Impact of the Patient-Centered Medical Home on Consistently High-Cost Patients

ABSTRACT

Objective: To evaluate the effect of a statewide multipayer patient-centered medical home (PCMH) demonstration on patients consistently within the highest ranks of health services expenditure across Maryland.

Study Design: Post hoc longitudinal analyses of administrative data on privately insured patients of medical homes that participated in the Maryland Multi-Payer PCMH Program (MMPP), matched for comparison to medical homes in a single-payer PCMH program and to non-PCMH practices.

Methods: Consistently high-cost patients (CHPs) were defined as being in the top statewide quintile of payer expenditure over a 2-year baseline period. Using population-averaged generalized linear regression models, we evaluated the odds of CHPs remaining in the highest-cost quintile during the 2-year MMPP implementation period and assessed changes in their utilization patterns.

Results: Six percent of included patients were CHPs and accounted for one-third of total expenditure. For CHPs in multipayer PCMHs, estimated odds of remaining in this status after 2 years were lower by 34% (adjusted OR [AOR], 0.66; 95% CI, 0.41-0.90; P = .03) relative to CHPs in non-PCMH practices and higher by 41% (AOR, 1.41; 95% CI, 1.08-1.75; P = .004) compared with CHPs in single-payer PCMHs. Relative to CHPs in non-PCMH practices, CHPs in multipayer PCMHs had inpatient admissions decline by 40% (incidence rate ratio [IRR], 0.60; 95% CI, 0.36-1.00; P = .049) and visits to the attributed primary care provider increase by 21% (IRR, 1.21; 95% CI, 1.05-1.39; P = .01).

Conclusions: Relative to routine primary care, the PCMH model significantly reduces the probability that CHPs remain in this expensive category and enhances continuity of care.

Am J Manag Care. 2023;29(12):680-686. https://doi.org/10.37765/ajmc.2023.89467

Takeaway Points

We evaluated the impact of the patient-centered medical home (PCMH) model on the costliest privately insured adult patients in Maryland.

• Consistently high-cost patients (CHPs) in PCMHs that participated in a statewide multipayer demonstration saw their odds of remaining in this expensive category lowered by 34% relative to counterparts in matched non-PCMH practices.
• CHPs in participating PCMHs also had lower risk of inpatient admissions and higher frequency of visits to their primary care provider relative to non-PCMH CHPs.
• These findings suggest that medical homes could alter the population distribution of health expenditure by curbing recurrently high expenditure patterns among the costliest patients.

In the time since the patient-centered medical home (PCMH) model was operationalized for adult primary care,¹ evaluations of the largest PCMH demonstrations have not yielded impressive expenditure outcomes.^2-6 Payers, which have originated and financed most PCMH initiatives, need stronger evidence validating the potential of the medical home to contribute to significant and sustained reductions in health expenditure, particularly for beneficiaries who account for a disproportionate share of payers’ disbursements.

Four characteristics limit the utility of existing PCMH evaluations for addressing this critical gap. First, most research to date has aggregated expenditure across all patients in a medical home, including young and healthy patients whose utilization patterns are not likely to change significantly in the short term.^7-12 Second, studies typically measure PCMH cost effects as mean reduction in per-member per-month (PMPM) expenditures.^7-17 The distribution of health expenditure among a payer’s beneficiaries is, however, neither uniform nor Gaussian.¹⁸ Evaluations that report mean estimates mask the impact of the PCMH on the subgroup of patients largely driving expenditure trends. Third, frequent use of the repeated cross-sectional research design introduces regression to the mean in cases where incidental medical procedures, or expensive but infrequent medical encounters, cause patients to artificially appear as high utilizers.^10,12-15,17 This phenomenon obscures actual reductions in expenditure attributable to medical home features among patients who are genuinely consistent high-cost utilizers. Fourth, comparing the performance of a small sample of medical homes with that of non-PCMH comparator practices does not provide generalizable inferences to a payer with a beneficiary population that may span an entire state or region.^7-15,17

Based on these limitations, a more valid and pragmatic evaluation design to justify the potential of the PCMH model to payers would assess the impact on expenditures for patients who have the greatest likelihood of exposure to core PCMH features and who have demonstrated patterns of recurrently high expenditure. The approach would also evaluate the model’s performance with respect to a payer’s entire beneficiary population, not only a limited set of intervention and comparator practices. This study attempts to close the gap by revisiting the evaluation of a comprehensive, statewide, multipayer PCMH initiative to estimate its impact on expenditure levels among beneficiaries who consistently had the highest level of health services expenditure across several insurers in a state. The intent was to test the potential of the PCMH model to achieve significant and lasting reductions in expenditure for patients with a variety of health conditions and care coordination challenges suited to the core features that distinguish the PCMH model from routine primary care.²

METHODS

Study Setting and Design

The setting is the Maryland Multi-Payer PCMH Program (MMPP), a statewide demonstration through which 52 PCMHs purposively selected from across the state received financial and technical support from Medicaid and major private payers to support and advance their medical home functioning from 2011 to 2013.^19,20 Participating practices had achieved level 1 (lowest), level 2 (intermediate), or level 3 (highest) PCMH recognition by the National Committee for Quality Assurance (NCQA)²¹ when the program started in April 2011. In addition to regular fee-for-service payments, the PCMHs received unconditional PMPM payments ranging from $3.51 to $6.01 for patients insured by participating payers to support care management. Practices were also eligible for 30% to 50% of savings from reductions in health expenditure among attributed patients, conditional on quality performance. Finally, the practices received technical support for quality improvement through the Maryland Learning Collaborative.²² The statewide context and multipayer involvement were unique strengths of this PCMH demonstration.²³ More recent PCMH programs of comparable scale have been limited to patients of a single private payer (like the CareFirst PCMH Program evaluated in this study), focused mainly on Medicare beneficiaries (such as CMS’ Comprehensive Primary Care²⁴ and Multi-Payer Advanced Primary Care Practice²⁵ demonstrations) or on special populations (like the Veterans Affairs Patient-Aligned Care Teams²⁶).

The study design is a retrospective, quasi-experimental evaluation of the impact of the MMPP’s multipayer financial and technical support to medical homes on the probability of consistently high-cost patients (CHPs) remaining in this status and on utilization levels among CHPs. For a prior evaluation,^27,28 MMPP practices were matched using propensity scores on data from 2010 (the year before the MMPP commenced) to 57 Maryland primary care practices partaking in a regional medical home program funded by a single private payer, CareFirst,²⁹ and to 47 primary care practices in Maryland that were not certified as medical homes by the NCQA or partaking in the CareFirst PCMH Program in 2010. We termed these comparison groups single-payer PCMH and non-PCMH practices, respectively. The propensity scores modeled participation in the MMPP as a function of practices’ structural features and aggregated patient characteristics. Both the MMPP and the CareFirst PCMH Program kicked off in 2011 with a strong emphasis on care coordination for high utilizers and the opportunity for participating practices to earn shared savings. The CareFirst PCMH Program, however, provided an equivalent of $10.34 PMPM, shared savings up to 80% of annual billings, and additional compensation for developing care management plans for high-risk patients.^17,30 These rewards were limited to patients insured by the sponsoring payer.

The baseline period for the study is defined as the 2 calendar years from January 1, 2010, to December 31, 2011. The baseline period encompasses the entire year preceding the MMPP’s start in April 2011 and the first 8 months of the program. The implementation period is defined to immediately follow the baseline, and it covers 2 calendar years of the MMPP, starting in January 2012. By January 2013, participating practices had to attain the intermediate (level 2) or highest (level 3) NCQA PCMH certification. The extension of the baseline period beyond the MMPP start date accounts for delayed implementation of the MMPP and CareFirst PCMH Program in participating practices, gradual onboarding of care managers, and refinement of care management processes.^17,31 The extension also allows a duration of 2 calendar years to validly define patients as recurrently high-cost users.³²

Study Data

Claims data on patients’ health services utilization and expenditures were obtained from the Maryland Medical Care Data Base, the private insurer portion of the state’s all-payer claims database.³³ We used the Johns Hopkins ACG (Adjusted Clinical Groups) System (version 11.0) to classify patients annually into aggregated diagnostic groups (ADGs) reflecting diagnoses with serious morbidity and into resource utilization bands reflecting similar levels of health care use.³⁴ The nominal count of diagnosed chronic conditions and indicators for diagnosis with psychosocial conditions, malignancy, and frailty were also obtained from the ACG System for each patient-year of observation. Using a validated algorithm,³⁵ we computed the Charlson Comorbidity Index score for each patient as an estimate of relative risk of death within a year due to diagnosed comorbidities.³⁶

The structural characteristics of MMPP and comparator practices in the baseline period were obtained for propensity score matching from 2 sources: applications submitted by practices to be considered for acceptance into the program and information on practices provided by physicians for license renewal in the databases of the Maryland Board of Physicians. In the latter source, which was primarily used for comparator practices, the modal response among the providers of a practice was selected to represent the practice. Practice characteristics reported include setting, geographic location, ownership type, primary medical specialty, number of physicians, and format of medical recordkeeping.

Study Population

We included privately insured adult patients continuously attributed to the same MMPP or comparator practice for 2 successive calendar years in either the baseline period or the implementation period. Patients were attributed retrospectively to the primary care provider that serviced the plurality of their evaluation and management claims during each calendar year. Attributed patients had to be aged 18 to 64 years in each year of observation to exclude children and to reduce the likelihood of coverage by Medicare (which did not participate in the MMPP).

Study Measures

The primary dependent variable is the binary classification of an individual as a CHP. Adapted from a prior study,³² a CHP was defined here as being in the top quintile of total payer expenditure for 4 consecutive half-year periods among all privately insured beneficiaries with similar age and sex statewide. The 80th percentile threshold of expenditure for CHP status was calculated semiannually for each unique combination of patient’s sex and the following age categories in years: 18 to 25, 26 to 35, 36 to 45, 46 to 55, and 56 to 64. Included patients with total payer expenditure greater than the 80th percentile of their age-sex category for all 4 half-years in 2010 and 2011 were classified as CHPs for the baseline period. Similarly, included patients with total payer expenditure in the top quintile of their age-sex category for all 4 half-years in 2012 and 2013 were classified as CHPs in the implementation period. Statewide thresholds for CHP status are presented for age-sex categories in eAppendix Table 1 (eAppendix available at ajmc.com). Total payer expenditure was measured as the sum of reimbursed amounts by the insurance plan across all institutional, professional, and pharmaceutical claims.

Statistical Analyses

To validate the propensity score matching, we examined differences in practice-level and patient characteristics among multipayer PCMHs, single-payer PCMHs, and non-PCMH practices. Bivariate tests, specifically Wilcoxon rank sum tests for continuous variables and χ² tests for categorical variables, were applied to test for significant differences between comparison groups. P values less than .01 were considered significant for patient-level comparisons due to the large sample sizes and multiple comparisons across groups.

We evaluated whether patients defined as CHPs in the baseline period remained in this status during the implementation period and whether the probability of remaining in CHP status among these patients varied by practice group. We fit a marginal logistic regression model of the binary outcome of a baseline CHP remaining in CHP status during the implementation period, adjusted for age category, sex, Charlson Comorbidity Index score, a binary indicator for diagnosis with psychosocial conditions, and count of visits to the attributed provider. Practice-level covariates included the number of patients, an indicator variable for urban/rural status of the practice’s county, and number of physicians in the practice.

Finally, we evaluated whether mean utilization counts changed from the baseline period to the implementation period among patients initially defined as CHPs. The categories assessed included annual number of emergency department visits, inpatient admissions, ambulatory visits (defined as primary care or specialty office visits), and ambulatory visits to the attributed provider. We calculated incidence rate ratios (IRRs) of the change in mean levels among CHPs in multipayer PCMHs to the respective change among CHPs in comparator practice groups. We derived these estimates from population-averaged generalized linear models of the Poisson-distributed utilization outcomes, with robust adjustments to account for overdispersion. The regression models controlled for an individual’s age category, sex, count of diagnosed chronic conditions, and count of patients in the attributed practice.

All analyses were conducted in Stata version 15 (StataCorp LLC). P values less than .05 were considered significant for estimates from regression models. The study protocols were approved by the Johns Hopkins Bloomberg School of Public Health Institutional Review Board.

RESULTS

The counts of attributed individuals during the baseline period and during the implementation period were 55,475 patients from 110 practices and 83,625 patients from 113 practices, respectively. There were 23,404 patients continuously attributed during both the baseline and implementation periods. At baseline, there were minimal differences in structural features among the multipayer PCMHs, matched single-payer PCMHs, and non-PCMH practices (Table 1). During the baseline period, the proportion of CHPs was 5.8% among patients attributed to multipayer PCMHs, 5.6% among patients of single-payer PCMHs, and 6.7% among non-PCMH patients. CHPs attributed to multipayer PCMHs at baseline were similar to CHPs in comparator practices with respect to age, sex, and most diagnostic characteristics (eAppendix Table 2). Mean annual expenditure was not significantly different among CHPs in multipayer PCMHs ($13,690), single-payer PCMHs ($14,620), and non-PCMH practices ($14,089) during the baseline period (P = .98).

Within all practice groups, CHPs were markedly different from non-CHPs demographically, clinically, and in health services utilization trends (Table 2). CHPs were slightly older, had a higher count of diagnosed chronic conditions, and had a greater prevalence of major ADGs, psychosocial conditions, malignancy, and frailty. In both non-PCMH and PCMH practices, the mean count of ambulatory visits was higher among CHPs than among non-CHPs. However, non-CHPs made a greater proportion of these visits with their attributed primary care provider. Although CHPs composed approximately one-fifteenth of the population in each practice group, they accounted for approximately one-third of total expenditure and more than half of pharmaceutical expenditure.

Among continuously enrolled patients, 39.0% of baseline CHPs in multipayer PCMHs transitioned to non-CHP status during the implementation period. The transitional proportions were 45.2% of baseline CHPs in single-payer PCMHs and 29.6% of baseline CHPs in non-PCMH practices. Patients who transitioned out of CHP status saw unadjusted mean (SD) expenditure reduce to $4551 ($4308) in multipayer PCMHs, $4124 ($3668) in single-payer PCMHs, and $4235 ($3234) in non-PCMH practices by the final year of the implementation period. In adjusted analyses, the odds of remaining in CHP status during the implementation period were lower by 34% (adjusted OR [AOR], 0.66; 95% CI, 0.41-0.90; P = .03) for CHPs in multipayer PCMHs relative to CHPs in non-PCMH practices. Conversely, odds of remaining in CHP status were greater by 41% (AOR, 1.41; 95% CI, 1.08-1.75; P = .004) among CHPs in multipayer PCMHs compared with CHPs in single-payer PCMHs.

Regarding utilization, inpatient admissions declined among CHPs in multipayer PCMHs from 2010 to 2012 relative to non-PCMH counterparts (IRR, 0.60; 95% CI, 0.36-1.00; P = .049) (Table 3). Ambulatory visits to the attributed primary care provider increased among CHPs in multipayer PCMHs from 2010 to 2012 (IRR , 1.18; 95% CI, 1.04-1.34; P = .01) and from 2010 to 2013 (IRR , 1.21; 95% CI, 1.05-1.39; P = .01) relative to CHPs in non-PCMH practices.

DISCUSSION

We evaluated the association of participating in a statewide, multipayer-supported PCMH demonstration with the probability of a primary care practice’s patients recurrently being ranked among the costliest privately insured patients across Maryland. The odds of remaining in this expensive category reduced by 34% among privately insured adult patients continuously attributed to multipayer PCMHs relative to counterparts in non-PCMH practices. The PCMH’s pronounced effect on curbing excessive expenditure levels among the costliest patients in this state supports the model’s potential to alter the population distribution of health expenditure as it becomes more widely implemented nationwide. Whereas previous work shows that the medical home has a greater impact on expenditure for individuals with specific chronic conditions,^3,37 this study generalizes the finding to individuals with complex combinations of chronic conditions and whose high utilization patterns may be driven by nonmedical factors. In both PCMH and non-PCMH practices, CHPs were diagnosed with a mean of 6 chronic medical and psychosocial conditions. Hence, evaluations that focus on a single, specific ailment would undercount the most expensive utilizers in a patient population and may underestimate the effectiveness of the medical home. Relative to CHPs in non-PCMHs, CHPs attributed to multipayer PCMHs also experienced nominal reductions in inpatient and emergency care utilization, but ambulatory visits to their personal primary care physician increased significantly during the demonstration. The latter result is encouraging given the baseline observation that the proportion of encounters that CHPs made with their attributed provider was much lower than among other patients. Care continuity with a limited set of providers fosters improved patient outcomes and reduced expenditure in individuals with chronic conditions.³⁸

Our analyses also demonstrate that practices in the single payer–funded CareFirst PCMH Program outperformed the multipayer PCMHs of the MMPP in reducing the likelihood that CHPs remained in the costliest statewide category during the MMPP implementation period. The CareFirst PCMH Program had 2 distinct features that may explain its greater control over health expenditure of the costliest patients. Whereas the MMPP did not impose licensing or qualification requirements for a care manager, this role was more standardized in the CareFirst PCMH Program because external nurses were deployed to practices on request to develop individualized care plans for historically high-cost patients. CareFirst PCMH providers also had access to an electronic portal to continually track the total cost of care for the most expensive patients in their panel, and they had information on hospital and specialist costs to inform more efficient referrals. Qualitative and quantitative evaluations attribute the cost savings reported during the program’s early years to comprehensive care coordination and close monitoring of financial performance.^17,30,39,40 Future implementation and expansion of the medical home model may consider these additional elements to enhance outcomes.

Limitations

Findings from this study must be interpreted cautiously in light of important limitations. First, health expenditure was measured using payer reimbursements, without taking patient liabilities into account. It is possible that reimbursement values may differ among patients for the same service based on how deductibles and co-payments are structured under different insurance plans, variation among plans in negotiated rates for health services, and whether patients are frequenting high-cost or low-cost providers for their care needs. The clear differences reported in health status and utilization metrics between CHPs and non-CHPs in this study confirm that the former are indisputably high utilizers of health services and not merely individuals with insurance plans that tend to pay higher rates for services used. Furthermore, analyses were limited to privately insured patients, and the data available for this study did not allow adjustment for nonmedical factors associated with health expenditure and utilization levels, including patient’s race and socioeconomic status.^41,42 Practice characteristics were observed only in the baseline year, and analyses did not account for subsequent changes in systems of care, practice-level innovations apart from PCMH implementation, and other temporal improvements.

CONCLUSIONS

This study demonstrated that consistently high-cost, privately insured adult patients within practices participating in a multipayer PCMH demonstration—characterized by enhanced provider payment and incentives for cost savings—saw reductions in their likelihood of remaining among the highest-cost utilizers at the statewide level. To increase the utility for payers, future research evaluating expenditure outcomes under the PCMH model should consider its impact on consistently high-cost patients defined at the statewide level.

Author Affiliations: Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health (OAF, YJH, JPW, JAM), Baltimore, MD.

Source of Funding: Funding was provided by the Johns Hopkins Primary Care Consortium.

Author Disclosures: Dr Weiner reports that Johns Hopkins University received royalties on the ACG software used as part of the analysis in this article. The remaining authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (OAF, YJH, JPW, JAM); acquisition of data (JAM, JPW); analysis and interpretation of data (OAF, YJH, JPW, JAM); drafting of the manuscript (OAF); critical revision of the manuscript for important intellectual content (OAF, YJH, JPW, JAM); statistical analysis (OAF); provision of patients or study materials (JAM); obtaining funding (OAF, JAM); administrative, technical, or logistic support (YJH); and supervision (YJH, JPW, JAM).

Address Correspondence to: Oludolapo A. Fakeye, PhD, MA, The Hilltop Institute at the University of Maryland Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250. Email: ofakeye@hilltop.umbc.edu.

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