| Literature DB >> 18045482 |
Asheley Cockrell Skinner1, Michelle L Mayer.
Abstract
BACKGROUND: The current climate of rising health care costs has led many health insurance programs to limit benefits, which may be problematic for children needing specialty care. Findings from pediatric primary care may not transfer to pediatric specialty care because pediatric specialists are often located in academic medical centers where institutional rules determine accepted insurance. Furthermore, coverage for pediatric specialty care may vary more widely due to systematic differences in inclusion on preferred provider lists, lack of availability in staff model HMOs, and requirements for referral. Our objective was to review the literature on the effects of insurance status on children's access to specialty care.Entities:
Mesh:
Year: 2007 PMID: 18045482 PMCID: PMC2222624 DOI: 10.1186/1472-6963-7-194
Source DB: PubMed Journal: BMC Health Serv Res ISSN: 1472-6963 Impact factor: 2.655
Figure 1Distribution of articles included in full literature review.
Characteristics of included articles.
| Number | Percent | |
| All/Not specific | 20 | 67 |
| Asthma specialist | 6 | 20 |
| Juvenile rheumatoid arthritis specialist | 1 | 3 |
| Cardiology | 1 | 3 |
| Urology | 1 | 3 |
| Otolaryngology | 1 | 3 |
| Local/Other | 12 | 40 |
| State | 12 | 40 |
| National | 6 | 20 |
| Utilization | 17 | 57 |
| Referral rate | 3 | 10 |
| Referral type | 1 | 3 |
| Satisfaction with availability of specialists | 1 | 3 |
| Unmet need | 5 | 17 |
| Time to referral | 1 | 3 |
| Appointment availability | 2 | 7 |
| 0 | ||
| Patients | 26 | 87 |
| Physicians | 3 | 10 |
| Both | 1 | 3 |
Summary of articles addressing the effects of uninsurance on access to specialty care.
| Kane et al. [12] | 2005 | 700 | National Survey of CSHCN, single state | Cross-sectional | Unmet needs | Logistic regression; likelihood of unmet need | OR = 8.6, p < 0.001 | ||
| Mayer et al. [13] | 2003 | 38,866 | National Survey of CSHCN | Cross-sectional | Unmet need | Logistic regression; likelihood of unmet need for specialty care | OR = 4.29, p < 0.01 | ||
| Park et al. [14] | 2002 | 1,985 | National Health Interview Survey | Cross-sectional | Utilization | Proportion having seen a specialist (exact values not reported) | Less likely vs. any insurance | ||
| Perlstein et al. [15] | 1997 | 544 | Regional cardiac registry | Retrospective cohort | Time to referral | t-test; mean age at referral | 251 days vs. 80 days, p < 0.05 | ||
| Szilagyi, et al. [16] | 2000 | 2,126 | Single SCHIP | Quasi-experimental | Utilization | t-test, difference in number of specialist visits (pre- and post-enrollment) | Fivefold increase in utilization after SCHIP enrollment |
Summary of articles addressing the effects of public insurance on access to specialty care.
| Cabana et al. [21] | 2002 | 3,163 | Single MCO | Cross-sectional | Utilization | Logistic regression; likelihood of specialty care | Private with copay: OR = 2.52, p < 0.05 Private w/o copay: OR = 3.40, p = NS | ||
| Damiano et al. [22] | 2003 | 463 | State SCHIP | Prospective cohort | Unmet need | McNemar; unmet need pre- vs. post-enrollment | 40% vs. 13%; p < 0.05 | ||
| Davidoff et al. [23] | 2005 | 3413 | National Health Interview Survey | Quasi-experimental | Utilization | Change in proportion with any visit | +3.8, p = NS | ||
| Forrest et al. [24] | 1999 | 27,104 | National practice-based research network | Prospective | Referral rates | t-test, percent referred; logistic regression, likelihood of referral to specialty | 4.46% vs. 2.61%, p < 0.001 | ||
| Holl et al [25] | 2000 | 1,730 | Single SCHIP | Quasi-experimental | Utilization | Change in proportion with any specialist visit | Age < 1 year: 15.5% vs. 16.1%, p = NS; Age 1–5 years: 19.7% vs. 19.4%, p = NS | ||
| Hwang et al. [26] | 2005 | 54 | Clinics in a single state | Cross-sectional | Appointment availability | t-test, proportion offering appointment | 96% vs. 41%, p < 0.0001 | ||
| Kempe et al. [27] | 2000 | 596 | Pediatric practices in a single state | Retrospective cohort | Referral rates | χ2; proportion with referral | 11% vs. 20%, p = 0.09 | ||
| Kempe et al [28] | 2005 | 480 | Single SCHIP | Prospective cohort | Utilization | Logistic regression; saw specialist when needed; any specialist visit | OR = 1.96, p < 0.05; OR = 1.22, p = NS | ||
| Mayer et al. [13] | 2004 | 38,866 | National Survey of CSHCN | Cross-sectional | Unmet need | Logistic regression; likelihood of unmet need for specialty care | Medicaid: OR = 1.26, p = NS; SCHIP: OR = 0.82, p = NS | ||
| Ortega et al. [29] | 2001 | 1,002 | Multiple hospitals; single geographic region | Retrospective cohort | Utilization | χ2;percent seeing an asthma specialist | 30% vs. 6%, p < 0.001 | ||
| Park et al. [14] | 2002 | 1,985 | National Health Interview Survey | Cross-sectional | Utilization | Proportion having seen a specialist | Less likely vs. private insurance | ||
| Perlstein et al. [15] | 1997 | 544 | Regional cardiac registry | Retrospective cohort | Time to referral | t-test; mean age at referral | 168 days vs. 80 days, p < 0.05 | ||
| Price et al. [34] | 1999 | 94 | Single hospital | Cross-sectional | Utilization | t-test; number of specialist visits | All: 3 vs. 6, p = NS; asthma-related: 2 vs.4, p < 0.05 | ||
| Szilagyi, et al. [31] | 2000 | 187 | Single SCHIP, children with asthma | Quasi-experimental | Utilization | χ2 and t-test; percent seeing specialist, number of visits | Any specialist: 30% vs. 40%, p = 0.02; Visits: 0.36 vs. 0.48, p = 0.02 | ||
| Szilagyi, et al. [16] | 2000 | 2,126 | Single SCHIP | Quasi-experimental | Utilization | t-test, difference in number of specialist visits | 0.174 more visits after enrollment, p < 0.001 | ||
| Szilagyi et al. [30] | 2004 | 2,644 | Single SCHIP | Prospective cohort | Utilization and unmet need | Logistic regression, change in unmet needs pre- and post-enrollment | 15.5 percentage point decrease after enrollment, p < 0.01 | ||
| Wang et al. [32] | 2004 | 100 | Clinics in single state | Cross-sectional | Appointment availability | Percentage comparisons, no statistical test, percent offering an appointment | 97% vs. 27% | ||
| Zwanziger, et al. [33] | 2000 | 1,910 | Single SCHIP | Quasi-experimental | Utilization | OLS, change in expenditures pre- and post-enrollment | $71.85 increase after enrollment |
Summary of articles addressing the effects of managed care on access to specialty care.
| Alessandrini et al. [37] | 2001 | 553 | Single hospital | Prospective cohort | Utilization | χ2; % with a specialty visit; number of visits | 10% vs. 12%, p = 0.68; 0.2 vs. 0.2, p = 0.65 | ||
| Cartland and Yudkowsky [43] | 1992 | 1,264 | American Academy of Pediatrics Fellows | Cross-sectional | Referral rates | χ2; frequency of referral of MCO patients | More frequent: 2.5%; less frequent, 8.7%; p < 0.05 | ||
| Cuesta et al. [44] | 2000 | 49 | Single hospital | Retrospective cohort | Referral type | χ2 | Initial referral is to rheumatologist vs. orthopedic surgeon | Managed care: 83% vs. 17%; "Traditional commercial": 58% vs. 42%; p = NS | |
| Ferris et al. [39] | 2002 | 59,952 | Single MCO | Quasi-experimental | Utilization | t-test; number of specialist visits and proportion new specialist visits | Visits: 0.28 vs. 0.28, p = NS; % new visits: 30.6% vs. 34.8%; p < 0.05 | ||
| Ferris et al. [45] | 2001 | 1,839 | Single insurance plan | Prospective cohort | Utilization | t-test; change in visits | 57% decrease vs. 31% increase; p = 0.005 | ||
| Forrest et al [24] | 1999 | 27,104 | National practice-based research network | Prospective | Referral rates | t-test, percent referred; logistic regression, likelihood of referral to specialty | Medicaid, OR = 1.86, p < 0.001; Private, OR = 1.76, p < 0.01 | ||
| Garrett et al [38] | 2003 | 34,280 | National Health Interview Survey | Retrospective | Utilization | Probit; mandatory PCCM vs. FFS, mandatory HMO vs. FFS; likelihood of any specialist visit | PCCM = 0.003, p = NS; HMO = 0.378, p < 0.05 | ||
| Lake [46] | 1999 | 12,383 | Community Tracking Survey | Cross-sectional | Satisfaction | Logistic regression; difference in percent satisfied with choice of specialists | -8.3%, p < 0.05 | ||
| Mitchell, Khatutsky, and Swigonski [40] | 2001 | 966 | Single SCHIP | Cross-sectional | Unmet need | χ2; percent with unmet need for specialist | 6.0% vs. 10.6%, p = NS | ||
| Perlstein et al. [15] | 1997 | 544 | Regional cardiac registry | Retrospective cohort | Time to referral | t-test; mean age at referral | 140 days vs. 80 days, p < 0.05 | ||
| Price et al. [34] | 1999 | 94 | Single hospital | Cross-sectional | Utilization | t-test; number of specialist visits | All: 7.5 vs. 6, p = NS; asthma-related: 5 vs. 4, p,0.05 | ||
| Roberto et al. [53] | 2005 | 935 | Single Medicaid program | Quasi-experimental | Utilization | Probit; change in access to specialist | b = 0.221, p < 0.05 | ||
| Shenkman at al. [42] | 2004 | 2,333 | Single SCHIP | Cross-sectional | Utilization | Logistic regression; likelihood of a specialist visit | Percent paid on FFS basis: 0.950, p = 0.003; Bonus for quality profile: 1.714, p = 0.0003 | ||
| Shields, et al. [41] | 2002 | 6,231 | Single Medicaid program | Cross-sectional | Utilization | Logistic regression; likelihood of specialist visit | OR = 1.80, p < 0.05 |