Patient Centered Outcomes Research Institute (PCORI) ESCAPED Study: Comparison of Patient Centered Outcomes for People With SCD in the Acute Care Setting
Conditions: Sickle Cell Disease
Sponsor: Johns Hopkins University

 
 
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Title:  Comparison of Patient Centered Outcomes in the Management of Pain 
between Emergency Department and Dedicated Acute Care Facilities for Adults 
with Sickle Cell Disease 
 
 
 
 
NCT number:  02411396 
 
Date of documents: 2/17/2015 
 
 
 
 
 
 
 
 
 
 
 

 
 
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Date: ___2-17-15_________________    
Principal Investigator: __Sophie Lanzkron___________ 
Application Number: _IRB00054029  __________ 
 
 
JHM IRB - eForm A – Protocol 
 
 
 
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in each. If a section is not applicable, leave heading in and insert N/A. 
 When submitting JHM IRB eForm A (new or revised), enter the date submitted to the field at 
the top of JHM IRB eForm A. 
 
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1. 
Abstract 
a. Provide no more than a one page research abstract briefly stating the problem, the research 
hypothesis, and the importance of the research. 
Sickle cell disease (SCD) is a genetic disorder of the blood that leads to severe morbidity and 
early mortality. It is the most common disease detected by newborn screening efforts in the United 
States (U.S.).1Between 80,000 and 100,000 individuals in the U.S. are affected by some form of 
SCD. The best-known burden of SCD is the vaso-occlusive crisis (VOC). These acute, 
excruciatingly painful events are the leading cause of hospital and emergency department 
utilization,5 and can be associated with such lethal and disabling complications as acute chest 
syndrome and stroke. 
The Emergency Department (ED) has been the standard location where patients with SCD go to 
seek care for the treatment of acute painful events.  ED care for SCD is marked by long delays, 
lack of efficacy, and conflict. Nationally, forty percent of ED visits for SCD pain are concluded by 
hospital admissions.7 SCD patients report not having enough involvement in decisions about their 
own care and also that providers do not demonstrate respect, trust, and compassion.23 Numerous 
studies have demonstrated that providers hold highly negative attitudes toward SCD patients and 
are strongly predisposed to suspect addiction in patients presenting for VOC care.23  
 
A strong body of literature supports the assertion that a subspecialty infusion center (IC), staffed 
by expert clinicians and delivering individualized care, can improve care quality while reducing 
costs. Benjamin et al. found that establishment of a dedicated SCD day hospital led to a 40% 
reduction in inpatient admissions relative to ED management.24 Since this seminal finding, a 
number of supporting papers have confirmed that rapid assessment of VOC, close monitoring, 
social service support, and individualized care improves outcomes.25-28 Yet there has never been 
a direct comparison between IC clinics and the ED setting 
The purpose of this study is to compare outcomes between IC and ED settings in four locations 
around the US.  
 
2. 
Objectives (include all primary and secondary objectives) 
Primary outcome-  time from arrival to first dose of parenteral pain medication. 
 
Secondary outcomes: 
a. Outcome of acute visit – admission v discharge home 
b. Was patient reassessed 30 minutes after their first dose of pain medication 
c. Assess patient reported satisfaction and patient reported perceptions of risk (e.g. from 
medical errors) 
 
 

 
 
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3. 
Background (briefly describe pre-clinical and clinical data, current experience with procedures, 
drug or device, and any other relevant information to justify the research) 
Sickle cell disease (SCD) is a genetic disorder of the blood that leads to severe morbidity and early 
mortality. It is the most common disease detected by newborn screening efforts in the United States 
(U.S.).1Between 80,000 and 100,000 individuals in the U.S. are affected by some form of SCD.2 African-
Americans (AA) are most affected in the U.S., as 1 per every 400 AA newborns is born with the disease. 
The damage SCD inflicts on sufferers is dramatic. The disease reduces life expectancy by approximately 
30 years compared to the general population.3 Furthermore, the disease limits quality of life - as 
severely as does end-stage renal disease requiring hemodialysis.4 
The best-known burden of SCD is the vaso-occlusive crisis (VOC). These acute, excruciatingly painful 
events are the leading cause of hospital and emergency department utilization,5 and can be associated 
with such lethal and disabling complications as acute chest syndrome and stroke. Acute and chronic pain, 
psychiatric co-morbidity and disease severity are factors that likely contribute to extraordinarily high levels 
of unemployment and decreased productivity in this patient population, with estimates that 40% of adults 
with SCD are unemployed.6 
The Emergency Department (ED) has been the standard location where patients with SCD go to seek 
care for the treatment of acute painful events.  The purpose of this proposal is to demonstrate that, from 
the patient perspective, the ED is not the ideal site for the management of acute, uncomplicated VOC 
events. While SCD is considered a rare disease in the US, the burden of ED care and subsequent 
hospitalization is high, and it is borne by adults. The number of ED visits by patients with SCD has 
increased yearly, with a 28% increase since 2006 (the first year data is available from AHRQ). Sixty eight 
percent of these visits are coded as acute painful crises. In 2011, there were 317,557 ED visits for people 
with SCD, and 82% of these visits were by people aged 18 and over. Of ED visits that resulted in hospital 
admissions, for every 100 people estimated to be living with the disease in the US (2006), 68.4 were for 
SCD, compared with 1.1 hospital admissions for asthma and 17.3 hospital admissions for CHF7.  In 
addition, 30 day readmission rates for this patient population are the highest of any recorded diagnosis, at 
31.9%.8 These estimates suggest that SCD confers a significant burden on the patient, with a parallel 
excessive impact on the health care system.   
Numerous studies show that patients and healthcare providers are dissatisfied with the quality of 
SCD pain management, which is currently centered in the ED.23 ED care for SCD is marked by long 
delays, lack of efficacy, and conflict. Nationally, forty percent of ED visits for SCD pain are concluded by 
hospital admissions.7 SCD patients report not having enough involvement in decisions about their own 
care and also that providers do not demonstrate respect, trust, and compassion.23 Numerous studies 
have demonstrated that providers hold highly negative attitudes toward SCD patients and are strongly 
predisposed to suspect addiction in patients presenting for VOC care.23  
A strong body of literature supports the assertion that a subspecialty infusion center (IC), staffed by 
expert clinicians and delivering individualized care, can improve care quality while reducing costs. 
Benjamin et al. found that establishment of a dedicated SCD day hospital led to a 40% reduction in 
inpatient admissions relative to ED management.24 Since this seminal finding, a number of supporting 
papers have confirmed that rapid assessment of VOC, close monitoring, social service support, and 
individualized care improves outcomes.25-28 Yet there has never been a direct comparison between IC 
clinics and the ED setting.  The dearth of data has contributed to the lack of widespread adoption of this 
model of care. At this time there are less than 10 dedicated IC’s for adults with SCD, so few patients have 
access to such clinics and thus acute care in the US for painful episodes continues to occur primarily in 
the ED. The goal of this proposal is to demonstrate that care provided in an Infusion Center is more 
patient centered and efficient than care provided in an Emergency Department for adults with SCD and 
uncomplicated VOC. 
While VOC is the most common complication of SCD there are currently no evidenced based guidelines 
for the management of these events.29 (RQ-1) Using an expert panel, Wang et al 30 developed a set of 
quality measures for the treatment of children with SCD. This group identified 41 measures that could be 
used to assess health systems quality of care for children with SCD.  Two of these measures were for the 
management of acute pain.  The first measure was that children who present with an acute pain episode 
should receive a parenteral analgesic within 60 min of registration or 30 min of triage. The second 
measure was that there should be a reassessment of pain level repeated within 30 min of the first dose of 
analgesic. There are no similar studies in adults, but the National Heart Lung and Blood Institute (NHLBI) 

 
 
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is finalizing guidelines, based on a systematic review of the literature, that have similar recommendations 
for acute pain management for all people with SCD. (RQ-1) Neither of these quality outcomes is routinely 
achieved in the ED setting.  While there is a lack of available national data on quality measures, data on 
the average wait time to see a physician for a patient with SCD in the ED shows that it is over an hour.31 
This wait is 25% longer than for patients in the general ED population. As the physician must see the 
patient prior to writing an order for pain medication, it is clear that the average time to first dose of 
analgesia in this nationwide sample is well over an hour. Data from the Johns Hopkins ED for 2013 shows 
that the average time from triage to first dose of analgesia is 2 hours and 26 minutes and that the average 
time to reassessment after the first dose is 1 hour and 18 minutes. Similarly, in the ED at the University 
Hospital Case Medical Center in Cleveland the average time from triage to first dose of parenteral pain 
medication is 2 hours and 7 minutes.  In the Cleveland ED only 47% of the visits had any documentation 
of pain reassessment after medication was given and in those where there was documentation it occurred 
on average 1 hour and 12 minutes after the first dose of pain medication.    
 
There continues to be a wide variation in how acute painful events are diagnosed and managed in the 
acute setting because management of VOC has never been studied in a systematic fashion (RQ-1).  
There are no objective clinical or laboratory measures of the presence or severity of a crisis, and so the 
only way to confirm that a patient is having a crisis is to ask the patient (i.e., patient self-report). The 
current pain scales used for self-report have not been validated in this patient population.29  It is therefore 
not surprising that due to this uncertainty many patients receive suboptimal care in the acute setting, 
especially when managed by clinicians, as in the ED, who are unfamiliar with them and who are not 
trained to specifically manage their disease and its complications. 
The purpose of this study is to compare patient centered outcomes for those patients being 
treated for an uncomplicated VOC in ICs and EDs. We have designed this study based on preliminary, 
single site retrospective data on ICs from our participating sites which have shown similar outcomes to 
that of Benjamin24. The Johns Hopkins Sickle Cell Infusion Center (SCIC) which opened in 2008 provides 
acute care solely for adults with SCD. In 2008, 50% of all ED visits for VOC resulted in hospital admission 
at Johns Hopkins Hospital (JHH). The SCIC initially was opened 5 days a week and in 2011 increased 
hours to include the weekends. The SCIC has 5 treatment slots for acute care visits, and is staffed by a 
clinic coordinator, nurse, clinical nurse associate, social worker and physician extender. Supervision is 
provided by Dr. Lanzkron, who is the medical director and the proposed PI for this study.  From the period 
February 2008 through December 2011 there were 3874 visits to the SCIC by 361 unique patients. On 
average, there were 3.8 visits to the infusion clinic daily (range 0-10). The average number of visits by 
each individual was 10 (range 1-84) or 2.5/yr.  Eighty five percent of visits ended with the patient being 
discharged home. The remainder were either directly admitted to the hospital or sent to the ED for further 
treatment. The average time to receipt of first dose of opioid from arrival to the clinic was 57.7 minutes 
(95% CI 56.5, 58.8). The average time that patients spent in the SCIC was 4 hours and 55 minutes. The 
average pain level on arrival using the numerical rating scale (NRS), which measures pain on a scale of 0-
10,  was 8.4 (95% CI 8.3, 8.4).  The average decrease in pain score from arrival to discharge was 2.62 
points on the NRS (95% CI 2.55, 2.69). Those who went home had a significantly greater decrease in pain 
than those that remained for hospital care (Δ-2.9 vs. Δ-1.2, p<0.001).  There was borderline statistical but 
no clinically significant difference in time to first dose of opioid for patients who were discharged home 
compared to those that required additional hospital care (57.2 min v 60.3 min, p=0.06). In examining the 
association of changes in pain scores with discharge disposition, we found that, after adjusting for gender, 
patients were 2 times (OR 2.01, 95% CI 1.85, 2.19) more likely to be discharged home for every 1 point 
decrease in their pain. In comparing these outcomes to the JHH ED between 4/2010-7/2012, there were 
1554 total ED visits for SCD pain made by 254 unique patients.  In the ED, the average time from triage to 
first dose of pain medication during this time period was 190 minutes (SD 129.8).  In a model controlling 
for acuity in the ED, for every 10 minute increase in time to first dose of pain medication, the relative risk of 
admission increased by 0.7% (95% CI 1.00 1.01, p=0.024).  Since the opening of the SCIC there has been 
a 22% reduction in admissions and reduction in 30 day readmissions from 39% to 22%. 
A similar clinic to the SCIC opened at Froedtert Hospital in Milwaukee (FASCC) in 2011.  The FASCC 
clinic is open weekdays and serves the needs of 300 adults with SCD. The average length of stay in the 
clinic is 3 hours and 96.5% of visits end with the patient being discharged home. Since this clinic opened 
there has been a 38% decrease in admissions and a decrease in 30 day readmissions from 61 to 28%.  
 

 
 
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Without a direct comparison of ED to IC, many argue that there is something different about the patients 
that receive care in an ED versus those that seek care in an IC. Further, the recent expansion in ICs has 
been driven primarily by economic consideration (length of stay, readmissions), rather than by patient-
centered outcomes, on which there is a lack of data. Demonstrating attainment of important clinical 
outcomes in ICs may increase their stability and viability. With this proposal we will demonstrate that 
the improved outcomes seen in an IC v. the ED are not due to differences in the type of patients 
seen for care but rather in the processes of care for VOC in these two sites.  
 
4. 
Study Procedures 
a. Study design, including the sequence and timing of study procedures   
(distinguish research procedures from those that are part of routine care). 
We will prospectively enroll patients that are seen in participating centers into a study cohort.  We will 
then capture data from their acute visits. We will enroll participants from 4 sites: Baltimore, Cleveland, 
Milwaukee and Baton Rouge. When any participant is treated in either an ED or IC, data on clinical 
outcomes and patient experiences of care will be collected.  
Baseline data collection will include:  SCD genotypes and co-morbidities35  
a. AVN 
b. Gall bladder disease  
c. Sickle chronic lung disease  
d. Leg ulcer 
e. Priapism (male) 
f. Renal failure 
g. Retinopathy 
h. Stroke  
2. Self-reported number of acute care visits and hospitalizations in the prior 12 months 
3. Daily chronic pain using the Numeric Rating scale (NRS). 
4. Prior and current treatments, including: 
a. hydroxyurea use 
b. chronic transfusions 
c. pain medications, (specific regimens used to treat chronic daily or intermittent pain) 
After participants have consented they will be asked to contact by phone or email the research 
assistants about all acute care visits.  In addition, the research assistant will review the daily census for 
IC’s and ED’s at the local site to identify participants with an acute care visit.  Furthermore, each 
participant will be contacted by phone monthly and asked about acute care visits. 
 
Once an acute care visit for an uncomplicated VOC has occurred, the following data will be collected: 
Time crisis started, Arrival time, Triage time, Pain level on arrival, Time to first dose of opioid, Time from 
first dose to nurse reassessment of pain, Time in the ED/IC, Pain level at discharge from ED/IC, Change 
in pain scale from arrival to discharge, Disposition at time of discharge from ED/IC (home, admit, etc.). In 
order to assess patient experiences of care in the acute setting, participants will be surveyed either 
toward the end of their acute visit or by phone within 72 hours of their visit.   As reinforcement, at each 
monthly call, we will verify contact information and encourage participants to call us within 3 days of any 
acute visit. The survey tools that will be used include the Painful Crises Experiences of Care for SCD 
tool (PEPS); a survey of safety and a survey of patient satisfaction with ED pain management. 
 
b. Study duration and number of study visits required of research participants.  Participants will be 
part of the study for 18 months.  During which time there will be no in person study visits.  
There will be monthly phone calls and contact at the time of acute care visits.  
c. Blinding, including justification for blinding or not blinding the trial, if applicable. NA 
d. Justification of why participants will not receive routine care or will have current therapy 
stopped. NA 
e. Justification for inclusion of a placebo or non-treatment group. NA 
f. Definition of treatment failure or participant removal criteria. NA 
g. Description of what happens to participants receiving therapy when study ends or if a 
participant’s participation in the study ends prematurely. NA 

 
 
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All data collection will be done using RedCap.  RedCap is a secure web based database tool that has 
multisite functionality. Each external site will enter their data into a single database. Each external 
site will only have access to their own data through the site.  As the central coordinating site, 
Hopkins will have access to all of the data. When data collection is complete and records are 
finalized the data will undergo data lock.  As all data will be entered into a common database 
merging of data will be done after data is exported from RedCap into Stata for further analysis.  
Merging of data will need to be done for combining the demographic data with data collected from 
each acute visit.     
5. 
Inclusion/Exclusion Criteria 
All individuals with confirmed SCD who live within 60 miles of the study center or who already receive 
regular care at the participating centers will be eligible for enrollment. The only exclusions will be patients 
who are pregnant, who have been stable on chronic transfusion therapy and have not had a painful 
episode within two years of enrollment (transfusions may prevent all acute painful events) and patients 
who are unwilling or unable to sign consent.  
 
 
6. 
Drugs/ Substances/ Devices 
a. The rationale for choosing the drug and dose or for choosing the device to be used. NA 
b. Justification and safety information if FDA approved drugs will be administered for non-FDA 
approved indications or if doses or routes of administration or participant populations are 
changed. NA 
c. Justification and safety information if non-FDA approved drugs without an IND will be 
administered. NA 

 
 
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Date: ____________________    
Principal Investigator: _________________ 
Application Number: __________ 
 
7. 
Study Statistics 
Primary and secondary outcome variables: This is an observational study from which we will draw 
inferences about outcomes of care attributable to the treatment setting. As we are not randomizing 
patients to ED care or to IC care, we must control for confounders in the relationship between site of care 
and outcomes.  We note, however, that there may be regional differences that impact on outcomes: 
percentage of high utilizers in the region, duration IC has been functioning, and ED crowding. In our study, 
we have clustering of individual patients by regions (n=4).  We will account for both known and unknown 
confounders at the level of the regions.   
 
Given the anticipated differences in patients who seek care in these settings, we propose using propensity 
score techniques to balance patient characteristics in the two treatment groups both within and across 
sites. We will use relatively new methods developed for use of propensity scores in the context of 
multilevel data.42  We look towards using propensity scores for achieving balance in the distributions of 
covariates to allow for a causal comparison. Our treatment assignment is at the individual level and we 
propose using appropriate propensity weighting methods to generate valid causal inferences, under the 
assumption of absence of unmeasured confounders. 
 
For causal comparisons, we adopt the potential outcome framework for causal inference.43 Under the 
standard stable unit treatment value assumption (SUTVA)44, which states that the outcomes for each 
patient are unaffected by the treatment assignments of the other patients, each patient has two potential 
outcomes corresponding to the two treatments (ED or IC care), only one of which is observed for each 
patient.  We believe the SUTVA assumption to be true in our setting. We aim to estimate the population 
average treatment effect, although we may also look at the population average treatment effect on the 
treated (ATT), which we expect will be very similar. 
Notation Let k = 1, 2, …, K denote number of regions and i=1, 2, …, n_k denote the number of 
participants in region k.  Total sample size is n = 
.  Each subject belongs to one of two groups, ED 
(control) or IC (treatment) care.  Let Zki be the binary variable indicating whether the subject is in the 
treatment (Z=1) or control (Z=0) group. Also, let Uki be a vector of subject-level covariates and Vk be a 
vector of region-level covariates, and Xki = (Uki, Vk).  For each subject, an outcome Yki is observed, which, 
in our study, can be continuous or binary.  The propensity score is defined as e(Xki) = Pr(Zki=1 | Xki).   
Fitting a Propensity Model Given the multi-region (clustered) data, we cannot use standard techniques 
for propensity score modeling but instead will use a random effects model that accounts for clustering. We 
have chosen this model because we are uncertain about all of the cluster-level covariates that might 
impact on treatment effect. The few that we hypothesize to be regional-level confounders, as described 
above, we will include in the model. The individual level covariates will include: SCD complications, self-
reported number of acute care visits and hospitalizations in the prior 12 months, pain rating upon first 
arrival for care, distance from residence to site of care, and demographic variables.  The random effects 
model to generate the propensity score is as follows: 
 
 
logit (eki) = k + Xki 

 
This model includes individual level covariates, as well as cluster-specific intercepts due to measured and 
unmeasured cluster-level covariates, and a prior distribution for cluster-level main effects, k ~ N(0, 2). We 
expect that since we will have many patients within each region (cluster), we should not have any difficulty 
in fitting the random-effects model.  The goodness of fit of this model will be checked by conventional 
diagnostics of covariate balance between the ED and IC treated patients, checking the overall and within-
region balance of the weighted distribution of covariates in the two groups. 
Estimating an Overall Treatment Effect We will then use the inverse of the propensity score, eki, 
generated from the random effects model described above, to weight the outcomes for each individual. 
This will allow us to draw valid inferences about the differences between groups. We propose using a non-
parametric clustered-estimator as our inverse-probability-weighted estimator.  
  
 
 
(2) 

 
 
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Where wk = 
, wki = Zki/eki + (1-Zki)/(1-eki), and 
 is the inverse-propensity weighted treatment effect for 
the k-th region. This estimator accounts for clustering of the patients by region. The standard error of the 
estimate will be generated by bootstrapping.  
To test the first hypothesis (time to pain medication), we will use the observed time to first dose (a 
continuous outcome) in the two groups.  We do not need to use time-to-event models since there will be 
no censoring. We will evaluate whether the time needs to be log-transformed in order to be approximately 
normally distributed. To test the second hypothesis, we will describe the proportion of patients in each 
group that is reassessed in the first 30 minutes after dosing.  We will describe the proportion of patients 
admitted in each of the treatment groups, using the estimator described above.  For evaluations of the 
difference in patient experience of care in these two settings this likely reflects the adequacy of symptom 
relief during the visit and the patient-centeredness of the visit including being treated respectfully and 
feeling unthreatened in the environment. The outcome of interest is an ordinal measure on a scale of 18 
points that we will analyze as a continuous outcome, using the estimator above. The other surveys will be 
analyzed similarly. 
Sensitivity analysis In our sensitivity analyses, we will stratify patients into quintiles based on their 
propensity scores and test for differences in the outcomes of interest between ED and IC treated patients 
in each quintile.  These quintile-specific estimates will be reported, as well as pooled estimates from 
application of random effects methods.   
We will also estimate propensity scores using a fixed effect model rather than a random effects model (Eq 
2).  We might also explore the use of a doubly robust estimator, where we would model the potential 
outcomes using a random effects model. The results are expected to be similar.  
We will also test whether our inferences are sensitive to hidden biases from unmeasured confounders. We 
will estimate how strong an unmeasured confounder needs to be related to both exposure and outcome to 
affect the inference about difference in effect in the treatment sites. Potential unmeasured confounders 
might be patient-preference for site of care, or local culture or climate regarding care of patients with SCD. 
a. 
Statistical plan including sample size justification and interim data analysis. 
We have based the needed sample size on the outcome requiring the most participants, the admission 
rate from the ED v. IC. We hypothesize that we will observe an ED admission rate of 50%9, and an IC 
admission rate of 27% (an absolute reduction of at least 23%). We took the following design 
considerations into account in estimating the sample sizes needed to detect this difference: We have a 2-
arm study (IC vs. ED) with 4 clusters (sites) per arm.  With a type I error of 0.05, a type II error of 0.20 
(power 0.80), and an estimated intracluster correlation coefficient (ICC) of 0.02, we will require an average 
of 41 participants in each cluster (site) per arm.  410 participants total (205 per arm) are required to detect 
our hypothesized difference in admission rate. We estimate we will observe a lost-to-follow-up rate of 18% 
so our total required sample size is [410/(1-0.18)] = 500 participants. 
 
b. Early stopping rules. NA 
 
8. 
Risks 
a. Medical risks, listing all procedures, their major and minor risks and expected frequency. 
The risks from this study are minimal. The participants may become tired or bored while filling out 
the surveys. There is also the risk of loss of privacy. Participants can choose to not participate in 
this study as it is not a treatment protocol there are no alternatives.  
b. Steps taken to minimize the risks. All primary data to be collected will be de-identified using a 
unique identifier and will be kept in a secure office in a password protected computer.  The data 
put in REDCap will be de-identified.  As REDCap is a secure website and only deidentified data 
will be put in it the risk of loss of privacy is minimal.  Every attempt will be made to assure that 
all locally collected data is kept in a secure environment and that all identifiers will be removed 
from primary data.  The spreadsheet with the identifying info linked to the unique identifier will 
be destroyed when the REDCap database is finalized and locked.  
 
c. Plan for reporting unanticipated problems or study deviations. Any breach of patient 
confidentiality will be reported to the IRB.  

 
 
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d. Legal risks such as the risks that would be associated with breach of confidentiality.NA 
e. Financial risks to the participants. NA 
 
 
9. 
Benefits 
a. 
Description of the probable benefits for the participant and for society. 
There will be no direct benefit to the subjects for participating in this study. What is learned from 
this study may improve the way in which adults with VOC are treated in the future.  
Importance of the Knowledge to be Gained The knowledge gained from this first time 
comparison of the treatment of acute pain in SCD comparing ED’s and IC’s will result in a better 
understanding of where this treatment should occur.  The study will demonstrate how IC’s can 
provide more rapid and appropriate care for this patient population and this should lead to greater 
access to these services for patients throughout the US who suffer from SCD.  
 
10. 
Payment and Remuneration 
a. 
Detail compensation for participants including possible total compensation, proposed bonus, 
and any proposed reductions or penalties for not completing the protocol. 
We will compensate participants for time and inconvenience associated with study participation. 
Participants will receive $25 for completing the initial study survey, and $25 every 6 months 
thereafter (for a total of 18 months of follow-up), for maintaining ongoing participation and 
communication with the study. 
 
11. 
Costs 
a. 
Detail costs of study procedure(s) or drug (s) or substance(s) to participants and identify 
who will pay for them. 
NA