section i. basic measure information - st. louis children ... · pdf filei.a. measure name...

Nomination of Children’s Health Care Quality Measures for Potential Inclusion in the CHIPRA Improved Core Set of Health Care Quality Measures for Medicaid/CHIP Or Other Public Purpose

(OMB Version 02/06/2012)

Section I. Basic Measure Information I.A. Measure Name Recording radiation exposure from diagnostic computed tomography exams

I. B. Measure Description Please provide a non-technical description of the measure that conveys what it measures to a broad audience.

Children frequently undergo computed tomography (CT) scans to determine the cause of their illness and guide the subsequent treatment. While these procedures provide great benefit, they expose children to the harmful effects of x-rays. While efforts are continually made to reduce these risks, a better understanding of X-ray use in children is needed to improve the balance between risks and benefits. The first step in this process will be encouraging hospitals and clinics to routinely report the intensity of these X-ray exposures in the child’s electronic medical record. The measure is part of a future measure hierarchy on healthcare associated exposure to ionizing radiation.

I.B.1. Measure Hierarchy Please note here if the measure is part of a measure group or composite measure:

a. Please identify the name of the collection of measures to which the measure belongs (if applicable). A Collection is the highest possible level of the measure hierarchy. A Collection may contain one or more Sets, Subsets, Composites, and/or Individual Measures.

Healthcare associated exposure to ionizing radiation

b. Please identify the name of the measure set to which the measure belongs (if applicable). A Set is the second level of the hierarchy. A Set may include one or more Subsets, Composites, and/or Individual Measures.

Radiation exposure during diagnostic examinations

c. Please identify the name of the subset to which the measure belongs (if applicable). A Subset is the third level of the hierarchy. A Subset may include one or more Composites, and/or Individual Measures.

Radiation exposure during diagnostic computed tomography exams

d. Please identify the name of the composite measure to which the measure belongs (if applicable). A Composite is a measure with a score that is an aggregate of scores from other measures. A Composite may include one or more other Composites and/or Individual Measures. Composites may comprise component Measures that can or cannot be used on their own; this information is provided in the Description field of the Measure Summaries.

This measure is currently not part of a composite measure. In the future, it will be combined with measures of exposure for common exams and used to determine what fraction of a facility’s common CT scans fall within the expected range.

I.C. Denominator Statement (as appropriate) Number of diagnostic computed tomography exams performed at a facility



I.D. Numerator Statement (as appropriate) Number of diagnostic computed tomography exams where metrics of radiation exposure are recorded in the electronic medical record

I.E. Data Sources

Check off all data sources specified by the measure.

Data Source [Online form will have radio buttons

here]

1.Administrative Claims Yes

2. Paper Medical Record

3. Survey – Health care professional report

4. Survey – Parent/caregiver report

5. Survey – Child report

6. Electronic Medical Record Yes

7. Other

If other, please list all other data sources in the field below. For the purposes of this measure, the electronic medical record includes:

a. The Picture Archiving and Communication Systems (PACS), commonly used to organize and store medical images

b. The radiology report that describes the diagnostic implications of the CT images c. The Radiology Information System and associated databases which contain measures of

radiation exposure

I.G. Exclusions None

I.H. Measure Owner and National Quality Forum (NQF) ID (if applicable) A. Measure Owner St. Louis Children’s Hospital B. National Qualify Forum ID number (if applicable) Not applicable

Section II: Summary Statement Provide a summary rationale for why the measure should be selected for use, taking into account a balance among desirable attributes of the measure. Please highlight specific advantages that this measure has over alternative measures on the same topic that were considered by the measure developer or specific advantages that this measure has over existing measures.



Radiation exposure is a compelling public health problem. Until recently, exposure was predominantly from natural sources such as radon and resulted in an annual per capita dose of approximately 2.7 mSv. However the growth of medical imaging where studies routinely exceed 10mSv means that the dominant source is now medical imaging (Figure 1). A convenient rule of thumb is that the lifelong risk of a future cancer increases by 1 in 1000 for every 10 mSv. This growth in medical imaging means that more and more children are being exposed to ever higher levels of ionizing radiation. While medical imaging provides tremendous benefits, children are particularly sensitive to the damaging effects of x-rays. Although their smaller size allows effective pediatric imaging with lower doses of x-rays, adult settings are often used to image children. These factors compound the risks and it is common to find children who underwent imaging for abdominal pain or minor head trauma where there future health risks are 10 fold higher than necessary.

Year

1950 1960 1970 1980 1990 2000 2010

US

Per

Cap

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ose

(m

Sv)

0

1

2

3

4

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6

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Natural Sources

Medical

Figure 1 Trends in US per capita exposure to ionizing radiation. Before 1970, the predominant source of ionizing radiation was from natural sources but since then, there has been a rapid increase in medical imaging that has doubled the per capita exposure. CT is the largest contributor due to the marked increase in the number of CT studies and the substantial radiation dose needed to create the 10-300 images in a typical CT study. Increases in nuclear medicine studies and fluoroscopic interventions have also played a role. Adapted from Mettler et al, Radiology 2009; 253:520.

Efforts have been made to assess the societal benefits of optimizing radiation use. FDA researchers previously calculated the benefits of a modest (15%) reduction in dose during fluoroscopic procedures. Using 1995 data, they estimated a nationwide benefit of $320 million per year. Most of this benefit accrued from upper gastrointestinal (UGI) exams in children (Figure 2). We expect analysis of CT studies would demonstrate a similar pattern where small improvements in common exams (CT exams performed for minor head trauma or abdominal pain) during the first two decades of life would provide substantial cost savings. We recently estimated that since 2005, the changes in CT alone at St. Louis Children’s Hospital (Figure 3) have likely prevented nearly 5 future deaths from cancer. Using the FDA’s estimate of $5M for each statistical death avoided, these efforts are estimated to have saved more than $20M.

Figure 2. Benefits of a small reduction in radiation dose during common procedures. Investigators from the FDA modeled the benefits that might be observed 10 years after a 15% reduction in radiation exposure during upper GI series (black), diagnostic coronary angiography (red) and coronary angioplasty (blue). The projected years of life saved was estimated using dose savings, exam frequency, excess mortality due to cancer and years of life remaining. Their figures demonstrate the vast majority of benefit would accrue in children and young adults undergoing routine upper GI exams. This benefit would be in addition to the far larger projected years of life saved if radiation exposure for CT scans was reduced 15%. Adapted from Federal Register 2005, 70: 33997.

Although the above figure highlights the risks associated with fluoroscopic procedures, the proposed measure focuses on CT since CT is much more common and results in a higher per capita exposure. In addition, CT exams are more amenable to standardization and the systems used to capture and analyze exposure from CT exams are more mature. Finally, the data from our center and others suggests that efforts to reduce childhood radiation exposure from CT have been successful both by reducing the reducing the number of CT exams and the exposure/CT exam.



0

500

1000

Barnes-Jewish Hospital (Adult Focused Facility)

CT

Scan V

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5000

National data for 0-18 yr olds

1996 1998 2000 2002 2004 2006 2008 2010 2012

ER

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%)

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St Louis Children's Hospital

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Figure 3. CT volume. The monthly CT volume at St. Louis Children’s Hospital and Barnes-Jewish Hospital was obtained from administrative datasets and showed that CT volume steadily increased at both institutions between 1996 and 2005. This mirrors national trends as illustrated by increased CT utilization in emergency rooms across the nation (bottom panel). Since 2005, CT volume at St Louis Children’s Hospital has steadily decreased while CT volume at the adjacent adult focused facility and ERs around the country has continued to increase. The small decrease in CT volume at Barnes-Jewish Hospital in 2011 is attributed to a change in CT billing practices rather than a decrease in CT volume.

Section III: Detailed Measure Specifications

Description The proportion of diagnostic CT scans where a measure of radiation exposure is recorded in the

medical record

Eligible population All patients less than 21 years of age who undergo a diagnostic CT scan. Enrollment will be

continuous.

Administrative Specification Any facility that uses a computed tomography (CT) x-ray system for medical diagnosis in children

would record a measure of x-ray exposure in the electronic medical record. Compliant methods of recording x-ray exposure include:

1. Storing a copy of the protocol page that lists the technical factors and measure of radiation exposure in the facility’s electronic picture archiving and communications systems (PACS)

2. Including a single suitable metric of radiation exposure in the radiology report which describes the study’s findings and interpretation. Suitable metrics include any of the following:



a. Computed Tomography Dose Index Volume (CTDIvol) b. Dose Length Product (DLP) c. Size-Specific Dose Estimate (SSDE) d. Other metric recommended by the American Association of Physicists in Medicine (AAPM)

3. Including one or more of the metrics described above in a separate facility database. This could include storing detailed records of the exposure using the format specified by the Digital Communications in Medicine (DICOM) Supplement 127, CT Radiation Dose Reporting (Dose SR). These reports might be sent to the PACS as non-image files and later processed or loaded directly into the separate database. Alternatively, radiation metric(s) could be manually entered into the database after each CT exam is completed.

Denominator and Numerators

Numerator and Source

Denominator and Source

Linkage Quality Metric Calculation

Metric embedded within radiology report

CT specific CPT codes in administrative claims*

Report links radiation metric to billing codes

Manual audit of reports

Metric embedded within images stored on PACS


PACS includes metadata which is used to link images to billing system

Electronic calculation following extraction of radiation metrics from PACS

Metric stored in radiation database


Database establishes linkage

Electronic calculation

*Diagnostic CT CPT codes in administrative claims currently include:

70450, 70460, 70470, 70480, 70481, 70482, 70486, 70487, 70488, 70490, 70491, 70492, 70496, 70498, 71250, 71260, 71270, 71275, 72125, 72126, 72127, 72128, 72129, 72130, 72131, 72132, 72133, 72191, 72192, 72193, 72194, 73200, 73201, 73202, 73700, 73701, 73702, 73706, 74150, 74160, 74170, 74174, 74175, 74176, 74177, 74178, 74261, 76262, 74263, 75571, 75572, 75573, 75574, 75635, 76380, 77078, 78814, 78815, 78816

Section IV: Importance of the Measure

IV. A. Importance

Provide brief descriptions of how the measure meets one or more of the following criteria for measure importance, citing scientific literature and providing references or data.

References are provided in Section IV D following the glossary.

IV.A.1. Evidence for general importance of the measure

Provide evidence for all applicable aspects of general importance:

The increasing number of CT scans have raised concerns about the long term risks of medical imaging. Berrington et al estimated that 72 million CT scans were performed in 2007 and 5 million of these were performed on children1. They used that information to estimate the potential future cancer risks and calculated that the pediatric CT scans performed in 2007 would eventually induce approximately 5300 additional cancers in children less than 21 years old (Figure 4).



Figure 4. Predicted number of future cancers that could be related to CT scans performed in 2007

1. They used Medicare

claims data and surveys of CT use from 2451 US facilities to estimate the frequency of different CT scans. These estimates were scaled to the US population. CT exposure data for each scan type was taken from the FDA’s National Evaluation of X-Ray Trends survey and used to estimate organ specific doses. The incidence of future cancer was then calculated using risk projection models that were based on the National Research Council’s “Biological Effects of Ionizing Radiation” report

6.

One clear quality gap is the marked variation in CT utilization for pediatric patients with common conditions such as abdominal pain and minor head trauma. Our institutional data coincides with Larson et al’s finding that when children present to an pediatric focused emergency room they were less likely to undergo CT scanning than if they went to an adult focused facility2. The denominator of this quality metric will provide insight into CT utilization for pediatric patients and the numerator will identify sites that are committed to improving quality and safety by tracking exposure/CT exam.

In addition to variations in CT utilization, variation in CT exposure/exam is another quality gap. When exposure/exam data from St Louis Children’s Hospital was compared to adult focused facilities in our system, we found that two fold differences were common. Further when families bring in outside CT studies for review, we find that young children are still being imaged with adult protocols. This often leads to exposures that are 10 fold higher than those used at St Louis Children’s Hospital. These results agree well with published reports where some exams exhibited 20 fold variation in exposure/exam3, 4 and adult protocols were being used to image children5.

These quality gaps are especially important for chronically ill children since they are more likely to repeatedly undergo CT imaging. Indeed, we expect that the temporal pattern and intensity of radiation exposure will correlate with the severity of illness. Radiation exposure also has long term health consequences, since the detrimental effects of ionizing radiation accumulate over a lifetime and the available data (Figure 4) indicates that future cancer risks are weighted towards childhood exposure. There is also increasing concern about the risks of radiation induced organ dysfunction and germline mutation6.

Risk of future cancer after exposing 100,000 women to a single dose of 100 mGy

Age at Exposure (years)

0 20 40 60 80

Lifetim

e A

ttributa

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Ris

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Figure 4 Children are a particularly vulnerable population because they are far more sensitive to the detrimental effects of ionizing radiation. The risks of developing cancer after exposure to ionizing radiation have been repeatedly estimated. The most recent report by the National Academy of Sciences Committee to Assess Health Risks from Exposure to Low Levels of Ionizing Radiation provided these estimates

6. The risks of germline

mutations that are passed to future generations and the risks of radiation induced organ dysfunction are in addition to these estimated cancer risks.



Our experience indicates that the fiscal burden of measuring CT utilization and CT exposure/exam is small since radiology departments already have a robust informatics infrastructure. The development of standardized reporting formats such as DICOM structured reports (DICOM-SR) that include detailed records of radiation exposure will not only reduce data capture costs but also improve the data’s accuracy.

IV.A.2. Evidence for importance of the measure to Medicaid and/or CHIP

Comment on any specific features of this measure important to Medicaid and/or CHIP that are additional to the evidence of importance described above, including:

- The extent to which the measure is understood to be sensitive to changes in Medicaid and/or CHIP (e.g., policy changes, quality improvement strategies).

- Relevance to the Early and Periodic Screening, Diagnostic and Treatment benefit in Medicaid.1 - Please describe any other specific relevance to Medicaid/CHIP or to populations overrepresented in

Medicaid or CHIP.

The overrepresentation of children with chronic diseases in Medicaid and CHIP and the probability that they will repeatedly undergo CT scans is discussed above. This metric is the first in a set of measures that will help programs like Medicaid and CHIP link utilization rates to facilities and patients. Given the long time frames involved, this is the first step in monitoring utilization across a variety of timeframes that include exposure per exam, exposure per hospitalization, exposure per illness and exposure per year, decade or lifetime. Once measured, each should be amenable to improvement.

IV. A. 3. Relationship to other measure, if any

Please describe how this measure complements or improves on an existing measure in this topic area for the child or adult population (if known), or if it is intended to fill a specific gap in an existing measure or whether this question does not apply.

No existing measures are in place for CT. This measure is complementary to PQRI Measure #145, Exposure Time Reported for Procedures Using Fluoroscopy.

1 The Early and Periodic Screening, Diagnostic and Treatment service, EPSDT, is a comprehensive set of benefits available to

children and youth under age 21 who are enrolled in Medicaid. For more information, see http://www.healthlaw.org/images/stories/epsdt/3-ESDPT08.pdf 2 Public Law 111-3, Available at: http://frwebgate.access.gpo.gov/cgi-

bin/getdoc.cgi?dbname=111_cong_public_laws&docid=f:publ003.111 3 Under Section 214 of CHIPRA, states may elect to cover the following groups under Medicaid only or under both Medicaid

and CHIP: pregnant women and children up to age 19 for CHIP or up to age 21 for Medicaid.

http://www.healthlaw.org/images/stories/epsdt/3-ESDPT08.pdf

http://frwebgate.access.gpo.gov/cgi-bin/getdoc.cgi?dbname=111_cong_public_laws&docid=f:publ003.111

http://frwebgate.access.gpo.gov/cgi-bin/getdoc.cgi?dbname=111_cong_public_laws&docid=f:publ003.111



IV.B. Measure Categories

Does the measure address this category [Yes/No drop-down]

a. Care Setting – ambulatory Yes

b. Care Setting – inpatient Yes

c. Care Setting – other—please specify

No [Add the following choices: home, school, long-term care,

other---drop-down or radio buttons]

NA

d. Service – preventive health Yes

e. Service – care for acute conditions

Yes

f. Service - care for children with special health care needs/chronic conditions

Yes

g. Service – health promotion and services to promote healthy birth

No

h. Service-other (please specify)

No

i. Measure Topic -duration of enrollment

Yes

j. Measure Topic – clinical quality

Yes

k. Measure Topic – patient safety

Yes

l. Measure Topic – family experience with care

No

m. Measure Topic – care in the most integrated setting

Yes

n. Measure Topic – other (please specify)

Yes Health of future generations

o. Population – pregnant women

No

p. Population – neonatal (28 days after birth)

Yes

q. Population – infant (29 days to 1 year)

Yes

r. Population – pre-school age children (1 year through 5 years)

Yes

s. Population – school-age children (6 years through 10 years)

Yes

t. Population – adolescents (11 years through 20 years)

Yes



IV.C. Evidence for the Focus of the Measure

The evidence base for the focus of the measures will be made explicit and transparent as part of the public release of CHIPRA deliberations; thus, it is critical for submitters to specify the scientific evidence or other basis for the focus of the measure.

IV.C.1.A. Research Evidence

Research evidence would include a brief description of the evidence base for the relationship between a structure or process of health care that influences outcomes or an outcome that is influenced by a structure or process of health care.

Using the table provided below, describe the nature of the evidence, including study design, and provide up to five relevant citations to that evidence. Use as many rows as necessary to describe the extent of the evidence base or rationale for the measure.

TYPE OF EVIDENCE2

KEY FINDINGS

KEY CITATION(S)

Systematic review of research literature;

Detrimental effects of ionizing radiation and increased sensitivity of children relative to adults

National Research Council, BIER VII Phase 2 Report

6

Research studies and published formal

consensus

Increasing per capita exposure to ionizing radiation due to growth of medical imaging. Increasing exposure of children as part of this trend. Need to record x-ray exposure in the medical record.

Fazel et al7, Mettler et al

8, National

Council on Radiation Protection and Measurement 160

9, Brenner

10, The Joint

Commission11

Research studies Children are commonly imaged at facilities that do not specialize in pediatric imaging. Marked variation in exposure for common CT exams

Berrington et al1, Smith-Bindman et al

3,

Larson et al2

Research studies and published formal

consensus

Pediatric centers have successfully reduced pediatric exposure to ionizing radiation during CT exams

Goske et al12

, Arch and Frush13

2 Definitions and instructions:

A systematic review of the research literature: In the space provided, indicate how the systematic review of evidence has been assessed, for example, according to the guidance of relevant stakeholders, such as those used by the:

Cochrane Collaborative, including EPOC as appropriate (http://www. http://www.cochrane.org/).

U.S. Preventive Services Task Force (http://www.uspreventiveservicestaskforce.org/uspstf07/methods/currprocess.pdf); (http://www.effectivehealthcare.ahrq.gov/tools-and-resources/researcher-resources/)

Oxford Center for Evidence-Based Medicine (http://www.cebm.net/index.aspx?o=1011)

Or other appropriate taxonomy (http://www.equator-network.org/)

Research studies: Published in a National Library of Medicine (NLM) indexed, peer-reviewed journal (specify study design and other critical features relevant to assessing the quality of the study).

Published formal consensus procedure: Involving experts in relevant clinical, methodological, public health, and organizational sciences.

http://www.uspreventiveservicestaskforce.org/uspstf07/methods/currprocess.pdf

http://www.effectivehealthcare.ahrq.gov/tools-and-resources/researcher-resources/

http://www.cebm.net/index.aspx?o=1011



IV.D. Scientific Soundness of the Measure

Please explain the methods used to determine the scientific soundness of the measure itself. Please include results of all tests of validity and reliability, including description(s) of the study sample(s) and methods used to arrive at the results. Note how characteristics of the data system/data sources may impact validity and reliability. A glossary of terms related to reliability and validity is included below

The measure is fairly simple: proportion of CT exams where a record of radiation exposure is recorded in the electronic medical record. A variety of compliant methodologies are proposed and will allow the widest possible range of facilities to develop data capture methodologies that suit their local circumstances.

Method Numerator and Source Denominator and Source

Quality Metric Calculation

1 Metric embedded within radiology report

CT specific CPT codes in administrative claim*

Manual audit of reports

2 Metric embedded within images stored on PACS


Electronic calculation following extraction of radiation metrics from PACS

3 Metric stored in radiation database


Electronic calculation

St Louis Children’s Hospital has been using Method #3 to monitor its performance over the last year (Figure 5). It continues to store a dose report containing the radiation metrics in PACS but chose to have technologists enter the Dose Length Product into the Radiology Information System since that simplifies the Quality Metric Calculation. Many sites are using open source software tools such as RADIANCE14 to extract this data from their PACS and thus might use Method #2. An increasing number of sites are using vendor supported software to create and maintain radiation databases and thus would use Method #3. At other sites, the radiologists might include the radiation metric in their radiology report and those facilities could manually audit reports and calculate the metric. These methods are partly based on recent California legislation where Senate Bill 1237 amended the state Health and Safety Codes (sections 115111, 115112, 115113) to require recording CT exposure metrics in either the radiology report or PACS.

Figure 5 Method #3 was used to calculate the metric from St Louis Children’s Hospital data. That facility conducts between 400-500 CT exams per month and following each study, the CT technologist enters Dose Length Product into the Radiology Information System (Siemens Syngo V31). High compliance was achieved by creating an interactive dialog page that required data entry after each study. While every CT study included a DLP value, we elected to discard nonsensical values such as “0” when calculating the metric. This occurred approximately 1% of the time. In the next twelve months, we plan to transition to a system where radiation metrics are captured electronically via DICOM structured reports since these will avoid the data entry errors that occur in our manual process. Also, the DICOM structured reports will include much more granular data and this will facilitate investigation of outliers.



The proposed methods will leverage administrative claims data to determine the denominator. The number of diagnostic CT codes in any timeframe will be straightforward calculation. Calculating the numerator requires acknowledging that CT scanners do not report exposure metrics alongside their corresponding Current Procedural Terminology (CPT) code. Rather CT scanners report exposure metrics each time the xray generator is activated and a series of images are acquired. Each activation is termed an “irradiation event” and a single irradiation event might be used to image multiple body parts (chest, abdomen and pelvis) during a single injection of iodinated contrast. This single irradiation event would be billed using two separate CPT codes (71260, 74177). Conversely, a single CPT code may describe an exam that requires more than one irradiation event (71270 CT thorax without and with iodinated contrast). While detailed dose reports separately describe the parameters used during each irradiation event, entering a single value into the radiology report usually requires data aggregation.

The intent of the proposed metric is to prompt facilities to record an accurate measure of exposure in the electronic medical record after each CT study. As result, compliance can be achieved by reporting a single value which reflects total exposure during that study even though administrative records might record 1 or more CPT codes for that session. Compliance can also be achieved by reporting detailed metrics from every irradiation event during the entire CT Study.

GLOSSARY

Absorbed Dose – a measure of the energy deposited in a medium by ionizing radiation. It is measured in Gray (Gy). It is important to note that absorbed dose is not a good indicator of the biological effect since some tissues are much more sensitive to the detrimental effects of ionizing radiation.

Current Procedural Terminology (CPT) – the code set maintained by the American Medical Association through its CPT Editorial Panel. The CPT code set describes medical, surgical and diagnostic services and is designed to communicate uniform information about medical services and procedures among physicians, patients, accreditation organizations and payers for administrative, financial and analytical purposes.

CT Dose Index (CTDI and CTDIvol) – a measure of radiation exposure that is typically determined using a CT phantom and ionization chamber which is placed in the center of the phantom. It measures absorbed dose and is expressed in Gray (Gy). The volume CTDI (CTDIvol) is used to express the average dose delivered to the scan volume for a specific examination. It is often considered to reflect the dose estimate per CT slice.

CT Exam – the CT imaging events that result in a single CPT code. A single CT exam includes 1 or more CT irradiation events. In some cases, the exposure metrics from a single CT irradiation event might describe the exposure during 2 or more CT exams.

CT Irradiation Event – the irradiation being applied to a patient in a single continuous timeframe between the start (release) and the stop (cease) of the irradiation. A single sequence of scanning comprised of multiple slices acquired with successive tube rotations and table increments is treated as a single irradiation event.

CT Protocol – the machine settings used to acquire images constitute a CT protocol or imaging plan. Planning each irradiation event requires choosing parameters such as tube current, voltage, slice thickness, table speed, contrast injection. Protocols may also include several irradiation events such as scout image, precontrast, arterial phase, venous phase and delayed. Protocols are often matched to clinical indications (eg. PE Protocol)

CT Scanner – An x-ray system as described in Code of Federal Regulation Title 21 Part 1020. CT scanners typically consist of two parts: an xray generator and array of detectors both of which rotate around the patient to create a series of cross sectional images.

CT Study – the complete set of CT irradiation events and CT exams that occur within a single imaging session. The typical CT study begins and ends when the patient enters and leaves the CT exam room. The CT study may



address one or more discrete clinical questions and involve imaging more or more body regions. For the purposes of the proposed quality measure, a CT study is described by a series of CPT codes and the accumulated series of CT irradiation events.

Digital Imaging and Communications in Medicine (DICOM) – an international standard for handling, storing, and transmitting information in medical imaging. The DICOM standard define file formats and networking protocols. Supplement 127 to the DICOM standard includes a template for Diagnostic X-ray CT Dose Reporting in DICOM (DICOM CT Dose SR or DICOM-SR).

DICOM Structured Reports (DICOM-SR) – an international standard that describes how data from every irradiation event during a CT imaging session will be stored in a computer readable file. The specification includes 30 separate parameters for each CT irradiation event. It also describes how dose value accumulations over several irradiation events will be combined and reported in a CT Accumulated Dose Data report.

Dose Estimate – an estimate of absorbed dose and snonymously with the exposure metric. Dose estimates are an attempt to gauge what fraction of the energy measured outside the patient reached the patient and the potential consequences of that exposure.

Dose Length Product (DLP) – since CTDIvol and SSDE estimate absorbed dose within a single CT slice, Dose Length Product is used to calculate the absorbed dose for the series of images acquired during a CT scan. DLP is calculated by multiplying CTDIvol or SSDE by the scan length. The equivalent dose is estimated by multiplying DLP and a conversion factor that varies with the body region that was imaged.

Electronic medical record (EMR) – patient specific medical information stored in electronic formats. EMR can include text, DICOM images, DICOM structured reports or data elements from a database.

Equivalent dose - computed average measure of the radiation absorbed by a fixed mass of biological tissue. The equivalent dose attempts to account for the different biological damage potential of different types of ionizing radiation. It includes a quality factor that connects the deposited energy of the radiation which can be measured with a sensor to an estimate of the biological reaction or damage from the particular amount and type of radiation. For medical imaging, equivalent dose is measured in milliSieverts (mSv).

Exposure metrics – a measure of xray exposure. For CT, a variety of metrics are used to measure exposure. These can be transformed into estimates of the risks inherent in that xray exposure. Common exposure metrics for CT include the CT Dose Index (CTDIvol), Dose Length Product, and Size Specific Dose Estimate

Facility – hospital or clinic that uses a CT scanner to image pediatric patients

Ionizing radiation – particles that individually can liberate an electron from an atom. The resulting ions tend to be chemically reactive. For medical imaging, the major detrimental effect of ionizing radiation is its tendency to cause double stranded breaks in DNA that cannot be repaired without introducing mutations.

Picture Archiving and Communication System (PACS) – technology which stores and provides access to images from multiple modalities via the DICOM format. The PACS eliminates the need to manually file, retrieve or transport film based images. Non-image data such as scanned documents or CT Dose Reports can be encapsulated within the DICOM format and stored on the PACS.

Pediatric patients - children less than 21 years old at the time of the CT exam

Radiation dose – the physical and biological consequences of how the energy from ionizing radiation interacts with matter. Typically expressed using absorbed dose and equivalent dose. The most concerning biological consequence is damage to the DNA segments that encode genes or regulate gene expression.



Radiation exposure – a setting where patient may be exposed to ionizing radiation. The intensity and duration of that exposure are then used to estimate absorbed and equivalent dose

Radiology Information System (RIS) – database and network infrastructure used by radiology departments to schedule studies, track patients, report results and monitor information flow. The RIS complements and communicates with the Hospital Information System to facilitate exam ordering and results reporting. The RIS also plays a key role in collecting the information needed for preparation of an administrative claim.

Size Specific Dose Estimate(SSDE) – attenuation of the xray beam as it passes through tissue means that the CTDIvol fails to accurately convey the dose absorbed by patients who are substantially larger or smaller than the CT phantom used to calculate the CTDIvol. As a result, Size Specific Dose Estimates have been developed and are especially relevant to calculating the risks of CT for pediatric patients.

REFERENCES 1. Berrington de Gonzalez, A., et al., Projected cancer risks from computed tomographic scans performed in

the United States in 2007. Arch Intern Med, 2009. 169(22): p. 2071-7. 2. Larson, D.B., et al., National trends in CT use in the emergency department: 1995-2007. Radiology, 2011.

258(1): p. 164-73. 3. Smith-Bindman, R., et al., Radiation dose associated with common computed tomography examinations

and the associated lifetime attributable risk of cancer. Arch Intern Med, 2009. 169(22): p. 2078-86. 4. Guite, K.M., et al., Ionizing radiation in abdominal CT: unindicated multiphase scans are an important

source of medically unnecessary exposure. J Am Coll Radiol, 2011. 8(11): p. 756-61. 5. Donnelly, L.F., et al., Minimizing radiation dose for pediatric body applications of single-detector helical

CT: strategies at a large Children's Hospital. AJR Am J Roentgenol, 2001. 176(2): p. 303-6. 6. National Research Council (U.S.). Committee to Assess Health Risks from Exposure to Low Level of Ionizing

Radiation., Health risks from exposure to low levels of ionizing radiation : BEIR VII Phase 2. 2006, Washington, D.C.: National Academies Press. xvi, 406 p.

7. Fazel, R., et al., Exposure to low-dose ionizing radiation from medical imaging procedures. N Engl J Med, 2009. 361(9): p. 849-57.

8. Mettler, F.A., Jr., et al., Radiologic and nuclear medicine studies in the United States and worldwide: frequency, radiation dose, and comparison with other radiation sources--1950-2007. Radiology, 2009. 253(2): p. 520-31.

9. National Council on Radiation Protection and Measurements., National Council on Radiation Protection and Measurements. Scientific Committee 6-2 on Radiation Exposure of the U.S. Population., and National Council on Radiation Protection and Measurements., Ionizing radiation exposure of the population of the United States : recommendations of the National Council on Radiation Protection and Measurements. NCRP report. 2009, Bethesda, Md.: National Council on Radiation Protection and Measurements.

10. Brenner, D.J. and E.J. Hall, Computed tomography--an increasing source of radiation exposure. N Engl J Med, 2007. 357(22): p. 2277-84.

11. (2011) Sentinel Event Alert, Issue 47: Radiation risks of diagnostic imaging. 12. Goske, M.J., et al., The 'Image Gently' campaign: increasing CT radiation dose awareness through a

national education and awareness program. Pediatr Radiol, 2008. 38(3): p. 265-9. 13. Arch, M.E. and D.P. Frush, Pediatric body MDCT: a 5-year follow-up survey of scanning parameters used by

pediatric radiologists. AJR Am J Roentgenol, 2008. 191(2): p. 611-7. 14. Cook, T.S., et al., Automated extraction of radiation dose information for CT examinations. J Am Coll

Radiol, 2010. 7(11): p. 871-7.



IV.D.1. Validity

Validity of the measure is the extent to which the measure meaningfully represents the concept being evaluated and its relationship to measuring quality. The method for establishing the reliability or validity of a measure will depend on the type of measure, data source, and other factors. Please explain your rationale for selecting the methods you have chosen, show how you used the methods chosen, and provide information on the results (e.g., R2 for concurrent validity).

The rationale for selecting the current measure is twofold. First is to encourage facilities that image children to routinely capture data regarding patient exposure and store it in the Electronic Medical Record. Second is to ensure that local processes will satisfy the recommendations and requirements of oversight agencies such as The Joint Commission, California Department of Public Health and FDA.

As shown in Figure 5, St. Louis Children’s Hospital is using one of the proposed methods to monitor its capacity. Further analysis of process capability is shown in Figure 6. Although we propose three specific methods of calculating the quality metric, we have not yet measured each to calculate the concurrent validity. Additional testing at our site as well as feasibility and validity testing at other sites is planned.

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Figure 6: Process Capability Sixpack of Proposed Quality Metric

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IV.D.2. Reliability

Reliability of the measure is the extent to which the measure results are reproducible when conditions remain the same. The method for establishing the reliability or validity of a measure will depend on the type of measure, data



source, and other factors. Please explain your rationale for selecting the methods you have chosen, show how you used the methods chosen, and provide information on the results (e.g., the Kappa statistic).

Figure 6 above indicates that stable processes are readily achievable. We expect that transitioning to a completely electronic system where DICOM-SR files for each CT study are sent directly to a radiation exposure database and that database is used to populate the corresponding field in the patient’s electronic medical record should be even more reliable. Conversely, we expect methods that require radiologists to manually enter exposure metrics into their radiology reports will be far less reliable.

IV.E. Identification of Disparities

CHIPRA requires that quality measures be able to identify disparities by race, ethnicity, socioeconomic status, and special health care need. Thus, we strongly encourage nominators to have tested measures in diverse populations. Such testing provides evidence for assessing measures’ performance for disparities identification.

IV.E.1. Race/Ethnicity

Recognizing that children with differing races and ethnicities make up a diverse population of individuals with needs of varying complexity, please describe the results of any efforts to demonstrate the capacity of this measure to produce results that stratify by race and ethnicity.

No systematic studies have yet addressed whether results vary according to race and/or ethnicity.

IV.E.2. Special health care needs

Recognizing that children with special health needs comprise a diverse population of individuals with needs of varying complexity, please describe the results of any efforts to demonstrate the capacity of this measure to produce results that stratify by special health care needs.

Chronically ill children are expected to be imaged more than their healthy counterparts.

IV.E.3. Socioeconomic status

Recognizing that children of different socioeconomic statuses make up a diverse population of individuals with needs of varying complexity, please describe the results of any efforts to demonstrate the capacity of this measure to produce results that stratify by socioeconomic status.

No systematic studies have yet addressed whether results vary according to socioeconomic status.

IV.E.4. Rurality/Urbanicity

Recognizing that children living in areas with differing levels of rurality/urbanicity make up a diverse population of individuals with needs of varying complexity, please describe the results of any efforts to demonstrate the capacity of this measure to produce results that stratify by levels of rurality/urbanicity.

No systematic studies have addressed this question but we expect that limited access to pediatric specialty centers in rural areas will lead to lower values.



IV.F. Feasibility

Feasibility is the extent to which the data required for the measure are readily available, retrievable without undue burden, and can be implemented for measurement.3 Please explain the methods used to determine the feasibility of implementing the measure.

IV.F.1. Opportunities/Issues in Implementation

Please describe the measure’s feasibility:

a. What is the potential availability of data in existing data systems? How readily are the data available?

Source data in the form of manufacturer specific CT Dose Reports which are archived in the PACS is already widely available. Open source software capable of mining that data is already available14 and being used by a number of facilities.

b. If data are not available in existing data systems or would be better collected from future data systems, what is the potential for modifying current data systems or creating new data systems to enhance the feasibility of the measure and facilitate implementation?

Comprehensive, vendor-supported exposure monitoring systems are rapidly coming into general practice. This reflects the impact of the FDA initiative, The Joint Commission recommendations and California legislation.

c. Describe the extent to which the measure has been used or is in use (or has not been used), including the

diversity of settings in which it has been used. If the measure has been used or is in use, what data collection methods, if any, have already been used to collect data for this measure? What lessons learned are available from its prior or current use?

Numerous academic centers and several nonacademic centers already routinely capture the source data and are already focusing on optimizing CT utilization and exposure/CT exam. The American College of Radiology has experience with a multicenter CT Dose Index Registry and found local variation in CT naming conventions and this confounded efforts to compare exposure metrics across different sites. The proposed measure circumvents that difficulty by using the standardized CPT coding architecture found in administrative records.

IV.F.2. Eligible Population and Performance Rates

Please describe the following for this measure:

a. Describe the eligible populations and results of testing in the eligible populations. Children less than 21 years old on the date of the CT Exam

b. Provide an estimate of the required sample size to gain adequate numbers of observations for sufficiently precise comparisons of stratifications of race, ethnicity, special health care need, and socioeconomic status.

3 Adapted from: CMS-Centers for Medicare & Medicaid Services Quality Measurement and Health Assessment Group glossary

http://www.cms.gov/MMS/19_MeasuresManagementSystemBlueprint.asp#TopOfPage. Accessed February6, 2012.

http://www.cms.gov/MMS/19_MeasuresManagementSystemBlueprint.asp#TopOfPage



The proposed measure seeks to bypass sampling strategies and instead monitor the entire population of children exposed to ionizing radiation during diagnostic CT exams.

IV.H. Levels of Aggregation:

CHIPRA states that data used in quality measures must be collected and reported in a standard format that permits comparison (at minimum) at State, health plan, and provider levels.

Please describe the following for this measure:

Level of aggregation Is measure intended to apply at this level? [Drop-down box, Yes/No] and field to specify where needed

Has this measure been calculated at this level? [Drop-down box, Yes/No] and field to SPECIFY which level if needed.

More than one State (if yes, specify which)

Yes No

State: Measure assesses quality for all covered by Medicaid, CHIP, or both in one State (specify which State, and which program(s))

Yes No

State: Measure assesses quality for all children in the State (specify which), regardless of payer

Yes No

Payment model: For which payment model (e.g., managed care, primary care case management, fee-for-service, other, or all) does the measure assess quality (specify)?

Yes No

Health plan: Measure assesses quality at the health plan level

Yes No

Hospital or other residential facility (e.g., residential treatment center, nursing home, rehab center)—specify which

Yes - hospital Yes

Individual health care provider (specify which)

Yes – imaging center No

Practice site Yes No

Other groupings of providers No NA

Other (specify which) NA NA



IV.I. Understandability

CHIPRA states that the core set should allow purchasers, families, and health care providers to understand the quality of care for children. Please describe the usefulness of this measure to purchasers, families, and health care providers. If any efforts have been made to assess the understandability of this measure, please describe.

St Louis Children’s Hospital regularly communicates directly with families, healthcare providers and purchasers about the need to optimize childhood radiation exposure. Continuous quality/safety improvement programs depend on reliable data collection systems. This quality measure is readily understood by families, healthcare providers and purchasers. Efforts are focusing on improving the understandability of exposure metrics and how they relate to the risk/benefit calculations that underlie healthcare decision making.

IV.J. Health Information Technology (Health IT)

Please respond to the following questions in terms of any health information technology (health IT) that has been or could be incorporated into the measure calculation.

VI. J.1. Health IT Enhancement

Please describe how health IT may enhance the use of this measure.

Radiology departments have an advanced informatics infrastructure and standardized file formats. Enhancements such as DICOM-SR are being implemented and will enhance the use of this measure.

VI. J.2. Health IT Testing

Has the measure been tested as part of an electronic health record (EHR) or other health IT system?

Yes

If so, in what health IT system was it tested and what were the results of testing?

Siemens Syngo V31. Results are shown in Figures 5 and 6.

VI.J.3 Health IT Workflow

Please describe how the information needed to calculate the measure may be captured as part of routine clinical or administrative workflow and how it may be captured.

The Radiology Information System and its role in creating administrative claims provide the means of calculating the measure’s denominator. RIS or PACS or DICOM-SR data will be used to calculate the measure’s numerator.

VI.J.4. Health IT Standards

Are the data elements in this measure supported explicitly by the Office of the National Coordinator for Health IT Standards and Certification criteria (see http://healthit.hhs.gov/portal/server.pt/community/healthit_hhs_gov__standards_ifr/1195)?

No

If so, please describe.

NA

VI.J.5. Health IT Calculation

http://healthit.hhs.gov/portal/server.pt/community/healthit_hhs_gov__standards_ifr/1195



Please assess the likelihood that missing or ambiguous information will lead to calculation errors.

Any method which requires technologists or physicians to transcribe data from the CT scanner or dose report into either the radiology report or radiation database will likely have an error rate of at least 1% (Figure 5). As more and more facilities adopt a completely electronic workflow for capturing and reporting exposure metrics, the error rate for the numerator should drop at least tenfold. The error rate for the denominator will depend on the accuracy of administrative claims reporting and is likely on the order of 1% due to difficulties of transcoding clinical work into CPT terminology. The overall error rate for this measure is not be expected to exceed 5% despite collecting data on over 5 million pediatric CT exams a year.

VI.J.6. Health IT Other Functions

If the measure is implemented in an EHR or other health IT system, how might implementation of other health IT functions (e.g., computerized decision support systems in an EHR) improve performance characteristics of the measure?

Routinely capturing data on childhood exposure to ionizing radiation will be a step towards calculating exposure estimates for various CT exams at the facility, individual child and population levels. Such estimates will be needed to improve the decision support tools that will eventually be added computerized physician order entry systems. Such systems will become a venue for assuring the appropriateness of exposing children to ionizing radiation.

In the future, one can also imagine a system where measures of radiation exposure are incorporated

into the billing record/administrative claim. In this future system, not only would the billing record include information on procedure type, date, indication, patient information, and facility information but also it would include quality/safety metrics. This system would also facilitate efforts to collect x-ray exposure data at a national level.

Section V: Additional Information Complete information about the person submitting the material, including:

a) Gary LaBlance, PhD with assistance from James Duncan, MD PhD b) Vice President of Quality, Service and Information Management c) St. Louis Children’s Hospital d) One Children’s Place, St. Louis MO 63110 e) 314 454-6000 f) [email protected] and [email protected] g) A written statement guaranteeing that all aspects of the measure will be publicly available, as defined

in the Submission Guidelines section.

mailto:[email protected]

mailto:[email protected]

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