Team-Based Approach to Successful Annual Wellness Visits.

OBJECTIVE: The purpose of this study was to implement a 2-phase approach to rapidly increase the number of annual wellness visits (AWVs) and build a sustainable model at 3 study units (Mayo Clinic in Rochester, Minnesota, and clinics in 2 regions of Mayo Clinic Health System), which collectively serve approximately 80 000 patients who qualify for an AWV annually. METHODS: In the rapid improvement phase, beginning in July 2022, goals at the facilities were reoriented to prioritize AWVs, educate staff on existing AWV resources, and create low-effort workflows so that AWVs could be incorporated into existing patient appointments. Staff at all 3 study units worked independently and iterated quickly. In the second phase, all study units collaborated to design and implement a best-practice solution while they leveraged the engagement and lessons learned from the first phase and invested in additional system elements and change management to codify long-term success. RESULTS: The number of AWVs completed monthly increased in each study unit. In the rapid improvement phase, the number of AWVs increased but then plateaued (or decreased at some study units). In April 2023, the final scheduled outreach automation and visit tools were implemented, and the number of AWVs was sustained or increased, while outreach and scheduling times were decreased. The number of completed AWVs increased from 1148 across all study units in the first 6 months of 2022 to 14 061 during the first 6 months of 2023. CONCLUSIONS: The lessons learned from this project can be applied to other health systems that want to provide more patients with AWVs while improving operational efficiency. The keys are to have a clear vision of a successful outcome, engage all stakeholders, and iterate quickly to find what works best for the organization.

Self-Triage Use, Subsequent Healthcare Utilization, and Diagnoses: A Retrospective Study of Process and Clinical Outcomes Following Self-Triage and Self-Scheduling for Ear or Hearing Symptoms.

Background: Self-triage is becoming more widespread, but little is known about the people who are using online self-triage tools and their outcomes. For self-triage researchers, there are significant barriers to capturing subsequent healthcare outcomes. Our integrated healthcare system was able to capture subsequent healthcare utilization of individuals who used self-triage integrated with self-scheduling of provider visits. Methods: We retrospectively examined healthcare utilization and diagnoses after patients had used self-triage and self-scheduling for ear or hearing symptoms. Outcomes and counts of office visits, telemedicine interactions, emergency department visits, and hospitalizations were captured. Diagnosis codes associated with subsequent provider visits were dichotomously categorized as being associated with ear or hearing concerns or not. Nonvisit care encounters of patient-initiated messages, nurse triage calls, and clinical communications were also captured. Results: For 2168 self-triage uses, we were able to capture subsequent healthcare encounters within 7 days of the self-triage for 80.5% (1745/2168). In subsequent 1092 office visits with diagnoses, 83.1% (891/1092) of the uses were associated with relevant ear, nose and throat diagnoses. Only 0.24% (4/1662) of patients with captured outcomes were associated with a hospitalization within 7 days. Self-triage resulted in a self-scheduled office visit in 7.2% (126/1745). Office visits resulting from a self-scheduled visit had significantly fewer combined non-visit care encounters per office visit (fewer combined nurse triage calls, patient messages, and clinical communication messages) than office visits that were not self-scheduled (-0.51; 95% CI, -0.72 to -0.29; P < .0001). Conclusion: In an appropriate healthcare setting, self-triage outcomes can be captured in a high percentage of uses to examine for safety, patient adherence to recommendations, and efficiency of self-triage. With the ear or hearing self-triage, most uses had subsequent visit diagnoses relevant to ear or hearing, so most patients appeared to be selecting the appropriate self-triage pathway for their symptoms.

Designing for Effective and Safe Multidisciplinary Primary Care Teamwork: Using the Time of COVID-19 as a Case Study.

Effective medical teamwork can improve the effectiveness and experience of care for staff and patients, including safety. Healthcare organizations, and especially primary care clinics, have sought to improve medical teamwork through improved layout and design, moving staff into shared multidisciplinary team rooms. While co-locating staff has been shown to increase communication, successful designs balance four teamwork needs: face-to-face communications; situational awareness; heads-down work; perception of teamness. However, precautions for COVID-19 make it more difficult to conduct face-to-face communications. In this paper we describe a model for understanding how layout affects these four teamwork needs and describe how the perception of teamwork by staff changed after COVID-19 precautions were put in place. Observations, interviews and two standard surveys were conducted in two primary care clinics before COVID-19 and again in 2021 after a year of precautions. In general, staff felt more isolated and found it more difficult to conduct brief consults, though these perceptions varied by role. RNs, who spent more time on the phone, found it convenient to work part time-from home, while medical assistants found it more difficult to find providers in the distanced clinics. These cases suggest some important considerations for future clinic designs, including greater physical transparency that also allow for physical separation and more spaces for informal communication that are distanced from workstations.

The impact of clinic design on teamwork development in primary care.

BACKGROUND: Traditional clinic design supports a high-volume, hierarchical practice model. New design models are evolving to foster a high-functioning team delivery model. PURPOSE: The goal of this study was to determine whether new design models, specifically colocation, improve care team development. METHODOLOGY/APPROACH: A quasi-experimental design was used in this study to obtain validated teamwork development scores and patient satisfaction data to compare clinic design models. We took advantage of a difference in designs of primary care clinics among several clinics within the same care system in the Upper Midwest region of the United States. The participants were staff members of the primary care delivery teams in the studied clinics. The intervention was a redesign of staff space in the clinic. Our measures included a validated measure of team development and a commonly used patient satisfaction tool that were both in use at our institution at the time of the study. RESULTS: Teamwork scores were significantly higher in clinics where the primary work space of the entire team was colocated than in clinics where providers were in spaces separate from other team members. The differences in scores held across team roles, including providers, registered nurses, and licensed practical nurses. Patient satisfaction was not different. CONCLUSION: Colocation in clinic design appears to have a significant impact on team development across primary care team member roles. PRACTICE IMPLICATIONS: Primary care practice leaders should consider colocated clinic designs if their goal is to optimize care team development in support of team-based care delivery models. A more precise understanding of colocation that includes aspects such as distance to and visibility to teammates might help improve design in the future.

The Representational Function of Clinic Design: Staff and Patient Perceptions of Teamwork.

OBJECTIVE: This study empirically investigates the relationships between visibility attributes and both patients' and staff members' teamwork experiences. BACKGROUND: Teamwork among healthcare professionals is critical for the safety and quality of patient care. While a patient-centered, team-based care approach is promoted in primary care clinics, little is known about how clinic layouts can support the teamwork experiences of staff and patients in team-based primary clinics. METHODS: This article measured teamwork perceptions of staff members and patients at four primary care clinics providing team-based care. Visual access to staff workstations from both staff and patient perspectives was analyzed using VisualPower tool(version 21). The relationships between teamwork perception and visibility attributes were analyzed for each entity: staff members and patients. RESULTS: The results showed that the visual relationships among staff members and those between staff members and patients have significant associations with overall perceptions of teamwork. While clinics providing more visual connections between staff workstations reported higher teamwork perception of staff members, patient perceptions of staff teamwork were inversely related to the number of visual connections between patients and staff workstations. CONCLUSIONS: The findings of the study provide implications for designing team-based primary care clinics to enhance the teamwork experience of both staff members and patients, which is also applicable to teamwork perceptions in other settings where both inhabitants and visitors are main user groups of the spaces. This study illustrates the representational function of space: Organizations can emphasize their values via layout design by regulating what they show to inhabitants or visitors.

Association of Neighborhood Measures of Social Determinants of Health With Breast, Cervical, and Colorectal Cancer Screening Rates in the US Midwest.

Importance: Despite advances in cancer treatment and cancer-related outcomes, disparities in cancer mortality remain. Lower rates of cancer prevention screening and consequent delays in diagnosis may exacerbate these disparities. Better understanding of the association between area-level social determinants of health and cancer screening may be helpful to increase screening rates. Objective: To examine the association between area deprivation, rurality, and screening for breast, cervical, and colorectal cancer in patients from an integrated health care delivery system in 3 US Midwest states (Minnesota, Iowa, and Wisconsin). Design, Setting, and Participants: In this cross-sectional study of adults receiving primary care at 75 primary care practices in Minnesota, Iowa, and Wisconsin, rates of recommended breast, cervical, and colorectal cancer screening completion were ascertained using electronic health records between July 1, 2016, and June 30, 2017. The area deprivation index (ADI) is a composite measure of social determinants of health composed of 17 US Census indicators and was calculated for all census block groups in Minnesota, Iowa, and Wisconsin (11 230 census block groups). Rurality was defined at the zip code level. Using multivariable logistic regression, this study examined the association between the ADI, rurality, and completion of cancer screening after adjusting for age, Charlson Comorbidity Index, race, and sex (for colorectal cancer only). Main Outcomes and Measures: Completion of recommended breast, cervical, and colorectal cancer screening. Results: The study cohorts were composed of 78 302 patients eligible for breast cancer screening (mean [SD] age, 61.8 [7.1] years), 126 731 patients eligible for cervical cancer screening (mean [SD] age, 42.6 [13.2] years), and 145 550 patients eligible for colorectal cancer screening (mean [SD] age, 62.4 [7.0] years; 52.9% [77 048 of 145 550] female). The odds of completing recommended screening were decreased for individuals living in the most deprived (highest ADI) census block group quintile compared with the least deprived (lowest ADI) quintile: the odds ratios were 0.51 (95% CI, 0.46-0.57) for breast cancer, 0.58 (95% CI, 0.54-0.62) for cervical cancer, and 0.57 (95% CI, 0.53-0.61) for colorectal cancer. Individuals living in rural areas compared with urban areas also had lower rates of cancer screening: the odds ratios were 0.76 (95% CI, 0.72-0.79) for breast cancer, 0.81 (95% CI, 0.79-0.83) for cervical cancer, and 0.93 (95% CI, 0.91-0.96) for colorectal cancer. Conclusions and Relevance: Individuals living in areas of greater deprivation and rurality had lower rates of recommended cancer screening, signaling the need for effective intervention strategies that may include improved community partnerships and patient engagement to enhance access to screening in highest-risk populations.

Backstage Staff Communication: The Effects of Different Levels of Visual Exposure to Patients.

OBJECTIVE: This article examines how visual exposure to patients predicts patient-related communication among staff members. BACKGROUND: Communication among healthcare professionals private from patients, or backstage communication, is critical for staff teamwork and patient care. While patients and visitors are a core group of users in healthcare settings, not much attention has been given to how patients' presence impacts staff communication. Furthermore, many healthcare facilities provide team spaces for improved staff teamwork, but the privacy levels of team areas significantly vary. METHOD: This article presents an empirical study of four team-based primary care clinics where staff communication and teamwork are important. Visual exposure levels of the clinics were analyzed, and their relationships to staff members' concerns for having backstage communication, including preferred and nonpreferred locations for backstage communication, were investigated. RESULTS: Staff members in clinics with less visual exposure to patients reported lower concerns about having backstage communication. Staff members preferred talking in team areas that were visually less exposed to patients in the clinic, but, within team areas, the level of visual exposure did not matter. On the other hand, staff members did not prefer talking in visually exposed areas such as corridors in the clinic and visually exposed areas within team spaces. CONCLUSIONS: Staff members preferred talking in team areas, and they did not prefer talking in visually exposed areas. These findings identified visually exposed team areas as a potentially uncomfortable environment, with a lack of agreement between staff members' preferences toward where they had patient-related communication.

Development and Implementation of a Team-Based, Primary Care Delivery Model: Challenges and Opportunities.

In this article, we describe the implementation of a team-based care model during the first 2 years (2016-2017) after Mayo Clinic designed and built a new primary care clinic in Rochester, Minnesota. The clinic was configured to accommodate a team-based care model that included complete colocation of clinical staff to foster collaboration, designation of a physician team manager to support a physician to advanced practice practitioner ratio of 1:2, expanded roles for registered nurses, and integration of clinical pharmacists, behavioral health specialists, and community specialists; this model was designed to accommodate the growth of nonvisit care. We describe the implementation of this team-based care model and the key metrics that were tracked to assess performance related to the quadruple aim of improving population health, improving patient experience, reducing cost, and supporting care team's work life.

Making the Paradigm Shift from Siloed Population Health Management to an Enterprise-Wide Approach.

Health systems across the United States have started their journeys toward population health management and the future of accountable care. Models of population health management include patient-centered medical homes and private sector accountable care organizations (ACOs). Other models include public sector efforts, such as Physician Group Practice Transition Demonstrations, Medicare Health Care Quality Demonstration Programs, Beacon Communities, Medicare Shared Savings Program, and Pioneer ACOs. As a result, health care organizations often have pockets of population health initiatives that lack an enterprise-wide strategy. The next steps are to build on these efforts, leverage the learnings from these experiences, and incorporate the initiatives into an overarching framework and a road map for the future. This paper describes the current challenge many organizations face to implement an enterprise solution, describes how to transition from existing siloed initiatives, and shares a case study of how Mayo Clinic launched its Mayo Model of Community Care.

The Method for Performance Measurement Matters: Diabetes Care Quality as Measured by Administrative Claims and Institutional Registry.

OBJECTIVES: Performance measurement is used by health care providers, payers, and patients. Historically accomplished using administrative data, registries are used increasingly to track and improve care. We assess how measured diabetes care quality differs when calculated using claims versus registry. DATA SOURCES/STUDY SETTING: Cross-sectional analysis of administrative claims and electronic health records (EHRs) of patients in a multispecialty integrated health system in 2012 (n = 368,883). STUDY DESIGN: We calculated percent of patients attaining glycohemoglobin <8.0 percent, LDL cholesterol <100 mg/dL, blood pressure <140/90 mmHg, and nonsmoking (D4) in cohorts, identified by Medicare Accountable Care Organization/Minnesota Community Measures (ACO-MNCM; claims-based), Healthcare Effectiveness Data and Information Set (HEDIS; claims-based), and registry (EHR-based). DATA COLLECTION/EXTRACTION METHODS: Claims were linked to EHR to create a dataset of performance-eligible patients. PRINCIPAL FINDINGS: ACO-MNCM, HEDIS, and registry identified 6,475, 6,989, and 6,425 measurement-eligible patients. Half were common among the methods; discrepancies were due to attribution, age restriction, and encounter requirements. D4 attainment was lower in ACO-MNCM (36.09 percent) and HEDIS (37.51 percent) compared to registry (43.74 percent) cohorts. CONCLUSIONS: Registry- and claims-based performance measurement methods identify different patients, resulting in different rates of quality metric attainment with implications for innovative population health management.

Clinical decision support improves quality of telephone triage documentation--an analysis of triage documentation before and after computerized clinical decision support.

BACKGROUND: Clinical decision support (CDS) has been shown to be effective in improving medical safety and quality but there is little information on how telephone triage benefits from CDS. The aim of our study was to compare triage documentation quality associated with the use of a clinical decision support tool, ExpertRN©. METHODS: We examined 50 triage documents before and after a CDS tool was used in nursing triage. To control for the effects of CDS training we had an additional control group of triage documents created by nurses who were trained in the CDS tool, but who did not use it in selected notes. The CDS intervention cohort of triage notes was compared to both the pre-CDS notes and the CDS trained (but not using CDS) cohort. Cohorts were compared using the documentation standards of the American Academy of Ambulatory Care Nursing (AAACN). We also compared triage note content (documentation of associated positive and negative features relating to the symptoms, self-care instructions, and warning signs to watch for), and documentation defects pertinent to triage safety. RESULTS: Three of five AAACN documentation standards were significantly improved with CDS. There was a mean of 36.7 symptom features documented in triage notes for the CDS group but only 10.7 symptom features in the pre-CDS cohort (p < 0.0001) and 10.2 for the cohort that was CDS-trained but not using CDS (p < 0.0001). The difference between the mean of 10.2 symptom features documented in the pre-CDS and the mean of 10.7 symptom features documented in the CDS-trained but not using was not statistically significant (p = 0.68). CONCLUSIONS: CDS significantly improves triage note documentation quality. CDS-aided triage notes had significantly more information about symptoms, warning signs and self-care. The changes in triage documentation appeared to be the result of the CDS alone and not due to any CDS training that came with the CDS intervention. Although this study shows that CDS can improve documentation, further study is needed to determine if it results in improved care.

Telemedicine barriers associated with regional quality measures.

Telemedicine practitioners are familiar with multiple barriers to delivering care at a distance. Licensing and reimbursement barriers are well known and are being addressed at national and state levels by the American Telemedicine Association. Another telemedicine barrier comes in the form of quality measures for diabetes. Minnesota medical practices are currently being compared on the proportion of their patients with diabetes who have attained goals for blood pressure, low-density lipoprotein cholesterol, and hemoglobin A1C. The quality measure for blood pressure specifically excludes measurements taken by the patient, thus precluding blood pressure telemonitoring as a way to meet the blood pressure goal. To counter this barrier, advocacy in telemedicine is needed so that telemonitoring as a data collection tool is included in quality measures.

Trends in computed tomography utilization rates: a longitudinal practice-based study.

OBJECTIVES: Computed tomography (CT) use has increased dramatically over the past 2 decades, leading to increased radiation exposure at the population level. We assessed trends in CT use in a primary care (PC) population from 2000 to 2010. METHODS: Trends in CT use from 2000 to 2010 were assessed in an integrated, multi-specialty group practice. Administrative data were used to identify patients associated with a specific primary care provider and all CT imaging procedures. Utilization rates per 1000 patients and CT rates by type and medical specialty were calculated. RESULTS: Of 179,032 PC patients, 55,683 (31%) underwent CT. Mean age (SD) was 31.0 (23.6) years; 53% were female patients. In 2000, 178.5 CT scans per 1000 PC patients were performed, increasing to 195.9 in 2010 (10% absolute increase, P = 0.01). Although utilization rates across the 10-year period remained stable, emergency department (ED) CT examinations rose from 41.1 per 1000 in 2000 to 74.4 per 1000 in 2010 (81% absolute increase, P < 0.01). CT abdomen accounted for more than 50% of all CTs performed, followed by CT other (19%; included scans of the spine, extremities, neck and sinuses), CT chest (16%), and CT head (14%). Top diagnostic CT categories among those undergoing CT were abdominal pain, lower respiratory disease, and headache. CONCLUSIONS: Although utilization rates across the 10-year period remained stable, CT use in the ED substantially increased. CT abdomen and CT chest were the two most common studies performed and are potential targets for interventions to improve the appropriateness of CT use.

Impact of patient portal secure messages and electronic visits on adult primary care office visits.

INTRODUCTION: Secure messages and electronic visits ("e-visits") through patient portals provide patients with alternatives to face-to-face appointments, telephone contact, letters, and e-mails. Limited information exists on how portal messaging impacts face-to-face visits in primary care. MATERIALS AND METHODS: We conducted a retrospective cohort study of 2,357 primary care patients who used electronic messaging (both secure messages and e-visits) on a patient portal. Face-to-face appointment frequencies (visits/year) of each patient were calculated before and after the first message in a matched-pairs analysis. We analyzed visit frequencies with and without adjustments for a first message surge in visits, and we examined subgroups of high message utilizers and long-term users. RESULTS: Primary care patients who sent at least one message (secure message or e-visit) had a mean of 2.43 (standard deviation [SD] 2.3) annual face-to-face visits before the first message and 2.47 (SD 2.8) after, a nonsignificant difference (p=0.45). After adjustment for a first message surge in visits, no significant visit frequency differences were observed (mean, 2.35 annual visits per patient both before and after first message; p=0.93). Subgroup analysis also showed no significant change in visit frequency for patients with higher message utilization or for those who had used the messaging feature longer. CONCLUSIONS: No significant change in face-to-face visit frequency was observed following implementation of portal messaging. Secure messaging and e-visits through a patient portal may not result in a change of adult primary care face-to-face visits.

Risk-stratification methods for identifying patients for care coordination.

BACKGROUND: Care coordination is a key component of the patient-centered medical home. However, the mechanism for identifying primary care patients who may benefit the most from this model of care is unclear. OBJECTIVES: To evaluate the performance of several risk-adjustment/stratification instruments in predicting healthcare utilization. STUDY DESIGN: Retrospective cohort analysis. METHODS: All adults empaneled in 2009 and 2010 (n = 83,187) in a primary care practice were studied. We evaluated 6 models: Adjusted Clinical Groups (ACGs), Hierarchical Condition Categories (HCCs), Elder Risk Assessment, Chronic Comorbidity Count, Charlson Comorbidity Index, and Minnesota Health Care Home Tiering. A seventh model combining Minnesota Tiering with ERA score was also assessed. Logistic regression models using demographic characteristics and diagnoses from 2009 were used to predict healthcare utilization and costs for 2010 with binary outcomes (emergency department [ED] visits, hospitalizations, 30-day readmissions, and highcost users in the top 10%), using the C statistic and goodness of fit among the top decile. RESULTS: The ACG model outperformed the others in predicting hospitalizations with a C statistic range of 0.67 (CMS-HCC) to 0.73. In predicting ED visits, the C statistic ranged from 0.58 (CMSHCC) to 0.67 (ACG). When predicting the top 10% highest cost users, the performance of the ACG model was good (area under the curve = 0.81) and superior to the others. CONCLUSIONS: Although ACG models generally performed better in predicting utilization, use of any of these models will help practices implement care coordination more efficiently.

Patient-generated secure messages and eVisits on a patient portal: are patients at risk?

BACKGROUND: Patient portals are becoming increasingly common, but the safety of patient messages and eVisits has not been well studied. Unlike patient-to-nurse telephonic communication, patient messages and eVisits involve an asynchronous process that could be hazardous if patients were using it for time-sensitive symptoms such as chest pain or dyspnea. METHODS: We retrospectively analyzed 7322 messages (6430 secure messages and 892 eVisits). To assess the overall risk associated with the messages, we looked for deaths within 30 days of the message and hospitalizations and emergency department (ED) visits within 7 days following the message. We also examined message content for symptoms of chest pain, breathing concerns, and other symptoms associated with high risk. RESULTS: Two deaths occurred within 30 days of a patient-generated message, but were not related to the message. There were six hospitalizations related to a previous secure message (0.09% of secure messages), and two hospitalizations related to a previous eVisit (0.22% of eVisits). High-risk symptoms were present in 3.5% of messages but a subject line search to identify these high-risk messages had a sensitivity of only 15% and a positive predictive value of 29%. CONCLUSIONS: Patients use portal messages 3.5% of the time for potentially high-risk symptoms of chest pain, breathing concerns, abdominal pain, palpitations, lightheadedness, and vomiting. Death, hospitalization, or an ED visit was an infrequent outcome following a secure message or eVisit. Screening the message subject line for high-risk symptoms was not successful in identifying high-risk message content.

Episode-based payment: evaluating the impact on chronic conditions.

BACKGROUND: Policy makers are interested in aggregating fee-for-service reimbursement into episode-based bundle payments, hoping it will lead to greater efficiency in the provision of care. The focus of bundled payment initiatives has been upon surgical or discrete procedures. Relatively little is known about calculating and implementing episode-based payments for chronic conditions. OBJECTIVE: Compare the differences in two different episode-creation algorithms for two common chronic conditions: diabetes and coronary artery disease (CAD). STUDY DESIGN: We conducted a retrospective evaluation using enrollees with continuous coverage in a self-funded plan from 2003 to 2006, meeting Healthcare Effectiveness Data and Information Set (HEDIS) criteria for diabetes or CAD. For each condition, an annual episode-based payment was assessed using two algorithms: Episode Treatment Groups (ETGs) and the Prometheus model. PRINCIPAL FINDINGS: We began with 1,580 diabetes patients with a 4-year total payment mean of $67,280. ETGs identified 1,447 (92%) as having diabetes with 4-year episode-based mean payments of $12,731; while the Prometheus model identified 1,512 (96%) as having diabetes, but included only 1,195 of them in the Prometheus model with mean diabetes payments of $23,250. Beginning with 1,644 CAD patients with a 4-year total payment mean of $65,661, ETGs identified 983 patients (60%) with a 4-year episode-based mean of $24,362. The Prometheus model identified 1,135 (69%) as CAD patients with 948 CAD patients having a mean of $26,536. CONCLUSIONS: The two episode-based methods identify different patients with these two chronic conditions. In addition, there are significant differences in the episode-based payment estimates for diabetes, but similar estimates for CAD. Implementing episode-based payments for chronic conditions is challenging, and thoughtful discussions are needed to determine appropriate payments.

Improving rates of herpes zoster vaccination with a clinical decision support system in a primary care practice.

RATIONALE: Herpes zoster (shingles) is a localized neurocutaneous eruption of blisters caused by reactivation of the varicella zoster virus. The cost of care for herpes zoster and its complications is estimated at $1.1 billion. The Centers for Disease Control and Prevention's Advisory Committee on Immunization Practices recommends a one-time dose of the vaccine for adults aged 60 years or older. Despite that recommendation, utilization of the vaccine is very low. One way to boost the delivery of preventive services such as vaccinations is with a computerized clinical decision support system. Our study found that the herpes zoster vaccination rate increased significantly after the implementation of such a system. AIMS: To study utilization of herpes zoster vaccine before and after the implementation of a web-based clinical decision support software solution in a primary care practice. METHODS: Billing data was utilized to determine number of herpes zoster vaccination administered to patients for a 12-month period during the implementation of the software solution. RESULTS: The utilization of vaccinations improved from 63 to 117 (53.8% increase) for one primary care practice and from 54 to 127 (42.5% increase) in the other primary care practice. CONCLUSION: Herpes zoster vaccination rate significantly improved with implementation of a web-based clinical decision support system.