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Enregistrement W2979035489 · doi:10.1097/corr.0000000000000552

Value-based Healthcare: Applying Time-driven Activity-based Costing in Orthopaedics

2018· article· en· W2979035489 sur OpenAlexaff
Aakash Keswani, Nicole Sheikholeslami, Kevin J. Bozic

Notice bibliographique

RevueClinical Orthopaedics and Related Research · 2018
Typearticle
Langueen
DomaineEconomics, Econometrics and Finance
ThématiqueHealth Systems, Economic Evaluations, Quality of Life
Établissements canadiensCARE Canada
Organismes subventionnairesnon disponible
Mots-clésActivity-based costingHealth careMedicineCost driverIndirect costsOperations managementProcess costingCost accountingResource-based relative value scaleCost estimateLiberian dollarBusinessAccountingEconomicsNursing

Résumé

récupéré en direct d'OpenAlex

Introduction Healthcare delivery and payment in orthopaedics is shifting towards value, defined as patient health outcomes achieved per healthcare dollar spent [7]. Although we are improving our ability to measure and deliver care that focuses on improving outcomes that matter to patients, our ability to measure and understand the costs associated with that care remains challenging. Traditional cost accounting methods employ a “top-down” approach, applying cost-to-charge ratios or relative value units to estimate and allocate indirect and support costs. Although efficient, these approaches are largely arbitrary and do little to deconstruct the complex processes of healthcare delivery and elucidate major drivers of cost, rendering them unusable for measuring value. Time-driven activity-based costing (TDABC), developed by Kaplan and Anderson [3], addresses many of the shortcomings of traditional cost accounting methods. Taking a “bottom-up” approach, TDABC more-accurately estimates cost by allocating indirect/support costs to activities performed by capacity-supplying resources such as clinical/nonclinical staff and equipment. Cost estimates for TDABC are based on two parameters: (1) Per-minute cost for each resource involved in the process of care and (2) average time of each resource required. For personnel, the former is calculated as a function of salary and benefits divided by the practical capacity (considered full-time less sick-time, vacation, presenteeism). Utilization times are determined via direct observation or by interviewing personnel [3]. Time-driven activity-based costing can be used to estimate expected per-patient costs for the management of specific musculoskeletal conditions such as hip or knee osteoarthritis, neck pain, or back pain. To date, TDABC has been applied at three levels: (1) The procedure level (epidural analgesia for thoracic surgery patients [6], carpal tunnel release [4]), (2) the index admission level (head and neck cancer [8], ankle fracture [5]), and (3) the 90-day episode level (total joint replacement [1]) to improve processes, understand profitability, and inform pricing strategy. Applying TDABC to Orthopaedics Applying TDABC is a collaborative effort that requires both clinical and nonclinical expertise. Before implementing TDABC, it is important first to define the scope (process, procedure, or pathway) to which TDABC will be applied; following that, one can develop a process map, which includes summative lists of all steps involved in care delivery (including both direct patient-care and supporting activities) based on input from personnel involved in both types of activities (Fig. 1).Fig. 1: Hip/knee osteoarthritis care pathway (related visits/patient touchpoints) by disease severity and treatment approach (surgical versus nonsurgical).Let’s use outpatient knee injection as an example (Fig. 2). Time-driven activity-based costing can be implemented by healthcare providers in four steps [6]. Develop process maps (chronological steps in care delivery) for the injection, taking into consideration the clinical and nonclinical team members involved. Calculate per-minute costs (capacity cost rates) for personnel/equipment in administration of the knee injection, and estimate the time required to perform the treatment during the visit. Multiply the capacity cost rates for each resource against the time utilization to arrive at a total cost of the resource for the process. Estimate additional overhead costs like space (exam, procedure, or operating room), healthcare information technology, and general supplies that can be allocated to the knee injection based on total costs for these services from the organization’s accounting system. For example, if total facilities costs represent 100 exam rooms operating 50 weeks per year, TDABC would calculate the cost of one exam room for 20 minutes. To understand the cost of the full cycle of care, add together the total costs for each utilized resource, the attributable overhead costs, and any direct costs such as the purchase price of appropriate dose of injectable drugs. Fig. 2: An illustrative example of TDABC of a knee injection procedure is shown. The left side describes basic components of any TDABC estimate. Steps A-E on the right side lay out the sequential steps for carrying out TDABC for a knee injection procedure.Applying TDABC in this manner to an outpatient knee injection procedure allows for more accurate estimation of costs and identifies opportunities to reduce costs through process improvements. Improving Operational Efficiency Mapping of direct patient care and supporting activities can identify important opportunities for improving operational efficiency. For example, in our practice, the per-patient costs of initial and followup visits has decreased substantially by having the associate provider—a specialty-trained physician assistant/nurse practitioner—as the patient’s first point of contact and leader in designing his/her care plan. This approach of reallocating personnel to function at the highest level of their licensure has been applied across treatment pathways to all shared resources including behavioral health, nutrition counseling, and social work. Beyond reducing per-minute costs of each visit, activity-mapping helps identify redundant steps that can be eliminated as well as those steps (data gathering, scheduling, huddles for developing preliminary plans for each patient) that can be moved out of the clinic setting and simply done over the phone, online, or pushed upstream (before the initial visit) to minimize each patient’s in-clinic cycle time. Improving the latter increases the number of patients that can be seen and cared for in high-cost spaces such as exam or procedure rooms. Any proposed process change must be assessed in context of the entire practice to avoid the potential impact of increasing costs or creating inefficiencies in care for other conditions as capacity-supplying resources (personnel, equipment, procedure rooms) are shared across conditions. Lastly, ongoing monitoring of costs and efficiency can be incorporated into performance-based incentives as has been done previously for total joint replacement [2]. Identifying Opportunities to Improve Value By adjusting for demographic characteristics, clinical comorbidity burden, and musculoskeletal disease prevalence, TDABC modeling can be used to estimate the expected costs and resources (staffing, equipment) required to manage a target patient population. Comparing TDABC cost estimates to a payer/employer’s baseline costs (derived from claims data) can help providers identify the conditions, procedures, and patients where value can be most improved via a value-centric delivery approach. Providers can then allocate resources, staffing, and marketing towards those patients/conditions where the provider is best positioned to succeed. Informing Value-based Contracting Adjusted TDABC cost estimates, along with a built-in buffer for error or outliers, are critical for setting a price floor in value-based contracting. For patients/conditions where expected time-based costs of value-based healthcare delivery exceed the status quo, providers are better-equipped to explain the exact reasons for higher costs and justify the upfront investment with expected reduction in total episode costs of care (either from reduced use of costly interventions like surgery or incremental reductions in ongoing condition-related spending). Conclusion Time-driven activity-based costing has many important advantages to provider organizations looking to deliver higher-value care. By examining complex services via process mapping and capacity cost rates, health care systems gain a better understanding of the major cost drivers associated with the services they deliver, unnecessary or redundant processes, and how best to allocate resources when longitudinally managing cost and outcomes of musculoskeletal conditions and procedures. In essence, TDABC helps to bridge our ability to measure and understand the costs associated with the provision of musculoskeletal care, which is a critical step in improving value.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,009
score de la tête « metaresearch » (Gemma)0,041
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,012
Score d'incertitude au seuil0,046

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0090,041
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0060,009
Études des sciences et des technologies0,0010,002
Communication savante0,0050,005
Science ouverte0,0030,003
Intégrité de la recherche0,0020,003
Charge utile insuffisante (le modèle a refusé de juger)0,0060,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,516
Tête enseignante GPT0,555
Écart entre enseignants0,039 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations12
Publié2018
Routes d'admission1
Résumé présentoui

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