Application of the Ambulatory Care Groups in the Primary Care of a European National Health Care System

Orueta, Juan F.; López-de-Munain, Josefina; Báez, Koldo; Aiarzagüena, José María; Aranguren, Jon I.; Pedrero, Eduardo Fonseca

doi:10.1097/00005650-199903000-00004

Cited by 57 publications

(41 citation statements)

References 11 publications

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“…The model identifi ed 4 ADGs that signifi cantly increased the risk of a patient being a persistently high user of primary care visits. These ADGs were chronic medical-unstable (11); see and reassure (30); psychosocial: time limited, minor (23); and signs/symptoms, minor (26). ADG 33 for pregnancy was negatively associated with the persistence of clinic visits.…”

Section: Resultsmentioning

confidence: 99%

“…22,23 For this study, we used the Johns Hopkins adjusted clinical groups (ACGs) system to categorize patients into diagnosis groups. [24][25][26] ACGs were developed by a team including medical experts in primary care to be both clinically meaningful and predictive of utilization and resource costs. ACGs are currently used by managed care plans and others for risk-adjusting fi nancial arrangements with providers and for physician profi ling.…”

Section: Clinical Risk Factorsmentioning

confidence: 99%

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Predicting Persistently High Primary Care Use

Naessens

Baird

Houten

et al. 2005

The Annals of Family Medicine

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PURPOSE We wanted to identify risk factors for persistently high use of primary care. METHODSWe analyzed outpatient offi ce visits to practitioners in family medicine, general internal medicine, general pediatrics, and obstetrics for 1997-1999 among patients in a small Midwestern city covered by a fee-for-service insurance plan with no co-payments for physician visits and no requirement for referral to specialty care. Logistic regression was used to predict which patients with 10 or more primary care visits in 1997 would repeat high use in 1998 based on demographic and diagnostic categories (adjusted clinical groups [ACGs]). A confi rmatory data set (high primary care use in 1998 persistent into 1999) was used to evaluate the model. RESULTSTwo percent of the 54,074 patients had 10 or more primary care visits in 1997, and of these, almost 19% had 10 or more visits in the next year. Among adults, 4 ambulatory diagnosis groups (ADGs) were simultaneously positive predictors of repeated high primary care visits: unstable chronic medical conditions, see and reassure conditions, minor time-limited psychosocial conditions, and minor signs and symptoms. Meanwhile, pregnancy was negatively associated. The area under the receiver operating characteristic (ROC) curve was 0.794 for adults in the developmental data set and 0.752 in the confi rmatory data set, indicating a moderately accurate assessment. A satisfactory model was not developed for pediatric patients. CONCLUSIONSMany persistently high primary care users appear to be overserviced but underserved, with underlying problems not addressed by a medical approach. Some may benefi t from psychosocial support, whereas others may be good candidates for disease management interventions. INTRODUCTIONT he well-known concentration of health care utilization and costs among relatively few individuals 1 allows for targeted interventions and modeling of patient risks for more equitable health care reimbursement.2-4 Factors associated with high utilization include patient demographics, previous use of health care, patient diagnosis, and severity of illness. 5,6 If certain patient characteristics are predictive of high persistent use, it may be possible to offer more cost-effective alternatives to frequent primary care visits, including disease management, case management, group visits, and patient education. [7][8][9][10][11] Better management of persistent primary care use may better address the patients' underlying problems, reduce unnecessary demand, and relieve some of the pressure on the capacity of primary care providers to deliver care to all patients. 12,13 Most efforts to identify and adjust for patients with high expected health care use have been directed at predicting total health care expenditures 3,6,14,15 METHODS Study Site and Patient PopulationThe study population included approximately 58,000 people continuously insured with a fee-for-service plan in a small urban area in the midwestern United States. Patients who did not authorize research use of their...

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Section: Resultsmentioning

confidence: 99%

Section: Clinical Risk Factorsmentioning

confidence: 99%

Predicting Persistently High Primary Care Use

Naessens

Baird

Houten

et al. 2005

The Annals of Family Medicine

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“…Different but complementary perspectives on the prevalent morbidity in these cases can be verified through the Aggregated Diagnosis Groups (ADGs) and Extended Diagnosis Clusters (EDCs) [31]. Other studies have shown that recognizing the complexity of cases, in terms of both outpatient [32][33][34][35] and hospital care [36][37][38], can lead to optimized and patient-oriented management strategies and solutions. In the state of São Paulo, stratification adjusted for risk factors together with underlying morbidity can help to identify improvement opportunities, policy strategies for allocation of differentiated resources, or cases where there is a need to structure more complex services so that procedures in cardiac surgeries can be done.…”

Section: Discussionmentioning

confidence: 99%

Heart surgery programs innovation using surgical risk stratification at the São Paulo State Public Healthcare System: SP-SCORE-SUS STUDY

Mejía¹,

Lisboa²,

Dallan³

et al. 2013

Revista Brasileira De Cirurgia Cardiovascular

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“…Both have been developed as a result of academic endeavours [19][20][21][22] and both have been subject to independent testing, including on populations outside the US. [23][24][25] Examples of categories in the systems are shown in Table 1.…”

Section: Methodsmentioning

confidence: 99%