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Patient Assessment of Chronic Illness Care (PACIC) and improved patient-centered outcomes for chronic conditions.

ABSTRACT: BACKGROUND: The Patient Assessment of Chronic Illness Care (PACIC) has potential for use as a patient-centered measure of the implementation of the Chronic Care Model (CCM), but there is little research on the relationship between the PACIC and important behavioral and quality measures for patients with chronic conditions. OBJECTIVE: To examine the relationship between PACIC scores and self-management behaviors, patient rating of their health care, and self-reported quality of life. DESIGN: Cross-sectional survey with a 61% response rate. PARTICIPANTS: Included in the survey were 4,108 adults with diabetes, chronic pain, heart failure, asthma, or coronary artery disease in the Kaiser Permanente Medical Care program across 7 regions nationally. MEASUREMENTS: The PACIC was the main independent variable. Dependent variables included use of self-management resources, self-management behaviors such as regular exercise, self-reported adherence to medications, patient rating of their health care, and quality of life. RESULTS: PACIC scores were significantly, positively associated with all measures (odds ratio [ORs] ranging from 1.20 to 2.36) with the exception of self-reported medication adherence. CONCLUSIONS: Use of the PACIC, a practical, patient-level assessment of CCM implementation, could be an important tool for health systems and other stakeholders looking to improve the quality of chronic disease care.

SUBMITTER: Schmittdiel J

PROVIDER: S-EPMC2173922 | biostudies-literature | 2008 Jan

REPOSITORIES: biostudies-literature

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Patient Assessment of Chronic Illness Care (PACIC) and improved patient-centered outcomes for chronic conditions.

Schmittdiel Julie J Mosen David M DM Glasgow Russell E RE Hibbard Judith J Remmers Carol C Bellows Jim J

Journal of general internal medicine 20071121 1

<h4>Background</h4>The Patient Assessment of Chronic Illness Care (PACIC) has potential for use as a patient-centered measure of the implementation of the Chronic Care Model (CCM), but there is little research on the relationship between the PACIC and important behavioral and quality measures for patients with chronic conditions.<h4>Objective</h4>To examine the relationship between PACIC scores and self-management behaviors, patient rating of their health care, and self-reported quality of life. ...[more]

PMID: 18030539

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Project description:BackgroundThe prevalence of chronic wounds is predicted to increase within the aging populations in industrialized countries. Patients experience significant distress due to pain, wound secretions, and the resulting immobilization. As the number of wounds continues to rise, their adequate care becomes increasingly costly in terms of health care resources worldwide. eHealth support systems are being increasingly integrated into patient care. However, to date, no systematic analysis of such apps for chronic wounds has been published.ObjectiveThe aims of this study were to systematically identify and subjectively assess publicly available German- or English-language mobile apps for patients with chronic wounds, with quality assessments performed by both patients and physicians.MethodsTwo reviewers independently conducted a systematic search and assessment of German- or English-language mobile apps for patients with chronic wounds that were available in the Google Play Store and Apple App Store from April 2022 to May 2022. In total, 3 apps met the inclusion and exclusion criteria and were reviewed independently by 10 physicians using the German Mobile App Rating Scale (MARS) and the System Usability Scale (SUS). The app with the highest mean MARS score was subsequently reviewed by 11 patients with chronic wounds using the German user version of the MARS (uMARS) and the SUS. Additionally, Affinity for Technology Interaction (ATI) scale scores were collected from both patients and physicians.ResultsThis study assessed mobile apps for patients with chronic wounds that were selected from a pool of 118 identified apps. Of the 73 apps available in both app stores, 10 were patient oriented. After excluding apps with advertisements or costs, 3 apps were evaluated by 10 physicians. Mean MARS scores ranged from 2.64 (SD 0.65) to 3.88 (SD 0.65) out of 5, and mean SUS scores ranged from 50.75 (SD 27) to 80.5 (SD 17.7) out of 100. WUND APP received the highest mean MARS score (mean 3.88, SD 0.65 out of 5) among physicians. Hence, it was subsequently assessed by 11 patients and achieved a similar rating (uMARS score: mean 3.89, SD 0.4 out of 5). Technical affinity, as measured with the ATI scale, was slightly lower in patients (score: mean 3.62, SD 1.35 out of 6) compared to physicians (score: mean 3.88, SD 1.03 out 6).ConclusionsThe quality ratings from physicians and patients were comparable and indicated mediocre app quality. Technical affinity, as assessed by using the ATI scale, was slightly lower for patients. Adequate apps for patients with chronic wounds remain limited, emphasizing the need for improved app development to meet patient needs. The ATI scale proved valuable for assessing technical affinity among different user groups.

Project description:BACKGROUND:Providing patient-centered care (PCC) during the last year of life (LYOL) can be challenging due to the complexity of the patients' medical, social and psychological needs, especially in case of chronic illnesses. Assessing PCC can be helpful in identifying areas for improvements. Since not all patients can be surveyed, a questionnaire for proxy informants was developed in order to retrospectively assess patient-centeredness in care during the whole LYOL. This study aimed to evaluate the feasibility and validity of an adapted version of the German Patient Assessment of Chronic Illness Care (PACIC) for surveying bereaved persons in order to assess PCC during the decedents' LYOL. METHODS:The German PACIC short form (11 items) was adapted to a nine-item version for surveying bereaved persons on the decedent's LYOL (PACIC-S9-Proxy). Items were rated on a five-point Likert scale. The PACIC adaptation and validation was part of a cross-sectional survey in the region of Cologne. Participants were recruited through self-selection and active recruitment by practice partners. Sociodemographic characteristics and missing data were analyzed using descriptive statistics. An exploratory factor analysis was conducted in order to assess the structure of the PACIC-S9-Proxy. Internal consistency was estimated using Cronbach's alpha. RESULTS:Of the 351 informants who participated in the survey, 230 (65.52%) considered their decedent to have suffered from chronic illness prior to death. 193 of these informants (83.91%) completed ?5 items of the questionnaire and were included in the analysis. The least answered item was item (74.09%) was item 4 (encouragement to group & classes for coping). The most frequently answered item (96.89%) was item 2 (satisfaction with care organization). Informants rated the item" Given a copy of their treatment plan" highest (mean 3.96), whereas "encouragement to get to a specific group or class to cope with the condition" (mean 1.74) was rated lowest. Cronbach's alpha was 0.84. A unidimensional structure of the questionnaire was found (Kaiser-Meyer-Olkin 0.86, Bartlett's test for sphericity p?<?0.001), with items' factor loadings ranging from 0.46 to 0.82. CONCLUSIONS:The nine-item questionnaire can be used as efficient tool for assessing PCC during the LYOL retrospectively and by proxies. TRIAL REGISTRATION:The study was registered in the German Clinical Trials Register ( DRKS00011925 ) on 13 June 2017.

Project description:BackgroundThe Patient Assessment of Chronic Illness Care (PACIC) is a US measure of chronic illness quality of care, based on the influential Chronic Care Model (CCM). It measures a number of aspects of care, including patient activation; delivery system design and decision support; goal setting and tailoring; problem-solving and contextual counselling; follow-up and coordination. Although there is developing evidence of the utility of the scale, there is little evidence about its performance in the United Kingdom (UK). We present preliminary data on the psychometric performance of the PACIC in a large sample of UK patients with long-term conditions.MethodWe collected PACIC, demographic, clinical and quality of care data from patients with long-term conditions across 38 general practices, as part of a wider longitudinal study. We assess rates of missing data, present descriptive and distributional data, assess internal consistency, and test validity through confirmatory factor analysis, and through associations between PACIC scores, patient characteristics and related measures.ResultsThere was evidence that rates of missing data were high on PACIC (9.6% - 15.9%), and higher than on other scales used in the same survey. Most PACIC sub-scales showed reasonable levels of internal consistency (alpha = 0.68 - 0.94), responses did not demonstrate high skewness levels, and floor effects were more frequent (up to 30.4% on the follow up and co-ordination subscale) than ceiling effects (generally <5%). PACIC demonstrated preliminary evidence of validity in terms of measures of long-term condition care. Confirmatory factor analysis suggested that the five factor PACIC structure proposed by the scale developers did not fit the data: reporting separate factor scores may not always be appropriate.ConclusionThe importance of improving care for long-term conditions means that the development and validation of measures is a priority. The PACIC scale has demonstrated potential utility in this regard, but further assessment is required to assess low levels of completion of the scale, and to explore the performance of the scale in predicting outcomes and assessing the effects of interventions.

Dataset Information

Patient Assessment of Chronic Illness Care (PACIC) and improved patient-centered outcomes for chronic conditions.

Publications

Patient Assessment of Chronic Illness Care (PACIC) and improved patient-centered outcomes for chronic conditions.

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