Electronic Patient Records in Interprofessional Decision Making: Standardized Categories and Local Use

Encouraging patients to play a more active role in their health care is crucial for healthcare planning and for the design of services. This chapter shifts the scholarly focus from practitioners' decision making to that of laypersons' trying to make sense of the lab results available on their EPRs. The authors developed a methodology to capture the relationship between information formats (graph, numeric, or verbal), laypersons' assessment of the conditions' gravity, and their preferred course of action. Focusing on the effect of “not knowing” on laypersons' preferred courses of action, our findings show that formats that left respondents less able to understand the results—namely, the numeric and verbal formats—produced a lower sense of urgency, and correspondingly, less inclination to actively seek professional help. The chapter takes a step toward deriving practical recommendations as to how personal clinical information should be communicated, to improve laypersons' interpretation of the information's significance.

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Data-Driven Decision Making for New Drugs

Organizational Applications of Business Intelligence Management ◽

10.4018/978-1-4666-0279-3.ch011 ◽

2012 ◽

pp. 144-162

Author(s):

George P. Sillup ◽

Ronald Klimberg ◽

David P. McSweeney

Keyword(s):

Decision Making ◽

Healthcare Delivery ◽

New Drugs ◽

Pharmaceutical Marketing ◽

Patient Records ◽

Electronic Patient Records ◽

Real World Data ◽

Collaborative Process ◽

Pharmacy Claims ◽

Student Teams

Two courses, advanced decision-making and pharmaceutical marketing, were combined in a collaborative process to mimic how the pharmaceutical industry determines the potential of new drugs. Integrated student teams worked together to complete semester-long projects and taught each other their respective knowledge areas—marketing and statistics. Real-world data for medical and pharmacy claims payments were “cleaned” and mined by students to analyze usage and cost patterns for anti-hypertensive and anti-hypercholesterolemia drugs currently on the market. Analyses included merging the medical and pharmaceutical data records to derive individual electronic patient records, which were the basis of financial projections for the new drugs. Importantly, the single patient record is congruent with the needs of the stakeholders currently working to reform U.S. healthcare delivery.

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Electronic Patient Records in Medical Practice: A Multidisciplinary Endeavor

Methods of Information in Medicine ◽

10.1055/s-0038-1634416 ◽

1999 ◽

Vol 38 (04/05) ◽

pp. 287-288 ◽

Cited By ~ 1

Author(s):

J. van der Lei ◽

P. W. Moorman ◽

M. A. Musen

Keyword(s):

Medical Practice ◽

Patient Records ◽

Electronic Patient Records

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Clinical Judgment Revisited

Methods of Information in Medicine ◽

10.1055/s-0038-1634415 ◽

1999 ◽

Vol 38 (04/05) ◽

pp. 279-286 ◽

Cited By ~ 5

Author(s):

L. L. Weed

Keyword(s):

Decision Making ◽

Medical Practice ◽

Clinical Judgment ◽

Medical Information ◽

Patient Records ◽

Practice Of Medicine ◽

The Way

AbstractIt is widely recognised that accessing and processing medical information in libraries and patient records is a burden beyond the capacities of the physician’s unaided mind in the conditions of medical practice. Physicians are quite capable of tremendous intellectual feats but cannot possibly do it all. The way ahead requires the development of a framework in which the brilliant pieces of understanding are routinely assembled into a working unit of social machinery that is coherent and as error free as possible – a challenge in which we ourselves are among the working parts to be organized and brought under control.Such a framework of intellectual rigor and discipline in the practice of medicine can only be achieved if knowledge is embedded in tools; the system requiring the routine use of those tools in all decision making by both providers and patients.

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Postmarketing Surveillance Based on Electronic Patient Records: The IPCI Project

Methods of Information in Medicine ◽

10.1055/s-0038-1634402 ◽

1999 ◽

Vol 38 (04/05) ◽

pp. 339-344 ◽

Cited By ~ 88

Author(s):

J. van der Lei ◽

B. M. Th. Mosseveld ◽

M. A. M. van Wijk ◽

P. D. van der Linden ◽

M. C. J. M. Sturkenboom ◽

...

Keyword(s):

General Practitioner ◽

General Practitioners ◽

Validation Studies ◽

Resource Planning ◽

Routine Practice ◽

Patient Records ◽

Postmarketing Surveillance ◽

Electronic Patient Records ◽

Use Of Data ◽

Data Requirements

AbstractResearchers claim that data in electronic patient records can be used for a variety of purposes including individual patient care, management, and resource planning for scientific research. Our objective in the project Integrated Primary Care Information (IPCI) was to assess whether the electronic patient records of Dutch general practitioners contain sufficient data to perform studies in the area of postmarketing surveillance studies. We determined the data requirements for postmarketing surveil-lance studies, implemented additional software in the electronic patient records of the general practitioner, developed an organization to monitor the use of data, and performed validation studies to test the quality of the data. Analysis of the data requirements showed that additional software had to be installed to collect data that is not recorded in routine practice. To avoid having to obtain informed consent from each enrolled patient, we developed IPCI as a semianonymous system: both patients and participating general practitioners are anonymous for the researchers. Under specific circumstances, the researcher can contact indirectly (through a trusted third party) the physician that made the data available. Only the treating general practitioner is able to decode the identity of his patients. A Board of Supervisors predominantly consisting of participating general practitioners monitors the use of data. Validation studies show the data can be used for postmarketing surveillance. With additional software to collect data not normally recorded in routine practice, data from electronic patient record of general practitioners can be used for postmarketing surveillance.

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Electronic patient record and its effects on social aspects of interprofessional collaboration and clinical workflows in hospitals (eCoCo): a mixed methods study protocol

BMC Health Services Research ◽

10.1186/s12913-021-06377-5 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Marina Beckmann ◽

Kerstin Dittmer ◽

Julia Jaschke ◽

Ute Karbach ◽

Juliane Köberlein-Neu ◽

...

Keyword(s):

Mixed Methods ◽

Health Services ◽

Healthcare Professionals ◽

Social Research ◽

Interprofessional Collaboration ◽

Participant Observation ◽

Patient Records ◽

Electronic Patient Records ◽

Daily Work ◽

Network Analyses

Abstract Background The need for and usage of electronic patient records within hospitals has steadily increased over the last decade for economic reasons as well as the proceeding digitalization. While there are numerous benefits from this system, the potential risks of using electronic patient records for hospitals, patients and healthcare professionals must also be discussed. There is a lack in research, particularly regarding effects on healthcare professionals and their daily work in health services. The study eCoCo aims to gain insight into changes in interprofessional collaboration and clinical workflows resulting from introducing electronic patient records. Methods eCoCo is a multi-center case study integrating mixed methods from qualitative and quantitative social research. The case studies include three hospitals that undergo the process of introducing electronic patient records. Data are collected before and after the introduction of electronic patient records using participant observation, interviews, focus groups, time measurement, patient and employee questionnaires and a questionnaire to measure the level of digitalization. Furthermore, documents (patient records) as well as structural and administrative data are gathered. To analyze the interprofessional collaboration qualitative network analyses, reconstructive-hermeneutic analyses and document analyses are conducted. The workflow analyses, patient and employee assessment analyses and classification within the clinical adoption meta-model are conducted to provide insights into clinical workflows. Discussion This study will be the first to investigate the effects of introducing electronic patient records on interprofessional collaboration and clinical workflows from the perspective of healthcare professionals. Thereby, it will consider patients’ safety, legal and ethical concerns and quality of care. The results will help to understand the organization and thereby improve the performance of health services working with electronic patient records. Trial registration The study was registered at the German clinical trials register (DRKS00023343, Pre-Results) on November 17, 2020.

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Using electronic patient records to assess the effect of a complex antenatal intervention in a cluster randomised controlled trial—data management experience from the DESiGN Trial team

Trials ◽

10.1186/s13063-021-05141-8 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Sophie Relph ◽

◽

Maria Elstad ◽

Bolaji Coker ◽

Matias C. Vieira ◽

...

Keyword(s):

Clinical Trials ◽

Data Quality ◽

Data Management ◽

Randomised Control Trial ◽

Data Dictionary ◽

Patient Records ◽

Electronic Patient Records ◽

Cluster Randomised ◽

Quality Checks ◽

Data Harmonisation

Abstract Background The use of electronic patient records for assessing outcomes in clinical trials is a methodological strategy intended to drive faster and more cost-efficient acquisition of results. The aim of this manuscript was to outline the data collection and management considerations of a maternity and perinatal clinical trial using data from electronic patient records, exemplifying the DESiGN Trial as a case study. Methods The DESiGN Trial is a cluster randomised control trial assessing the effect of a complex intervention versus standard care for identifying small for gestational age foetuses. Data on maternal/perinatal characteristics and outcomes including infants admitted to neonatal care, parameters from foetal ultrasound and details of hospital activity for health-economic evaluation were collected at two time points from four types of electronic patient records held in 22 different electronic record systems at the 13 research clusters. Data were pseudonymised on site using a bespoke Microsoft Excel macro and securely transferred to the central data store. Data quality checks were undertaken. Rules for data harmonisation of the raw data were developed and a data dictionary produced, along with rules and assumptions for data linkage of the datasets. The dictionary included descriptions of the rationale and assumptions for data harmonisation and quality checks. Results Data were collected on 182,052 babies from 178,350 pregnancies in 165,397 unique women. Data availability and completeness varied across research sites; each of eight variables which were key to calculation of the primary outcome were completely missing in median 3 (range 1–4) clusters at the time of the first data download. This improved by the second data download following clarification of instructions to the research sites (each of the eight key variables were completely missing in median 1 (range 0–1) cluster at the second time point). Common data management challenges were harmonising a single variable from multiple sources and categorising free-text data, solutions were developed for this trial. Conclusions Conduct of clinical trials which use electronic patient records for the assessment of outcomes can be time and cost-effective but still requires appropriate time and resources to maximise data quality. A difficulty for pregnancy and perinatal research in the UK is the wide variety of different systems used to collect patient data across maternity units. In this manuscript, we describe how we managed this and provide a detailed data dictionary covering the harmonisation of variable names and values that will be helpful for other researchers working with these data. Trial registration Primary registry and trial identifying number: ISRCTN 67698474. Registered on 02/11/16.

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