Evaluating practice variance among family physicians to identify targets for laboratory utilization management

Ferritin Cutoffs and Diagnosis of Iron Deficiency in Primary Care

Importance

Ferritin is often measured by general practitioners, but the association of different cutoffs with the rates of iron deficiency diagnoses, particularly nonanemic iron deficiency, is unknown.

Objective

To investigate the association of the ferritin cutoff choice with the incidence of nonanemic and anemic iron deficiency diagnoses in primary care.

Design, Setting, and Participants

In this retrospective cohort study, patients 18 years or older with at least 1 consultation with a general practitioner participating in the Family Medicine Research Using Electronic Medical Records (FIRE) project, an electronic medical records database of Swiss primary care, from January 1, 2021, to November 30, 2023, were evaluated.

Exposures

Sex, age, clinical patient characteristics, and professional general practitioner characteristics.

Main Outcomes and Measures

Incidence of iron deficiency diagnoses (nonanemic and anemic) at ferritin cutoffs of 15, 30, and 45 ng/mL and ferritin testing itself. Time-dependent Cox proportional hazards regression was used to examine associations of patient and general practitioner characteristics with ferritin testing as adjusted hazard ratios (AHRs).

Results

The study included 255 351 patients (median [IQR] age, 52 [36-66] years; 52.1% female). Per 1000 patient-years and at ferritin cutoffs of 15, 30, and 45 ng/mL, iron deficiency diagnoses had incidences of 10.9 (95% CI, 10.6-11.2), 29.9 (95% CI, 29.4-30.4), and 48.3 (95% CI, 47.7-48.9) cases, respectively; nonanemic iron deficiency diagnoses had incidences of 4.1 (95% CI, 3.9-4.2), 14.6 (95% CI, 14.3-15.0), and 25.8 (95% CI, 25.3-26.2) cases, respectively; and anemic iron deficiency diagnoses had incidences of 3.5 (95% CI, 3.3-3.7), 6.0 (95% CI, 5.8-6.2), and 7.5 (95% CI, 7.3-7.7) cases, respectively. Ferritin testing showed notable associations with fatigue (AHR, 2.03; 95% CI, 1.95-2.12), anemia (AHR, 1.75; 95% CI, 1.70-1.79), and iron therapy (AHR, 1.50; 95% CI, 1.46-1.54). Ferritin testing was associated with female sex in all age groups, including postmenopausal. Of the patients who received ferritin testing, 72.1% received concomitant hemoglobin testing, and 49.6% received concomitant C-reactive protein testing.

Conclusions and Relevance

In this retrospective cohort study of primary care patients, ferritin cutoffs of 30 and 45 ng/mL were associated with a substantially higher incidence of iron deficiency compared with 15 ng/mL. These results provide a basis for health system-level evaluation and benchmarking of ferritin testing in high-resource settings and call for a harmonization of diagnostic criteria for iron deficiency in primary care.

Association Between Provider-Sponsored Health Plan Ownership and Health Insurance Marketplace Plan Quality

BACKGROUND

Over 15.3 million Americans relied on the individual health insurance market for health coverage in 2021. Yet, little is known about the relationships between the organizational characteristics of individual market health insurers and quality of coverage, particularly with respect to clinical outcomes.

OBJECTIVE

To examine variation in marketplace insurers' quality performance and investigate how performance varies by insurer organizational characteristics.

DESIGN

Retrospective cohort study.

PARTICIPANTS

381 insurer products, representing 184 unique insurers in 50 states in 2019 and 2020.

MAIN MEASURES

Marketplace plan clinical quality measures reported in the 2019-2020 CMS Plan Quality Rating System dataset and insurer-product organizational attributes identified from several data sources, including non-profit ownership, Blue Cross Blue Shield Association membership, Medicaid focus and whether or not the insurer product is vertically integrated with a provider organization.

KEY RESULTS

Among the 381 insurer products in this study, 35% are part of a provider-sponsored health plan (PSHP) and 70% of these entities received four stars or above for overall quality performance. Overall, PSHPs exhibited higher quality than non-PSHPs for both clinical quality management (0.36 increased on a 5-point scale; 95% CI = 0.11 to 0.62; P = 0.005) and enrollee experience (0.27; 95% CI = 0.03 to 0.50; P = 0.03) summary indicators. Medicaid focused insurers were associated with lower performance on enrollee experience, plan administration, and various outcomes related to clinical quality.

CONCLUSIONS

Provider-sponsored health plans in the health insurance marketplaces are associated with higher-quality care, as measured by CMS clinical quality measures.

Use of machine learning to predict clinical decision support compliance, reduce alert burden, and evaluate duplicate laboratory test ordering alerts

Objectives

While well-designed clinical decision support (CDS) alerts can improve patient care, utilization management, and population health, excessive alerting may be counterproductive, leading to clinician burden and alert fatigue. We sought to develop machine learning models to predict whether a clinician will accept the advice provided by a CDS alert. Such models could reduce alert burden by targeting CDS alerts to specific cases where they are most likely to be effective.

Materials and Methods

We focused on a set of laboratory test ordering alerts, deployed at 8 hospitals within the Partners Healthcare System. The alerts notified clinicians of duplicate laboratory test orders and advised discontinuation. We captured key attributes surrounding 60 399 alert firings, including clinician and patient variables, and whether the clinician complied with the alert. Using these data, we developed logistic regression models to predict alert compliance.

Results

We identified key factors that predicted alert compliance; for example, clinicians were less likely to comply with duplicate test alerts triggered in patients with a prior abnormal result for the test or in the context of a nonvisit-based encounter (eg, phone call). Likewise, differences in practice patterns between clinicians appeared to impact alert compliance. Our best-performing predictive model achieved an area under the receiver operating characteristic curve (AUC) of 0.82. Incorporating this model into the alerting logic could have averted more than 1900 alerts at a cost of fewer than 200 additional duplicate tests.

Conclusions

Deploying predictive models to target CDS alerts may substantially reduce clinician alert burden while maintaining most or all the CDS benefit.

Determinants of Medical Practice Variation Among Primary Care Physicians: Protocol for a Three Phase Study

BACKGROUND

One of the greatest challenges of modern health systems is the choice and use of resources needed to diagnose and treat patients. Medical practice variation (MPV) is a broad term which entails the differences between health care providers inclusive of both the overuse and underuse. In this paper, we describe a 3-phase research protocol examining MPV in primary care.

OBJECTIVE

We aim to identify the potential targets for behavioral modification interventions to reduce the variation in practice patterns and thus improve health care, decrease costs, and prevent disparities in care.

METHODS

The first phase will delineate the variation in primary care practice over a wide range of services and long follow-up period (2003-2017), the second will examine the 3 determinants of variation (ie, patient, physician, and clinic characteristics), and attempt to derive the unexplained variance. In the third phase, we will assess a novel component that might contribute to the previously unexplained variance - the physicians' personal behavioral characteristics (such as risk aversion, fear of malpractice, stress from uncertainty, empathy, and burnout).

RESULTS

This work was supported by the research grant from Israel National Institute for Health Policy Research (Grant No. 2014/134). Soroka University Medical Center Institutional Ethics Committee has approved the updated version of the study protocol (SOR-14-0063) in February 2019. All relevant data for phases 1 and 2, including patient, physician, and clinic, were collected from the Clalit Health Services data set in 2019 and are currently being analyzed. The evaluation of the individual physician characteristics (eg, risk aversion) by the face-to-face questionnaires was started on 2018 and remains in progress. We intend to publish the results during 2020-2021.

CONCLUSIONS

Based on the results of our study, we aim to propose a list of potential targets for focused behavioral intervention. Identifying new targets for such an intervention can potentially lead to a decrease in the unwarranted variation in the medical practice. We suggest that such an intervention will result in optimization of the health system, improvement of health outcomes, reduction of disparities in care and savings in cost.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/18673.

Trends and Between-Physician Variation in Laboratory Testing: A Retrospective Longitudinal Study in General Practice

Laboratory tests are frequently ordered by general practitioners (GPs), but little is known about time trends and between-GP variation of their use. In this retrospective longitudinal study, we analyzed over six million consultations by Swiss GPs during the decade 2009–2018. For 15 commonly used test types, we defined specific laboratory testing rates (sLTR) as the percentage of consultations involving corresponding laboratory testing requests. Patient age- and sex-adjusted time trends of sLTR were modeled with mixed-effect logistic regression accounting for clustering of patients within GPs. We quantified between-GP variation by means of intraclass correlation coefficients (ICC). Nine out of the 15 laboratory test types considered showed significant temporal increases, most eminently vitamin D (ten-year odds ratio (OR) 1.88, 95% confidence interval (CI) 1.71–2.06) and glycated hemoglobin (ten-year OR 1.87, 95% CI 1.82–1.92). Test types both subject to substantial increase and high between-GP variation of sLTR were vitamin D (ICC 0.075), glycated hemoglobin (ICC 0.101), C-reactive protein (ICC 0.202), and vitamin B12 (ICC 0.166). Increasing testing frequencies and large between-GP variation of specific test type use pointed at inconsistencies of medical practice and potential overuse.

Essential role of laboratory physicians in transformation of laboratory practice and management to a value-based patient-centric model

The laboratory is a vital part of the continuum of patient care. In fact, there are few programs in the healthcare system that do not rely on ready access and availability of complex diagnostic laboratory services. The existing transactional model of laboratory "medical practice" will not be able to meet the needs of the healthcare system as it rapidly shifts toward value-based care and precision medicine, which demands that practice be based on total system indicators, clinical effectiveness, and patient outcomes. Laboratory "value" will no longer be focused primarily on internal testing quality and efficiencies but rather on the relative cost of diagnostic testing compared to direct improvement in clinical and system outcomes. The medical laboratory as a "business" focused on operational efficiency and cost-controls must transform to become an essential clinical service that is a tightly integrated equal partner in direct patient care. We would argue that this paradigm shift would not be necessary if laboratory services had remained a "patient-centric" medical practice throughout the last few decades. This review is focused on the essential role of laboratory physicians in transforming laboratory practice and management to a value-based patient-centric model. Value-based practice is necessary not only to meet the challenges of the new precision medicine world order but also to bring about sustainable healthcare service delivery.

Dataset of clinical laboratory tests according to ordering variance among family physicians in Calgary, Alberta, Canada

This data incorporates 2016 testing volumes ordered by family physicians and performed at Calgary Laboratory Services (CLS), the sole supplier of clinical laboratory services for the catchment area of the City of Calgary, Alberta, Canada. For each test, the mean number of tests ordered per patient was calculated over ordering Calgary physicians, along with arithmetic coefficients of variation (CV's). The latter parameter is reflective of variance in ordering practice among family physicians practicing in Calgary and is proposed as a benchmark measure for laboratory utilization in our accompanying research article [1]. The data table encompasses 358 tests ordered by at least 3 family physicians at a minimum total frequency of 100 within the 2016 study period and is presented in ascending order of rank in CV.