Multi-Institutional Sharing of Electronic Health Record Data to Assess Childhood Obesity

Objective

To evaluate the validity of multi-institutional electronic health record (EHR) data sharing for surveillance and study of childhood obesity.

Methods

We conducted a non-concurrent cohort study of 528,340 children with outpatient visits to six pediatric academic medical centers during 2007–08, with sufficient data in the EHR for body mass index (BMI) assessment. EHR data were compared with data from the 2007–08 National Health and Nutrition Examination Survey (NHANES).

Results

Among children 2–17 years, BMI was evaluable for 1,398,655 visits (56%). The EHR dataset contained over 6,000 BMI measurements per month of age up to 16 years, yielding precise estimates of BMI. In the EHR dataset, 18% of children were obese versus 18% in NHANES, while 35% were obese or overweight versus 34% in NHANES. BMI for an individual was highly reliable over time (intraclass correlation coefficient 0.90 for obese children and 0.97 for all children). Only 14% of visits with measured obesity (BMI ≥95%) had a diagnosis of obesity recorded, and only 20% of children with measured obesity had the diagnosis documented during the study period. Obese children had higher primary care (4.8 versus 4.0 visits, p<0.001) and specialty care (3.7 versus 2.7 visits, p<0.001) utilization than non-obese counterparts, and higher prevalence of diverse co-morbidities. The cohort size in the EHR dataset permitted detection of associations with rare diagnoses. Data sharing did not require investment of extensive institutional resources, yet yielded high data quality.

Conclusions

Multi-institutional EHR data sharing is a promising, feasible, and valid approach for population health surveillance. It provides a valuable complement to more resource-intensive national surveys, particularly for iterative surveillance and quality improvement. Low rates of obesity diagnosis present a significant obstacle to surveillance and quality improvement for care of children with obesity.     

Levels of State and Trait Anxiety in Patients Referred to Ophthalmology by Primary Care Clinicians: A Cross Sectional Study

Purpose

There is a high level of over-referral from primary eye care leading to significant numbers of people without ocular pathology (false positives) being referred to secondary eye care. The present study used a psychometric instrument to determine whether there is a psychological burden on patients due to referral to secondary eye care, and used Rasch analysis to convert the data from an ordinal to an interval scale.

Design

Cross sectional study.

Participants and Controls

322 participants and 80 control participants.

Methods

State (i.e. current) and trait (i.e. propensity to) anxiety were measured in a group of patients referred to a hospital eye department in the UK and in a control group who have had a sight test but were not referred. Response category analysis plus infit and outfit Rasch statistics and person separation indices were used to determine the usefulness of individual items and the response categories. Principal components analysis was used to determine dimensionality.

Main Outcome Measure

Levels of state and trait anxiety measured using the State-Trait Anxiety Inventory.

Results

State anxiety scores were significantly higher in the patients referred to secondary eye care than the controls (p<0.04), but similar for trait anxiety (p>0.1). Rasch analysis highlighted that the questionnaire results needed to be split into “anxiety-absent” and “anxiety-present” items for both state and trait anxiety, but both subscales showed the same profile of results between patients and controls.

Conclusions

State anxiety was shown to be higher in patients referred to secondary eye care than the controls, and at similar levels to people with moderate to high perceived susceptibility to breast cancer. This suggests that referral from primary to secondary eye care can result in a significant psychological burden on some patients.     

Multimorbidity Patterns in Elderly Primary Health Care Patients in a South Mediterranean European Region: A Cluster Analysis

Objective

The purpose of this study was to identify clusters of diagnoses in elderly patients with multimorbidity, attended in primary care.

Design

Cross-sectional study.

Setting

251 primary care centres in Catalonia, Spain.

Participants

Individuals older than 64 years registered with participating practices.

Main outcome measures

Multimorbidity, defined as the coexistence of 2 or more ICD-10 disease categories in the electronic health record. Using hierarchical cluster analysis, multimorbidity clusters were identified by sex and age group (65–79 and ≥80 years).

Results

322,328 patients with multimorbidity were included in the analysis (mean age, 75.4 years [Standard deviation, SD: 7.4], 57.4% women; mean of 7.9 diagnoses [SD: 3.9]). For both men and women, the first cluster in both age groups included the same two diagnoses: Hypertensive diseases and Metabolic disorders. The second cluster contained three diagnoses of the musculoskeletal system in the 65- to 79-year-old group, and five diseases coincided in the ≥80 age group: varicose veins of the lower limbs, senile cataract, dorsalgia, functional intestinal disorders and shoulder lesions. The greatest overlap (54.5%) between the three most common diagnoses was observed in women aged 65–79 years.

Conclusion

This cluster analysis of elderly primary care patients with multimorbidity, revealed a single cluster of circulatory-metabolic diseases that were the most prevalent in both age groups and sex, and a cluster of second-most prevalent diagnoses that included musculoskeletal diseases. Clusters unknown to date have been identified. The clusters identified should be considered when developing clinical guidance for this population.     

Modeling Disease Severity in Multiple Sclerosis Using Electronic Health Records

Objective

To optimally leverage the scalability and unique features of the electronic health records (EHR) for research that would ultimately improve patient care, we need to accurately identify patients and extract clinically meaningful measures. Using multiple sclerosis (MS) as a proof of principle, we showcased how to leverage routinely collected EHR data to identify patients with a complex neurological disorder and derive an important surrogate measure of disease severity heretofore only available in research settings.

Methods

In a cross-sectional observational study, 5,495 MS patients were identified from the EHR systems of two major referral hospitals using an algorithm that includes codified and narrative information extracted using natural language processing. In the subset of patients who receive neurological care at a MS Center where disease measures have been collected, we used routinely collected EHR data to extract two aggregate indicators of MS severity of clinical relevance multiple sclerosis severity score (MSSS) and brain parenchymal fraction (BPF, a measure of whole brain volume).

Results

The EHR algorithm that identifies MS patients has an area under the curve of 0.958, 83% sensitivity, 92% positive predictive value, and 89% negative predictive value when a 95% specificity threshold is used. The correlation between EHR-derived and true MSSS has a mean R² = 0.38±0.05, and that between EHR-derived and true BPF has a mean R² = 0.22±0.08. To illustrate its clinical relevance, derived MSSS captures the expected difference in disease severity between relapsing-remitting and progressive MS patients after adjusting for sex, age of symptom onset and disease duration (p = 1.56×10⁻¹²).

Conclusion

Incorporation of sophisticated codified and narrative EHR data accurately identifies MS patients and provides estimation of a well-accepted indicator of MS severity that is widely used in research settings but not part of the routine medical records. Similar approaches could be applied to other complex neurological disorders.     

Hospital Admissions in Children with Down Syndrome: Experience of a Population-Based Cohort Followed from Birth

Objective

Children with Down syndrome, the most common genetic cause of intellectual disability, are prone to multiple and varied health-related problems. This study describes patterns of hospitalisations for children and young people with Down syndrome in Western Australia.

Methods

Birth records were linked to the Western Australian population-based Intellectual Disability database to identify all children born with Down syndrome in Western Australia between 1 January, 1983 and 31 December, 1999. These records were linked to the Hospital Morbidity Data System to provide information on all hospitalisations up to 31 December, 2004. Hospitalisation data, coded using ICD-9CM or ICD-10 (v0.5) were grouped into clinically relevant categories using the primary diagnosis. Rates of hospital admission for all and specific diagnoses were expressed in 1000-person-years at-risk and median age at first admission and length of stay were calculated.

Results

Of the 405 children, 395 had one or more hospital admissions, totalling 3786 admissions for all children and an estimated 39.5 person-years in hospital. On average, children were admitted 9.7 times, with an estimated rate of 757.2 admissions per 1000pyr (95% CI: 680, 843). A quarter of all admissions occurred in the first year of life. The average hospital length of stay was 3.8 days (95% CI: 3.7, 4.1). Upper respiratory tract conditions affected the most children (58.5%) and accounted for 12.1% of all admissions. Other disorders which affected a high percentage of children were ear/hearing conditions (50.6%), disorders of the oral cavity (38.0%) and lower respiratory tract conditions (37.5%). Overall, children with Down syndrome were hospitalised at a rate five times (95% CI = 4.3–6.2) that of the general population.

Conclusion

Children with Down syndrome are at increased risk of morbidity for varied causes underlining the importance of comprehensive and targeted primary care for this group.     

Extracting diagnoses and investigation results from unstructured text in electronic health records by semi-supervised machine learning

Background

Electronic health records are invaluable for medical research, but much of the information is recorded as unstructured free text which is time-consuming to review manually.

Aim

To develop an algorithm to identify relevant free texts automatically based on labelled examples.

Methods

We developed a novel machine learning algorithm, the ‘Semi-supervised Set Covering Machine’ (S3CM), and tested its ability to detect the presence of coronary angiogram results and ovarian cancer diagnoses in free text in the General Practice Research Database. For training the algorithm, we used texts classified as positive and negative according to their associated Read diagnostic codes, rather than by manual annotation. We evaluated the precision (positive predictive value) and recall (sensitivity) of S3CM in classifying unlabelled texts against the gold standard of manual review. We compared the performance of S3CM with the Transductive Vector Support Machine (TVSM), the original fully-supervised Set Covering Machine (SCM) and our ‘Freetext Matching Algorithm’ natural language processor.

Results

Only 60% of texts with Read codes for angiogram actually contained angiogram results. However, the S3CM algorithm achieved 87% recall with 64% precision on detecting coronary angiogram results, outperforming the fully-supervised SCM (recall 78%, precision 60%) and TSVM (recall 2%, precision 3%). For ovarian cancer diagnoses, S3CM had higher recall than the other algorithms tested (86%). The Freetext Matching Algorithm had better precision than S3CM (85% versus 74%) but lower recall (62%).

Conclusions

Our novel S3CM machine learning algorithm effectively detected free texts in primary care records associated with angiogram results and ovarian cancer diagnoses, after training on pre-classified test sets. It should be easy to adapt to other disease areas as it does not rely on linguistic rules, but needs further testing in other electronic health record datasets.     

Early Diagnosis of Extrahepatic Biliary Atresia in an Open-Access Medical System

Introduction

Biliary atresia (BA) is the most common cause of cholestatic jaundice in infancy. Early diagnosis and surgical management, ideally before 60 days of age, result in improved outcomes. We aimed to determine the age at diagnosis of BA in the Military Health System (MHS) and to compare the age at diagnosis by access to care models. We hypothesized that children with BA receiving primary care in military facilities have an earlier age at diagnosis due to decreased economic and access barriers.

Methods

Data for all Tricare enrollees born in fiscal years 2004–2008 with a diagnosis of BA were extracted from MHS databases. Non-parametric tests, Kaplan-Meier curves and log rank tests compared differences in age at diagnosis by type of primary care facility, gender, prematurity and presence of additional anomalies.

Results

64 subjects were identified within the five year period. Median age at diagnosis was 40 days [range 1–189], with 67% diagnosed by 60 days and 80% by 90 days. 45 (70%) received civilian primary care within the MHS. There was no difference in the median age at diagnosis between subjects in the MHS with civilian primary care vs. military primary care (37 days [1–188] vs. 46 days [1–189]; p = 0.58).

Conclusion

In the MHS, two-thirds of infants with biliary atresia are diagnosed prior to 60 days of life. Gender, prematurity or presence of additional anomalies do not affect the timing of diagnosis. Civilian and military primary care models within the MHS make timely diagnoses of biliary atresia at equivalent rates.     

Prospective Study of the Quality of Colonoscopies Performed by Primary Care Physicians: The Alberta Primary Care Endoscopy (APC-Endo) Study

Background

The quality of colonoscopies performed by primary care physicians (PCPs) is unknown.

Objective

To determine whether PCP colonoscopists achieve colonoscopy quality benchmarks, and patient satisfaction with having their colonoscopy performed by a primary care physician.

Design

Prospective multi-center, multi-physician observational study. Colonoscopic quality data collection occurred via completion of case report forms and pathological confirmation of lesions. Patient satisfaction was captured by a telephone survey.

Setting

Thirteen rural and suburban hospitals in Alberta, Canada.

Measurements

Proportion of successful cecal intubations, average number of adenomas detected per colonoscopy, proportion of patients with at least one adenoma, and serious adverse event rates; patient satisfaction with their wait time and procedure, as well as willingness to have a repeat colonoscopy performed by their primary care endoscopist.

Results

In the two-month study period, 10 study physicians performed 577 colonoscopies. The overall adjusted proportion of successful cecal intubations was 96.5% (95% CI 94.6–97.8), and all physicians achieved the adjusted cecal intubation target of ≥90%. The average number of ademonas detected per colonoscopy was 0.62 (95% CI 0.5–0.74). 46.4% (95% CI 38.5–54.3) of males and 30.2% (95% CI 22.3–38.2) of females ≥50 years of age having their first colonoscopy, had at least one adenoma. Four serious adverse events occurred (three post polypectomy bleeds and one perforation) and 99.3% of patients were willing to have a repeat colonoscopy performed by their primary care colonoscopist.

Limitations

Two-month study length and non-universal participation by Alberta primary care endoscopists.

Conclusions

Primary care physician colonoscopists can achieve quality benchmarks in colonoscopy. Training additional primary care physicians in endoscopy may improve patient access and decrease endoscopic wait times, especially in rural settings.     

Skin Autofluorescence,a Non-Invasive Marker for AGE Accumulation,Is Associated with the Degree of Atherosclerosis

Introduction

Advanced glycation endproducts (AGEs) may be involved in the development of atherosclerosis, beyond diabetes and renal disease. Skin autofluorescence (AF) is a non-invasive marker for AGEs. We examined whether skin AF is increased in (subclinical) atherosclerosis and associated with the degree of atherosclerosis independent of diabetes and renal function.

Methods

A cross-sectional study of 223 patients referred for primary (n = 163) or secondary (n = 60) prevention between 2006 and 2012 was performed. Skin AF was measured using the AGE-Reader. Ultrasonography was used to assess plaques in carotid and femoral arteries and computed tomography for the calculation of the coronary artery calcium score (CACS; in primary prevention only). Primary prevention patients were divided into a group with subclinical atherosclerosis defined as >1 plaque or CACS>100 (n = 67; age 53 year [interquartile range 48–56]; 49% male) and without (controls; 96; 43 [38–51]; 55%). Secondary prevention were patients with peripheral arterial disease (60; 64 [58–70]; 73%).

Results

Skin AF was higher in subclinical and clinical atherosclerosis compared with controls (skin AF 2.11 [interquartile range 1.83–2.46] and 2.71 [2.15–3.27] vs. 1.87 [1.68–2.12] respectively; P = 0.005 and <0.001). In a multivariate analysis, the association of skin AF with the atherosclerosis categories was independent of age, sex, diabetes, presence of the metabolic syndrome, Framingham Risk Score, and renal function. Skin AF correlated with most cardiovascular risk factors, Framingham risk score, and IMT and CACS.

Conclusions

Skin AF is increased in documented subclinical and clinical atherosclerosis, independent of known risk factors such as diabetes and renal disease. These data suggest that AGEs may be associated with the burden of atherosclerosis and warrant a prospective study to investigate its clinical usability as a risk assessment tool for primary prevention.     

Signs of the 2009 Influenza Pandemic in the New York-Presbyterian Hospital Electronic Health Records

Background

In June of 2009, the World Health Organization declared the first influenza pandemic of the 21^st century, and by July, New York City''s New York-Presbyterian Hospital (NYPH) experienced a heavy burden of cases, attributable to a novel strain of the virus (H1N1pdm).

Methods and Results

We present the signs in the NYPH electronic health records (EHR) that distinguished the 2009 pandemic from previous seasonal influenza outbreaks via various statistical analyses. These signs include (1) an increase in the number of patients diagnosed with influenza, (2) a preponderance of influenza diagnoses outside of the normal flu season, and (3) marked vaccine failure. The NYPH EHR also reveals distinct age distributions of patients affected by seasonal influenza and the pandemic strain, and via available longitudinal data, suggests that the two may be associated with distinct sets of comorbid conditions as well. In particular, we find significantly more pandemic flu patients with diagnoses associated with asthma and underlying lung disease. We further observe that the NYPH EHR is capable of tracking diseases at a resolution as high as particular zip codes in New York City.

Conclusion

The NYPH EHR permits early detection of pandemic influenza and hypothesis generation via identification of those significantly associated illnesses. As data standards develop and databases expand, EHRs will contribute more and more to disease detection and the discovery of novel disease associations.     

The risk for depression in patients with ankylosing spondylitis: a population-based cohort study

Introduction

Depression is frequent in ankylosing spondylitis (AS) patients. However, epidemiological data about the potential increase in risk are lacking. This study compares the rate of doctor-diagnosed depression in a well defined cohort of AS patients to the general population seeking care.

Methods

The Skåne Healthcare Register comprises healthcare data of each resident in Region Skåne, Sweden (population 1.2 million), including ICD-10 diagnoses. Using physician coded consultation data from years 1999 to 2011, we calculated depression consultation rates for all AS patients. We obtained standardized depression-rate ratios by dividing the observed depression rate in AS patients by the expected rate based on the corresponding age- and sex-specific rates of depression in the general population seeking care. A ratio >1 equals a higher rate of depression among AS patients.

Results

The AS cohort consisted of 1738 subjects (65% men) with a mean age of 54 years. The reference population consisted of 967,012 subjects. During the 13-year observation period 10% (n = 172) of the AS cohort had a doctor-diagnosed depression compared to 6% (n = 105) to be expected. The standardized estimate of depression-rate ratio was 1.81 (95% confidence interval 1.44 to 2.24) in women men and 1.49 (1.20 to 1.89) in men.

Conclusions

The rate of doctor-diagnosed depression is increased about 80% in female and 50% in male AS patients. Future challenges are to timely identify and treat the AS patients who suffer from depression.     

Cost-Effectiveness of a Community Pharmacist-Led Sleep Apnea Screening Program – A Markov Model

Background

Despite the high prevalence and major public health ramifications, obstructive sleep apnea syndrome (OSAS) remains underdiagnosed. In many developed countries, because community pharmacists (CP) are easily accessible, they have been developing additional clinical services that integrate the services of and collaborate with other healthcare providers (general practitioners (GPs), nurses, etc.). Alternative strategies for primary care screening programs for OSAS involving the CP are discussed.

Objective

To estimate the quality of life, costs, and cost-effectiveness of three screening strategies among patients who are at risk of having moderate to severe OSAS in primary care.

Design

Markov decision model.

Data Sources

Published data.

Target Population

Hypothetical cohort of 50-year-old male patients with symptoms highly evocative of OSAS.

Time Horizon

The 5 years after initial evaluation for OSAS.

Perspective

Societal.

Interventions

Screening strategy with CP (CP-GP collaboration), screening strategy without CP (GP alone) and no screening.

Outcomes measures

Quality of life, survival and costs for each screening strategy.

Results of base-case analysis

Under almost all modeled conditions, the involvement of CPs in OSAS screening was cost effective. The maximal incremental cost for “screening strategy with CP” was about 455€ per QALY gained.

Results of sensitivity analysis

Our results were robust but primarily sensitive to the treatment costs by continuous positive airway pressure, and the costs of untreated OSAS. The probabilistic sensitivity analysis showed that the “screening strategy with CP” was dominant in 80% of cases. It was more effective and less costly in 47% of cases, and within the cost-effective range (maximum incremental cost effectiveness ratio at €6186.67/QALY) in 33% of cases.

Conclusions

CP involvement in OSAS screening is a cost-effective strategy. This proposal is consistent with the trend in Europe and the United States to extend the practices and responsibilities of the pharmacist in primary care.     

Comparable Ascertainment of Newly-Diagnosed Atrial Fibrillation Using Active Cohort Follow-Up versus Surveillance of Centers for Medicare and Medicaid Services in the Atherosclerosis Risk in Communities Study

Objective

Increasingly, epidemiologic studies use administrative data to identify atrial fibrillation (AF). Capture of incident AF is not well documented. We examined incidence rates and concordance of AF diagnosis based on active cohort follow-up versus surveillance of Centers for Medicare and Medicaid Services data in the Atherosclerosis Risk in Communities study.

Methods

Atherosclerosis Risk in Communities cohort participants without prevalent AF enrolled in fee-for-service Medicare, with inpatient and outpatient coverage, for at least 12 continuous months between 1991 and 2009 were included. In active Atherosclerosis Risk in Communities study follow-up, annual telephone calls captured hospitalizations and deaths with incident AF diagnosis codes. For Centers for Medicare and Medicaid Services data, incident AF was defined by billed inpatient and outpatient diagnoses.

Results

Of 10,134 eligible cohort participants, 738 developed AF according to both Atherosclerosis Risk in Communities and Centers for Medicare and Medicaid Services data; an additional 93 and 288 incident cases were identified using only Atherosclerosis Risk in Communities and Centers for Medicare and Medicaid Services data, respectively. Incidence rates per 1,000 person-years were 10.8 (95% confidence interval: 10.1–11.6) and 13.6 (95% confidence interval: 12.8–14.4) in Atherosclerosis Risk in Communities and Centers for Medicare and Medicaid Services, respectively; agreement was 96%; kappa was 0.77 (95% confidence interval: 0.75–0.80). Earlier AF ascertainment by one system versus the other was not associated with any cardiovascular disease risk factors, after accounting for sociodemographic factors. Additional Centers for Medicare and Medicaid Services events did not alter observed associations between risk factors and AF.

Conclusion

Among fee-for-service enrollees, AF incidence rates were slightly lower for active cohort follow-up than for Centers for Medicare and Medicaid Services surveillance, because the latter included outpatient atrial fibrillation. Concordance was high and combining the two approaches could provide a more complete picture of newly-diagnosed AF.     

"There are too many, but never enough": qualitative case study investigating routine coding of clinical information in depression

Background

We sought to understand how clinical information relating to the management of depression is routinely coded in different clinical settings and the perspectives of and implications for different stakeholders with a view to understanding how these may be aligned.

Materials and Methods

Qualitative investigation exploring the views of a purposefully selected range of healthcare professionals, managers, and clinical coders spanning primary and secondary care.

Results

Our dataset comprised 28 semi-structured interviews, a focus group, documents relating to clinical coding standards and participant observation of clinical coding activities. We identified a range of approaches to coding clinical information including templates and order entry systems. The challenges inherent in clearly establishing a diagnosis, identifying appropriate clinical codes and possible implications of diagnoses for patients were particularly prominent in primary care. Although a range of managerial and research benefits were identified, there were no direct benefits from coded clinical data for patients or professionals. Secondary care staff emphasized the role of clinical coders in ensuring data quality, which was at odds with the policy drive to increase real-time clinical coding.

Conclusions

There was overall no evidence of clear-cut direct patient care benefits to inform immediate care decisions, even in primary care where data on patients with depression were more extensively coded. A number of important secondary uses were recognized by healthcare staff, but the coding of clinical data to serve these ends was often poorly aligned with clinical practice and patient-centered considerations. The current international drive to encourage clinical coding by healthcare professionals during the clinical encounter may need to be critically examined.     

Cost-Effectiveness of Collaborative Care for Depression in UK Primary Care: Economic Evaluation of a Randomised Controlled Trial (CADET)

Background

Collaborative care is an effective treatment for the management of depression but evidence on its cost-effectiveness in the UK is lacking.

Aims

To assess the cost-effectiveness of collaborative care in a UK primary care setting.

Methods

An economic evaluation alongside a multi-centre cluster randomised controlled trial comparing collaborative care with usual primary care for adults with depression (n = 581). Costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios (ICER) were calculated over a 12-month follow-up, from the perspective of the UK National Health Service and Personal Social Services (i.e. Third Party Payer). Sensitivity analyses are reported, and uncertainty is presented using the cost-effectiveness acceptability curve (CEAC) and the cost-effectiveness plane.

Results

The collaborative care intervention had a mean cost of £272.50 per participant. Health and social care service use, excluding collaborative care, indicated a similar profile of resource use between collaborative care and usual care participants. Collaborative care offered a mean incremental gain of 0.02 (95% CI: –0.02, 0.06) quality-adjusted life-years over 12 months, at a mean incremental cost of £270.72 (95% CI: –202.98, 886.04), and resulted in an estimated mean cost per QALY of £14,248. Where costs associated with informal care are considered in sensitivity analyses collaborative care is expected to be less costly and more effective, thereby dominating treatment as usual.

Conclusion

Collaborative care offers health gains at a relatively low cost, and is cost-effective compared with usual care against a decision-maker willingness to pay threshold of £20,000 per QALY gained. Results here support the commissioning of collaborative care in a UK primary care setting.     

The Incidence of First Venous Thromboembolism in and around Pregnancy Using Linked Primary and Secondary Care Data: A Population Based Cohort Study from England and Comparative Meta-Analysis

Background

Recent linkage between primary and secondary care data has provided valuable information for studying heath outcomes that may initially present in different health care settings. The aim of this study was therefore, twofold: to use linked primary and secondary care data to determine an optimum definition for estimating the incidence of first VTE in and around pregnancy; and secondly to conduct a systematic literature review of studies on perinatal VTE incidence with the purpose of comparing our estimates.

Methods

We used primary care data from the Clinical Practice Research Datalink (CPRD), which incorporates linkages to secondary care contained within Hospital Episode Statistics (HES) between 1997 and 2010 to estimate the incidence rate of VTE in the antepartum and postpartum period. We systematically searched the literature on the incidence of VTE during antepartum and postpartum periods and performed a meta-analysis to provide comparison.

Findings

Using combined CPRD and HES data and a restrictive VTE definition, the absolute rate during the antepartum period and first six weeks postpartum (early postpartum) were 99 (95%CI 85–116) and 468 (95%CI 391–561) per 100,000 person-years respectively. These were comparable to the pooled estimates from our meta-analysis (using studies after 2005) during the antepartum period (118/100,000 person-years) and early postpartum (424/100,000 person-years). When we used only secondary care data to identify VTE events, incidence was lower during the early postpartum period (308/100,000 person-years), whereas relying only on primary care data lead to lower incidence during the time around delivery, but higher rates during the postpartum period (558/100,000 person-years).

Conclusion

Using combined CPRD and HES data gives estimates of the risk of VTE in and around pregnancy that are comparable to the existing literature. It also provides more accurate estimation of the date of VTE diagnosis which will allow risk stratification during specific pregnancy and postpartum periods.     

Continuity in a VA Patient-Centered Medical Home Reduces Emergency Department Visits

Background

One major goal of the Patient-Centered Medical Home (PCMH) is to improve continuity of care between patients and providers and reduce the utilization of non-primary care services like the emergency department (ED).

Objective

To characterize continuity under the Veterans Health Administration’s PCMH model – the Patient Aligned Care Team (PACT), at one large Veterans Affair’s (VA’s) primary care clinic, determine the characteristics associated with high levels of continuity, and assess the association between continuity and ED visits.

Design

Retrospective, observational cohort study of patients at the West Haven VA (WHVA) Primary Care Clinic from March 2011 to February 2012.

Patients

The 13,495 patients with established care at the Clinic, having at least one visit, one year before March 2011.

Main Measures

Our exposure variable was continuity of care –a patient seeing their assigned primary care provider (PCP) at each clinic visit. The outcome of interest was having an ED visit.

Results

The patients encompassed 42,969 total clinic visits, and 3185 (24%) of them had 15,458 ED visits. In a multivariable logistic regression analysis, patients with continuity of care – at least one visit with their assigned PCP – had lower ED utilization compared to individuals without continuity (adjusted odds ratio [AOR] 0.54; 95% CI: 0.41, 0.71), controlling for frequency of primary care visits, comorbidities, insurance, distance from the ED, and having a trainee PCP assigned. Likewise, the adjusted rate of ED visits was 544/1000 person-year (PY) for patients with continuity vs. 784/1000 PY for patients without continuity (p = 0.001). Compared to patients with low continuity (<33% of visits), individuals with medium (33–50%) and high (>50%) continuity were less likely to utilize the ED.

Conclusions

Strong continuity of care is associated with decreased ED utilization in a PCMH model and improving continuity may help reduce the utilization of non-primary care services.     

Relationship between Longitudinal Continuity of Primary Care and Likelihood of Death: Analysis of National Insurance Data

Background

Continuity of care (COC) is a widely accepted core principle of primary care and has been associated with patient satisfaction, healthcare utilization and mortality in many, albeit small, studies.

Objective

To assess the relationship between longitudinal continuity with a primary care physician (PCP) and likelihood of death in the French general population.

Design

Observational study based on reimbursement claims from the French national health insurance (NHI) database for salaried workers (2007–2010).

Setting

Primary care.

Patients

We extracted data on the number and pattern of visits made to a PCP and excluded all patients who did not visit a PCP at least twice within 6 months. We recorded age, gender, comorbidities, social status, and deaths.

Main outcome measures

The primary endpoint was death by all causes. We measured longitudinal continuity of care (COC) with a PCP twice a year between 2007 and 2010, using the COC index developed by Bice and Boxerman. We introduced the COC index as time-dependent variables in a survival analysis after adjustment for age, gender and stratifying on comorbidities and social status.

Results

A total of 325 742 patients were included in the analysis. The average COC index ranged from 0.74 (SD: 0.35) to 0.76 (0.35) (where 1.0 is perfect continuity). Likelihood of death was lower in patients with higher continuity (hazard ratio for an increase in 0.1 of continuity, adjusted for age, sex, and stratified on comorbidities and social status: 0.96 [0.95–0.96]).

Conclusion

Higher longitudinal continuity was associated with a reduced likelihood of death.