The Impact of Comprehensive Pre-visit Preparation on Patient Engagement and Quality of Care in a Population of Underserved Patients with Diabetes: Evidence from the Care Management Medical Home Center Model

Abstract

This study evaluated the impact of pre-visit preparation, a key component of Patient-Centered Medical Home guidelines, on compliance with recommended tests and screenings in a diabetic patient population receiving care in Federally Qualified Health Centers in Miami-Dade County. The pre-visit preparation consisted of a pre-visit phone call to review patient compliance with recommended tests and screenings, provide encouragement for self-care goal setting, answer patient questions, assure referrals and tests were scheduled, and notify an in-center patient care team about which services are required at the upcoming visit. Aggregated data from 7 health centers and a cohort analysis of 7491 patients showed significantly higher compliance among those who were successfully contacted prior to the visit compared to those who were not successfully contacted at 24 months for all compliance measures included in the study. These results included a 28.8 percentage point difference in compliance with HbA1c testing, a 14.6 percentage point difference in influenza immunization, a 27.7 percentage point difference in diabetic foot exam compliance, and a 33.2 percentage point difference in compliance with annual low-density lipoprotein testing. After 24 months, the patient no-show rate decreased by 6.8 percentage points (from 20.7% to 14.0%) among contacted patients and by 5.5 percentage points (from 20.7% to 15.2%) among patients who were not contacted. Study results suggest that proactive pre-visit preparation may be a key strategy for primary care practices to improve areas critical for chronic disease management, such as patient engagement, appointments kept, and compliance with recommended screenings, tests, and services. (Population Health Management 2016;19:171–177)

Introduction

Primary care practices that have successfully transitioned from episodic care to population-based care engage patients with various approaches to pre-visit preparation.¹ Primary care improvement efforts often focus on electronic record systems, patient care teams, reengineered workflows, teaching self-management, and patient support groups to improve clinical care outcomes and the patient experience.^2,3,4 However, these interventions can only positively impact clinical health outcomes if patients attend and are prepared for their visits. Recognizing the importance of engaging patients in their care before the provider visit, the National Committee for Quality Assurance (NCQA) Patient-Centered Medical Home (PCMH) recognition program includes “pre-office visit preparation” within its core standards.⁵ Patient engagement, specifically via pre-visit preparation, is considered part of the “toolkit” for managing patient populations with complex chronic conditions such as hypertension and chronic obstructive pulmonary disease.^6,7

Effective pre-visit patient engagement strategies make provider visits more productive and efficient. Patients feel more prepared and are more likely to keep their appointments.^8,9 Optimal primary care visit no-show rates in a typical practice have been reported to range between 5% and 7%.¹⁰ In populations with barriers to accessing care, including low-income, uninsured, and minority populations, appointment no-show rates can be as high as 60%.¹¹ Missed appointments reduce continuity of care and the productivity of primary care practices. Fewer than 5% of patients with diabetes receive the American Diabetes Association standard level of care, which includes provider visits every 3–6 months and yearly screenings for 11 items.^12,13 Controlling glycated hemoglobin (HbA1c) is critical for preventing or delaying the onset of complications, which significantly reduce health-related quality of life. Patients with diabetes who have higher no-show rates are more likely to have higher HbA1c levels than patients who attend their provider appointments.^14,15,16 Frequency of HbA1c testing is correlated with improved diabetes control.¹⁷ Although intensive glucose control is initially costly, over the long term it “substantially reduced the costs of complications and increased time free of complications.”¹⁸ Patients with diabetes who miss provider appointments are almost twice as likely to have a hospital admission within 6 months after the appointment compared to those who kept their appointments.¹⁹

With more effective patient engagement of a predominantly uninsured minority population a key goal, 7 South Florida member Federally Qualified Health Centers (FQHCs) of Health Choice Network of Florida implemented the Care Management Medical Home Center (CMMHC) demonstration project to improve patient care and population health for the patients with diabetes they collectively served in South Florida. Funded by the GE Foundation Developing Health program, the CMMHC is unique in its method of providing personalized (nonautomated), comprehensive pre-visit telephone call outreach. A centralized care team of nurses and health aides used a centralized, population-based diabetes patient registry to conduct personalized pre-visit patient telephone calls on behalf of 7 primary care office teams. The value of a diabetes patient registry in improving diabetic care in low-income populations has been studied.²⁰ Personalized telephone calls have been shown to be more effective than both text message reminders and automated calls in decreasing the no-show rate.^21,22,23 A study of an automated telephone call system used specifically to remind patients with diabetes about retinopathy, microalbumin, and HbA1c testing failed to increase compliance with these tests.²⁴

Distinct from the majority of telephone-based interventions that focus on 1 outcome, often visit attendance or referral completion, the CMMHC's pre-office visit phone call is comprehensive. In addition to reminding patients of their upcoming appointment, the centralized care team gathers information on health status, adherence to self-care goals, and recent emergency room visits and hospital admissions. The centralized care team member reviews appointment completion history, previously scheduled laboratory testing and referrals, and also facilitates solutions to financial, transportation, and other challenges before the clinic visit. The pre-visit phone call occurs a week before the office appointment. A patient care team within each center receives this information from the centralized care team prior to the appointment and uses it to maximize the patient visit; for instance, by scheduling laboratory testing prior to the provider office visit.

The CMMHC model seeks to address many of the factors that reduce a patient's engagement with his or her diabetes self-management, including knowledge, functional health literacy, ethnic and cultural barriers, and clinical relationships.²⁵ Overall, the CMMHC model reflects many of the recommendations set forth by NCQA in their article, “Addressing the Quality Gaps in Diabetes Prevention and Care.”²⁶ The purpose of this study was to examine the impact of pre-visit preparation on reducing patient no-show rates and improving compliance with recommended tests and screenings.

Methods

Health Choice Network of Florida is a nonprofit, Health Resources and Services Administration-designated Health Center Controlled Network providing electronic health record (EHR), billing, clinical, and population-based care management support to 37 member centers in 9 states, including 7 centers in South Florida. These centers operate on a common EHR platform with standardized preventive health and chronic disease care registries maintained by Health Choice Network of Florida, and common EHR patient care templates and medical home policies and procedures. In 2010, Health Choice Network of Florida received a grant from the GE Foundation Developing Health program to implement and evaluate the CMMHC demonstration project to improve care for more than 10,000 patients with diabetes. A detailed description of the model and initial outcomes of the CMMHC have been reported.²⁷

Intervention

The CMMHC intervention begins with pre-office visit preparation and continues through the patient's primary care visit. The centralized care team at Health Choice Network of Florida initiates pre-visit preparation for the entire patient population with scheduled office visits. A centralized care team member contacts the patient 7 days prior to any (primary, behavioral, specialty care) upcoming appointment. The team member leaves a voice message appointment reminder for any patient who does not answer the phone call. For patients who answer the phone, the centralized care team member prepares a CMMHC Questionnaire Form using the patient's EHR to identify incomplete tests and screenings and gaps in care. The team member reviews this with the patient and encourages the patient to address these care gaps with her or his provider during the upcoming visit. The team member asks the patient about outstanding referrals to specialists or exams, recent hospital admissions or emergency room visits, and personal health goals. The centralized care team member reminds the patient of the date, time, and location of the upcoming appointment, inquires about transportation plans, and reminds the patient to bring medications and daily glucose check records. The call is intended to motivate the patient to maintain self-care habits, complete recommended laboratory tests and preventive health screenings, and arrive prepared to optimize her or his appointment. If the patient cannot attend the appointment, the centralized care team member facilitates contact with the patient care team located within the center or the scheduling department to reschedule the appointment. The centralized care team documents each call or patient status into an EHR system questionnaire and transmits this information to the patient care team the following day. Two to 6 days before the appointment, the patient care team within the center contacts the patient and support services departments to address the patient's needs, including outstanding laboratory testing, medications, transportation services, or financial assistance. The day before or the morning of the appointment, the patient care team meets to review the patient's pre-visit information and any subsequent actions and makes final plans to optimize the visit. There is not an opportunity to schedule outstanding tests and screenings ahead of the patient's appointment for those patients who do not answer the phone call from the centralized care team.

Procedures

Data for this study were obtained from the Diabetic Patient Registry and Report Card, an aggregated report including patient EHR data from all participating centers. During the first year, one of the original community health centers withdrew from the study, reducing the number of participating centers to 6. Patients included in the registry were those who had at least 2 primary care visits in the past 12 months. This registry contains demographic and patient compliance measures in 30 categories for 179 items. Aggregate data from each center were obtained from this registry. These aggregate reports cards provide snapshots at points in time for the full participating population and for each center.

To further isolate the impact of the pre-visit phone call on patient compliance with recommended tests and screenings and to identify factors associated with successfully receiving the pre-visit phone call, a cohort analysis was conducted using patient-level data from the EHR. The cohort consisted of existing patients who had exposure to the CMMHC model during the first year of operation and who were active patients in the patient registry at the time of CMMHC implementation. The cohort did not include patients who became active during the first year of model implementation. The final sample for this cohort analysis included 7491 patients with diabetes who had clinical information collected before and after CMMHC implementation to facilitate a pre-post analysis of outcomes.

Measures

This study compared aggregate no-show rates and compliance with recommended tests and screenings. Compliance measures included eye, foot, dental, or urine protein exams; screenings for creatinine, colorectal cancer, and cervical cancer; receipt of influenza or Pneumovax vaccines; and HbA1c and low-density lipoprotein tests. Patients were in compliance if they completed the exam or were screened at least once in the past 12 months. Compliance for the HbA1c test was defined as having had at least 2 HbA1c tests in the past 12 months. No-show rates were calculated as the number of missed appointments divided by the total number of appointments scheduled.

Analyses

The effect of the CMMHC model on diabetes patient population compliance with recommended tests and screenings was assessed using data from the patient registry. To show the changes in the no-show rate and patient compliance in the clinics over time, the percentage of patients with diabetes in the registry who were compliant with each measure during the prior 12 months was computed at baseline, 12 months, and 24 months post implementation. These measures were computed for each FQHC and then aggregated. For each test or screening, the proportion of the diabetes patient population in compliance was measured as the number who had successfully completed the test or screening within the specified time period divided by the number of patients in the registry at that time. The percentage change in the compliance measures was calculated as the change in compliance rates from baseline to 12 and 24 months post implementation divided by the baseline compliance rates. Z-tests of differences in the proportions at 12 and 24 months post implementation were performed to determine whether the differences were statistically significant from the baseline values. Because the unit of analysis used to assess no-show rates was the appointment rather than the patient, tests of statistical significance were not conducted.

For the cohort study, a pre-post analysis was performed to evaluate the effect of CMMHC on patient compliance 12 months after implementation. Statistically significant differences between the mean outcome at baseline and the mean outcome 1 year after implementation were tested for statistical significance. The analysis was performed separately for patients contacted and not contacted via a telephone call. To make both groups comparable, contacted and not contacted patients were matched with similar demographic and clinical characteristics at baseline using a propensity score matching algorithm.²⁸ For the data set and intervention design under analysis, multivariable regressions produce similar treatment effect estimates. However, the standard errors of these effects are corrected when panel data estimation is performed. Consequently, all significance levels reported in this study were obtained from multivariable regression results. The panel data estimation included individual fixed effects and correct robust standard errors by potential intracluster correlation at the health center level.

Results

Demographic characteristics of patients in the aggregate registry data have been reported in a prior article.²⁷ Demographics of the 7491 patients with diabetes in the cohort study are reported in Table 1. The aggregate patient registry represents adults (older than 18 years), with the largest fraction of patients older than age 50 and from socioeconomically disadvantaged, ethnic minority groups without health insurance. More than 50% of patients in this cohort had a pre-visit planning contact via a telephone call. Of these 7491 patients, 5007 were successfully matched on observable characteristics.

Table 1.

Patient Demographics

Demographics (in percentages unless otherwise indicated)
Age (in years)	56.52
Female	62.02
White	52.82
Black	42.80
Asian	0.97
Other	0.48
Hispanic	50.16
Homeless	19.89
Veteran	0.32
Insured	40.07
Pre-visit phone call contact	52.69
Sample size (N)	7,491

Note: Sample includes active patients, defined as having had ≥ 2 primary care visits in the prior 12 months, when the Care Management Medical Home Center was implemented.

The percentage of patients in compliance with each of the 11 diabetes-related compliance measures was greater at 12 months and 24 months for patients who were successfully contacted by the centralized care team than for patients who were not contacted (Table 2). Differences in compliance at 24 months between those contacted and not contacted were significant at P < 0.001 for all 11 compliance measures. The statistically significant differences at 24 months include an 18.0 percentage point improvement in HbA1c test compliance and 20.3 percentage point improvement in Pneumovax compliance.

Table 2.

Compliance Measures at Baseline, 12 Months. and 24 Months for Patients Contacted and Not Contacted by the CMMHC

Percentage of Patients in Compliance with Recommended Services
	12 Months			24 months
Measure	Baseline	Contacted	Not Contacted	Difference	Contacted	Not Contacted	Difference
Pneumovax vaccine	24.3	36.8	25.7	11.1^***	48.3	28	20.3^***
HbA1c test	34.1	42.1	26.5	15.6^***	47.4	29.4	18^***
Flu vaccine	25	48.3	37.1	11.2^***	51.2	34.5	16.7^***
Foot exam	46.4	62.3	48.2	14.1^***	75.9	63.1	12.8^***
Urine protein exam	62.7	71.7	58.9	12.8^***	69.5	60.4	9.1^***
LDL test	71.7	76.4	63.1	13.4^***	75.9	65.6	10.3^***
Creatinine screening	76	81.6	71.3	10.3^***	81.1	74.5	6.6^***
Dental exam	9.9	14.8	5.1	9.7^***	14.4	4.6	9.8^***
Eye exam	5.3	12.9	7.2	5.8^***	11.8	6.1	5.7^***
Cervical cancer screening	25.4	29.5	18.9	10.6^***	30.8	19.4	11.4^***
Colorectal cancer screening	11.4	17.9	13.8	4.1^***	28.2	20.5	7.7^***

Numbers represent the percentage of patients compliant with each measure. Changes were calculated as the difference between baseline and 12 or 24-month values.

***

denotes statistical significance at the 1% level.

Twelve-month data appear as reported in a prior publication.²⁹

CMMHC, Care Management Medical Home Center; LDL, low-density lipoprotein

Between baseline and 24 months, the no-show rate decreased for all patients in the registry and at all centers (Table 3). However, the no-show rate for patients contacted decreased by a greater percent than for patients not contacted. One center experienced a 9.8 percentage point reduction in their no-show rate for contacted patients over 24 months. Another center experienced a 9.3 percentage point reduction in no-show rates for contacted patients over 24 months.

Table 3.

No-Show Rate Percentage—Contacted vs. Not Contacted at 12 Months and 24 Months

	No-Show Rate Percentage - Contacted vs. Not Contacted
		12 Months Post Implementation		24 Months Post Implementation		% Point Difference over 24 months
Measure Center	Before CMMHC Entire Registry	Contacted	Not Contacted	Contacted	Not Contacted	Contacted	Not Contacted
FQHC 1	22.7	19.1	18.1	16.8	17.0	−5.9	−5.7
FQHC 2	28.2	21.0	23.8	18.4	23.1	−9.8	−5.1
FQHC 3	14.4	13.7	13.4	13.2	12.3	−1.2	−2.1
FQHC 4	19.8	13.0	16.0	10.5	11.9	−9.3	−7.9
FQHC 5	18.9	13.1	15.2	n/a	n/a	n/a	n/a
FQHC 6	21.5	13.1	15.2	12.4	13.1	−9.1	−8.4
FQHC 7	19.2	14.0	14.4	12.6	13.5	−6.6	−5.7
All Centers	20.7	15.3	16.6	14.0	15.2	−6.7	−5.5

Numbers represent the percentage of appointments kept from aggregated data of active patients in the registry, defined as patients who had at least 2 primary care visits in the prior 12 months.

CMMHC, Care Management Medical Home Center; FQHC, Federally Qualified Health Center

For the cohort analysis, contacted patients were matched to non-contacted patients based on similar demographic and clinic characteristics at baseline to make the pre-post changes in compliance for contacted and non-contacted patients comparable. Table 4 reports the percentage of patients compliant with the 11 recommended tests and screenings. The table compares preintervention and postintervention means differentiated by pre-visit planning telephone call contact. The group of patients who were not contacted (1600 or 32% of the matched sample) demonstrated statistically significant reductions in compliance after the intervention for most of the compliance measures. Only influenza and Pneumovax vaccine compliance improved after the intervention. In contrast, the group of patients who had a pre-visit phone contact (3407 patients or 68% of the matched sample) had statistically significant improvements in compliance for several of the compliance measures. Compared to patients who were not contacted, compliance among contacted individuals improved for all measures. For example, the change in compliance for the HbA1c test among contacted patients was 28.8 percentage points higher than the change observed among patients who were not contacted.

Table 4.

Pre- and Postintervention Averages by Pre-visit Telephone Call Contact

	Not Contacted			Contacted
	Pre	Post	Change †	Pre	Post	Change †	Contacted – Not Contacted ‡
Compliance (in percentages)
HbA1c test	53.7	26.7	−27.0^***	53.8	55.5	1.7	28.8^***
LDL test	84.2	40.7	−43.5^***	84.4	74.1	−10.3^**	33.2^***
Eye exam	8.1	6.7	−1.5	7.4	15.8	8.4^***	9.9^**
Foot exam	53.0	31.9	−21.1^*	53.7	60.3	6.6	27.7^***
Dental exam	11.6	3.8	−7.8^***	12.4	14.7	2.3	10.2^***
Urine protein exam	76.2	34.3	−41.8^***	75.8	65.9	−9.9^*	31.9^***
Creatinine screening	88.3	43.9	−44.4^***	89.0	78.8	−10.2^***	34.2^***
Colorectal cancer screening	17.5	15.0	−2.6	15.7	21.5	5.8^**	8.4^***
Cervical cancer screening	38.4	40.7	2.3	45.3	59.2	13.9^***	11.6^***
Influenza vaccine	31.6	39.2	7.6^*	32.1	54.3	22.2^***	14.6^***
Pneumovax vaccine	16.9	25.6	9.7^***	17.2	40.5	23.3^**	13.6^**
Sample size	1,600			3,407			5,007

Patients who were contacted and not contacted were matched by demographic and clinical characteristics based on propensity score matching.

†Postintervention minus preintervention differences, and difference in means tests.

‡Difference in changes between patients who were contacted and not contacted. Significance level obtained from robust standard errors from panel data estimation with patient fixed effects, corrected by intercluster correlation at health center level.

***

Significant at 1%; ^**significant at 5%; ^*significant at 10%.

LDL, low-density lipoprotein.

Analysis of patient characteristics correlated with being contacted suggested that African Americans, Hispanics, and females were more likely to have a pre-visit phone contact. Homeless patients were less likely to be successfully contacted, and veteran or insurance status did not play a significant role in this selection. Compliance at baseline also was an important predictor of pre-visit phone contact. Patients who complied on dental, HbA1c test, influenza vaccine, or urine protein exams were more likely to be contacted. Finally, having uncontrolled HbA1c levels (above 9%) increased the probability of having a pre-visit phone contact.

Discussion

Results of this centralized pre-visit planning approach showed promising gains in patient engagement as measured by appointments scheduled and kept, and compliance with recommended tests and screenings over 24 months, areas critical for improved chronic disease population health management. The cohort analysis results from 24 months of CMMHC implementation suggest that the comprehensive pre-office visit preparation by telephone contact is the main driver in the compliance outcome improvements observed in Table 2. Prior research demonstrated that the CMMHC intervention has increased the number of diabetes patients in the registry receiving care.²⁷ Many of these patients then attended provider visits and their compliance with diabetic testing and screening recommendations improved significantly. In years 2 and 3 of implementation, the effect of pre-visit preparation on long-term clinical outcomes, provider and patient satisfaction, health care costs, and return on investment will be evaluated.

Analyses of aggregated report card data showed that compliance with all 11 measures was significantly higher among those who were successfully contacted by a member of the centralized care team compared to compliance among those who were not contacted. The relationship between more frequent HbA1c testing and improved diabetes control, and subsequently reduced diabetic complications, improved quality of life, and reduced costs, has been well established.^12,13,29 Compliance with eye and dental exams improved for contacted patients. However, levels remain low, perhaps in part because these services require a referral outside of the centers and out-of-pocket payments from patients. No-show rates declined both for those contacted and not contacted. This may reflect the positive impact in baseline patient engagement levels achieved from office transformation through PCMH recognition. It is also possible that, for those patients who did not receive the phone call, the message left by the centralized care team served as a reminder of the upcoming appointment.

The results of the aggregate report card analysis were supported by a cohort study of those patients who were able to be followed pre and post CMMHC implementation. Although there was a tendency for patients to fall out of compliance over time, most of these reductions were among those who did not receive a pre-office visit phone call from the centralized care team. Among those who did receive a phone call, the tendency was to become more compliant with tests and screenings, supporting the important role of a pre-visit phone call and preparation in promoting compliance. This study supported previous literature concerning the positive impact of contacting the patient via a telephone call on improving attendance to an upcoming provider visit.^30,31,32,33

Although cost savings for the CMMHC have not yet been calculated, the reduction in no-show rates and increased office efficiencies likely reduced clinician, office team, and administrative expenses.³⁴ The estimated CMMHC administrative savings, and the short- and long-term impact on overall health care utilization and health care costs will be evaluated in future studies.

The CMMHC pre-visit preparation framework has multiple unique components. Using a centralized care team for pre-visit preparation and transferring this information through the EHR to the center-based patient care teams is a model for multisite or integrated health systems. A centralized team ensures that outreach is standardized across sites and that the center is not burdened by the additional time required for the preparations. Published outcomes supported interventions that implemented various components of the CMMHC pre-visit preparation model. For example, a successful Mayo Health System quality improvement initiative involved telephone outreach, identification of patient needs, and lab visit scheduling prior to the appointment. The rate of patients meeting 5 clinical outcomes increased 3-fold between 2008 and 2009.³⁵ Another center that reported utilizing a similar centralized diabetes outreach model within its PCMH model, including a diabetes registry and a central outreach team focusing on high-risk patients and missed appointments, reported improved diabetes outcomes.¹⁶

The CMMHC population health intervention and study design had some limitations. The CMMHC intervention did not include an outreach workflow, such as a home visit, for the diabetes patient population in the cohort who did not respond to their pre-visit phone call or keep their scheduled follow-up appointment. Evidence suggests that home visits may be an innovative and effective strategy to engage low-income, elderly, and other hard-to-reach patient populations. As a community-based health promotion implementation, the study design did not include a control group or prospectively randomize patients or participating health centers. A randomized controlled trial of the CMMHC model should be conducted in the future to establish causality between the intervention and the improvements in outcomes. In the future, nonparticipating centers could serve as case controls once protocols for obtaining data from nonparticipating centers are established. The relatively low no-show rates for the non-contacted patient population may have reflected the degree of office transformation attained during the project and relative to other primary care practices. Future randomized trials also may account for those practices with and without NCQA PCMH recognition.

The results of this study indicate that proactive pre-visit preparation may be a key strategy for high-performing primary care practices to reduce no-show rates and improve compliance with recommended tests and screenings. Further studies are needed to evaluate whether the improvements in compliance with chronic care guidelines are correlated with improved health outcomes and reduced health care costs. Finally, this study is notable for demonstrating increased patient compliance with recommended tests and screenings and a decreased no-show rate for appointments in an underserved, underinsured population receiving care in a community health care setting. Such positive outcomes are essential for improving population-wide diabetes care and curbing the rising burden of diabetes in the United States.

Footnotes

Author Disclosure Statement

Drs. Page, Arrierta, Amofah, Rodriguez, and Williams, and Ms. Rivo, Ms. McCann, and Mr. Kassaye declared no conflicts of interest with respect to the research, authorship, and/or publication of this article.

The authors received the following financial support for the research, authorship, and/or publication of this article: This work was supported by a grant from the GE Foundation Developing Health Program.

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