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ACOG’s “reVITALize” Project Wants Your Opinion!

December 20th, 2012 by avatar

By Christine H. Morton, PhD

The American Congress of Obstetricians and Gynecologists (ACOG) has undertaken the reVITALize Project and they want your help, thoughts and input. A significant revolution is underway in maternity care.  With increased attention on maternal health outcomes, the measurement and reporting of key maternal quality metrics is on the agenda of childbearing women, maternal health advocates, payers and purchasers, hospitals, regulatory agencies and maternity care clinicians.    An important element of this revolution is an effort to clearly define what we mean when we talk about pregnancy and childbirth in the data sources most utilized in developing these measures – patient medical charts, registries, electronic medical records, patient discharge data, and our vital statistics (birth certificates).

This is an important and critical opportunity for all stakeholders in US Maternity Care to contribute to the national dialogue on measuring maternal health outcomes.

From the ACOG website: 

The reVITALize Obstetric Data Definitions Conference in early August 2012 brought together over 80 national leaders in women’s health care with the common goal of standardizing clinical obstetric data definitions for use in registries, electronic medical record systems, and vital statistics. Over the course of the two-day in-person meeting and the months that followed, more than 60 obstetrical definitions were reviewed, discussed, and refined.  Data elements included: induction of labor, gestational age and term, parity, TOLAC, and more. The full executive summary of the reVITALize Obstetric Data Definitions Conference can be read here.

The public comment period for the definitions of these data elements ends January 15, 2013. To submit comments, click on one of the category links below to open the respective Public Comment form. The data elements contained within each Public Comment form have been grouped according to category; the data elements assigned to each category are listed under the category heading below. You are permitted to comment on any number of categories. You can also view an alphabetical listing of all data elements available for comment here.

Delivery
• Cesarean Delivery
• Date of Delivery
• Forceps Assistance
• Malpresentation
• Perineal Lacerations
• Placenta Accreta
• Primary Cesarean Delivery
• Repeat Cesarean Delivery
• Shoulder Dystocia
• Spontaneous Vaginal Delivery
• Vacuum Assistance
• Vaginal Birth After Cesarean
• Vertex Presentation

Gestational Age & Term
• Preterm
• Early Term
• Full Term
• Late Term
• Post Term
• Estimated Date of Delivery
• Gestational Age (calculation formula)

Labor
• Artificial Rupture of Membranes
• Augmentation of Labor
• Duration of Ruptured Membranes
• Induction of Labor
• Labor
• Labor After Cesarean
• Non-Medically Indicated Induction of Labor or Cesarean Delivery
• Number of Centimeters Dilated on Admission
• Onset of Labor
• Pharmacologic Induction of Labor
• Physiologic Childbirth
• Pre-Labor Rupture of Membranes
• Spontaneous Labor and Birth
• Spontaneous Onset of Labor
• Spontaneous Rupture of Membranes

Maternal Indicators: Current Co-Morbidities and Complications
• Abruption
• Antenatal Small for Gestational Age
• Any Antenatal Steroids
• Clinical Chorioamnionitis
• Depression
• Early Postpartum Hemorrhage
• Oligohydramnios – HOLD; Pending Further Revision
• Polyhydramnios – HOLD: Pending Further Revision

Maternal Indicators: Historical Diagnoses
• Chronic Hypertension
• Gravida
• Maternal Weight Gain During Pregnancy
• Non-Cesarean Uterine Surgery
• Nulliparous
• Parity
• Plurality
• Positive GBS Risk Status
• Pre-Gestational Diabetes

How to Submit Effective Comments

In order to make the process as productive as possible, please keep the following in mind when commenting:

• Be clear. Clearly identify the issues on which you are commenting and explain your reasons for your position.
• Be concise. Although there is no minimum or maximum requirement for comments, it is best to keep your comments short and to the point.
• Suggest alternatives. If you identify a problem with the proposed definition on which you are commenting, consider suggesting an alternative.
• Spread the word. If you know others who can provide helpful comments, please direct them to www.acog.org/revitalize  for more information.

What happens to comments after they are submitted?

http://flic.kr/p/8Box52

All comments received during the Public Comment period will be reviewed and logged for consideration and careful review by reVITALize leadership. The leadership teams are comprised of both clinical and operational members. Comments will be reviewed and responded to accordingly and will help to form the basis for any additional changes that need to be made to the refined definitions prior to final approval. Should comments require further clarification, the individual submitting the comment may be contacted during the review period to obtain any clarifying information needed to make an informed and appropriate decision regarding a potential revision.

Thank you for your help in making this initiative a success! Any questions or concerns should be directed to QI@acog.org

ACOG, Evidence Based Medicine, Guest Posts, Legal Issues, Maternal Quality Improvement, Research, Research Opportunities , , , ,

Part One: Maternal Morbidity and Mortality in the United States: where do we go from here?

January 2nd, 2012 by avatar

Last week, we featured the five-part completion of Christine Morton and Kathleen Pine’s assessment of the current Maternal Quality Care landscape in the United StatesWhat a great way to close out the year by scrutinizing the measures our nation is taking–at both the federal and community levels–to improve the quality of maternity care.  This week, as we contemplate the year that lies before us, I would like to add some additional thoughts on the state of our maternity care system, and offer some ideas on policy and programming that might be instituted at various levels to continue that process of improvement.

On December 16, 2011, Diane Sawyer and her 20/20 team ran a special episode entitled, Giving Birth:  A Risky Proposition.  The forty-minute segment spoke of the risks associated with giving birth in some of the poorest places on earth–and the people and organizations who are working to change that.  Unarguably, women in many places outside the U.S. face down a life-and-death proposition with each conception and birth, and when we look at our maternity care system, comparatively, we are able to utter those powerful words: we are so lucky.  And yet…

Last semester in my Public Health MCH program, I wrote a series of papers looking at the maternal morbidity and mortality rates here in the U.S. and what type of attention these issues seem to garner at our own federal and local legislation and community levels.  Over the next five days, I’d like to share some of these thoughts with you.
[note: references for this five-day series will be made available at the conclusion of the last post]


Maternal Mortality:  An Overview of the Increasing Trend in the United States

According to the preliminary, 2009 data from the Centers for Disease Control and Prevention’s National Vital Statistics Reports, the leading five causes of death in the United States remain: heart disease, cancer, chronic (lower) respiratory disease, cerebrovascular disease and accidents (Centers for Disease Control, 2011). According to the CDC Vital Statistics report, 10 out of the 15 leading causes of death in the U.S. decreased in total number of people affected between 2008 and 2009. As these causes of death continue to gain—and benefit from—public health attention, their relative risk to the general population is gradually dropping.  However, there is another cause of death in the United States which has garnered much less public health attention, despite an increase in recent decades.

According to the report, Trends in Maternal Mortality: 1990-2008 (World Health Organization, 2010) between the years of 1990 – 2008, the estimated maternal mortality ratio for the United States increased from 12 to 24/100,000—an increase of 3.7% per year. A more conservative estimate places our ratio at 12.7 deaths per 100,000 live births (U.S. Department of Health and Human Services, 2010). Amnesty International’s Deadly Delivery Report (2011), cautions that while 147 countries decreased their maternal mortality numbers, 23 countries experienced an increase—the United States being one of them.  And according to the report, Maternal Mortality in the United States, 1935-2007 (Singh, 2010) of the roughly 4 million women who give birth in the U.S. each year, black, Native American and low income/impoverished women maintained significantly higher maternal mortality rates than women of other races.  In fact in 2005, the maternal mortality rate for African American women was 36.5 per 100,000 (Kung, Hoyert, Xu, & Murphy, 2005). While 99% of global maternal mortality incidences occur in developing nations (World Health Organization, 2010), there seems to be a disturbing disconnect between the otherwise excellent medical system the United States boasts, and this increasing trend in maternal death.  With 2015 looming, the fifth of the Millennium Development Goals—to decrease world-wide maternal mortality by 75%, and our country’s maternal mortality ratio to 3.3 deaths per 100,000 live births (Gaskin, 2008)—seems to be a long way off for those nations like ours which are still experiencing increases in maternal mortality (http://www.un.org/millenniumgoals/maternal.shtml).
Maternal mortality is defined as follows: the death of a female of childbearing age during or within 42 days of the completion of pregnancy, due to complications associated with the pregnancy, or management of the pregnancy, and excluding non-pregnancy-related accidents or injuries (Ronsmans & Graham, 2006).   The primary causes of maternal death world-wide are severe bleeding, hypertensive diseases, and infections.  Here in the U.S., hemorrhage is also the leading cause, followed by embolism and hypertensive disorders (Berg, Atrash, Koonin & Tucker, 1996).
Despite the estimated $86 billion per year spent on pregnancy-related hospitalization, women who are pregnant and giving birth in the United States are more likely to die during this time in their lives than they are in 50 other countries around the world (Amnesty International, 2011).  In 2007, there were 548 officially documented maternal deaths—slightly higher than the U.S. Department of Health and Human Services’ estimation of 12.7 deaths per 100,000 live births (U.S. Department of Health and Human Services, 2010).  Perhaps then, the simplistic question to ask is, “If we are spending so much money each year on maternity care, why is the maternal death rate in our country climbing when expenditures—estimated to be in the hundreds of billions of dollars—on other health conditions, such as cardiovascular disease, are resulting in declining death rates?” (Heindrich, et al., 2011)
From Amnesty International’s Deadly Delivery report: “According to the Centers for Disease Control and Prevention (CDC), approximately half of all maternal deaths in the USA are preventable. Preventable maternal mortality is not just a public health issue, it is a human rights issue.” (Amnesty International, 2011)

            Beyond being a public health and human rights issue, maternal mortality in the United States is a systemic tracking issue. Compared to the United Kingdom where a maternal mortality auditing report entitled, Saving Mothers’ Lives: Reviewing Maternal Deaths to Make Motherhood Safer is published every triennium, here in the U.S. we have no federally mandated method of tracking pregnancy-related deaths (Confidential Enquiry into Maternal and Child Health [CEMACH], 2007).  Disappointingly, 29 of our states have no internal maternal mortality review procedure in place (Amnesty International, 2011).  Without a centralized method to track deaths pertaining to pregnancy, estimates of maternal mortality in our country are little more than that—crude estimates which may represent gross underreporting.

 

In tomorrow’s post, I will suggest ways of implementing several health behavior models which might be employed to start chipping away at our country’s excalating maternal morbidity and mortality rates.

Posted by:  Kimmelin Hull, PA, LCCE, FACCE

 

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The Maternal Quality Landscape–Part Three, Segment Five: How do we measure AND achieve it?

December 30th, 2011 by avatar

[Editor’s Note:  In this final segment of Christine Morton and Kathleen Pine’s series on the Maternal Quality Care landscape in the United States, the post authors look at where the <39 weeks elective deliveries bans have been effective, and where such attempts may have some unintended outcomes.  Finally, Morton and Pine offer a feasible list of actions childbirth educators and doulas can take in their own communities.  To read this entire series from the beginning, go here.]

 

Unintended consequences

We would like to now draw your attention to some of the unintended consequences of quality measurement.

 There has been strong support for this initiative among many stakeholders, including ACOG, the March of Dimes, and several National Quality organizations, such as NQF, TJC and Leapfrog.  Many states or major hospital systems have convened collaboratives, such as Ohio and Intermountain HealthCare in Utah, and several more are in the works, such as North Carolina, Oregon, Oklahoma and Illinois.  State Medicaid programs are expressing interest, especially in payment reforms and commercial insurance companies have launched initiatives, such as Anthem Blue Cross Patient Safety First initiative in California.  This type of support from a wide range of stakeholders is impressive, and positive.  Yet, some stakeholders promoting the <39 weeks measure assumed its adoption would lead to a significant reduction in the overall cesarean section rate.   Unfortunately, this assumption is largely unwarranted since only about 4-10% of all births are elective deliveries between 37 and 39 weeks, and most of these are scheduled repeat cesareans.

 Another unintended consequence is that this measure may affect the way elective inductions are scheduled.  At the micro-level, it is possible that schedulers may simply schedule inductions so as to not negatively impact the hospital’s statistics (for example, by scheduling inductions automatically for 39 weeks and 1 day gestation).  However, this brings up a big-picture question: If we focus on 39 weeks, what are we doing to prevent elective inductions at any gestational age, which may arguably be the bigger issue?  It is possible that this measure may sensitize stakeholders to the wrong issue: timing of birth rather than the fact that it is generally best when labor begins on its own.  Additionally, is it possible that 39 weeks could become the new “ideal” gestational age, because it will be assumed that 39 completed weeks is the best time to be born?  While the measure does not state that 39 weeks is ideal for all inductions, providers and the general public may not understand that selecting 39 weeks as an upper limit is not an endorsement of this age as the ideal age to be born.

 

 

The last unintended consequence we discuss has to do with how the public message is conveyed via the media, such as the recent NPR story with the title, “Doctors to Pregnant Women: Wait at Least 39 Weeks.”  Some reports, like the one in the Portland Tribune, cover the issue in a balanced way, and note that there are pressures/drivers from both women and physicians in early term deliveries.  Yet, others, with headlines like “More hospitals banning elective C-sections” convey the message that women have been the driving force behind this trend in early deliveries and hospitals/providers are finally drawing the line in the sand.   Data from Listening to Mothers II doesn’t support such claims, but while it’s true some women seek early elective deliveries there are also physicians who recommend or ‘lead women’ to that decision.   After all, women can’t schedule a cesarean or an induction – only hospital staff can, upon orders from a provider.   The result of this framing is that public comments on such stories often take women to task for being selfish and unthinking, unfit mothers. There are a few who provide the other side, however, citing providers as drivers, and hospitals as willing partners, of the increase in early deliveries.

 

What can childbirth educators and doulas do?

  • Take advantage of education resources, including the March of Dimes’ “brain card” which illustrates the differences in brain development at 35 and 40 weeks of pregnancy, and can be used to help women understand the importance of waiting.
  • Share this excellent article by Kathleen Rice Simpson and colleagues on the success of an educational intervention to decrease the rate of elective labor indication among nulliparous women at a community hospital with hospital staff in your community, and implement in your own classes.
  • Make sure your local hospital maternity nursing staff is aware of AWHONN’s new education campaign: “40 Reasons to Go the Full 40 Weeks.”
  • Reach out to a local March of Dimes organization to partner with them on a public education seminar- this is an issue for the general public as much as for pregnant women.  March of Dimes chapters tend to have good relationships with hospitals and may be a new ally in your community for promoting optimal birth practices.
  • Set up Google Alerts for key words (“Elective Deliveries” “cesarean”) so that you are notified by email when new content appears online (news or blogs).  Then monitor the public comments pages and offer your perspective as a childbirth educator/doula and be sure to include information on your services or cite Lamaze as a place for people to get evidence based information.
  • Ask the perinatal nurse manager at your local hospital(s) whether the facility is going to report on TJC perinatal measure set.  If not, ask when they plan to, and who in the hospital is the decision maker.   But understand it may be a struggle for hospitals to report on this measure set, and the process might be slower than advocates would like.
  •  Reach out to non-mainstream audiences, especially among those who are not likely to attend typical childbirth classes but who may be at greater risk for elective deliveries –Latinas, African American women, younger and non-native English speaking women and those without partners.

    Posted by:  Christine Morton, PhD and Kathleen Pine (University of California, Irvine)

    References

 

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The Maternal Quality Landscape–Part Three, Segment Four: How do we measure AND achieve it?

December 29th, 2011 by avatar

[Editor’s note:  Continuing with Christine Morton and Kathleen Pine’s review of U.S. maternal quality care measures assessment this week, and in completion of their three-part series, today they discuss methods of data collection and the problems that sometimes occur in accurate documentation.]

Reporting the Measure
The <39 Weeks measure is a good example of why accuracy in data collection and reporting of measures is important. The Leapfrog Group (a patient safety group that conducts self-selected patient safety and quality surveys with participant hospitals and makes the results public) adopted the measure after its NQF endorsement, and incorporated it into the 2010 Leapfrog survey. When the results of the measure were made public, some hospitals had extremely high ED <39 weeks rates and some had extremely low rates. Such wide variation can indicate true differences in incidence of a procedure, or it can reflect challenges in measurement.  Quality advocates pay close attention to how a measure is calculated, because if the data is challenged as inaccurate, hospitals will not acknowledge they have a quality improvement issue.  In this case, at least some of the variation seen in the Leapfrog data may have been due to hospitals not reporting just those elective deliveries within the specified time frame. Correct measurement is crucial not just to improve quality but to the quality improvement endeavor as a whole.  Hospitals and providers must understand how a measure is correctly executed and have the time and resources to prepare data.  As hospitals and initiatives move forward on this issue, specifications for this measure have been refined.  In the 2011 Leapfrog survey, the measurement specifications were adapted to match those of TJC.  It will be interesting to compare the results in the next survey with those reported in 2010.

Obtaining accurate data
In order to trust that the information being reported by a measure reflects the actual practices in a hospital and their outcomes, the data that the quality measures are built on must be accurate.  <39 weeks presents several potential problems with data accuracy, chief among them:

1) Gestational age.  Although ACOG provides criteria for confirming gestational age (ACOG, 2009), it can be difficult to gauge gestational age effectively, and the further a pregnancy progresses, the more difficult it is. There are two issues: the accuracy of gestational age and consistency in using a particular method to assess it.  Women may not know when their last menstrual period before pregnancy was, and menstrual cycles vary in length.  Ultrasound used in early pregnancy provides a more accurate estimate, but some women do not seek early prenatal care or receive a first trimester ultrasound.  The medical record may indicate gestational age as calculated by last menstrual period, by ultrasound or some other means.   In addition, hospitals vary in terms of which department and what level of staff are assigned to fill in the data required by the birth certificate.  In some cases, birth clerks are assigned this task and may not receive adequate training to ensure they select the most accurate gestational age, if there is more than one estimate in various places throughout the chart.

2) Documentation.  Accurate and complete documentation of the data elements required to make the measurement is crucial.  If something is charted wrong at the bedside, it may be impossible to catch the error in later calculations.  Good documentation practice often requires extensive education of providers from quality analysts and educators.  <39 weeks, for instance, requires providers to accurately record whether a patient was induced, and this becomes an ICD-9 procedure code.  A common mistake in documentation on the part of providers is to note that a patient was augmented with Pitocin when they were actually induced or vice versa.  Definitions of induction can be confusing, it may be difficult to determine whether or not labor started on its own, and those collecting the data often must do extensive “detective work” when one piece of information does not match up with another to create a clear picture of what happened.  The chart review component of this measure can be time consuming.

3) Sampling issues. TJC specifications allow for hospitals use sampling methods to select a random subset of births to calculate the measure. The problem with this is that hospitals with small numbers of births may select a random sample of cases in which there are few elective deliveries < 39 weeks, thus under-reporting the issue.  If instead, obstetric departments work with their medical records or quality department and screen cases (less the excluded ICD-9 codes) for the desired time period, they then use the delivery logbook (electronic or paper) to identify all births occurring between 37-39 weeks.  Those births coded with a cesarean or induction will need to undergo a chart review to ascertain whether the woman had rupture of membranes or was in labor to exclude those cases.  Sampling seems simpler, but has the potential to be the victim of the law of small numbers, leaving hospitals with nothing to report but not necessarily accurate.  Doing chart review can be time-consuming – for a hospital with about 100 births a month, this simplified approach would result in about 8-10 births needing a chart review.  At an estimated 15-20 minutes per chart review, this entails 2-3 hours per month to collect the data for the <39 weeks measure.

4) Redefining the issue.  It may be that by adopting a hard stop policy, hospitals will be successful in reducing early inductions.  However, rather than charting the intervention as an ‘induction,’ hospital staff may instead chart the intervention as an ‘augmentation,’ with a concomitant rise in augmentations.  It is important for quality measure advocates to develop mechanisms to ensure that focused attention on reducing one practice do not result in increasing the incidence of another, related practice.  It also means that a set of ‘balancing’ measures can be helpful to avoid certain processes/outcomes being relabeled.

[Tomorrow, Christine and Kathleen will complete this series with a look at the unintended consequences that sometimes coincide with <39 weeks messaging, as well as a call to action for childbirth educators and doulas.  To read segment one go here.  To read this series from the beginning, go here.]

 

Posted by:  Chritine Morton PhD and Kathleem Pine, University of California, Irvine

Maternal Quality Improvement, Maternity Care, Uncategorized , , , , , , , , , , , , ,

The Maternal Quality Landscape–Part Three, Segment Three: How do we measure AND achieve it?

December 28th, 2011 by avatar

How Hospitals Measure ED < 39 Weeks

 

Next we discuss how hospitals actually compile the data elements needed to calculate their rate of elective deliveries occurring between 37 and 39 completed weeks gestation.  It is crucial to remember that successful quality measurement depends on the local practices of collecting data, making calculations, and reporting data to quality improvement organizations.  Each hospital and unit presents a different configuration of personnel, technology, documentation practices, and other resources, thus conducting measurements in practice may look quite different from one context to the next.  As we noted in our first post, maternal quality measures are fairly recent.  Hospitals have long reported on measures but obstetrics departments may not have the staff or training to do the work necessary to accurately collect and report on the newer maternal quality measures.  Obstetrics has long been considered an “island” in the hospital, with little crossover in terms of staff or patient population, and thus may not have much experience working with the quality department.  To further complicate the situation, it turns out that there are several dilemmas faced by hospitals, providers, and quality analysts as they perform the local practices of quality measurement.

 

Measure Specifications
The Joint Commission publishes the specifications
for calculating the perinatal quality measures.  The premise of the <39 weeks measure is to calculate a percentage by dividing the number of women who had elective deliveries between 37 and 39 weeks (the numerator) by the total number of women who had elective deliveries (the denominator).  One basic sequence of steps in calculating the measure is:

1) Identify births to all mothers between 8 and 65 years old who were not part of clinical trials;

2) Exclude all mothers with an ICD-9 code on the exclusion list (see box);

3) Exclude all mothers where the birth occurred at less than 37 or more than 39 completed weeks’ gestation;

4) Of those identified so far, include those mothers who had a cesarean section or induction of labor by ICD-9 code.

5) By chart review, exclude those labor inductions or cesarean deliveries done after spontaneous rupture of membranes and/or active labor.

Five steps doesn’t seem so bad!  However, calculating the measure in practice can be quite tricky.  In most hospitals, the data elements needed for each step are found in the patient discharge database containing ICD-9 codes, the birth certificate and/or the delivery logbook and the actual medical chart.  Assembling all these sources of information can be challenging, as we describe below.

 

Deciding on exclusions
There are a number of reasons that elective delivery between 37 and 39 weeks may be medically indicated.  The Joint Commission lists such “exclusions” in its specifications manual and the most recent of these are noted in the box.  These cases are “exclusions” to the denominator- they must be pulled out before the calculation is made.  Although it is possible to identify and list a number of likely scenarios that would be appropriate to exclude, it is impossible to account for every possible scenario that may make early delivery an appropriate choice.  This is acknowledged as an issue by the authors of the <39 Weeks Toolkit:

 

For the purposes of creating a quality measure that was not overly labor intensive to collect, TJC chose to utilize diagnoses that had ICD-9 codes no matter if some codes were over-inclusive (gestational diabetes) or simply not available (prior vertical cesarean section scar). TJC has noted during private conversations with CMQCC leaders that the list of codes is not exhaustive and anticipates that every hospital will have some cases of medically justified elective deliveries prior to 39 weeks that are not on the TJC list. Therefore, each hospital, hospital system or perinatal region should, based on the available evidence, set their own internal medical standards for conditions that justify a scheduled delivery prior to 39 weeks. Note that too loose an internal standard will become apparent once hospitals are publically compared (Main et al, 2010).

 

Thus, it is up to hospitals to develop their own list of exclusions and decide in unusual cases whether early elective delivery was justified or not.  Quality advocates work under the assumption that sloppy or inaccurate measurement practices will be reflected in the data but not until the measure is collected and rates publically reported will it become obvious if a hospital has set too loose a standard for medically-justified elective delivery.

 

[Tomorrow’s post will look at data collection and reporting, and the pitfalls that sometimes occur in the process.  To read segment one go here.  To read from the beginning of this series, go here.]

 

Posted by:  Christine Morton, PhD and Kathleen Pine, University of California, Irvine

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