Related Groups', 'Function Related Groups', 'Resource Utilization Groups' or 'AN-SNAP'). In addition, a hand search of reference lists of included articles was conducted. Information about study aims, design, country, setting, methods, outcome variables, study results, and information regarding the authors' discussion of results, study limitations and implications was extracted. RESULTS: Ten included studies provided evidence demonstrating that adding functioning information into casemix systems improves predictive ability and fosters homogeneity in casemix groups with regard to costs and length of stay. Collection and integration of functioning information varied across studies. Results suggest that, in particular, DRG casemix systems can be improved in predicting resource use and capturing outcomes for frail elderly or severely functioning-impaired patients. CONCLUSION: Further exploration of the value of adding functioning information into casemix systems is one promising approach to improve casemix systems ability to adequately capture the differences in patient's needs for services and to better predict resource use.

The Impact of COVID-19 on Hospital Admissions in Croatia.

Background: The COVID-19 pandemic disrupted hospital care, as hospitals had to deal with a highly infectious virus, while at the same time continuing to fulfill the ongoing health service needs of their communities. This study examines the direct effects of COVID-19 on the delivery of inpatient care in Croatia. Materials and Methods: The research is a retrospective, comparative analysis of the hospital admission rate across all Diagnosis Related Group (DRG) classes before and during the pandemic. It is based on DRG data from all non-specialized acute hospitals in Croatia, which account for 96% of national inpatient activity. The study also used COVID-19 data from the Croatian Institute of Public Health (CIPH). Results: The results show a 21% decrease in the total number of admissions [incident rate ratio (IRR) 0.8, p < 0.0001] across the hospital network during the pandemic in 2020, with the greatest drop occurring in April, when admissions plunged by 51%. The decrease in activity occurred in non-elective DRG classes such as cancers, stroke, major chest procedures, heart failure, and renal failure. Coinciding with this reduction however, there was a 37% increase (IRR 1.39, p < 0.0001) in case activity across six COVID-19 related DRG classes. Conclusions: The reduction in hospital inpatient activity during 2020, can be attributed to a number of factors such as lock-downs and quarantining, reorganization of hospital operations, the rationing of the medical workforce, and the reluctance of people to seek hospital care. Further research is needed to examine the consequences of disruption to hospital care in Croatia. Our recommendation is to invest multidisciplinary effort in reviewing response procedures to emergencies such as COVID-19 with the aim of minimizing their impact on other, and equally important community health care needs.

A new clinical complexity model for the Australian Refined Diagnosis Related Groups.

BACKGROUND: The Australian Refined Diagnosis Related Groups (AR-DRG) underwent a major review in 2014 with changes implemented in Version 8.0 of the classification. The core to the changes was the development of a new methodology to estimate the Diagnosis Complexity Level (DCL) and to aggregate the complexity level of individual diagnoses to the complexity of an entire episode, resulting in an Episode Clinical Complexity Score (ECCS). This paper provides an overview of the new methodology and its application in Version 8.0. METHOD: The AR-DRG V8.0 refinement project was overseen by a Classifications Clinical Advisory Group and a Diagnosis Related Groups (DRG) Technical Group. Admitted Patient Care National Minimum Dataset and the National Hospital Cost Data Collection were used for complexity modelling and analysis. RESULT: In total, Version 8.0 comprised 807 DRGs, including 3 error DRGs. Of the 321 Adjacent DRGs (ADRGs) that had a split, 315 ADRGs used ECCS as the only splitting variable while the remaining 6 ADRGs used splitting variables other than ECCS: 2 used age and 4 used transfer. DISCUSSION AND CONCLUSION: A new episode clinical complexity (ECC) model was developed and introduced in AR-DRG V8.0, replacing the original model introduced in the 1990s. Clear AR-DRG structure principles were established for revising the system. The new complexity model is conceptually based and statistically derived, and results in an improved relationship with actual variations in resource use due to episode complexity.

Risk adjustment policy options for casemix funding: international lessons in financing reform.

This paper explores modified hospital casemix payment formulae that would refine the diagnosis-related group (DRG) system in Victoria, Australia, which already makes adjustments for teaching, severity and demographics. We estimate alternative casemix funding methods using multiple regressions for individual hospital episodes from 2001 to 2003 on 70 high-deficit DRGs, focussing on teaching hospitals where the largest deficits have occurred. Our casemix variables are diagnosis- and procedure-based severity markers, counts of diagnoses and procedures, disease types, complexity, day outliers, emergency admission and "transfers in." The results are presented for four policy options that vary according to whether all of the dollars or only some are reallocated, whether all or some hospitals are used and whether the alternatives augment or replace existing payments. While our approach identifies variables that help explain patient cost variations, hospital-level simulations suggest that the approaches explored would only reduce teaching hospital underpayment by about 10%. The implications of various policy options are discussed.

The effect of increased private health insurance coverage on Victorian public hospitals.

It was anticipated that the recent reforms to private health insurance arrangements would reduce the demand pressures on Australian public hospitals. However, this has not been demonstrated by trends in elective surgery waiting lists in Victorian public hospitals. Moreover, it appears that the increased caseload assumed by Victorian private hospitals since the reforms took effect mainly reflects an increase in low cost same day episodes.

ICF and casemix models for healthcare funding: use of the WHO family of classifications to improve casemix.

PURPOSE: Casemix models for funding activity in health care and assessing performance depend on data based on uniformity of resource utilisation. It has long been an ideal to relate the measure of value more to patient outcome than output. A problem frequently expressed by clinicians is that measures of activity such as Functional Independence Measure (FIM) and Barthel Index scores may not sufficiently represent the aspirations of patients in many care programs. METHOD: Firstly, the key features of the International Classification of Functioning, Disability and Health are outlined. Secondly, the use of ICF dimensions in Australia and other countries is reviewed. Thirdly, a broader set of domains with potential for casemix funding models and performance reporting is considered. RESULTS: In recent years, the ICF has provided a more developed set of domains against which outcome goals can be expressed. Additional dimensions could be used to supplement existing data. Instances of developments in this area are identified and their potential discussed. CONCLUSIONS: A well-selected set of data items representing the broader dimensions of outcome goals may provide the ability to more meaningfully and systematically measure the goals of both curative and rehabilitation care against which outcome should be measured. More information about patient goals may be needed.

Attendance rates and outcomes of cardiac rehabilitation in Victoria, 1998.

OBJECTIVE: To describe the patterns of use of cardiac rehabilitation in Victoria and to assess whether the survival benefits predicted in clinical trials have been realised in the community. DESIGN: Cohort study based on data linkage. PARTICIPANTS: All patients admitted for acute myocardial infarction (AMI), coronary artery bypass grafting (CABG) or percutaneous transluminal coronary angioplasty (PTCA) in Victoria in 1998 (n = 12821). INTERVENTIONS: Attendance at one of 66 participating outpatient cardiac rehabilitation centres in Victoria. MAIN OUTCOME MEASURES: Rates of attendance at rehabilitation based on key factors such as diagnosis, age, sex, and comorbidity. Five-year survival for attendees compared with non-attendees. RESULTS: Rates of participation in rehabilitation were 15% for AMI, 37% for CABG, and 14% for PTCA. Rehabilitation attendance rates dropped sharply after 70 years of age. Attendees had a 35% improvement in 5-year survival (hazard ratio for death associated with rehabilitation attendance, 0.65 [95% CI, 0.56-0.75]). CONCLUSIONS: Attendance rates at cardiac rehabilitation are suboptimal, even though attendance confers a clinically significant difference in 5-year survival. The elderly, women, and those with comorbid conditions may benefit measurably from increased rates of attendance.