New reimbursement models to promote better patient outcomes and overall value in laboratory medicine and healthcare

The most widespread healthcare reimbursement models, including diagnostic laboratory services, are Fee-for-Service, Reference Pricing and Diagnosis-Related Groups. Within these models healthcare providers are remunerated for each specific service or procedure they operate. Healthcare payers are increasingly exploring alternative models, such as bundled payments or value-based reimbursement to encourage value of patient care rather than the simple amount of delivered services. These alternative models are advised, as they are more efficient in promoting cost-effective, high-quality laboratory testing, thereby improving patient health outcomes. If outcomes-based evaluation is a pillar in a new vision of "Value-Based Healthcare", an active policy of Value-Based Reimbursement in laboratory medicine will assure both an efficiency-based sustainability and a high-quality effectiveness-based diagnostic activity. This review aims to evaluate current and alternative reimbursement models, to support a wider agenda in encouraging more Value-Based Healthcare and Value-Based Reimbursement in laboratory medicine.

Methods for determining clinical utility

Measuring the clinical utility of a diagnostic test involves evaluating its impact on patient outcomes, clinical decision-making, and healthcare resource utilization. Determining clinical utility requires accessing patient medical history and outcomes data. These studies involve enrolling patients undergoing diagnostic tests and tracking their clinical outcomes. Researchers can determine the test's clinical utility by comparing the outcomes of patients who receive the diagnostic test to those who do not. These outcomes include benefits and harm. The highest level of evidence to support clinical utility determinations may be obtained from clinical trials. However, clinical laboratories are often not involved in clinical trials, and laboratory specialists may not be experienced in conducting such trials. Many established laboratory tests have never had clinical utility determined. Prospective studies assessing a diagnostic test's impact on clinical outcomes may require long-term patient monitoring, which is problematic. This paper presents methods that may be used to assess clinical utility.

Optimizing laboratory test utilization in long-term acute care hospitals

Laboratory tests can be considered inappropriate if overused or when repeated, unnecessary "routine" testing occurs. For chronically critically ill patients treated in long-term acute care hospitals (LTACHs), inappropriate testing may result in unnecessary blood draws that could potentially harm patients or increase infections. A quality improvement initiative was designed to increase physician awareness of their patterns of lab utilization in the LTACH environment. Within a large network of LTACHs, 9 hospitals were identified as having higher patterns of lab utilization than other LTACHs. Meetings were held with administrative staff and physicians, who designed and implemented hospital-specific strategies to address lab utilization. Lab utilization was measured in units of lab tests ordered per inpatient day (lab UPPD) for 8 months prior to the initial meeting and 7 months after the meeting. A repeated measures mixed model determined that postintervention lab utilization improved, on average and adjusted by case mix index, by 0.37 lab UPPD (t = -3.61, 95% CI 0.17 to 0.58) compared to the preintervention period. Overall, the case mix index 8 months prior to the intervention was no different than it was 7 months after the initial meeting (t[8] = -0.96, P = 0.37). Patient safety and outcome measures, including percentage of patients weaned from a ventilator, readmission rates, central catheter utilization rates, and the incidence of methicillin-resistant Staphylococcus aureus and other multidrug resistant organisms, showed no significant change. Hospital staff meetings focused on lab utilization and the development and deployment of tailored lab utilization strategies were associated with LTACHs achieving significantly lower lab utilization without negatively impacting quality outcomes.

Molecular assays for the diagnosis of sepsis in neonates

BACKGROUND

Microbial cultures for diagnosis of neonatal sepsis have low sensitivity and reporting delay. Advances in molecular microbiology have fostered new molecular assays that are rapid and may improve neonatal outcomes.

OBJECTIVES

To assess the diagnostic accuracy of various molecular methods for the diagnosis of culture-positive bacterial and fungal sepsis in neonates and to explore heterogeneity among studies by analyzing subgroups classified by gestational age and type of sepsis onset and compare molecular tests with one another.

SEARCH METHODS

We performed the systematic review as recommended by the Cochrane Diagnostic Test Accuracy Working Group. On 19 January 2016, we searched electronic bibliographic databases (the Cochrane Library, PubMed (from 1966), Embase (from 1982), and CINAHL (from 1982)), conference proceedings of the Pediatric Academic Societies annual conference (from 1990), clinical trial registries (ClinicalTrials.gov, International Standard Randomised Controlled Trial Number (ISRCTN) registry, and World Health Organization (WHO) International Clinical Trials Platform (ICTRP) Search portal), and Science Citation Index. We contacted experts in the field for studies.

SELECTION CRITERIA

We included studies that were prospective or retrospective, cohort or cross-sectional design, which evaluated molecular assays (index test) in neonates with suspected sepsis (participants) in comparison with microbial cultures (reference standard).

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed the methodologic quality of the studies and extracted data. We performed meta-analyses using the bivariate and hierarchical summary receiver operating characteristic (HSROC) models and entered data into Review Manager 5.

MAIN RESULTS

Thirty-five studies were eligible for inclusion and the summary estimate of sensitivity was 0.90 (95% confidence interval (CI) 0.82 to 0.95) and of specificity was 0.93 (95% CI 0.89 to 0.96) (moderate quality evidence). We explored heterogeneity by subgroup analyses of type of test, gestational age, type of sepsis onset, and prevalence of sepsis and we did not find sufficient explanations for the heterogeneity (moderate to very low quality evidence). Sensitivity analyses by including studies that analyzed blood samples and by good methodology revealed similar results (moderate quality evidence).

AUTHORS' CONCLUSIONS

Molecular assays have the advantage of producing rapid results and may perform well as 'add-on' tests.