Skip to main content

Main menu

  • HOME
  • ARTICLES
    • Current Issue
    • Ahead of Print
    • Archives
    • Abstracts In Press
    • Special Issue Archive
    • Subject Collections
  • INFO FOR
    • Authors
    • Reviewers
    • Call For Papers
    • Subscribers
    • Advertisers
  • SUBMIT
    • Manuscript
    • Peer Review
  • ABOUT
    • The JABFM
    • The Editing Fellowship
    • Editorial Board
    • Indexing
    • Editors' Blog
  • CLASSIFIEDS
  • Other Publications
    • abfm

User menu

Search

  • Advanced search
American Board of Family Medicine
  • Other Publications
    • abfm
American Board of Family Medicine

American Board of Family Medicine

Advanced Search

  • HOME
  • ARTICLES
    • Current Issue
    • Ahead of Print
    • Archives
    • Abstracts In Press
    • Special Issue Archive
    • Subject Collections
  • INFO FOR
    • Authors
    • Reviewers
    • Call For Papers
    • Subscribers
    • Advertisers
  • SUBMIT
    • Manuscript
    • Peer Review
  • ABOUT
    • The JABFM
    • The Editing Fellowship
    • Editorial Board
    • Indexing
    • Editors' Blog
  • CLASSIFIEDS
  • JABFM on Bluesky
  • JABFM On Facebook
  • JABFM On Twitter
  • JABFM On YouTube
Research ArticleOriginal Research

Sickle-Cell Disease Co-Management, Health Care Utilization, and Hydroxyurea Use

Nancy Crego, Christian Douglas, Emily Bonnabeau, Marian Earls, Kern Eason, Elizabeth Merwin, Gary Rains, Paula Tanabe and Nirmish Shah
The Journal of the American Board of Family Medicine January 2020, 33 (1) 91-105; DOI: https://doi.org/10.3122/jabfm.2020.01.190143
Nancy Crego
From Duke University School of Nursing, Durham, NC (NC, CD, EB, PT); Community Care of North Carolina, Raleigh, NC (ME, KE); University of Texas College of Nursing, Austin, TX (EM); Duke University School of Medicine, Durham, NC (GR); Duke University Medical Center, Durham, NC (NS)
PhD
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Christian Douglas
From Duke University School of Nursing, Durham, NC (NC, CD, EB, PT); Community Care of North Carolina, Raleigh, NC (ME, KE); University of Texas College of Nursing, Austin, TX (EM); Duke University School of Medicine, Durham, NC (GR); Duke University Medical Center, Durham, NC (NS)
DrPh
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Emily Bonnabeau
From Duke University School of Nursing, Durham, NC (NC, CD, EB, PT); Community Care of North Carolina, Raleigh, NC (ME, KE); University of Texas College of Nursing, Austin, TX (EM); Duke University School of Medicine, Durham, NC (GR); Duke University Medical Center, Durham, NC (NS)
BA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Marian Earls
From Duke University School of Nursing, Durham, NC (NC, CD, EB, PT); Community Care of North Carolina, Raleigh, NC (ME, KE); University of Texas College of Nursing, Austin, TX (EM); Duke University School of Medicine, Durham, NC (GR); Duke University Medical Center, Durham, NC (NS)
MD
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Kern Eason
From Duke University School of Nursing, Durham, NC (NC, CD, EB, PT); Community Care of North Carolina, Raleigh, NC (ME, KE); University of Texas College of Nursing, Austin, TX (EM); Duke University School of Medicine, Durham, NC (GR); Duke University Medical Center, Durham, NC (NS)
MBA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Elizabeth Merwin
From Duke University School of Nursing, Durham, NC (NC, CD, EB, PT); Community Care of North Carolina, Raleigh, NC (ME, KE); University of Texas College of Nursing, Austin, TX (EM); Duke University School of Medicine, Durham, NC (GR); Duke University Medical Center, Durham, NC (NS)
PhD
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Gary Rains
From Duke University School of Nursing, Durham, NC (NC, CD, EB, PT); Community Care of North Carolina, Raleigh, NC (ME, KE); University of Texas College of Nursing, Austin, TX (EM); Duke University School of Medicine, Durham, NC (GR); Duke University Medical Center, Durham, NC (NS)
BA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Paula Tanabe
From Duke University School of Nursing, Durham, NC (NC, CD, EB, PT); Community Care of North Carolina, Raleigh, NC (ME, KE); University of Texas College of Nursing, Austin, TX (EM); Duke University School of Medicine, Durham, NC (GR); Duke University Medical Center, Durham, NC (NS)
PhD, MSN, MPH
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Nirmish Shah
From Duke University School of Nursing, Durham, NC (NC, CD, EB, PT); Community Care of North Carolina, Raleigh, NC (ME, KE); University of Texas College of Nursing, Austin, TX (EM); Duke University School of Medicine, Durham, NC (GR); Duke University Medical Center, Durham, NC (NS)
MD
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • References
  • Info & Metrics
  • PDF
Loading

Article Figures & Data

Figures

  • Tables
  • Figure 1.
    • Download figure
    • Open in new tab
    Figure 1.

    Area under the curve–receiver operating characteristics (AUC-ROC) curve for comanagement. Performance of predictor measures and a combined model including age, gender, residency, and months enrolled in Community Care of North Carolina (CCNC) for comanagement with area under the curve values for each.

  • Figure 2.
    • Download figure
    • Open in new tab
    Figure 2.

    Performance of predictor measures and a combined model including Primary Care visit alone, Hematology visit alone, Co-management, age, gender, residency and months enrolled in Community Care of North Carolina (CCNC) for good versus fair or poor hydroxyurea adherence with area under the curve values for each.

Tables

  • Figures
    • View popup
    Table 1.

    Demographic Characteristics and Enrollment in CCNC Programs (Sample = 2045)

    CharacteristicsStatistic
    Sex, n (%)
        Female1162 (56.82)
        Male883 (43.18)
    Age, mean (SD)22.87 (16.41)
    N (%)
        1 to 9 years old499 (24.40)
        10 to 17 years old436 (21.32)
        18 to 30 years old537 (26.26)
        31 to 45 years old347 (16.97)
        46 to 64 years old194 (9.49)
        ≥65 years old32 (1.56)
    CCNC program months enrolled*, mean (SD)10.67 (3.43)
    Dual eligible Medicare and Medicaid, n (%)
        Yes417 (20.39)
        No1628 (79.61)
    Residence†, n (%)
        Metro1558 (76.19)
        Non-Metro adjacent to Metro440 (21.52)
        Non-Metro un-adjacent to Metro47 (2.30)
    CCNC network, n (%)
        Access East390 (19.07)
        Access Care180 (8.80)
        Carolina Collaborative Community Care125 (6.11)
        Carolina Community Health Partnership30 (1.47)
        Community Care Partners of Greater Mecklenburg320 (15.65)
        Community Care of Southern Piedmont66 (3.23)
        Community Care of Wake/Johnston Counties217 (10.61)
        Community Care of Western North Carolina20 (0.98)
        Community Care of the Lower Cape Fear112 (5.48)
        Community Care of the Sandhills102 (4.99)
        Community Health Partners37 (1.81)
        Northern Piedmont Community Care133 (6.5)
        Northwest Community Care Network134 (6.55)
        Partnership for Community Care179 (8.75)
    • CCNC, Community Care of North Carolina

    • ↵* CCNC program enrollment is defined as having active full Medicaid coverage and being linked to a medical home.

    • ↵† Residence categories were determined using the United States Department of Agriculture 2013 Rural-Urban Continuum Codes.

    • View popup
    Table 2.

    List of Non-Hematology Specialist by Type and Visit Frequency for Age 1 to 65+ (Sample N = 2045)

    Specialty TypeFrequency
    Primary care visits6251
    Hematology specialty visits2792
    Non-hematology specialty visits8827
        Acute care*2743
        Physician assistant (unidentified specialty or family practice)1477
        Nurse practitioner (unidentified specialty or family practice)1144
        Unidentifiable (null)†458
        Obstetrician/gynecologist383
        Other specialty visits‡377
        Orthopedic medicine295
        Ophthalmology/optometry282
        Surgery235
        Cardiology191
        Neurology178
        Pulmonary174
        Oncology161
        Nephrology122
        Otolaryngology116
        Anesthesiology103
        Gastroenterology96
        Physical and rehabilitation medicine91
        Foot & ankle surgery/podiatric medicine87
        Urology82
        Psychology32
    • ↵* Acute care visit—a visit that occurred in an out-patient acute setting.

    • ↵† Unidentifiable (Null) category includes office visits with a billing provider code for “multi-specialty” or “single specialty” with no rendering provider information.

    • ↵‡ Other specialty visits include outpatient visits not historically linked to SCD care or a frequency of visits within the specialty category ≤ 1% of the total number of specialty visits. Excludes SCD and general NP or PA visits. Includes addiction medicine, allergy and immunology, anatomic pathology, critical care medicine, dermatology, development behavior, diagnostic radiology, endocrinology, geriatric medicine, infectious disease, special hospital, neonatal-perinatal medicine, neuro-development, rheumatology, sleep medicine, sports medicine, vascular and interventional.

    • View popup
    Table 3.

    Emergency Department Encounters, In-Patient Stays, Out-Patient Visits, Emergency Department Reliance and Co-Management for North Carolina Medicaid Enrolled 12 Months and Age 1 to 65+ (Sample = 2045)

    AgeTotal ED EncountersWithin 7-day Re-EncountersWithin 14-day Re-EncountersWithin 30-day Re-Encounters
    Participants, n (%)Encounters, n (mean)Median (IQR)Participants, n (%)Encounters, n (mean)Median (IQR)Participants, n (%)Encounters, n (mean)Median (IQR)Participants, n (%)Encounters, n (mean)Median (IQR)
    1 to 9 (n = 499)348 (69.74)930 (1.86)1 (0, 3)75 (15.03)102 (0.20)0 (0, 0)96 (19.24)146 (0.29)0 (0, 0)114 (22.85)220 (0.44)0 (0, 0)
    10 to 17 (n = 436)268 (61.47)643 (1.47)1 (0, 2)47 (10.78)61 (0.14)0 (0, 0)60 (13.76)84 (0.19)0 (0, 0)74 (16.97)128 (0.29)0 (0, 0)
    18 to 30 (n = 537)423 (78.77)2801 (5.22)2 (1, 6)166 (30.91)934 (1.74)0 (0, 1)189 (35.20)1253 (2.33)0 (0, 1)229 (42.64)1663 (3.10)0 (0, 2)
    31 to 45 (n = 347)258 (74.35)1804 (5.20)2 (0, 4)84 (20.49)703 (2.03)0 (0, 0)105 (30.36)914 (2.63)0 (0, 1)125 (36.02)1176 (3.39)0 (0, 2)
    46 to 64 (n = 194)132 (68.04)607 (3.13)1 (0, 4)37 (19.07)148 (0.76)0 (0, 0)44 (22.68)209 (1.08)0 (0, 0)55 (28.35)297 (1.53)0 (0, 1)
    65+ (n = 32)22 (68.75)49 (1.53)1 (0, 2)1 (3.13)1 (0.03)0 (0, 0)2 (6.25)2 (0.06)0 (0, 0)6 (18.75)9 (0.28)0 (0, 0)
    All (n = 2045)1451 (70.95)6834 (3.34)1 (0, 4)410 (20.05)1949 (0.94)0 (0, 0)496 (24.25)2608 (1.28)0 (0, 0)603 (29.49)3493 (1.71)0 (0, 1)
    AgeTotal IP HospitalizationsWithin 7-Day RehospitalizationWithin 14-Day RehospitalizationWithin 30-Day Rehospitalization
    Participants, n (%)Stays, n (mean)Median (IQR)Participants, n (%)Stays, n (mean)Median (IQR)Participants, n (%)Stays, n (mean)Median (IQR)Participants, n (%)Stays, n (mean)Median (IQR)
    1 to 9 (n = 499)176 (35.27)312 (0.63)0 (0, 1)13 (2.61)13 (0.03)0 (0, 0)16 (3.21)20 (0.04)0 (0, 0)26 (5.21)43 (0.09)0 (0, 0)
    10 to 17 (n = 436)133 (30.50)324 (0.74)0 (0, 1)10 (2.29)10 (0.02)0 (0, 0)20 (4.59)25 (0.06)0 (0, 0)30 (6.88)56 (0.13)0 (0, 0)
    18 to 30 (n = 537)318 (59.22)1211 (2.26)1 (0, 2)45 (8.38)84 (0.16)0 (0, 0)73 (13.59)234 (0.44)0 (0, 0)100 (18.62)479 (0.89)0 (0, 0)
    31 to 45 (n = 347)184 (53.03)618 (1.78)1 (0, 2)22 (6.34)34 (0.10)0 (0, 0)32 (9.22)81 (0.23)0 (0, 0)46 (13.26)208 (0.60)0 (0, 0)
    46 to 64 (n = 194)88 (45.36)225 (1.16)0 (0, 1)4 (2.06)7 (0.04)0 (0, 0)9 (4.64)22 (0.11)0 (0, 0)17 (8.76)55 (0.28)0 (0, 0)
    65+ (n = 32)17 (53.13)19 (0.59)1 (0, 1)0 (0)0 (0)0 (0, 0)0 (0)0 (0)0 (0, 0)0 (0)0 (0)0 (0, 0)
    All (n = 2045)916 (44.79)2709 (1.32)0 (0, 1)94 (4.60)148 (0.07)0 (0, 0)150 (7.33)382 (0.19)0 (0, 0)219 (10.71)841 (0.41)0 (0, 0)
    AgeTotal Outpatient VisitsPCP VisitsHematology Specialty VisitsNon-Hematology Specialty Visits
    Participants, n (%)Visits, n (mean)Median (IQR)Participants, n (%)Visits, n (mean)Median (IQR)Participants, n (%)Visits, n (mean)Median (IQR)Participants, n (%)Visits, n (mean)Median (IQR)
    1 to 9 (n = 499)486 (97.39)4044 (8.10)6 (4, 11)437 (87.58)1853 (3.71)3 (1, 5)257 (51.50)761 (1.53)1 (0, 2)345 (69.14)1430 (2.87)2 (0, 4)
    10 to 17 (n = 436)410 (94.04)3299 (7.57)5 (3, 9)344 (78.90)1101 (2.53)2 (1, 3)209 (47.94)667 (1.53)0 (0, 2)329 (75.46)1531 (3.51)2 (1, 4)
    18 to 30 (n = 537)482 (89.76)4174 (7.77)6 (2, 11)332 (61.82)1226 (2.28)1 (0, 3)214 (39.85)668 (1.24)0 (0, 2)406 (75.61)2280 (4.25)2 (1, 6)
    31 to 45 (n = 347)319 (91.93)3708 (10.69)8 (4, 16)254 (73.20)1214 (3.50)2 (0, 5)134 (38.62)459 (1.32)0 (0, 1)271 (78.10)2035 (5.86)3 (1, 8)
    46 to 64 (n = 194)180 (92.78)2286 (11.78)9 (4, 17)140 (72.16)716 (3.69)2 (0, 5)72 (37.11)222 (1.14)0 (0, 1)162 (83.51)1348 (6.95)4 (2, 10)
    65+ (n = 32)30 (93.75)359 (11.22)9 (4.5,14)26 (81.25)141 (4.41)4 (1.5, 6)6 (18.75)15 (0.47)0 (0, 0)27 (84.38)203 (6.34)4.5 (1, 8)
    All (n = 2045)1907 (93.25)17870 (8.74)7 (3, 12)1533 (74.96)6251 (3.06)2 (0, 4)892 (43.62)2792 (1.37)0 (0, 2)1540 (75.31)8827 (4.32)2 (1, 6)
    AgeED Reliance ScoreCo-management
    % of Sample with EDR ≥ 0.33Mean (SD)n (Row %)
    1 to 9 (n = 499)21.840.19 (0.21)224 (44.88)
    10 to 17 (n = 436)23.170.19 (0.24)171 (39.22)
    18 to 30 (n = 537)44.690.35 (0.31)153 (28.49)
    31 to 45 (n = 347)34.010.27 (0.28)105 (30.26)
    46 to 64 (n = 194)24.230.20 (0.25)53 (27.32)
    65+ (n = 32)12.500.14 (0.20)6 (18.75)
    All (n = 2045)30.270.25 (0.27)712 (34.82)
    • ED, emergency department, EDR, emergency department reliance; PCP, primary care physician; IQR, interquartile ranges; IP, In-Patient; SD, standard deviation.

    • View popup
    Table 4.

    Hydroxyurea (HU) Prescription (Rx) Fills and Adherence for North Carolina Medicaid Enrolled at least 12-monthnths Age 1 to 64 (N = 2013)

    Medicaid Enrolled for 12-monthnths by Age Group
    1 to 9 (n = 499)10 to 17 (n = 436)18 to 30 (n = 537)31 to 45 (n = 347)46 to 64 (n = 194)All (n = 2013)
    Participants with a HU Rx Filled
        N (% of eligible sample)200 (40.08)201 (46.10)183 (34.08)43 (12.39)22 (11.34)649 (32.24)
    Description of usage for participants with at least one HU Rx Enrolled in Medicaid for 12-months
    1 to 9 (n = 200)10 to 17 (n = 201)18 to 30 (n = 183)31 to 45 (n = 43)46 to 64 (n = 22)All (n = 649)
    Number of HU Rx Filled
        Median (IQR)7 (4, 10)6 (4, 8)4 (1, 7)4 (2, 7)5.5 (2, 10)5 (2, 8)
    Number of Days Supplied†
        Median (IQR)221 (104.5, 319)180 (105, 270)110 (30, 210)120 (58, 210)165 (90, 300)159 (85, 270)
    Duration of HU Treatment (days)‡
        Median (IQR)340 (301, 349)334 (285, 350)322 (266, 345)336 (305, 347)334 (287, 357)334 (284, 349)
    Number of Days between breaks in treatment§
        Median (IQR)14.21 (0, 50.75)22.8 (7.75, 51.50)49.33 (19.67, 139)40.40 (21.60, 103.50)35.45 (0, 89.67)29.6 (7, 72.5)
    HU Adherence¶, n (%)
        Good95 (47.50)60 (29.85)33 (18.03)9 (20.93)8 (36.36)205 (31.59)
        Fair30 (15.00)48 (23.88)23 (12.57)8 (18.60)2 (9.09)111 (17.10)
        Poor75 (37.50)93 (46.27)127 (69.40)26 (60.47)12 (54.55)333 (51.31)
    • IQR, interquartile ranges

    • * There were zero participants on HU in the 65+ age group so they were excluded from this analysis.

    • ↵† Number of days supplied is the sum of the days of supply on the Rx (eg, 30-day supply) in a 12-month period per person.

    • ↵‡ Duration of HU treatment days is the number of days between the first HU Rx filled and February 28, 2017.

    • ↵§ Number of days between breaks in treatment is the sum of days of no HU coverage divided by the number of gaps (missing next HU Rx fill) per person.

    • ↵¶ HU adherence is considered Good—if number of days supplied is ≤80% of duration of HU treatment; Fair or Moderate—if number of days supplied is 60% to 79% of duration of HU treatment; Poor—if number of days supplied is >60% of duration of HU treatment.

PreviousNext
Back to top

In this issue

The Journal of the American Board of Family     Medicine: 33 (1)
The Journal of the American Board of Family Medicine
Vol. 33, Issue 1
January-February 2020
  • Table of Contents
  • Table of Contents (PDF)
  • Cover (PDF)
  • Index by author
  • Back Matter (PDF)
  • Front Matter (PDF)
Print
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word on American Board of Family Medicine.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Sickle-Cell Disease Co-Management, Health Care Utilization, and Hydroxyurea Use
(Your Name) has sent you a message from American Board of Family Medicine
(Your Name) thought you would like to see the American Board of Family Medicine web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
4 + 2 =
Solve this simple math problem and enter the result. E.g. for 1+3, enter 4.
Citation Tools
Sickle-Cell Disease Co-Management, Health Care Utilization, and Hydroxyurea Use
Nancy Crego, Christian Douglas, Emily Bonnabeau, Marian Earls, Kern Eason, Elizabeth Merwin, Gary Rains, Paula Tanabe, Nirmish Shah
The Journal of the American Board of Family Medicine Jan 2020, 33 (1) 91-105; DOI: 10.3122/jabfm.2020.01.190143

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
Sickle-Cell Disease Co-Management, Health Care Utilization, and Hydroxyurea Use
Nancy Crego, Christian Douglas, Emily Bonnabeau, Marian Earls, Kern Eason, Elizabeth Merwin, Gary Rains, Paula Tanabe, Nirmish Shah
The Journal of the American Board of Family Medicine Jan 2020, 33 (1) 91-105; DOI: 10.3122/jabfm.2020.01.190143
Twitter logo Facebook logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • Methods
    • Results
    • Discussion
    • Conclusion
    • Notes
    • References
  • Figures & Data
  • References
  • Info & Metrics
  • PDF

Related Articles

  • No related articles found.
  • PubMed
  • Google Scholar

Cited By...

  • Family Medicine and the "New" Opioid Epidemic
  • Google Scholar

More in this TOC Section

  • Associations Between Modifiable Preconception Care Indicators and Pregnancy Outcomes
  • Perceptions and Preferences for Defining Biosimilar Products in Prescription Drug Promotion
  • Evaluating Pragmatism of Lung Cancer Screening Randomized Trials with the PRECIS-2 Tool
Show more Original Research

Similar Articles

Keywords

  • Child Health
  • Emergency Departments
  • Hematology
  • Hospitalization
  • Hydroxyurea
  • Medicaid
  • Minority Health
  • North Carolina
  • Primary Health Care
  • Sickle-Cell Anemia
  • Vulnerable Populations

Navigate

  • Home
  • Current Issue
  • Past Issues

Authors & Reviewers

  • Info For Authors
  • Info For Reviewers
  • Submit A Manuscript/Review

Other Services

  • Get Email Alerts
  • Classifieds
  • Reprints and Permissions

Other Resources

  • Forms
  • Contact Us
  • ABFM News

© 2025 American Board of Family Medicine

Powered by HighWire