Abstract
Objectives
Recent health policy changes have focused efforts on reducing emergency department (ED) visits as a way to reduce costs and improve quality of care. This was a systematic review of interventions based outside the ED aimed at reducing ED use.
Methods
This study was designed as a systematic review. We reviewed the literature on interventions in five categories: patient education, creation of additional non-ED capacity, managed care, prehospital diversion, and patient financial incentives. Studies written in English, with interventions administered outside of the ED, and a comparison group where ED use was an outcome, were included. Two independent reviewers screened search results using MEDLINE, Cochrane, OAIster, or Scopus. The following data were abstracted from included studies: type of intervention, study design, population, details of intervention, effect on ED use, effect on non-ED health care use, and other health and financial outcomes. Quality of individual articles was assessed using Grading of Recommendations Assessment, Development, and Evaluation (GRADE) guidelines.
Results
Of 39 included studies, 34 were observational and five were randomized controlled trials. Two of five studies on patient education found reductions in ED use ranging from 21% to 80%. Out of 10 studies of additional non-ED capacity, four showed decreases of 9% to 54%, and one a 21% increase. Both studies on prehospital diversion found reductions of 3% to 7%. Of 12 studies on managed care, 10 had decreases ranging from 1% to 46%. Nine out of 10 studies on patient financial incentives found decreases of 3% to 50%, and one a 34% increase. Nineteen studies reported effect on non-ED use with mixed results. Seventeen studies included data on health outcomes, but 13 of these only included data on hospitalizations rather than morbidity and mortality. Seven studies included data on cost outcomes. According to the GRADE guidelines, all studies had at least some risk of bias, with four moderate quality, one low quality, and 34 very low quality studies.
Conclusions
Many studies have explored interventions based outside the ED to reduce ED use in various populations, with mixed evidence. Approximately two-thirds identified here showed reductions in ED use. The interventions with the greatest number of studies showing reductions in ED use include patient financial incentives and managed care, while the greatest magnitude of reductions were found in patient education. These findings have implications for insurers and policymakers seeking to reduce ED use.
Growing health care costs in the United States have made patients, providers, and payers examine the value of services delivered.1 Concepts such as accountable care organizations and medical homes are gaining momentum with the goal of limiting avoidable, redundant, ineffective, or harmful treatments in favor of expanding effective care, access to care, and care coordination.
Many programs aimed at improving efficiency focus on the use of hospital-based emergency departments (ED) for care. EDs care for critically ill patients and acute unscheduled conditions and serve as a safety net for those with limited access to health care due to insurance status, the timely availability of clinic-based physicians, and the need for care outside of traditional business hours.2 The focus on the ED as a place to improve efficiency stems from observations that ED care for low-acuity conditions results in higher charges than for similar diagnoses seen in other settings.3 In addition, an ED visit may be a marker of a potentially avoidable injury or illness that could have been prevented with better primary care, patient education, or enhanced public health measures.
Studies have examined the effect of interventions to reduce ED use that are performed outside the ED, such as patient education, improved clinic access, care coordination, patient-centered care, and others. While ED-based interventions also exist, they are fundamentally different because of their location and their focus (e.g., follow-up vs. prevention). Our group recently conducted a systematic review of ED-based care coordination interventions.4 Therefore, this review focuses specifically on interventions based outside of the ED looking at systems-level changes, rather than ED-specific changes. Prior reviews of aggregated non-ED interventions have either focused only on one type of intervention or excluded some subsets of visits such as pediatric patients or categories of intervention such as prehospital diversion.5–7 To our knowledge, there has been no broad-based inclusive review of the comparative effectiveness of the myriad interventions tested to reduce ED use. The goal of this investigation was to review the evidence on the effectiveness of interventions based outside of the ED aimed at reducing ED use and, ultimately, to explore themes about which interventions may be most effective, along with any undesired consequences.
Methods
Study Design
We systematically reviewed the literature on the effectiveness of non-ED interventions aimed at reducing ED use. Non-ED interventions were defined as those implemented outside of an ED or hospital (e.g., insurance-based, outpatient clinic-based). No human subjects or medical records were reviewed as a part of this study so institutional review board approval was not required.
The databases MEDLINE, Cochrane, OAIster, and Scopus were examined from 1966 to the present. Keywords used included emergency department, emergency medical services, utilization, demand, patient education, primary care, capacity, extended hours, advanced access, telephone triage, general practitioner, care coordination, copayment, and payment reform (MEDLINE search terms in Appendix A). Searches were limited to English language publications. Because of the variety in the interventions and outcome measurements in the results, we performed a qualitative rather than quantitative systematic review.
Data Collection and Processing
Two independent reviewers (MA, SRM) screened search results and excluded those with titles that did not fit inclusion criteria (next section). The two reviewers then screened the abstracts of the remaining citations, again excluding those that did not fit inclusion criteria. The remaining articles underwent full-text review to exclude any remaining studies that did not fit inclusion criteria. Intrarater reliability was measured with a 10% sample of citations, resulting in a kappa of 0.92. Each article with conflicting opinion from reviewers was discussed with a third reviewer (JMP) for a final resolution.
The following data were abstracted from all eligible studies: type of intervention, study design, population, details of intervention, effect on ED use, effect on non-ED health care use, and other health and financial outcomes. Reviewers used a standard format to abstract data; this format mirrors the categories in the tables presented here. We attempted to standardize results across studies. In studies with data available for absolute number of ED visits before and after the intervention was implemented (as opposed to, for example, number of visits per person, etc.), we calculated a percentage reduction of ED visits. When visit numbers were reported, the difference between number of visits before and after the intervention was divided by the number of ED visits prior to intervention to standardize the comparison of study results.
We followed guidelines created in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement to create a four-phase flow diagram (Data Supplement S1, available as supporting information in the online version of this paper) showing the number of records included and excluded at each phase.8
Inclusion and Exclusion Criteria
Studies were included if they had interventions administered outside of the ED, had a comparison group where ED use was an outcome, and were in English. While studies in other languages were excluded, studies were included regardless of country and health care system if published in English. Five categories of interventions were included: 1) patient education on medical conditions and appropriate medical care use for low-acuity conditions, 2) creation of additional capacity in non-ED settings (e.g., expanded hours or same-day access), 3) managed care (e.g., primary care physician capitation or gatekeeping), 4) prehospital diversion, and 5) patient financial incentives (e.g., copayments or deductibles). Two other interventions, telephone triage and case management, were initially searched for but because recent systematic reviews have compiled the results of those topics; these were excluded.5,6
Studies with ED-based interventions were excluded, as were studies without measurable objective outcomes. Studies with outcomes assessed through patient or provider subjective surveys were also excluded.
Quality Assessment
Quality assessment was done using the portion of the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) criteria aimed at assessing the risk of bias in individual articles.9 Because of the heterogeneity in study designs, other components of the GRADE criteria, including the formal overall evaluation of the body of literature, were not used. Additionally, studies with risk-adjusted results and where significance was measured are reported.
Results
Literature Search
The search yielded 793 titles. After removing duplicates and exclusions based on title or abstract, 62 studies remained and underwent full-text review (Data Supplement S1). An additional 19 references were identified and also underwent full-text review, which resulted in a total number of included studies of 39 that ranged from publication dates of 1986 to 2011. The number of included studies per category is as follows: patient education on medical conditions and health care use, five studies;10–14 creation of additional non-ED capacity, 10 studies;15–24 prehospital diversion of low-acuity patients, two studies;25,26 managed care, 12 studies;27–38 and patient financial incentives, 10 studies.39–47
Description of Included Studies
Patient Education on Medical Conditions Health Care Use
Two out of five studies found significant reductions in the use of the ED after interventions, with reductions ranging from 21% to 80% (Table 1).10–14 All studies were based in the United States. Interventions included use of booklets or in-person educational sessions. Both pediatric and adult patients are included. Three studies reported data on non-ED use with one finding 0.03 fewer clinic visits per person.10–12 Three articles reported health outcomes and no significant adverse events were noted.11–13 No studies reported risk-adjusted data.
Table 1. Patient Education on Health Care Use.
Author/Year | Design | Population | Intervention | Effect on ED Use | Effect on Non-ED Use | Other Outcomes |
---|---|---|---|---|---|---|
Intervention: Booklet | ||||||
Glavan et al. (1998)10 | Pre–post interventional study United States 6 months |
Air Force base Intervention group: 1,555 subjects Control group: 972 subjects |
Subjects in intervention group were given a self-care book with an information session on how to use the book | Intervention group: reduction in ED use rate per person from 0.353 to 0.279 (p = 0.02) Control group: increase in ED use rate per person from 0.386 to 0.421 |
Intervention group: reduction in clinic use rate per person from 1.072 to 1.038 Control group: increase in clinic visits rate per person from 1.040 to 1.168 | Not reported |
Rector et al. (1999)14 | Randomized, parallel group study United States January–July 1998 |
Two urban Medicaid health plans (Plan A and B) Intervention group: house holds sent educational brochure Control group: households not sent educational brochure |
Households were randomized to receive a booklet, First Look, about care of common nonurgent conditions | Nonsignificant reductions in ED use of 1.1% (Plan A, 95% CI = −3.1% to 0.8%) and −1.2% (Plan B, 95% CI = −4.1% to 1.4%) | No difference in either plan in physician office visits | |
Intervention: Training Sessions | ||||||
McWilliams et al. (2008)11 | Retrospective cohort-control study, difference-in-difference model United States 12 months |
Primary care practices at academic health center Intervention group: 191 patients in practice Control groups:
|
Nurses provided standardized education along with prescription for pain relieving ear drops Parents reminded of 24-hour medical advice telephone access |
Reduction in ED use for ear pain by 80.3% (p = 0.009) at intervention site. Concurrent control site had 25% nonsignificant increase in ED use |
Nonsignificant reductions in urgent care center use by 40.3% (p = 0.33), and primary care center use by 27.8% (p = 0.14) at intervention site. In control site, 28% reduction in urgent care use, and a 4% reduction in primary care use | 3-year medical record review of all children in the intervention group revealed no episodes of mastoiditis |
Rettig et al. (1986)12 | Randomized controlled trial United States One year |
Multiple home health nursing agencies Intervention group: 180 diabetic patients Control group: 193 diabetic patients |
Diabetic patients in the intervention group underwent home teaching sessions on diabetic health problems | Nonsignificant reduction in ED visits in intervention vs. control group (0.06 vs. 0.08) (nonsignificant) | Nonsignificant increase in primary care visits within 6 months by intervention vs. control group (3.11 vs. 2.78) | Nonsignificant changes in hospitalization rates/1,000 members/year in intervention group vs. control group:
|
Schonlau et al. (2005)13 | Pre–post interventional study United States |
Primary health care centers recruited through Break through Series Collaborative Intervention group: three sites with 109 patients Control group: two sites with 76 patients | Asthmatic patients at intervention sites underwent educational sessions | Nonsignificant differences in acute care visits between groups (1.72 vs. 0.92 average visits; p = 0.08) | Not reported | No significant difference in quality of life, number of bed days, and acute care service use |
Capacity Increase in Non-ED Settings
Of 10 studies, three examined interventions that expanded capacity through new community clinics, while the remainder involved existing physician practices expanding appointments and/or hours of care. Four studies found significant decreases in the use of the ED after increases in non-ED capacity, with reductions ranging from 9% to 54%, while five were nonsignificant and one found an increase of 21% (Table 2).15–24 Four studies were based in the United States and the remaining six in Canada or Europe. Regarding effect on non-ED use, five studies reported data with four showing increases in non-ED use ranging from 1% to 102%.16,17,20–23 Of these, one article reported that while there was an increase in primary care use, there was a concurrent decrease in urgent care use.20 Two articles reported health outcomes.20,21 Three studies reported cost data showing 10% to 20% savings with the intervention.15,18,20 Two studies risk-adjusted data.20,21
Table 2. Capacity Increase in Non-ED Settings.
Author (Year) | Design; Country; Duration of Study | Population | Intervention | Effect on ED Use | Effect on Non-ED Use | Other Outcomes |
---|---|---|---|---|---|---|
Intervention: Additional Clinic(s) | ||||||
Chalder et al. (2003)22 | Matched time-series analysis England One year before and after |
NHS developed walk-in centers with drop-in service Intervention group: 10 towns with walk-in center Control group: 10 similar size towns in same region without walk-in centers |
Walk-in centers provided nurse-led, drop-in service with broad hours of operation | Decrease of 173.3 visits/month vs. decrease of three visits/ month in control group (p = 0.11) | Before and after increase of 3.9 visits to primary care facility vs. 23.7 visits in control group (p = 0.25) | None |
Hsu et al. (2003)24 | Before-and-after observational study with control group England 6 months before and after |
NHS developed walk-in centers with drop-in service Intervention group: one town with walk-in center Control group: one nearby town in the same region without walk-in center |
Walk-in centers provided nurse-led, drop-in service with broad hours of operation | ED visits increased by 10% (adjusted RR = 1.10; 95% CI = 1.00 to 1.21) | 0.10 fewer emergency consultations per day (95% CI = −3.75 to 3.55) | None |
O'Kelly et al. (2010)16 | Retrospective study Ireland 1999–2007 | Single, large ED and out-of-hours general practice emergency service clinic associated with same hospital Intervention group: Dubdoc patients Control group: low-triage-level ED patients |
“Dubdoc” is an out-of-hours general practice emergency services clinic | Significant decrease low-triage-level ED visits during Dubdoc hours (54% decrease in low-acuity ED visits vs. 52% decrease outside Dubdoc hours; p < 0.033) | Increase of 102% in “Dubdoc” visits (3,810 in 1999 to 7,696 in 2007) | Not reported |
Rust et al. (2009)19 | Cohort study United States 2003–2005 | Rural counties in state of Georgia Intervention group: counties with CHCs (n = 24) Control group: counties without federally funded CHCs (n = 93) |
CHCs provide care to the uninsured without medical homes | Non-CHC counties had higher rates of ED visits (RR = 1.21; 95% CI = 1.02 to 1.41) | None reported | None reported |
Intervention: Change in scheduling/hours | ||||||
Hudec et al. (2010)15 | Case-comparison study before-and-after advance access implementation Canada 3 months |
Four family physician practices Intervention group: patients of general practice with advanced access booking Control group: patients of three general practices with traditional booking |
Practice instituted a model in which most appointments are same-day access | 28% reduction in low-acuity ED visits in group | None | 7% revenue increase for practice Improved self-reported patient satisfaction (p < 0.05) |
Philips et al. (2010)23 | Before-and-after observational study with control group Belgium 2006–2007 |
Formation of GPCs Intervention group: city (Turnhout) that implemented GPC Control group: two other large cities that did not have GPC (Ghent and Antwerp) |
GPC reorganized providers for that region and centralized out-of-hours primary health center, open on weekends and holidays | 815 visits to ED before and 791 visits post (no significant change) | Primary care visits increased in the intervention region (714 to 1197 visits) (OR = 1.37; 95% CI = 1.20 to 1.57), while stayed relatively constant in control region (734 to 850 visits) | |
Solberg et al. (2004)20 | Retrospective pre–post study United States 1999–2001 Risk adjusted |
Large, multispecialty medical group Patients with three select chronic conditions (heart disease, diabetes, depression) Intervention group: 17,376 patients in 2001 after implementation of open access Control group: 16,099 patients in 1999 before implementation of open access |
Full advanced access appointments introduced, which included standardization of schedule slots and extra visit time for clinicians | No significant difference in risk-adjusted proportion of patients visiting ED (during this time period, ED visits also increased by 7.8% for the medical group) (all p > 0.05) | Increase in primary care visits (all p < 0.01) Significant decrease in risk-adjusted proportion of patients visiting urgent care (all p < 0.001) |
Total cost per patients increased 10%–20% depending on condition Significant reduction of proportion of patients with hospitalizations (1%) and length of stay >3 days (4%) for heart disease patients only (nonsignificant changes for other conditions) |
Solberg et al. (2006)21 | Retrospective pre–post study United States 1999–2001 Risk adjusted |
Large, multispecialty medical group owned by health plan Intervention group: 6,609 patients with depression in 2001 after implementation of open access Control group: 7,284 patients with depression in 1999 before implementation of open access |
Advanced access appointments instituted (third next-day available appointment reduced from 19.4 to 4.5 days) | No significant change in ED visits | 1% increase in primary care visits (p < 0.01) 2% increase in hospitalizations (p < 0.05) |
17.6% reduction in proportion of patients with no follow-up after starting new medication (p = 0.001) Majority of visits with one physician (continuity of care) increased by 6.7% (p < 0.001) |
van Uden et al. (2004)17 | Retrospective pre–post cohort study Limburg, the Netherlands |
Regional general practitioner cooperatives Intervention group: 12,319 patient contacts after implementation of GPCs Control group: 11,781 patient contacts before implementation of GPCs |
Large cooperatives of general practitioners to offer out of hours primary care, also act as gatekeeper for ED visits | 9% decrease in ED visits after hours 13.7% absolute reduction number of self-referrals to ED |
10% increase in primary care visits after hours 4.6% increase in overall patient contacts after hours 3.6% shift in use from ED to primary care (p < 0.001) |
None |
Wang et al. (2005)18 | Pre–post intervention study with comparison group United States 12 months |
Large, private, primary care pediatric practice with Medicaid patients Intervention group: 17,382 children in the enhanced access program Control group: 26,066 Medicaid-eligible children who received services from other local community primary care providers |
Increased care coordination, case management, expanded after-hours clinics and walk in hours at clinic | 20% reduction in ED utilization for the intervention group (p = 0.007) | Cost per member per month was $8.53 was found in the control group and $7.17 in intervention group, thus a comparative savings of 16% |
CHCs = community health centers; GPCs = group practitioner cooperatives; RR = rate ratio.
Prehospital Diversion of Low-acuity Patients
Both studies examining the effects of emergency medical services (EMS) diversion of low-acuity patients away from the ED found significant decreases in the use of the ED after interventions, with reductions ranging from 3% to 7% (Table 3).25,26 One study was conducted in the United States, and the other, in the United Kingdom. One intervention involved EMS offering either home or clinic care to low-acuity patients.25 The other involved transportation of such patients to clinic care without home care as an option.26 Regarding effect on non-ED use, both studies found increases in use of other care settings. No studies directly addressed other health or cost outcomes. No data were risk adjusted.
Table 3. Prehospital Diversion of Low-acuity Patients.
Author (Year) | Design | Population | Intervention | Effect on ED Use | Effect on Non-ED Use |
---|---|---|---|---|---|
Schaefer et al. (2002)25 | Cohort study with matched historical controls United States August 2000–January 2001 |
Two EMS Intervention group: 1,016 patients Control (historical) group: 2,617 patients |
Low-acuity patients in the intervention group were offered an alternate care sources (clinic or home care) rather than ED use by the EMS staff | There was 7% fewer ED use by the intervention group compared to the control group (44.6% vs. 51.8%) (p = 0.001) | Clinic use: there was 3.5% more clinic use by the intervention group compared to the control group (8% vs. 4.5%) (p = 0.001) No transport (home care): there was 3.7% more home care (no transport) by the intervention group compared to the control group (47.4% vs. 4.5) (p = 0.043) |
Snooks et al. (2004)26 | Cluster randomized controlled trial United Kingdom 6 months |
Two EMS. Intervention group: 409 patients Control group: 425 patients |
Low-acuity patients in the intervention group were transported to a MIU by the EMS staff | There was 2.8% fewer ED use by the intervention group compared to the control group (74.1% vs. 76.9%) | MIU use: there was 1.3% more MIU use by the intervention group compared to the control group (10% vs. 8.7%) |
MIU = minor injuries unit.
Managed Care
Of the 12 studies examining the effects of managed care on ED use, six had interventions with capitated payment of primary care physician, five had a requirement of primary care physician approval or gatekeeping, and one was a hybrid of these two (Table 4).27–38 Ten studies were based in the United States, one in Canada, and one in Ireland. The majority of U.S. studies were in Medicaid populations and included pediatric patients. Overall, nine studies (six with capitation and four with gatekeeping as interventions) found significant decreases in the use of the ED after managed care interventions, with reductions ranging from 1% to 46%, while two did not find any significant difference.27–31,33–38 The final study found mixed results with no change in ED use when comparing physicians pre- and postcapitation, but with an increase in ED use among physicians compensated through capitation versus fee-for-service.32
Table 4. Managed Care (Capitation or Gatekeeping).
Author (Year) | Design | Population | Intervention | Effect on ED Use | Effect on Non-ED Use | Other Outcomes |
---|---|---|---|---|---|---|
Intervention: Gatekeeping | ||||||
Badgett (1986)27 | Before-and-after study United States 3 years 1983–1985 |
Single, pediatric ED Intervention group: patients assigned to PCP under AFDC recipients, estimated ∼40,000 Control group: same group of patients, 1 year prior to start of program |
Citicare program (PCP approval required for ED services), provided physician coverage 24 hours a day, 7 days a week | Total ED visits: Pre: 35,704 During: 25,543 Post: 31,248 Total ED use decreased 23% during the study period compared to period after end of program, for patients enrolled in AFDC program, ED use decreased 46% |
Not reported | Total hospital admissions from ED (no significant change): Pre: 3,545 During: 3,555 Post: 3,922 |
Franco et al. (1997)31 | Prospective cohort study with historical controls | Single, university-based pediatric clinic. Medicaid patients. Intervention group: 4,766 patients (July 1–August 30, 1991) Control group: 2,798 patients (July 1–Augist 30, 1981) |
Program requiring PCP approval for ED use | ED visits declined 2.4% (p = 0.00005) Inappropriate ED visits declined 33% (p < 0.00001) |
Not reported | Not reported |
Hurley et al. (1989)33 | Retrospective cohort study | Four Medicaid demonstration programs Intervention group: AFDC in program requiring gatekeeper approval Control group: recipients of traditional Medicaid programs |
Assigned PCP with approval required for ED services | Proportion of patients with one ED visit showed reductions from 27.5% to 36.7% in children, and between 30.6% to 44% for adults | None | None |
Murphy et al. (1997)35 | Before-and-after study Ireland 1993–1995 |
Large, single ED Intervention group: Patients were GMS ineligible did not qualify for free care in Ireland Control group: all patients who visited ED |
Patients who were GMS ineligible were charged a certain amount for each visit to the ED instead of their GP. If the patient had a letter of referral from a GP, they were exempted from the charge. | The total number of GMS ineligible visited the ED during the year before the implantation of the copayment was 19,562/43,202 (45.3%) and in the year after was 19,947/45,302 (44%), which shows a reduction by 1.3% (95% CI = −0.6 to −1.9) | Among the GMS-ineligible patients referred by a GP to the ED, the total number of this group in the year before was 2,619/19,562 (13.4%) and the year after 3,156/19,947 (15.8%), an increase of 2.4% (95% CI = 1.73 to 3.1) | Not reported |
Schillinger et al. (2000)38 | Randomized control trial United States 1997–1998 |
Single, university-affiliated primary care practice Intervention group: 1,121 patients Control group: 1,172 patients |
Intervention group required PCP approval for access to specialty and ED services | Nonsignificant increase in risk-adjusted, nonurgent ED visits in intervention group (0.06 visits/patient/year, p = 0.42) | PCP visits: nonsignificant increase in intervention group (0.27 visits/patient/year, p = 0.14) Specialty visits: significant reduction in visits in intervention group (0.57 visits/patient/year, p = 0.04) |
Inpatient care: significant reduction in hospitalizations in intervention group (0.14 hospitalizations/patient/year, p = 0.02) |
Intervention: Capitation/Physician Payment | ||||||
Catalano et al. (2000)28 | Interrupted time-series quasi-experiment | Pediatric Medicaid patients, single state Intervention group: recipients in areas with capitation Control group: recipients in areas without capitation |
Community mental health centers under capitated agreement with Medicaid. Centers billed by hospital EDs for psychiatric emergency services. | No significant increase in the level of ED usage | Decrease in inpatient psychiatric admission Increase in outpatient visits in for for-profit capitated areas |
Estimated decrease by $17–$21 million over 1 year in total (inpatient and outpatient) costs |
Catalano et al. (2005)29 | Interrupted time-series quasi-experiment | Single-state, Medicaid patients year prior and after intervention Intervention group: recipients in areas with capitation Control group: recipients in areas without capitation |
Community mental health centers under capitated agreement with Medicaid. Centers billed by hospital EDs for psychiatric emergency services | 28% decline in psychiatric ED visits compared to expected | Not reported | Not reported |
Dickey et al. (1996)30 | Before-and-after quasi-experiment | Single-state, Medicaid patients Intervention group: 10,685 patients (1993) 7,541 patients (1994) Control group: 6,614 patients (1991) 7,295 patients (1992) |
Single provider of psychiatric services (inpatients and outpatient) contracted with state under capitated agreement | 19% decrease in ED visits in years after intervention compared to years prior | Nonquantified increase in outpatient visits Inpatient admission decreased by 4% Median length-of-stay decreased by 3.3 days |
Increase in 30-day readmissions by 1.9% Reduction in expenditures per beneficiary $420 |
Glazier et al. (2009)32 | Retrospective cohort study Canada 2005–2006 |
Single province in country with universal health care system Intervention group: 487,131 patients in primary care practices of physicians who chose capitated system Control group: 2,517,527 patients in primary care practices of physicians who chose fee-for-service system |
Physicians reimbursed by age- and sex-adjusted capitation payments and required patient enrollment (still eligible for fee-for-service payments for hospital services) | No change in ED visits in capitation group vs. same physicians precapitation Increase likelihood of OR = 1.20, 95% CI = 1.15 to 1.25) for capitation group vs. fee-for-service group (4% more patients in capitation group made visits to ED Higher ratio of low-acuity visits among capitation (1.6) vs. control (0.9) groups |
Less after-hours care in capitation practices (OR = 0.68, 95% CI = 0.61 to 0.75) | Lower morbidity and comorbidity indices in capitation practices |
Josephson et al. (1997)34 | Retrospective cohort study | Members of five insurers in one city Intervention groups: 22,316 patients in fully capitated HMO 38,030 patients in any of three IPA Control group: 14,110 patients in a traditional indemnity insurance plan (estimated) |
Capitation in HMO. In IPA, capitated payments to the association but fee-for-service compensation of physician | ED use rates (p <0.05): 70 per 1000 members in capitated panel, 363 per 1000 members in IPA panel, 466 per 1000 members in indemnity panel (85% lower ED use rates in capitated vs. indemnity panel) |
None | Admission for five ambulatory sensitive conditions 0.8 per 1000 members in capitated panel, 2.7 per 1000 members in IPA panel, 2.9 per 1000 members in indemnity panel |
Piehl et al. (2000)36 | Before-and-after study United States 1995–1997 |
Pediatric visits at two community EDs over 2 year, determined rates of ED visits after implementation of managed care plan Intervention group: Medicaid-managed care with 20,663 ED visits Control group: non-Medicaid group: 34,079 ED visits |
Managed care program (recipients have assigned PCP and 24-hour access, at least telephone); PCP received monthly fee for each enrollee in addition to fee for each service | Medicaid group: 24% reduction in overall ED visits (p < 0.001) (33.5 [SD ± 5.3] reduced to 25.6 [SD ± 2.3] monthly ED visit per 1,000 enrollees); 37% reduction in nonurgent ED visits (p < 0.001) Non–Medicaid-insured group: 8% increase in overall ED visits (p < 0.001) 8% increase in nonurgent ED visits (p not given) |
Not reported | Not reported |
Price et al. (1999)37 | Retrospective cohort study United States One year |
Three asthmatic pediatric patients groups based on their type of insurance Fee-for-service group: 47 patients Capitated (HMO) group: 24 patients Medicaid group: 22 patients |
The effect of the type of insurance on the medical care use in 1 year | ED use: Fee for service, 2/47 (4%); Capitated, 6/24 (25%); Medicaid, 7.5/22 (34%); p = 0.038 |
Physician visits Fee for service, 12/47 (25%); Capitated, 12/24 (50%); Medicaid, 9.5/22 (43%); p = 0.56 Specialist visits Fee for service, 6/47 (12.7%); Capitated, 7.5/24 (31%); Medicaid, 3/22 (13.6%); p = 0.118 |
Hospital visits Fee for service, 2/47 (4%); Capitated, 2/24 (8.3%); Medicaid, 3/22 (13.6%); p = 0.14 |
AFDC = Aid to Families with Dependent Children; GMS = General Medical Services; GP = general practitioner; HMO = health maintenance organization; IPA = independent practice associations; PCP = primary care clinic.
Regarding the effect on non-ED use, six studies did report data, with only four reporting significance and mixed results.28,30,32,35,37,38 Six articles included health outcome data, five in the form of effect on hospitalizations and one on morbidity indices; results were mixed and did not always assess for significance.27,30,32,34,37,38 Two studies reported cost data with both showing decreases with capitation.28,30 No studies reported risk-adjusted data.
Patient Financial Incentives
Of the 10 studies using costs to influence patients to use certain sites for care, or to use care efficiently, nine studies found significant decreases in the use of the ED after implementation of the intervention, with reductions ranging from 3% to 50% (Table 5).39–47 The remaining study found a significant relative increase of 34% in ED visits.48 All studies took place in the United States. The intervention in seven studies was the requirement for patient copayment or coinsurance, and in three it was the implementation of a high deductible. Half of studies were in Medicaid populatons, with the majority of those single-state interventions, while the others involved commercial insurers.
Table 5. Patient Financial Incentives.
Author (Year) | Design | Population | Cost Intervention | Effect on ED Use | Effect on Non-ED Use | Other Outcomes |
---|---|---|---|---|---|---|
Intervention: Copayment/Coinsurance | ||||||
Hsu et al. (2006)39 | Quasi-experimental, longitudinal, concurrent controls United States 1999–2001 Risk adjusted |
Prepaid integrated delivery system, 19 medical center Intervention group: commercially insured, 2,257,445 patients (copayment levels: $0, $1–$5, $10–$15, $20–$35, and $50–$10 per ED visit) Control group: Medicare, with employer supplementation, 261,091 patients (copayment levels: $0, $1–$15, and $20–$50 per ED visit) |
|
|
Not reported |
|
Lowe et al. (2008)47 | Before-and-after observational study United States 48 months |
26 EDs, purposive sample of the state Intervention group: post–Oregon health plan cutbacks Control group: pre–Oregon health plan cut-backs Five groups of patients based on the class of payer:
|
Medicaid cutback, Oregon: the beneficiaries of the Oregon health plan receive new policy changes that include copayment for most of the health services (PCP visits, ED use, and hospitalization); decreased enrollment in health plan with increased number of uninsured patients |
|
Not reported | Hospitalization from ED visit (adjusted ORs):
|
Lowe et al. (2010)40 | Before-and-after study United States 2001–2004 |
State population study Intervention group: Medicaid enrollees with the standard plan Control group: Medicaid enrollees with the plus plan (not affected by cutbacks) |
Medicaid cutback, Oregon: The beneficiaries of the Oregon health plan receive new policy changes that include copayment for most of the health services (PCP visits, ED use, and hospitalization and eliminated outpatient behavioral health services | Decrease in ED use rates (RR = 0.84; 95% CI = 0.83–0.86). Compared to Plus Plan members, use also decreased (RR = 0.82; 95% CI = 0.80–0.84) Injury-related visits also decreased (p < 0.001). | Not reported | ED visits leading to hospital admission also decreased: (RR = 0.83; 95% CI = 0.79–0.86). Compared to Plus Plan members, utilization also decreased (RR = 0.85; 95% CI = 0.82–0.89). |
Mortensen (2010)48 | Quasi experimental, pre–post design (differences-in-differences methodology) 24 months Risk adjusted |
State-level study among Medicaid enrollees in 29 states. Intervention group: Medicaid enrollees in states with copayment increase (nine states) Control group: Medicaid enrollees in states without no copayment or no copayment change (20 states) |
|
Significant increase in probability of any ED visits in a year (33.1 per person-month for change group vs. 24.7 for control group, p = 0.000) | Not reported | Not reported |
O'Grady et al. (1985)41 | Randomized controlled trial United States |
State-level among six geographic areas in four states Intervention group: 3,973 persons were assigned randomly to different fee-for-service insurance plans with copayment rates of 0, 25, 50, or 95% |
A coinsurance rate of 25, 50, or 95%—up to maximum of $1,000 as out-of-pocket costs | The probability of ED use among the copayment groups was fewer than the free group
|
Not reported | The ED visit resulting in hospitalization among the copayment groups was fewer than the free group
|
Selby et al. (1996)42 | Matched cohort study Risk adjusted | Group-model HMO, 15 medical centers Intervention group: 30,276 patients Control group: 60,408 patients (matched for age, sex, and location); second group 37,539 patients (matched for same + employer) |
Introduction of a $25–$35 copayment for ED use in an HMO |
|
|
|
Wallace et al. (2008)43 | Retrospective cohort study, difference-in-differences methodology United States 2001–2004 |
State population study, propensity score matched population Intervention group: Medicaid enrollees with the Standard Plan, 10,176 subjects Control Group: Medicaid enrollees with the Plus Plan, 10,319 subjects |
Addition of $50 copayment for ED visits that did not result in admission. Intervention also included elimination of certain benefits (dental, mental health, etc.) as well as other copayments (outpatient visits, inpatient admissions, pharmacy, etc). | ED visits decreased by 7.9% (p = 0.03) in the standard (copayment) group relative to the plus group. ED visit expenditures by user increased 7.9% (p = 0.03) over the same time period despite the decrease In visits. | Pharmacy: decrease in use and expenditures (−2.2%, p < 0.001; −10.5%, p < 0.001). Inpatient: increase in use and expenditures (+27.3%, p < 0.001; +20.1, p < 0.001) Hospital outpatient: increase in use and expenditures (+13.5%, p < 0.001; 19.7%, p < 0.001) Ambulatory: decrease in use (−7.7%, p < 0.001) but increase in expenditures by user (+6.6%, p = 0.75) |
Total expenditures (+2.2%, p = 0.47) by person unchanged despite overall reduction in use (−2.2%, p < 0.001) |
Intervention: HDHP | ||||||
Waters et al. (2011)45 | Retrospective cohort study Risk adjusted |
Major insurer in single state, propensity score matched sample Intervention group: 1,354 HDHP group initially in PPO, then switched and maintained in HDHP for all 3 study years Control group: 1,354 members of enrolled in PPO plan |
HDHP with deductibles ranging from $1,700 to $6,000 vs. PPO plan. HDHP enrollees used standard PPO contracted amounts before meeting their deductible. | HDHP enrollees had lower probability of use and level of use (p < 0.05) | HDHP enrollees appeared to have decreased primary care use (p < 0.01), but greater specialty physician use (p < 0.05) | HDHP enrollees had significantly higher prescription drug utilization and expenditures (p < 0.05) |
Wharam et al. (2007)44 | Before-and-after study United States 2001–2005 |
Single-state, single-insurance carrier offering HDHP and HMO plans Intervention group: 8,724 enrollees with HDHP for at least 6 months, after 1 year of traditional HMO Control group: 59,557 enrollees with traditional HMO, matched on adult/child status. |
Individuals in the HDHP group have annual individual deductibles ranging from $500 to $2,000. If the expenditure exceeds the deductible, individuals pay a copayment ($100) for each ED use. Individuals in the intervention group had copayment for each ED ($20-$100) and outpatient visit ($5–$25). |
ED visits with 10.0% relative decrease (absolute change, 20.2 visits per 1,000) in the HDHP group compared with controls from baseline to follow-up (95% CI = −16.6% to −2.8%; p = 0.007) | ED visits resulting in hospitalizations with 24.7% relative decrease (with an absolute rate difference of −2.6% in the HDHP group (95% CI = −41.0% to −3.9%; p = 0.02) ED expense per HDHP member decreased from $75 in the baseline year to $36 in the follow-up period, an absolute decline of $52, representing a 58.5% relative decline (95% CI = −64.4% to −51.5%; p <0.001) |
|
Intervention: Health Savings Account | ||||||
Wilson et al. (2008)46 | Multiyear cross-sectional study United States 2004–2006 Risk adjusted |
Commercial insurance plan with both comprehensive major medical and CDHP Intervention group: enrollees of CDHP plan for the study year Control group: enrollees of traditional comprehensive major medical plan |
CDHP includes a variety of products including health reimbursement accounts and health savings accounts, which are portable if an employee leaves his or her employer. All offer first-dollar coverage for preventive services. | After risk adjustment, CDHP plan members had 129.1 vs. 141.2 ED visits/1,000 members/year |
CDHP = consumer-driven health plan; HDHP = high-deductible health plan; HMO = health maintenance organization; ICU = intesive care unit; PCP = primary care provider; PPO = preferred provider organization; RR = rate ratio.
Regarding effect on non-ED use, two studies did report data with one showing no change in urgent care, pediatric office, adult office, and ambulatory care visits, but one showed an increase in hospital outpatient department use.42,43 Six studies reported health outcomes in the form of ED visits resulting in hospitalization, which decreased or were unchanged.39–42,44,47 Of these six, two also reported effects on morbidity, one showing no change and one showing a decrease.39,42 Three studies reported cost data with mixed results.43–45 Five studies risk-adjusted data.39,42,45,46,48
Quality Assessment
Quality assessment for risk of bias in individual articles can be found in Table 6 and Data Supplement S2 (available as supporting information in the online version of this paper). All 34 observational studies were of very low quality according to GRADE guidelines, in which observational studies are at best low quality and any serious risk of bias lowers the quality to very low. Four of the randomized trials were of moderate quality and one of low quality.
Table 6. Quality Assessment of Selected Observational Studies on Non-ED Interventions to Reduce ED Utilization Using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) Criteria.
Possible limits of observational studies
| ||
---|---|---|
First Author (Reference) | Existing Limitations | Overall Quality of Evidence |
Patient education | ||
Glavan (10) | 1, 3, 4 | Very low |
McWilliams (11) | 1, 3 | Very low |
Schonlau (13) | 1, 3 | Very low |
Non-ED capacity increase | ||
Chalder (22) | 1, 2, 3 | Very low |
Hsu (24) | 1, 3, 4 | Very low |
Hudec (15) | 1, 3, 4 | Very low |
O'Kelly (16) | 1, 2, 3, 4 | Very low |
Philips (23) | 1, 2, 3 | Very low |
Rust (19) | 1, 2, 3 | Very low |
Solberg (20) | 1,2,3 | Very low |
Solberg (21) | 1,2,3,4 | Very low |
van Uden (17) | 1, 2, 3 | Very low |
Wang (18) | 2, 3 | Very low |
Prehospital diversion | ||
Schaefer (25) | 1, 3, 5 | Very low |
Managed care | ||
Badgett (27) | 1, 3, 4 | Very low |
Catalano (28) | 1, 3 | Very low |
Catalano (29) | 1,3, 4 | Very low |
Dickey (30) | 1, 3, 4 | Very low |
Franco (31) | 1, 2, 3 | Very low |
Glazier (32) | 1, 3 | Very low |
Hurley (33) | 1, 2, 3, 4 | Very low |
Josephson (34) | 1,3, 4 | Very low |
Murphy (35) | 1, 3 | Very low |
Piehl (36) | 3, 4 | Very low |
Price (37) | 2, 4 | Very low |
Patient financial incentives | ||
Hsu (39) | 3 | Very low |
Lowe (47) | 1, 2, 3 | Very low |
Lowe (40) | 2, 3 | Very low |
Mortensen (48) | 1, 2, 3, 5 | Very low |
Selby (42) | 3 | Very low |
Wallace (43) | 3 | Very low |
Waters (45) | 2, 3,4 | Very low |
Wharam (44) | 1,3,5 | Very low |
Wilson (46) | 2, 3 | Very low |
Discussion
In 2003, Asplin et al.2 identified input, throughput, and output factors associated with crowding in the ED. In this paper, we explore primarily the effect of how systems outside the ED can influence demand for ED care and focused entirely on “input.” This expands on previous work where we conducted a systematic review of care coordination within the ED.4 With respect to non-ED interventions, we found there have been many studies exploring non-ED interventions to reduce ED use in various populations across more than two decades with mixed evidence. Over two-thirds (27 of 39, 69% ) of the identified studies in the five categories of intervention included showed reductions in ED use, with reductions ranging from 1% to 80%. Nearly all of the studies were observational, many coinciding with systemic changes within the region, and only five out of the 39 were randomized trials. Only seven of 39 studies (17.9%) reported risk-adjusted data.
The areas with the largest number of studies showing reductions in ED use include patient financial incentives and managed care interventions, with nine of 10 (90%) and 10 of 12 (83%) of those studies showing reductions, respectively. By contrast, less than half (four of 10) of the studies on increasing capacity found reductions in ED use, and one even found an increase, suggesting that adding capacity could potentially have the opposite effect. This may be due to issues with supply-induced demand. Findings on capacity should be interpreted carefully, however, as the majority of articles on this topic are international, and several take place in single-payer health care systems. The area showing the largest magnitude of reduction is patient education, with a maximum of an 80% reduction in one study.
We hope to build on the growing body of literature that addresses the overall aim to reduce ED use. Prior reviews exist on two topics not included here, telephone triage and case management. For telephone triage, a Cochrane review of nine studies included seven studies that examined the effect on ED use.5 Of these, six showed no difference, and one showed an increase in ED use. A review of interventions targeted at frequent ED use included 11 studies, of which the intervention in seven was case management.6 The results were mixed, with the majority of observational trials showing reductions in ED use, but one showing an increase, and only one out of three randomized trials showing a reduction.
More recently, Flores-Mateo et al.7 examined interventions that increased the supply of non-ED services and those that reduced demand. Similar to our findings, the authors concluded that increasing the supply of primary care physicians and cost sharing with patients were effective in reducing ED use, but increased out-of-hours primary care was not. However, there were differences in our methods, especially inclusion criteria. We included different types of studies, specifically pediatric studies, physician capitation, advanced access scheduling, and prehospital diversion and excluded ED-based studies, telephone triage, those with survey data, and those without controls. As a result, the authors of the prior review found that educational interventions did not appear to reduce ED use, while we found the opposite.
We also reviewed the articles for the effect on utilization of other health care settings. About half of the articles reported this data, although the results were presented in different ways (primary care visits, urgent care visits, specialist visits, etc.) and varied significant by category. Two of five (40%) of the education studies that examined non-ED use found decreases in use, while the others found no significant effect, suggesting that perhaps education may reduce use in general, rather than the possibility of induced demand by adding capacity. Both of the studies on prehospital diversion and five of 10 (50%) of those on capacity increases found increases in non-ED use, which may represent a type of substitution effect in which patients do not reduce their overall consumption of health care, but instead shift it to other settings. Again, many of these studies took place in single-payer systems where patients may have more access to primary care settings, whereas in the United States, access could limit this shift. Only two of 10 (20%) studies on patient financial incentives examined non-ED use, and these showed reductions. Often, though, copayments were implemented both inside and outside the ED, so it is difficult to tease apart direct and indirect effects on ED use. Interventions involving managed care showed mixed results with some increasing and some decreasing non-ED use.
Seventeen of the 29 studies (43.5%) reported adverse events, and the outcomes used varied widely, although no significant adverse events were attributed to interventions. The health outcome that was generally measured was hospitalization, and this is really a secondary outcome, with morbidity and mortality being the primary health outcome of interest. Similarly, only eight of the 39 articles (20.5%) reported any cost data, which was both limited and mixed. Some of the interventions may have ethical questions. For one, those with financial implications for patients may result in patients avoiding needed care and could result in worse health outcomes, and in the long run, possibly increased costs to the health care system. Another example is systems designed with physician or nurse gatekeepers who take away the patient's autonomy by dictating whether insurance will cover an ED visit. Our findings, taken along with prior reviews, are promising that non-ED interventions designed to reduce ED visits may be successful; however, it is clear that more study is needed to understand the most effective ways to reduce ED use.
When organizations decide that reducing ED visits is a priority, the choice must be made which interventions should be implemented. We think that the choice should be made based on organization priorities and considering the profile of pros and cons for each intervention. For example, education is simple, can be inexpensive, and has an added benefit of improving health literacy; however, it is difficult to standardize. On the other hand, managed care and patient financial incentives are powerful tools but may have unintended consequences, like deferring needed care or limiting patient choice. In addition, adding capacity may have the opposite effect as desired. However, we can conclude that reducing ED use will require broad, organizational changes. Change could include a careful multilayered approach integrating several interventions along with a feedback mechanism to monitor outcomes and adverse events.
Future research should attempt to delineate the balance of intended and unintended effects of these interventions. Across all categories, more exploration of the effect on health outcomes and costs would be beneficial. Regarding education, researchers should consider further study of specific educational materials, from booklet to in-person teaching, or even technology-based solutions. EMS diversion has such limited data that any deeper examination of this area would add to our knowledge, especially focusing on the safety and accuracy of EMS assessments. Most of the managed care studies are observations of large-scale systemic changes over several years. More randomized controlled trials are needed across all categories to reduce confounding and improve the generalizability of results.
Limitations
Many of the studies reported were observational with the potential for confounders, and few studies reported risk-adjusted data. In addition, some of the payment reform interventions were part of a bundle of changes, and it was impossible to unwind which specific intervention (or just the combination) was responsible for the changes in utilization. Many studies were similarly restricted to a single site, which reduces the generalizability to other settings.
Our primary audience was EDs in English-speaking parts of the world; therefore, we included only studies published in English. As a result, this study may miss important findings in from non-English studies. Also, eight of the 39 studies were based in Canada or Europe, while the rest were in the United States, and differences in health care systems, in particular the presence of single payer versus multipayer systems, may affect outcomes.
There was also variability in the interventions administered as well as the outcomes reported. For example, some studies reported total ED visits whereas others reported ED visits per user. This made comparison between the studies difficult and limits the ability to draw robust conclusions from the findings of the review.
Conclusions
We found that about two-thirds of the studied interventions showed reductions in ED use. Future studies should attempt to reduce confounding through robust design (i.e., randomization) and should measure unintended consequences of increased demand for other types of health care services, health outcomes, and financial effects.
Supplementary Material
Acknowledgments
Dr. Chang is generally supported by Award Number 1K12HL108974-01 from the National Heart, Lung, and Blood Institute. Dr. Pines is an associate editor for this journal, but had no involvement with the review or publication decision for this manuscript.
Appendix A:
MEDLINE Search Terms
(((“emergency medical services” [all fields] OR “emergency medicine” [all fields] OR “emergency department” [all fields]) AND ((“utilization” [subheading] OR “utilization” [all fields]) OR demand [all fields] OR visits [all fields])) AND (“intervention” [all fields] OR “solutions” [MeSH Terms] OR “solutions” [all fields])) AND (“advanced access” [all fields] OR “primary care” [all fields] OR capacity [all fields] OR “extended hours” [all fields] OR “telephone triage” [all fields] OR “care management” [all fields] OR “patient education” [all fields] OR “general practitioner” [all fields] OR “care coordination” [all fields] OR copayment [all fields] OR diversion [all fields] OR acuity [all fields]) AND English [lang] AND English [lang].
Footnotes
Presented at the American College of Emergency Physicians Scientific Assembly, Denver, CO, October 2012.
Supporting Information: The following supporting information is available in the online version of this paper:
The documents are in DOC format.
Please note: Wiley Periodicals Inc. is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing material) should be directed to the corresponding author for the article.
Contributor Information
Sofie Rahman Morgan, Department of Emergency Medicine, Emory University, Atlanta, GA.
Anna Marie Chang, Department of Emergency Medicine, Oregon Health and Science University, Portland, OR.
Mahfood Alqatari, Department of Emergency Medicine, George Washington University, Washington, DC.
Jesse M. Pines, Departments of Emergency Medicine and Health Policy, George Washington University Hospital, Washington, DC.
References
- 1.Centers for Medicare & Medicaid Services. National Health Expenditure Tables. [Accessed Jul 25, 2013]; Available at: http://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData/downloads/tables.pdf.
- 2.Asplin BR, Magid DJ, Rhodes KV, Solberg LI, Lurie N, Camargo CA., Jr A conceptual model of emergency department crowding. Ann Emerg Med. 2003;42:173–80. doi: 10.1067/mem.2003.302. [DOI] [PubMed] [Google Scholar]
- 3.Mehrotra A, Liu H, Adams JL, et al. Comparing costs and quality of care at retail clinics with that of other medical settings for 3 common illnesses. Ann Intern Med. 2009;151:321–8. doi: 10.7326/0003-4819-151-5-200909010-00006. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Katz EB, Carrier ER, Umscheid CA, Pines JM. Comparative effectiveness of care coordination interventions in the emergency department: a systematic review. Ann Emerg Med. 2012;60:12–23. doi: 10.1016/j.annemergmed.2012.02.025. [DOI] [PubMed] [Google Scholar]
- 5.Bunn F, Byrne G, Kendall S. Telephone consultation and triage: effects on health care use and patient satisfaction. Cochrane Database Syst Rev. 2004;(4):CD004180. doi: 10.1002/14651858.CD004180.pub2. [DOI] [PubMed] [Google Scholar]
- 6.Althaus F, Paroz S, Hugli O, et al. Effectiveness of interventions targeting frequent users of emergency departments: a systematic review. Ann Emerg Med. 2011;58:41–52. doi: 10.1016/j.annemergmed.2011.03.007. [DOI] [PubMed] [Google Scholar]
- 7.Flores-Mateo G, Violan-Fors C, Carrillo-Santisteve P, Peiró S, Argimon JM. Effectiveness of organizational interventions to reduce emergency department utilization: a systematic review. PLoS ONE. 2012;7:e35903. doi: 10.1371/journal.pone.0035903. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Liberati A, Altman DG, Tetzlaff J, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. BMJ. 2009;339:b2700. doi: 10.1136/bmj.b2700. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Guyatt GH, Oxman AD, Vist G, et al. GRADE guidelines: 4. Rating the quality of evidence--study limitations (risk of bias) J Clin Epidemiol. 2001;64:407–15. doi: 10.1016/j.jclinepi.2010.07.017. [DOI] [PubMed] [Google Scholar]
- 10.Glavan KA, Haynes M, Jones DR, Philput C. A military application of a medical self-care program. Mil Med. 1998;163:678–81. [PubMed] [Google Scholar]
- 11.McWilliams DB, Jacobson RM, Van Houten HK, Naessens JM, Ytterberg KL. A program of anticipatory guidance for the prevention of emergency department visits for ear pain. Arch Pediatr Adolesc Med. 2008;162:151–6. doi: 10.1001/archpediatrics.2007.30. [DOI] [PubMed] [Google Scholar]
- 12.Rettig BA, Shrauger DG, Recker RR, Gallagher TF, Wiltse H. A randomized study of the effects of a home diabetes education program. Diabetes Care. 1986;9:173–8. doi: 10.2337/diacare.9.2.173. [DOI] [PubMed] [Google Scholar]
- 13.Schonlau M, Mangione-Smith R, Chan KS, et al. Evaluation of a quality improvement collaborative in asthma care: does it improve processes and outcomes of care? Ann Fam Med. 2005;3:200–8. doi: 10.1370/afm.269. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Rector TS, Venus PJ, Laine AJ. Impact of mailing information about nonurgent care on emergency department visits by Medicaid beneficiaries enrolled in managed care. Am J Manag Care. 1999;5:1505–12. [PubMed] [Google Scholar]
- 15.Hudec JC, MacDougall S, Rankin E. Advanced access appointments: effects on family physician satisfaction, physicians' office income, and emergency department use. Can Fam Phys. 2010;56:e361–7. [PMC free article] [PubMed] [Google Scholar]
- 16.O'Kelly FD, Teljeur C, Carter I, Plunkett PK. Impact of a GP cooperative on lower acuity emergency department attendances. Emerg Med J. 2010;27:770–3. doi: 10.1136/emj.2009.072686. [DOI] [PubMed] [Google Scholar]
- 17.van Uden CJ, Crebolder HF. Does setting up out of hours primary care cooperatives outside a hospital reduce demand for emergency care? Emerg Med J. 2004;21:722–3. doi: 10.1136/emj.2004.016071. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Wang C, Villar ME, Mulligan DA, Hansen T. Cost and utilization analysis of a pediatric emergency department diversion project. Pediatrics. 2005;116:1075–9. doi: 10.1542/peds.2004-2093. [DOI] [PubMed] [Google Scholar]
- 19.Rust G, Baltrus P, Ye J, et al. Presence of a community health center and uninsured emergency department visit rates in rural counties. J Rural Health. 2009;25:8–16. doi: 10.1111/j.1748-0361.2009.00193.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Solberg LI, Maciosek MV, Sperl-Hillen JM, et al. Does improved access to care affect utilization and costs for patients with chronic conditions? Am J Manag Care. 2004;10:717–22. [PubMed] [Google Scholar]
- 21.Solberg LI, Crain AL, Sperl-Hillen JM, Hroscikoski MC, Engebretson KI, O'Connor PJ. Effect of improved primary care access on quality of depression care. Ann Fam Med. 2006;4:69–74. doi: 10.1370/afm.426. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Chalder M, Sharp D, Moore L, Salisbury C. Impact of NHS walk-in centres on the workload of other local healthcare providers: time series analysis. Br Med J. 2003;326:532–4. doi: 10.1136/bmj.326.7388.532. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Philips H, Remmen R, Van Royen P, et al. What's the effect of the implementation of general practitioner cooperatives on caseload? Prospective intervention study on primary and secondary care. BMC Health Serv Res. 2010;10:222. doi: 10.1186/1472-6963-10-222. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Hsu RT, Lambert PC, Dixon-Woods M, Kurinczuk JJ. Effect of NHS walk-in centre on local primary healthcare services: before and after observational study. Br Med J. 2003;326:530–2. doi: 10.1136/bmj.326.7388.530. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Schaefer RA, Rea TD, Plorde M, Peiguss K, Goldberg P, Murray JA. An emergency medical services program of alternate destination of patient care. Prehosp Emerg Care. 2002;6:309–14. doi: 10.1080/10903120290938355. [DOI] [PubMed] [Google Scholar]
- 26.Snooks H, Foster T, Nicholl J. Results of an evaluation of the effectiveness of triage and direct transportation to minor injuries units by ambulance crews. Emerg Med J. 2004;21:105–11. doi: 10.1136/emj.2003.009050. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Badgett JT. Can Medicaid format alter emergency department utilization patterns? Pediatr Emerg Care. 1986;2:67–70. doi: 10.1097/00006565-198606000-00001. [DOI] [PubMed] [Google Scholar]
- 28.Catalano R, Libby A, Snowden L, Cuellar AE. The effect of capitated financing on mental health services for children and youth: the Colorado experience. Am J Public Health. 2000;90:1861–5. doi: 10.2105/ajph.90.12.1861. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Catalano RA, Coffman JM, Bloom JR, Ma Y, Kang SH. The impact of capitated financing on psychiatric emergency services. Psychiatric Serv. 2005;56:685–90. doi: 10.1176/appi.ps.56.6.685. [DOI] [PubMed] [Google Scholar]
- 30.Dickey B, Normand ST, Norton EC, Azeni H, Fisher W, Altaffer F. Managing the care of schizophrenia: lessons from a 4-year Massachusetts Medicaid study. Arch Gen Psychiatry. 1996;53:945–52. doi: 10.1001/archpsyc.1996.01830100095012. [DOI] [PubMed] [Google Scholar]
- 31.Franco SM, Mitchell CK, Buzon RM. Primary care physician access and gatekeeping: a key to reducing emergency department use. Clin Pediatr. 1997;36:63–8. doi: 10.1177/000992289703600201. [DOI] [PubMed] [Google Scholar]
- 32.Glazier RH, Klein-Geltink J, Kopp A, Sibley LM. Capitation and enhanced fee-for-service models for primary care reform: a population-based evaluation. CMAJ. 2009;180:E72–81. doi: 10.1503/cmaj.081316. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Hurley RE, Freund DA, Taylor DE. Emergency room use and primary care case management: evidence from four Medicaid demonstration programs. Am J Public Health. 1989;79:843–6. doi: 10.2105/ajph.79.7.843. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Josephson GW, Karcz A. The impact of physician economic incentives on admission rates of patients with ambulatory sensitive conditions: an analysis comparing two managed care structures and indemnity insurance. Am J Manag Care. 1997;3:49–56. [PubMed] [Google Scholar]
- 35.Murphy AW, Leonard C, Plunkett PK, et al. Effect of the introduction of a financial incentive for fee-paying A and E attenders to consult their general practitioner before attending the A and E department. Fam Pract. 1997;14:407–10. doi: 10.1093/fampra/14.5.407. [DOI] [PubMed] [Google Scholar]
- 36.Piehl MD, Clemens CJ, Joines JD. Narrowing the gap: decreasing emergency department use by children enrolled in the Medicaid program by improving access to primary care. Arch Pediatr Adolesc Med. 2000;154:791–5. doi: 10.1001/archpedi.154.8.791. [DOI] [PubMed] [Google Scholar]
- 37.Price MR, Norris JM, Bartleson BB, Gavin LA, Klinnert MD. An investigation of the medical care utilization of children with severe asthma according to their type of insurance. J Asthma. 1999;36:271–9. doi: 10.3109/02770909909075411. [DOI] [PubMed] [Google Scholar]
- 38.Schillinger D, Bibbins-Domingo K, Vranizan K, Bacchetti P, Luce JM, Bindman AB. Effects of primary care coordination on public hospital patients. J Gen Intern Med. 2000;15:329–36. doi: 10.1046/j.1525-1497.2000.07010.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Hsu J, Price M, Brand R, et al. Cost-sharing for emergency care and unfavorable clinical events: findings from the safety and financial ramifications of ED copayments study. Health Serv Res. 2006;41:1801–20. doi: 10.1111/j.1475-6773.2006.00562.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Lowe RA, Fu R, Gallia CA. Impact of policy changes on emergency department use by Medicaid enrollees in Oregon. Med Care. 2010;48:619–27. doi: 10.1097/MLR.0b013e3181dbddb1. [DOI] [PubMed] [Google Scholar]
- 41.O'Grady KF, Manning WG, Newhouse JP, Brook RH. The impact of cost sharing on emergency department use. N Engl J Med. 1985;313:484–90. doi: 10.1056/NEJM198508223130806. [DOI] [PubMed] [Google Scholar]
- 42.Selby JV, Fireman BH, Swain BE. Effect of a copayment on use of the emergency department in a health maintenance organization. N Engl J Med. 1996;334:635–41. doi: 10.1056/NEJM199603073341006. [DOI] [PubMed] [Google Scholar]
- 43.Wallace NT, McConnell KJ, Gallia CA, Smith JA. How effective are copayments in reducing expenditures for low-income adult Medicaid beneficiaries? Experience from the Oregon health plan. Health Serv Res. 2008;43:515–30. doi: 10.1111/j.1475-6773.2007.00824.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Wharam JF, Landon BE, Galbraith AA, Kleinman KP, Soumerai SB, Ross-Degnan D. Emergency department use and subsequent hospitalizations among members of a high-deductible health plan. J Am Med Assoc. 2007;297:1093–102. doi: 10.1001/jama.297.10.1093. [DOI] [PubMed] [Google Scholar]
- 45.Waters TM, Chang CF, Cecil WT, Kasteridis P, Mirvis D. Impact of high-deductible health plans on health care utilization and costs. Health Serv Res. 2011;46:155–72. doi: 10.1111/j.1475-6773.2010.01191.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Wilson AR, Bargman EP, Pederson D, et al. More preventive care, and fewer emergency room visits and prescription drugs--health care utilization in a consumer-driven health plan. Benefits Q. 2008;24:46–54. [PubMed] [Google Scholar]
- 47.Lowe RA, McConnell KJ, Vogt ME, Smith JA. Impact of Medicaid cutbacks on emergency department use: the Oregon experience. Ann Emerg Med. 2008;52:626–34. doi: 10.1016/j.annemergmed.2008.01.335. [DOI] [PubMed] [Google Scholar]
- 48.Mortensen K. Copayments did not reduce Medicaid enrollees' nonemergency use of emergency departments. Health Aff (Millwood) 2010;29:1643–50. doi: 10.1377/hlthaff.2009.0906. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.