Literature DB >> 28725789

Improving American Healthcare Through "Clinical Lab 2.0": A Project Santa Fe Report.

James M Crawford1, Khosrow Shotorbani2, Gaurav Sharma3, Michael Crossey2, Tarush Kothari1, Thomas S Lorey4, Jeffrey W Prichard5, Myra Wilkerson5, Nancy Fisher2.   

Abstract

Project Santa Fe was established both to provide thought leadership and to help develop the evidence base for the valuation of clinical laboratory services in the next era of American healthcare. The participants in Project Santa Fe represent major regional health systems that can operationalize laboratory-driven innovations and test their valuation in diverse regional marketplaces in the United States. We provide recommendations from the inaugural March 2016 meeting of Project Santa Fe. Specifically, in the transition from volume-based to value-based health care, clinical laboratories are called upon to provide programmatic leadership in reducing total cost of care through optimization of time-to-diagnosis and time-to-effective therapeutics, optimization of care coordination, and programmatic support of wellness care, screening, and monitoring. This call to action is more than working with industry stakeholders on the basis of our expertise; it is providing leadership in creating the programs that accomplish these objectives. In so doing, clinical laboratories can be effectors in identifying patients at risk for escalation in care, closing gaps in care, and optimizing outcomes of health care innovation. We also hope that, through such activities, the evidence base will be created for the new value propositions of integrated laboratory networks. In the very simplest sense, this effort to create "Clinical Lab 2.0" will establish the impact of laboratory diagnostics on the full 100% spend in American healthcare, not just the 2.5% spend attributed to in vitro diagnostics. In so doing, our aim is to empower regional and local laboratories to thrive under new models of payment in the next era of American health care delivery.

Entities:  

Keywords:  disruption; innovation; laboratory medicine; pathology; value

Year:  2017        PMID: 28725789      PMCID: PMC5497901          DOI: 10.1177/2374289517701067

Source DB:  PubMed          Journal:  Acad Pathol        ISSN: 2374-2895


Introduction

In vitro diagnostics, the healthcare industry term for clinical laboratory services, represents US$73 billion of the US$3 trillion spend on US healthcare—about 2.5%. And yet, this sector of healthcare informs the majority of health care management, estimated at “up to 70% of decisions.”[1,2] To date, very few laboratories or pathologists are actively engaged in providing leadership for optimizing integration of laboratory diagnostics into clinical workflows and population management. Building the evidence base for the positive outcomes that arise from acting upon laboratory diagnostic information is actually a difficult task. But upon such evidence rest decisions about the role that the laboratory plays in the coming era of risk-based health care. The question is: are laboratory services strictly a commodity or do laboratory services have a higher valuation that can drive better outcomes for patients, providers, and financial stakeholders alike? Project Santa Fe was established to test the latter hypothesis. Project Santa Fe is a coalition of like-minded major regional laboratories, coming together to create and help drive the new frontiers that will define the future economic valuation and placement of laboratory diagnostic services in American healthcare. Both through “think tank” efforts and through the building of a rigorous evidence base, the members will pursue a disruptive “value” paradigm. Our collective goal is to be trailblazers in the role of laboratory leadership in reengineering health care delivery and the practice of medicine. This is a first report from Project Santa Fe, articulating foundational premises for moving laboratory services from its current posture as “Clinical Lab 1.0” to “Clinical Lab 2.0” in the next era of health care.

Opportunities for Laboratory Services

Health care expenditures currently represent 17.5% of the US gross domestic product (GDP).[3] Virtually all analysts agree that, without major reform, health care’s share of GDP will continue to rise rapidly, potentially reaching 28% in 2030 and 34% in 2040.[4] Escalating health care costs are due in part to system inefficiencies: spending a substantial amount on high-cost, low-value treatments, patients obtaining too little of certain types of care that are effective and of high value, patients not receiving care in the most cost-effective setting, extensive variation in the quality of care provided to patients, preventable medical errors that lead to worse outcomes and higher costs, and system complexity that adds high administrative costs. We believe that laboratory professionals must provide strategic programmatic leadership in reducing these inefficiencies and in promoting better health care delivery. Moreover, we do not feel that we have the luxury of even single years to accomplish these ends.[5] The evidence base for laboratory valuation must be established in a proximate time frame, including bringing institutional demonstration projects forward in the peer-review literature. In the inpatient setting, information generated by the clinical laboratory can inform the severity of illness that the patient has, provide real-time risk stratification of the evolving acuity of care needed, and track the patient’s progress through the episode of care. In the ambulatory setting, laboratory services can constitute a driver for continuity in care, both through the longitudinal continuity of laboratory testing performed on patients with chronic diseases and through informing providers about evolving risk conditions and potential gaps in care. In both instances, the laboratory can inform real-time, targeted intervention for populations of patients with risk conditions. Moreover, in both inpatient and ambulatory settings, the increasing use of esoteric testing brings to health care the leading edge of medical science and the promise of “precision medicine” for individual patients. Laboratory professionals play a central role in driving appropriate test utilization and in guiding the clinical action based on these tests. While laboratory testing necessarily informs the diagnoses rendered under the disease-related groups model of payment for inpatient health care, only recently has ambulatory health care come under a risk-based form of healthcare payment. The alternative payment models for US health care require documentation of risk conditions that describe the severity of acute and chronic illness for covered beneficiaries, in order to guide payment for such care.[6] Similar to inpatient care, the diagnosis of disease conditions in the ambulatory setting is also substantially informed by laboratory services. Hence, in both settings now, laboratory test data underpin the valuation of care given by health-care providers. It stands to reason that laboratory professionals can provide leadership in optimizing this use of laboratory data as well. Collectively, these opportunities are summarized in Table 1. This optimistic view of the opportunities contrasts with the premise that laboratory diagnostics are movable and are unlinked to the local delivery of care except as dictated by turnaround time obligations and the provision of test result data. Such depersonalization of laboratory diagnostics threatens the premise that “health care is local” and disempowers the ability of local health care providers to work with laboratory subject matter experts. In addition, time delays in test results due to this commodity mentality risk creating clinician behavioral changes such as massive lab order sets to avoid any potential delay in diagnoses. The logical, stepwise approach to clinical diagnosis is supplanted by a “shotgun” approach with the ensuing information chaos and loss of clarity.
Table 1.

Opportunities for Laboratory Services Under Alternative Payment Models.

Organizing principles of alternative payment models
 Transition from volume based to value based reimbursement
 Transition from cost per unit to total episodic costs
 Transition from fee-for-service transactions to bundled payments
Leadership activities for laboratory services
 Establishment of institution-wide laboratory test formularies
 Documentation and Education of Provider test utilization patterns
 Laboratory Utilization Management of expensive and esoteric testing: inpatient, ambulatory
 Real-time risk stratification of covered populations (eg, in managed care products)
 Predictive modelling of chronic disease states in those covered populations
 Provision of analytical services to reduce physician burden in quality measurement and reporting (HEDIS, MIPS, P4P, ACO metrics)
 Closing of “care gaps”
  Provision of real-time laboratory data to providers at the point of care
  Working with health systems and civic authorities to identify patients in-need
 Provision to physicians and provider groups of information on utilization and cost of laboratory testing, including peer-to-peer benchmark comparative reports
 Reduction of out-of-network leakage of laboratory testing, both as a cost-savings exercise and as part of attaining comprehensive laboratory data on covered populations
 Assisting providers in identifying, monitoring, and following up on patients with chronic and costly conditions, as through Disease Registries
 Working with payers and ACOs to identify and manage patients enrolled in disease management and care management programs
 Using point-of-care laboratory testing to improve patient access and for effective patient engagement and chronic care management (including testing at patients’ homes)
 Integration of laboratory testing with telemedicine care delivery models

Abbreviations: ACO, Accountable Care Organization; HEDIS, Healthcare Effectiveness Data and Information Set; MIPS, Merit-Based Incentive Payment System; P4P, Pay-for-Performance.

Opportunities for Laboratory Services Under Alternative Payment Models. Abbreviations: ACO, Accountable Care Organization; HEDIS, Healthcare Effectiveness Data and Information Set; MIPS, Merit-Based Incentive Payment System; P4P, Pay-for-Performance. An article of faith for laboratory professionals is that pathology and laboratory medicine touch the virtual entirety of the human condition, in a high-impact “patient-centered” fashion. Since laboratory testing is part of wellness and preventive care as well as treatment for disease, under the best of circumstances clinical laboratories touch the lives of almost everyone. In so doing, laboratory diagnostics constitute an extraordinarily broad front to help bring the promise of health care innovations to fruition for the entire population. This promise can be realized at the time of the diagnostic assessment and at the time of health care decision-making. The question is, who carries responsibility for delivering on that promise? Under the “commoditization of laboratory services” model, it is other sectors of the health-care industry that will compile the massive sources of information emanating from the clinical laboratory, to extract value and put that value into play. The clinical laboratory simply remains a source of transactional data, without significant input into either the demand for that data (test ordering) or its interpretation. We argue that this displacement of interpretive effort is not commutative—that something is lost by separating the laboratory from data analysis and interpretation. The basis for such argument is that laboratory professionals have unique expertise (Table 2). For the technical professionals of the laboratory workforce, their expertise lies in maximizing the accuracy of laboratory diagnostics, optimizing the efficiency of their delivery and helping to ensure that innovations from medical science are successfully deployed at this front line of health care delivery. For the medical professionals—pathologists, clinical doctoral scientists, and informaticists alike—a primary career responsibility is knowledge of the impact of diagnostic testing and interpretations on patient prognosis, treatment, and outcomes. It is precisely this expertise that enables pathologists, clinical scientists, and informaticists to inform decision-making regarding the most effective ways to deliver outstanding patient care. With medical care becoming increasingly specialized, the laboratory testing that goes with it is also increasingly specialized. It is becoming exceedingly difficult for providers to stay abreast of best evidence regarding laboratory medicine, a factor which may help to explain the wide variation in ordering patterns. Pathologists can be of enormous value in workup of specific clinical disorders.[7,8]
Table 2.

The Unique Attributes of Laboratory Professionals.

Our specialty requires us to understand the scientific basis of all of human disease.

We must be lead adapters for advances in the medical science of diagnosis.

We must understand the impact of treatment and intervention on the entirety of the human condition, not just the disease being treated (owing to the impact of such treatments on the host).

To be effective consultants to providers, we must understand the impact of our test information on medical decision-making.

We live-and-breath Quality and Safety.

We have sight lines to virtually every sector of health care.

We practice “system management” as a core expertise.

Our innovations can be rapidly promulgated throughout a health system and can be quickly emulated by other health systems (scalability and replicability).

Our innovations don’t cost much, but can have great impact.

We have data streams on the entire population.

We see the diagnostic test data first.

The Unique Attributes of Laboratory Professionals. Our specialty requires us to understand the scientific basis of all of human disease. We must be lead adapters for advances in the medical science of diagnosis. We must understand the impact of treatment and intervention on the entirety of the human condition, not just the disease being treated (owing to the impact of such treatments on the host). To be effective consultants to providers, we must understand the impact of our test information on medical decision-making. We live-and-breath Quality and Safety. We have sight lines to virtually every sector of health care. We practice “system management” as a core expertise. Our innovations can be rapidly promulgated throughout a health system and can be quickly emulated by other health systems (scalability and replicability). Our innovations don’t cost much, but can have great impact. We have data streams on the entire population. We see the diagnostic test data first. In sum, we believe that laboratory professionals are well-positioned to play a key role in the transition of US health care from “sick care” to “health care.” We are proposing that this be accomplished via the clinical laboratory business model’s evolution from “Clinical Lab 1.0” (transactional) to “Clinical Lab 2.0” (integrative), the attributes of which are depicted in Figure 1. This effort can be driven through such population-based activities as given in Table 3.
Figure 1.

Proposed Transition of Pathology and Laboratory Services from a Transactional to an Integrative Model: “Clinical Lab 2.0”.

Table 3.

Population Health activities of the Laboratory.

Reducing time to diagnosis and time to intervention

Chronic disease management

 Gaps in care: alerts, notifications, improvements in patient access, tracking of outcomes

 Registries: for risk assessment and intervention and for actuarial planning

Wellness care: screening; early intervention

High-acuity care: real-time risk escalation and intervention

Transitions in care

 Continuity in problem lists; support of coordinated care across multiple care sites

 Advance notifications to downstream sites

Laboratory: pharmacy reconciliation

 Antibiotic stewardship

 Chronic disease reconciliation and compliance

Real-time risk stratification and assessment

 Unmasking of at-risk populations through real-time analytics

 Assessing the disease burden of populations

 Tracking disease progression (or not) through time

 Identifying actionable subgroups of patients

Populating actuarial risk models with real clinical data

 Assessing the real-time actuarial value of laboratory-generated information

 Accelerating (decreasing) the cycle time for identifying risk acquisition by cost-bearing stakeholders

Quality tracking and reporting

 Providing quality measures for health systems and providers

Building the evidence base for innovation

 Precision medicine

 Pharmacogenomics

 Clinical outcomes of interventions at the population level

Proposed Transition of Pathology and Laboratory Services from a Transactional to an Integrative Model: “Clinical Lab 2.0”. Population Health activities of the Laboratory. Reducing time to diagnosis and time to intervention Chronic disease management Gaps in care: alerts, notifications, improvements in patient access, tracking of outcomes Registries: for risk assessment and intervention and for actuarial planning Wellness care: screening; early intervention High-acuity care: real-time risk escalation and intervention Transitions in care Continuity in problem lists; support of coordinated care across multiple care sites Advance notifications to downstream sites Laboratory: pharmacy reconciliation Antibiotic stewardship Chronic disease reconciliation and compliance Real-time risk stratification and assessment Unmasking of at-risk populations through real-time analytics Assessing the disease burden of populations Tracking disease progression (or not) through time Identifying actionable subgroups of patients Populating actuarial risk models with real clinical data Assessing the real-time actuarial value of laboratory-generated information Accelerating (decreasing) the cycle time for identifying risk acquisition by cost-bearing stakeholders Quality tracking and reporting Providing quality measures for health systems and providers Building the evidence base for innovation Precision medicine Pharmacogenomics Clinical outcomes of interventions at the population level

Leadership by Clinical Laboratories

A specific challenge thus emerges: what leadership can and should laboratory professionals provide? The downside concern is that, absent such leadership, the threats to the laboratory industry will continue unabated. The upside opportunity is that such laboratory leadership will improve the delivery of health care more rapidly, with greater realized benefit, than could otherwise be realized. With those polar opposites in mind, programmatic examples of laboratory leadership are given in Table 4. Unfortunately, barriers to providing such leadership are many (Table 5) and will have to be overcome in order to realize the benefit that the laboratory can provide in the abbreviated time frames now required for successful improvement of the US health care system.
Table 4.

New Opportunities for Leadership by Laboratory Professionals.

Promoting better patient access to health care services, to include:

 Identification of care gaps and their root causes

 Enhancing access of patients to ambulatory laboratory services

Supporting provider use of cost effective and rational choices for diagnostic testing

Linking laboratory diagnostics to patient outcomes, to help maximize utility of laboratory testing

Linking laboratory diagnostics to population outcomes, to help guide coordinated care programming

Linking laboratory data to risk stratification, to include:

 Identification of patients at risk for adverse health outcomes

 Tracking of HCCs in covered patient populations

Linking laboratory data to claims and total cost-of-care

 Empowering health systems to optimize revenue recovery in the provision of episodes-of-care

 Empowering health systems to optimize the total coordination of care

Knowledge of health IT architecture, utilization, and analytics

 Acting as subject matter experts on data sourcing and interpretation

Knowledge of APM, to include:

 Understanding of metrics for quality performance that depend on laboratory test data

 Understanding total costs of care (including claims data) and its relationship to laboratory test data

 Providing leadership for optimization of health system revenue performance under APM

Engagement in managed care contracting processes of health system to help ensure effective implementation of pay-for-performance outcomes measures

Engagement with providers, care management organizations, and payers in effective design and delivery of disease and care management programs

Abbreviations: APM, alternative payment models; IT, information technology; HCC, hierarchical condition categories.

Table 5.

Barriers to Laboratory Leadership in Health Care Innovation.

Lack of a common language with providers, health systems, payers

Lack of models for comparisons and benchmarking

Lack of integrative information management technologies

Lack of outcomes-based evidence for laboratory-led innovation

Lack of aligned incentives

Inadequate leveraging of laboratory data into actionable information

Lack of access to capital for in-system laboratories, that is available to the for-profit sector of laboratory industry

Lack of access to new required new skill sets

Inadequate engagement with senior leadership (“C-suite”) of health systems

Lack of playbook for providing leadership

New Opportunities for Leadership by Laboratory Professionals. Promoting better patient access to health care services, to include: Identification of care gaps and their root causes Enhancing access of patients to ambulatory laboratory services Supporting provider use of cost effective and rational choices for diagnostic testing Linking laboratory diagnostics to patient outcomes, to help maximize utility of laboratory testing Linking laboratory diagnostics to population outcomes, to help guide coordinated care programming Linking laboratory data to risk stratification, to include: Identification of patients at risk for adverse health outcomes Tracking of HCCs in covered patient populations Linking laboratory data to claims and total cost-of-care Empowering health systems to optimize revenue recovery in the provision of episodes-of-care Empowering health systems to optimize the total coordination of care Knowledge of health IT architecture, utilization, and analytics Acting as subject matter experts on data sourcing and interpretation Knowledge of APM, to include: Understanding of metrics for quality performance that depend on laboratory test data Understanding total costs of care (including claims data) and its relationship to laboratory test data Providing leadership for optimization of health system revenue performance under APM Engagement in managed care contracting processes of health system to help ensure effective implementation of pay-for-performance outcomes measures Engagement with providers, care management organizations, and payers in effective design and delivery of disease and care management programs Abbreviations: APM, alternative payment models; IT, information technology; HCC, hierarchical condition categories. Barriers to Laboratory Leadership in Health Care Innovation. Lack of a common language with providers, health systems, payers Lack of models for comparisons and benchmarking Lack of integrative information management technologies Lack of outcomes-based evidence for laboratory-led innovation Lack of aligned incentives Inadequate leveraging of laboratory data into actionable information Lack of access to capital for in-system laboratories, that is available to the for-profit sector of laboratory industry Lack of access to new required new skill sets Inadequate engagement with senior leadership (“C-suite”) of health systems Lack of playbook for providing leadership

Examples of Laboratory Leadership to Date

In the traditional paradigm of medicine, laboratory services are a transactional event: a provider orders a test based on her/his clinical impression of a patient’s ailment at a given point in time and interprets the individual test results at the time of receiving the test results. The value of this activity is thus finite and time limited. However, in generating a test result, the laboratory creates a specific and indelible record of the state of health of a patient at a given point of time and often over an extended spectrum of disease progression. Laboratory data (unlike clinical data) are often very structured, quantifiable, and classifiable, ergo, the data are amenable to multiple retrievable and analytical methods. Thus, it is not surprising that the very field of clinical informatics found a firm footing in the clinical laboratory, in the form of laboratory information systems, representing the first home of the electronic health record.[9] In this new era in which pathologists and clinical laboratory professionals are working with clinical stakeholders to better leverage the immense value of information emanating from the clinical laboratory, there are superb examples in the recent literature. Appendix A presents a compilation of such recent activities. In turn, the member laboratories of Project Santa Fe have embarked upon demonstration projects in support of the recommendations of the March 2016 inaugural meeting (Table 6).
Table 6.

2016-2017 Demonstration Projects by Project Santa Fe Membership.

Gaps in care: identification of and tracking of pregnancies in a Medicaid population (TriCore)

Gaps in care: identification of acute kidney injury (AKI) during hospital admission (Northwell)

Gaps in care: latency in laboratory test data, not acted upon clinically (Kaiser-Permanente)

Patient experience: structured quality monitors for anatomic pathology turnaround time (Geisinger)

Utilization management: laboratory test formulary (Henry Ford)

2016-2017 Demonstration Projects by Project Santa Fe Membership. Gaps in care: identification of and tracking of pregnancies in a Medicaid population (TriCore) Gaps in care: identification of acute kidney injury (AKI) during hospital admission (Northwell) Gaps in care: latency in laboratory test data, not acted upon clinically (Kaiser-Permanente) Patient experience: structured quality monitors for anatomic pathology turnaround time (Geisinger) Utilization management: laboratory test formulary (Henry Ford)

The Scientific Method

Comment must be made regarding the scientific method. Laboratory-led innovations will be implemented in the setting of real-time health care delivery, with almost countless variables that may have impact on measured outcomes. Attributing quantitative outcomes causally to the programmatic leadership of the clinical laboratory will not fall into the paradigm of randomized controlled clinical trials because laboratory services cannot be withdrawn from patient care to test a hypothesis (placebo group). Instead, the established formulation for testing the utility of laboratory services is worth recalling[10]: Did the (new) laboratory testing cause harm? Was the laboratory testing able to distinguish between patients who had disease versus those who did not? Was the innovation in laboratory testing able to provide better patient diagnostic information than previous options for such testing? Did patients benefit from such testing having been done? We propose a new formulation to meet the scientific aims of these Project Santa Fe recommendations: Do innovations introduced by laboratory leadership cause harm to patients or populations? Are populations of individuals subjected to such innovations measurably different from populations not subject to innovation? Are the differences in a favorable direction? Did patients (or populations) benefit from such innovation having been introduced? Through this scientific formulation, we aim to evaluate the hypothesis that leadership emanating from the clinical laboratory can benefit individual patients, patient populations, and the health systems that provide for their care. Conversely, we must be attentive to the null hypothesis that leadership and interventions initiated by laboratories have no identifiable effect on health care outcomes and the total costs of delivering care.

Conclusion

The recommendations brought forth in this report constitute a call to action for creation of the evidence base in support of the role of clinical laboratories in the next era of American health care. This is to be achieved through innovative programmatic leadership by laboratory professionals, drawing upon their unique expertise in understanding the potential impact of information coming from laboratory diagnostics. We recommend that laboratory professionals do more than work with clinical and institutional stakeholders in leveraging such information. We feel that programmatic leadership by laboratory professionals is also required, including the design and execution of health care delivery programs. In so doing, the clinical laboratory can itself become an efferent arm in advancing innovation, for the betterment of the populations we serve.
  50 in total

1.  Information management and informatics: need for a modern pathology service.

Authors:  Rick Jones; John O'Connor
Journal:  Ann Clin Biochem       Date:  2004-05       Impact factor: 2.057

2.  Impact of weekly feedback on test ordering patterns.

Authors:  Christine Minerowicz; Nicole Abel; Krystal Hunter; Kathryn C Behling; Elizabeth Cerceo; Charlene Bierl
Journal:  Am J Manag Care       Date:  2015-11       Impact factor: 2.229

3.  Managing demand for laboratory tests: a laboratory toolkit.

Authors:  Anthony A Fryer; W Stuart A Smellie
Journal:  J Clin Pathol       Date:  2012-09-26       Impact factor: 3.411

4.  Optimizing personalized bone marrow testing using an evidence-based, interdisciplinary team approach.

Authors:  Adam C Seegmiller; Annette S Kim; Claudio A Mosse; Mia A Levy; Mary Ann Thompson; Megan K Kressin; Madan H Jagasia; Stephen A Strickland; Nishitha M Reddy; Edward R Marx; Kristy J Sinkfield; Herschel N Pollard; W Dale Plummer; William D Dupont; Edward K Shultz; Robert S Dittus; William W Stead; Samuel A Santoro; Mary M Zutter
Journal:  Am J Clin Pathol       Date:  2013-11       Impact factor: 2.493

Review 5.  Anatomy of a value proposition for laboratory medicine.

Authors:  Christopher P Price; Andrew St John
Journal:  Clin Chim Acta       Date:  2014-05-28       Impact factor: 3.786

6.  Computational Pathology: A Path Ahead.

Authors:  David N Louis; Michael Feldman; Alexis B Carter; Anand S Dighe; John D Pfeifer; Lynn Bry; Jonas S Almeida; Joel Saltz; Jonathan Braun; John E Tomaszewski; John R Gilbertson; John H Sinard; Georg K Gerber; Stephen J Galli; Jeffrey A Golden; Michael J Becich
Journal:  Arch Pathol Lab Med       Date:  2015-06-22       Impact factor: 5.534

7.  Diabetes wellness care: a successful employer-endorsed program for employees.

Authors:  Cynthia C Bevis; June M Nogle; Barbara Forges; Philip C Chen; Deborah Sievers; Karlene Ranghell Lucas; John J Mahoney; James M Crawford
Journal:  J Occup Environ Med       Date:  2014-10       Impact factor: 2.162

8.  Evaluation of Electronic Medical Record Administrative data Linked Database (EMRALD).

Authors:  Karen Tu; Tezeta F Mitiku; Noah M Ivers; Helen Guo; Hong Lu; Liisa Jaakkimainen; Doug G Kavanagh; Douglas S Lee; Jack V Tu
Journal:  Am J Manag Care       Date:  2014       Impact factor: 2.229

Review 9.  When diagnostic testing leads to harm: a new outcomes-based approach for laboratory medicine.

Authors:  Paul L Epner; Janet E Gans; Mark L Graber
Journal:  BMJ Qual Saf       Date:  2013-08-16       Impact factor: 7.035

10.  The Value of In Vitro Diagnostic Testing in Medical Practice: A Status Report.

Authors:  Ulrich-Peter Rohr; Carmen Binder; Thomas Dieterle; Francesco Giusti; Carlo Guiseppe Mario Messina; Eduard Toerien; Holger Moch; Hans Hendrik Schäfer
Journal:  PLoS One       Date:  2016-03-04       Impact factor: 3.240

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  8 in total

Review 1.  The Pursuit of Value in Laboratory Medicine - Progress and Challenges.

Authors:  Andrew St John
Journal:  Clin Biochem Rev       Date:  2020-02

2.  Strengthening Laboratory Partnerships, Enhancing Recruitment, and Improving Retention Through Training and Outreach Activities: The Minnesota Experience.

Authors:  Anna K Strain; Maureen M Sullivan
Journal:  Public Health Rep       Date:  2019 Nov/Dec       Impact factor: 2.792

3.  Design and Evaluation of an Electronic Information Exchange System Connecting Laboratories and Physicians' Offices.

Authors:  Hamid Moghaddasi; Farkhondeh Asadi; Negisa Seyyedi; Mohsen Hamidpour
Journal:  Perspect Health Inf Manag       Date:  2022-07-01

4.  Integrating Social Determinants of Health and Laboratory Data: A Pilot Study To Evaluate Co-Use of Opioids and Benzodiazepines.

Authors:  Jill S Warrington; Nick Lovejoy; Jamie Brandon; Keith Lavoie; Chris Powell
Journal:  Acad Pathol       Date:  2019-10-30

5.  The Value Proposition for Pathologists: A Population Health Approach.

Authors:  Barbara S Ducatman; Alan M Ducatman; James M Crawford; Michael Laposata; Fred Sanfilippo
Journal:  Acad Pathol       Date:  2020-01-14

6.  Driving Access to Care: Use of Mobile Units for Urine Specimen Collection During the Coronavirus Disease-19 (COVID-19) Pandemic.

Authors:  Jill S Warrington; Alexa Brett; Heather Foster; Jamie Brandon; Samuel Francis-Fath; Michael Joseph; Mark Fung
Journal:  Acad Pathol       Date:  2020-09-18

7.  Generating Discretionary Income in an Academic Department of Pathology.

Authors:  David N Bailey; James M Crawford; Peter E Jensen; Debra G B Leonard; Susan McCarthy; Fred Sanfilippo
Journal:  Acad Pathol       Date:  2021-09-23

Review 8.  Effectiveness of Practices to Support Appropriate Laboratory Test Utilization: A Laboratory Medicine Best Practices Systematic Review and Meta-Analysis.

Authors:  Matthew Rubinstein; Robert Hirsch; Kakali Bandyopadhyay; Bereneice Madison; Thomas Taylor; Anne Ranne; Millie Linville; Keri Donaldson; Felicitas Lacbawan; Nancy Cornish
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