The Effects of Medicaid Eligibility on Mental Health Services and Out‐of‐Pocket Spending for Mental Health Services

Objective

Millions of low‐income Americans will gain health insurance through Medicaid under the Affordable Care Act. This study assesses the impact of previous Medicaid expansions on mental health services utilization and out‐of‐pocket spending.

Data Sources

Secondary data from the 1998–2011 Medical Expenditure Panel Survey Household Component merged with National Health Interview Survey and state Medicaid eligibility rules data.

Study Design

Instrumental variables regression models were used to estimate the impact of expanded Medicaid eligibility on health insurance coverage, mental health services utilization, and out‐of‐pocket spending for mental health services.

Data Extraction Methods

Person‐year files were constructed including adults ages 21–64 under 300 percent of the Federal Poverty Level.

Principal Findings

Medicaid expansions significantly increased health insurance coverage and reduced out‐of‐pocket spending on mental health services for low‐income adults. Effects of expanded Medicaid eligibility on out‐of‐pocket spending were strongest for adults with psychological distress. Expanding Medicaid eligibility did not significantly increase the use of mental health services.

Conclusions

Previous Medicaid eligibility expansions did not substantially increase mental health service utilization, but they did reduce out‐of‐pocket mental health care spending.     

Physical Therapy or Advanced Imaging as First Management Strategy Following a New Consultation for Low Back Pain in Primary Care: Associations with Future Health Care Utilization and Charges

Objective

Compare health care utilization and charges for low‐back‐pain (LBP) patients receiving advanced imaging or physical therapy as a first management strategy following a new primary care consultation.

Data Source

Electronic medical record (EMR) and insurance claims data.

Study Design

Retrospective analysis of propensity‐matched groups.

Data Collection/Extraction

Claims and EMR data were used. Utilization and LBP‐related charges over a 1‐year period were extracted from claims data.

Principal Findings

In the propensity‐matched sample (n = 406), advanced imaging recipients had higher odds of all utilization outcomes. Charges were higher with advanced imaging by an average $4,793 (95 percent CI: $3,676, $5,910).

Conclusions

For patients with LBP whom newly consulted primary care referred for additional management, advanced imaging as a first management was associated with higher health care utilization and charges than physical therapy.     

Reforming Access: Trends in Medicaid Enrollment for New Medicare Beneficiaries, 2008–2011

Objective

To evaluate whether aligning the Part D low‐income subsidy and Medicaid program enrollment pathways in 2010 increased Medicaid participation among new Medicare beneficiaries.

Data Sources

Medicare enrollment records for years 2007–2011.

Study Design

We used a multinomial logistic model with state fixed effects to examine the annual change in limited and full Medicaid enrollment among new Medicare beneficiaries for 2 years before and after the reforms (2008–2011).

Data Extraction Methods

We identified new Medicare beneficiaries in the years 2008–2011 and their participation in Medicaid based on Medicare enrollment records.

Principal Findings

The percentage of beneficiaries enrolling in limited Medicaid at the start of Medicare coverage increased in 2010 by 0.3 percentage points for individuals aging into Medicare and by 1.3 percentage points for those qualifying due to disability (p < .001). There was no significant difference in the size of enrollment increases between states with and without concurrent limited Medicaid eligibility expansions.

Conclusions

Our findings suggest that streamlining financial assistance programs may improve Medicare beneficiaries’ access to benefits.     

Financial Strain and Medication Adherence among Diabetes Patients in an Integrated Health Care Delivery System: The Diabetes Study of Northern California (DISTANCE)

Objective

To examine self‐reported financial strain in relation to pharmacy utilization adherence data.

Data Sources/Study Setting

Survey, administrative, and electronic medical data from Kaiser Permanente Northern California.

Study Design

Retrospective cohort design (2006, n = 7,773).

Data Collection/Extraction Methods

We compared survey self‐reports of general and medication‐specific financial strain to three adherence outcomes from pharmacy records, specifying adjusted generalized linear regression models.

Principal Findings

Eight percent and 9 percent reported general and medication‐specific financial strain. In adjusted models, general strain was significantly associated with primary nonadherence (RR = 1.37; 95 percent CI: 1.04–1.81) and refilling late (RR = 1.34; 95 percent CI: 1.07–1.66); and medication‐specific strain was associated with primary nonadherence (RR = 1.42, 95 percent CI: 1.09–1.84).

Conclusions

Simple, minimally intrusive questions could be used to identify patients at risk of poor adherence due to financial barriers.     

Benchmarking Outpatient Rehabilitation Clinics Using Functional Status Outcomes

Objective

To utilize functional status (FS) outcomes to benchmark outpatient therapy clinics.

Data Sources

Outpatient therapy data from clinics using Focus on Therapeutic Outcomes (FOTO) assessments.

Study Design

Retrospective analysis of 538 clinics, involving 2,040 therapists and 90,392 patients admitted July 2006–June 2008. FS at discharge was modeled using hierarchical regression methods with patients nested within therapists within clinics. Separate models were estimated for all patients, for those with lumbar, and for those with shoulder impairments. All models risk‐adjusted for intake FS, age, gender, onset, surgery count, functional comorbidity index, fear‐avoidance level, and payer type. Inverse probability weighting adjusted for censoring.

Data Collection Methods

Functional status was captured using computer adaptive testing at intake and at discharge.

Principal Findings

Clinic and therapist effects explained 11.6 percent of variation in FS. Clinics ranked in the lowest quartile had significantly different outcomes than those in the highest quartile (p < .01). Clinics ranked similarly in lumbar and shoulder impairments (correlation = 0.54), but some clinics ranked in the highest quintile for one condition and in the lowest for the other.

Conclusions

Benchmarking models based on validated FS measures clearly separated high‐quality from low‐quality clinics, and they could be used to inform value‐based‐payment policies.     

The Subjective Well‐Being Method of Valuation: An Application to General Health Status

Objective

To introduce the subjective well‐being (SWB) method of valuation and provide an example by valuing health status. The SWB method allows monetary valuations to be performed in the absence of market relationships.

Data Sources

Data are from the 1975–2010 General Social Survey.

Study Design

The value of health status is determined via the estimation of an implicit derivative based on a happiness equation. Two‐stage least‐squares was used to estimate happiness as a function of poor‐to‐fair health status, annual household income adjusted for household size, age, sex, race, marital status, education, year, and season. Poor‐to‐fair health status and annual household income are instrumented using a proxy for intelligence, a temporal version of the classic distance instrument, and the average health status of individuals who are demographically similar but geographically separated. Instrument validity is evaluated.

Principal Findings

Moving from good/excellent health to poor/fair health (1 year of lower health status) is equivalent to the loss of $41,654 of equivalized household income (2010 constant dollars) per annum, which is larger than median equivalized household income.

Conclusion

The SWB method may be useful in making monetary valuations where fundamental market relationships are not present.     

Dual‐System Use and Intermediate Health Outcomes among Veterans Enrolled in Medicare Advantage Plans

Objective

The concurrent use of multiple health care systems may duplicate or fragment care. We assessed the characteristics of veterans who were dually enrolled in both the Veterans Affairs (VA) health care system and a Medicare Advantage (MA) plan, and compared intermediate quality outcomes among those exclusively receiving care in the VA with those receiving care in both systems.

Data Sources/Study Setting

VA and MA quality and administrative data from 2008 to 2009.

Study Design

We used propensity score methods to test the association between dual use and five intermediate outcome quality measures. Outcomes included control of cholesterol, blood pressure, and glycosylated hemoglobin among persons with coronary heart disease (CHD), hypertension, and diabetes.

Data Collection/Extraction Methods

VA and MA data were merged to identify VA‐only users (n = 1,637) and dual‐system users (n = 5,006).

Principal Findings

We found no significant differences in intermediate outcomes between VA‐only and dual‐user populations. Differences ranged from a 3.2 percentage point (95 percent CI: −1.8 to 8.2) greater rate of controlled cholesterol among VA‐only users with CHD to a 2.2 percentage point (95 percent CI: −2.4 to 6.6) greater rate of controlled blood pressure among dual users with diabetes.

Conclusions

For the five measures studied, we did not find evidence that veterans with dual use of VA and MA care experienced improved or worsened outcomes as compared with veterans who exclusively used VA care.     

Percutaneous Coronary Intervention in the United States: Risk Factors for Untimely Access

Objective

To determine how access to percutaneous coronary intervention (PCI) is distributed across demographics.

Data Sources

Secondary data from the 2011 American Hospital Association (AHA) survey data combined with 2010 Census.

Study Design

We calculated prehospital times from 32,370 ZIP codes to the nearest PCI center. We used a multivariate logit model to determine the odds of untimely access by the ZIP code''s concentration of vulnerable populations.

Data Collection

We used ZIP code–level data on community characteristics from the 2010 Census and supplemented it with 2011 AHA survey data on service‐line availability of PCI for responding hospitals.

Principal Findings

For approximately 306 million Americans, the median prehospital time to the nearest PCI center is 33 minutes. While 84 percent of Americans live within one hour of a PCI center, the odds of untimely access are higher in low‐income (OR: 3.00; 95 percent CI: 2.39, 3.77), rural (8.10; 95 percent CI: 6.84, 9.59), and highly Hispanic communities (2.55; 95 percent CI: 1.86, 3.49).

Conclusions

While the majority of Americans live within 60 minutes of a PCI center, rural, low‐income, and highly Hispanic communities have worse PCI access. This may translate into worse outcomes for patients with acute myocardial infarction.     

Community Discharge of Nursing Home Residents: The Role of Facility Characteristics

Objective

Using a socio‐ecological model, this study examines the influence of facility characteristics on the transition of nursing home residents to the community after a short stay (within 90 days of admission) or long stay (365 days of admission) across states with different long‐term services and supports systems.

Data Source

Data were drawn from the Minimum Data Set, the federal Online Survey, Certification, and Reporting (OSCAR) database, the Area Health Resource File, and the LTCFocUs.org database for all free‐standing, certified nursing homes in California (n = 1,127) and Florida (n = 657) from July 2007 to June 2008.

Study Design

Hierarchical generalized linear models were used to examine the impact of facility characteristics on the probability of transitioning to the community.

Principal Findings

Facility characteristics, including size, occupancy, ownership, average length of stay, proportion of Medicare and Medicaid residents, and the proportion of residents admitted from acute care facilities are associated with discharge but differed by state and whether the discharge occurred after a short or long stay.

Conclusion

Short‐ and long‐stay nursing home discharge to the community is affected by resident, facility, and sometimes market characteristics, with Medicaid consistently influencing discharge in both states.     

Availability of New Medicaid Patient Appointments and the Role of Rural Health Clinics

Objective

To examine the willingness to accept new Medicaid patients among certified rural health clinics (RHCs) and other nonsafety net rural providers.

Data Sources

Experimental (audit) data from a 10‐state study of primary care practices, county‐level information from the Area Health Resource File, and RHC information from the Center for Medicare and Medicaid Services.

Study Design

We generate appointment rates for rural and nonrural areas by patient‐payer type (private, Medicaid, self‐pay) to then motivate our focus on within‐rural variation by clinic type (RHC vs. non‐RHC). Multivariate linear models test for statistical differences and assess the estimates’ sensitivity to the inclusion of control variables.

Data Collection

The primary data are from a large field study.

Principal Findings

Approximately 80 percent of Medicaid callers receive an appointment in rural areas—a rate more than 20 percentage points greater than nonrural areas. Importantly, within rural areas, RHCs offer appointments to prospective Medicaid patients nearly 95 percent of the time, while the rural (nonsafety net) non‐RHC Medicaid rate is less than 75 percent. Measured differences are robust to covariate adjustment.

Conclusions

Our study suggests that RHC status, with its alternative payment model, is strongly associated with new Medicaid patient acceptance. Altering RHC financial incentives may have consequences for rural Medicaid enrollees.     

Using Medical Claims for Policy Effectiveness Surveillance: Reimbursement and Utilization of Abdomen/Pelvis Computed Tomography Scans

Objective

To quantify changes in private insurance payments for and utilization of abdominal/pelvic computed tomography scans (CTs) after 2011 changes in CPT coding and Medicare reimbursement rates, which were designed to reduce costs stemming from misvalued procedures.

Data Sources

TruvenHealth Analytics MarketScan Commercial Claims and Encounters database.

Study Design

We used difference‐in‐differences models to compare combined CTs of the abdomen/pelvis to CTs of the abdomen or pelvis only. Our main outcomes were inflation‐adjusted log payments per procedure, daily utilization rates, and total annual payments.

Data Extraction Methods

Claims data were extracted for all abdominal/pelvic CTs performed in 2009–2011 within noncapitated, employer‐sponsored private plans.

Principal Findings

Adjusted payments per combined CTs of the abdomen/pelvis dropped by 23.8 percent (p < .0001), and their adjusted daily utilization rate accelerated by 0.36 percent (p = .034) per month after January 2011. Utilization rate of abdominal‐only or pelvic‐only CTs dropped by 5.0 percent (p < .0001). Total annual payments for combined CTs of the abdomen/pelvis decreased in 2011 despite the increased utilization.

Conclusions

Private insurance payments for combined CTs of the abdomen/pelvis declined and utilization accelerated significantly after 2011 policy changes. While growth in total annual payments was contained in 2011, it may not be sustained if 2011 utilization trends persist.     

EHR Adoption and Hospital Performance: Time‐Related Effects

Objective

To assess whether, 5 years into the HITECH programs, national data reflect a consistent relationship between EHR adoption and hospital outcomes across three important dimensions of hospital performance.

Data Sources/Study Setting

Secondary data from the American Hospital Association and CMS (Hospital Compare and EHR Incentive Programs) for nonfederal, acute‐care hospitals (2009–2012).

Study Design

We examined the relationship between EHR adoption and three hospital outcomes (process adherence, patient satisfaction, efficiency) using ordinary least squares models with hospital fixed effects. Time‐related effects were assessed through comparing the impact of EHR adoption pre (2008/2009) versus post (2010/2011) meaningful use and by meaningful use attestation cohort (2011, 2012, 2013, Never). We used a continuous measure of hospital EHR adoption based on the proportion of electronic functions implemented.

Data Collection/Extraction Methods

We created a panel dataset with hospital‐year observations.

Principal Findings

Higher levels of EHR adoption were associated with better performance on process adherence (0.147; p < .001) and patient satisfaction (0.118; p < .001), but not efficiency (0.01; p = .78). For all three outcomes, there was a stronger, positive relationship between EHR adoption and performance in 2010/2011 compared to 2008/2009. We found mixed results based on meaningful use attestation cohort.

Conclusions

Performance gains associated with EHR adoption are apparent in more recent years. The large national investment in EHRs appears to be delivering more consistent benefits than indicated by earlier national studies.     

Sustained Reduction in Health Disparities Achieved through Targeted Quality Improvement: One‐Year Follow‐up on a Three‐Year Intervention

Objective

To assess a quality improvement disparity reduction intervention and its sustainability.

Data Sources/Study Setting

Electronic health records and Quality Index database of Clalit Health Services in Israel (2008–2012).

Study Design

Interrupted time‐series with pre‐, during, and postintervention disparities measurement between 55 target clinics (serving approximately 400,000 mostly low socioeconomic, minority populations) and all other (126) clinics.

Data Collection/Extraction Methods

Data on a Quality Indicator Disparity Scale (QUIDS‐7) of 7 indicators, and on a 61‐indicator scale (QUIDS‐61).

Principal Findings

The gap between intervention and nonintervention clinics for QUIDS‐7 decreased by 66.7 percent and by 70.4 percent for QUIDS‐61. Disparity reduction continued (18.2 percent) during the follow‐up period.

Conclusions

Quality improvement can achieve significant reduction in disparities in a wide range of clinical domains, which can be sustained over time.     

Comparing the Cost of Caring for Medicare Beneficiaries in Federally Funded Health Centers to Other Care Settings

Objective

To compare total annual costs for Medicare beneficiaries receiving primary care in federally funded health centers (HCs) to Medicare beneficiaries in physician offices and outpatient clinics.

Data Sources/Study Settings

Part A and B fee‐for‐service Medicare claims from 14 geographically diverse states. The sample was restricted to beneficiaries residing within primary care service areas (PCSAs) with at least one HC.

Study Design

We modeled separately total annual costs, annual primary care costs, and annual nonprimary care costs as a function of patient characteristics and PCSA fixed effects.

Data Collection

Data were obtained from the Centers for Medicare & Medicaid Services.

Principal Findings

Total median annual costs (at $2,370) for HC Medicare patients were lower by 10 percent compared to patients in physician offices ($2,667) and by 30 percent compared to patients in outpatient clinics ($3,580). This was due to lower nonprimary care costs in HCs, despite higher primary care costs.

Conclusions

HCs may offer lower total cost practice style to the Centers for Medicare & Medicaid Services, which administers Medicare. Future research should examine whether these lower costs reflect better management by HC practitioners or more limited access to specialty care by HC patients.     

Accelerating Improvement and Narrowing Gaps: Trends in Patients' Experiences with Hospital Care Reflected in HCAHPS Public Reporting

Objective

Measure HCAHPS improvement in hospitals participating in the second and fifth years of HCAHPS public reporting; determine whether change is greater for some hospital types.

Data

Surveys from 4,822,960 adult inpatients discharged July 2007–June 2008 or July 2010–June 2011 from 3,541 U.S. hospitals.

Study Design

Linear mixed‐effect regression models with fixed effects for time, patient mix, and hospital characteristics (bedsize, ownership, Census division, teaching status, Critical Access status); random effects for hospitals and hospital‐time interactions; fixed‐effect interactions of hospital characteristics and patient characteristics (gender, health, education) with time predicted HCAHPS measures correcting for regression‐to‐the‐mean biases.

Data Collection Methods

National probability sample of adult inpatients in any of four approved survey modes.

Principal Findings

HCAHPS scores increased by 2.8 percentage points from 2008 to 2011 in the most positive response category. Among the middle 95 percent of hospitals, changes ranged from a 5.1 percent decrease to a 10.2 percent gain overall. The greatest improvement was in for‐profit and larger (200 or more beds) hospitals.

Conclusions

Five years after HCAHPS public reporting began, meaningful improvement of patients'' hospital care experiences continues, especially among initially low‐scoring hospitals, reducing some gaps among hospitals.     

Measurement Error in Public Health Insurance Reporting in the American Community Survey: Evidence from Record Linkage

Objective

Examine measurement error to public health insurance in the American Community Survey (ACS).

Data Sources/Study Setting

The ACS and the Medicaid Statistical Information System (MSIS).

Study Design

We tabulated the two data sources separately and then merged the data and examined health insurance reports among ACS cases known to be enrolled in Medicaid or expansion Children''s Health Insurance Program (CHIP) benefits.

Data Collection/Extraction Methods

The two data sources were merged using protected identification keys. ACS respondents were considered enrolled if they had full benefit Medicaid or expansion CHIP coverage on the date of interview.

Principal Findings

On an aggregated basis, the ACS overcounts the MSIS. After merging the data, we estimate a false‐negative rate in the 2009 ACS of 21.6 percent. The false‐negative rate varies across states, demographic groups, and year. Of known Medicaid and expansion CHIP enrollees, 12.5 percent were coded to some other coverage and 9.1 percent were coded as uninsured.

Conclusions

The false‐negative rate in the ACS is on par with other federal surveys. However, unlike other surveys, the ACS overcounts the MSIS on an aggregated basis. Future work is needed to disentangle the causes of the ACS overcount.     

The Impact of Pediatrician Supply on Child Health Outcomes: Longitudinal Evidence from Japan

Objective

To investigate the effect of pediatrician supply on under‐5 mortality over the period 2000–2010.

Data Sources

Multiple publicly available data sources were used.

Study Design

Japan''s 366 “Secondary Tier of Medical Care Units” (STMCU) were used as study units. To evaluate the association between under‐5 mortality and pediatrician supply, we explored time and area fixed‐effects Poisson regression model. The following factors were introduced into the models as time‐varying controls: (1) number of physicians other than pediatricians per total population except for under‐5‐year‐old population, and (2) income per total population by year and STMCU. Extensive sensitivity analyses were conducted to assess robustness of results.

Principal Findings

Pediatrician density was inversely associated with under‐5 mortality. We estimated that a unit increase in pediatrician density was associated with a 7 percent (95 percent CI: 2–12 percent) reduction in the child mortality rate after adjustment for all other variables. The results were consistent and robust across all specifications tested.

Conclusions

The results suggest that increasing human health resources can have positive effects on child health, even in settings where child mortality of less than 5 per 1,000 has been achieved.     

Do Racial/Ethnic Disparities in Quality and Patient Experience within Medicare Plans Generalize across Measures and Racial/Ethnic Groups?

Objective

To examine how similar racial/ethnic disparities in clinical quality (Healthcare Effectiveness Data and Information Set [HEDIS]) and patient experience (Consumer Assessment of Healthcare Providers and Systems [CAHPS]) measures are for different measures within Medicare Advantage (MA) plans.

Data Sources/Study Setting

5.7 million/492,495 MA beneficiaries with 2008–2009 HEDIS/CAHPS data.

Study Design

Binomial (HEDIS) and linear (CAHPS) hierarchical mixed models generated contract estimates for HEDIS/CAHPS measures for Hispanics, blacks, Asian‐Pacific Islanders, and whites. We examine the correlation of within‐plan disparities for HEDIS and CAHPS measures across measures.

Principal Findings

Plans with disparities for a given minority group (vs. whites) for a particular measure have a moderate tendency for similar disparities for other measures of the same type (mean r = 0.51/.21 and 53/34 percent positive and statistically significant for CAHPS/HEDIS). This pattern holds to a lesser extent for correlations of CAHPS disparities and HEDIS disparities (mean r = 0.05/0.14/0.23 and 4.4/5.6/4.4 percent) positive and statistically significant for blacks/Hispanics/API.

Conclusions

Similarities in CAHPS and HEDIS disparities across measures might reflect common structural factors, such as language services or provider incentives, affecting several measures simultaneously. Health plan structural changes might reduce disparities across multiple measures.     

Measuring Prices in Health Care Markets Using Commercial Claims Data

Objective

To compare methods of price measurement in health care markets.

Data Sources

Truven Health Analytics MarketScan commercial claims.

Study Design

We constructed medical prices indices using three approaches: (1) a “sentinel” service approach based on a single common service in a specific clinical domain, (2) a market basket approach, and (3) a spending decomposition approach. We constructed indices at the Metropolitan Statistical Area level and estimated correlations between and within them.

Principal Findings

Price indices using a spending decomposition approach were strongly and positively correlated with indices constructed from broad market baskets of common services (r > 0.95). Prices of single common services exhibited weak to moderate correlations with each other and other measures.

Conclusions

Market‐level price measures that reflect broad sets of services are likely to rank markets similarly. Price indices relying on individual sentinel services may be more appropriate for examining specialty‐ or service‐specific drivers of prices.     

Higher Incentive Payments in Medicare Advantage's Pay‐for‐Performance Program Did Not Improve Quality But Did Increase Plan Offerings

Objective

To evaluate the effects of the size of financial bonuses on quality of care and the number of plan offerings in the Medicare Advantage Quality Bonus Payment Demonstration.

Data Sources

Publicly available data from CMS from 2009 to 2014 on Medicare Advantage plan quality ratings, the counties in the service area of each plan, and the benchmarks used to construct plan payments.

Study Design

The Medicare Advantage Quality Bonus Payment Demonstration began in 2012. Under the Demonstration, all Medicare Advantage plans were eligible to receive bonus payments based on plan‐level quality scores (star ratings). In some counties, plans were eligible to receive bonus payments that were twice as large as in other counties. We used this variation in incentives to evaluate the effects of bonus size on star ratings and the number of plan offerings in the Demonstration using a differences‐in‐differences identification strategy. We used matching to create a comparison group of counties that did not receive double bonuses but had similar levels of the preintervention outcomes.

Principal Findings

Results from the difference‐in‐differences analysis suggest that the receipt of double bonuses was not associated with an increase in star ratings. In the matched sample, the receipt of double bonuses was associated with a statistically insignificant increase of +0.034 (approximately 1 percent) in the average star rating (p > .10, 95 percent CI: −0.015, 0.083). In contrast, the receipt of double bonuses was associated with an increase in the number of plans offered. In the matched sample, the receipt of double bonuses was associated with an overall increase of +0.814 plans (approximately 5.8 percent) (p < .05, 95 percent CI: 0.078, 1.549). We estimate that the double bonuses increased payments by $3.43 billion over the first 3 years of the Demonstration.

Conclusions

At great expense to Medicare, double bonuses in the Medicare Advantage Quality Bonus Payment Demonstration were not associated with improved quality but were associated with more plan offerings.