Biomedical subjects

Henry C Chueh

Publications and source records attributed to Henry C Chueh.

14 recordsLinked to original sources

PubMed2006

New models of population management for patients with diabetes--using informatics tools to support primary care.

Diabetes management continues to fall short of evidence-based goals of care. Population management represents a new approach to diabetes care for large numbers of patients with diabetes cared for within a single clinical system. This method is information intensive and generally requires an advanced informatics infrastructure. While Information Processing is a critical first step in population management, to have a significant impact on disease control population-based intervention must also employ potent Clinical Action tools that lower barriers to effective care. In this review we present two recent population management interventions within our health system that illustrate the principles of Information Processing and Clinical Action in diabetes care.

Cholesterol↗

PubMed2006

Cost of an informatics-based diabetes management program.

OBJECTIVES: The relatively high cost of information technology systems may be a barrier to hospitals thinking of adopting this technology. The experiences of early adopters may facilitate decision making for hospitals less able to risk their limited resources. This study identifies the costs to design, develop, implement, and operate an innovative informatics-based registry and disease management system (POPMAN) to manage type 2 diabetes in a primary care setting. METHODS: The various cost components of POPMAN were systematically identified and collected. RESULTS: POPMAN cost 450,000 dollars to develop and operate over 3.5 years (1999-2003). Approximately 250,000 dollars of these costs are one-time expenditures or sunk costs. Annual operating costs are expected to range from 90,000 dollars to 110,000 dollars translating to approximately 90 dollars per patient for a 1,200 patient registry. CONCLUSIONS: The cost of POPMAN is comparable to the costs of other quality-improving interventions for patients with diabetes. Modifications to POPMAN for adaptation to other chronic diseases or to interface with new electronic medical record systems will require additional investment but should not be as high as initial development costs. POPMAN provides a means of tracking progress against negotiated quality targets, allowing hospitals to negotiate pay for performance incentives with insurers that may exceed the annual operating cost of POPMAN. As a result, the quality of care of patients with diabetes through use of POPMAN could be improved at a minimal net cost to hospitals.

Costs and Cost Analysis↗

PubMed2006

Randomized controlled trial of an informatics-based intervention to increase statin prescription for secondary prevention of coronary disease.

OBJECTIVE: Suboptimal treatment of hyperlipidemia in patients with coronary artery disease (CAD) is well documented. We report the impact of a computer-assisted physician-directed intervention to improve secondary prevention of hyperlipidemia. DESIGN AND SETTING: Two hundred thirty-five patients under the care of 14 primary care physicians in an academically affiliated practice with an electronic health record were enrolled in this proof-of-concept physician-blinded randomized, controlled trial. Each patient with CAD or risk equivalent above National Cholesterol Education Program-recommended low-density lipoprotein (LDL) treatment goal for greater than 6 months was randomized, stratified by physician and baseline LDL. Physicians received a single e-mail per intervention patient. E-mails were visit independent, provided decision support, and facilitated "one-click" order writing. MEASUREMENTS: The primary outcomes were changes in hyperlipidemia prescriptions, time to prescription change, and changes in LDL levels. The time spent using the system was assessed among intervention patients. RESULTS: A greater proportion of intervention patients had prescription changes at 1 month (15.3% vs 2%, P=.001) and 1 year (24.6% vs 17.1%, P=.14). The median interval to first medication adjustment occurred earlier among intervention patients (0 vs 7.1 months, P=.005). Among patients with baseline LDLs >130 mg/dL, the first postintervention LDLs were substantially lower in the intervention group (119.0 vs 138.0 mg/dL, P=.04). Physician processing time was under 60 seconds per e-mail. CONCLUSION: A visit-independent disease management tool resulted in significant improvement in secondary prevention of hyperlipidemia at 1-month postintervention and showed a trend toward improvement at 1 year.

Adult↗

PubMed2006

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

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.

Adult↗

PubMed2005

Automated identification of a physician's primary patients.

OBJECTIVE: To develop and validate an automated method for determining the set of patients for whom a given primary care physician holds overall clinical responsibility. DESIGN: The study included all adult patients (16,185) seen at least once in an ambulatory setting during a three-year period by 18 primary care physicians in ten practices. The physicians indicated whether they considered themselves to be the physician primarily responsible for the overall clinical care of each visiting patient. Statistical models were constructed to predict the physicians' designations using predictor variables derived from electronically available appointment schedules and demographic information. MEASUREMENTS: Predictive accuracy was assessed primarily using the area under the receiver-operating characteristic curve (AUC), and secondarily using positive predictive value (PPV) and sensitivity. RESULTS: A minimal set of six variables was identified as predictive of the physicians' designations. The constructed model had a median AUC for individual physicians of 0.92 (interquartile interval: 0.90-0.96), a PPV of 0.94 (interquartile interval: 0.87-0.95), and a sensitivity of 0.95 (interquartile interval: 0.87-0.97). CONCLUSION: A statistical model using a minimal set of commonly available electronic data can accurately predict the set of patients for whom a physician holds primary clinical responsibility. Further research examining the generalization of the model to other settings would be valuable.

Adult↗

PubMed2005

Internet use among primary care patients with type 2 diabetes: the generation and education gap.

BACKGROUND: The Internet represents a promising tool to improve diabetes care. OBJECTIVE: To assess differences in demographics, self-care behaviors, and diabetes-related risk factor control by frequency of Internet use. DESIGN AND PARTICIPANTS: We surveyed 909 patients with type 2 diabetes attending primary care clinics. MEASUREMENTS: Frequency of Internet use, socioeconomic status, and responses to the Problem Areas in Diabetes (PAID), Summary of Diabetes Self-care Activities (SDSCA), and Health Utilities Index (HUI) scales. Survey responses were linked to last measured hemoglobin A1c, cholesterol, and blood pressure results. Comorbidities and current medications were obtained from the medical record. RESULTS: Internet "never-users" (n=588, 66%) were significantly older (70.0+/-11.2 vs 59.0+/-11.3 years; P<.001) and less educated (26% vs 71% with>high school; P<.001) than Internet users (n=308, 34%). There were few significant differences in PAID or SDSCA scores or in diabetes metabolic control despite longer diabetes duration (10.3+/-8.2 vs 8.3+/-6.7 years; P<.001) and greater prevalence of coronary disease (40% vs 24%; P<.001) in nonusers. Less than 10% of current nonusers would use the Internet for secure health-related communication. CONCLUSIONS: Older and less educated diabetes patients are less likely to use the Internet. Despite greater comorbidity, nonusers engaged in primary care had equal or better risk factor control compared to users.

Age Factors↗

PubMed2005

SPIN query tools for de-identified research on a humongous database.

The Shared Pathology Informatics Network (SPIN), a research initiative of the National Cancer Institute, will allow for the retrieval of more than 4 million pathology reports and specimens. In this paper, we describe the special query tool as developed for the Indianapolis/Regenstrief SPIN node, integrated into the ever-expanding Indiana Network for Patient care (INPC). This query tool allows for the retrieval of de-identified data sets using complex logic, auto-coded final diagnoses, and intrinsically supports multiple types of statistical analyses. The new SPIN/INPC database represents a new generation of the Regenstrief Medical Record system - a centralized, but federated system of repositories.

Confidentiality↗

PubMed2005

Designing an electronic medication reconciliation system.

Unintended medication discrepancies at hospital admission and discharge potentially harm patients. Explicit medication reconciliation (MR) can prevent unintended discrepancies among care settings and is mandated by JCAHO for 2005. Enterprise-wide, we are linking pre-admission and discharge medication lists in our outpatient electronic health records (EHR) with our inpatient order entry applications (OE) - currently not interoperable - to support MR and inform the development of comprehensive MR among hospitalized patients.

Hospitalization↗

PubMed2004

A controlled trial of population management: diabetes mellitus: putting evidence into practice (DM-PEP).

OBJECTIVE: Population-level strategies to organize and deliver care may improve diabetes management. We conducted a multiclinic controlled trial of population management in patients with type 2 diabetes. RESEARCH DESIGN AND METHODS: We created diabetic patient registries (n = 3,079) for four primary care clinics within a single academic health center. In the intervention clinic (n = 898), a nurse practitioner used novel clinical software (PopMan) to identify patients on a weekly basis with outlying values for visit and testing intervals and last measured levels of HbA1c, LDL cholesterol, and blood pressure. For these patients, the nurse practitioner e-mailed a concise patient-specific summary of evidence-based management suggestions directly to primary care providers (PCPs). Population changes in risk factor testing, medication prescription, and risk factor levels from baseline (1 January 2000 to 31 August 2001) to follow-up (1 December 2001 to 31 July 2003) were compared with the three usual-care control clinics (n = 2,181). RESULTS: Patients had a mean age of 65 years, were mostly white (81%), and the majority were insured by Medicare/Medicaid (62%). From baseline to follow-up, the increase in proportion of patients tested for HbA1c (P = 0.004) and LDL cholesterol (P < 0.001) was greater in the intervention than control sites. Improvements in diabetes-related medication prescription and levels of HbA1c, LDL cholesterol, and blood pressure in the intervention clinic were balanced by similar improvements in the control sites. CONCLUSIONS: Population-level clinical registries combined with summarized recommendations to PCPs had a modest effect on management. The intervention was limited by good overall quality of care at baseline and temporal improvements in all control clinics. It is unknown whether this intervention would have had greater impact in clinical settings with lower overall quality. Further research into more effective methods of translating population registry information into action is required.

Aged↗

PubMed2003

Automated coded ambulatory problem lists: evaluation of a vocabulary and a data entry tool.

BACKGROUND: Problem lists are fundamental to electronic medical records (EMRs). However, obtaining an appropriate problem list dictionary is difficult, and getting users to code their problems at the time of data entry can be challenging. OBJECTIVE: To develop a problem list dictionary and search algorithm for an EMR system and evaluate its use. METHODS: We developed a problem list dictionary and lookup tool and implemented it in several EMR systems. A sample of 10,000 problem entries was reviewed from each system to assess overall coding rates. We also performed a manual review of a subset of entries to determine the appropriateness of coded entries, and to assess the reasons other entries were left uncoded. RESULTS: The overall coding rate varied significantly between different EMR implementations (63-79%). Coded entries were virtually always appropriate (99%). The most frequent reasons for uncoded entries were due to user interface failures (44-45%), insufficient dictionary coverage (20-32%), and non-problem entries (10-12%). CONCLUSION: The problem list dictionary and search algorithm has achieved a good coding rate, but the rate is dependent on the specific user interface implementation. Problem coding is essential for providing clinical decision support, and improving usability should result in better coding rates.

Algorithms↗

PubMed2003

Impact of population management with direct physician feedback on care of patients with type 2 diabetes.

OBJECTIVE: Population-level strategies may improve primary care for diabetes. We designed a controlled study to assess the impact of population management versus usual care on metabolic risk factor testing and management in patients with type 2 diabetes. We also identified potential patient-related barriers to effective diabetes management. RESEARCH DESIGN AND METHODS: We used novel clinical software to rank 910 patients in a diabetes registry at a single primary care clinic and thereby identify the 149 patients with the highest HbA(1c) and cholesterol levels. After review of the medical records of these 149 patients, evidence-based guideline recommendations regarding metabolic testing and management were sent via e-mail to each intervention patient's primary care provider (PCP). Over a 3-month follow-up period, we assessed changes in the evidence-based management of intervention patients compared with a matched cohort of control patients receiving usual care at a second primary care clinic affiliated with the same academic medical center. RESULTS: In the intervention cohort, PCPs followed testing recommendations more often (78%) than therapeutic change recommendations (36%, P = 0.001). Compared with the usual care control cohort, population management resulted in a greater overall proportion of evidence-based guideline practices being followed (59 vs. 45%, P = 0.02). Most intervention patients (62%) had potential barriers to effective care, including depression (35%), substance abuse (26%), and prior nonadherence to care plans (18%). CONCLUSIONS: Population management with clinical recommendations sent to PCPs had a modest but statistically significant impact on the evidence-based management of diabetes compared with usual care. Depression and substance abuse are prevalent patient-level adherence barriers in patients with poor metabolic control.

Adult↗

PubMed2003

A visual interface designed for novice users to find research patient cohorts in a large biomedical database.

One of the more difficult tasks of informatics is allowing for the navigation of complex databases. At Partners Healthcare Inc. we have developed an analytical database to allow for searching clinical data to obtain cohorts of patients for research studies. The characteristics of the patients within the cohorts must often comply with complex inclusion and exclusion criteria. The users of the database are research clinicians, often with no prior database experience. To assist these clinicians in finding their patient cohorts, we constructed a Querytool that they use directly to find their desired populations. In order to understand if the Querytool could indeed be used successfully by novice users, we analyzed the first 10 queries of 219 users. This analysis was able show that novice users are able to achieve excellent success using the Querytool

Computer Graphics↗

PubMed2002

A security architecture for query tools used to access large biomedical databases.

Disseminating information from large biomedical databases can be crucial for research. Often this data will be patient-specific, and therefore require that the privacy of the patient be protected. In response to this requirement, HIPAA released regulations for the dissemination of patient data. In many cases, the regulations are so restrictive as to render data useless for many purposes. We propose in this paper a model for obfuscation of data when served to a client application, that will make it extremely unlikely that an individual will be identified. At Partners Healthcare Inc, with over 1.4 million patients and 400 research clinician users, we implemented this model. Based on the results, we believe that a web-client could be made generally available using the proposed data obfuscation scheme that could allow general usage of large biomedical databases of patient information without risk to patient privacy.

Computer Security↗

PubMedDate not supplied

Design and implementation of an application and associated services to support interdisciplinary medication reconciliation efforts at an integrated healthcare delivery network.

Confusion about patients' medication regimens during the hospital admission and discharge process accounts for many preventable and serious medication errors. Many organizations have begun to redesign their clinical processes to address this patient safety concern. Partners HealthCare, an integrated delivery network in Boston, Massachusetts, has answered this interdisciplinary challenge by leveraging its multiple outpatient electronic medical records (EMR) and inpatient computerized provider order entry (CPOE) systems to facilitate the process of medication reconciliation. This manuscript describes the design of a novel application and the associated services that aggregate medication data from EMR and CPOE systems so that clinicians can efficiently generate an accurate pre-admission medication list. Information collected with the use of this application subsequently supports the writing of admission and discharge orders by physicians, performance of admission assessment by nurses, and reconciliation of inpatient orders by pharmacists. Results from early pilot testing suggest that this new medication reconciliation process is well accepted by clinicians and has significant potential to prevent medication errors during transitions of care.

Clinical Pharmacy Information Systems↗