The Potential Effects Of HEDIS Performance Measures On The Quality Of Care

Evaluation of patient health outcomes of a student-run free clinic in East Harlem

BACKGROUND

Most United States medical schools have affiliated student-run free clinics, but the quality of services provided in such contexts compared to national metrics is unknown. This study determines whether a student-run, attending-supervised free clinic servicing a low-income and minority race patient population in New York City can meet national metrics of care.

METHODS

Through chart review from January 1, 2020 to December 31, 2020, patient outcomes and service utilization in the Healthcare Effectiveness Data and Information Set were examined and compared to national rates of patients using Medicaid HMO or Medicare. Patients are ≥ 21 years of age, residents of East Harlem, and ineligible for health insurance because of legal residency requirements. The majority identify as Hispanic and speak Spanish as their primary language. All patients who were seen in the clinic during the 2020 calendar year were included. The primary study outcome is the number of Healthcare Effectiveness Data and Information Set measures in which patients, seen in a student-run free clinic, meet or exceed national comparisons.

RESULTS

The healthcare outcomes of 238 patients, mean age 47.8 years and 54.6% female, were examined in 18 Healthcare Effectiveness Data and Information Set measures. The student-run free clinic met or exceeded national metrics in 16 out of 18 categories.

CONCLUSIONS

The student-run free clinic met or exceeded the national standard of care according to national metrics. Evidence-based priorities have been clarified for future improvement. Other student-run free clinics should similarly evaluate the quality of their services.

Medical assistant health coaching ("MAC") for type 2 diabetes in diverse primary care settings: A pragmatic, cluster-randomized controlled trial protocol

In the US, nearly 11% of adults were living with diagnosed diabetes in 2017, and significant type 2 diabetes (T2D) disparities are experienced by socioeconomically disadvantaged, racial/ethnic minority populations, including Hispanics. The standard 15-min primary care visit does not allow for the ongoing self-management support that is needed to meet the complex needs of individuals with diabetes. "Team-based" chronic care delivery is an alternative approach that supplements physician care with contact from allied health personnel in the primary care setting (e.g., medical assistants; MAs) who are specially trained to provide ongoing self-management support or "health coaching." While rigorous trials have shown MA health coaching to improve diabetes outcomes, less is known about if and how such a model can be integrated within real world, primary care clinic workflows. Medical Assistant Health Coaching for Type 2 Diabetes in Diverse Primary Care Settings - A Pragmatic, Cluster-Randomized Controlled Trial will address this gap. Specifically, this study compares MA health coaching versus usual care in improving diabetes clinical control among N = 600 at-risk adults with T2D, and is being conducted at four primary care clinics that are part of two health systems that serve large, ethnically/racially, and socioeconomically diverse populations in Southern California. Electronic medical records are used to identify eligible patients at both health systems, and to examine change in clinical control over one year in the overall sample. Changes in behavioral and psychosocial outcomes are being evaluated by telephone assessment in a subset (n = 300) of participants, and rigorous process and cost evaluations will assess potential for sustainability and scalability.

Care Team Integration in Primary Care Improves One-Year Clinical and Financial Outcomes in Diabetes: A Case for Value-Based Care

Despite significant treatment advances, diabetes outcomes remain suboptimal and health care costs continue to rise. There are limited data on the feasibility and financial implications of integrating a diabetes-specific care team in the primary care setting (ie, where the majority of diabetes is treated). This pragmatic quality improvement project investigated whether a cardiometabolic care team intervention (CMC-TI) could achieve greater improvements in clinical, behavioral, and cost outcomes compared to usual diabetes care in a large primary care group in Southern California. Over 12 months, n = 236 CMC-TI and n = 239 usual care patients with type 1 or 2 diabetes were identified using the electronic medical record. In the CMC-TI group, a registered nurse (RN)/certified diabetes educator care manager, medical assistant health coach, and RN depression care manager utilized electronic medical record-based risk stratification reports, standardized decision-support tools, live and remote tailored treatments, and coaching to manage care. Results indicated that the CMC-TI group achieved greater improvements in glycemic and lipid control, diabetes self-management behaviors, and emotional distress over 1 year compared with the usual care group (all P < .05). The CMC-TI group also had a significant 12.6% reduction in total health care costs compared to a 51.7% increase in the usual care group during the same period and inclusive of CMC-TI program costs. Patients and providers reported high satisfaction with CMC-TI. These findings highlight that team-based care management interventions that utilize nurses, medical assistant health coaches, and behavioral specialists to support diabetes patients can help primary care practices achieve value-based targets of improved health, cost, and patient experience.

Making Inroads in Addressing Population Health in Underserved Communities With Type 2 Diabetes

IN BRIEF Diabetes continues to represent a substantial individual and societal burden for those affected by the disease and its complications in the United States, and especially for racial/ethnic minorities, the socioeconomically disadvantaged, and the underinsured. Although tools and strategies are now available to manage the condition and its associated comorbidities at the patient level, we continue to struggle to gain control of this health burden at the population health level. Most patients are not achieving desired clinical goals and thus continue to be exposed to preventable risks and complications. As the U.S. health system moves toward a more value-based system of reimbursement, there are opportunities to rethink our approaches to patient and population health management and to harness the available tools and technologies to better understand the disease burden, stratify our patient populations by risk, redirect finite resources to high-impact initiatives, and facilitate better diabetes care management for patients and providers alike.

Albuminuria Testing by Race and Ethnicity among Patients with Hypertension with and without Diabetes

BACKGROUND

Detection of chronic kidney disease (CKD) with urine albumin-to-creatinine ratio (UACR) among patients with hypertension (HTN) provides an opportunity for early treatment, potentially mitigating risk of CKD progression and cardiovascular complications. Differences in UACR testing patterns among racial/ethnic populations at risk for CKD could contribute to known disparities in CKD complications.

METHODS

We examined the prevalence of UACR testing among low-income adult primary care patients with HTN, defined by a new administrative code for HTN or 2 clinic blood pressures >140/90 mm Hg between January 1, 2014, and January 1, 2017, in one public health-care delivery system with a high prevalence of end-stage kidney disease among race/ethnic minorities. Logistic regression was used to identify odds of UACR testing within 1 year of a HTN diagnosis, overall, and by racial/ethnic subgroup, adjusted for demographic factors, estimated glomerular filtration rate, and HTN severity. Models were also stratified by diabetes status.

RESULTS

The cohort (n = 16,414) was racially/ethnically diverse (16% White, 21% Black, 34% Asian, 19% Hispanic, and 10% other) and 51% female. Only 35% of patients had UACR testing within 1 year of a HTN diagnosis. Among individuals without diabetes, odds of UACR testing were higher among Asians, Blacks, and Other subgroups compared to Whites (adjusted OR [aOR] 1.19; 95% CI 1.00-1.42 for Blacks; aOR 1.33; 1.13-1.56 for Asians; aOR 1.30; 1.04-1.60 for Other) but were not significantly different between Hispanics and Whites (aOR 1.17; 0.97-1.39). Among individuals with diabetes, only Asians had higher odds of UACR testing compared to Whites (aOR 1.35; 1.12-1.63).

CONCLUSIONS

Prevalence of UACR testing among low-income patients with HTN is low in one public health-care delivery system, with higher odds of UACR testing among racial/ethnic minority subgroups compared to Whites without diabetes and similar odds among those with diabetes. If generalizable, less albuminuria testing may not explain higher prevalence of kidney failure in racial/ethnic minorities.

Reducing morbidity and complications after major head and neck cancer surgery: the (future) role of enhanced recovery after surgery protocols

PURPOSE OF REVIEW

To review the development and the benefits of enhanced recovery after surgery (ERAS) protocols in non-head and neck disciplines and to describe early implementation efforts in major head and neck surgeries.

RECENT FINDINGS

Several groups have adopted ERAS protocols for major head and neck surgery and demonstrated its feasibility and effectiveness.

SUMMARY

There is growing evidence that clinical and financial outcomes for patients undergoing major head and neck surgery rehabilitation can be significantly improved by standardizing preoperative, intraoperative, and postoperative treatment protocols. Current experience is limited to single centers. A future goal is to broaden the adoption of ERAS in head and neck surgical oncology to include national and international collaboration, data sharing, and learning.

Using Clinical Data Standards to Measure Quality: A New Approach

BACKGROUND

Value-based payment for care requires the consistent, objective calculation of care quality. Previous initiatives to calculate ambulatory quality measures have relied on billing data or individual electronic health records (EHRs) to calculate and report performance. New methods for quality measure calculation promoted by federal regulations allow qualified clinical data registries to report quality outcomes based on data aggregated across facilities and EHRs using interoperability standards.

OBJECTIVE

This research evaluates the use of clinical document interchange standards as the basis for quality measurement.

METHODS

Using data on 1,100 patients from 11 ambulatory care facilities and 5 different EHRs, challenges to quality measurement are identified and addressed for 17 certified quality measures.

RESULTS

Iterative solutions were identified for 14 measures that improved patient inclusion and measure calculation accuracy. Findings validate this approach to improving measure accuracy while maintaining measure certification.

CONCLUSION

Organizations that report care quality should be aware of how identified issues affect quality measure selection and calculation. Quality measure authors should consider increasing real-world validation and the consistency of measure logic in respect to issues identified in this research.

Methods for Building and Validating Equations for Physiology-Based Mathematical Models: Glucose Metabolism and Type 2 Diabetes in the Archimedes Model

OBJECTIVES

Describe steps for deriving and validating equations for physiology processes for use in mathematical models. Illustrate the steps using glucose metabolism and Type 2 diabetes in the Archimedes model.

METHODS AND RESULTS

The steps are as follows: identify relevant variables, describe their relationships, identify data sources that relate the variables, correct for biases in data sources, use curve fitting algorithms to estimate equations, validate the accuracy of curve fitting against empirical data, perform partially and fully independent external validations, examine any discrepancies to determine causes and make corrections, and periodically update and revalidate equations as necessary. Specific methods depend on the available data. Specific data sources and methods are illustrated for equations that represent the cause of Type 2 diabetes and its effect on fasting plasma glucose in the Archimedes model. Methods for validating the equations are illustrated. Applications enabled by including physiological equations in healthcare models are discussed.

CONCLUSIONS

The methods can be used to derive equations that represent the relationships between physiological variables and the causes of diseases and that validate well against empirical data.

The 'Global Outcomes Score': a quality measure, based on health outcomes, that compares current care to a target level of care

The quality of health care is measured today using performance measures that calculate the percentage of people whose health conditions are managed according to specified processes or who meet specified treatment goals. This approach has several limitations. For instance, each measure looks at a particular process, risk factor, or biomarker one by one, and each uses sharp thresholds for defining "success" versus "failure." We describe a new measure of quality called the Global Outcomes Score (GO Score), which represents the proportion of adverse outcomes expected to be prevented in a population under current levels of care compared to a target level of care, such as 100 percent performance on certain clinical guidelines. We illustrate the use of the GO Score to measure blood pressure and cholesterol care in a longitudinal study of people at risk of atherosclerotic diseases, or hardening of the arteries. In that population the baseline GO Score was 40 percent, which indicates that the care being delivered was 40 percent as effective in preventing myocardial infarctions and strokes as our target level of care. The GO Score can be used to assess the potential effectiveness of different interventions such as prevention activities, tests, and treatments.

Use of IndiGO individualized clinical guidelines in primary care

Objective

To determine if IndiGO individualized clinical guidelines could be implemented in routine practice and assess their effects on care and care experience.

Methods

Matched comparison observational design. IndiGO individualized guidelines, based on a biomathematical simulation model, were used in shared decision-making. Physicians and patients viewed risk estimates and tailored recommendations in a dynamic user interface and discussed them for 5–10 min. Outcome measures were prescribing and dispensing of IndiGO-recommended medications, changes in physiological markers and predicted 5-year risk of heart attack and stroke, and physician and patient perceptions.

Results

489 patients using IndiGO were 4.9 times more likely to receive a statin prescription than were matched usual care controls (p=0.015). No effect was observed on prescribing of antihypertensive medications, but IndiGO-using patients were more likely to pick up at least one dispensing (p<0.05). No significant changes were observed in blood pressure or serum lipid levels. Predicted risk of heart attack or stroke decreased 1.6% among patients using IndiGO versus 1.0% among matched controls (p<0.01). Physician and patient experiences were positive to neutral.

Limitations

We could not assess the separate effects of individualized guidelines, user interface, and physician–patient discussions. Patient selection could have influenced results. The measure of risk reduction was not independent of the individualized guidelines.

Conclusions

IndiGO individualized clinical guidelines were successfully implemented in primary care and were associated with increases in the use of cardioprotective medications and reduction in the predicted risk of adverse events, suggesting that a larger trial could be warranted.

Health-weighted Composite Quality Metrics Offer Promise to Improve Health Outcomes in a Learning Health System

Health system leaders sometimes adopt quality metrics without robust supporting evidence of improvements in quality and/or quantity of life, which may impair rather than facilitate improved health outcomes. In brief, there is now no easy way to measure how much “health” is conferred by a health system. However, we argue that this goal is achievable. Health-weighted composite quality metrics have the potential to measure “health” by synthesizing individual evidence-based quality metrics into a summary measure, utilizing relative weightings that reflect the relative amount of health benefit conferred by each constituent quality metric. Previously, it has been challenging to create health-weighted composite quality metrics because of methodological and data limitations. However, advances in health information technology and mathematical modeling of disease progression promise to help mitigate these challenges by making patient-level data (eg, from the electronic health record and mobile health (mHealth) more accessible and more actionable for use. Accordingly, it may now be possible to use health information technology to calculate and track a health-weighted composite quality metric for each patient that reflects the health benefit conferred to that patient by the health system. These health-weighted composite quality metrics can be employed for a multitude of important aims that improve health outcomes, including quality evaluation, population health maximization, health disparity attenuation, panel management, resource allocation, and personalization of care. We describe the necessary attributes, the possible uses, and the likely limitations and challenges of health-weighted composite quality metrics using patient-level health data.

The burden and management of dyslipidemia: practical issues

The objective of this study is to describe briefly the burden of dyslipidemia, and to discuss and present strategies for health professionals to improve dyslipidemia management, based on a review of selected literature focusing on interventions for dyslipidemia treatment adherence. Despite the availability of effective lifestyle and pharmaceutical therapies for dyslipidemias, they continue to present a significant economic burden in the United States. Adherence to evidence-based guidelines for the treatment of dyslipidemias is unsatisfactory. The reasons for medication nonadherence are complex and specific to each patient. The lack of progress in achieving optimal lipid targets is caused by many factors: patient (medication adherence, cost of medication, literacy), medication (adverse effects, complexity of regimen), provider (lack of adherence to evidence-based practice guidelines, poor communication), and the US healthcare system (being focused on acute care rather than prevention, lack of continuity of care, general lack of use of an electronic health record). Combined interventions that target each part of the system have been effective in improving treatment adherence and achieving lipid goals. Patients, providers, pharmacists, and employers all play a role in management of dyslipidemia. No single approach will solve the complex issue of improving dyslipidemia management. The required lifestyle changes are known and effective medications are available. The challenge is for all interested parties-including nurses, nurse practitioners, doctors, pharmacists, other health care professionals, employers, and health plans-to help patients achieve behavioral changes.

The impact of decision aids to enhance shared decision making for diabetes (the DAD study): protocol of a cluster randomized trial

Background

Shared decision making contributes to high quality healthcare by promoting a patient-centered approach. Patient involvement in selecting the components of a diabetes medication program that best match the patient’s values and preferences may also enhance medication adherence and improve outcomes. Decision aids are tools designed to involve patients in shared decision making, but their adoption in practice has been limited. In this study, we propose to obtain a preliminary estimate of the impact of patient decision aids vs. usual care on measures of patient involvement in decision making, diabetes care processes, medication adherence, glycemic and cardiovascular risk factor control, and resource utilization. In addition, we propose to identify, describe, and explain factors that promote or inhibit the routine embedding of decision aids in practice.

Methods/Design

We will be conducting a mixed-methods study comprised of a cluster-randomized, practical, multicentered trial enrolling clinicians and their patients (n = 240) with type 2 diabetes from rural and suburban primary care practices (n = 8), with an embedded qualitative study to examine factors that influence the incorporation of decision aids into routine practice. The intervention will consist of the use of a decision aid (Statin Choice and Aspirin Choice, or Diabetes Medication Choice) during the clinical encounter. The qualitative study will include analysis of video recordings of clinical encounters and in-depth, semi-structured interviews with participating patients, clinicians, and clinic support staff, in both trial arms.

Discussion

Upon completion of this trial, we will have new knowledge about the effectiveness of diabetes decision aids in these practices. We will also better understand the factors that promote or inhibit the successful implementation and normalization of medication choice decision aids in the care of chronic patients in primary care practices.

Trial registration

NCT00388050

Revisiting Diabetes 2000: challenges in establishing nationwide diabetic retinopathy prevention programs

PURPOSE

To evaluate the impact of the Diabetes 2000 program, an initiative launched by the American Academy of Ophthalmology in 1990 to improve nationwide screening of diabetic retinopathy (DR) and to reduce the prevalence and severity of the condition.

DESIGN

Retrospective, observational case study of Diabetes 2000 program.

METHODS

This is a perspective piece with a review of literature and personal opinions.

RESULTS

Patients with diabetes are likely to see an increase in the disease burdens associated with DR unless effective programs for early detection and control of DR are implemented.

CONCLUSIONS

Despite recent efforts to educate both patients and physicians alike about the importance of routine DR screening, the lessons learned from the Diabetes 2000 program illustrate the need for new strategies capable of improving accessibility to high-quality eye care, increasing involvement of primary care physicians in DR screening and encouraging at-risk individuals to seek testing.

Cost implications of improving blood pressure management among U.S. adults

OBJECTIVE

To examine the cost-effectiveness of improving blood pressure management from the payer perspective.

DATA SOURCE/STUDY SETTING

Medical record data for 4,500 U.S. adults with hypertension from the Community Quality Index (CQI) study (1996-2002), pharmaceutical claims from four Massachusetts health plans (2004-2006), Medicare fee schedule (2009), and published literature.

STUDY DESIGN

A probability tree depicted blood pressure management over 2 years.

DATA COLLECTION/EXTRACTION METHODS

We determined how frequently CQI study subjects received recommended care processes and attained accepted treatment goals, estimated utilization of visits and medications associated with recommended care, assigned costs based on utilization, and then modeled how hospitalization rates, costs, and goal attainment would change if all recommended care was provided.

PRINCIPAL FINDINGS

Relative to current care, improved care would cost payers U.S.$170 more per hypertensive person annually (2009 dollars). The incremental cost per person newly attaining treatment goals over 2 years would be U.S.$1,696 overall, U.S.$801 for moderate hypertension, and U.S.$850 for severe hypertension. Among people with severe hypertension, blood pressure would decline substantially but seldom reach goal; the incremental cost per person attaining a relaxed goal (≤ stage 1) would be U.S.$185.

CONCLUSIONS

Under the Health Care Effectiveness Data and Information Set program, which monitors the attainment of blood pressure treatment goals, payers will find it slightly more cost-effective to improve care for moderate than severe hypertension. Having a secondary, relaxed goal would substantially increase payers' incentive to improve care for severe hypertension.

Translation of hypertension treatment guidelines into practice: a review of implementation

Compared with the history of national guideline development, the science attached to implementation of guidelines is relatively new. Effectiveness of a highly evidence-based guideline, such as the 8th Joint National Committee recommendations on the treatment of high blood pressure, depends on successful translation into clinical practice. Implementation relies on several steps: clear and executable guideline language, audit and feedback attached to education of practitioners charged with carrying out the guidelines, team-based care delivery, credibility of blood pressure measurement, and measures to address therapeutic inertia and medication adherence. An evolving role of the electronic health record and patient empowerment are developments that will further promote implementation of the hypertension guideline. Further research will be needed to assess the efficacy and cost effectiveness of various implementation tools and strategies.

Modeling the effects of omalizumab over 5 years among patients with moderate-to-severe persistent allergic asthma

OBJECTIVE

Omalizumab is a monoclonal antibody indicated for adults and adolescents with moderate-to-severe persistent allergic asthma whose symptoms are inadequately controlled with inhaled corticosteroids. Omalizumab has been demonstrated to improve health outcomes of asthmatic patients as compared to placebo. However, to date, the trials conducted have been relatively short (less than 1 year) and have been restricted to a limited set of patients who met the clinical study criteria. This study examined the expected effects of omalizumab over 5 years on a representative sample of all patients eligible for omalizumab in the US.

METHODS

The Archimedes Asthma Model was used to simulate the following treatment scenarios for US patients age 12 and older with moderate-to-severe persistent allergic asthma: (1) Current asthma treatment (CAT) (treatment according to National Heart, Lung, and Blood Institute (NHLBI) guidelines, without use of omalizumab, and with adherence levels as observed in the National Asthma Survey); (2) Guideline asthma treatment (GAT) without omalizumab (NHLBI guidelines without use of omalizumab, assuming perfect adherence); (3) GAT plus omalizumab; and (4) GAT plus omalizumab with steroid reduction. The simulation was run for 5 years.

MAIN OUTCOME MEASURES

Symptom days, asthma exacerbations, emergency room/urgent care (ER/UC) visits, hospitalizations, and medication use.

RESULTS

For the full simulated population of omalizumab-eligible patients, the simulation forecasted that omalizumab would decrease cumulative exacerbations by 30%, ER/UC visits by 37%, and hospitalizations by 38% over 5 years. Among responders to omalizumab, assuming that 60.5% of patients respond, the results suggest that omalizumab would decrease cumulative exacerbations by 50%, ER/UC visits by 62%, and hospitalizations by 63% over 5 years. In addition, the simulation predicted that omalizumab would allow 45% of patients who are taking more than the minimum steroid dose to reduce their steroid dose, while maintaining similar asthma control as achieved in the GAT plus omalizumab arm (no steroid dose reduction) and better asthma control than following treatment protocols that do not include omalizumab.

CONCLUSION

Based on the results of this simulation, omalizumab is effective for those who respond, reducing serious events by more than 50% among the responder group, while also allowing many patients to reduce their steroid dose.

Trends in time to confirmation and recognition of new-onset hypertension, 2002-2006

Achieving full benefits of blood pressure control in populations requires prompt recognition of previously undetected hypertension. In 2003, the Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure provided definitions of hypertension and recommended that single elevated readings be confirmed within 1 to 2 months. We sought to determine whether the time required to confirm and recognize (ie, diagnose and/or treat) new-onset hypertension decreased from 2002 to 2006 for adult members of 2 large integrated healthcare delivery systems, Kaiser Permanente Northern California and Colorado. Using electronically stored office blood pressure readings, physician diagnoses, and pharmacy prescriptions, we identified 200 587 patients with new-onset hypertension (2002-2006) marked by 2 consecutive elevated blood pressure readings in previously undiagnosed, untreated members. Mean confirmation intervals (time from the first to second consecutive elevated reading) declined steadily from 103 to 89 days during this period. For persons recognized within 12 months after confirmation, the mean interval to recognition declined from 78 to 61 days. However, only 33% of individuals were recognized within 12 months. One third were never recognized during observed follow-up. For these patients, most subsequent blood pressure recordings were not elevated. Higher initial blood pressure levels, history of previous cardiovascular disease, and older age were associated with shorter times to recognition. Times to confirmation and recognition of new-onset hypertension have become shorter in recent years, especially for patients with higher cardiovascular disease risk. Variability in office-based blood pressure readings suggests that further improvements in recognition and treatment may be achieved with more specific automated approaches to identifying hypertension.