A Systematic Approach to Diabetes Mellitus Care in Underserved Populations: Improving Care of Minority and Homeless Persons

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623 A Systematic Approach to Diabetes Mellitus Care in Underserved Populations: Improving Care of Minority and Homeless Persons Philip J. Baty, MD; Susan K. Viviano, RN; M. Rosita Schiller, RSM, PhD; Andrea L. Wendling, MD Background and Objectives: Discrepancy in care of between racial and ethnic minority groups and Caucasians is well documented in America. System-based practices have been shown to improve quality of care outcomes. We implemented a disease registry and management system proven successful in a suburban practice network in four community health centers to improve process outcomes. Methods: Diabetes care measures including HbA1C, LDL, microalbumin testing, and testing for retinopathy were compared for suburban practices and Community Health Center practices within the same health system. A comprehensive systems-based disease management process including a registry that had been successful with the suburban practices was implemented at the Community Health Centers. Diabetes care measures were followed to determine whether disparity in care could be improved with process-based initiatives. Results: Following implementation of a registry and system-based disease management process, the percent of Community Health Center patients meeting guidelines improved significantly in all quality measures except the percentage of patients with HbA1C>9%. Despite this improvement, there remained a statistically significant discrepancy in performance between the Community Health Clinics and the suburban practices in most measures including percentage of patients with HbA1C<7%, HbA1C>9%, LDL<130, LDL<100, and percentage of patients with retinopathy screen or microalbumin test within the past year, with the Community Health Centers lagging behind in all comparisons. Conclusions: A structured systemsbased approach to care of minority and at-risk populations utilizing registries resulted in significant improvement in clinical outcomes and helped to reduce but not eliminate disparities in outcome measurements between vulnerable and Caucasian populations. (Fam Med 2010;42(9):623-7.) The Diabetes Control and Complications Trial 1 confirmed that -related complications can be reduced through smoking cessation and through strict control of blood glucose, blood pressure, and cholesterol, and these can be regulated by aggressive medical care and self-management. However, the National Health Care Quality Report 2008 shows only 40% of adults with received hemoglobin A1c testing, dilated eye exam, and foot examination in 2008. 2 The National Institutes of Health (NIH) reported in January 2004 that fewer than 12% of people with meet recommended goals for blood glucose. 3 From the Advantage Health Physicians, Saint Mary s Health Care, Grand Rapids, MI. Racial and ethnic minority groups are less likely than Caucasians to receive needed services. 4,5 The Institute of Medicine (IOM) found gaps in care even after controlling for variations in insurance status, patient income, severity of disease, and the presence of comorbid illnesses. To eliminate health care disparities, the IOM recommended that health care providers should be made aware of racial and ethnic disparities even when none are intended. Further, the IOM recommended identifying barriers to high-quality care among vulnerable groups. 4 Given NIH findings, it is probable that racial and ethnic minorities with are less likely than Caucasians to receive the care needed to maintain tight glucose control and to prevent consequential complications of.

624 October 2010 Family Medicine It has been shown that systems-based care can improve health care outcomes and specifically outcomes related to management. Such care includes electronic medical databases, 6 patient registries, 7 feedback to physicians, 8 computerized reminders, 7,9,10 and having physicians involved in the quality improvement process. 7,9 Although systems-based care and electronic registries have been shown to improve outcomes in disadvantaged populations, 11,12 there is little in the literature comparing outcome disparity between advantaged and disadvantaged care sites when similar processes are instituted. To study the effectiveness of systems-based care in an underserved population, our study was designed to determine whether the application of a successful systems-based approach that utilized a computerized patient registry in a suburban, commercial, and mainly insured patient population could reduce disparity in care for cultural, ethnic, and socioeconomic minorities when applied to Community Health Centers serving indigent populations. Methods Saint Mary s Health Care, a nonprofit ministry organization of Trinity Health (Novi, MI), operates four community-based ambulatory health centers in Western Michigan: Clinica Santa Maria (79% Hispanic), Browning Claytor Health Center (42% African American, mainly inner city), Heartside (40% African American and 8% Hispanic, all homeless), and Sparta Health Center (45% Hispanic migrant workers and 40% Caucasian rural). In these four clinics, the combined patient population served in 2005 was approximately 26,000, of whom 736 had been diagnosed with. Most patients are uninsured or covered by Medicaid. Saint Mary s Health Care also has part ownership of Advantage Health, a primary care physician network in Western Michigan consisting of 90 physicians who provide medical services at 13 commercial physician offices. These physicians provide care for approximately 120,000 patients, most of which are Caucasian and insured. The 90 Advantage Health physicians annually treat 3,500 4,000 patients with. In 1995, Advantage Health began a quality improvement process with the primary goal of improving clinical outcomes. The work was based on standard Clinical Practice Guidelines 13 and incorporated a sophisticated system that included structured administrative support, a free computerized patient registry (CDEMS [Chronic Disease Electronic Management System]), 14 and office staff and provider education. The quality improvement initiative was successful. In 2005, Advantage Health received the prestigious Michigan Association of Health Plans 2005 Pinnacle Award for Best Practices for their innovation in dramatically improving diabetic outcomes in their patients. 15 This quality initiative process initially instituted at the commercial Advantage Health offices was extensive. Although the commercial Advantage Health practices are part of a health system network, each office operates independently with variations in physician practice styles, staffing, and paper versus computerized records. In addition, physicians receive patient information from several hospitals, insurance providers, and testing facilities. When developing the initial quality improvement measures, all of these data needed to be incorporated in a standardized and usable fashion. To facilitate this, Advantage Health hired a full-time medical management specialist (an RN case manager), two full-time data specialists, and dedicated 1 day per week of physician time for a quality director to oversee the quality improvement project for all 13 commercial offices. The role of this team was to monitor data from health plans to choose quality improvement targets, outline specific quality initiatives, collect patients clinical data from various sources including practice management information, and integrate this into the CDEMS. Once data was collected and integrated, the team generated reports for patient charts. In addition, each commercial office chose an office quality coordinator from within existing staff and rededicated 8 hours per week of this employee s time per 4,000 patient lives covered for quality initiatives within the office. The office quality coordinator received quality reports, placed reports (either physically or electronically) into charts, and generated phone calls or mailings to those patients that are identified as needing services. The cost for these positions was recouped through the improved performance pay received from insurance contracts. In addition, Advantage Health physicians individually received financial incentives for meeting target indicators for patients with. Since inception, the performance incentives received from insurance contracts have exceeded the annual administrative and physician incentive costs for the program at the commercial sites. Historically, the Saint Mary s Community Health Centers were not included in the quality improvement initiatives instituted for the Advantage Health commercial practices. In 2005, with funding from a Trinity Community Health Fund grant, the same processes that had been used in Advantage Health commercial suburban primary care physician offices were implemented at the four Community Health Center clinics. Initially, an office quality coordinator was chosen for each site. Office quality coordinators, physicians, and Saint Mary s Community Health Center site managers received training on clinical guidelines and recommendations adapted from American Diabetes Association Standards of Medical Care in Diabetes. 4 The computerized patient registry used at Advantage Health physician offices (CDEMS) was expanded to include patients

625 from the four Community Health Centers. Baseline data were collected from paper medical records at each of the four clinics. To protect confidentiality and the integrity of patient information, a dedicated server and firewall-protected network line were installed to support the CDEMS database. Each month the medical management specialist at Advantage Health produced and sent a printout with current data for patients with to each Community Health Center site. By reviewing the printout, each physician and office quality coordinator could proactively identify patients who were in need of services. Additionally, a sheet was placed at the beginning of each patient s medical record to display their status with regard to guidelines including blood pressure, HbA1c, LDL, and smoking status. The Advantage health quality director and the medical management specialist visited each Community Health Center semi-annually during the study period to meet with individual physicians, mid-level providers, office managers, lead office staff, and administrative personnel to identify issues, solve problems, and ensure continual improvement in the care of patients with. Quality indicator data summarizing care and outcomes were obtained from all patients with identified from the four Community Health Centers and 13 suburban Advantage Health practices. Quality indicator data included the number of patients with, percent of patients having annual HbA1C testing, annual LDL testing, HbA1C <7% or >9%, LDL<100, and the percentage with retinopathy screen and microalbumin testing in the past year. Although blood pressure data were initially included as a target for quality initiatives, blood pressure from every visit was not consistently included in recorded data, and subsequently this measure was eliminated from the study. Data were grouped into Community Health Centers or commercial practices. Data were compared between these two aggregate sites as well as within each site before and after intervention. Data were recorded as of entered data on the 31st of December of each year. Annual was defined as having a result within the designated calendar year. Individual patients were not tracked for the purposes of the study, and outcomes were defined in aggregate based on the numbers of patients within each office during the defined study period. The study did not track whether specific individual patients were included in subsequent study groupings. Descriptive statistics were used to summarize demographic information of the patient population. Chi square was used to compare 2004 and 2005 outcomes for Community Health Centers. Chi square with Bonferroni correction was used when multiple variables were involved. The statistical software used was NCSS 2004 (Kaysville, UT). This study was reviewed and approved by the Saint Mary s Health Care Institutional Review Board. Results Table 1 shows the demographic composition of patients at both the Community Health Centers and commercial Advantage Health offices. The Community Health clinics serve primarily racial and ethnic minority populations and at-risk Caucasian patients, many of whom are uninsured or underinsured. The 13 suburban physician offices provide services to a primarily Caucasian population, and some type of health insurance covers most of these patients. Table 2 shows performance data for an aggregate of the four Community Health Centers. Data for 2004 are baseline figures captured from medical records at each clinic. These data were shared with physicians and personnel at each Community Health Center, and deliberate steps were initiated as outlined above to improve outcomes. After implementation of systems-based changes at the Community Health Centers, outcomes for 2005 Table 1 2005 Demographic Profile of Patients With Diabetes at Four Saint Mary s Community Health Centers and 13 Advantage Health Commercial Primary Care Physician Number and percent of patients with primary or secondary diagnosis Number and percent with Type 2 Four Urban Clinics 13 Suburban Primary Care Physician 2005 2005 736 3,952 624 (85%) 3,636 (92%) P Value Mean age patients with 54 60.5 <.05 * Number and percent males with 301 (41%) 1,992 (50.4%) Percent females with 433 (59%) 1,960 (49.6%) Ethnicity (%) African American Latino/Hispanic Caucasian Other (Asian, unknown) 184 (25%) 330 (45%) 147 (20%) 73 (10%) 316 (8%) 316 (8%) 3,162 80%) 158 (4%) Statistically significant using * unpaired Student s t test or ** chi square.

626 October 2010 Family Medicine showed dramatic improvement (Table 2). The Community Health Centers showed a larger number of patients with. There was improvement in every Table 2 2004 and 2005 Quality Indicator Data for Four Community Health Centers That Serve Primarily Racial and Ethnic Minority and Other At-risk Populations Number of patients with Mean Values for Grouping of Four Community Health Centers 2004 2005 % Change P Value 511 736 +44 % having annual HbA1c 337 (66%) 623 (85%) +25 <.05* % with HbA1c <7% 158 (31%) 288 (39%) +22 <.05* % with HbA1c > 9% 61 (12%) 142 (19%) -50 <.05* % with LDL measured annually 271 (53%) 658 (90%) +66 <.05* % with LDL < 100 97 (19%) 303 (41%) +115 <.05* % with retinopathy screen past year % with microalbumin test past year All are improvements except A1c > 9. 26 (5%) 233 (32%) +440 <.05* 122 (24%) 452 (62%) +145 <.05* * Statistically significant chi square test between 2004 and 2005. Table 3 Comparison of Performance Between Community Health Centers and Commercial in 2004 and 2005 Community Health Centers 2004 2005 Commercial Chi Square (P Value) Community Health Centers indicator with the exception of the percent of patients with HbA1c >9%. Mean outcomes in quality measures in the Community Health Centers ranged from +22% improvement in the percent of patients with HbA1c below 7% to over +400% mean improvement in the percent of patients who had a retinopathy screen Commercial Diabetes 511 4,055 736 3,952 in the past year. Table 3 shows a comparison of performance at the Community Health Centers and commercial offices between 2004 and 2005. Performance at the commercial offices continued to improve as providers became more accustomed to using standard protocols when caring for patients with. Despite significant improvements in quality indicators at the Community Health Centers, however, outcomes remained markedly lower than those realized at the suburban offices. Both baseline data and results after 1 year showed major disparities in care of racial and ethnic minority and underserved populations. Discussion The patient care model presented here had been refined over a period of 10 years at commercial primary care offices. Basics of the model were consistent use of practice guidelines, a computerized patient registry, strong administrative support, effective management systems, regular feedback, Chi Square (P Value) Annual A1c 337 (66%) 3,203 (79%) <.05* 623 (85%) 3,620 (92%) <.05* A1c <7% 158 (31%) 1,825 (45%) <.05* 288 (39%) 2,149 (54%) <.05* A1c >9 61 (12%) 284 (7%) <.05* 142 (19%) 303 (8%) <.05* LDL annually 271 (53%) 3,325 (82%) <.05* 658 (90%) 3,774 (95%) <.05* LDL <100 97 (19%) 1,500 (37%) <.05* 303 (41%) 2,015 (51%) <.05* Retinopathy screen Microalbumin screen 26 (5%) 933 (23%) <.05* 233 (32%) 2,112 (53%) <.05* 122 (24%) 2,190 (54%) <.05* 452 (62%) 2,965 (75%) <.05* * Statistically significant differences between the Community Health Centers and commercial offices using chi square with Bonferroni correction for multiple variables. and incentives for quality performance. With funding from a 2005 Trinity Community Health Fund Grant, we implemented this model at four Community Health Centers to attempt to identify and eliminate the discrepancy in care within our patient populations. Our results initially verified that there were major variations in care provided at suburban primary care offices and community outreach clinics serving mostly ethnic and racial minority and other at-risk populations. This discrepancy in care is consistent

627 with other published data 16 and, as Deming 17 noted, inferior quality can often be the result of inadequate processes. This study then demonstrated the value of implementing a structured systems-based program for the care of patients with. After initiating the program, quality indicator outcomes among racial and ethnic minorities improved dramatically. Every tracked indicator improved except HbA1c control > 9.0%. This is perhaps a reflection of the increased percentage of patients having an annual HbA1c test and/or new patients being identified. This shows that significant quality improvements can be realized when providers are given quantitative information and frequent feedback using a systems-based approach. Our findings are consistent with a Cochrane review of audit and feedback in that low baseline compliance with recommended practice and higher intensity of audit and feedback is associated with larger improvements in outcomes. 18 Unfortunately, despite these significant improvements, the significant disparity between our suburban clinics and community-based clinics remained. Some of this discrepancy could be explained by the duration of the study suburban clinics and suburban patients in our model had been utilizing the systems-based care process for longer, which may have contributed to better outcomes. Other barriers to care that were identified during focus group meetings at Community Based Clinics, however, included inability to obtain prescribed medications and lack of funds for out of pocket health care costs. Our study had several limitations. First, it was conducted in a single health system, using a specific disease registry. Results may not be generalizable to other health systems or electronic databases. Secondly, our Community Health Centers received multiple levels of support from our commercial physician office administration including support from the quality director and medical management specialist, the computerized patient registry, physician and staff training, and financial support in incentive payments for physicians. Realistically, many underserved health clinics would not currently have this level of support, which would potentially make implementation of such a system more difficult. An additional limitation is that the data regarding blood pressure control was excluded from the study due to the difficulty of transferring every blood pressure reading from the paper patient charts to the computerized database. We have since improved our system and are now able to track these data as well. We also did not record whether individual patients from the original study group were included in subsequent data sets so we were unable to track individual patient outcomes. Despite these limitations, however, our data demonstrate that implementing standardized processes that support best practices and high-quality care greatly improved outcomes for ethnic and racial minorities as well. Implementing such system-based care in underserved health populations could help to minimize current disparities in health outcomes. Acknowledgments: We acknowledge GRMERC for statistical analysis. Corresponding Author: Address corespondence to Dr Baty, Advantage Health-Northeast, 5171 Plainfield Avenue NE, Grand Rapids, MI 49525. 616-685-8350. Fax: 616-752-6586. batyp@trinity-health.org. Re f e r e n c e s 1. Diabetes Control and Complications Trial Research Group. Lifetime benefits and costs of intensive therapy as practiced in the Diabetes Control and Complications Trial. JAMA 1996;276:1409-15. 2. National Health Care Quality Report 2008. AHRQ publication no. 09-0001, March 2009. Available at www.ahrq.gov/qual/qrdr08.htm. Accessed September 17, 2009. 3. NIH News. Most people with do not meet treatment goals. Washington, DC: US Department of Health and Human Services, NIH, January 20, 2004. Available at www.nih.gov/news/pr/jan2004/niddk-20. htm. Accessed March 21, 2005. 4. Institute of Medicine. Unequal treatment: what health care providers need to know about racial and ethnic disparities in health care. Available at www.iom.edu/cms/3740/4475/4175.aspx. Accessed April 5, 2006. 5. Kirk JK, D Agostino RB Jr, Bell RA, et al. Disparities in HbA1c levels between African-American and non-hispanic white adults with : a meta-analysis. Diabetes Care 2006;29(9):2130-6. 6. Schmittdiel JA, Shortell SM, Rundall TG, Bodenheimer T, Selby JV. Effect of primary health care orientation on chronic care management. Ann Fam Med 2006;4(2):117-23. 7. Fleming B, Silver A, Ocepek-Welikson K, Keller D. The relationship between organizational systems and clinical quality in care. Am J Manag Care 2004;10(12):934-44. 8. Lieu TA, Finkelstein JA, Lozano P, et al. Cultural competence policies and other predictors of asthma care quality for Medicaid insured children. Pediatrics 2004;114(1):e102-10. 9. Jackson GL, Yano EM, Edelman D, et al. Veterans Affairs primary care organizational characteristics associated with better control. Am J Manag Care 2005;11(4):225-37. 10. Hung DY, Rundall TG, Crabtree BF, Tallia AF, Cohen DJ, Halpin HA. Influence of primary care practice and provider attributes on preventive service delivery. Am J Prev Med 2006;30(5):413-22. 11. Thompson JW, Ryan KW, Pinidiya SD, Bost JE. Quality of care for children in commercial and Medicaid managed care. JAMA 2003;290:1486-93. 12. Clark CR, Baril N, Kunicki M, et al. Mammography use among black women: the role of electronic medical records. J Womens Health (Larchmt) 2009;18(8):1153-62. 13. American Diabetes Association. Standards of medical care in. Diabetes Care 2004;27(Suppl 1):S15-S35. 14. www.cdems.com/. A free chronic disease registry service. 15. Michigan Association of Health Plans. Accessed at www.mahp.org/. 16. Peek ME, Cargill A, Huang ES. Diabetes health disparities: a systematic review of health care interventions. Med Care Res Rev 2007;64(5) Supp:101S-156S. 17. Deming WE. The new economics: for industry, government, education. Cambridge, MA: MIT, 1993. 18. Jamtvedt G, Young JM, Kristoffersen Dt, O Brien MA, Oxman AD. Audit and feedback: effects on professional practice and health care outcomes. Cochrane Database Syst Rev 2006, Issue 2. Art. No: CD000259. DOI:10.1002/14651858.CD000259.pub2.