Dataset Information

Is this "my" patient? Development and validation of a predictive model to link patients to primary care providers.

ABSTRACT:

Background

Evaluating the quality of care provided by individual primary care physicians (PCPs) may be limited by failing to know which patients the PCP feels personally responsible for.

Objective

To develop and validate a model for linking patients to specific PCPs.

Design

Retrospective convenience sample.

Participants

Eighteen PCPs from 10 practice sites within an academic adult primary care network.

Measurements

Each PCP reviewed the records for all outpatients seen over the preceding 3 years (16,435 patients reviewed) and designated each patient as "My Patient" or "Not My Patient." Using this reference standard, we developed an algorithm with logistic regression modeling to predict "My Patient" using development and validation subsets drawn from the same patient set. Quality of care was then assessed by "My Patient" or "Not My Patient" designation by analyzing cancer screening test rates.

Results

Overall, PCPs designated 11,226 patients (68.3%, range per provider 15% to 93%) to be "My Patient." The model accurately categorized patients in development and validation subsets (combined sensitivity 80.4%, specificity 93.7%, and positive predictive value 96.5%). To achieve positive predictive values of > 90% for individual PCPs, the model excluded 19.6% of PCP "My Patients" (range 5.5% to 75.3%). Cancer screening rates were higher among model-predicted "My Patients."

Conclusions

Nearly one-third of patients seen were considered "Not My Patient" by the PCP, although this proportion varied widely. We developed and validated a simple model to link specific patients and PCPs. Such efforts may help effectively target interventions to improve primary care quality.

SUBMITTER: Atlas SJ

PROVIDER: S-EPMC1831616 | biostudies-literature | 2006 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Is this "my" patient? Development and validation of a predictive model to link patients to primary care providers.

Atlas Steven J SJ Chang Yuchiao Y Lasko Thomas A TA Chueh Henry C HC Grant Richard W RW Barry Michael J MJ

Journal of general internal medicine 20060901 9

<h4>Background</h4>Evaluating the quality of care provided by individual primary care physicians (PCPs) may be limited by failing to know which patients the PCP feels personally responsible for.<h4>Objective</h4>To develop and validate a model for linking patients to specific PCPs.<h4>Design</h4>Retrospective convenience sample.<h4>Participants</h4>Eighteen PCPs from 10 practice sites within an academic adult primary care network.<h4>Measurements</h4>Each PCP reviewed the records for all outpati ...[more]

PMID: 16918744

Similar Datasets

Project description:IntroductionIntegrated service delivery is considered to be an essential condition for improving the management and health outcomes of people with chronic kidney disease (CKD). However, research on the assessment of integrated care by patients and care providers is hindered by the absence of brief, reliable, and valid measurement tools.ObjectiveThe aim of this study was to develop survey instruments for healthcare professionals and patients based on the Rainbow Model of Integrated Care (RMIC), and to evaluate their psychometric properties.DesignThe development process was based on the US Food and Drug Administration guidelines. This included item generation from systematic reviews of existing tools and expert opinion on clarity and content validity, involving renal care providers and chronic kidney patients. A cross-sectional, multi-centre design was used to test for internal consistency and construct validity.SettingOutpatient clinics in a large renal network.ParticipantsA sample of 30.788 CKD patients, and 8.914 renal care providers.Methods and analysisBoth survey instruments were developed using previous qualitative work and published literature. A multidisciplinary expert panel assessed the face and content validity of both instruments and following a pilot study, the psychometric properties of both instruments were explored. Exploratory factor analysis with principal axis factoring and with promax rotation was used to assess the underlying dimensions of both instruments; Cronbach's alpha was used to determine the internal constancy reliability.Results17.512 patients (response rate: 56.9%) and 8.849 care providers (response rate: 69.5%) responded to the questionnaires. Factor analysis of the patient questionnaire yielded three internally consistent (Cronbach's alpha > 0.7) factors: person-centeredness, clinical coordination, and professional coordination. Factor analysis of the provider questionnaire produced eight internally consistent (Cronbach's alpha > 0.7) factors: person-centeredness, community centeredness, clinical coordination, professional coordination, organisational coordination, system coordination, technical and cultural competence. As hypothesised, care coordination patient and providers scores significantly correlated with questions about quality of care, treatment involvement, reported health, clinics' organisational readiness, and external care coordination capacity.ConclusionThis study provides evidence for the reliability and validity of the RMIC patient and provider questionnaires as generic tools to assess the experience with or perception of integrated renal care delivery. The instruments are recommended in future applications testing test-retest reliability, convergent and predictive validity, and responsiveness.

Project description:BackgroundExternal supervision of primary health care facilities to monitor and improve services is common in low-income countries. Currently there are no tools to measure the quality of support in external supervision in these countries.AimTo develop a provider-reported instrument to assess the support delivered through external supervision in Rwanda and other countries.Methods"External supervision: Provider Evaluation of Supervisor Support" (ExPRESS) was developed in 18 steps, primarily in Rwanda. Content validity was optimised using systematic search for related instruments, interviews, translations, and relevance assessments by international supervision experts as well as local experts in Nigeria, Kenya, Uganda and Rwanda. Construct validity and reliability were examined in two separate field tests, the first using exploratory factor analysis and a test-retest design, the second for confirmatory factor analysis.ResultsWe included 16 items in section A ('The most recent experience with an external supervisor'), and 13 items in section B ('The overall experience with external supervisors'). Item-content validity index was acceptable. In field test I, test-retest had acceptable kappa values and exploratory factor analysis suggested relevant factors in sections A and B used for model hypotheses. In field test II, models were tested by confirmatory factor analysis fitting a 4-factor model for section A, and a 3-factor model for section B.ConclusionsExPRESS is a promising tool for evaluation of the quality of support of primary health care providers in external supervision of primary health care facilities in resource-constrained settings. ExPRESS may be used as specific feedback to external supervisors to help identify and address gaps in the supervision they provide. Further studies should determine optimal interpretation of scores and the number of respondents needed per supervisor to obtain precise results, as well as test the functionality of section B.

Dataset Information

Is this "my" patient? Development and validation of a predictive model to link patients to primary care providers.

Background

Objective

Design

Participants

Measurements

Results

Conclusions

Publications

Is this "my" patient? Development and validation of a predictive model to link patients to primary care providers.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets