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Personalized Preventive Care Leads to Significant Reductions in Hospital Utilization
Andrea Klemes, DO, FACE; Ralph E. Seligmann, MD; Lawrence Allen, MD; Michael A. Kubica, MBA, MS; Kimberly Warth, BS, MPA; and Bernard Kaminetsky, MD, FACP
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Personalized Preventive Care Leads to Significant Reductions in Hospital Utilization

Andrea Klemes, DO, FACE; Ralph E. Seligmann, MD; Lawrence Allen, MD; Michael A. Kubica, MBA, MS; Kimberly Warth, BS, MPA; and Bernard Kaminetsky, MD, FACP
We assessed the impact of the MDVIP personalized preventive care model on hospital utilization and found the MDVIP members' rates were substantially lower than nonmembers'.
In addition, relative hospital utilization tended to decrease as MDVIP membership increased over time. The estimated utilization savings for just 2010 in these 5 states was calculated to be $109.2 million for Medicare and approximately $10.2 million for commercial members, totaling $119.4 million, which was derived from the 2009 inpatient cost per admission value from the US Department of Health and Human Services (since the 2010 value was not available).10

For elective admissions, the overall MDVIP member discharges/ 1000 was approximately 59% lower than nonmembers for both 2006 and 2007. For 2008, 2009, and 2010, the relative reductions in elective admissions were 71%, 77%, and 83%, respectively.  For non-elective admissions, the overall MDVIP member discharges/1000 were approximately 37%, 43%, 49%, 52%, and 56% lower than nonmembers for the years 2006, 2007, 2008, 2009, and 2010, respectively.

Of the non-elective admissions, the overall MDVIP member discharges/1000 for urgent admissions were approximately 17%, 35%, 42%, 40%, and 42% lower than nonmembers for the years 2006, 2007, 2008, 2009, and 2010, respectively. For emergent admissions, the overall MDVIP member discharges/ 1000 for urgent admissions were approximately 41%, 45%, 51%, 54%, and 58% lower than nonmembers for the years 2006, 2007, 2008, 2009, and 2010, respectively.

MDVIP members experienced approximately 23%, 31%, 38%, 47%, and 49% fewer avoidable admissions than nonmembers for the years 2006, 2007, 2008, 2009, and 2010, respectively. Furthermore, MDVIP members experienced approximately 45%, 49%, 56%, 59%, and 63% fewer unavoidable admissions than nonmembers for the years 2006, 2007, 2008, 2009, and 2010, respectively.

While the comparative utilization analysis matched MDVIP and nonmember populations on all available measures, we recognize the possible effects of selection bias, ie, MDVIP members may differ from nonmembers on factors such as attitudes toward health, personal health behaviors, and baseline health status, none of which are discernible from hospital inpatient utilization data. To better understand systematic influences on the utilization differences between MDVIP and non-MDVIP populations, we performed sensitivity analyses. First, we tested for bias introduced from scaling. The baseline comparative utilization analysis used the comparator group population of the MDVIP physician’s state of practice (matched as described previously). This established a comparison population ratio of roughly 425:1 (nonmembers:MDVIP member). We would expect true utilization differences to be robust to a reduction in scaling differential. To test this, we limited the comparator group to the population of matched nonmembers residing in the same zip code as the physician practice, reducing the comparison population ratio to 15:1. Using this scale, across all payers for the 5 reporting states, inpatient utilization was 57% lower for MDVIP members versus nonmembers. From this we can conclude that the utilization difference for MDVIP versus non-MDVIP is robust to population scaling. Second, since year-over-year differences between MDVIP and nonmember populations increased in magnitude for the past several years, we examined the relationship between mean caseload maturity (ie, how long the average person has been an MDVIP member) and the difference in utilization. We found a strong relationship; roughly 86% of the variance in utilization is accounted for by increased caseload maturity. However, due to a relatively small sample size (4 years of data), analysis of variance did not find significance at the 0.05 level (there is roughly a 7% chance that the relationship would be found by chance).

To further understand the dramatic differences between the hospital utilization of MDVIP Medicare members relative to non-MDVIP Medicare members, readmission rates were evaluated. When compared with the 2009 readmission rates for non-MDVIP Medicare members within the 5 same states,9 MDVIP members were readmitted 97%, 95%, and 91% less frequently for acute MI, CHF, and pneumonia, respectively (Figure 3).


The hospital utilization rates of MDVIP members were substantially lower than nonmembers for each of the 5 years overall and for the commercial and Medicare populations separately. In addition, elective, non-elective, emergent, urgent, avoidable, and unavoidable admissions were all lower in the MDVIP members compared with nonmembers for each of the 5 years. Greater reductions in hospital discharges were seen in the older, Medicare population (>65 years of age) compared with the commercial population (35-64 years of age).

Studies have shown that better management and a higher quality of ambulatory care can lead to lower hospitalization rates, especially for ambulatory care–sensitive conditions. Scholle et al found that commercial health plans that achieved higher performance on Health Plan Employer Data and Information Set effectiveness-of-care measures of quality tended to have lower hospitalization rates.11 Wang et al found a decrease in diabetes-related preventable hospitalizations in the United States from 1998 to 2006, which the authors suggested could be due to improvements in the quality of primary care.12

In addition, a higher quality of ambulatory care can lead to better patient health outcomes. For example, better glycemic control in persons with diabetes can lead to reductions in healthcare costs and improved outcomes by preventing heart attacks, strokes, amputations, blindness, and end-stage renal disease.13 In a study of more than 8000 family practices, practices with a higher proportion of diabetic patients with moderate glycemic control were shown to have fewer emergency admissions for short-term complications of diabetes.14 Readmission rates for the same ambulatory care–sensitive conditions have also been shown to be higher when timely PCP follow-up was lacking.15 In a population-based study of the 2006 California State Inpatient Dataset, 26.3% of hospitalized patients (>50 years) with diabetes were readmitted within 3 months of their index hospitalization, and most readmissions (87%) were unscheduled, suggesting issues in quality and coordination of care.16 Sharma et al found that patients with chronic obstructive pulmonary disease who had an early post-hospitalization follow-up with their PCP had lower rates of emergency department visits and readmissions. 17 The readmission rates shown in this study suggest that the reduction in hospital utilization for MDVIP versus non-MDVIP Medicare members may be driven by differences in aftercare.

Additionally, the great monetary savings to the system seen in these 5 states alone ($119.4 million total for 2010) is notable. This savings represents in aggregate a $2551 savings per patient. The cost savings in hospital utilization alone would more than cover the MDVIP annual membership fee and would ensure that patients get comprehensive, integrated care from their PCP.

There are several limitations to this study. This was an observational study of hospital discharge rates in only 5 states, whereas MDVIP is a national US company. However, the 5 states chosen represent a large sample of MDVIP membership as well as large non-MDVIP base populations (traditional practice of over 2000 patients). Additionally, we were only able to extract information from the Intellimed database based on physician-provided information; individual patient identifiers and demographic variables were not available in the database. Hospital utilization was measured by discharges, not admissions; therefore, we do not account for patients who were admitted but not discharged (eg, deaths). Readmission rates were also estimates of multiple discharges for the same ICD-9-CM code based on a patient’s age and sex and the same physician provider, as individual patient identifiers were not available.

There are also 2 potential sources of selection bias: physicians and members. MDVIP-affiliated physicians may have joined the network because of their interest in the MDVIP primary care model of personalized preventive care and therefore may have better outcomes than non-MDVIP network physicians. Also, there may be differences in demographic attributes for patients electing to become MDVIP members versus those who do not. Since MDVIP members pay an annual fee, they may be more interested in wellness and more likely to comply with the physician’s recommendations.6 As noted earlier, demographics such as education level and socioeconomic status were not available in the Intellimed database to ensure a truly matched cohort for this study. The MDVIP membership was also increasing over time, which did not allow for a clean baseline period without any MDVIP exposure. The average age of members in the entire MDVIP network is 64 years, and 75% of MDVIP members are older than 55 years. The average age of patients in these 5 states pre–transition to MDVIP was 56 years, and post-transition was 65 years. Therefore, this supports that the patients who join MDVIP are older and may have more chronic conditions. As MDVIP is not an insurance company and therefore does not have claims data, the Intellimed database was the best source of these data. Currently, we are in the process of creating a data warehouse of electronic medical records so that we can perform larger and longitudinal studies of all MDVIP members to evaluate healthcare utilization and other health outcome measures.

Despite these limitations, our results have important implications. PCPs are typically the first-contact coordinators of ambulatory care.18 PCPs have the monumental task of managing all relevant health issues. Acute concerns cannot be deferred and customarily take priority over chronic disease management and prevention; as a result, the time needed for acute, chronic, and preventive care vastly exceeds the total time PCPs have available for ambulatory care.8 We believe that the MDVIP personalized preventive care model of smaller practices allows the physician to take a more proactive, rather than reactive, approach. MDVIP-affiliated physicians have the time to focus on all relevant health issues (acute, chronic, and preventive), and we believe that this increased physician interaction has resulted in lower hospital utilization and ultimately lower healthcare costs. Larger and longitudinal studies are necessary to further evaluate whether the findings here are representative and due to the effect of the MDVIP model.

The authors gratefully acknowledge the technical assistance of Karen Driver in the writing and preparation of the manuscript.

Author Affiliations: From MDVIP (AK, KW, BK), Boca Raton, FL; MDVIP-affiliated physician (RES), Scottsdale, AZ; MDVIP-affiliated physician (LA), Las Vegas, NV; Applied Quantitative Sciences, Inc (MAK), Pompano Beach, FL.

Funding Source: There were no external funding sources for this study.

Author Disclosures: Drs Klemes and Kaminetsky and Ms Warth report employment with MDVIP. Drs Seligmann and Allen are physicians affiliated with MDVIP. Mr Kubica reports receiving consultancies and receipt of payment for involvement in the preparation of this manuscript.

Authorship Information: Concept and design (AK, RES, KW, BK); acquisition of data (RES, KW); analysis and interpretation of data (MAK, KW, BK); drafting of the manuscript (AK, RES, LA, BK); critical revision of the manuscript for important intellectual content (AK, LA, MAK, KW, BK); statistical analysis (MAK, KW); administrative, technical, or logistic support (KW); and supervision (AK. LA).

Address correspondence to: Andrea Klemes, DO, FACE, 1875 NW Corporate Blvd, Suite 300, Boca Raton, FL 33431. E-mail:
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