Measures Of Primary Care Quality Research Articles

KANSURVIVE: Testing a telementoring model for improving cancer survivorship care in rural practice.

e13791 Background: Cancer survivors require long-term, coordinated care to address the physical, emotional, and psychosocial effects of cancer and its treatment. KanSurvive, a single arm feasibility trial, evaluated the effectiveness of the KanSurvive ECHO intervention combined with practice facilitation (PF) to promote better adoption of evidence-based practice (EBP) survivorship care guidelines for breast, colorectal, lung, and prostate cancer among rural survivors. Methods: Fifteen primary care clinics in Kansas (80% in RUCA codes 4-10), including 62 healthcare professionals, were invited to participate in four, 1-hour Project ECHO telementoring program held in 2021. Real-time videoconferencing sessions covered EBP survivorship guidelines for breast, colorectal, lung, and prostate cancer. Clinics used brief plan-do-study-act cycles with PF supporting implementation of the quality improvement process. Utilizing the National Quality Forum framework, a performance indicator booklet with established measures in preventive health and cancer survivorship was developed as a data collection and quality improvement resource. Performance indicators included EBP screening actions related to cancer surveillance, lifestyle factors, distress, evidence of a review of family history of cancer, and the patient’s cancer diagnosis documented in the EHR. Results: Three clinics (7 = healthcare professionals) withdrew from the project citing competing demands and a provider leaving the practice. The COVID-19 pandemic delayed project initiation and prevented clinic visits. Recruitment and study procedures were implemented remotely. Clinic staff identified 138 cancer survivors (M = 13, IQR [6-16] per practice) seen in the year pre-intervention, and 129 survivors in the year prior to post-intervention. Pre-intervention, overall tumor surveillance was 91%, but lung cancer surveillance was lower than other tumor types at 70%. Other than surveillance, measures of baseline performance were similar across tumor types: screening for distress 84%, assessment of BMI 97%, screening for tobacco use 83% and documentation of family history 70%. Post-intervention performance indicators were similar except for documentation of family history which increased to 89% (p < 0.01). Conclusions: Standardized survivorship metrics can facilitate quality assessment as part of an ECHO-based cancer survivorship program. Although there are modest opportunities for improvement, PCPs in this study caring for rural patients perform reasonably well across a variety of cancer survivorship performance metrics comparable to national primary care quality measures. Documented assessment of family history of cancer lags other metrics and improved after participation in the KanSurvive telementoring program.

The Impact of Nurse Practitioner-Led Primary Care on Quality and Cost for Medicaid-Enrolled Patients in States With Pay Parity.

Studies have established that nurse practitioners (NPs) deliver primary care comparable to physicians in quality and cost, but most focus on Medicare, a program that reimburses NPs less than physicians. In this retrospective cohort study, we evaluated the quality and cost implications of receiving primary care from NPs compared to physicians in 14 states that reimburse NPs at the Medicaid fee-for-service (FFS) physician rate (i.e., pay parity). We linked national provider and practice data with Medicaid data for adults with diabetes and children with asthma (2012-2013). We attributed patients to primary care NPs and physicians based on 2012 evaluation & management claims. Using 2013 data, we constructed claims-based primary care quality measures and condition-specific costs of care for FFS enrollees. We estimated the effect of NP-led care on quality and costs using: (1) weighting to balance observable confounders and (2) an instrumental variable (IV) analysis using differential distance from patients' residences to primary care practices. Adults with diabetes received comparable quality of care from NPs and physicians at similar cost. Weighted results showed no differences between NP- and physician-attributed patients in receipt of recommended care or diabetes-related hospitalizations. For children with asthma, costs of NP-led care were lower but quality findings were mixed: NP-led care was associated with lower use of appropriate medications and higher rates of asthma-related emergency department visits but similar rates of asthma-related hospitalization. IV analyses revealed no evidence of differences in quality between NP- and physician-led care. Our findings suggest that in states with Medicaid pay parity, NP-led care is comparable to physician-led care for adults with diabetes, while associations between NP-led care and quality were mixed for children with asthma. Increased use of NP-led primary care may be cost-neutral or cost-saving, even under pay parity.

Impact of COVID-19 on Primary Care Quality Measures in an Academic Integrated Health System.

BackgroundAccess to primary care was hindered by the coronavirus disease 2019 (COVID-19) pandemic.ObjectiveEvaluate changes in health screening rates before and during the pandemic.DesignRetrospective analysis of health maintenance and disease management screening rates among primary care patients before and during the pandemic.ParticipantsOver 150,000 patients of a large, academic health system.Main MeasuresSix quality measures were analyzed: colon cancer, breast cancer, cervical cancer, diabetes Hgb A1C, diabetes eye, and diabetes nephropathy monitoring. Based on US Preventative Services Task Force screening guidelines, we determined which patients were due for at least one of the quality measures. We tracked completion rates during three time periods: pre-pandemic (January 1–March 3, 2020), stay-at-home (March 4–May 8, 2020), and phased reopening (May 9–July 8, 2020). Differences in quality measure completion rates were evaluated using mixed-effects logistic regression models.Key ResultsCompared to pre-pandemic rates, completion of all health screenings declined during the stay-at-home period: mammograms (OR: 0.34; 95% CI: 0.31–0.37), cervical cancer (OR: 0.83; 95% CI: 0.76–0.91), colorectal cancer (OR: 0.25; 95% CI: 0.23–0.28), diabetes eye (OR: 0.34; 95% CI: 0.29–0.41), diabetes Hgb A1c (OR: 0.41; 95% CI: 0.37–0.46), and diabetes nephropathy (OR: 0.46, 95% CI: 0.41–0.53). During phased reopening, completion of all quality measures increased compared to the stay-at-home period, except for cervical cancer screening (OR: 0.83; 95% CI: 0.76–0.92). There was a persistent reduction in completion of all quality measures, except for diabetic nephropathy monitoring (OR: 0.99; 95% CI: 0.89–1.09), during phased reopening compared to pre-pandemic.ConclusionsHealthcare screening rates were reduced during the early part of the COVID-19 pandemic and did not fully recover to pre-pandemic rates by July 2020. Future research should aim to clarify the long-term impacts of delayed health screenings. New interventions should be considered for expanding remote preventative health services.

Quality of primary care delivered to children with asthma in South London before the introduction of integrated child focused care model: a population cohort study of primary care records

BackgroundAsthma is one condition being evaluated in a randomised control trial (RCT) of the Children and Young People's Health Partnership (CYPHP) model of care across two boroughs in South London. The integrated, specialist nurse lead service aims to deliver focused, age appropriate, good quality care to improve child health, within an ethnically diverse and deprived population. Providing good quality, evidence-based care is vital to keep children with asthma healthy. This study aimed to determine the quality of asthma care provided to children in primary care before the introduction of CYPHP in May, 2018. MethodsWe examined primary care health records of children registered within GP practices in Southwark and Lambeth. We identified children aged 5–15 years between April 1, 2014, and March 31, 2018, with asthma by a coded asthma diagnosis or three or more asthma medications in a 12-month period, and with more than 400 days of continuous GP registration after their asthma was identified. Child asthma quality measures were determined from guidelines and published literature, as follows: children aged 5 years and older with asthma have a personalised action plan; an annual asthma review; asthma control monitored at review; documented height at review; and a prescribed spacer device (which optimises medication delivery). FindingsOf the 7995 children identified with asthma, 44% (n=3508) were from the most deprived fifth of the national population. 36% (n=2868) had a coded annual asthma review record, and 15% (n=1219) had a personalised asthma action plan. Of the 2868 children with a coded annual review, 98% (n=2806) had evidence of asthma control being monitored, while only 2% (n=70) had a coded height documented. 80% (n=6381) had ever been prescribed a spacer. InterpretationCoding of primary care quality measures for child asthma was poor before the CYPHP service. This finding does not mean that the care was not provided, because information could have been recorded as uncoded text. An audit of primary care records is needed to determine the uncoded care provided. Prescription data are complete for the period a child is registered at a given practice. The fact that 20% of children were never prescribed a spacer needs further investigation. FundingGuy's and St Thomas' Charity.

The Five‐Year Effect of Medicaid Expansion on Community Health Centers: Coverage, Quality of Care, and Service Volume

Our objective was to assess the five‐year impact of Medicaid expansion on community health centers using nationally representative data on all US health centers, where 35% of the patient population was uninsured prior to expansion. We examined the impact of expansion on insurance coverage and type, quality of care, and utilization of services. Understanding longer term effects of expansion is critical given that some quality measures may take multiple years to be clinically affected while pent‐up demand may also result in short‐term effects on utilization.Using the 2011‐2018 Uniform Data System, we conducted a difference‐in‐differences (DID) analysis with inverse probability of treatment weights (IPTWs), based on propensity scores, to compare outcomes in centers located in expansion versus nonexpansion states. Outcomes included insurance coverage type (none, Medicaid, private), 47 utilization measures (number of patient visits) for select categories of service and chronic conditions based on CPT and ICD codes, and 8 primary care quality measures that may be sensitive to Medicaid expansion. Propensity scores included 23 baseline covariates (patient demographics, health center organizational features, county‐level characteristics). For each measure, using IPTWs, a difference‐in‐difference was calculated using generalized linear models. We included a treatment indicator, time in postperiod indicator, treatment*post‐time interaction, vector of time‐variant covariates, state and year fixed effects, and clustered errors at the center‐level.100% sample of US health centers (N = 1061 centers/year, or 24.5 million patients/year, after exclusions).By 2018, compared to centers in nonexpansion states, centers in expansion states experienced a 12.0 percentage‐point decrease in the percent patients without health insurance (P < .001) and a 13.2 percentage‐point increase in those with Medicaid coverage (P < .001). These gains were largely driven by coverage gains in 2014‐2015.Medicaid expansion was associated with improved quality of care for 5 of 8 measures, though relative gains in quality dissipated over the five‐year postperiod for some measures (eg, asthma treatment) while relative gains for other measures (eg, colorectal cancer screening, diabetes control) were not detected until several years postexpansion. For instance, by 2018, expansion was a 4.5 percentage‐point relative increase in rates of HbA1c control among diabetics (95% CI 2.2‐6.8) and a 3.5 percentage‐point relative increase in colorectal cancer screening rates (95% CI 0.1‐6.9); neither measure was statistically affected until 3 years postexpansion.By 2018, Medicaid expansion was associated with relative increases in 31 of 47 patient visit measures. Effect sizes in 2018 were greatest for visits for HIV testing (IRR = 2.02), hepatitis C testing (IRR = 1.88), mammograms (IRR = 1.45), alcohol disorder (IRR = 1.50), depression (IRR = 1.47), and other mental health (IRR = 1.77) (P < .01).The first five years of Medicaid expansion were associated with increases in insurance coverage, measured quality, and visit volume among health center patients, where effects on quality of care for measures such as diabetes control were not detected until three years into the postperiod.Findings highlight the longer term, significant role of Medicaid expansion in improving quality and in building capacity for health centers. This is particularly important in light of federal and state decisions about the future of Medicaid and extension of health center grant funding.Agency for Healthcare Research and Quality.

Does Provider Gender Affect the Quality of Primary Care?

Women providers have a more patient-centered communication style than men, and some studies have found women primary care providers are more likely to meet quality performance measures. To explore gender differences in the quality of primary care process and outcome measures. Retrospective analysis of primary care performance data from 1year (2018-2019). A total of 586 primary care providers (311 women and 275 men) who cared for 241,428 primary care patients at 96 primary care clinics at 8 Veterans Affairs (VA) medical centers. Our primary outcome was a composite quality measure that averaged all thirty-four primary care performance measures that assessed performance in cancer screening, diabetes care, cardiovascular care, tobacco counseling, risky alcohol screening, immunizations, HIV testing, opiate care, and continuity. Our secondary outcomes were performance on each of the 34 measures. There was no difference in the average performance on our composite measure between men and women (75.8% vs. 76.6%, p = 0.17). Among the 34 primary care quality measures collected, there was no difference between male and female providers' performance. Using a more conservative cut-point, women were more likely to screen at-risk diabetic patients for hypoglycemia and document follow-up on risky alcohol behavior noted during patient check-in. These differences were clinically small and likely due to chance, given the multiple measures evaluated in this study. We found little evidence of difference in the performance on primary care quality measures between male and female providers.

Balancing patient priorities for technical and interactional aspects of care in a measure of primary care quality.

This study attempts to strike a balance to measure primary care quality in a way that considers what is important to patients, providers and the healthcare system, all at the same time. The interest in delivering patient-centered primary care implies a need for patient-centered performance measurement. However, the distinction between measures of patient experience and technical aspects of care raises an unanswerable question: if a provider has good performance on technical measures but not on patient experience measures (or vice versa), what can be said about the quality of care? We surveyed patients to determine the relative priorities of each of a series of primary care measures in the patients' relationship with their primary care provider. The on-line survey was co-designed with patient co-investigators. The items consisted of 14 primary care quality measures used in pre-existing performance report, 41 additional indicators including a novel set of patient-generated Key Performance Indicators and 17 questions about patients' demographics, health and socioeconomic status as well as open-ended questions. Despite challenges, the study suggests that this is feasible. We argue that it is necessary to get better at measuring and finding ever-better ways to put patients at the center of primary care.

The Effect of Primary Care Team Realignment on Point-of-Care Screening.

Reporting primary care quality measures is an essential component of value-based care delivery and is part of the strategy to bend the health care cost curve. As primary care physicians are increasingly pressed for time, incorporating ancillary staff screening into pre-visit workflows can increase screening rates, but can pose a challenge in large practice settings. The objective was to improve screening rates for depression and falls risk at a large, urban primary care practice. Jefferson Family Medicine Associates is a practice in downtown Philadelphia that serves 35,000 patients and provides approximately 80,000 visits annually. The majority of patients are African American. Screening responsibilities were realigned within medical assistant workflows, and a training program was designed and implemented to ensure its success and sustainability. Monthly Group Practice Reporting Option data on depression screening and falls risk screening was collected from January 1, 2015, to October 31, 2016. The primary outcome measures were the rate of depression screening and falls risk screening performed for patients who had a visit during the study period. The average monthly depression screening rate changed from 1.41% pre intervention to 49.77% post intervention (z = -100.65; P < .001). The average monthly falls screening rate changed from 19.23% pre intervention to 61.33% post intervention (z = -77.97, P < .001). This workflow redesign, training model, and implementation was successful at increasing screening rates for depression and falls risk, and may benefit other practices that hope to accomplish similar quality measure improvements.

The ethics of setting national antibiotic policies using financial incentives.

Antimicrobial resistance (AMR) is an increasingly urgent global public health issue. Data from Public Health England — from the English Surveillance Programme for Antimicrobial Utilisation and Resistance (ESPAUR) — quantifies the scale of antibiotic resistance in key bacterial pathogens. The Department of Health’s 5-year strategy to reduce morbidity and mortality associated with AMR (2013–2018) focused on optimising antibiotic prescribing and improving infection prevention and control.1 In April 2015 NHS England introduced a Quality Premium (QP) focusing on reducing antibiotics. QPs are financial rewards, with a maximal value equivalent to £5 per patient, intended to reward clinical commissioning groups (CCGs) for improvements in the quality of the services that they commission and for associated improvements in health outcomes and reducing inequalities. The AMR QP provided commissioners with financial incentives to reduce antibiotic prescribing; 80% were linked to primary care quality measures (reduction in absolute number of antibiotic prescriptions by 1%, decrease in use of broad spectrum antibiotics by 10%) and 20% linked to improving availability of antibiotic prescribing data from secondary care.2 Incentives are a tool that governments use to help support behaviour change, are a recognised domain in behaviour change methodology, and can be considered a form of trade. CCGs are offered an incentive in the form of additional funds for investment if they have reduced antibiotic prescribing. However, the CCG also has to show that it manages public funds responsibly and will only receive a QP if it has managed its funds according to the ‘Managing Public Money’ guidelines and does not require financial support during the financial year (nor deviate substantially from expected surpluses/deficits).2 In 2014/2015 only 27% of the total available QP was achieved by CCGs. Although the financial incentive is directed towards CCGs, the behavioural change being targeted is at the level of …

Do higher primary care practice performance scores predict lower rates of emergency admissions for persons with serious mental illness? An analysis of secondary panel data

BackgroundSerious mental illness (SMI) is a set of chronic enduring conditions including schizophrenia and bipolar disorder. SMIs are associated with poor outcomes, high costs and high levels of disease burden. Primary care plays a central role in the care of people with a SMI in the English NHS. Good-quality primary care has the potential to reduce emergency hospital admissions, but also to increase elective admissions if physical health problems are identified by regular health screening of people with SMIs. Better-quality primary care may reduce length of stay (LOS) by enabling quicker discharge, and it may also reduce NHS expenditure.ObjectivesWe tested whether or not better-quality primary care, as assessed by the SMI quality indicators measured routinely in the Quality and Outcomes Framework (QOF) in English general practice, is associated with lower rates of emergency hospital admissions for people with SMIs, for both mental and physical conditions and with higher rates of elective admissions for physical conditions in people with a SMI. We also tested the impact of SMI QOF indicators on LOS and costs.DataWe linked administrative data from around 8500 general practitioner (GP) practices and from Hospital Episode Statistics for the study period 2006/7 to 2010/11. We identified SMI admissions by a mainInternational Classification of Diseases, 10th revision (ICD-10) diagnosis of F20–F31. We included information on GP practice and patient population characteristics, area deprivation and other potential confounders such as access to care. Analyses were carried out at a GP practice level for admissions, but at a patient level for LOS and cost analyses.MethodsWe ran mixed-effects count data and linear models taking account of the nested structure of the data. All models included year indicators for temporal trends.ResultsContrary to expectation, we found a positive association between QOF achievement and admissions, for emergency admissions for both mental and physical health. An additional 10% in QOF achievement was associated with an increase in the practice emergency SMI admission rate of approximately 1.9%. There was no significant association of QOF achievement with either LOS or cost. All results were robust to sensitivity analyses.ConclusionsPossible explanations for our findings are (1) higher quality of primary care, as measured by QOF may not effectively prevent the need for secondary care; (2) patients may receive their QOF checks post discharge, rather than prior to admission; (3) people with more severe SMIs, at a greater risk of admission, may select into practices that are better organised to provide their care and which have better QOF performance; (4) better-quality primary care may be picking up unmet need for secondary care; and (5) QOF measures may not accurately reflect quality of primary care. Patient-level data on quality of care in general practice is required to determine the reasons for the positive association of QOF quality and admissions. Future research should also aim to identify the non-QOF measures of primary care quality that may reduce unplanned admissions more effectively and could potentially be incentivised.FundingThe National Institute for Health Research Health Services and Delivery Research programme.

PP23 Variation of Primary Care Quality with Contract type: An Observational Study

BackgroundSince 2004, policy reforms in the English NHS have allowed new contracting mechanisms for provision of general practice services. A wider variety of provider organisations were allowed under the alternative...

Quality Measures for Primary Care of Complex Pediatric Patients

A well-recognized gap exists in assessing and improving the quality of care for medically complex patients. Our objective was to examine evidence for primary care based on the patient-centered medical home model and to identify valid and meaningful quality measures for use in complex pediatric patients. We conducted literature searches on Medline and the National Quality Measures Clearinghouse for existing measures, as well as evidence to inform the development of new quality measures. We used a 3-step process to select relevant sources from published literature: (1) the titles were screened by 2 independent reviewers; (2) the abstracts were reviewed for quality-of-care contents or constructs; and (3) full-text articles were obtained and reviewed for measure specification. All materials were reviewed for the Oxford Centre For Evidence-Based Medicine level of evidence and for relevance to primary care of complex pediatric patients. A national expert panel was convened to evaluate and rate the measures by using the Rand/University of California Los Angeles Appropriateness Method. We presented 74 quality measures to the expert panel for review and discussion. The panel rated and accepted 35 measures as valid and feasible for assessing primary care quality in complex pediatric patients. The final set of quality measures was grouped in the following domains: primary care-general (14), patient/family-centered care (8), chronic care (2), coordination of care (9), and transition of care (2). By using the patient-centered medical home framework of accessible, continuous, family-centered, coordinated, and culturally effective care, a national expert panel selected 35 primary care quality measures for complex pediatric patients.

What The United States Could Learn From Israel About Improving The Quality Of Health Care

In 1999 Israel began to implement a system for monitoring quality of care in its health plans. That system was based largely on a similar system in the United States that, until recently, was associated with steady improvements in performance. However, in recent years health plan quality in the United States appears to have reached a plateau. In contrast, health plans in Israel have continued to show improvements on many of the same measures. Between 2005 and 2007 they achieved a gain of 6.7 percent in nine measures of primary care quality, while US performance on these measures declined. These gains were achieved, in part, through intense cooperation among health plans and physicians. Israel is a much smaller country and differs greatly from the United States in how it finances health care. Nonetheless, we suggest that the Israeli experience could help the United States accelerate the move toward quality improvement-for example, through increased coordination among US employers, health plans, physicians, and physician groups.

Validity of the Family Asthma Management System Scale with an Urban African-American Sample

To examine the reliability and validity of the Family Asthma Management System Scale for low-income African-American children with poor asthma control and caregivers under stress. The FAMSS assesses eight aspects of asthma management from a family systems perspective. Forty-three children, ages 8-13, and caregivers were interviewed with the FAMSS; caregivers completed measures of primary care quality, family functioning, parenting stress, and psychological distress. Children rated their relatedness with the caregiver, and demonstrated inhaler technique. Medical records were reviewed for dates of outpatient visits for asthma. The FAMSS demonstrated good internal consistency. Higher scores were associated with adequate inhaler technique, recent outpatient care, less parenting stress and better family functioning. Higher scores on the Collaborative Relationship with Provider subscale were associated with greater perceived primary care quality. The FAMSS demonstrated relevant associations with asthma management criteria and family functioning for a low-income, African-American sample.

Associations Between Structural Capabilities of Primary Care Practices and Performance on Selected Quality Measures

Recent proposals to reform primary care have encouraged physician practices to adopt such structural capabilities as performance feedback and electronic health records. Whether practices with these capabilities have higher performance on measures of primary care quality is unknown. To measure associations between structural capabilities of primary care practices and performance on commonly used quality measures. Cross-sectional analysis. Massachusetts. 412 primary care practices. During 2007, 1 physician from each participating primary care practice (median size, 4 physicians) was surveyed about structural capabilities of the practice (responses representing 308 practices were obtained). Data on practice structural capabilities were linked to multipayer performance data on 13 Healthcare Effectiveness Data and Information Set (HEDIS) process measures in 4 clinical areas: screening, diabetes, depression, and overuse. Frequently used multifunctional electronic health records were associated with higher performance on 5 HEDIS measures (3 in screening and 2 in diabetes), with statistically significant differences in performance ranging from 3.1 to 7.6 percentage points. Frequent meetings to discuss quality were associated with higher performance on 3 measures of diabetes care (differences ranging from 2.3 to 3.1 percentage points). Physician awareness of patient experience ratings was associated with higher performance on screening for breast cancer and cervical cancer (1.9 and 2.2 percentage points, respectively). No other structural capabilities were associated with performance on more than 1 measure. No capabilities were associated with performance on depression care or overuse. Structural capabilities of primary care practices were assessed by physician survey. Among the investigated structural capabilities of primary care practices, electronic health records were associated with higher performance across multiple HEDIS measures. Overall, the modest magnitude and limited number of associations between structural capabilities and clinical performance suggest the importance of continuing to measure the processes and outcomes of care for patients. The Commonwealth Fund.