Society for Maternal-Fetal Medicine
Society for Maternal-Fetal Medicine (SMFM) Special Report: Current approaches to measuring quality of care in obstetrics

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Heath care measurement and evaluation is an integral piece of the health care system. The creation and assessment of care performance metrics are important and relevant for the obstetric community including both clinicians and patients. Careful deliberation is required to create a measurement system that results in optimal care for women and families. This article reviews the current approaches to measuring quality in obstetrics.

Introduction

Increasingly there has been pressure on hospitals and physicians to measure quality and prove the adequacy of the care they are delivering. This pressure comes from insurers and consumers who want to be sure they are not only obtaining good outcomes but also obtaining good value for dollars spent. While the need to spend wisely is understandable, the dilemma remains of how to prove the quality of care provided is high. That is to say, is quality of care measurable?

The Institute of Medicine defines quality of care as “the degree to which heath care services for individuals and populations increase the likelihood of desired health outcomes and are consistent with current professional knowledge.”1 According to Agency for Healthcare Research and Quality (AHRQ), “quality measures” are mechanisms that enable the user to quantify a selected aspect of care by comparing it to an evidence-based criterion.2 A “clinical performance measure” is a type of quality measure that assesses the degree to which a provider competently and safely delivers a clinical service to a patient within the optimal time period. Performance measures have been created by a number of advocacy coalitions, patient safety institutions, government agencies, and professional organizations. To measure performance adequately and accurately, process, structure/capacity, access, patient satisfaction, and outcome measures must not only be created, but must be relevant, scientifically sound, feasible, actionable, accurately measurable (reliable and valid), and ultimately result in improved outcomes for the population. In the case of outcome measures, they may need to be risk-adjusted as well. To paraphrase Einstein, everything should be made as simple as possible, but not any simpler.

Various types of quality measures exist as summarized in the Figure.

Structure/capacity measures are designed to assess whether the capacity to perform a service or function exists in a particular system (eg, what proportion of providers have undergone a certain postpartum hemorrhage (PPH) training or whether a particular service is available at an institution such as massive transfusion policy or PPH cart).

Process measures are designed to assess the frequency of usage of a particular clinical process; they are calculated using the number of patients eligible for a particular service in the denominator and the number of patient who actually receive the service in the numerator (eg, the proportion of GBS carriers who received antibiotics during labor).

Outcome measures are created by assessing the frequency or prevalence of a specific outcome in a given population (eg, number of third- or fourth-degree tears, brachial plexus injuries, or postpartum intensive care unit [ICU] admissions per 1000 deliveries).

Access measures assess the attainment by patients of timely care as well as the delays and barriers (educational, financial, prejudiced, geographic, or environmental) that may result in failure to obtain care.

Finally, patient experience/satisfaction measures assess the patient’s perception and experience of health care delivery. These measures are typically dependent on patient survey data and are not obtainable by typical administrative data generated by a hospital.

Using measures for quality improvement involves 6 steps: identifying deficiencies or areas for improvement, selecting measures to assess these areas, obtaining preintervention baseline data, performing an intervention, performing postintervention measurement, and finally, refining the measurement and the intervention. Quality improvement may involve assessment of internal processes at a single institution or may involve assessments across different institutions that result in regional, state, or national comparisons.

Having established that it is desirable and conceptually possible to measure quality of care, this article will review current approaches to measure quality of care in obstetrics and preview new measures on the horizon. Additionally, systems for using and maintaining quality measures will be discussed.

Section snippets

Current measures of obstetrical quality

There are multiple different metrics currently being suggested or employed in an effort to measure quality of obstetric care. Current metrics for obstetrics endorsed by national organizations, such as the AHRQ, National Quality Forum (NQF), and Joint Commission, are shown in Table 1. However, the lack of an obstetric national database has resulted in measurement difficulty leading to high resource use for certain types of metrics required by organizations such as the Joint Commission and

Responsible use of quality measures

While it is possible that aspects of quality may be measurable, the ability of obstetrical quality measures to translate into clinical improvements depends greatly on how they are applied. The data source, the group of measures chosen, and the way they are reported can all affect whether the measures can lead to benefits vs unintended harms.

Data sources vary greatly in quality. While direct observation is the gold standard for data collection, it is prohibitively expensive. Medical records are

Future obstetric quality measures

It is difficult to predict the new obstetric quality measures that will emerge in the United States over the next 2-5 years, which is the approximate time required for a new indicator to be vetted and validated through the quality indicator development process. Even an indicator with a broad consensus and clear evidence of link to improved outcome requires a minimum of 20–24 months from conception to implementation.10

Much can be learned from other countries that have a political mandate to

What is needed for measurement to occur?

Three things are needed to enhance measurement reporting. First, a uniform core data set, perhaps even a registry of all births with a unique medical identification number that can allow for longitudinal follow-up, would facilitate quality indicator reporting. This is the model utilized by Denmark and other Scandinavian countries allowing for epidemiologic studies and population-based outcomes. Because many adverse events in childbirth are rare, the United Kingdom (UK) has a national obstetric

What will make quality metric reporting in obstetrics inevitable?

We must embrace the need for improvement and continue to engage all stakeholders in measurement to define the purpose of the measures. Several phenomena are occurring, making the need for consensus about what to measure crucial: (1) EMR, wearable bioapplications, and other such health data ultimately will allow for documentation and monitoring of health (clinical data, laboratory data, vital signs, behaviors, clinician notes, orders, referrals, charges) enabling data (processes and outcomes) to

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    A listing of articles in this series that were published in other journals before #36 appeared in the June 2015 issue of AJOG is available at smfm.org/publications/.

    All authors and Committee members have filed a conflict of interest disclosure delineating personal, professional, and/or business interests that might be perceived as a real or potential conflict of interest in relation to this publication. Any conflicts have been resolved through a process approved by the Executive Board. The Society for Maternal-Fetal Medicine has neither solicited nor accepted any commercial involvement in the development of the content of this publication.

    Committee Members: Quality and Safety Committee: Alfred Abuhamad, Peter Bernstein, Meredith Birsner, Steven Clark, C. Andrew Combs, Carey Eppes, Jennifer McNulty, Brian Mercer, Peter Napolitano, Daniel O’Keeffe, Christian Pettker, Patrick Ramsey, Larry Shields

    Committee Members Health Policy: John Albert, Joanne Armstrong, Dana Block-Abraham, Mark Clapp, Rebekah Gee, William Grobman, Lisa Hollier, Irogue Igbinosa, Men Jean Lee, Sarah Little, James Meserow, Emily Miller, George Saade, Katie Schuber, Erika Werner

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