Assessing quality care in kidney disease: The double‐edged sword versus the Gordian knot

Pay-for-performance programs effectiveness in healthcare: the case of the end-stage renal disease quality incentive program

This paper focuses on Medicare's End-Stage Renal Disease Quality Incentive Program (QIP). QIP aims to promote high-quality services in outpatient dialysis facilities by tying their payments to their performance on pre-specified quality measures. In this paper, employing principal-agent theory, we examine the effectiveness of QIP by exploring the changes in various clinical/operational measures when they become a part of the program as a performance measure. We study five QIP quality measures; two are operational: hospitalization and readmission. And three others are clinical: blood transfusion, hypercalcemia, and dialysis adequacy. Overall, we observe a significant improvement in all QIP quality measures after being included in the program, except for readmission. We recommend adjusting the weight and redesigning the readmission measure for Medicare to incentivize providers to reduce readmission. We also discuss establishing care coordination and employing data-driven clinical decision support systems as opportunities for dialysis facilities to improve the care delivery process.

Risk selection reduces efficiency of value-based healthcare

Value-based healthcare aims to improve efficiency and value for patients. Value-based payment models are a form of provider reimbursement to achieve this. Studies on these models have found positive results, but may be biased by unintended consequences, such as risk selection. Risk selection is a multi-dimensional phenomenon that occurs at the patient, hospital, and system level, and is a source of inefficiency and inequality in healthcare. Risk selection may occur because of selection bias in the outcomes that are evaluated and rewarded, or due to the selection of lower cost patients. Risk selection may also stem from professional reputation. The motivation to engage in risk selection may also arise from differences in the meaning of value. To mitigate these unintended consequences, several strategies can be adopted. These include making value-based payment models attractive, but not mandatory, as well as incentivising transparent reporting of best practices, using adequate risk adjustment, expanding performance metrics, and including patient-reported experience measures. Other mitigation strategies could include adopting a mixture of performance measures, using mixed methods of paying physicians, and implementing monitoring and evaluation mechanisms. However, such approaches are not flawless, and the problem may never be fully solved. This perspective serves as a warning for the constant presence of risk selection, as well as informing policy makers, politicians, and organisations implementing VBP models on ways to minimise the possibility of risk selection.

An Environmental Scan of Canadian Quality Metrics for Patients on In-Center Hemodialysis

Background:

Quality metrics or indicators help guide quality improvement work by reporting on measurable aspects of health care upon which improvement efforts can focus. For recipients of in-center hemodialysis (ICHD) in Canada, it is unclear what ICHD quality indicators exist and whether they adequately cover different domains of health care quality.

Objectives:

To identify and evaluate current Canadian ICHD quality metrics to document a starting point for future collaborations and standardization of quality improvement in Canada.

Design:

Environmental scan of quality metrics in ICHD, and subsequent indicator evaluation using a modified Delphi approach.

Setting:

Canadian ICHD units.

Participants:

Sixteen-member pan-Canadian working group with expertise in ICHD and quality improvement.

Measurements:

We classified the existing indicators based on the Institute of Medicine (IOM) and Donabedian frameworks.

Methods:

Each metric was rated by a 5-person subcommittee using a modified Delphi approach based on the American College of Physicians/Agency for Healthcare Research and Quality criteria. We shared these consensus ratings with the entire 16-member panel for additional comments.

Results:

We identified 27 metrics that are tracked across 8 provinces, with only 9 (33%) tracked by multiple provinces (ie, more than 1 province). We rated 9 metrics (33%) as “necessary” to distinguish high-quality from low-quality care, of which only 2 were tracked by multiple provinces (proportion of patients by primary access and rate of vascular access-related bloodstream infections). Most (16/27, 59%) indicators assessed the IOM domains of safe or effective care, and none of the “necessary” indicators measured the IOM domains of timely, patient-centered, or equitable care.

Limitations:

The environmental scan is a nonexhaustive list of quality indicators in Canada. The panel also lacked representation from patients, administrators, and allied health professionals, with more representation from academic sites.

Conclusions:

Quality indicators in Canada mainly focus on safe and effective care, with little provincial overlap. These results highlight current gaps in quality of care measurement for ICHD, and this initial work should provide programs with a starting point to combine highly rated indicators with newly developed indicators into a concise balanced scorecard that supports quality improvement initiatives across all aspects of ICHD care.

Trial Registration:

not applicable.

Evaluating national trends in outcomes after implementation of a star rating system: Results from dialysis facility compare

OBJECTIVE

To examine which factors are driving improvement in the Dialysis Facility Compare (DFC) star ratings and to test whether nonclinical facility characteristics are associated with observed longitudinal changes in the star ratings.

DATA SOURCES

Data were collected from eligible patients in over 6,000 Medicare-certified dialysis facilities from three annual star rating and individual measure updates, publicly released on DFC in October 2015, October 2016, and April 2018.

STUDY DESIGN

Changes in the star rating and individual quality measures were investigated across three public data releases. Year-to-year changes in the star ratings were linked to facility characteristics, adjusting for baseline differences in quality measure performance.

DATA COLLECTION

Data from publicly reported quality measures, including standardized mortality, hospitalization, and transfusion ratios, dialysis adequacy, type of vascular access for dialysis, and management of mineral and bone disease, were extracted from annual DFC data releases.

PRINCIPAL FINDINGS

The proportion of four- and five-star facilities increased from 30.0% to 53.4% between October 2015 and April 2018. Quality improvement was driven by the domain of care containing the dialysis adequacy and hypercalcemia measures. Additionally, independently owned facilities and facilities belonging to smaller dialysis organizations had significantly lower odds of year-to-year improvement than facilities belonging to either of the two large dialysis organizations (Odds Ratio [OR]: 0.736, 95% Confidence Interval [CI]: 0.631-0.856 and OR: 0.797, 95% CI: 0.723-0.879, respectively).

CONCLUSIONS

The percentage of four- and five-star facilities has increased markedly over a three-year time period. These changes were driven by improvement in the specific quality measures that may be most directly under the control of the dialysis facility.