Alberta's Acute Care Funding Project

1992 ◽  
Vol 5 (3) ◽  
pp. 4-11 ◽  
Author(s):  
Philip Jacobs ◽  
Edward M. Hall ◽  
Judith R. Lave ◽  
Murray Glendining

Alberta initiated the Acute Care Funding Project (ACFP) in 1988, a new hospital funding system that institutes case mix budgeting adjustments to the global budget so that hospitals can be treated more equitably. The initiative is a significant departure in principle from the former method of funding. The ACFP is summarized and critiqued, and focuses on the inpatient side of the picture. The various elements of the project are discussed, such as the hospital performance index, the hospital performance measure, the Refined Diagnostic Related Group, case weights, typical and outlier cases, and the costing mechanisms. Since its implementation, the ACFP has undergone substantial changes; these are discussed, as well as some of the problems that still need to be addressed. Overall, the system offers incentives to reduce length of stay and to increase the efficiency with which inpatient care is provided.

1995 ◽  
Vol 8 (2) ◽  
pp. 17-22 ◽  
Author(s):  
Philip Jacobs ◽  
Edward M. Hall ◽  
Richard H.M. Plain

From 1990 until 1994 Alberta Health adjusted the acute care portion of hospital budgets based on a case mix index, initially called the Hospital Performance Index (HPI). The HPI formula method was a temporary measure; in November 1993, Alberta Health announced that, commencing in 1994, hospitals would be funded on a prospective basis, although they would still use the core of the HPI in the setting of funding rates. The creation of 17 health regions in June 1994 created the need for a new system of funding which would supplant the modified prospective system. In this paper we review the evolution of the HPI plan and its individual components — patient data, patient classification, funding weights, inpatient costs and adjustment factors.


2007 ◽  
Vol 13 (1) ◽  
pp. 7-9 ◽  
Author(s):  
Femi Oyebode

Payment by results, a system for paying healthcare trusts, is intended as a fair and consistent basis for hospital funding. It relies on a national tariff structured around a case-mix measure known as healthcare resource groups. It is often argued that if payment by results works as planned, the National Health Service will become more efficient and productive. However, the use of a case-mix measure, the healthcare resource group, which derives from the diagnostic related (or diagnosis-related) group, has attendant problems. These include the risk that the payment structure will be inaccurate, unfair and liable to cause the financial destabilisation of trusts. There is also the risk that healthcare institutions will falsify patient classifications (‘up-coding’) to ensure higher remuneration. It has been argued that payment by results may be particularly unsuited to psychiatry. The ability of healthcare resource groups to accurately predict resource use in psychiatry is doubtful. In conclusion, mental health trusts will need to adapt to payment by results but there will inevitably be losers.


BMJ Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. e041648
Author(s):  
Omid Fekri ◽  
Edgar Manukyan ◽  
Niek Klazinga

ObjectivesTo examine the association between hospital deaths (hospital standardised mortality ratio, HSMR), readmission, length of stay (LOS) and eight hospital characteristics.DesignLongitudinal observational study.SettingA total of 119 teaching and large-sized hospitals in Canada between fiscal years 2013–2014 and 2017–2018.ParticipantsAnalysis focused on indicator results and characteristics of individual Canadian hospitals.Primary and secondary outcomesHospital deaths (HSMR); all patients readmitted to hospital; average LOS and a series of eight hospital characteristic summary measures: number of acute care hospital stays; number of acute care beds; number of emergency department visits; average acute care resource intensity weight; total acute care resource intensity weight; hospital occupancy rate; patients admitted through the emergency department (%); patient days in alternate level of care (%).ResultsComparing 2013–2014 to 2017–2018, hospital deaths (HSMR) largely declined, while readmissions increased; 69% of hospitals decreased their hospital deaths (HSMR), while 65% of hospitals increased their readmissions rates. A greater proportion of community-large hospitals (31%, n=14) improved on both hospital deaths (HSMR) and readmission compared to Teaching hospitals (13.9%, n=5). Hospital deaths (HSMR), readmission and LOS largely showed very weak and non-significant correlations. LOS was largely positively and statistically significantly correlated with the suite of eight hospital characteristics. Hospital deaths (HSMR) was largely negatively (not statistically significantly) correlated with the hospital characteristics. Readmission was largely not statistically significantly correlated and showed no clear pattern of correlation (direction) with hospital characteristics.ConclusionsExamining publicly reported hospital performance results can reveal meaningful insights into the association among outcome indicators and hospital characteristics. Good or bad hospital performance in one care domain does not necessarily reflect similar performance in other care domains. Thus, caution is warranted in a narrow use of outcome indicators in the design and operationalisation of hospital performance measurement and governance models (namely pay-for-performance schemes). Analysis such as this can also inform quality improvement strategies and targeted efforts to address domains of care experiencing declining performance over time; further granular subdivision of the analyses, for example, by hospital peer-groups, can reveal notable differences in performance.


1991 ◽  
Vol 4 (4) ◽  
pp. 22-32 ◽  
Author(s):  
Charles K. Botz

The construct of Resource Intensity Weights (RIWs) contains implicit financial incentives if they are used for hospital funding purposes. This paper compares the RIW (funding) credit to the expected average per diem cost for each of the new subcategories (typicals, deaths, transfers, signouts and outliers) of Case Mix Groups (CMGs). RIW construction, and inherent incentives for a hospital to reduce costs or length of stay(LOS), differ significantly for each subcategory. At some point or points in a patient's LOS, when RIW credit equals case cost, RIWs are incentive neutral. However, it can also be demonstrated that RIW credit is not generally congruent with average costs on each day of a patient's stay. Financial incentives (both positive and negative) arise when RIW credit and costs differ. Only by being fully aware of these differences can hospitals determine how to respond to the introduction of case mix funding to maintain financial viability. Funding agencies, too, need to appreciate the sometimes subtle policy implications that come with the adoption of RIWs for funding purposes.


2018 ◽  
Vol 17 (3) ◽  
pp. 120-120
Author(s):  
MNT (Marjolein) Kremers ◽  
◽  
Prabath WB Nanayakkara ◽  

In recent years we indeed have witnessed an increasing demand on healthcare services coupled with spiraling healthcare costs forcing us towards identifying factors and interventions leading to greater healthcare efficiency. The case mix of our ED patients is changing with an increase in the number of the elderly needing acute (hospital) care, often suffering from multiple comorbidities leading to simple problems becoming easily complex and demanding admission. Partly due to this changing case mix, acute bed capacity is under serious pressure leading to ED stagnation and increased waiting times internationally. When the ED is at its capacity, acute physicians have to make choices how to divide the few available beds. Are we able to predict who needs a bed the most and make justified decisions? Which patient can wait at the ED before admission and which ones can’t? The study of Byrne et al. in this issue focused on the association between ED waiting times and clinical outcomes in Ireland, measured by 30 days mortality, using patient data of admitted acute medical patients collected from 2002 until 2017. High Risk Score patients with a longer waiting time at the ED, appear to have an increased risk on mortality. It is therefore necessary to identify these patients early and prioritize their hospital admission. However, to our knowledge, the used risk score isn’t implemented in daily practice. In 2012 the National Early Warning Score (NEWS) has been broadly implemented and it would be of interest to know whether the used retrospective Risk Score using laboratory data accord to the NEWS. Curiously, in this study, patients in all three MTS urgent categories with <4 hours waiting time, have a higher risk on mortality than patients experiencing a longer waiting time. What’s the cause of this effect? Are patients so severely ill that urgent treatment and admission can’t change the adverse outcome? Or is it possible that all three urgent MTS categories identify patients who are sicker with a higher chance of dying? Intriguingly, in Ireland the mortality amongst admitted acute medical patients decreased since 2002 by 1.3%. An important question remained unanswered by Byrne et al: why has this mortality decreased? Has the severity of the diseases by urgently admitted patients diminished? Has the treatment for acute medical patients been improved? Don’t severely ill patients come to the ED anymore, due to proper advanced care planning? In contrast to the decreased mortality, the median waiting times >6 hours have increased by 50%, from 10 to 15 hours. What caused this increase? What happened in the acute care in Ireland? Have other European countries experienced the same effect or can’t the Irish results not being extrapolated to other European acute care systems? For example, in the Netherlands, the total number of patients being seen at the ED has decreased and stabilised in the last years, although the number of acute medical patients, especially elderly, is increasing. During the last flu season patients we were faced with ED closures, long length of stay and overnight ED stays due to the lack of beds in-hospital. However, waiting hours >12 hours at the ED are rare in Dutch EDs. A key factor in constraining the patient flow to the ED is the well-functioning primary care system with adequate out of office hours care by GP-posts. When a GP post is placed at an ED, GPs treat 75% of the self-referred patient, which is safe and cost-effective. Due to this the ED`s can concentrate on the sick patients who need urgent care. Despite the decreased patient flow to the ED in the Netherlands, the organisation of the acute care has gained much attention of policy makers, media and health care professionals due to frequent ED closures and stagnation in some regions in the Netherlands. Recently, a prediction model for hospital admission in a mixed ED population has been established by using data directly available after triage, aiming to use for shortening the Length of Stay (LOS) at the ED. A computerised tool calculates admission probability for any patient at the time of triage by using age, triage category, arrival mode and main symptom. It demonstrates that different European countries are facing the same issues and are trying to optimize the acute care with some overlapping focus. We believe that at a time where the demand on acute care is increasing, it’s essential to pay attention to the organisation of acute care so that high-quality care is guaranteed and the available resources should be handled efficiently. Studies such as executed by Byrne et al. contribute to this topic and provide lessons which can be learned internationally. We need tools to identify sick patients who need properly care on time and acute physicians can play a central role in developing these tools.


2021 ◽  
Vol 10 (2) ◽  
pp. e001230
Author(s):  
Michael Reid ◽  
George Kephart ◽  
Pantelis Andreou ◽  
Alysia Robinson

BackgroundRisk-adjusted rates of hospital readmission are a common indicator of hospital performance. There are concerns that current risk-adjustment methods do not account for the many factors outside the hospital setting that can affect readmission rates. Not accounting for these external factors could result in hospitals being unfairly penalized when they discharge patients to communities that are less able to support care transitions and disease management. While incorporating adjustments for the myriad of social and economic factors outside of the hospital setting could improve the accuracy of readmission rates as a performance measure, doing so has limited feasibility due to the number of potential variables and the paucity of data to measure them. This paper assesses a practical approach to addressing this problem: using mixed-effect regression models to estimate case-mix adjusted risk of readmission by community of patients’ residence (community risk of readmission) as a complementary performance indicator to hospital readmission rates.MethodsUsing hospital discharge data and mixed-effect regression models with a random intercept for community, we assess if case-mix adjusted community risk of readmission can be useful as a quality indicator for community-based care. Our outcome of interest was an unplanned repeat hospitalisation. Our primary exposure was community of residence.ResultsCommunity of residence is associated with case-mix adjusted risk of unplanned repeat hospitalisation. Community risk of readmission can be estimated and mapped as indicators of the ability of communities to support both care transitions and long-term disease management.ConclusionContextualising readmission rates through a community lens has the potential to help hospitals and policymakers improve discharge planning, reduce penalties to hospitals, and most importantly, provide higher quality care to the people that they serve.


Author(s):  
Jonathan Plante ◽  
Karine Latulippe ◽  
Edeltraut Kröger ◽  
Dominique Giroux ◽  
Martine Marcotte ◽  
...  

Abstract Older persons experiencing a longer length of stay (LOS) or delayed discharge (DD) may see a decline in their health and well-being, generating significant costs. This review aimed to identify evidence on the impact of cognitive impairment (CI) on acute care hospital LOS/DD. A scoping review of studies examining the association between CI and LOS/DD was performed. We searched six databases; two reviewers independently screened references until November 2019. A narrative synthesis was used to answer the research question; 58 studies were included of which 33 found a positive association between CI and LOS or DD, 8 studies had mixed results, 3 found an inverse relationship, and 14 showed an indirect link between CI-related syndromes and LOS/DD. Thus, cognitive impairment seemed to be frequently associated with increased LOS/DD. Future research should consider CI together with other risks for LOS/DD and also focus on explaining the association between the two.


2012 ◽  
Vol 60 (8) ◽  
pp. 1585-1587 ◽  
Author(s):  
Olivier Beauchet ◽  
Samantha Remondière ◽  
Micheline Mahé ◽  
Florence Repussard ◽  
Frederic Decavel ◽  
...  

1998 ◽  
Vol 21 (1) ◽  
pp. 37 ◽  
Author(s):  
Don Hindle ◽  
Pieter Degeling ◽  
Ono Van Der Wel

The Diagnosis Related Group classification has provided an excellent basis forenhancing the equity of resource allocation between public acute hospitals. However,it underestimates the higher levels of severity and consequent costliness of referralhospitals.This paper describes a practical way of measuring within-DRG variations in severity,which can be used to increase the precision of casemix-based funding. It involves theregression of length of stay against the numbers of significant diagnoses and procedures,and hence the prediction of additional justified costs. An example is given of itsapplication to data from South Australian public hospitals.


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