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.

Developing Composite Quality Measures for EHR-Enabled Primary Care Practices in New York City.

We describe the process of developing composite quality measures (CQMs). During the initial consultative process, we grouped quality measures based on the associated clinical workflow and difficulty, and then confirmed the groupings with factor analysis. The CQMs are estimated as the mean of the measures for each group. We used analysis of variance followed by a post hoc analysis to assess: (1) performance among the different CQMs each year; and (2) the performance trend for each of the composite measures from 2009 to 2011. The four CQMs were Control-BP, Control-Other, Assessment, and Screening. Performance was highest at baseline for Control-BP (58%, SD 15.07), followed by Control-Other (48.04%, SD 22.75), Screening (46.49%, SD 20.21), and Assessment (42.15%, SD 19.08). Performance on the CQMs increased significantly with time, whereas the gap between the CQMs decreased significantly over time. The CQMs reflect the clinical care domains, and practice performance is influenced by electronic health record functionality, clinician workflow, and clinical difficulty.

Patient Characteristics Associated With Smoking Cessation Interventions and Quit Attempt Rates Across 10 Community Health Centers With Electronic Health Records.

OBJECTIVES: We used electronic health record (EHR) data to determine rates and patient characteristics in offering cessation interventions (counseling, medications, or referral) and initiating quit attempts. METHODS: Ten community health centers in New York City contributed 30 months of de-identified patient data from their EHRs. RESULTS: Of 302 940 patients, 40% had smoking status recorded and only 34% of documented current smokers received an intervention. Women and younger patients were less likely to have their smoking status documented or to receive an intervention. Patients with comorbidities that are exacerbated by smoking were more likely to have status documented (82.2%) and to receive an intervention (52.1%), especially medication (10.8%). Medication, either alone (odds ratio [OR] = 1.9; 95% confidence interval [CI] = 1.5, 2.3) or combined with counseling (OR = 1.8; 95% CI = 1.5, 2.3), was associated with higher quit attempts compared with no intervention. CONCLUSIONS: Data from EHRs demonstrated underdocumentation of smoking status and missed opportunities for cessation interventions. Use of data from EHRs can facilitate quality improvement efforts to increase screening and intervention delivery, with the potential to improve smoking cessation rates.

Designing a quality improvement program with electronic health records: New York City's Health eQuits.

Despite clear recommendations for identifying and intervening with smokers, clinical preventive practice is inconsistent in primary care. Use of electronic health records could facilitate improvement. Community health centers treating low-income and Medicaid recipients with greater smoking prevalence than the general population were recruited for a pilot program. Key design elements used to engage centers' participation include designating a project champion at each organization, confirming ability to transmit data for reporting and participation, and offering money to facilitate initial engagement; however, financial incentives did not motivate all organizations. Other methods to elicit participation and to motivate practice change included building on centers' previous experiences with similar programs, utilizing existing relationships with state cessation centers, and harnessing the "competitive" spirit-sharing both good news and areas for improvement to stimulate action. These experiences and observations may assist others in designing programs to improve clinical interventions with smokers.

Increases in smoking cessation interventions after a feedback and improvement initiative using electronic health records -- 19 community health centers, New York City, October 2010-March 2012.

Quitting smoking substantially reduces smokers' risk for smoking-related morbidity and mortality and can increase life expectancy by up to a decade. Most smokers want to quit and make at least one medical provider visit annually. Health care providers can play an important role in helping smokers quit by documenting patients' tobacco use, advising smokers to quit, and providing evidence-based cessation treatments or referrals for treatment, but many providers and practices do not regularly take these actions. Systems to increase provider screening and delivery of cessation interventions are available; in particular, electronic health records (EHRs) can be powerful tools to facilitate increased cessation interventions. This analysis reports on an EHR-based pay-for-improvement initiative in 19 community health centers (CHCs) in New York City (NYC) that sought to increase smoking status documentation and cessation interventions. At the end of the initiative, the mean proportion of patients who were documented as smokers in CHCs had increased from 24% to 27%, whereas the mean proportion of documented smokers who received a cessation intervention had increased from 23% to 54%. Public health programs and health systems should consider implementing strategies to equip and train clinical providers to use information technology to increase delivery of cessation interventions.

Patient experiences at primary care practices using electronic health records.

We assessed patient experiences before and one year after electronic health record (EHR) implementation among primary care practices in New York City. These practices represented an ethnically diverse population in lower-income, urban communities. Surveys, available in English, Spanish, and Chinese languages, were administered at 10 sites. Generally, patients reported positive responses during both periods. After EHR implementation, patients were more likely to want e-mail communication with their doctors' office. The 70% of patients with Internet access were generally more satisfied with their experience and more likely to recognize benefits of EHRs. However, older patients and those with lower education levels or chronic diseases were significantly less likely than their counterparts to use the Internet. Therefore, disparities in Internet access could potentially lead to unequal access and use of healthcare if not addressed. Practices should routinely record patient communication preferences within the EHR, to tailor communications and improve patient experiences.

Skeletal consequences of hormone therapy discontinuance: a systematic review.

UNLABELLED: Although hormone therapy protects against bone loss after menopause, currently it is not recommended once menopausal symptoms have subsided. We reviewed randomized clinical trials to quantify bone loss after stopping hormone therapy and summarize treatment options for women who discontinue hormone treatment. We conducted a search of MEDLINE and EMBASE for randomized, controlled trials measuring bone mineral density (BMD) after hormone therapy discontinuation. Other known published and unpublished data were also included. Eleven studies fulfilled the search criteria. In each, bone loss was rapid after stopping hormone therapy, with BMD declines ranging from 2.3% to 6.2% in the first year. Increases in bone turnover markers also occurred rapidly when hormone therapy was stopped. Limited data addressing treatment after hormone therapy is stopped exist; only 2 studies specifically evaluated therapy to protect bone after hormone discontinuation. Taken together, these 2 studies demonstrate that alendronate produced significant increases relative to placebo in spine, hip, and total body BMD in women with low bone density who had discontinued hormone therapy within the past 3 months, preventing the rapid bone loss seen on discontinuation of hormone therapy. Among treatment options for preventing bone loss on discontinuation of hormone therapy for which randomized clinical trial data are available, alendronate prevented bone loss or increased bone density in postmenopausal women with low bone density. Women who are discontinuing hormone therapy should be counseled about potential bone loss and effective treatment options. TARGET AUDIENCE: Obstetricians & Gynecologists, Family Physicians. LEARNING OBJECTIVES: After completion of this article, the reader should be able to state that discontinuation of replacement menopausal hormone therapy, which protects against bone loss, is not recommended after menopause symptoms have subsided; recall that it may accelerate bone loss; and explain that there is bone loss preventive treatment for women after discontinuation of hormone therapy.

The effect of raloxifene on the incidence of ovarian cancer in postmenopausal women.

OBJECTIVE: The aim of this study was to determine the incidence of ovarian cancer in postmenopausal women treated with raloxifene compared with placebo. METHODS: This analysis comprises integrated data from seven randomized, placebo-controlled trials of raloxifene (N = 9837). Ovarian cancer cases were identified from the safety database and reviewed by a gynecologic adjudication review board. RESULTS: Sixteen cases of ovarian cancer were reported: 8 women (79.4/100,000 patient-years) on placebo and 8 (37.4/100,000 patient-years) on pooled raloxifene doses. The relative risk of ovarian cancer associated with raloxifene therapy was 0.50 (95% confidence interval, 0.19-1.35). CONCLUSION: Raloxifene use was not associated with an increased risk for ovarian cancer.