 To assess whether Medicare patients’ reports of denied care, appeals/complaints, and satisfactory resolution were associated with ratings of their health plan or care.

 Retrospective analysis of 2010 Medicare Advantage Consumer Assessment of Healthcare Providers and Systems (CAHPS) survey data.

 Multivariate linear regression of data from 154,766 respondents (61.1% response rate) tested the association of beneficiary ratings of plan and care with beneficiary reports of denied care, appeals, complaints, and complaint resolution, adjusting for beneficiary demographics.

 Beneficiaries who reported being denied needed care rated their plans and care significantly less positively, by 17.2 points (on a 100-point scale) and 9.1 points, respectively. Filing an appeal was not statistically significantly associated with further lower ratings. Beneficiaries who filed a complaint that was satisfactorily resolved gave slightly lower ratings of plans (—3.4 points) and care (–2.5 points) than those not filing a complaint (

 Lower ratings from patients reporting complaints and denied care may notably affect the overall 0-10 CAHPS ratings of Medicare Advantage plans. Our results suggest that beneficiaries may attribute the actions that lead to complaints or denials to plans more than to the care they received. Successful complaint resolution and utilization management review might eliminate most deficits associated with complaints and denied care, consistent with the service recovery paradox. High rates of complaints and denied care might identify areas that need improved utilization management review, customer service, and quality improvement. Among those reporting being denied care, filing an appeal was not associated with lower patient ratings of plan or care.

Patients who reported denials of needed care gave low ratings to their care, and especially their plan, regardless of whether they appealed the denial. Beneficiaries satisfied with complaint resolution provided only slightly lower ratings than those with no complaints.

Medicare beneficiaries may largely attribute the actions that lead to complaints or denials to their plans more than to the care they received.

Medicare plans should focus on successful complaint resolution, as it can substantially mitigate the low ratings patients give their plan that result from whatever motivated them to file a complaint.

Patients’ complaints about their health insurance plan and denials of care are important aspects of the patient experience. The extent to which specific care is necessary can be complex and contentious.

 Denials to cover care may reflect barriers to accessing needed care or appropriate curtailing of unnecessary care. Throughout this article, we will refer to a health plan’s decision to not cover care as “denial of care” as an imperfect shorthand for the patient’s report, recognizing that patients can choose to pay out-of-pocket or out-of-network for their care. Similarly, complaints about health insurance plans may indicate a misunderstanding, a lack of plan responsiveness, or appropriate voicing of patient concerns.

Managed care organizations have delivery systems that greatly influence interactions between physicians and patients.

 Their rules and restrictions on choice of providers, network coverage, review processes, preauthorization, and drug formularies may create conflicts with patients and providers. Through the denial and appeals process, patients, physicians, and health plans communicate and determine what care is medically necessary.

As required by CMS, all Medicare Advantage (MA) contracts (health plans) must provide beneficiaries a means to file a complaint or appeal a denial of coverage.

 Denied coverage for care may adversely affect MA enrollees’ perceptions of plans and care. Nineteen percent of 2010 Medicare beneficiary disenrollments were prompted by denials of coverage for medical services,

 and over one-third of callers to the Medicare Rights Center’s national helpline expressed difficulty managing coverage denials and appeals.

Health plans may benefit from how they respond to grievances, complaints, and service failures, known as service recovery.

 found that it is not the service failure that reduces customer ratings of their plan or care, but the service provider’s actions (ie, recovery) following the failure that matter. This phenomenon is the “service recovery paradox,” wherein those who complain and see their problems resolved by the offending organization may rate the organization higher than those who experience no problems.

Service recovery in healthcare differs from other settings, like retail, banking, restaurants, or hotels, because it may not be possible to “make things right” or “undo the situation” in healthcare. A service provider’s apology also could be construed as an admission of a mistake and become the basis for litigation.

 The few articles about healthcare service recovery in the literature primarily offer managerial suggestions to healthcare administrators rather than empirical evidence.

 One study of a single health management organization (HMO) found a strong positive relationship between satisfaction with the complaint handling process and overall satisfaction with the HMO.

In general, however, relatively little is known about how denials of coverage for needed care, subsequent appeals of the denied coverage or complaints, and resolution status affect a patient’s rating of their plan or care. The question remains whether patients attribute the denial or complaint to their plan or to their providers. These attributions may also differ by beneficiaries’ health status, given that a denial of care may have greater consequences for those in poor health or with multiple chronic conditions.

Previous research on patient complaints and plans’ reported denials of care has focused on whether a patient has negative or positive experiences with care coverage and identifying any contributing factors. For example, kidney transplant recipients’ interactions with their insurers

 suggest that patients have difficult interactions with insurers and limited skills in navigating insurance options, thereby curbing their access to needed medications and health services. More than one-third of Medicaid enrollees reported denials of care for their children in the previous year, with families of children with chronic conditions more likely to report a denial of care.

Among the few studies that have focused on patient complaints and plans’ reported denials of care, only 2 appear to examine the relationship between denial of care (whether it was appealed and its resolution) and the patient’s subsequent rating of their health plan or care. Denial of needed care was associated with lower ratings of health plan quality and significantly less trust in patients’ primary care physicians.

 Similarly, many patients who are denied authorization for emergency department (ED) care are dissatisfied with their health plan but still intend to return to the ED.

 These results follow Folger’s fairness theory,

 which states that judgments of fairness are related to people’s “would/could/should” reasoning about a decision by a powerful other. Fairness theory predicts that after being denied care, the patient, in assigning responsibility for the injustice, would choose the powerful other with the most “could” authority, here the health plan with authority over authorizations, not the care provider.

This article uses a nationally representative sample of MA enrollees to assess the relationship between patient-reported denials of care, appeals, complaints, and resolution and their association with overall patient ratings of plans and care. Information on plan disenrollment or health plan ratings prompted by coverage denials could be a valuable tool for consumers who need to select a plan or identify an important missed opportunity for Medicare and other health plans for service recovery with patients. Furthering understanding of complaints and reported denials of care is especially pertinent for Medicare recipients, whose average healthcare needs exceed those of the general population and who, in some cases, may have difficulty managing the complaint or appeal process due to age or infirmity.

In 2010, the MA Consumer Assessment of Healthcare Providers and Systems (CAHPS) survey provided a unique opportunity to study these issues, as it included items that asked about complaints and denial of care. Under the Affordable Care Act, patient experience measures from this survey play a role in the determination of quality bonus payments for MA plans.

This study used additional items from the 2010 MA CAHPS survey to assess the association of MA enrollee ratings of their plan and care with whether they reported a denial of needed care, appealed the denial, or filed a complaint, along with the resolution status of the complaint. We first established the extent to which MA beneficiaries reported filing complaints with their plans or being denied coverage for needed care. Then we tested whether those with complaints/denials provided lower ratings of their health plan or care. Based on fairness theory, we hypothesized that members would assign less blame to the care they received because caregivers did not have the power  (ie, “could” authority) to accept or deny the appeal. In contrast, health plan management did have the “could” authority, and so responsibility was attributed to health plans. Thus, plans received lower ratings. Next, we tested whether the patient ratings of their plan and care differed for those filing an appeal and those with successful resolution of an appeal. Based on the service recovery paradox, we hypothesized that members with successful resolution would rate their health plan nearly as high or even higher than those who experienced no problems. Finally, we tested whether those who are in poorer health rated their plans or care more negatively following denied coverage or complaints.

We used data from the 2010 MA CAHPS survey, which included items on complaints and denial of care. This survey was a mail survey of MA beneficiaries, with telephone follow-up on nonrespondents.

Our population of interest was MA enrollees 65 years or older, excluding those in US territories. The analysis was restricted to responding beneficiaries (61.1% response rate for this population), excluding the 6% not completing items about complaints or denial of care, which left 154,766 cases. We examined responses to the survey items listed in 

 and estimated health contract—level standard deviations of denial, appeal, complaint, and resolution responses as the square root of contract variance components.

Second, multivariate linear regression predicted the responses to 2 ratings (health plan and care) from the denial, appeal, complaint, and resolution responses and several covariates: gender, age, race/ethnicity, education, self-reported health and mental health status, Census division, self-reported chronic conditions, Patient Health Questionnaire-2 depression symptoms,

 current smoking status, functional limitations, proxy assistance, dual eligibility for Medicaid, Part D or MA only, Special Needs Plan status, and whether the respondent had a personal doctor. We ran 4 sets of regression analyses to calculate 1) population estimates, 2) within-contract estimates, 3) associations, and 4) differences in these associations. Data were weighted to account for the sample design and nonresponse.

not shown) assessed whether those with poorer health had a stronger negative association with plan ratings than those in better health via an interaction term between overall health status and denial of service. As the average associations were similar for those who did and did not subsequently file an appeal of the denied care, we combined these groups in this analysis.

Characteristics of the MA beneficiaries 65 years and older appear in 

. Forty-three percent were male, 72% were non-Hispanic white, and 26% were 80 years or older. Eighteen percent had a 4-year college degree, and 14% did not have Part D coverage through their MA plan.

Prevalence of Denials, Appeals, and Complaints 

 shows the prevalence of denials, appeals, and complaints. Six percent of respondents reported that their plan denied care or services they believed they needed. Among beneficiaries who reported a denial of needed care or services, 49% filed an appeal. Overall, 8% of respondents filed a complaint, 54% of whom indicated that their complaint was resolved to their satisfaction.

The contract-level standard deviation of satisfactory complaint resolution from a linear mixed model was 9.9%, suggesting that approximately two-thirds of health plans had rates of satisfactory complaint resolution between 44% and 64% (after accounting for sampling error) and that most contracts had a rate of satisfactory complaint resolution ranging from 34% to 74%. Complaints, which had a contract-level standard deviation of 3.8%, involved a variety of issues and did not necessarily concern denials of needed care. Contract-level standard deviations were 3.7% for reports of denial of care and 5.4% for appeals.

 show multivariate linear regressions results that tested the association of denials, appeals, complaints, and resolution with overall ratings of health plan and healthcare, adjusting for beneficiary health and demographic characteristics. Compared with models that only included case-mix characteristics (Model 1), the addition of either denials and appeals (Model 2) or complaints and resolution (Model 3) resulted in a significant increase in predictive power, as shown by the increased R

<.001 for all partial F tests). For both plan and care ratings, denials and appeals added slightly more predictive power than complaints and resolutions.

Compared with beneficiaries who did not report denials of care, those who reported denials gave significantly lower care and plan ratings, rating their care 8.2 points and their plan 17.0 points lower than others on 100-point scales (Table 4). Similarly, those who reported filing a complaint rated their care 5.2 points and their plan 11.2 points lower than others. When denials and complaints were entered together in a model, all results remained highly significant (

<.001), with slightly less magnitude, but still indicating significantly lower plan and care ratings among those who filed an appeal or complaint. This suggests that each factor affected plan and care ratings independently.

Among those who reported being denied needed care, both care and plan ratings were somewhat worse for those who did not appeal their denials (a reduction of 7.0 points for those who appealed vs 9.4 for those who did not; 

<.001) (Table 5). Complaints that were not resolved satisfactorily were associated with much worse ratings of plan and of care than those that were resolved satisfactorily. In Model 3, including only complaint/resolution (along with beneficiary characteristics), complaints with a satisfactory resolution had an average 3.8-point lower plan rating, whereas those without a satisfactory resolution had an average 20.2-point lower plan rating (

<.001 for each, as well as for the difference between them).

Although denials/appeals and complaints/resolution were strongly associated with both care and plan ratings, the differences were much greater for plan ratings (Table 5). The model predicting care ratings with both denials/appeals and complaints/resolution (Model 4) had an R

 36% higher than the model with case-mix adjustors alone (Model 1); for plan ratings, the increase was 179%. In those models (Model 4), appeals were associated with average differences of —5.0 points for care rating and –12.4 points for plan rating. Similarly, filing a complaint that was not resolved satisfactorily was associated with differences of –6.6 and –16.3 points, respectively.

The relationship between patients and their health plans is fundamental to high-quality care. The denial and appeals process offers patients, physicians, and health plans a means to communicate and determine what care is medically necessary. The complaint resolution process allows patients to voice their concerns about care and attempt a solution. Perceived denial of needed care and unresolved complaints can adversely affect patients’ attitudes and experiences with their health plan and care.

This study of MA beneficiaries 65 years and older found that 6% reported being denied care in the past 6 months compared with the 7% prevalence in an earlier study of a single HMO’s commercially insured population

 in the prior 12 months. We found that 48% of beneficiaries who reported being denied care filed an appeal and 9% registered a complaint; 54% of complaints were resolved satisfactorily.

Our results reinforce the earlier finding

 that patients reporting a denial of coverage rated their care substantially lower than other patients. We extended previous research by comparing those who reported being denied needed care with those who were denied care and appealed their denial. In addition, beneficiaries who filed a complaint that was satisfactorily resolved had only slightly lower ratings of their plan and care, whereas those who had a complaint that was not satisfactorily resolved had much lower ratings, especially of their plan. We found that although denials/appeals and complaints/resolution were strongly associated with lower care and plan ratings, the association was much stronger for plan ratings. Our findings partially support the service recovery paradox, in that plan ratings improve when there is an appeal after a denial and a resolution after a complaint.

Given the significantly stronger negative associations of denied care and complaints with plan ratings in our study, it appears that beneficiaries attribute nonresolution of a complaint or denial of care to their health plan and much less so to the care they received. Patients may perceive denials and unresolved complaints as a breach of faith by their health plan, rather than their provider. These results support the prediction of fairness theory that patients associate accountability to the health plan (not the care provider) of authority over the complaint or the denied care.

Given that most MA plans satisfactorily resolved only about half of their complaints, there may be substantial opportunity to improve patients’ overall health plan ratings and reduce disenrollment by focusing efforts on increasing the rate of satisfactory complaint resolution and thoroughness during utilization review. Greater transparency with patients about coverage decisions, criteria, and utilization review may help.

Our findings also highlight the value of complaint and appeal data for identifying opportunities to improve customer service and patient education on criteria used in coverage decisions. This information could aid MA and other health plans in service recovery with patients.

This study had several limitations. It was not designed to link Medicare CAHPS survey responses to actual Medicare health plan coverage decisions, so it was not possible to determine whether each patient’s report of a denial of coverage reflected a health plan decision. Patients reporting a health plan denial may have misinterpreted statements by their physicians or actions by their physicians’ group practice. We knew only that the patients believed they had experienced a denial of coverage. Our study provided no data on subsequent healthcare utilization or outcomes, and it was not intended to evaluate the legitimacy of the grounds on which the MA plan based its denials of coverage.

Although just under half of patients who reported being denied care filed an appeal, filing an appeal does not seem to reflect a beneficiary perception that the denial was particularly egregious, but may instead reflect the beneficiaries’ self-efficacy with respect to filing an appeal. Patients who file a complaint that is not resolved satisfactorily may continue to view their plan experiences negatively, more so than their care experiences, which may increase their risk of disenrollment.

 The most common reason for disenrollment in 2010, applying to one-fourth of MA disenrollments, was concerns or issues related to out-of-network providers and prompted by an acute episode of illness or diagnosis (most often cancer).

Although there may be unobserved differences associated with beneficiaries whose complaints are satisfactorily resolved and those whose complaints are not, our results suggest that improved complaint resolution might substantially improve the perceptions of patients whose initial experiences were sufficiently negative to motivate a complaint. Given that many beneficiaries may have equally negative experiences but do not file complaints, active outreach to patients to elicit concerns might identify additional opportunities to improve care and patient experiences.

RAND Corporation (DDQ, DJK, MNE), Santa Monica, CA; RAND Corporation (AMH, JWD), Pittsburgh, PA; Carnegie Mellon University (AMH), Pittsburgh, PA.

 Preparation of this manuscript was supported through a cooperative agreement from CMS (contract number HHSM-500-2005-00028I).

 The authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article. 

 Concept and design (DDQ, AMH, MNE); acquisition of data (MNE); analysis and interpretation of data (DDQ, AMH, JWD, DJK, MNE); drafting of the manuscript (DDQ, JWD, DJK, MNE); critical revision of the manuscript for important intellectual content (AMH, JWD, DJK, MNE); statistical analysis (AMH, DJK, MNE);  obtaining funding (MNE); administrative, technical, or logistic support (DDQ); and supervision (MNE).

Marc N. Elliott, PhD, RAND Corporation, 1776 Main St, Santa Monica, CA 90401-2138. Email: elliott@rand.org.

Articles

WEB EXCLUSIVE

Patient ratings of plans and care were lower among beneficiaries filing complaints or reporting denied care. Appeals did not further predict ratings, but successful complaint resolution did.

Patient-Reported Denials, Appeals, and Complaints: Associations With Overall Plan Ratings

 To describe the characteristics and outcomes of patients discharged from the emergency department (ED) by hospitalist physicians.

 Retrospective cohort study at a tertiary academic medical center.

 We used consultation Current Procedural Technology codes to identify patients discharged from the ED after referral for hospitalist admission from April 2011 to April 2014. We report patient demographics and primary diagnoses. Main outcome measures included return to the ED, hospitalization, or mortality, all within 30 days.

 There were 710 discharges from the ED for 670 patients referred for hospitalist admission; 21.7% returned to the ED, 12.3% were hospitalized, and 0.4% died within 30 days. Chest pain was the most common diagnosis (38.2%); 18.1% of these patients returned to the ED within 30 days. Patients with the following 3 diagnoses returned to the ED most frequently: sickle cell disease (82.4%), alcohol-related diagnoses (43.5%), and abdominal pain (35.7%). In multivariate analysis, abdominal pain (odds ratio [OR], 3.2; 

= .003) increased the odds of ED revisits, whereas syncope (OR, 0.23; 

= .049) reduced the odds. Chest pain reduced the odds of hospitalization (OR, 0.37; 

 A majority of patients discharged from the ED after referral for hospitalist admission did not return to the ED within 30 days, and the 30-day hospitalization rate was low. Our data suggest that hospitalists can safely aid patients by reducing the costs and adverse outcomes associated with unnecessary hospitalization.

Hospitalists are uniquely positioned to help avoid unnecessary admissions. Among 710 emergency department (ED) discharges for 670 patients referred for hospitalist admission:

Four of 5 patients did not return to the ED and 9 of 10 patients did not require hospitalization within 30 days.

Chest pain was the most common diagnosis.

Those with alcohol-related diagnoses, abdominal pain, and sickle cell disease with crisis were more likely to return to the ED, whereas those presenting with chest pain were less likely.

Those with Medicare and Medicaid were more likely to return to the ED compared with those who were privately insured.

There are approximately 136.3 million emergency department (ED) visits in the United States each year; 16.2 million of these visits result in a hospital admission.

 Hospitalization is expensive: The average cost per hospital stay in 2012 was $10,400

 and more than one-third of healthcare spending within the United States is attributable to hospital care.

 Hospitalization is also associated with potential harms. A 2013 study estimated that 7% of hospitalizations are associated with a “highly undesirable event.”

 Additionally, approximately 20% of hospitalized patients will experience an injury related to medical management within a month of discharge.

 Some authors argue that hospitalization itself has deleterious health consequences, an acquired transient condition of increased generalized health risk dubbed “posthospital syndrome.”

Unnecessary hospitalizations, therefore, expose patients to unnecessary costs and risks. Hospitalist physicians are well positioned to evaluate the need for admission for patients referred from the ED. Recent efforts have focused on finding safer and more efficient ways of caring for patients who come to the hospital through the ED

 and improving collaboration between ED physicians and hospitalists.

 However, the characteristics and outcomes of patients discharged from the ED after referral for admission have not yet been explored. In this report, we describe the demographics, diagnoses, and healthcare outcomes of patients discharged from the ED after referral for hospital admission at an academic medical center.

We conducted a retrospective cohort study at an 804-bed tertiary academic medical center, the University of North Carolina Hospitals. We received institutional review board approval for this study (UNC IRB #14-2559). The Division of Hospital Medicine at the University of North Carolina School of Medicine is responsible for approximately 25% of all patients admitted through the ED. Occasionally, ED patients referred for admission are evaluated by a hospitalist physician and deemed safe for discharge without hospitalization. The consulting hospitalist assumes responsibility for providing discharge instructions, documentation of a consult note, and any necessary follow-up arrangements and prescription medications.

Consults performed in the ED by hospital medicine physicians over the 3-year period between April 1, 2011, and April 1, 2014, were identified via Current Procedural Terminology consult codes 99241 through 99245 and 99281 through 99285. One investigator reviewed the medical record of each patient to ensure accuracy of the data. Patients were included if they were: 1) referred for admission to our hospital medicine group or general medical teaching service with a hospitalist attending and 2) were discharged from the ED after medical consultation. We excluded patients who were admitted to any hospital service after the index consultation.

We collected demographic data, including age, race, sex, and type of insurance. Primary and secondary diagnoses were identified using 

International Classification of Diseases, Ninth Revision

) codes assigned to the index consultation. All diagnoses were categorized into common or related diagnosis groups (eg, all 

The primary outcome measures were rates of return to the ED within 30 days, hospitalization within 30 days, and mortality within 30 days of an index consultation. Mortality data were verified for each patient by manual chart review and via search of the US Social Security Death Index, which contains mortality data through February 28, 2014, due to record availability and legislative ruling.

Rates of ED returns, hospitalizations, and mortality within 30 days were calculated as percentages for all patients, as well as for the 6 most common diagnosis groupings. Unadjusted and adjusted analyses (using multivariate logistic regression) were used to describe demographic (age, gender, race/ethnicity, and insurance type) and clinical (diagnosis at index consult) predictors of return to the ED and hospitalization within 30 days after the index consult. Statistical calculations were performed using Stata/SE 13.1 (StataCorp; College Station, Texas).

There were 710 patient encounters identified during the study period for 670 unique patients (

]). The mean age was 52.1 years. More than half of the patients (61.0%) were white, and almost 30% were black. Approximately 75% of the patients had some form of insurance, with Medicare making up the largest single insurance type.

There were 178 diagnoses. The most common diagnosis was unspecified chest pain (34.1%), followed by unspecified abdominal pain (9.0%). The 6 most common diagnosis groups, shown in 

, made up 68.2% of the total patient encounters analyzed. After categorization, chest pain was the largest diagnosis group (38.2%).

Of all patient encounters in the study, 21.7% returned to the ED within 30 days of the index consultation. For the patient encounters with chest pain, 18.1% returned to the ED within 30 days. There was large variability in the 30-day revisit rates based on diagnosis (Table 1). The 3 diagnosis groups that returned to the ED most frequently were sickle cell disease with crisis, alcohol-related diagnoses, and abdominal pain. These diagnoses made up 18.7% of the total cohort of patient encounters evaluated.

), a diagnosis of abdominal pain (odds ratio [OR], 3.23; 95% CI, 1.75-5.94) or alcohol-related diagnoses (OR, 3.10; 95% CI, 1.49-6.45) increased the likelihood of return to the ED within 30 days. Syncope (OR, 0.23; 95% CI, 0.05-0.99) decreased that likelihood. Among insurance types, patients with Medicaid had the highest likelihood of returning to the ED within 30 days (OR, 4.54; 95% CI, 2.27-9.49). Patients with private insurance and other forms of healthcare coverage (ie, liability, TRICARE, worker’s compensation) were least likely.

We found that 12.3% of all patients were hospitalized within 30 days (Table 1). Of those who initially presented with chest pain, 6.3% were hospitalized within 30 days, including 1 (0.1%) who returned to the hospital with an ST-segment elevation myocardial infarction (STEMI); the patient was successfully treated and had an uncomplicated hospital course. In adjusted analysis (Table 2), patients with chest pain had a reduced likelihood of hospitalization (OR, 0.37; 95% CI, 0.19-0.74). Similar to the ED revisit results, the patients most frequently hospitalized within 30 days were initially diagnosed with sickle cell disease with crisis, alcohol-related diagnoses, and abdominal pain. In addition, patients with Medicaid had the highest likelihood of hospitalization among insurance types (OR, 3.94; 95% CI, 1.59-9.74).

Of all patients evaluated, 3 (0.4%) died within 30 days of an index consultation. Two of the patients were receiving hospice care, one with a diagnosis of terminal metastatic bladder cancer and the other with terminal metastatic prostate cancer. The third patient was diagnosed with pneumonia and ultimately found to have progressive renal cell carcinoma.

Our study found that the majority of patients discharged from the ED after referral for hospitalist admission did not have subsequent acute healthcare utilization, with 4 of 5 patients avoiding an ED return visit and 9 of 10 patients avoiding hospitalization within 30 days. These numbers were similar to our ED’s 30-day revisit rate, which was slightly less than 20% at the beginning of 2016, and our own hospital medicine group’s readmission rate, which was around 10% during the time period of our study. The 30-day ED revisit rate for our study was likely slightly higher than our ED’s 30-day revisit rate due to the higher proportion of patients with sickle cell disease and alcohol-related diagnoses that the ED asks our hospitalists to evaluate for admission. Mortality for this cohort, identified via manual record review for all patients and the US Social Security Death Index for the majority, was well below 1%. Given the known harms associated with hospitalization, these results suggest that hospitalist physicians are able to safely benefit patients and the healthcare system by identifying unnecessary hospitalizations.

Patients with chest pain made up the largest diagnosis grouping, and these patients returned to the ED with the same frequency as the entire cohort. Recent literature has shown that the risk of having a cardiac event after a negative ED evaluation for cardiac chest pain is extremely low. For example, the HEART Pathway, a prospectively validated study that combined the HEART risk stratification score with serial cardiac biomarker testing at 0 and 3 hours, identified a large group of patients presenting to the ED who were at very low risk (~1%) of having a major adverse cardiac event within 30 days.

 In our study, although there was 1 patient who initially presented with chest pain and had a nonfatal STEMI within 30 days, those who presented with chest pain had reduced odds of hospitalization within 30 days of an index consultation compared with the rest of the cohort. Admission for further risk stratification with a stress test for low-risk patients has not been shown to confer greater benefit and does not identify preventable bad outcomes.

We identified several diagnoses with a higher risk of return to the ED: alcohol-related diagnoses, abdominal pain, and sickle cell disease with crisis. Two of these groups, patients with alcohol-related diagnoses and sickle cell disease, are known to have high rates of healthcare utilization, especially those covered by Medicaid.

 Our hospitalist group has published clinical protocols for evaluating and caring for both of these groups of patients.

 In this study, patients presenting with alcohol-related diagnoses and abdominal pain had more than 3 times the odds of returning to the ED within 30 days compared with the entire cohort. We suspect that sickle cell disease with crisis also likely conveys a higher risk of return to the ED, although the total number of patient encounters was low and the adjusted OR did not reach statistical significance.

There was substantial variation in the likelihood of healthcare utilization within 30 days of the index consultation based on insurance type. Patients with Medicaid had more than 4 times the odds of returning to the ED within 30 days and nearly 4 times the odds of hospitalization within 30 days compared with patients with private insurance. Patients with Medicare or no health insurance had more than twice the odds of returning to the ED within 30 days compared with patients who had private insurance. This may reflect the trend noted over the past 10 years in which the ED has acted as a safety net for medically underserved patients, specifically those patients with Medicaid.

 High repeat utilization in these patients could also be due to other factors, such as higher rates of chronic illness, especially in those patients with Medicare.

Mortality within 30 days of an index consultation was well below 1%, and all patients who died carried a diagnosis of malignancy. Two of the patients who died had terminal malignancies and, upon chart review, were receiving palliative care and were expected to die within weeks of their ED encounter and evaluation by a hospitalist. The third patient had a newly diagnosed renal cell carcinoma, and the patient and family focused on quality-of-life measures after discharge. Although it may be reasonable to hospitalize patients at the end of life with high care needs, many patients and families prefer to avoid hospitalization in this setting if possible.

Although our data were limited to a single tertiary academic medical center ED, the patients we identified had many characteristics similar to those identified by national survey data of ED patients in the United States. For example, the majority of our patients were white (61.0%) and female (52.5%), comparable to national data of 72.0% and 54.7%, respectively. Similarly, chest pain was one of the most frequent presenting complaints among adult patients admitted to the ED nationally, matching our cohort.

 Because our data were limited to a single center, we were unable to determine how frequently patients were seen at other institutions after discharge from our ED. We also did not have a clear way of knowing if patients were initially evaluated at another ED prior to our index consult. It is possible that we did not account for all patient deaths, although our manual chart review supplemented by use of a national database (complete through all but the final month of our study) makes this unlikely. In terms of the diagnosis groupings, they were organized based on primary 

 codes for a single primary and a single secondary diagnosis, and so we may have missed some other associated health conditions. We had some smaller diagnosis groupings with frequent encounters by the same patients (ie, sickle cell disease), which thus may not have provided an accurate or sufficient representation for those diagnoses. The final limitation of our study is that it was not designed with a control group of patients whom hospitalist consultants decided to admit to the hospital. Future studies should compare characteristics of patients discharged home by hospitalist consultants with patients admitted to the hospital. The comparison could be used to develop risk scores based on patient characteristics that facilitate standardized evidence-based risk stratification for safe discharge from the ED.

Our study adds to the literature by describing the characteristics of patients discharged from the ED after referral for hospitalist admission. Given the overall low rates of subsequent healthcare utilization for these patients, there are substantial opportunities for improved care and cost savings with this practice if applied at other institutions. In 2012, Medicare paid an average of $1741 per hospital observation stay.

 If we extrapolate this cost to our patients who were not admitted to this hospital within 30 days, we could have avoided over $1 million in healthcare spending during the 3-year study period. These figures do not take into account the 20% of cost the patient would be responsible for, expenses not covered by Medicare Part B, or the potential cost of harm to the patient during a short hospital stay.

Areas for potential future study include the development of a prediction tool that could help to inform decisions about discharging patients referred for admission. This may lead to the creation of a standardized approach, improving 30-day outcomes by optimizing who is selected for discharge. Ultimately, understanding the characteristics of this population will provide hospitalists a better approach to caring for these patients and their disease process.&ensp;

The authors would like to thank Loretta Fearrington of the North Carolina Translational and Clinical Sciences Institute and Scott Keller of the University of North Carolina Department of Medicine for their assistance in the planning and conduct of this study.

 Division of Hospital Medicine (CAC, JS, ZS, CM, EAL), and North Carolina TraCS Institute (JPL), and Division of General Medicine and Clinical Epidemiology (DEJ), University of North Carolina, Chapel Hill, NC.

 Statistical analysis was provided by North Carolina Translational and Clinical Sciences Institute (NC TraCS), which is supported by the National Center for Advancing Translational Sciences (NCATS), National Institutes of Health, through Grant Award Number UL1TR001111. There were no other sources of funding.

 The authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

 Concept and design (CAC, JS, DEJ, EAL); acquisition of data (CAC, JS, ZS, EAL); analysis and interpretation of data (CAC, JS, ZS, JPL, CM, DEJ, EAL); drafting of the manuscript (CAC, JS, ZS, JPL, EAL); critical revision of the manuscript for important intellectual content (CAC, JS, CM, DEJ, EAL); statistical analysis (JPL, CM); and administrative, technical, or logistic support (CAC, EAL).

 Christopher A. Caulfield, MD, University of North Carolina School of Medicine, 101 Manning Dr, CB #7085, Chapel Hill, NC 27599-7085. Email: ccaulfie@med.unc.edu.

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2. Weiss AJ, Elixhauser A. Overview of hospital stays in the united states, 2012 [HCUP statistical brief #180]. Healthcare Cost and Utilization Project website. hcup-us.ahrq.gov/reports/statbriefs/sb180-Hospitalizations-United-States-2012.pdf. Published October 2014. Accessed October 7, 2015.

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. 2013;35(5):20-31. doi: 10.1111/jhq.12027.

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TRENDS FROM THE FIELD

Hospitalization is costly and associated with the potential for adverse medical events. Hospitalists are uniquely positioned to help avoid unnecessary emergency department admissions through consultation.

Patients Discharged From the Emergency Department After Referral for Hospitalist Admission

A substantial portion of healthcare spending is wasted on services that do not directly improve patient health and that cause harm in some cases. Features of health insurance coverage, including enrollment in high-deductible health plans (HDHPs) or health maintenance organizations (HMOs), may provide financial and nonfinancial mechanisms to potentially reduce overuse of low-value healthcare services.

 Using 2009 to 2013 administrative data from 3 large commercial insurers, we examined patient characteristics and health insurance plan types associated with overuse of 6 healthcare services identified by the Choosing Wisely campaign.

We explored associations between overuse and patient characteristics using multivariate logistic regression models, including patient age, gender, enrollment in an HMO, enrollment in an HDHP, an indicator of primary care fragmentation, and number of outpatient visits as explanatory variables.

Measurement of services highlighted as potential overuse by the Choosing Wisely recommendations revealed low to moderate prevalence, depending on the service. HMO coverage and enrollment in HDHPs were significantly associated with differences in prevalence of all 6 services, albeit differently in terms of the direction of the effects. Primary care fragmentation was significantly associated with higher rates of overuse.

Neither HDHPs nor HMO plans, with their closed networks and referral requirements, consistently reduced overuse, although HMO plans were never associated with higher rates of overuse. As policy makers seek levers for reducing low-value healthcare utilization, health insurance plan features may prove a valuable target, although the effect may be complicated by other factors.

We found low to moderate overuse of 6 low-value health services among patients with commercial insurance.

Health insurance plan type, including enrollment in a health maintenance organization or high-deductible health plan, was significantly associated with differences in prevalence of all 6 services.

Primary care fragmentation was significantly associated with higher rates of overuse.

Health insurance plan features should be considered alongside more targeted mechanisms, like preauthorization and value-based cost sharing, to influence overuse of these low-value services.

Driven by the urgency to achieve affordable healthcare for more Americans, many policy experts are focusing on defining, identifying, and reducing waste in healthcare. Some policy makers and researchers suggest that generous insurance coverage may prompt patients to demand more testing and interventions than they otherwise would, leading to overuse of services. To the extent this is occurring, health insurance plan type, which can include cost-sharing schemes or utilization management, may reduce waste by curbing demand-driven use of low-value services. To begin addressing this issue, the American Board of Internal Medicine Foundation launched the Choosing Wisely campaign in 2012, an initiative aimed at reducing unnecessary use of healthcare services. More than 80 specialty societies created lists of low-value services,

 and the campaign was associated with modest decreases in some services.

The potential impact of health insurance plan type and, more specifically, high-deductible health plans (HDHPs) on minimizing waste remains inconclusive. HDHPs have high levels of initial cost sharing until the deductible is met, potentially reducing inappropriate use by making consumers more sensitive to the prices of healthcare services. Shifts in the employer-sponsored insurance landscape indicate a gradual increase in the number of firms offering and number of employees enrolling in HDHPs in the past 5 years.

 It is thus increasingly important to understand the relationship between health insurance plan type and overuse of care.

Although evidence on the long-term effect of HDHPs on overuse is limited, some results of studies examining the short-term effects on utilization and spending suggest that HDHPs may reduce outpatient visits, out-of-pocket (OOP) spending, and emergency department use.

 Others have found that HDHPs do not affect utilization of laboratory tests or acute care visits and that decreases in utilization are temporary as the patient transitions to a new plan with higher levels of cost sharing.

 The evidence on high deductibles and cost sharing suggests that consumers have difficulty differentiating high- and low-value care; this often requires physician judgment.

 Studies also reveal variation in patient adherence to providers’ medical advice and suggest that adherence can be influenced by several patient factors, including age, gender, and patient—provider relationship.

Health maintenance organizations (HMOs) are thought to reduce overuse by requiring patients to select a primary care provider (PCP), from whom a referral is required in order to see a specialist, who must be part of the plan’s network.

 These plans may steer patients away from providers with high rates of low-value service use through limited networks. There may also be financial and nonfinancial mechanisms, such as preauthorization or utilization review, that discourage physicians from ordering low-value services.

Little is known about trends in overuse for adults with private insurance, although evidence is mounting on the prevalence of and variation in overuse in the Medicare population.

 Most studies describing overuse of low-value care among the privately insured have focused on pediatric populations or assessed overuse in a single insurer or state.

 With renewed interest and professional engagement in naming and addressing low-value services, policy makers and payers need evidence on which tools and levers reduce overuse.

We examined cross-sectional data from a large commercially insured population to describe trends in overuse of low-value care between 2009 and 2013 and to capture the association among patient characteristics, health insurance plan type, and the use of 6 low-value services.

We obtained commercial insurance claims data from the Health Care Cost Institute (HCCI) for patients with employer-sponsored health insurance coverage from 2009 to 2013. This dataset includes commercial data from 3 large insurers: Aetna, Humana, and UnitedHealthcare. Across all years, the data reflect the healthcare claims of approximately 45 million adults aged 18 to 64 years. HCCI estimates that these claims data account for about 26% of adults younger than 65 years with employer-sponsored insurance in the United States.

Selecting Choosing Wisely Services for Measurement

We developed claims-based algorithms for 6 services, representing 22 Choosing Wisely recommendations. We selected recommendations for analysis based on: 1) the feasibility of measuring the service and manner of use in claims data only, 2) the expected denominator size, and 3) our desire to study services that vary broadly in cost and represent diverse segments of healthcare. The Choosing Wisely services excluded from analysis were either difficult to measure in claims data or pertained to a very small percentage of the commercially insured population. We studied nonindicated use of the following: imaging early in the course of new back pain, vitamin D deficiency screening for low-risk patients, prescription opioids for migraine, cardiac testing in low-risk patients, short-interval bone densitometry (DEXA), and preoperative cardiac testing in low-risk patients ahead of low-risk (noncardiac) surgery.

Construction of Measure-Specific Cohorts at Risk

) and Current Procedural Terminology codes to construct cohorts at risk for 6 Choosing Wisely services and to identify health service events highlighted by the Choosing Wisely recommendations. In the 

), we describe the measure and event definitions. We used HCCI pharmacy claims data, where applicable, for cohort inclusion/exclusion and to identify Choosing Wisely prescription service events. In all cases, we conservatively excluded beneficiaries not targeted by the Choosing Wisely recommendation. We limited our analysis to nonindicated tests and procedures, excluding services with claims diagnoses that suggested appropriate medical indication. When possible, we drew from published validated claims-based measures and conducted sensitivity analyses to optimize the measure construct. Although we used 2009 to 2013 data for the analyses, some measures were limited to smaller time windows to permit sufficient look-back periods within the data to identify, for example, prevalent disease states.

Multivariate logistic models with hospital referral region (HRR) fixed effects were fitted to analyze the factors associated with overuse at the patient level. To identify the association between overuse of low-value care and each insurance plan type, we created several binary indicator variables. Included in the model were an indicator for enrollment in an HMO plan (compared with all other plan types, of which the majority were point-of-service [POS] plans, exclusive provider organizations [EPOs], or preferred provider organization [PPO] models) and an indicator for an HDHP. We also included an indicator for patients with administrative services only (ASO) plans, which are arrangements where an employer contracts with an organization to deliver administrative services, like claims processing, for its self-funded health insurance program. The indicator for ASO plans may pick up the effects of either or both characteristics of these plans and the patients who are enrolled in them compared with fully insured plans that are not captured by the network type and HDHP indicator. We also included the patient’s age, gender, and health status as explanatory variables. We hypothesized that patients with more contact with the health system overall, which we captured as the number of outpatient visits during the study year, would have more opportunities for overuse. Finally, we included the number of unique PCPs seen during the study period as an indicator of the fragmentation of primary care, which may also be a risk factor for low-value care receipt. We included year indicators in the model to allow for changes over time.

The study was approved by the institutional review board at the Harvard T.H. Chan School of Public Health.

Age and gender differences were consistent with the clinical circumstances of the featured tests and treatments (

). Patients in our sample were enrolled in health insurance products that varied by managed care structure and cost sharing: 8.5% to 15.3% of patients in each measure sample were enrolled in an HMO and 14.1% to 17.2% were enrolled in an HDHP.

Rates of overuse ranged from a low of 6.8% for short-interval DEXA testing to a high of 28.1% for preoperative cardiac testing (Table 1). Two of 6 measures revealed a downward trend in overuse in 2009, 2010, 2011, and 2012: prescription opioids for migraine and preoperative cardiac testing. We observed monotonically increasing overuse of vitamin D deficiency screening from 2009 through 2013. In multivariate analyses controlling for region and individual characteristics for each of the 6 measures, health insurance plan type was associated with overuse (

). HMO enrollment was associated with significantly less overuse of imaging for low back pain (odds ratio [OR], 0.880; 95% CI, 0.870-0.890), vitamin D deficiency screening (OR, 0.606; 95% CI, 0.604-0.607), cardiac testing (OR, 0.962; 95% CI, 0.959-0.965), and preoperative cardiac testing (OR, 0.937; 95% CI, 0.923-0.951). The association between having an HDHP and overuse differed by measure (

); those enrolled in HDHPs had slightly but significantly lower odds of overuse of imaging for low back pain (OR, 0.987; 95% CI, 0.979-0.995), prescription opioids for migraine (OR, 0.960; 95% CI, 0.943-0.980), and short-interval DEXA (OR, 0.946; 95% CI, 0.930-0.963). In contrast, enrollment in HDHPs was significantly associated with greater odds of overuse of vitamin D deficiency screening (OR, 1.036; 95% CI, 1.034-1.038) and preoperative cardiac testing (OR, 1.012; 95% CI, 1.001-1.023). Relative to those who were fully insured, having an ASO plan was associated with slightly but significantly greater odds of imaging for low back pain (OR, 1.010; 95% CI, 1.003-1.021), cardiac testing (OR, 1.020, 95% CI, 1.017-1.022), short-interval DEXA (OR, 1.301; 95% CI, 1.278-1.324), and preoperative cardiac testing (OR, 1.015; 95% CI, 1.005-1.025).

Compared with those with 3 or more PCPs, patients cared for by 1 or 2 PCPs had significantly lower odds of overuse for 4 of 6 measures: vitamin D deficiency screening, prescription opioids for migraine, cardiac testing, and short-interval DEXA.

Our findings suggest that overuse is widespread among commercially insured patients and, despite the availability of utilization management and higher cost sharing, comparable with rates found in

previous studies of the Medicare population.

 For nearly every service we studied, patient characteristics and health insurance plan type were significant predictors of overuse. Fragmentation of primary care, in particular, was associated with significantly more overuse for most measures. This finding is consistent with previous work suggesting that care continuity may play a role in reducing overuse and is perhaps attributable to patient—provider trust and communication.

 Current efforts to redesign primary care delivery, many of which prioritize care continuity, may play a role in reducing overuse.

All of the health insurance plan types studied (HMO, HDHP, or ASO) were associated with significant differences in overuse compared with EPOs, PPOs, or POS plans. However, the direction of the association differed across the set of 6 services studied. Focusing specifically on the role of HMO and HDHP enrollment in informing interventions to reduce waste, we found that these factors were important explanatory variables (based on statistical significance), but their association with overuse was inconsistent and warrants further investigation. Further insights on the causal effects of health insurance plan type could be derived from analyzing an exogenous source of variation in cost sharing or plan structure, such as when an employer switches plan offerings. From the standpoint of intervention, payers might do more to target cost sharing and other policies explicitly to address overuse, rather than put downward pressure on all nonpreventive healthcare utilization as in an HDHP. Although relying on higher cost sharing may achieve reductions in spending, it carries risks, and co-payment amounts and deductible sizes should be set carefully.

 Findings of several studies have shown that high deductibles may encourage individuals, particularly of lower income or with multiple chronic conditions, to forego essential medical care.

As a result, health insurance plan type should be considered alongside other policies and interventions to address overuse of low-value services.

Interpretation of our findings on ASO plans may reflect a complicated mix of both plan and population differences. A 2011 report to Congress indicated that there are small differences in coverage generosity when comparing self-insured and fully insured employer plans, which may affect the use of low-value care. Among HMO plans, for example, OOP payments are higher for self-insured plans relative to fully insured plans. Further, the report found that employers with low-risk employees are more likely to self-insure, resulting in different risk profiles between otherwise identical ASO and fully insured plans.

Our analysis had a number of limitations. We relied on administrative data with limited information on plan benefits and design to identify and describe the use of low-value services. Although we used conservative definitions and exclusion criteria to minimize misclassification risk, claims may not provide enough information or clinical detail to precisely identify low-value care. We were unable to include other measures of benefit design, such as co-payment amounts or OOP maximums. We proxied for these characteristics using insurance plan type. Second, although we aimed to include Choosing Wisely recommendations on lists from multiple specialty societies and services ordered by both specialists and PCPs, the range of services measured was narrow. Lack of variation in demographics or other patient-level factors may have impacted our results. Previous studies have found heterogeneity in nonelderly adults with private insurance; however, we do not think this focus will eliminate variation in our sample.

 Our model did not control for supply-side factors other than by controlling for region using HRR indicators. Finally, our analysis of factors associated with overuse was cross-sectional in nature and cannot be used to make definitive causal inferences. Low pseudo-R

 values are common in cross-sectional analyses with limited explanatory variables.

As clinicians and other experts expand our understanding of low-value health services, payers and policy makers are looking for tactics to influence the use of these services while maintaining access to effective care. For privately insured patients, such as the subjects of our analysis, health insurance plan type might be expected to affect the value of care received. Our work shows that HDHPs do not consistently reduce overuse, nor do HMO plans that typically have closed networks and referral requirements (although HMO plans were never associated with higher degrees of overuse). Contrary to the popular belief that patients need more cost sharing to internalize the value of healthcare services, our study plans with lower cost sharing were not consistently associated with higher use of low-value services. More targeted demand-side mechanisms (eg, value-based cost sharing) or stringent supply-side mechanisms (eg, preauthorization or risk bearing by providers) may be warranted to address the use of low-value care.&ensp;

The authors acknowledge the assistance of the Health Care Cost Institute (HCCI) and its data contributors, Aetna, Humana, and UnitedHealthcare, in providing the claims data analyzed in this study, as well as funding support from The Peterson Center on Healthcare. 

Department of Health Policy and Management, Harvard T.H. Chan School of Public Health (MBR, ZL, KHN), Boston, MA; The Dartmouth Institute for Health Policy and Clinical Practice (CHC, NEM, AJM), Lebanon, NH; Norris Cotton Cancer Center, Dartmouth-Hitchcock Medical Center (CHC), Lebanon, NH; Department of Community and Family Medicine, Geisel School of Medicine at Dartmouth (NEM), Lebanon, NH; Department of Health Care Policy, Harvard Medical School (TDS), Boston, MA; Division of General Internal Medicine, Brigham and Women’s Hospital (TDS), Boston, MA; Partners HealthCare (TDS), Boston, MA.

 Funding for this study was provided by The Peterson Center on Healthcare.

 Concept and design (MBR, CHC, NEM, TDS, AJM, ZL); acquisition of data (MBR, ZL); analysis and interpretation of data (MBR, CHC, NEM, TDS, ZL); drafting of the manuscript (MBR, CHC, NEM, KHN); critical revision of the manuscript for important intellectual content (MBR, CHC, NEM, TDS, AJM, KHN); statistical analysis (MBR, CHC, ZL); obtaining funding (MBR, CHC); administrative, technical, or logistic support (CHC, AJM, KHN); and supervision (MBR).

 Meredith B. Rosenthal, PhD, Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA 02215. Email: mrosenth@hsph.harvard.edu.

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Health insurance plan type may be an important lever for reducing low-value healthcare use among patients with commercial insurance.

March 2018

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