DRG coding practice: a nationwide hospital survey in Thailand

<p>Abstract</p> <p>Background</p> <p>Diagnosis Related Group (DRG) payment is preferred by healthcare reform in various countries but its implementation in resource-limited countries has not been fully explored.</p> <p>Objectives</p> <p>This study was aimed (1) to compare the characteristics of hospitals in Thailand that were audited with those that were not and (2) to develop a simplified scale to measure hospital coding practice.</p> <p>Methods</p> <p>A questionnaire survey was conducted of 920 hospitals in the Summary and Coding Audit Database (SCAD hospitals, all of which were audited in 2008 because of suspicious reports of possible DRG miscoding); the questionnaire also included 390 non-SCAD hospitals. The questionnaire asked about general demographics of the hospitals, hospital coding structure and process, and also included a set of 63 opinion-oriented items on the current hospital coding practice. Descriptive statistics and exploratory factor analysis (EFA) were used for data analysis.</p> <p>Results</p> <p>SCAD and Non-SCAD hospitals were different in many aspects, especially the number of medical statisticians, experience of medical statisticians and physicians, as well as number of certified coders. Factor analysis revealed a simplified 3-factor, 20-item model to assess hospital coding practice and classify hospital intention.</p> <p>Conclusion</p> <p>Hospital providers should not be assumed capable of producing high quality DRG codes, especially in resource-limited settings.</p

Toward the Measure of Credibility of Hospital Administrative Datasets in the Context of DRG Classification

Poor quality of coded clinical data in hospital administrative databases may negatively affect decision making, clinical and health care services research and billing. In this paper, we assessed the level of credibility of a nationwide Portuguese inpatient database concerning the codification of pneumonia, with a special emphasis on identifying suspicious cases of upcoding affecting proper APR-DRG (All-Patient Refined Diagnosis-Related Groups) classification and hospital funding. Using data on pneumonia-related hospitalizations from 2015, we compared six hospitals with similar complexity regarding the frequency of all pneumonia-related diagnosis codes in order to identify codes that were significantly overreported in a given facility relatively to its peers. To verify whether the discrepant codes could be related to upcoding, we built Support Vector Machine (SVM) models to simulate the APR-DRG system and assess its response to each discrepant code. Findings demonstrate that hospitals significantly differed in coding six pneumonia conditions, with five of them playing a major role in increasing APR-DRG complexity, being thus suspicious cases of upcoding. However, those comprised a minority of cases and the overall credibility concerning upcoding of pneumonia was above 99% for all evaluated hospitals. Our findings can not only be relevant for planning future audit processes by signalizing errors impacting APR-DRG classification, but also for discussing credibility of administrative data, keeping in mind their impact on hospital financing. Hence, the main contribution of this paper is a reproducible method that can be employed to monitor the credibility and to promote data quality management in administrative databases

An effectiveness analysis of healthcare systems using a systems theoretic approach

<p>Abstract</p> <p>Background</p> <p>The use of accreditation and quality measurement and reporting to improve healthcare quality and patient safety has been widespread across many countries. A review of the literature reveals no association between the accreditation system and the quality measurement and reporting systems, even when hospital compliance with these systems is satisfactory. Improvement of health care outcomes needs to be based on an appreciation of the whole system that contributes to those outcomes. The research literature currently lacks an appropriate analysis and is fragmented among activities. This paper aims to propose an integrated research model of these two systems and to demonstrate the usefulness of the resulting model for strategic research planning.</p> <p>Methods/design</p> <p>To achieve these aims, a systematic integration of the healthcare accreditation and quality measurement/reporting systems is structured hierarchically. A holistic systems relationship model of the administration segment is developed to act as an investigation framework. A literature-based empirical study is used to validate the proposed relationships derived from the model. Australian experiences are used as evidence for the system effectiveness analysis and design base for an adaptive-control study proposal to show the usefulness of the system model for guiding strategic research.</p> <p>Results</p> <p>Three basic relationships were revealed and validated from the research literature. The systemic weaknesses of the accreditation system and quality measurement/reporting system from a system flow perspective were examined. The approach provides a system thinking structure to assist the design of quality improvement strategies. The proposed model discovers a fourth implicit relationship, a feedback between quality performance reporting components and choice of accreditation components that is likely to play an important role in health care outcomes. An example involving accreditation surveyors is developed that provides a systematic search for improving the impact of accreditation on quality of care and hence on the accreditation/performance correlation.</p> <p>Conclusion</p> <p>There is clear value in developing a theoretical systems approach to achieving quality in health care. The introduction of the systematic surveyor-based search for improvements creates an adaptive-control system to optimize health care quality. It is hoped that these outcomes will stimulate further research in the development of strategic planning using systems theoretic approach for the improvement of quality in health care.</p

Model for allocation of medical specialists in a hospital network

Nantana Suppapitnarm,1,2 Krit Pongpirul1,3,4 1Department of Preventive and Social Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand; 2Medical Affairs Office, Bangkok Dusit Medical Services Public Company Limited, Bangkok, Thailand; 3Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; 4Thailand Research Center for Health Services System (TRC-HS), Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand Introduction: As human diseases are becoming increasingly complex, the need for medical specialist consultation is more pronounced, and innovative ways to allocate medical specialists in hospital networks are essential. This study aimed to construct allocation models using a multi-objective programming approach in a large private hospital network in Thailand. Methods: Our study included 13 medical specialist types in four main disease groups of the Bangkok Dusit Medical Services network. Mixed-integer linear programming models were developed using inputs from a modified Delphi survey of executives, the Physician Engagement Survey, and the Physician Registry (PR) databases and featuring three objectives: 1) minimizing travel expense, 2) optimizing physician engagement, and 3) maximizing the chance of direct patient encounters with respective medical specialists who were formally qualified for the clinical complexity of the patients, as measured by the case mix index (CMI). Results: The constructed models included the core components but varied by a combination of whether part-time medical specialists are included or not (noPT) and whether CMI is included (CMI) or not (noCMI). Because the noPT + CMI model had the highest capability to solve for specialist allocation, it was further improved for some specialist types in terms of flexibility for sensitivity analysis of the variables. Moreover, to assess the feasibility and practicality of the models, a web-based system incorporating the final model was developed to support the central executives&rsquo; decision to allocate medical specialists to the network, especially for finding the most optimal and timely solution for widespread shortages. Conclusion: The linear programming models that accommodate critical components for allocating medical specialists in the hospital network were feasible and practical for the central executives&rsquo; timely decision making. The models could be further tested for their application in hospitals in the public sector or other private hospital networks. Keywords: medical specialist, allocation, linear programming, human resource plannin

Five-year clinical outcomes of Crohn&rsquo;s disease: a report of 287 multiethnic cases from an International Hospital in Thailand

Vibhakorn Permpoon,1 Krit Pongpirul,2&ndash;4 Sinn Anuras11Digestive Disease Center, Bumrungrad International Hospital, Bangkok, Thailand; 2Department of Preventive and Social Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand; 3Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; 4Bumrungrad Research Center, Bumrungrad International Hospital, Bangkok, ThailandBackground: Crohn&rsquo;s disease (CD) has been relatively rare in Asian region whereas its clinical outcomes have been dominated by evidence from Caucasians in developed countries. This study reported clinical characteristics and outcomes of the multiethnic patients who visited our institution.Materials and methods: Medical records of all patients who visited our institution during 2005&ndash;2010 were reviewed. Colonoscopy and sigmoidoscopy were performed in compliance with the ASGE guidelines.Results: A total of 287 CD patients were followed up for 5.65 years on average: 41.80% Middle Eastern (ME), 29.62% Caucasian, 28.57% Asian. ME and Caucasian had higher CD prevalence than Asian (286.71, 278.66, and 43.10 per 100,000 population, respectively). Significant variation in male proportion was observed (p=0.001): 39.02% Asian, 65.83% ME, 68.24% Caucasian. The mean age was 39.46 years (ME 32.88, Asian 43.35, Caucasian 45.00; p&lt;0.001). ME had alonger duration of symptoms (26.55 months) than Caucasian (11.98 months) and Asian (12.35 months) (p=0.0008). The proportions of perianal lesions were statistically different across ethnic origins (p=0.014): 9.76% Asian, 24.17% ME and 12.94% Caucasian. Caucasian was severely active, compared with ME (10.83%) and Asian (6.10%). Disease progression existed in 88 of 254 patients who initially had non-severe pathology: 19.63% ME, 40% Caucasian, 50.65% Asian (p&lt;0.0001). Clinical improvement was observed in 82% of the patients. Seventy-five patients required either surgery or hospitalization with a significant ethnic variation: 37.65% Caucasian, 28.33% ME, 10.98% Asian (p&lt;0.0001).Conclusions: Crohn&rsquo;s disease prevalence, gender, age, duration of symptoms, perianal lesion, pathological severity and disease progression varied across ethnic origins.Keywords: Crohn&rsquo;s Disease, ethnic groups, anatomical pathological conditions, medical tourism, retrospective studie

Effect of pupillary dilation on Haigis formula-calculated intraocular lens power measurement by using optical biometry

Bharkbhum Khambhiphant,1 Suganlaya Sasiwilasagorn,2 Nattida Chatbunchachai,3 Krit Pongpirul2,4 1Department of Ophthalmology, King Chulalongkorn Memorial Hospital, Thai Red Cross Society, 2Department of Ophthalmology, Faculty of Medicine, Chulalongkorn University, Bangkok, 3Department of Ophthalmology, Samut Prakan Hospital, Samut Prakan, Thailand; 4Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA Purpose: The purpose of this study was to evaluate the effect of pupillary dilation on the Haigis formula-calculated intraocular lens (IOL) power and ocular biometry measurements by using IOLMaster&reg;. Methods: A prospective study was performed for biometry measurements of 373 eyes of 192 healthy subjects using the IOLMaster at the outpatient department of King Chulalongkorn Memorial Hospital from February 2013 to July 2013. The axial length (AL), anterior chamber depth (ACD), keratometry (K), and IOL power were measured before and after 1% tropicamide eye drop instillation. The Haigis formula was used in the IOL power calculation with the predicted target to emmetropia. Each parameter was compared by a paired t-test prior to and after pupillary dilation. Bland&ndash;Altman plots were also used to determine the agreement between each parameter. Results: The mean age of the subjects was 53.74&plusmn;14.41&nbsp;years (range 18&ndash;93&nbsp;years). No differences in AL (P=0.03), steepest K (P=0.42), and flattest K (P=0.41) were obtained from the IOLMaster after pupillary dilation. However, ACD and IOL power were significantly different postdilation (P&lt;0.01 and P&lt;0.01, respectively). In ACD and IOL power measurements, the concordance rates were 93.03% and 97.05% within 95% limits of agreement (-0.48 to 0.26&nbsp;mm and -1.09 to 0.88 D, respectively) in the Bland&ndash;Altman plots. Conclusion: Biometry measurements in the cycloplegic stage should be considered in the IOL formulas that use parameters other than AL and K. Keywords: Haigis formula, intraocular lens, IOLMaster, optical biometry, pupillary dilatio

A qualitative study of DRG coding practice in hospitals under the Thai Universal Coverage Scheme

<p>Abstract</p> <p>Background</p> <p>In the Thai Universal Coverage health insurance scheme, hospital providers are paid for their inpatient care using Diagnosis Related Group-based retrospective payment, for which quality of the diagnosis and procedure codes is crucial. However, there has been limited understandings on which health care professions are involved and how the diagnosis and procedure coding is actually done within hospital settings. The objective of this study is to detail hospital coding structure and process, and to describe the roles of key hospital staff, and other related internal dynamics in Thai hospitals that affect quality of data submitted for inpatient care reimbursement.</p> <p>Methods</p> <p>Research involved qualitative semi-structured interview with 43 participants at 10 hospitals chosen to represent a range of hospital sizes (small/medium/large), location (urban/rural), and type (public/private).</p> <p>Results</p> <p>Hospital Coding Practice has structural and process components. While the structural component includes human resources, hospital committee, and information technology infrastructure, the process component comprises all activities from patient discharge to submission of the diagnosis and procedure codes. At least eight health care professional disciplines are involved in the coding process which comprises seven major steps, each of which involves different hospital staff: 1) Discharge Summarization, 2) Completeness Checking, 3) Diagnosis and Procedure Coding, 4) Code Checking, 5) Relative Weight Challenging, 6) Coding Report, and 7) Internal Audit. The hospital coding practice can be affected by at least five main factors: 1) Internal Dynamics, 2) Management Context, 3) Financial Dependency, 4) Resource and Capacity, and 5) External Factors.</p> <p>Conclusions</p> <p>Hospital coding practice comprises both structural and process components, involves many health care professional disciplines, and is greatly varied across hospitals as a result of five main factors.</p