Sustained improvement in clinical preventive service delivery among independent primary care practices after implementing electronic health record systems

The Value of Electronic Health Records Since the Health Information Technology for Economic and Clinical Health Act: Systematic Review

Background

Electronic health records (EHRs) are the electronic records of patient health information created during ≥1 encounter in any health care setting. The Health Information Technology Act of 2009 has been a major driver of the adoption and implementation of EHRs in the United States. Given that the adoption of EHRs is a complex and expensive investment, a return on this investment is expected.

Objective

This literature review aims to focus on how the value of EHRs as an intervention is defined in relation to the elaboration of value into 2 different value outcome categories, financial and clinical outcomes, and to understand how EHRs contribute to these 2 value outcome categories.

Methods

This literature review was conducted using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). The initial search of key terms, EHRs, values, financial outcomes, and clinical outcomes in 3 different databases yielded 971 articles, of which, after removing 410 (42.2%) duplicates, 561 (57.8%) were incorporated in the title and abstract screening. During the title and abstract screening phase, articles were excluded from further review phases if they met any of the following criteria: not relevant to the outcomes of interest, not relevant to EHRs, nonempirical, and non–peer reviewed. After the application of the exclusion criteria, 80 studies remained for a full-text review. After evaluating the full text of the residual 80 studies, 26 (33%) studies were excluded as they did not address the impact of EHR adoption on the outcomes of interest. Furthermore, 4 additional studies were discovered through manual reference searches and were added to the total, resulting in 58 studies for analysis. A qualitative analysis tool, ATLAS.ti. (version 8.2), was used to categorize and code the final 58 studies.

Results

The findings from the literature review indicated a combination of positive and negative impacts of EHRs on financial and clinical outcomes. Of the 58 studies surveyed for this review of the literature, 5 (9%) reported on the intersection of financial and clinical outcomes. To investigate this intersection further, the category “Value–Intersection of Financial and Clinical Outcomes” was generated. Approximately 80% (4/5) of these studies specified a positive association between EHR adoption and financial and clinical outcomes.

Conclusions

This review of the literature reports on the individual and collective value of EHRs from a financial and clinical outcomes perspective. The collective perspective examined the intersection of financial and clinical outcomes, suggesting a reversal of the current understanding of how IT investments could generate improvements in productivity, and prompted a new question to be asked about whether an increase in productivity could potentially lead to more IT investments.

Use of a Preventive Index to Examine Clinic-Level Factors Associated With Delivery of Preventive Care

INTRODUCTION

There is an increasing need for the development of new methods to understand factors affecting delivery of preventive care. This study applies a new measurement approach and assesses clinic-level factors associated with preventive care delivery.

METHODS

This retrospective longitudinal cohort study of 94 community health centers used electronic health record data from the OCHIN community health information network, 2014-2015. Clinic-level preventive ratios (time covered by a preventive service/time eligible for a preventive service) were calculated in 2017 for 12 preventive services with A or B recommendations from the U.S. Preventive Services Task Force along with an aggregate preventive index for all services combined. For each service, multivariable negative binomial regression modeling and calculated rate ratios assessed the association between clinic-level variables and delivery of care.

RESULTS

Of ambulatory community health center visits, 59.8% were Medicaid-insured and 10.4% were uninsured. Ambulatory community health centers served 16.9% patients who were Hispanic, 13.1% who were nonwhite, and 68.7% who had household incomes <138% of the federal poverty line. Clinic-level preventive ratios ranged from 3% (hepatitis C screening) to 93% (blood pressure screening). The aggregate preventive index including all screening measures was 47% (IQR, 42%-50%). At the clinic level, having a higher percentage of uninsured visits was associated with lower preventive ratios for most (7 of 12) preventive services.

CONCLUSIONS

Approaches that use individual preventive ratios and aggregate prevention indices are promising for understanding and improving preventive service delivery over time. Health insurance remains strongly associated with access to needed preventive care, even for safety net clinic populations.

The use of Electronic Health Records to Support Population Health: A Systematic Review of the Literature

Electronic health records (EHRs) have emerged among health information technology as "meaningful use" to improve the quality and efficiency of healthcare, and health disparities in population health. In other instances, they have also shown lack of interoperability, functionality and many medical errors. With proper implementation and training, are electronic health records a viable source in managing population health? The primary objective of this systematic review is to assess the relationship of electronic health records' use on population health through the identification and analysis of facilitators and barriers to its adoption for this purpose. Authors searched Cumulative Index of Nursing and Allied Health Literature (CINAHL) and MEDLINE (PubMed), 10/02/2012-10/02/2017, core clinical/academic journals, MEDLINE full text, English only, human species and evaluated the articles that were germane to our research objective. Each article was analyzed by multiple reviewers. Group members recognized common facilitators and barriers associated with EHRs effect on population health. A final list of articles was selected by the group after three consensus meetings (n = 55). Among a total of 26 factors identified, 63% (147/232) of those were facilitators and 37% (85/232) barriers. About 70% of the facilitators consisted of productivity/efficiency in EHRs occurring 33 times, increased quality and data management each occurring 19 times, surveillance occurring 17 times, and preventative care occurring 15 times. About 70% of the barriers consisted of missing data occurring 24 times, no standards (interoperability) occurring 13 times, productivity loss occurring 12 times, and technology too complex occurring 10 times. The analysis identified more facilitators than barriers to the use of the EHR to support public health. Wider adoption of the EHR and more comprehensive standards for interoperability will only enhance the ability for the EHR to support this important area of surveillance and disease prevention. This review identifies more facilitators than barriers to using the EHR to support public health, which implies a certain level of usability and acceptance to use the EHR in this manner. The public-health industry should combine their efforts with the interoperability projects to make the EHR both fully adopted and fully interoperable. This will greatly increase the availability, accuracy, and comprehensiveness of data across the country, which will enhance benchmarking and disease surveillance/prevention capabilities.

Bridging the gap between clinical practice and public health: Using EHR data to assess trends in the seasonality of blood-pressure control

Electronic health records (EHRs) provide timely access to millions of patient data records while limiting errors associated with manual data extraction. To demonstrate these advantages of EHRs to public health practice, we examine the ability of a EHR calculated blood-pressure (BP) measure to replicate seasonal variation as reported by prior studies that used manual data extraction.

Our sample included 609 primary-care practices in New York City. BP control among hypertensives was defined as systolic blood pressure of 140 or less and diastolic blood pressure of 90 or less (BP < 140/90 mm Hg). An innovative query-distribution system was used to extract monthly BP control values from the EHRs of adult patients diagnosed with hypertension over a 25-month period. Generalized estimating equations were used to compare the association between seasonal temperature variations and BP control rates at the practice level, while adjusting for known demographic factors (age, gender), comorbid diseases (diabetes) associated with blood pressure, and months since EHR implementation.

BP control rates increased gradually from the spring months to peak summer months before declining in the fall months. In addition to seasonal variation, the adjusted model showed that a 1% increase in patients with a diabetic comorbidity is associated with an increase of 3% (OR 1.03; CI 1.028–1.032) on the BP measure.

Our findings identified cyclic trends in BP control and highlighted greater association with increased proportion of diabetic patients, therefore confirming the ability of the EHR as a tool for measuring population health outcomes.

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We replicated seasonal fluctuations in BP control using aggregate EHR data on outpatients in NYC.

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BP was better controlled in the warmer months than in the colder months.

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A higher proportion of patients with diabetic comorbidity at a practice increases the seasonal fluctuations in BP control.

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We found no association between BP control and the proportion of females or elderly at the practice.

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Our findings using EHR data was similar to prior studies that relied on manual chart review.

Applied Use of Composite Quality Measures for EHR-enabled Practices

Introduction:

The Primary Care Information Project (PCIP) of the New York City Department of Health and Mental Hygiene has been assisting providers to implement health information technology such as electronic health records (EHRs) since its founding in 2005. Currently, all practices affiliated with PCIP are offered technical support services in order to improve the use of the EHR. We studied the performance of clinical practices on EHR-derived Composite Quality Measures (CQMs) over time. Because specific EHR functionalities are important to calculating the quality measures, we hypothesize that performance on each of the CQMs will differ according to the EHR functionalities, and that this can inform the process of developing targeted technical assistance for the practices.

Methods:

We created four CQMs: (1) Screening, (2) Assessment, (3) Control-BP, and (4) Control-Other. Using data from 93 practices, we identified three tertiles of CQM performance (premier, average, and low tiers) for each measure. A scatterplot of CQMs in 2010 versus 2011 was used to examine the individual movement of practices by tier. A dependent t-test compared the change in mean CQMs, and a chi-square test examined the association between the score and performance tier changes.

Results:

Over a one-year period, low tier practices demonstrated the highest gains, average tier practices had modest gains, and premier tier practices had gains in some measures, but losses in others. On the Screening CQM 70 percent of practices remained within the same tier, with 60 percent on Assessment, 52 percent on Control-BP, and 38 percent on Control-Other; the Control-Other group showed the greatest improvement.

Discussion:

By considering EHR functionalities associated with each of the four CQMs, we suggest that technical assistance can be better targeted to low-tier performing practices. In addition, there is still the potential for improvement over time at practices more familiar with key functionalities.

Quality measure performance in small practices before and after electronic health record adoption

Introduction:

To date, little research has been published on the impact that the transition from paper-based record keeping to the use of electronic health records (EHR) has on performance on clinical quality measures. This study examines whether small, independent medical practices improved in their performance on nine clinical quality measures soon after adopting EHRs.

Methods:

Data abstracted by manual review of paper and electronic charts for 6,007 patients across 35 small, primary care practices were used to calculate rates of nine clinical quality measures two years before and up to two years after EHR adoption.

Results:

For seven measures, population-level performance rates did not change before EHR adoption. Rates of antithrombotic therapy and smoking status recorded increased soon after EHR adoption; increases in blood pressure control occurred later. Rates of hemoglobin A1c testing, BMI recorded, and cholesterol testing decreased before rebounding; smoking cessation intervention, hemoglobin A1c control and cholesterol control did not significantly change.

Discussion:

The effect of EHR adoption on performance on clinical quality measures is mixed. To improve performance, practices may need to develop new workflows and adapt to different documentation methods after EHR adoption.

Conclusions:

In the short term, EHRs may facilitate documentation of information needed for improving the delivery of clinical preventive services. Policies and incentive programs intended to drive improvement should include in their timelines consideration of the complexity of clinical tasks and documentation needed to capture performance on measures when developing timelines, and should also include assistance with workflow redesign to fully integrate EHRs into medical practice.

Clinical Preventive Services Coverage and the Affordable Care Act

The Affordable Care Act requires many health plans to provide coverage for certain recommended clinical preventive services without charging copays or deductible payments. This provision could lead to greater uptake of many services that can improve health and save lives. Although the coverage provision is broad, there are many caveats that also apply. It is important for providers and public health professionals to understand the nuances of the coverage rules to help maximize their potential to improve population health.

Use of electronic health records to support smoking cessation

BACKGROUND

Health information systems such as electronic health records (EHR), computerized decision support systems, and electronic prescribing are potentially valuable components to improve the quality and efficiency of clinical interventions for tobacco use.

OBJECTIVES

To assess the effectiveness of electronic health record-facilitated interventions on smoking cessation support actions by clinicians, clinics, and healthcare delivery systems and on patient smoking cessation outcomes.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group Specialised Register, CENTRAL, MEDLINE, EMBASE, PsycINFO, CINAHL, and reference lists and bibliographies of included studies. We searched for studies published between January 1990 and July 2014.

SELECTION CRITERIA

We included both randomized studies and non-randomized studies that reported interventions targeting tobacco use through an EHR in healthcare settings. The intervention could include any use of an EHR to improve smoking status documentation or cessation assistance for patients who use tobacco, either by direct action or by feedback of clinical performance measures.

DATA COLLECTION AND ANALYSIS

Characteristics and content of the interventions, participants, outcomes and methods of the included studies were extracted by one author and checked by a second. Because of wide variation in measurement of outcomes, we were not able to conduct a meta-analysis.

MAIN RESULTS

We included six group randomized trials, one patient randomized study, and nine non-randomized observational studies of fair to good quality that tested the use of an existing EHR to improve documentation and/or treatment of tobacco use. None of the studies included a direct assessment of patient quit rates. Overall, these studies found only modest improvements in some of the recommended clinician actions on tobacco use.

AUTHORS' CONCLUSIONS

Documentation of tobacco status and referral to cessation counselling appears to increase following EHR modifications designed to prompt the recording and treating of tobacco use at healthcare visits. There is a need for additional research to enhance the potential of EHRs to prompt additional tobacco use treatment and cessation outcomes in healthcare settings.

Diabetes and hypertension quality measurement in four safety-net sites: lessons learned after implementation of the same commercial electronic health record

BACKGROUND

In this new era after the Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009, the literature on lessons learned with electronic health record (EHR) implementation needs to be revisited.

OBJECTIVES

Our objective was to describe what implementation of a commercially available EHR with built-in quality query algorithms showed us about our care for diabetes and hypertension populations in four safety net clinics, specifically feasibility of data retrieval, measurements over time, quality of data, and how our teams used this data.

METHODS

A cross-sectional study was conducted from October 2008 to October 2012 in four safety-net clinics located in the Midwest and Western United States. A data warehouse that stores data from across the U.S was utilized for data extraction from patients with diabetes or hypertension diagnoses and at least two office visits per year. Standard quality measures were collected over a period of two to four years. All sites were engaged in a partnership model with the IT staff and a shared learning process to enhance the use of the quality metrics.

RESULTS

While use of the algorithms was feasible across sites, challenges occurred when attempting to use the query results for research purposes. There was wide variation of both process and outcome results by individual centers. Composite calculations balanced out the differences seen in the individual measures. Despite using consistent quality definitions, the differences across centers had an impact on numerators and denominators. All sites agreed to a partnership model of EHR implementation, and each center utilized the available resources of the partnership for Center-specific quality initiatives.

CONCLUSIONS

Utilizing a shared EHR, a Regional Extension Center-like partnership model, and similar quality query algorithms allowed safety-net clinics to benchmark and improve the quality of care across differing patient populations and health care delivery models.