Identifying meaningful outcome measures for the intensive care unit

Establishing a paediatric critical care core quality measure set using a multistakeholder, consensus-driven process

Introduction

Monitoring healthcare quality is challenging in paediatric critical care due to measure variability, data collection burden, and uncertainty regarding consumer and clinician priorities.

Objective

We sought to establish a core quality measure set that (i) is meaningful to consumers and clinicians and (ii) promotes alignment of measure use and collection across paediatric critical care.

Design

We conducted a multi-stakeholder Delphi study with embedded consumer prioritisation survey. The Delphi involved two surveys, followed by a consensus meeting. Triangulation methods were used to integrate survey findings prior tobefore the consensus meeting. In the consensus panel, broad agreement was reached on a core measure set, and recommendations were made for future measurement directions in paediatric critical care.

Setting and participants

Australian and New Zealand paediatric critical care survivors (aged >18 years) and families were invited to rank measure priorities in an online survey distributed via social media and consumer groups. A concurrent Delphi study was undertaken with paediatric critical care clinicians, policy makers, and a consumer representative.

Interventions

None.

Main outcome measures

Priorities for quality measures.

Results

Respondents to the consumer survey (n = 117) identified (i) nurse-patient ratios; (ii) visible patient goals; and (iii) long-term follow-up as their quality measure priorities. In the Delphi process, clinicians (Round 1 n = 191; Round 2 n = 117 [61% retention]; Round 3 n = 14) and a consumer representative reached broad agreement on a 51-item (61% of 83 initial measures) core measure set. Clinician priorities were (i) nurse-patient ratio; (ii) staff turnover; and (iii) long term-follow up. Measure feasibility was rated low due to a perceived lack of standardised case definitions or data collection burden. Five recommendations were generated.

Conclusions

We defined a 51-item core measurement set for paediatric critical care, aligned with clinician and consumer priorities. Next steps are implementation and methodological evaluation in quality programs, and where appropriate, retirement of redundant measures.

Association between atrial fibrillation and risk of end-stage renal disease among adults with diabetes mellitus

Diabetes mellitus (DM) is an important risk factor in patients with end-stage renal disease (ESRD). DM is associated with the development of cardiovascular diseases, such as atrial fibrillation (AF), due to poor glycemic control. However, few studies have focused on the risk of developing ESRD among DM patients with and without AF. This study evaluated ESRD risk among DM patients with and without AF in Taiwan. Data were retrieved from one million patients randomly sampled from Taiwan’s National Health Insurance Research Database, including 6,105 DM patients with AF propensity score–matched with 6,105 DM patients without AF. Both groups were followed until death, any dialysis treatment, or December 31, 2013, whichever occurred first. AF was diagnosed by a qualified physician according to the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM), using the diagnostic code 427.31. Patients aged <20 years or diagnosed with ESRD before the index date were excluded. A Cox proportional hazard regression model was used to calculate the relative ESRD risk. Among DM patients, those with AF have more comorbidities than those without AF. We also found a 1.18-fold (95% confidence interval [CI]: 1.01–1.46) increase in ESRD risk among patients with AF compared with those without AF. In addition, DM patients with hypertension, chronic kidney disease (CKD), or higher Charlson Comorbidity Index scores also have significantly increased ESRD risks than those without these complications. A 1.39-fold (95% CI: 1.04–1.86) increase in risk was observed for patients with AF among the non-CKD group. Our findings suggest that patients with DM should be closely monitored for irregular or rapid heart rates.

The association between Parkinson's disease and temporomandibular disorder

The prevalence of temporomandibular disorder (TMD) among elderly people with Parkinson’s disease (PD) is relatively high, but a population-based study of the relationship between PD and TMD is still lacking. This study, therefore, sought to investigate the association between TMD and PD by using data for one million randomly sampled beneficiaries of Taiwan’s National Health Insurance program, including 6,185 PD patients who were matched through propensity score matching with 18,555 non-PD patients. Both the PD and non-PD cohorts were followed until death, any diagnosis of TMD, or December 31, 2013, whichever occurred first. Each diagnosis of TMD was made by a qualified physician according to the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM), using the diagnosis codes 524.60, 524.62, 524.63, and 524.69 while excluding tooth abscess, wisdom tooth eruption, herpes zoster and postherpetic neuralgia, mastoiditis, otitis externa, otitis media, parotitis, sialadenitis, and trigeminal neuralgia. We used Cox proportional hazard regression models to calculate the relative risk of TMD and found a 2.11-fold (95% CI: 1.35–3.30) increased risk of TMD overall in the PD group compared with the non-PD group. Stratified by follow-up period, there was a 4.25-fold (95% CI: 1.51–11.93) increased risk in the PD group in the first year after the initial PD diagnosis and a 3.88-fold (95% CI: 1.33–11.28) increased risk in the second year. Over the long-term (>5 years), PD was significantly associated with an increased risk of TMD. These findings suggest that it is important to closely monitor the temporomandibular joint health of PD patients.

Gaussian Processes for Personalized Interpretable Volatility Metrics in the Step-Down Ward

Patients in a hospital step-down unit require a level of care that is between that of the intensive care unit (ICU) and that of the general ward. While many patients remain physiologically stabilized, others will suffer clinical emergencies and be readmitted to the ICU, with a subsequent high risk of mortality. Had the associated physiological deterioration been detected early, the emergency may have been less severe or avoided entirely. Current clinical monitoring is largely heuristic, requiring manual calculation of risk scores and the use of heuristic decision criteria. Technical drawbacks include ignoring the time-series dynamics of physiological measurements, and lacking patient-specificity (i.e., personalization of models to the individual patient). In this paper, we demonstrate how Gaussian process regression models can supplement current monitoring practice by providing interpretable and intuitive illustrations of erratic vital-sign volatility. These personalized volatility metrics may provide significantly advanced warning of deterioration, while minimizing the false alarms that induce so-called alarm fatigue. While many AI-based approaches to healthcare are criticized for being uninterpretable "black-box" methods, the cause of alarms generated from the proposed methods are explicitly interpretable and intuitive. We conclude that intelligent computational inference using methods such as those proposed can enhance current clinical decision making and potentially save lives.

Developing and Testing a Chart Abstraction Tool for ICU Quality Measurement

Quality measures are increasingly used to measure the performance of providers, hospitals, and health care systems. Intensive care units (ICUs) are an important clinical area in hospitals, given that they generate high costs and present high risks to patients. Yet, currently, few valid and clinically significant ICU-specific outcome measures are reported nationally. This study reports on the creation and evaluation of new abstraction tools that evaluate ICU patients for the following clinically important outcomes: central line-associated bloodstream infection, methicillin-resistant Staphylococcus aureus, gastrointestinal bleed, and pressure ulcer. To allow ICUs and institutions to compare their outcomes, the tools include risk-adjustment variables that can be abstracted from the chart.

Critical Care Organizations: Business of Critical Care and Value/Performance Building

OBJECTIVE

New, value-based regulations and reimbursement structures are creating historic care management challenges, thinning the margins and threatening the viability of hospitals and health systems. The Society of Critical Care Medicine convened a taskforce of Academic Leaders in Critical Care Medicine on February 22, 2016, during the 45th Critical Care Congress to develop a toolkit drawing on the experience of successful leaders of critical care organizations in North America for advancing critical care organizations (Appendix 1). The goal of this article was to provide a roadmap and call attention to key factors that adult critical care medicine leadership in both academic and nonacademic setting should consider when planning for value-based care.

DESIGN

Relevant medical literature was accessed through a literature search. Material published by federal health agencies and other specialty organizations was also reviewed. Collaboratively and iteratively, taskforce members corresponded by electronic mail and held monthly conference calls to finalize this report.

SETTING

The business and value/performance critical care organization building section comprised of leaders of critical care organizations with expertise in critical care administration, healthcare management, and clinical practice.

MEASUREMENTS AND MAIN RESULTS

Two phases of critical care organizations care integration are described: "horizontal," within the system and regionalization of care as an initial phase, and "vertical," with a post-ICU and postacute care continuum as a succeeding phase. The tools required for the clinical and financial transformation are provided, including the essential prerequisites of forming a critical care organization; the manner in which a critical care organization can help manage transformational domains is considered. Lastly, how to achieve organizational health system support for critical care organization implementation is discussed.

CONCLUSIONS

A critical care organization that incorporates functional clinical horizontal and vertical integration for ICU patients and survivors, aligns strategy and operations with those of the parent health system, and encompasses knowledge on finance and risk will be better positioned to succeed in the value-based world.

Measuring intensive care unit performance after sustainable growth rate reform: An example with the National Quality Forum metrics

BACKGROUND

Performance measurement is essential for quality improvement and is inevitable in the shift to value-based payment. The National Quality Forum is an important clearinghouse for national performance measures in health care in the United States.

AIM

We reviewed the National Quality Forum library of performance measures to highlight measures that are relevant to critical care medicine, and we describe gaps and opportunities for the future of performance measurement in critical care medicine.

CONCLUSION

Crafting performance measures that address core aspects of critical care will be challenging, as current outcome and performance measures have problems with validity. Future quality measures will likely focus on interdisciplinary measures across the continuum of patient care.