Surgeon involvement in clinical coding to improve data accuracy and remuneration in a shoulder and elbow unit

2021 ◽  
pp. 175857322199153
Author(s):  
Steven Kyriacou ◽  
David Butt ◽  
Will Rudge ◽  
Deborah Higgs ◽  
Mark Falworth ◽  
...  
Keyword(s):  
Data Quality ◽  
Data Accuracy ◽  
Operative Intervention ◽  
Clinical Activity ◽  
Surgical Team ◽  
Clinical Coding ◽  
Accurate Representation ◽  
Operative Note ◽  
Additional Income

Background Clinical coders are dependent on clear data regarding diagnoses and procedures to generate an accurate representation of clinical activity and ensure appropriate remuneration is received. The accuracy of this process may potentially be improved by collaboration with the surgical team. Methods Between November 2017 and November 2019, 19 meetings took place between the Senior Clinical Fellow of our tertiary Shoulder & Elbow Unit and the coding validation lead of our Trust. At each meeting, the Clinical Fellow assessed the operative note of cases in which uncertainty existed as to the most suitable clinical codes to apply and selected the codes which most accurately represented the operative intervention performed. Results Over a 24-month period, clinical coding was reviewed in 153 cases (range 3–14 per meeting, mean 8). Following review, the clinical coding was amended in 102 (67%) of these cases. A total of £115,160 additional income was generated as a result of this process (range £1677–£15,796 per meeting, mean £6061). Only 6 out of 28 (21%) cases initially coded as arthroscopic sub-acromial decompressions were correctly coded as such. Discussion Surgeon input into clinical coding greatly improves data quality and increases remuneration received for operative interventions performed.

scholarly journals Posterior Cloacal Variant with Clitorolabial Transposition and a Rectoperineal Fistula

2021 ◽  
Vol 09 (01) ◽  
pp. e46-e49
Author(s):  
Niveshni Maistry ◽  
Giulia Brisighelli ◽  
Chris Westgarth-Taylor
Keyword(s):  
Operative Intervention ◽  
Posterior Sagittal Anorectoplasty ◽  
Surgical Team ◽  
Ureteric Reimplantation ◽  
Long Term Follow Up

AbstractWe present a case and discuss the management of a posterior cloacal variant not as yet described in the literature. A 5-week-old infant presented to our institution with a posterior cloacal variant and transposition of the clitoris and labia. After initial radiological investigations, staged operative intervention was performed over a 1-year period. This included an initial laparotomy (with drainage of hydrocolpos and formation of a colostomy), a left ureteric reimplantation and a posterior sagittal anorectoplasty due to a rectoperineal fistula. The child is under continued long-term follow-up by our specialist pediatric surgical team.

scholarly journals Utilizing asynchronous email interviews for health research: overview of benefits and drawbacks

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Michelle Amri ◽  
Christina Angelakis ◽  
Dilani Logan
Keyword(s):  
Public Health ◽  
Data Collection ◽  
Data Quality ◽  
Health Research ◽  
Geographic Location ◽  
Public Health Research ◽  
Data Accuracy ◽  
Global Public Health ◽  
Snowball Sampling ◽  
Face To Face

Abstract Objective Through collating observations from various studies and complementing these findings with one author’s study, a detailed overview of the benefits and drawbacks of asynchronous email interviewing is provided. Through this overview, it is evident there is great potential for asynchronous email interviews in the broad field of health, particularly for studies drawing on expertise from participants in academia or professional settings, those across varied geographical settings (i.e. potential for global public health research), and/or in circumstances when face-to-face interactions are not possible (e.g. COVID-19). Results Benefits of asynchronous email interviewing and additional considerations for researchers are discussed around: (i) access transcending geographic location and during restricted face-to-face communications; (ii) feasibility and cost; (iii) sampling and inclusion of diverse participants; (iv) facilitating snowball sampling and increased transparency; (v) data collection with working professionals; (vi) anonymity; (vii) verification of participants; (viii) data quality and enhanced data accuracy; and (ix) overcoming language barriers. Similarly, potential drawbacks of asynchronous email interviews are also discussed with suggested remedies, which centre around: (i) time; (ii) participant verification and confidentiality; (iii) technology and sampling concerns; (iv) data quality and availability; and (v) need for enhanced clarity and precision.

Sensor Field Resource Management for Sensor Network Data Mining

2010 ◽  
pp. 280-304
Author(s):  
David J. Yates ◽  
Jennifer Xu
Keyword(s):  
Data Mining ◽  
Response Time ◽  
Data Quality ◽  
Real Time ◽  
Sensor Network ◽  
Resource Consumption ◽  
Data Accuracy ◽  
Network Data ◽  
Sensor Field ◽  
User Queries

This research is motivated by data mining for wireless sensor network applications. The authors consider applications where data is acquired in real-time, and thus data mining is performed on live streams of data rather than on stored databases. One challenge in supporting such applications is that sensor node power is a precious resource that needs to be managed as such. To conserve energy in the sensor field, the authors propose and evaluate several approaches to acquiring, and then caching data in a sensor field data server. The authors show that for true real-time applications, for which response time dictates data quality, policies that emulate cache hits by computing and returning approximate values for sensor data yield a simultaneous quality improvement and cost saving. This “win-win” is because when data acquisition response time is sufficiently important, the decrease in resource consumption and increase in data quality achieved by using approximate values outweighs the negative impact on data accuracy due to the approximation. In contrast, when data accuracy drives quality, a linear trade-off between resource consumption and data accuracy emerges. The authors then identify caching and lookup policies for which the sensor field query rate is bounded when servicing an arbitrary workload of user queries. This upper bound is achieved by having multiple user queries share the cost of a sensor field query. Finally, the authors discuss the challenges facing sensor network data mining applications in terms of data collection, warehousing, and mining techniques.

scholarly journals Real-Time Intraoperative Consultation Reporting in the Electronic Health Record

2020 ◽  
Vol 154 (3) ◽  
pp. 387-393
Author(s):  
Molly E Klein ◽  
Joseph W Rudolf ◽  
Maryna Tarbunova ◽  
Tanya Jorden ◽  
Susanna R Clark ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Real Time ◽  
Laboratory Medicine ◽  
Clinical Impact ◽  
Final Report ◽  
Health Record ◽  
Laboratory Information System ◽  
Surgical Team ◽  
Operative Note ◽  
Electronic Health

Abstract Objectives We sought to make pathologists’ intraoperative consultation (IOC) results immediately available to the surgical team, other clinicians, and laboratory medicine colleagues to improve communication and decrease postanalytic errors. Methods We created an IOC report in our stand-alone laboratory information system that could be signed out prior to, and independent of, the final report, and transfer immediately to the electronic health record (EHR) as a preliminary diagnosis. We evaluated two metrics: preliminary (IOC) result review in the EHR by clinicians and postanalytic errors. Results We assessed 2,886 IOC orders from the first 22 months after implementation. Clinicians reviewed 1,956 (68%) of the IOC results while in preliminary status, including 1,399 (48%) within the first 24 hours. We evaluated 150 cases preimplementation and 300 cases postimplementation for discrepancies between the pathologist’s IOC result and the IOC result recorded by the surgeon in the operative note. Discrepancies dropped from 12 of 150 preimplementation to 6 of 150 and 7 of 150 in postimplementation years 1 and 2. One of the 25 discrepancies had a major clinical impact. Conclusions Real-time reporting of IOC results to the EHR reliably transmits results immediately to clinical teams. This strategy reduces but does not eliminate postanalytic interpretive errors by clinical teams.

scholarly journals Data quality of the routine health management information system at the primary healthcare facility and district levels in Tanzania

2020 ◽  
Author(s):  
SUSAN F. RUMISHA ◽  
EMANUEL P. LYIMO ◽  
IRENE R. MREMI ◽  
PATRICK K. TUNGU ◽  
VICTOR S. MWINGIRA ◽  
...  
Keyword(s):  
Data Quality ◽  
Primary Healthcare ◽  
Reporting System ◽  
Health Management ◽  
Healthcare Facility ◽  
Data Accuracy ◽  
District Level ◽  
Management Information ◽  
District Office

Abstract Background: Effective planning for disease prevention and control requires accurate, adequately-analysed, interpreted and communicated data. In recent years, efforts have been put in strengthening health management information systems (HMIS) in Sub-Saharan Africa to improve data accessibility to decision-makers. This study assessed the quality of routine HMIS data at primary healthcare facility (HF) and district levels in Tanzania. Methods: This cross-sectional study involved reviews of documents, systems and databases, and collection of primary data from facility registers, tally sheets and monthly summary reports. Thirty-four indicators from Outpatient, Inpatient, Antenatal care, Family Planning, Post-natal care, Labour and Delivery, and Provider-Initiated Testing and Counselling service areas were assessed. Indicator records were tracked and compared across the process of data collection, compilation and submission to the district office. Monthly report forms submitted by facilities to the district were also reviewed. The availability and utilization of HMIS tools were assessed, while completeness and data accuracy levels were quantified for each phase of the reporting system. Results: A total of 115 HFs (including hospitals, health centres, dispensaries) in 11 districts were involved. Registers (availability rate=91.1%; interquartile range (IQR):66.7%-100%) and report forms (86.9%; IQR:62.2%-100%) were the most utilized tools. There was a limited use of tally-sheets (77.8%; IQR:35.6%-100%). Tools availability at the dispensary was 91.1%, health centre 82.2% and hospital 77.8%. The availability rate at the district level was 65% (IQR:48%-75%). Wrongly filled or empty cells in registers and poor adherence to the coding procedures were observed. Reports were highly over-represented in comparison to registers’ records, with large differences observed at the HF phase of the reporting system. The OPD and IPD areas indicated the highest levels of mismatch between data source and district office. Indicators with large number of clients, multiple variables, disease categorization, or those linked with dispensing medicine performed poorly. Conclusion: There are high variations in the tool utilisation and data accuracy at facility and district levels. The routine HMIS is weak and data at district level inaccurately reflects what is available at the source. These results highlight the need to design tailored and inter-service strategies for improving data quality.

Best practice in the management of clinical coding services: Insights from a project in the Republic of Ireland, Part 1

2017 ◽  
Vol 46 (2) ◽  
pp. 69-77 ◽  
Author(s):  
Beth A Reid ◽  
Lee Ridoutt ◽  
Paul O’Connor ◽  
Deirdre Murphy
Keyword(s):  
Quality Control ◽  
Data Quality ◽  
Medical Record ◽  
Best Practice ◽  
Control Measures ◽  
Data Quality Control ◽  
Clinical Coding ◽  
Republic Of Ireland ◽  
The Republic

Introduction: This article presents some of the results of a year-long project in the Republic of Ireland to review the quality of the hospital inpatient enquiry data for its use in activity-based funding (ABF). This is the first of two papers regarding best practice in the management of clinical coding services. Methods: Four methods were used to address this aspect of the project, namely a literature review, a workshop, an assessment of the coding services in 12 Irish hospitals by structured interviews of the clinical coding managers, and a medical record audit of the clinical codes in 10 hospitals. Results: The results included here are those relating to the quality of the medical records, coding work allocation and supervision processes, data quality control measures, communication with clinicians, and the visibility of clinical coders, their managers, and the coding service. Conclusion: The project found instances of best practice in the study hospitals but also found several areas needing improvement. These included improving the structure and content of the medical record, clinician engagement with the clinical coding teams and the ABF process, and the use of data quality control measures.

scholarly journals Institutionalized Data Quality Assessments: A Critical Pathway to Improving the Accuracy of Integrated Disease Surveillance Data in Sierra Leone

2020 ◽  
Author(s):  
Charles Kuria Njuguna ◽  
Mohamed Vandi ◽  
Malimbo Mugagga ◽  
Joseph Kanu ◽  
Evans Liyosi ◽  
...  
Keyword(s):  
Data Quality ◽  
Health Information ◽  
Sierra Leone ◽  
Health Facility ◽  
Disease Surveillance ◽  
Virus Disease ◽  
Health Facilities ◽  
Data Accuracy ◽  
Critical Pathway ◽  
Quality Assessments

Abstract Background Public health agencies require valid, timely and complete health information for early detection of outbreaks. Towards the end of the Ebola Virus Disease (EVD) outbreak in 2015, the Ministry of Health and Sanitation (MoHS), Sierra Leone revitalized the Integrated Disease Surveillance and Response System (IDSR). Data quality assessments were conducted to monitor accuracy of IDSR data. Methods Starting 2016, data quality assessments (DQA) were conducted in randomly selected health facilities. Structured electronic checklist was used to interview district health management teams (DHMT) and health facility staff. We used malaria data, to assess data accuracy as malaria was endemic in Sierra Leone. Verification factors (VF) calculated as the ratio of verified malaria cases in health facility registers to the number of malaria cases in the national health information database, were used to assess data accuracy. Allowing a 5% margin of error, VF <95% were considered over reporting while VF >105 was underreporting. Differences in the proportion of accurate reports at baseline and subsequent assessments were compared using Z-test for two proportions. Results Between 2016 -2018, four DQA were conducted in 444 health facilities where 1,729 IDSR reports were reviewed. Registers and IDSR technical guidelines were available in health facilities and health care workers were conversant with reporting requirements. Overall data accuracy improved from over- reporting of 4.7% (VF 95.3%) in 2016 to under-reporting of 0.2% (VF 100.2%) in 2018. Compared to 2016, proportion of accurate IDSR reports increased by 14.8 % (95% CI 7.2%, 22.3%) in May 2017 and 19.5% (95% CI 12.5% -26.5%) by 2018. Over reporting was more common in private clinics and not- for profit facilities while under-reporting was more common in lower level government health facilities. Leading reasons for data discrepancies included counting errors in 358 (80.6%) health facilities and missing source documents in 47 (10.6%) health facilities. Conclusion This is the first attempt to institutionalize routine monitoring of IDSR data quality in Sierra Leone. Regular data quality assessments may have contributed to improved data accuracy over time. Data compilation errors accounted for most discrepancies and should be minimized to improve accuracy of IDSR data.

scholarly journals Institutionalized Data Quality Assessments: A Critical Pathway to Improving the Accuracy of Integrated Disease Surveillance Data in Sierra Leone

2019 ◽  
Author(s):  
Charles Kuria Njuguna ◽  
Mohamed Vandi ◽  
Malimbo Mugagga ◽  
Joseph Kanu ◽  
Evans Liyosi ◽  
...  
Keyword(s):  
Data Quality ◽  
Health Information ◽  
Sierra Leone ◽  
Health Facility ◽  
Disease Surveillance ◽  
Virus Disease ◽  
Health Facilities ◽  
Data Accuracy ◽  
Critical Pathway ◽  
Quality Assessments

Abstract Background Public health agencies require valid, timely and complete health information for early detection of outbreaks. Towards the end of the Ebola Virus Disease (EVD) outbreak in 2015, the Ministry of Health and Sanitation (MoHS), Sierra Leone revitalized the Integrated Disease Surveillance and Response System (IDSR). Data quality assessments were conducted to monitor the accuracy of data generated through the IDSR system.Methods Starting 2016, regular data quality assessments (DQA)were conducted in randomly selected health facilities. A structured electronic checklist was used to interview district health management team (DHMT) members and health facility staff. We used malaria data to assess data accuracy as malaria was endemic in Sierra Leone. Verification factors (VF) calculated as the ratio of verified malaria cases in the health facility register to the number of malaria cases recorded in the national health information database, were used to assess data accuracy. Allowing a 5% margin of error, VF <95% were considered over reporting while a VF >105 was underreporting. Differences in the proportion of accurate reports in the first and fourth assessments were compared using Z-test for two proportions.Results Between 2016 -2018, four DQA were conducted in 444 health facilities where 1,729 IDSR reports were reviewed. Registers and IDSR technical guidelines were widely available in health facilities and health care workers were conversant with reporting requirements. Overall data accuracy improved from VF of 95.3% in 2016 to 100.2% in 2018. Compared to the baseline in 2016, the proportion of accurate IDSR reports in 2018 increased by 19.5% (CI 12.5% -26.5%). Over reporting was more common in private clinics and not for profit facilities while under-reporting was more common in lower level government health facilities. Leading reasons for data discrepancies included counting errors in 358 (80.6%) health facilities, and missing source documents in 47 (10.6%) health facilities.Conclusion This is the first attempt to institutionalize routine monitoring of IDSR data quality in Sierra Leone. Regular data quality assessments may have contributed to improved data accuracy over time. Data compilation errors accounted for most discrepancies and should be minimized to improve accuracy of IDSR data.

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